Glocalized Solutions for Sustainability in Manufacturing

Glocalized Solutions for Sustainability in Manufacturing

Jürgen Hesselbach • Christoph Herrmann Editors

Glocalized Solutions for Sustainability in Manufacturing Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011

Editors Prof. Dr.-Ing. Dr. h.c. Jürgen Hesselbach Technische Universität Braunschweig Institut für Werkzeugmaschinen und Fertigungstechnik (IWF) Langer Kamp 19B 38106 Braunschweig Germany

PD Dr.-Ing. Christoph Herrmann Technische Universität Braunschweig Institut für Werkzeugmaschinen und Fertigungstechnik (IWF) Langer Kamp 19B 38106 Braunschweig Germany

ISBN 978-3-642-19691-1 e-ISBN 978-3-642-19692-8 DOI 10.1007/978-3-642-19692-8 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2011924877 © Springer-Verlag Berlin Heidelberg 2011 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Cover design: eStudio Calamar S.L. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)

Preface „[Sein] Kampf um Klarheit und Übersicht hat ungemein dazu beigetragen, die Probleme, Methoden und Resultate der Wissenschaft in vielen Köpfen lebendig werden zu lassen.“1 1

“[His] struggle for clarity and a comprehensive view has contributed immensely to bring the problems, methods and results of science into life.” Albert Einstein on the 70th birthday of Arnold Berliner. Die Naturwissenschaften (The Science of Nature),Vol.20/51, Springer, Berlin (1932).

Globalization, rapid developments in information technology, fast process- and product innovations, changing market requirements (e.g. environmental policies, increasing energy- and raw material costs) as well as global challenges, as the growing world population and the intensive use of limited resources, determine the surrounding conditions of producing companies in the 21st century. The comprehension for the resulting complex structures of social, political, economic, technical, ecological and organizational coherences increases with growing insights gained from natural sciences and technology. “Sustainable development” describes a way of how the needs of today’s generations can be satisfied without interfering with the possibilities of future generations. In order to follow this path, “ecological” change processes have to take place in society and economy. “Sustainable economies” require innovative products and processes and a life-cycle-oriented way of thinking and acting or rather a way of thinking and acting in terms of systems, i.e. in value chains and -networks embedded in the natural environment. Only by this means the shifting of problems can be avoided and integrated solutions can be created. This way of thinking and acting does not end with the customer, but proceeds up to the disposal of products and handling of materials and products and/or product parts in life cycles. Decisions on the planning and design of products and processes also have to be made in an integrated manner. This means that technical, economic and ecological aspects have to be integrated into one approach. This should be accomplished under a ”cradle-to-cradle” view – from the raw materials extraction up to end-of-life. This view should take into account not only the manufactured products but also the equipment and auxiliary materials which are necessary for production (e.g. machine tools, cooling lubricants). For this year’s conference we chose the theme “Glocalized Solutions for Sustainability in Manufacturing”. The term “glocalization” is a combination of the words “globalization” and “localization”. It was invented to describe a product or service design developed and distributed globally and also adapted specifically to each locality or culture it is marketed in. However, “Glocalized Solutions for Sustainability in Manufacturing“ do not only involve products or services that are changed for a local market by simple substitution or the omitting of functions. We want to address products and services that ensure a high standard of living everywhere. Resources required for manufacturing and use of such products are limited and not evenly distributed in the world. Locally available resources, local capabilities as well as local constraints have to be drivers for product- and process innovations. Thus, “Best of Local” is a starting point for glocalized solutions. This means for example that the availability of fuels based on biomass is a starting point for engine development in Brazil, whereas solar energy is going to be the most important energy source for future electric vehicles in countries of the earth’s sun belt (up to 35 degrees north and south of the equator). While water-based cooling lubricants are developed in Germany, technical animal fats and used edible fats are the basis for the production of cooling lubricants in Spain. Dandelion is used for the production of rubber; thus, car tires develop from renewable resources. The crushed hard shells of fruit stones (e.g. cherry stones) serve as filling material for polymers or are used as technical abrasives for the cleaning of surfaces. Locally accumulating waste streams are locally processed into new products. Thus, old PET bottles are not only recycled into world cup soccer shirts, but also into laptop bags. However, the use of resources is always linked to the environmental impact over all stages of a product life cycle from material extraction, transport and manufacturing to usage and to the end-of-life. Even if a local scope for design is always linked to global impacts, it has the potential to reduce the impact to an ecologically compatible minimum. Future glocalized engineering solutions will have the potential to address global challenges by providing products, services and processes that take into account local capabilities and constraints to achieve an economically, socially and environmentally sustainable society in a global perspective. The CIRP International Conference on Life Cycle Engineering is a platform for this wide and complex field. It will require the efforts of all of us to bring the problems, methods and results of Life Cycle Engineering into life.

Jürgen Hesselbach

Christoph Herrmann

Table of Contents

Preface .....................................................................................................................................................................................................

v

a

Organization ............................................................................................................................................................................................ a

xiii

Keynotes Electricity Metering and Monitoring in Manufacturing Systems ........................................................................................................ S. Kara, G. Bogdanski, W. Li

1

Implementing life Cycle Engineering efficiently into Automotive Endustry Processes ................................................................... S. Krinke

11

Leveraging Manufacturing for a Sustainable Future ........................................................................................................................... D. Dornfeld

17

Sustainability Engineering by Product-Service Systems .................................................................................................................... G. Seliger

22

Solvis Zero-Emission Factory - The 'Solvis way' - Structure and Subject ......................................................................................... H. Jäger

29

Manufacturing and the Science of Sustainability ................................................................................................................................ T. G. Gutowski

32

Indian Solar Thermal Technology – Technology to Protect Environment and Ecology .................................................................. D. Gadhia

40

a

Automotive Life Cycle Engineering Assessment of Energy and Resource Consumption of Processes and Process Chains within the Automotive Sector ............. R. Schlosser, F. Klocke, B. Döbbeler, B. Riemer, K. Hameyer, T. Herold, W. Zimmermann, O. Nuding, B. A. Schindler, M. Niemczyk

45

Assessment of Alternative Propulsion Systems for Vehicles ............................................................................................................ C. Herrmann, K. S. Sangwan, M. Mennenga, P. Halubek, P. Egede

51

Concept and Development of Intelligent Production Control to enable Versatile Production in the Automotive Factories of the Future ................................................................................................................................................................................................. S. U. H. Minhas, C. Lehmann, U. Berger

57

Resource Efficiency – what are the Objectives? .................................................................................................................................. M. Gernuks

63

Comparative Life Cycle Assessment of Remanufacturing and New Manufacturing of a Manual Transmission .......................... J. Warsen, M. Laumer, W. Momberg

67

a

Automotive Life Cycle Engineering - Recycling Coordination of Design-for-Recycling Activities in Decentralized Product Design Processes in the Automotive Industry ....... K. Schmidt, T. Volling, T. S. Spengler

73

A Strategic Framework for the Design of Recycling Networks for Lithium-Ion Batteries from Electric Vehicles ......................... C. Hoyer, K. Kieckhäfer, T. S. Spengler

79

Recovery of Active Materials from Spent Lithium-Ion Electrodes and Electrode Production Rejects ........................................... C. Hanisch, W. Haselrieder, A. Kwade

85

New Technologies for Remanufacturing of Automotive Systems Communicating via CAN Bus ................................................... R. Steinhilper, S. Freiberger, M. Albrecht, J. Käufl, E. Binder, C. Brückner

90

LCM applied to Auto Shredder Residue (ASR) ..................................................................................................................................... L. Morselli, A. Santini, F. Passarini, I. Vassura, L. Ciacci

96

viii

Table of Contents

Life Cycle Design - Methods and Tools Eco-Innovation by Integrating Biomimetic with TRIZ Ideality and Evolution Rules ......................................................................... J. L. Chen, Y.-C. Yang

101

Reasoning New Eco-Products by Integrating TRIZ with CBR and Simple LCA Methods ................................................................ C. J. Yang , J. L. Chen

107

Proposal of an Integrated Eco-Design Framework of Products and Processes ............................................................................... S. Kondoh, N. Mishima

113

Development of CAD System for Life Cycle Scenario-Based Product Design ................................................................................. E. Kunii, S. Fukushige, Y. Umeda

118

Environmental Impact Assessment Model for Wireless Sensor Networks ....................................................................................... J. Bonvoisin, A. Lelah, F. Mathieux, D. Brissaud

124

Considering the Social Dimension in Environmental Design ............................................................................................................. B. Dreux-Gerphagnon, N. Haoues

130

Proposal of an Ecodesign Maturity Model: supporting Companies to improve Environmental Sustainability ............................. D. C. A. Pigosso, H. Rozenfeld

136

Environmental and Operational Analysis of Ecodesign Methods Based on QFD and FMEA ......................................................... F. N. Puglieri, A. R. Ometto

142

Synergico: a new “Design for Energy Efficiency” Method enhancing the Design of more environmentally friendly Electr(on)ic Equipments ......................................................................................................................................................................... L. Domingo, D. Evrard, F. Mathieux, G. Moenne-Loccoz

148

Improving Product Design based on Energy Considerations ............................................................................................................ Y. Seow, S. Rahimifard

154

Eco-Design Tool to support the Use of Renewable Polymers within Packaging Applications ....................................................... J. Colwill, S. Rahimifard, A. Clegg

160

A

Life Cycle Design - Selected Applications State-of-the-art Ecodesign on the Electronics Shop Shelves? A Quantitative Analysis of Developments in Ecodesign of TV Sets ........................................................................................................................................................................................................... C. Boks, R. Wever, A. Stevels

167

Simultaneous Application of Design for Sustainable Behavior and Linked Benefit Strategies in Practice .................................. J. Schmalz, C. Boks

173

Strategic Evaluation of Manufacturing Technologies ......................................................................................................................... G. Reinhart, S. Schindler, P. Krebs

179

Consideration of the Precautionary Principle – the Responsible Development of Nano Technologies ........................................ M. Weil

185

Proposal of a Design Support Method for Sustainability Scenarios 1st Report: Designing Forecasting Scenarios ................... H. Wada, Y. Kishita, Y. Mizuno, M. Hirosaki, S. Fukushige, Y. Umeda

189

a

Sustainability in Manufacturing Evaluating Trade-Offs Between Sustainability, Performance, and Cost of Green Machining Technologies ................................. M. Helu, J. Rühl, D. Dornfeld, P. Werner, G. Lanza

195

Sustainable Production by Integrating Business Models of Manufacturing and Recycling Industries ......................................... C. Jonsson, J. Felix , A. Sundelin , B. Johansson

201

Life Cycle Engineering – Integration of New Products on Existing Production Systems in Automotive Industry ....................... W. Walla, J. Kiefer

207

Managing Sustainability in Product Design and Manufacturing ........................................................................................................ K. Ioannou, A. Veshagh

213

A System for Resource Efficient Process Planning for Wire EDM ..................................................................................................... S. Dhanik, P. Xirouchakis, R. Perez

219

Increased Trustability of Reliability Prognoses for Machine Tools ................................................................................................... G. Lanza, P. Werner, D. Appel, B. Behmann

225

Table of Contents

ix

Hidden Aspects of Industrial Packaging - The Driving Forces behind Packaging Selection Processes at Industrial Packaging Suppliers .................................................................................................................................................................................................. S. S. Casell

229

Applying Functionally Graded Materials by Laser Cladding: a cost-effective way to improve the Lifetime of Die-Casting Dies ........................................................................................................................................................................................................... S. Müller, H. Pries, K. Dilger, S. Ocylok, A. Weisheit, I. Kelbassa

235

A Total Life-Cycle Approach towards Developing Product Metrics for Sustainable Manufacturing .............................................. A. Gupta, A. D. Jayal, M. Chimienti, I. S. Jawahir

240

Carbon Footprint Analysis for Energy Improvement in Flour Milling Production ........................................................................... C. W. P. Shi, F. Rugrungruang, Z. Yeo, B. Song

246

a

Sustainability in Manufacturing - Energy Efficiency in Machine Tools Modelling Machine Tools for Self-Optimisation of Energy Consumption ......................................................................................... R. Schmitt, J. L. Bittencourt, R. Bonefeld

253

Energy-Efficient Machine Tools through Simulation in the Design Process .................................................................................... C. Eisele, S. Schrems, E. Abele

258

Energy Consumption Characterization and Reduction Strategies for Milling Machine Tool Use ................................................... N. Diaz, E. Redelsheimer, D. Dornfeld

263

An Investigation into Fixed Energy Consumption of Machine Tools ................................................................................................. W. Li, A. Zein, S. Kara, C. Herrmann

268

Energy Efficiency Measures for the Design and Operation of Machine Tools: An Axiomatic Approach ...................................... A. Zein, W. Li, C. Herrmann, S. Kara

274

Analyzing Energy Consumption of Machine Tool Spindle Units and Identification of Potential for Improvements of Efficiency ................................................................................................................................................................................................. E. Abele, T. Sielaff, A. Schiffler, S. Rothenbücher

280

a

Sustainability in Manufacturing - Energy Efficiency in Process Chains Energy Consumption as One Possible Exclusion Criterion for the Reuse of Old Equipment in New Production Lines ............. L. Weyand, H. Bley, M. Swat, K. Trapp, D. Bähre

287

Optimizing Energy Costs by Intelligent Production Scheduling ........................................................................................................ A. Pechmann, I. Schöler

293

Methodology for an Energy and Resource Efficient Process Chain Design ..................................................................................... S. Schrems, C. Eisele, E. Abele

299

A New Shop Scheduling Approach in Support of Sustainable Manufacturing ................................................................................. K. Fang, N. Uhan, F. Zhao, J. W. Sutherland

305

Comparison of the Resource Efficiency of Alternative Process Chains for Surface Hardening .................................................... G. Reinhart, S. Reinhardt, T. Föckerer, M. F. Zäh

311

Synergies from Process and Energy Oriented Process Chain Simulation – A Case Study from the Aluminium Die Casting Industry .................................................................................................................................................................................................... C. Herrmann, T. Heinemann, S. Thiede

317

a

Sustainability in Manufacturing - Methods and Tools for Energy Efficiency Context-Aware Analysis Approach to Enhance Industrial Smart Metering ....................................................................................... C. Herrmann, S.-H. Suh, G. Bogdanski, A. Zein, J.-M. Cha, J. Um, S. Jeong, A. Guzman

323

Exergy Efficiency Definitions for Manufacturing Processes .............................................................................................................. Renaldi, K. Kellens, W. Dewulf, J. R. Duflou

329

State of Research and an innovative Approach for simulating Energy Flows of Manufacturing Systems .................................... S. Thiede, C. Herrmann, S. Kara

335

Modular Modeling of Energy Consumption for Monitoring and Control ........................................................................................... A. Verl, E. Abele, U. Heisel, A. Dietmair, P. Eberspächer, R. Rahäuser, S. Schrems, S. Braun

341

Architecture for Multilevel Monitoring and Control of Energy Consumption .................................................................................. A. Verl, E. Westkämper, E. Abele, A. Dietmair, J. Schlechtendahl, J. Friedrich, H. Haag, S. Schrems

347

x

Table of Contents

Sustainability in Manufacturing - Selected Applications Green Performance Map – An Industrial Tool for Enhancing Environmental Improvements within a Production System ......... K. Romvall, M. Kurdve, M. Bellgran, J. Wictorsson

353

Analysis and Quantification of Improvement in Green Manufacturing Process of Silicon Nitride Products ................................ N. Mishima, S. Kondoh, H. Hyuga, Y. Zhou, K. Hirao

359

Evaluation of the Environmental Impact of different Lubrorefrigeration Conditions in Milling of γ-TiAl Alloy ............................. G. Rotella, P. C. Priarone, S. Rizzuti, L. Settineri

365

Quantitative and Qualitative Benefits of Green Manufacturing: an Empirical Study of Indian Small and Medium Enterprises .. K. S. Sangwan

371

Preliminary Environmental Assessment of Electrical Discharge Machining .................................................................................... K. Kellens, Renaldi, W. Dewulf, J. R. Duflou

377

Development of an Interpretive Structural Model of Obstacles to Environmentally Conscious Technology adoption in Indian Industry .................................................................................................................................................................................................... V. K. Mittal, K. S. Sangwan

383

Identifying Carbon Footprint Reduction Opportunities through Energy Measurements in Sheet Metal Part Manufacturing ...... C. W. P. Shi, F. Rugrungruang, Z. Yeo, K. H. K. Gwee, R. Ng, B. Song

389

Sustainable Production Research - a Proposed Method to design the Sustainability Measures ................................................... M. K. Wedel, B. Johansson, A. Dagman, J. Stahre

395

Green Production of CFRP Parts by Application of Inductive Heating .............................................................................................. M. Frauenhofer, S. Kreling, H. Kunz, K. Dilger

401

Saving Potential of Water for Foundry Sand Using Treated Coolant Water ...................................................................................... J. O. Gomes, V. E. O. Gomes, J. F. de Souza, E. Y. Kawachi

407

a

End of Life Management - Reuse and Remanufacturing Modular Grouping Exploration to design Remanufacturable Products ............................................................................................ N. Tchertchian, D. Millet, O. Pialot

413

Development of Part Agents for the Promotion of Reuse of Parts through Experiment and Simulation ...................................... H. Hiraoka, K. Ito, K. Nishida, K. Horii, Y. Shigeji

419

Systematic Categorization of Reuse and Identification of Issues in Reuse Management in the Closed Loop Manufacturing ... T. Sakai, S. Takata

425

Approach for Integration of Sustainability Aspects into Innovation Processes ............................................................................... S. Severengiz, P. Gausemeier, G. Seliger, F. A. Pereira

431

Remanufacturing Engineering Literature Overview and Future Research Needs ............................................................................ Q. Ke, H.-C. Zhang, G. Liu, B. Li

437

a

End of Life Management - Selected Applications Effects of Lateral Transshipments in Multi-Echelon Closed-Loop Supply Chains ........................................................................... K. Tracht, M. Mederer, D. Schneider

443

Development of an Interpretive Structural Model of Barriers to Reverse Logistics Implementation in Indian Industry .............. A. Jindal, K. S. Sangwan

448

Recycling of LCD Screens in Europe - State of the Art and Challenges ........................................................................................... S. Salhofer, M. Spitzbart, K. Maurer

454

End of Life Strategies in the Aviation Industry .................................................................................................................................... J. Feldhusen, J. Pollmanns, J. E. Heller

459

Contribution of Recycling Processes to Sustainable Resource Management ................................................................................. A. Pehlken, K.-D. Thoben

465

Business Issues in Remanufacturing: Two Brazilian Cases in the Automotive Industry ................................................................ O. T. Oiko, A. P. B. Barquet, A. R. Ometto

470

A Systematic Investigation for Reducing Shredder Residue for Complex Automotive Seat Subassemblies ............................... S. Barakat, J. Urbanic

476

Eco Quality Polymers-EQP ..................................................................................................................................................................... C. Luttropp, E. Strömberg

482

Table of Contents

xi

Intelligent Products to Support Closed-Loop Reverse Logistics ....................................................................................................... K. A. Hribernik, M. von Stietencron, C. Hans, K.-D. Thoben

486

The Prospects of Managing WEEE in Indonesia .................................................................................................................................. J. Hanafi, H. J. Kristina, E. Jobiliong, A. Christiani, A. V. Halim, D. Santoso, E. Melini

492

Medical Electrical Equipment - Good Refurbishment Practice at Siemens AG Healthcare ............................................................. M. Plumeyer, M. Braun

497

a

Information and Knowledge Management Sustainable Product Lifecycle Management: A Lifecycle based Conception of Monitoring a Sustainable Product Development ............................................................................................................................................................................................ M. Eigner, M. von Hauff, P. D. Schäfer

501

Semantic Web Based Dynamic Energy Analysis and Forecasts in Manufacturing Engineering .................................................... K. Wenzel, J. Riegel, A. Schlegel, M. Putz

507

Energy Data Acquisition and Utilization for Energy-Oriented Product Data Management .............................................................. T. Reichel, G. Rünger, D. Steger, U. Frieß, M. Wabner

513

Integrating Energy-Saving Process Chains and Product Data Models ............................................................................................. G. Rünger, A. Schubert, S. Goller, B. Krellner, D. Steger

519

Challenges in Data Management in Product Life Cycle Engineering ................................................................................................. T. Fasoli, S. Terzi, E. Jantunen, J. Kortelainen, J Sääski, T. Salonen

525

Business Game for Total Life Cycle Management ............................................................................................................................... S. Böhme, T. Heinemann, C. Herrmann, M. Mennenga, R. Nohr, J. Othmer

531

Requirements Management – a Premise for adequate Life Cycle Design ......................................................................................... S. Klute, C. Kolbe, R. Refflinghaus

537

Towards a Methodology for Analyzing Sustainability Standards using the Zachman Framework ................................................ S. Rachuri, P. Sarkar, A. Narayanan, J. H. Lee, P. Witherell

543

Sustainability through Next Generation PLM in Telecommunications Industry ............................................................................... J. Golovatchev, O. Budde

549

Challenges of an Efficient Data Management for Sustainable Product Design ................................................................................ T. Leitner, M. Stachura, A. Schiffleitner, N. Stein

554

Product and Policy Life Cycle Inventories with Market Driven Demand: An Engine Selection Case Study .................................. H. Grimes-Casey, C. Girata, K. Whitefoot, G. A. Keloeian, J. J. Winebrake, S. J. Skerlos

558

A Case-Study: Finding References to Product Development Knowledge from Analysis of Face-to-Face Meetings ................... B. Piorkowski, J. Gao, R. Evans

564

a

Life Cycle Assessment - Methods and Tools CAD-Integrated LCA Tool: Comparison with dedicated LCA Software and Guidelines for the Improvement ............................... A. Morbidoni, C. Favi, M. Germani

569

Comparison of two LCA Methodologies in the Machine-Tools Environmental Performance Improvement Process ................... M. Azevedo, M. Oliveira, J. P. Pereira, A. Reis

575

Developing Impact Assessment Methods: an Approach for addressing inherent Problems .......................................................... M. Toxopeus, V. Kickert, E. Lutters

581

Developing a Conceptual Framework for UT based LCA .................................................................................................................... J.-M. Cha, S.-H. Suh

587

Towards the Integration of Local and Global Environmental Assessment Methods: Application to Computer System Power Management ............................................................................................................................................................................................ V. Moreau, N. Gondran, V. Laforest Cradle to Cradle and LCA – is there a Conflict? .................................................................................................................................. A. Bjørn, M. Z. Hauschild

593 599

xii

Table of Contents

Life Cycle Assessment - Selected Applications Environmental Assessment of Printed Circuit Boards from Biobased Materials ............................................................................. Y. Deng, K. Van Acker, W. Dewulf, J. R. Duflou Application of Life Cycle Engineering for the Comparison of Biodegradable Polymers Injection Moulding Performance ............................................................................................................................................................................................ D. Almeida, P. Peças, I. Ribeiro, P. Teixeira, E. Henriques

605

611

Using Ecological Assessment during the Conceptual Design Phase of Chemical Processes – a Case Study ............................ L. Grundemann, J. C. Kuschnerow, T. Brinkmann, S. Scholl

617

Environmental Footprint of Single-Use Surgical Instruments in Comparison with Multi-Use Surgical Instruments .................. J. Schulz, J. Pschorn, S. Kara, C. Herrmann, S. Ibbotson, T. Dettmer, T. Luger

623

Comparative Carbon Footprint Assessment of Door made from Recycled Wood Waste versus Virgin Hardwood: Case Study of a Singapore Wood Waste Recycling Plant ....................................................................................................................................... R. Ng, C. W. P. Shi, J. S. C. Low, H. M. Lee, B. Song

629

a

Life Cycle Costing A Target Costing-Based Approach for Design to Energy Efficiency ................................................................................................. A. Bierer, U. Götze

635

Life Cycle Costing Assessment with both Internal and External Costs Estimation ......................................................................... S. Martinez, M. Hassanzadeh, Y. Bouzidi, N. Antheaume

641

Environmental and Economic Evaluation of Solar Thermal Panels using Exergy and Dimensional Analysis ............................. G. Medyna, E. Coatanea, D. Millet

647

Implications of Material Flow Cost Accounting for Life Cycle Engineering ...................................................................................... T. Viere, M. Prox, A. Möller, M. Schmidt

652

a

Life Cycle Costing - Modelling Aircraft Engine Component Deterioration and Life Cycle Cost Estimation ...................................................................................... Y. Zhao, A. Harrison, R. Roy, J. Mehnen

657

Life Cycle Cost Estimation using a Modeling Tool for the Design of Control Systems ................................................................... H. Komoto, T. Tomiyama

663

Assessing the Value of Sub-System Technologies including Life Cycle Alternatives .................................................................... A. Bertoni, O. Isaksson, M. Bertoni, T. Larsson

669

Costing for Avionic Through-Life Availability ...................................................................................................................................... L. Newnes, A. Mileham, G. Rees, P. Green

675

Eco Global Evaluation: Cross Benefits of Economic and Ecological Evaluation ............................................................................. N. Perry, A. Bernard, M. Bosch-Mauchand, J. LeDuigou, Y. Xu

681

A Index of Authors ......................................................................................................................................................................................

687

Organization

CHAIRMEN Prof. J. Hesselbach PD Dr.-Ing. Christoph Herrmann ORGANIZING COMMITTEE Chief Organizers Dipl.-Wirtsch.-Ing. Mark Mennenga Dipl.-Wirtsch.-Ing. Tim Heinemann Organizing Committee Hannah Jule Schäfer, M.A.

Dipl.-Wirtsch.-Ing. Katrin Kuntzky

Dipl.-Ing. (FH) Stefan Andrew

Dr.-Ing. Tobias Luger

Dr.-Ing. Ralf Bock

Dipl.-Chem. Gerlind Öhlschläger

Dipl.-Ing. Gerrit Bogdanski

Anne-Marie Schlake, M.A.

Dr.-Ing. Tina Dettmer

Dipl.-Wirtsch.-Ing. Tim Spiering

Dipl.-Wirtsch.-Ing. Patricia Egede

Dipl.-Wirtsch.-Ing. Julian Stehr

Dipl.-Wirtsch.-Ing. Philipp Halubek

Dipl.-Wirtsch.-Ing. Sebastian Thiede

Dipl.-Ing. Mohamad Jamal Kayasa

Dipl.-Wirtsch.-Ing. Marius Winter

Dipl.-Ing. Michael Krause

Dipl.-Wirtsch.-Ing. André Zein

INTERNATIONAL SCIENTIFIC COMMITTEE Prof. L. Alting / DK

Prof. N. Nasr / US

Porf. C. Boks / NO

Prof. A. Nee / SG

Prof. B. Bras / US

Prof. R. Neugebauer / DE

Prof. D. Brissaud / FR

Prof. A. Ometto / BR

Prof. J. L. Chen / TW

Prof. S. Salhofer / AT

Prof. W. Dewulf / BE

Prof. K. S. Sangwan / IN

Prof. D. Dornfeld / US

Prof. G. Seliger / DE

Prof. J. Duflou / BE

Prof. W. Sihn / AT

Prof. T. Gutowski / US

Prof. S. Skerlos / US

Prof. M. Hauschild / DK

Prof. T. Spengler / DE

Prof. H. Kaebernick / AU

Prof. S. H. Suh / KR

Prof. S. Kara / AU

Prof. J. Sutherland / US

Prof. F. Kimura / JP

Prof. S. Takata / JP

Prof. W. Knight / US

Prof. S. Tichkiewitch / FR

Prof. T. Lien / NO

Prof. T. Tomiyama / NL

Dr. C. Luttropp / SW

Prof. Y. Umeda / JP

Prof. H. Meier / DE

Prof. E. Westkämper / DE

Prof. L. Morselli / I

Prof. H. Zhang / US

Electricity Metering and Monitoring in Manufacturing Systems S. Kara

1, 2

, G. Bogdanski

1, 3

, W. Li

1, 2

1

Joint German-Australian Research Group in Sustainable Manufacturing and Life Cycle Management

2

Life Cycle Engineering & Management Research Group, School of Mechanical & Manufacturing Engineering, The University of New South Wales, Australia

3

Institute of Machine Tools and Production Technology (IWF), Product- and Life-Cycle-Management Research Group, Technische Universität Braunschweig, Germany

Abstract Traditionally, electricity costs in manufacturing have been considered as an overhead cost. In the last decade, the manufacturing industry has witnessed a dramatic increase in electricity costs, which can no longer be treated as an overhead, but a valuable resource to be managed strategically. However, this can only be achieved by strategically gathering electricity consumption data by metering and monitoring. This keynote paper presents the latest developments and challenges in electricity metering and monitoring systems and standards in the context of manufacturing systems. An industry case is presented to emphasise the challenges and the possible solutions to address them. Keywords: Manufacturing Systems; Energy Efficiency; Metering and Monitoring

1

INTRODUCTION

Global warming and its disastrous environmental and economic effects are considered as one of the major challenges that today’s and future generations have to face during the 21 century. One of the main attribute of this challenge is due to the environmental impact e.g. Green House Gas (GWP) emission, caused during the generation of electricity from fossil fuels [1]. Therefore, one of the possible ways to reduce GWP emission is to reduce the electricity consumption, which is also enforced by national and international initiatives, e.g. Kyoto agreement. In addition, industry has a high interest in reducing the energy consumption, because energy has become a major cost driver, especially for high technology industries with their energy intensive manufacturing processes. Energy cost has long been treated as a necessary overhead cost for creating value-added products. However, more and more industrial companies are consciously shifting towards treating energy as a valuable resource, which needs to be planned and managed as a variable input for their plant. A necessary prerequisite for such energy-conscious behaviour is to be able to systematically measure energy consumption in a manufacturing plant. One of the challenges plant managers facing today is to gain transparency inside complex energy distribution networks of their manufacturing plants. A fundamental prerequisite for achieving this transparency is primarily to meter the consumed energy and its related characteristics in time. In order to gain full awareness, the metered physical values need to be monitored, interpreted and visualized in plant management systems. Electrical energy is in high favour of industry because it can easily be converted into many lower energy forms such as heat, light, compressed air, mechanical torque and many others. Consumption of electrical energy, in comparison to other energy forms, can be measured easily and precisely. Therefore, other energy forms are usually converted by sensors and transducers into electrical signals which themselves can be picked up by standard procedures of electrical signal metering techniques. In this paper the evolution and the latest development in electricity

metering and monitoring technologies are first introduced. A rapid development in measurement instruments requires up-to-date standards in order to compare and select appropriate device. After giving an overview about the most relevant international and national standards, the potentials of electricity metering and monitoring in manufacturing plants are illustrated and technical requirements for metering and monitoring systems are presented. The most important aspects that need to be considered when designing metering strategies are highlighted with a case study from an Australian manufacturing company. 2

EVOLUTION OF MONITORING

ELECTRICITY

MEASUREMENT

AND

Since the introduction of electricity distribution grids, there has been a demand for devices to measure the energy consumption in order to assist suppliers for distributing, pricing and monitoring their service. As early as during the 1880s, companies were authorized to sell electricity. One of the first patents for an electricity meter had been taken out by Pulvermacher in 1868 for an electrolytic meter [2]. Besides the electrolytic meters, there were other early inventions for measuring electricity, for instance thermal meters, clock meters and motor meters. In 1884 the Aron Meter Co. started selling the first meters of the true dynamometer type electricity meter patented by Hermann Aron. They were considered to have the highest degree of accuracy of the available meters at that time. As one form of the motor meters, the induction meter (Ferraris disc meter), had emerged to meet the needs of the emerging multiphase generation and transmission of electric power for high precision Alternating Current (AC) meters. The induction meter is still in general use today but is reaching its limits of accuracy and lacking ability to communicate its metering values. Recent developments try to meet the demands of the evolving smart grid technology calling for multi-value measurement and bi-directional communication ability [3]. The advances in semiconductor technology have led to the technological overrun of bulky electromechanical meters by smaller dimensioned, solely electronic metering devices by the early 1990s. By removing all complex

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_1, © Springer-Verlag Berlin Heidelberg 2011

1

2

Keynotes

analogue/digital converter circuitry for the basic measurements such as current and voltage



multiplier for the instantaneous measurement values



time to frequency converters for voltage and current [6].

The overall structure of measuring elements of electronic meters is basically the same. However, the applied measurement techniques are, in contrast to electromechanical metering systems, very different. The multiplication of voltage and current for example can be done by a hall multiplier, a time division multiplier or digital multiplier [5-6]. Providing at least the same functionality as hybrid meters the electronic meters aim at offering extended information to the user. This is done through digital signal processing by means of microprocessors or customized integrated circuits. The digital circuitry can perform time accurate calculation of active, reactive, apparent energy and power factor as well as frequency and harmonic distortion metering with many mathematical functionalities such as averaging, min/max detection, integration and accumulation [4, 6]. All performed metering is provided to serve for billing and controlling of the supplied and used electrical energy. The application of different measurement principles and individually designed integrated circuitry in metering devices calls for national and international standards to allow users to verify their metered value in accordance to approved limitations. As an example for international standards, the IEC 62053 and the ANSI C12.20 mandates the accuracy of static watt-hour meters and have defined four different classes: class 2, class 1, class 0.5 and class 0.2 (e.g. class 0.5 requires a repeatable meter precision of 0.5% of nominal current and voltage) [7-8]. The revised German VDE 0410 had even clustered these classes into utility measurement ranging from class 1 to class 5 and into precision measurement ranging from class 0.1 to class 0.5 for directly indicating metering devices with a scale. The VDE 0410 has been overworked in the IEC 60051, within a much more comprehensive international standard for direct acting analogue electrical measuring instruments [9-10]. The electrical meters measurement chain is subject to an error of the measurement chain, expressed in the accuracy G, indicated by the class and enabling the user to calculate the limitations of maximum and minimum deviation ∆x inside a given metering measurement range xmax-min of the instrument

∆x = G xmax-min / 100%.

(1)

Current digital electricity meters available on the market already claim to some extent, to meet the accuracy limitation of 0.1% or

PURPOSE OF ELECTRICITY MONITORING IN INDUSTRY

MEASUREMENT

AND

Electricity metering and monitoring in industrial applications address a wide range of applications, which can be divided into three broad levels of application: 

Factory Level



Department Level



Unit Process Level.

In general, from the customer perspective, metering and monitoring of electricity in industry applications is done to gain transparency into electricity billing, internal electricity distribution and energy controlling. Each of the three stated levels above contains its own set of technical requirements concerning the metering equipment and the attached monitoring system. They also have their own associated potential benefits and degree of transparency requirement from the application of electricity metering and monitoring. Figure 1 shows a factory from an electricity consumer perspective with all its organisational sub-consumers within the three levels. Transparency gains through electricity metering and monitoring

Organizational level structure

• energy billing • energy contract •…

Factory

• energy accounting • identify hot-spots • transparency of energy flow within the factory • …

• energy modelling • process simulation • machine efficiency redesign • ...

Factory



3

Department 1

Machine 1

…

Department n

SubDepartment 1.1

...

SubDepartment n.1

SubDepartment 1.m

…

SubDepartment n.m

…

Machine i

Periphery System 1

…

Department

For simple kilowatt-hour metering the electromechanical meters such as Ferraris disc meters, are still considered to be the most economical solution because of its extremely long life and durability [5-6]. The metering industry has been trying to lengthen the technology life of the predominant electromechanical technology by using hybrid solutions, e.g. adding electronics to the present devices, to fulfil additional functions like maximum demand calculations as demanded by today’s suppliers to price industry and medium to large sized commercial electricity customers [6]. With the help of add-on electronics, hybrid meters can provide their users various other functions such as multi-rate registers, seasonal registers, historical value registers, maximum demand, and consumptions threshold definition. The inevitable next step in the evolution of electricity meters is the electronic meters. In contrast to electromechanical meters different principles are used to measure the basic values of electricity, from which all other values of interest are usually derived by means of electronic calculation. Basic elements for each power phase are:

lower, causing buyers to be confused because there is no existing international standard of 0.1% accuracy which a manufacturer could claim compliance to [11]. Therefore, standards need to keep up the pace of technological innovation in order to ensure that metering equipment buyers are able to compare and benchmark claimed accuracy by providing manufacturers a specified set of tests over the whole range of operation conditions of load current, power factor, temperature and harmonic distortion.

Unit Process

moving mechanical parts, the electronic meters are able to house multi-sensors within highly integrated circuits [4].

Periphery System j

Figure 1: Three levels of a factory as a consumer of electricity. The most important fact that needs to be stated is that the organisational structure rarely complies with the technical electricity distribution network, which brings additional challenges during department level electricity metering and monitoring which will be discussed later. What all three levels have in common in relation to metering electricity is the basic measurement values that all other specific information can be mathematically driven from: voltage and current with respect to time. For instance, in a general 3 phase system, the total active power PW tot can be calculated as:

PW tot = PW1 + PW2 + PW3

(2)

= U1N eff I1 eff cos φ1 + U2N eff I2 eff cos φ2 + U3N eff I3 eff cos φ3.

(3)

Keynotes

3

Where φn is the phase angle between the current In and the voltage Un of the n-th phase. In 2-phase-systems it is theoretically possible to meter only two lines because one line can be seen as the neutral. Nevertheless, it is often seen that 3-phase-systems are also equipped with three separate power meters to monitor three phases and to ensure a higher accuracy of the metering result, especially at low powers and high phase angles [12]. The accuracy of a measurement is therefore always directly related to the accuracy of the current and voltage measurement error and needs to be calculated accordingly. (a)

I1

(b)

K

L

k

l

U

V

u

v

I2

Figure 2: Current (a) and voltage (b) transformer circuits [12]. Usually a galvanic isolation, as depicted in Figure 2, is used in the current and voltage meters to prevent them from accidental overload from harming the sensitive metering equipment. The most widespread application to realize a galvanic isolation is a simple current and voltage transformer which is going into saturation if an overload is applied on the primary windings. The secondary windings are short circuited by the current meter. The transformation rate is generally dimensioned to conduct 1 or 5 A (current meter) and 100 V (voltage meter) on the secondary windings. The transformers are also regarded as part of the measuring chain and are also adding their own error in terms of accuracy limitation to the total measurement system. The IEC 60044-1 is dealing with the technical requirements of current transformers for instruments as well as their indicated accuracy classes [13]. Assuming a normal distribution of the measurement errors of the components, the total measurement systems accuracy Gtot is calculated as considering the accuracy levels of the transformer Gtrans and of the instrument Ginst:

Gtot = ( Gtrans2 + Ginst2 )1/2.

(4)

The error of a current transformer is actually consisting of a basic error, which can be very low in a good technically designed transformer, and an angular error, which is highly dependent on the applied apparent current burden [12]. The following section will

present a more specific view on the potential gains from metering and monitoring applications on the three organizational levels. Recent publications show, that the industrialized countries are facing a multidimensional pressure from the economical, ecological as well as legislative side to shift their field of actions more towards energy and resource efficient processes and structures within their company, their products and their services to stay competitive in the global market environment. 3.1

Factory Level

The electricity metering and monitoring on factory level is done on the interface between the electricity supplier and the consumer (factory inlet). Electricity is an energy resource that is demanded by the manufacturing industry ever since the light bulb was invented and the establishment of the electricity industry in the late nineteenth century. With the rising demand, quality and the continuity of the supply have become a serious concern [14]. As a result, today’s electricity grid and the supply of electric voltage are standardized within different regulations. For instance in Europe, the EN 50160 written by the European Electrotechnical Standards Body CENELEC is used [15]. The EN 50160 address the electric voltage as a good and the quality has to be ensured in the provision to the customer. Otherwise the customer would be able to claim a better product quality from the supplier. Electricity is a very unique product, being produced, delivered and used at the same instant of time [14]. Due to a high level of dependence on electric voltage supply, the industry and the public have to be sure that they can operate their electrical equipment without incurring additional capital expenditures due to a lack of quality in the electricity supply from the low (LV) and the medium voltage (MV) grids. The voltage quality can be imagined as the usability of electrical energy without interruptions. The subject of voltage quality is becoming more and more important in highly developed countries, because of the increased use of applications, which are very sensitive to disturbances of the voltage amplitude or of the voltage wave shape [16]. In order to check the quality of the electrical voltage supplied to the customer according to the given characteristics of the EN 50160, metering equipment suitable for that task needs to be deployed. Table 1 lists an extract of specifications from EN 50160 that brings in another important aspect of modern digital electricity meters – the resolution in time [4]. A high resolution of metering data can be ensured by a high sampling rate of the analogue-digital circuitry and a short settling time of any analogue components like the current and the voltage transformers and the amplification circuits.

Acceptable limits

Measurement Monitoring period interval

Grid Frequency

49.5 Hz to 50.5 Hz, 47 Hz to 52 Hz

10 s

1 week

Slow Voltage Changes

230 V ±10%

10 min

1 week

Voltage Sags or Dips (≤ 1 min)

10 to 1000 times per year (under 85% of nominal)

10 ms

1 year

Short Interruptions (≤ 3 min)

10 to 100 times per year (under 1% of nominal)

10 ms

1 year

Accidental, long interruptions (> 3 min)

10 to 50 times per year (under 1% of nominal)

10 ms

1 year

Temporary Overvoltages (line to ground)

Mostly < 1.5 kV

10 ms

-

Transient Overvoltages (line to ground)

Mostly < 6 kV

-

-

Voltage Unbalance

Mostly 2%, but occasionally 3%

10 min

1 week

Harmonic Voltages

8% total harmonic distortion (THD)

10 min

1 week

Supply voltage phenomenon

Table 1: Summary of electricity specifications from EN 50160 and related measurement intervals from Shtargot [4].

4

Keynotes

On the factory level, several aspects of the electric energy are essential to be metered in order to gain the certain state of transparency of the factory’s energy consumption from a holistic perspective [17-18]. Table 2 lists a summary of possible cost factors based on the electricity consumption on the factory level and possible potential benefits that can be achieved by gaining a certain level of transparency through metering key values such as listed in Table 1. By using a simple initial monitoring and controlling of consumption the electricity consumer will be able to address the problems on time and not retrospectively after receiving the bill. Electricity metering and monitoring on the factory level enables the consumer to check the quality characteristics of the supplied product and enables him to gain an important amount of transparency for time dependent controlling of energy consumption. Factory level: Cost factors

Total energy consumed, peak power demand, power factor limitation, THD feedback

Potential benefits enabled through electricity metering

Adaption of the electricity supply contract; preventing of peak charges through rescheduling of processes or events

Table 2: Cost factors and potential benefits through electricity metering and monitoring on factory level. 3.2

Department level

The department level structure usually consists of n departments which can show the functional units of the factory. Table 3 shows the major cost factors concerning electricity and related potential benefits through electricity metering and monitoring on department level. Department level: Cost factors

Specific energy consumed, peak power demand, power factor limitation

Potential benefits enabled through electricity metering

Energy intensive process scheduling; ability to deploy and track continuous improvement measures; department based energy saving targeting and benchmarking; simulative improvement of energy costing; effective utilization of secondary energy carriers produced by electricity; quantify energy savings

Table 3:

Cost factors and potential benefits through electricity metering and monitoring on department level.

The contents of Table 3 comply very much with the goals of smart metering and energy accounting, known from private households. The main goal is to try shortening the informational feedback time from the consumption of energy to the moment of billing [19]. For industry the simple monitoring is already a big leap forward to raise the corporate awareness and to motivate each individual to minimize their own share of energy consumption and their related costs. This will also lead to putting some effort into reducing their individual energy consumption without just shifting consumption from one individual consumer to the other. It has been shown that an extended holistic process and system understanding is beneficial in order to increase energy and resource efficiency measures in manufacturing sites. This is due to the fact that many sub-systems are interlinked and have indirect or direct coupled energy consumption, which are not obvious at first

sight and can cause a problem shift if efficiency measures are only applied from a narrow point of view [20]. Several researchers have already stated the basic need for reliable energy consumption data for a successful development towards more energy efficient processes and factories e.g. by use of software tools (energy aware process chain simulation, LCI of manufacturing process chains, evaluation of machine tool configuration) [21-24]. Some even put a special focus on the energy aware upper level planning and control of production, which can be defined as an interface between all three levels of a factory [25-26]. Some researchers have even tried to break down the assessed energy of the whole factory in order to allocate it to one product manufactured at the site, stating that a more efficient monitoring and control of energy used in infrastructure and technical services can help to optimise the plant level activities [27]. When planning and ultimately deploying an electricity metering and monitoring concept in a factory, it quickly becomes obvious that the electrical distribution network structure inside a factory highly varies from a simple organisational structure. This makes setting-up of a consistent metering network with proper upper level monitoring quite challenging. Especially, when the department structures are being monitored with the purpose of energy accounting based on organizational structures, the complexity of the deployed metering strategy increases dramatically. 3.3

Unit process level

Unit process level of electricity metering and monitoring is considered as the lowest hierarchical type of metering point selection. Meters are directly attached to single machines or machine components (e.g. auxiliary pumps, ventilation systems) and peripheral units such as decentralized coolant treatment or decentralized compressed air production systems. On this lowest level the most detail of electrical energy consumption can be obtained [17]. Direct monitoring of single machines may be required for energy optimized production planning around highly energy intensive processes or to conduct a deeper understanding of the energy flow distribution onto sub-components of production machines or to better understand the energetic coupling of in-line production processes [24, 28-30]. Table 4 shows the major cost factors concerning electricity and related potential benefits through electricity metering and monitoring on unit process level. Unit process level: Cost factors

Specific Energy Consumption (SEC), peak power demand, power factor limitation, THD feedback

Potential benefits enabled through electricity metering

Supplementing unit process values to machine LCI databases; energy forecasting in production design, process planning and control; energy labelling of machine tools and products; specific quantification of single efficiency measures; evaluation of technical improvements; condition monitoring as a prophylactic measure in energy and resource sufficiency

Table 4: Cost factors and potential benefits through electricity metering and monitoring on unit process level. Other publications utilized electricity metering and monitoring on unit process level by using energy and time studies to assess the specific environmental and economic impact of particular production processes which can then be used to build Life Cycle Inventory (LCI) databases [31-32].

Keynotes

5

In addition to impact assessment and efficiency improvements as planning tools, electricity metering and monitoring can also be used for condition monitoring and diagnostics of machines and processes. This enables to prevent energy and resource losses ahead of time such as tool changes, planning of maintenance cycles as well as early detection of tool wear. The international standard such as ISO 13374-1, are helping users to implement such established measures [33]. Others have also demonstrated additional benefit by combining electricity metering and monitoring data with machine control data (e.g. from programmable logic controllers) to gain beneficial additional transparency into process specific environmental impact assessment [34-35]. 4

GUIDELINE FOR ELECTRICTY MONITORING IN MANUFACTURING

METERING

AND

Rohdin and Thollander have listed in detail the barriers that especially non-energy intensive manufacturing companies are confronted with, when being faced by a decision to actually go for energy efficiency assessments and measures [36]. The study indicated that responsible staff often fears the interruption of production processes, the lack of insufficient sub-metering in the company structure to quantify and assess implemented efficiency measures and some even face a lack of technical skill to put metering and monitoring into action. Occupational Health and Safety is also critical in use and selection of measurement instruments. The IEC 61010-1 declares the general safety requirements for electrical test and measurement equipment for electrical industrial process control and laboratory equipment [37]. For easier recognition of suitable devices, the standard defines four categories (CAT I, II, III and IV) indicating the specified area of usage for the specific instrument (ranging from measurement in circuits not directly connected to the network up to measurement on overvoltage protection devices). To ensure a true comparability of measurement instruments brought into the market in the European Union, the European Parliament has issued the directive 2004/22/EC, also known as the MID [38]. The MID and related European and international standards like the IEC 60359 ensure a proper indication of performance criteria, basic functional requirements, which are a common way to indicate measurement ranges and limitations of uncertainties of measurement as well as indication of calibration results [39]. Various metering instruments and monitoring solutions are available on the market, which are able to fulfil the requested task of the user. Therefore, the challenge of the user is to define the task. Although, researchers like Schleich have already identified that a lack of information about energy consumption patterns has been found to be a barrier for energy efficiency, which can be overcome by installing metering devices and implementing energy management systems [40]; the biggest difficulty is in fact to define and execute the corresponding metering strategy. Designing a metering strategy incorporates the definition of a metering task, the goal which also describes the characteristics of the resulting measurement in terms of accuracy and resolution. A metering strategy also implies an estimation of the expected value to be metered in order to dimension the metering equipment accordingly. An over or under dimensioned metering system can result in a low accuracy and high variance of the metered value or even an overload situations with fatal errors. Only a few publications are seen in the community of manufacturing engineering that actually address how electricity metering of single devices is actually performed and which measurement instruments are recommended to be used [41].

In the following sections of the paper a guideline for electrical energy metering and monitoring will be presented. Technical and economical challenges will be addressed and specific ranges of technical specifications suitable for the three defined levels of application will be suggested. The decision of selecting suitable measurement instruments always depends on the minimum requirements due to the defined task and the economic aspect as a limiting factor for the upper range of requirements. Technical challenges: Electricity metering instruments are designed to cover a lot of measurement purposes. Some have been developed for highly accurate and real time monitoring like oscilloscopes and others have been designed to suit a variety of tasks such as multi-meters for network quality analysis. Each one of the instruments has different technical specifications that the user has to be aware of before making the purchasing decision. Against each task required, individual set of technical specifications need to be clarified by formulating a measurement strategy while giving certain ranges of specifications of the informational degree. Economical challenges: Selecting the most cost-effective metering solution requires a clear vision of the required outcome. More available options and features are always more expensive and are a quick step towards over-dimensioning. The economical challenges of each level provide some considerations that inevitably come with designing a measurement strategy and implementing electricity metering and monitoring. Factory Level: Selecting the right accuracy class is essential to be able to control electricity billing. Technical challenges: Factory level metering is done on or near the interface between the electricity supplier and the customer. The installed meters from the supplier in industry applications are usually electronic meters that do not simply meter the energy consumption in kilowatt-hours but additionally use certain register intervals in which the specific amount of energy is accumulated. For instance, the register interval in Germany is fixed to 15 minutes, which means the resulting accumulated 15 minute energy is used to charge peak loads in individual electricity supply contracts for industry consumers. The register values from the electronic meters are collected by the supplier by using remote instrument reading. The MID as well as the IEC 62053 enable the customer to select appropriate metering instruments to meter with a higher accuracy and in higher temporal resolution. As a result, breaking down the 15 minute standard register interval from the supplier to 30 second intervals can be used to gain transparency into how 15 minute peak charges occur and be a first step towards evaluation of whether load management could be used to lower the charges. Economical challenges: The investment for metering equipment on this level is considered low since only a few meters (at least one at each medium voltage transformer inlet) are needed. The resulting data volume is considered negligible. Despite this, the selection of the metering instrument is not a simple task. Scientific discussions from the early nineties up until now have stated that higher levels of sophistication in electricity metering will be essential to prepare the suppliers and customers for the inevitable utilization of the smart grid [42-43]. It should be kept in mind that the consumed amount of kilowatt-hours is not the only number that is of interest for the electricity suppliers. There are other parameters such as current, voltage, apparent power and their specific behaviour in time that demands costly improvements and maintenance actions in the distribution networks. Therefore, it might be in the interest of the customer to know in advance about these parameters in order to have transparency into energy billing. The selection of a metering device with the capability to meter active power, apparent power, power factor and the total harmonic

6

Keynotes

distortion as a quality parameter with a temporal resolution of 30 seconds up to 15 minutes with accuracies complying with the standards described earlier (as well as with the local requirements of the state legislations) is highly recommended as a quality parameter. The amount of data collected from one metering device in standard office applications will result in a data volume ranging from 280 megabytes to 8.2 gigabytes per year (depending on the selected resolution). Department level: Metering on department level is done to gain a better transparency of the energy flows inside the organisational and the technical distribution network of the factory. A certain degree of transparency enables organisational and technical energy efficiency measures. The metering strategy and the related challenges in the selection of metering equipment on department level are highly dependent on the consumption behaviour of the single substructures. This paper draws a distinction between highly dynamic behaviour, low dynamic behaviour and near static behaviour as addressed in Table 5. Highly dynamic energy consumption behaviour can be found in assembly or production departments or single lines with several inline processes and machines that perform highly variable processes. As a result, energy demand from the grid is highly variable as well. Low dynamic consumption behaviour can be found in technical building services and are represented by processes like compressed air production, technical air ventilation or facility heating. Near static consumption behaviour can be found in office complexes or in server rooms. These substructures show distinct periodic cycles over days or weeks while being not very prone to sudden changes or peak demands.

Department

Technical challenge: Table 5 presents recommendations for metering specifications for different metering strategies on department level related to the dynamic consumption behaviour of the regarded department. The recommended temporal resolution of the output data of the electronic metering devices are linked with the dynamic behaviour. A high dynamic behaviour needs high resolutions of the metering output data in order to achieve certain transparency and a satisfactory understanding of the consumption behaviour of the department. Behaviour

Resolution

Parameters

Highly dynamic

1 s – 1 min

Wh, VAh, PF

Low dynamic

30 s – 5 min

Wh, VAh, PF

Near static

1 min – 30 min

for high dynamic metering tasks, would result in a yearly data volume of 256 gigabyte (raw data) if three parameters (active power, apparent power and power factor) are logged continuously. Each sub meter added to the metering and monitoring structure adds its part of the data volume share that needs to be handled by the data processing system. The measurement instruments itself will also play a considerable role in the economical challenge. Measurement instruments with high accuracy classes and capabilities to meter THD and PF characteristics are usually too expensive to be distributed on department level metering applications. However, more and more, ultra low cost power quality meters and energy management systems with class A IEC 610004-30 compliance are emerging which will make electricity measurement possible on this level in the near future [44]. In fact, electricity metering and monitoring on department level can actually pay off very quickly as shown in a case study by Stephenson and Paun. The authors demonstrated how a small manufacturer was able to shift and reschedule some of his manufacturing machines to avoid peak charges, and power factor charges by soft starting controls for machine start-ups on Mondays and deferring electrical consumption on activities like energy intensive drying processes or chilled water production by less than two hours without affecting production requirements [45]. Unit process level: On unit process level the single process, machine, or component is being metered and monitored. As mentioned above, it might be needed to do unit process metering in applications considered as department level metering and monitoring, but the actual unit process metering is mostly considered to be research related or only short term metering rather than continuous. In the scientific community unit process metering and monitoring are often found throughout many case studies. Solding et al. have used metering data of unit processes to accumulate the fundamental data basis for energy aware production simulation in various degrees of detail [46]. Considering consumption profiles from products Elias et al. have shown the importance of electricity metering in order to evaluate the user behaviour’s influence on the product’s electric energy consumption [47]. Whereas Dietmair et al. have used electricity metering and monitoring on unit process level to analyse and evaluate machine tool design strategies to foster energy efficiency [48]. Li et al developed an empirical approach to model and predict unit process energy consumption for material removal processes [49].

Wh, PF Behaviour

Economical challenge: The department level metering has probably the highest variety of possible economic impacts that tend to be very case specific. However, general propositions can still be made to address the challenges. Metering on department level is often used to do energy accounting for a fixed sub structure, which can be an organisational structure (department), a production line for a specific product or a storage area. Each one of these clusters of defined sub consumers is drawing electricity from the internal distribution network. Since organisational structures and technical structures are mostly not same due to the building design, the consumer clusters might not be situated in the same branch of the distribution network, which will result in a high number of submeters. These meters can also be used for determining the unit process energy consumption pattern on individual processes. Complex structures of metering systems on this level requires a well structured communication and data computation system to handle the monitoring of the complex metering output data. Single meters with a data output resolution of 1 second, as recommended

Unit process

Table 5: Department level metering specifications.

Highly dynamic Low dynamic

Resolution

Parameters

10 ms – 1 min

Wh, VAh, PF, THD

1 s – 5 min

Wh, VAh, PF, THD

Table 6: Unit process level metering specifications. In all these electricity metering and monitoring applications, the accuracy is not of primary importance since no monetary value is calculated from the metered values. Moreover it is the qualitative importance of the metered values directly related to the high temporal resolution which enables an understanding into the process. Technical challenge: As in department level, the unit process metering specifications are closely related to the dynamics of the unit process’ electrical energy consumption behaviour. Highly dynamic behaviour is likely to be seen in high speed machining processes or robotic applications, whereas low dynamic processes can be seen in thermal or galvanic processes. As Table 6 shows,

Keynotes

7

the recommended temporal resolution can go down to 10 milliseconds for highly dynamic processes. On unit process level, the source of the harmonic distortion and low power factor can also be found and compensated by making use of continuous unit process metering as an input for closed loop controls. Economical challenge: The investment for metering equipment on this level is estimated to be high, because only the highly sophisticated metering systems are able to provide such high temporal resolutions and are able to handle the high data output volume from the single metering equipment. This high data volume enables real time monitoring, but at the same time makes logging applications very data intensive. Especially on unit process level, the harmonic distortion charge of the suppliers can be addressed, as the countermeasures can be applied directly at the source. Total harmonic distortion (THD) is an electrical noise feedback caused by electrical inverters and phase controlled modulators. THD does not only lower the quality of the distribution network, but also severely impacts local machines and sensitive devices. The following section of this paper addresses difficulties in selecting the right measurement equipment for a given task. 5

REVIEW OF AVAILABLE ENERGY METERING DEVICES

In the previous chapter it has been shown that within each electricity measurement task, whether to enable energy efficiency measures or to do energy accounting within organisational structures, it is always a challenge to formulate the right measurement strategy and to select the right measurement instruments for the task of metering. This section gives a brief overview of some typically metering devices found in the market as well as explaining some basic distinguishing features that must be considered in industrial and research applications. Table 7 presents a selection of most commonly used electricity metering instruments from industrial and research applications. The aim is neither to provide a complete list nor to rate the instruments in any way. The selection is just a very limited selection of some important features that distinguish the single instruments. The instrument features range from installation, which describe whether the device can be mounted in a fixed location or if it can be used in mobile applications. Mobile applications are usually found in short time measurement for quick energy assessments on factory or unit process level or in special research applications. Fixed types Measurement instrument:

Installation

of devices can be found in the long time measurement applications available on all levels. Such devices can be built-in directly into control or distribution cabinets. As the evolution of electricity metering devices has allowed user to obtain not only single measurands meters (Ferraris disc meter) but also multi measurands meters, a broad selection of possible measurands becomes available and allows more integrated applications. This enables for example single devices at factory level to provide users the information about active energy consumption for energy controlling as well as reactive energy and total harmonic distortion values for quality monitoring at the same time. The amounts of measurands that can be read from the single devices are defined by the complexity of the electronic meters and often manifest itself in the purchasing price. Table 5 and Table 6 show certain ranges of recommended resolutions of the metering points needed to perform metering applications. The output resolution presented in Table 7 should match these required resolutions in order to be well dimensioned for the metering task. The degree of output resolution is directly proportional the purchasing price of the instruments. Data loggers with resolutions of higher than a metering point per second can exceed 5000 EUR. A high output data resolution is not always a sign of quality. It is rather an indication of the possible types of information that can be gained from the metering data through analysis. As discussed earlier, a high degree of metering data resolution can quickly result into high additional costs for handling of the large amounts of resulting data if centralized monitoring is used. Selecting the right degree of detail is an essential part of the right dimensioning of a metering strategy. In large metering networks, commonly found in department level metering and monitoring, the communications interface plays a very important role as well. Metering and monitoring applications have to be able to use the same communication interface. Real-time monitoring and control applications often use industrial bus interfaces like Profibus or in near real-time applications interfaces like Ethernet. Simple applications such as monitoring for energy accounting do not rely on real-time data and are usually working with bus systems based on RS485 or even impulse signal recognition. The communication interface matching is very important when designing cost-effective metering strategies. Multi interface applications can easily lead to complex and costly software and hardware conflicts. If a holistic department level

Measurands*

Brand, series/type

Output resolution*

Communication interface*

IME, NEMO 96

Fixed type

V, A, W, VA, PF, THD

60 s

RS485, Impulse

Siemens, SIMEAS

Fixed type

V, A, W, VAR, VA, PF, THD

< 1s

Profibus, RS485

Schneider, Electrics, PM

Fixed type

V, A, W, VA, PF, THD

60 s

RS485, Impulse

Simpson, GIMA1000

Fixed type

V, A, W, VAR, VA, PF

1s

RS485, Impulse

Yokogawa,

Fixed type

V, A, W, VAR, VA, PF

<1 s

Ethernet, RS485, Pulse

AccuEnergy, Acuvim

Fixed type

V, A, W, VAR, VA, PF, THD

<1 s

Ethernet, Profibus, RS485, Impulse

Janitza Electronics, UMG 604

Fixed type

V, A, W, VAR, VA, PF, THD

<1 s

Ethernet, Profibus, Impulse

Chauvin Arnoux, C.A.8335

Mobile type

V, A, W, VAR, VA, PF, THD

1s

USB

Fluke, 434

Mobile type

V, A, W, VAR, VA, PF, THD

0.5 s

Voltech, PM3000

Mobile type

V, A, W, VAR, VA, PF, THD

<10 ms

Load Controls, PPC

Mobile type

W

National Instruments, cDAQ*

Mobile type

V, A

15 ms <1 s

USB RS232, IEEE488 Analogue 0-10 volts or 4-20 milliampere USB

*the listed features are retrieved from the datasheets of the devices and are due to change in future instrument revisions

Table 7: Selection of often found electricity measurement instruments with a selection of important distinguishing features.

8

Keynotes

6

REVIEW OF SELECTED ELECTRICITY METERING AND MONITORING SYSTEMS FOR RESEARCH PURPOSES

In this section, a special emphasis will be given to electricity metering and monitoring systems for research related purposes. As stated before, research applications most often utilize mobile systems in order to redeploy them easier. The last five instruments listed in Table 7 are mobile metering devices with different features, individual advantages and weaknesses. The two devices from Fluke and Chauvin Arnoux are highly sophisticated industrial multi-measurands instruments that are capable to log measurement values in high temporal resolution of up to 0.5 and 0.1 seconds respectively. Plug and play features allow users to perform highly mobile measurement strategies as found in quick energy assessments or simple before-and-after measurements to evaluate energy efficiency measures. Other instruments like from Voltech and Load Controls are very likely to be used in detail energy system analyses. Very high metering data resolutions in the range of hundredth of a second allow analysing transients, inrush currents and other short term electrical events. The specific characteristic of these two devices is that they need additional external digital analogue converters with high sampling rates for logging purposes of the analogue data output interface, which is additionally affecting the accuracy of the logged metering values. The last item on the list from National Instruments is a typical laboratory solution for research tasks, with an open programming platform to create individual metering algorithms. The individual algorithms and the specifications of the individual input modules define the amount of calculated measurands and their accuracy. Since such an open platform is not sufficient for energy accounting or related purposes on factory or department level, this mobile device is solely meant for research applications with a high degree of individuality and freedom. 7

INDUSTRY CASE: ONGOING CHALLENGES OF DEPLOYING A METERING AND MONITORING STRATEGY IN AN AUSTRALIAN MANUFACTURER

The presented case is derived from the analysis of a bio-medical products manufacturing company in Australia. The increasing energy bill due to both business growth and rising energy cost has been considered as one of the main issues in this company. This not only impacts the environmental performance of this company but also affects its business strategy. Reducing energy consumption would benefit the company both economically and ecologically. The main aim was to identify the areas of improvement as well as implementing energy accounting for individual functional units, processes and ultimately for the individual products. Thus, the company has decided to implement an energy management system. The first step taken is to establish a metering and monitoring system in order to achieve transparency into its energy consumption. The company initially aims to monitor the energy consumption behaviour from top factory level down to sub-department levels. Multiple energy meters were thus allocated throughout the distribution network. The factory plant is powered by an 11 kV electrical connection from the energy supplier. The voltage is decreased to 400 V three-phases by 3 transformers, which powers

3 main switch boards and then splits into different distribution boards. The energy meters attached at the three main transformers is to be able to perform parallel metering on the factory, which aims to check the accuracy of the electricity bill from the supplier. The metering devices at the distribution boards and circuit breakers were then assigned to individual department or sub-departments. A Supervisory Control and Data Acquisition system (SCADA) here allows the real time management of energy consumption. The system also allows the user to configure analysis and reports to show the previous and current energy consumptions. By performing the analysis of the demand for each department or area, management can determine the Key Performance Indicator (KPI) and apply procedures to minimise demand, which leads to energy savings and lower energy bill. The output from the power meter devices were collected with the SCADA server via RS485 communication, which requires gateways to access them to the factory Ethernet communication network. However, the deployed energy metering and monitoring system failed to provide reliable information of energy consumption of the plant. The aggregation of energy consumption measured at three main transformers did not agree with the electricity bill. The gap between measured value and billed amount far exceeded the errors due to the measurement. Assuming that the energy supplier measured the real amount of energy consumption and billed correctly, the failure to obtain similar total energy consumption reading internally may possibly due to the selection of power meters. As the energy supplier charges not only the total work load but also peak power, low power factor and THD, the current meters did not cope with the range of all the energy billing categories. The following Figure 3 shows the energy consumption profile of the factory over a year per period.

Main Transformers Plant Room

Energy [kWh]

metering strategy is to be deployed, a high amount of time has to be invested for investigating the possible existing communications infrastructure and resulting requirements for the new data communication system.

Administration Bottle Filling

Jan

Feb Mar Apr May Jun

Jul

Aug Sep Oct Nov Dec

Figure 3: Break-down of energy consumption profile over a year. The reading of the power meters at the distribution boards and circuit breakers experienced inconsistency throughout the period. For example, the recorded data for one department gave zero energy consumption for the whole year, where the plant actually runs 24/7. Another example is that some unusual spike was recorded for Administration department as shown in Figure 3, which even exceeded the total energy consumption of the main transformers. The possible reason for this failure is mainly due to the connection problem within the communication system between power meters and SCADA server. Furthermore, the layout of distribution network did not agree with the organizational structure as shown in Figure 4. In order to implement energy accounting for each organizational department, the energy monitoring system requires new metering points in the distribution network. As a result a new energy monitoring system

Keynotes

9

has been implemented, which resulted in changing some of the existing devices and installing new ones in order to extend the monitoring and measuring to individual processes. A considerable cost is thus caused to improve the energy metering and monitoring system.

Organizational Structure

Machine 1

…

…

SubDepartment

SubDepartment

SubDepartment

…

SubDepartment

SubDepartment

SubDepartment

SubDepartment

Periphery System 1

…

After these changes, company’s external reading and energy bill have started to agree with the internal measurements. Currently the company, in collaboration with the authors, has been developing a new energy oriented factory planning system in order to link the material flow to the energy flow within the factory. Currently the company’s energy bill exceeds $1M a year. Despite the initial investment with the introduction of the new system, company is expected to reduce its energy bill by about 30% as well as reducing its carbon foot-print substantially. SUMMARY AND OUTLOOK

Today’s manufacturing companies are facing a more stringent cost pressure than ever before due to rising energy and resource costs and the associated environmental impact. Manufacturing companies have come to realisation the importance of electrical energy metering and monitoring as a foundation to work out energy efficiency improvement potentials. This key note paper presented a short review of the evolution and the latest developments in electricity metering monitoring systems. A special emphasis is given the challenges of the designing of metering strategies in order to properly dimension metering instruments for a given task. In addition, the paper addressed the critical aspects of data communication and the compatibility of interfaces in relation to different application areas. An exemplary list of metering devices was presented to demonstrate how the features of the different measurement instruments can be matched for certain measurement tasks on different application levels. In order to emphasise the importance of a well designed metering strategy and selection of the right metering and monitoring equipments, a case study from a manufacturing company was presented. 9 [1]

Schwendtner, M.F. (1996): Digital measurement system for electricity meters, in Metering and Tariffs for Energy Supply Conference Publication, Institution of Electrical Engineers, No. 426, pp. 190-193.

[6]

Schwendtner, M.F. (1996): Technological developments in electricity metering and associated fields, in Metering and Tariffs for Energy Supply Conference Publication, Institution of Electrical Engineers, No. 426, pp. 240-242.

[7]

International Electrotechnical Commission (2003): 62053:2003 - Electricity metering equipment (a.c.).

[8]

American National Standards Institute (2010): ANSI C12.202010 - Electricity Meters - 0.2 and 0.5 Accuracy Classes.

[9]

Verein Deutscher Elektrotechniker (1976): VDE 0410 Regeln für elektrische Meßgeräte.

[10]

International Electrotechnical Commission (1998): IEC 60051:1998 - Direct acting indicating analogue electrical measuring instruments and their accessories.

Periphery System n

Figure 4: Factory organisational structure and the existing metering system.

8

[5]

Department

SubDepartment

Machine n

Shtargot, J. (2008): Advanced Power-Line Monitoring Requires a High-Performance Simultaneous-Sampling ADC, in MAXIM Application Note 4281.

Distribution Network

Factory

Department

[4]

REFERENCES Herrmann, C.; Kara, S.; Thiede, S.; Luger, T. (2010): Energy Efficiency in Manufacturing – Perspectives from Australia and Europe, in: CIRP International Conference on Life Cycle Engineering, pp. 23-28.

[2]

Moore, A. E. (1935): The History of the Integrating Electricity Meter, in: Journal of the Institution of Electrical Engineers, Vol. 77, No. 468, pp. 851-859.

[3]

Colburn, R. (2010): The History of Making the Grid Smart, in: IEEE today’s engineer, online available on: http://www.todaysengineer.org/2010/May/history.asp, last th accessed on 8 December 2010.

IEC

[11] Irwin, L.A. (2010): A High Accuracy Standard for Electricity Meters, in Transmission and Distribution Conference and Exposition, New Orleans. [12] Lerch, R. (2007): Elektrische Messtechnik, Springer-Verlag Berlin Heidelberg. [13] International Electrotechnical Commission (1996): IEC 600441:1996 - Instrument transformers - Part 1: Current transformers. [14] Start, D.J. (1995): A review of the new CENELEC standard EN 50160, in: Issues in Power Quality, IEE Colloquium [15] European Committee for Electrotechnical Standardization (2007): EN 50160:2007 - Voltage characteristics of electricity supplied by public distribution networks. [16] Masetti, C. (2010): Revision of European Standard EN 50160 on power quality: Reasons and solutions, in: 14th International Conference on Harmonics and Quality of Power. [17] Herrmann, C.; Bogdanski, G.; Zein, A. (2010): Industrial Smart Metering – Application of Information Technology Systems to Improve Energy Efficiency in Manufacturing, in: 43rd CIRP International Conference on Manufacturing Systems, Wien, pp. n.a. [18] Hesselbach, J.; Herrmann, C.; Detzer, R.; Martin, L.; Thiede, S.; Lüdemann, B. (2008): Energy Efficiency through optimized coordination of production and technical building services, in: 15th CIRP International Conference on Life Cycle Engineering, Sydney, pp. 624-629. [19] Jahn, M.; Jentsch, M.; Prause, C.R.; Pramudianto, F.; AlAkkad, A.; Reiners, R. (2010): The Energy Aware Smart Home, in: 5th International Conference on Future Information Technology. [20]

Herrmann, C.; Thiede, S.; Zein, A.; Heinemann, T. (2010): Holisitc Approaches for Increasing Energy and Resource Efficiency in Manufacturing, in: Proceedings of the 1st International Conference on Automotive Materials and Manufacturing, Pune.

[21] Herrmann, C.; Thiede, S. (2010): Simulation-based Energy Flow Evaluation for Sustainable Manufacturing Sytems, in: CIRP International Conference on Life Cycle Engineering, pp. 99-104.

10 [22]

[23]

Keynotes Huang, H.; Liu, Z.; Zhang, H.-C.; Sutherland, J.W. (2010): A Proposed Method to Study the Life-cycle Energy Consumption of the Automotive Industry, in: CIRP International Conference on Life Cycle Engineering, pp. 127130. Klocke, F.; Lung, D.; Schlosser, R.; Nau, B. (2009): Energy and Resource Efficient Production – a Core Competence for Manufacturers, in: 16th CIRP International Conference on Life Cycle Engineering, pp. 209-214.

[24]

Herrmann, C.; Thiede, S. (2009): Towards Energy and Resource Efficient Process Chains, in: 16th CIRP International Conference on Life Cycle Engineering, pp. 303309.

[25]

Chiotellis, S.; Seliger, G.; Weinert, N. (2009): Energy-aware Production Planning and Control, in: 16th CIRP International Conference on Life Cycle Engineering, pp. 310-315.

[26]

Müller, E.; Löffler, T. (2009): Improving Energy Efficiency in th Manufacturing Plants – Case Studies and Guidelines, in: 16 CIRP International Conference on Life Cycle Engineering, pp. 465-471.

[27]

Rahimifard, S.; Seow, Y.; Childs, T. (2010): Minimising Embodied Product Energy to support energy efficient manufacturing, in: CIRP Annals – Manufacturing Technology, pp. 25-28.

[28]

[29]

[30]

[31]

Herrmann, C.; Thiede, S. Heinemann, T. (2010): A Holistic Framework for Increasing Energy and Resource Efficiency in Manufacturing, in: 8th Global Conference on Sustainable Manufacturing. Klocke, F.; Schlosser, R.; Lung, D. (2010): Energy and Resource Consumption of Cutting Processes, in: 17th CIRP International Conference on Life Cycle Engineering, pp. 111115. Dietmair, A.; Verl, A. (2010): Energy Consumption Assessment and Optimisation in the Design and Use Phase of a Machine Tool, in: 17th CIRP International Conference on Life Cycle Engineering, pp. 116-121. Devoldere, T.; Dewulf, W.; Deprez, W.; Duflou, J.R. (2008): Energy Related Life Cycle Impact and Cost Reduction Opportunities in Machine Design: The Laser Cutting Case, in: 15th CIRP International Conference on Life Cycle Engineering.

[32]

Devoldere, T.; Dewulf, W.; Deprez, W.; Willems, B.;Duflou, J.R. (2007): Improvement Potential for Energy Consumption in Discrete Part Production Machines, in: 14th CIRP International Conference on Life Cycle Engineering, pp. 311316.

[33]

International Standardization Organisation (2003): ISO 13374-1:2003 – Condition monitoring and diagnostics of machines – Data processing, communication and presentation, Part 1: General guidelines.

[34]

Bottene, A.C.; Franca, T.V.; Ometto, A.R.; Torrisi, N.M.; Filho, A.G. (2009): Methodology to integrate the electrical energy consumption real-time monitoring and related environmental impacts assessment, in: 16th CIRP International Conference on Life Cycle Engineering, pp. 373-376.

[35] Vijayaraghavan, A.; Dorenfeld, D. (2010): Automated energy monitoring of machine tools, in: CIRP Annals – Manufacturing Technology, pp. 21-24. [36]

Rohdin, P.; Thollander, P. (2006): Barriers to and driving forces for energy efficiency in the non-energy intensive

manufacturing industry in Sweden, in: Energy, vol. 31, issue 12, pp 1836-1844. [37] International Electrotechnical Commission (2009): IEC 610101:2009 - Safety requirements for electrical equipment for measurement, control, and laboratory use - Part 1: General requirements. [38] European Parliament and (2004): 2044/22/EC directive on measuring instruments, in: Official Journal of the European Union, L 135. [39]

International Electrotechnical Commission (2001): IEC 60359:2001 – Electrical and electronic measurement equipment – Expression of performance.

[40] Schleich, J. (2009): Barriers to energy efficiency: A comparison across the German commercial and services sector, in: Ecological Economics, Vol. 68, pp. 2150-2159. [41]

Herrmann, C.; Zein, A.; Winter, M.; Thiede, S. (2010): Procedures and Tools for Metering Energy Consumption of Machine Tools, in: 3rd International Scientific Conference with Expert Participation – MANUFACTURING.

[42] Sioshansi, F.P. (1991): Electronic metering and two-way communications – The electric power industry, in Utilties Policy, Vol. 1, No. 4, pp. 294-307. [43] Mak, S.T. (2010): Sensor Data Output Requirements for Smart Grid Applications, in Power and Energy Society General Meeting, IEEE, ISSN 1944-9925, pp. 1-3. [44] McEachern, A.; Eberhard, A. (2009): A new, ultra low cost th power quality and energy measurement technology, in: 20 International Conference on Electricity Distribution, ISBN: 978-1-84919126-5, pp. 1-4. [45] Stephenson, P.; Paun, M. (2000): Consumer Advantages from Half-Hourly Metering and Load Profiles in the UK Competitive Electricity Market, in: International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, pp. 35-40 [46] Solding, P.; Petku, D.; Mardan, N. (2009): Using simulation for more sustainable production systems, in: International Journal of Sustainable Engineering, Vol. 2, No. 2, pp. 111122. [47] Elias, E.W.; Dekoninck, E.A.; Cully, S.J. (2009): Quantifying the Energy Impacts of Use, in: 16th CIRP International Conference on Life Cycle Engineering, pp. 444-451. [48] Dietmair, A.; Zulaika, J; Sultika, M; Bustillo, A.; Verl, A. (2010): Lifecycle Impact Reduction and Energy Savings through Leight Weight Eco-Design of Machine Tools, in: 17th CIRP International Conference on Life Cycle Engineering, pp. 105-110. [49] Li, W.; Kara, S. (2011): An Empirical Model for Predicting Energy Consumption of Manufacturing Processes: A Case of Turning Process, in: Proceedings of the Institution of Mechanical Engineers, Part B, Journal of Engineering Manufacture.

Implementing Life Cycle Engineering efficiently into Automotive Industry Processes Stephan Krinke Volkswagen AG, Head of Group Research Environmental Affairs Product, Wolfsburg, Germany

Abstract Life cycle assessment (LCA) is a powerful tool which supports life cycle engineering. It can be used as an environmental management instrument within the product development. For successful life cycle engineering the formal incorporation of life cycle thinking into the company policy is a necessary pre-requisite. Additional success factors which have to be met are the transformation of LCA results into measurable targets for engineers. Based on given environmental targets, such as a certain target value for greenhouse gas emissions, LCA can be used to calculate a specific technical target such as the weight of a component, the fuel consumption of a vehicle or the minimum amount of recycled content in a product. The transformation of pure LCA results into measurable target values, which can be understood by engineers, will clearly show the added value which LCA can give in terms of life cycle engineering.Even for very complex products with a huge variety of different materials and a complex value chain life cycle assessment can be performed with a reasonable time demand, with good quality and integrated efficiently into business processes. Keywords Design for Environment; Automotive; LCA; Life Cycle Engineering



Environmental management based on figures and facts

The automotive industry is since decades one of the industrial focus areas for environmental technologies and environmental protection.



Identification of hot spots for product optimization along the entire value chain

But how can the environmental performance of a complex product such as an automobile be measured? The aspects which directly or indirectly influence the environment are manifold:



LCA is an internationally accepted method and a firm basis for a dialogue with stakeholders



LCA is part of company ratings which directly influences the interest rate and financial power of the company

1

INTRODUCTION

Starting with the production of raw materials and going along the value chain the entire production affects the environment. Especially the automotive industry is one of the industry sectors with a very complex value chain, including nearly all kind of materials such as metals, polymers, glass and ceramics. The usage phase of the vehicle also effects the environment due to the combustion of fuel and the herewith linked emissions such as CO2, contributing to climate change. Other tailpipe emissions such as carbon monoxide, nitrogen oxides and hydrocarbons contribute to local air quality (e.g. summer smog). The quantity of these impacts depends on the fuel consumption and the emission standard of the vehicle. And last but not least the driving behavior of the customer, which influences the fuel consumption, has an impact on the environment. During the end-of-life phase materials are recovered or recycled from the end-of-life vehicle and can be used as secondary (raw) materials in other applications. Therefore the environmental assessment of a vehicle has to cover the entire life cycle. One of the most suitable instruments to measure the potential environmental impact of a product is life cycle assessment [1, 2]. Volkswagen started in 1991 with a research study for the life cycle inventory (LCI) of the Golf III which was published as first automotive LCI of a complete vehicle worldwide in 1996 [3]. In the following years LCIs of different vehicles of the Volkswagen Group were published [4, 5, 6, 7]. Today the Volkswagen Group has incorporated life cycle thinking as a main principle of the product development. The advantages of this approach are:

In the following chapters the environmental strategy of the Volkswagen group and the implementation of life cycle engineering into the environmental management will be explained. 2

ENVIRONMENTAL STRATEGY

The key element of the Volkswagen group strategy 2018 is to position the Volkswagen group as a global economic and environmental leader among automobile manufacturers. We intend to set new environmental standards in vehicles, powertrains and lightweight construction. 2.1

Environmental challenges

The main environmental challenges for the automotive industry today and in future are climate protection, health and local air quality and resource protection. Therefore these three items are incorporated into the environmental principles product of the Volkswagen Group. This standard is the basis for the product related environmental strategy. 2.2

Environmental strategy of the Volkswagen Group

The environmental strategy of the Volkswagen group has two main pillars: The environmental standard production and the environmental principles product. The latter addresses the three main environmental challenges (climate protection, health and local air quality and resource protection) and incorporates the life cycle engineering as a main principle in product development.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_2, © Springer-Verlag Berlin Heidelberg 2011

11

12

Keynotes

Environmental Strategy Volkswagen Group „Individual ecological mobility“ Group Management Group Environmental Strategy Committee

Environmental Standards Product

Environmental Standards Production

Climate

- Emissions - Consumption -…

Infrastructure - Energy - Water - Waste -…

Resources

- Alternative fuels - Recycling -…

Health

Production processes

- Pollutants - Noises -…

Guidelines

Preamble

Environmental Policy

- Press shop - Paint shop - Foundry -…

Regional Environmental Conferences / Environmental-Audits ISO 14001 / EMAS Figure 1: Environmental strategy Volkswagen Group. The Volkswagen group is committed to developing vehicles and components in such a way that they have better environmental properties than their predecessors over the entire life cycle. Life cycle assessments are used to analyze and document the environmental performance of vehicles, technologies and processes.



Reliable, meaningful and measurable targets for product development



Communication strategy

3

For the Volkswagen group the environmental standards production and product are the basis for the environmental strategy. But for a successful environmental management system this is only the starting point.

SUCCESS FACTORS FOR LIFE CYCLE ENGINEERING

Whereas the first ideas of life cycle based analysis were developed 30 years ago, it still remains a challenge to implement life cycle assessment successfully as environmental management tool into business processes. In this chapter we describe the key success factors for such an implementation. The success factors are: 

Integration into company policy and processes



Reasonable time demand

3.1

Integration into company policy and processes

The commitment of the top management is crucial for the success of any environmental policy and strategy.

For the Volkswagen brand we developed an environmental management scheme according to Figure 2. Responsible for the implementation of environmental aspects into the product development is the environmental officer product.

Environmental Management at Volkswagen Networking and directing worldwide activities in environmental protection

Head of the Group Research Division

Board of Research and Development

Group Environmental Strategy Committee

Environmental management officer of the Volkswagen brand

Environment

Environmental officer product

Environmental protectors for R&D Volkswagen

Environmental Affairs Strategy

Vehicles

Environmental officer for production

Environmental Affairs Product

Modules

Environmental Affairs Production

Material controlling

LCA & raw material analysis

Environmental officers at the locations Wolfsburg

Emden

Hanover

Zwickau

Pamplona

Figure 2: Environmental management at Volkswagen.

Other locations

Keynotes

13

Environmentally compatible product development Volkswagen brand Product development over time

Development stages and tasks Environmental Analysis

Environmental Control

Material controlling

Research

Advance engineering

Vehicle targets

Characteristics catalog

Performance specifications

Product description book

LCAs and strategic environmental topics Raw material analysis

Model update

Follow-up Environmental commendations

Supervision of vehicle projects Screening of environmental related laws and activities of competitors

Product communication

Environmental targets, performance specifications and standards Environmental product Environment and descriptions innovation roadmaps Global material legislations

Material controlling Material data acquisition (MISS/IMDS) Legends Tasks Instruments

Figure 3: Environmentally compatible product development for the Volkswagen brand. Figure 3 shows an overview of different tasks and instruments along the product development which usually takes around 48 months until the start of production.

sure that the entire life cycle is taken into account during the development of our products.” This target is signed by the board member for the technical development for the Volkswagen brand.

Different teams act along the product development. The team environmental analysis has the task to perform LCA and strategic raw material analysis for different components and technologies. The focus of this work is the early phase of the product development including research. Strategic raw material analysis focuses on long term risk assessment [8] such as 

Supply and demand today and in future



Production costs



Geostrategic risks



Market power of the raw material suppliers

Life cycle inventory data and the herewith linked bill of materials is a powerful basis for raw material risk assessment which can not be performed without that information. The task of the LCA is to compare different technologies in the early phase of product development. The challenge of this task is that the information required for the LCA is often not fully available in the early phase of the product development. E.g. the body-in-white concept is known from the material perspective, but the exact weights of the different components are unknown. Here LCA should be applied in such a way that the unknown variables are calculated as measurable target values. In our example where we do not know the exact weight of all components the sum of the component weight can be calculated as target, which has not to be exceeded in order to achieve an environmental goal such as a maximum greenhouse gas emission potential. Another important aspect for the implementation of life cycle engineering is the formal inclusion of the suppliers. Volkswagen included in its supplier conditions that on request the supplier has to deliver life cycle inventory data for his parts and components [9]. Additionally the IMDS system (www.mdsystem.de) is a reliable data basis for information about the material composition and the bill of materials of a certain part. The most important aspect is that the Volkswagen brand included in its environmental objectives “that we will develop each model in such a way that, in its entirety, it presents better environmental properties than its predecessor. As we do so, we will always make

Figure 4: Environmental objectives of the Volkswagen brand.

14

3.2

Keynotes

Reasonable time demand

Data quality

LCA is a very comprehensive tool which offers a detailed insight in the environmental profile of a product. Performing an LCA of a complex product can be divided into two steps: The first is the data collection of the product. Here the part list of the product is required. For every single component the material composition must be quantified and the herewith linked production process chain must be defined. This step can be improved in terms of time efficiency via the implementation of IMDS data for the components and the linkage to other internal ISsystems of the company. Anyhow this still remains a time consuming step and can take even today up to 30 days. The final result of step 1 is a so called transfer file, which describes for a vehicle every single component by its bill of material and the respective production chains (see Figure 5). The second step is the transfer of this information into a LCA model. Within Volkswagen we developed an in-house solution which automatically builds up the LCA model based on the information of the transfer file and the so called correlation list [10]. The correlation list correlates each material and each production process to a respective LCI data set. The advantage of this approach is not only a huge reduction in time demand but also huge increase in consistency and quality of the LCA results. Time and Resource Demand for LCA of Cars ~ 1-30 days

transfer file

interface 1

~ 0-2 days

mapping file

other internal data sources

complete transfer file

For commodities generic data sets can be used as a first approach. For the modeling of special materials, which are new on the market or based on new technologies, a data acquisition in cooperation with the respective supplier is strongly recommended. At that point a formal requirement for data acquisition of life cycle inventory data in the supplier contracts is very helpful. For highly innovative industries, such as the automotive industry, it is of utmost importance to use high-quality inventory data in order to assess the environmental profile of new materials and new technologies. This is a challenge because the knowledge of new technologies and new materials is of course limited. But this does not mean that LCA can not be applied. Also in this case the area of unknown knowledge can be transformed by LCA into a measurable target value. If, for instance, the energy consumption of a new production process is still unknown, an LCA can be used to calculate the acceptable maximum energy consumption in order to achieve a certain environmental target. Anyhow there is a parallel between the automotive industry and life cycle assessment: High-tech powertrains need high-quality fuels – high-tech LCA need high-quality inventory data. Therefore today and in the future the provision of high-quality inventory data will remain an important and necessary task, especially for science and consultancy.

Situation today ~ 1 day

Foreground data, such as the bill of materials, information about production processes or energy consumption in the use phase, describes the characteristics of the product. From our experience this foreground data is of major relevance and has a strong influence on the overall LCA results.

interface 2

3.4 internal data sources

IMDS

specify vehicle

data base

technical drawings

product model

IMDS

 close data gaps  check weights  check materials manual processing

map material/ process information to available data sets in database

predefined process

electronic data

Figure 5: Time and resource demand for LCA of vehicles. Therefore life cycle assessments, even for complex products with a huge variety of different parts and materials, can be performed with a reasonable time demand.

3.3

Reliable and development

measurable

targets

for

the

product

Life cycle assessment is an environmental management tool that delivers scientific sound results, not less but also not more. A good environmental management system is therefore characterized by the capability to transform LCA results e.g. in terms of a greenhouse gas profile of different technologies into a technical target which can be understood, measured and monitored by an engineer. These targets can be fuel consumption, electric power consumption or the weight of a certain component. The real challenge of life cycle engineering is to bring together two different worlds: The world of the LCA expert, who models the product in terms of environmental impacts versus the world of the engineer who develops the product and takes technical measure that influence the environment. In order to derive reliable, meaningful and measurable targets the following aspects should be considered. Stable and reliable results As LCA is a model outcome every LCA result should be tested by sensitivity analysis in order to prove whether the result, or much more important, a derived technical recommendation, is stable while varying certain model parameters or assumptions.

Communication strategy

It is most important that products with special environmental features or technological improvements are also communicated as such. A company which invests in environmental performance and technology leadership should also use these characteristics in the communication and marketing. Therefore the challenge in that area is to translate LCA results into a communication that will be understood by the respective target groups. It is notable that economical and environmental optimization oftentimes are in line, especially with regard to the fuel consumption. In the case of the automobile industry we have to differentiate between private customers and fleet customers as two different kinds of target groups. Whereas private customers mostly focus on fuel consumption and emission levels in terms of costs, they do not reflect what we call total cost of ownership (TCO). While TCO means that higher purchase prices can be amortized over life time at the customer, the private customer has in many cases a limited willingness to pay for additional environmental features, even if they offer the opportunity to get the economical break-even within a time scale of 2-3 year. In contrast to that, fleet customers base their decisions often on TCO calculations. For an OEM this means that fleet customers have a willingness to pay for environmental technologies such as BlueMotion, if the economical break even will be reached within a few years. But also other environmental aspects might be important for fleet customers, e.g. a company can improve their sustainability ranking by improving the company fleet cars. For the Volkswagen brand we developed the so-called environmental commendations (www.environmentalcommendation.com). Environmental commendations for new vehicle models and technologies highlight ecological progress compared with predecessor models and previous technologies. We use environmental commendations to inform our customers, our shareholders and other stakeholders how we are making our

Keynotes products and production processes more environmentally compatible and what we have achieved in this respect. The underlying LCA not only covers the time when the vehicle is on the road but its entire life cycle from production through to use and disposal. This reflects the fact that we assume responsibility for the entire supply chain, including the production of raw materials and parts for our vehicles. We engage in dialogue with our suppliers to identify environmental measures that can be taken. The information of environmental commendations is based on an LCA, which has been verified and certified by the technical inspection organization TÜV NORD. The TÜV certificate confirms that the LCA is based on reliable data and that the methods used to compile it comply with the requirements of the ISO standards 14040 and 14044.

4

15 vehicles steeltechnologies.

and

aluminum

lightweight

are

established

INTELLIGENT LIGHTWEIGHT DESIGN OVER LIFE CYCLE

In this chapter we show how an LCA can be applied as environmental management tool within the product development. Lightweight design measures are chosen for this example. Modern lightweight design is one of the key technologies for an efficient future mobility, because it contributes to reduce the fuel consumption and the herewith linked CO2-emissions. Based on the Volkswagen’s environmental standard for products this means that any lightweight design measure should also have an environmental benefit over the entire life cycle. Approximately one third of the fuel consumption in the NEDC (New European Driving Cycle) depends on the mass of the vehicle. Lightweight materials such as aluminum or magnesium are energy intensive in the production as shown in Figure 6.

Figure 6: Greenhouse gas emission for the production of different materials. Figure 6 also shows the range of greenhouse gas emissions for the production of different metals. The reasons for this range are manifold: The amount of recycled material, the CO2-intensity of the used energy mix, different kinds of protecting agents and their impact on climate change are only a few aspects which influence the greenhouse gas balance of such a material. It is also important to note that a comparison of materials can not be done based on Figure 6. A comparison can be done by including the entire life cycle and by assessing products which fulfill the same functions. E.g. a body-in-white with the same crash performance will have different weights depending on the material-mix applied and the design of parts. For lightweight concepts the herewith linked CO2-emissions in the production phase are often, but not always, higher than those ones for conventional construction. These additional CO2-emissions which occur in the production phase should be compensated as fast as possible during the use phase due to lower fuel consumption of the lightweight design. Only when we achieve the ecological breakeven, we speak of an “intelligent“ lightweight design as shown in Figure 7. Volkswagen has different strategies to reduce the weight of a vehicle. Besides different material concepts the integration of different functionalities contributes to reduce the number of parts. For the body-in-white construction, which accounts for up to 35% of the overall vehicle weight in the series production of passenger

Figure 7: Lightweight design and environmental break-even. The question whether a specific lightweight concept has a better greenhouse gas balance than a competing concept, can be answered only by assessing the entire vehicle. An important question is whether a lightweight measure will lead to a smaller engine or not. Of course any lightweight measure reduces the fuel consumption. But this reduction is low (0,15 l/100km*100kg for gasoline engines) compared with a fuel reduction of 0,35 l/100km * 100kg which can be achieved by additional measure of the engine. What is clear from the above examples is, that it is not possible to make general claims along the lines that „material A is always better or always worse than material B“. Whether a lightweight design measure reduces life cycle greenhouse gas emissions or not will primarily depend on the following factors: the extent of the weight savings by material and material-adopted design, whether powertrain modifications can be implemented and the quality of secondary (recycled) materials derived from the end-of-life vehicle. In practice, one and the same lightweight design measure might allow powertrain modifications to be made on vehicle A but might not, by itself, be sufficient to warrant such modifications on vehicle B. Saying this, it is often the case in practice that components or assemblies are optimized and assessed in isolation from each other, so that the significance of each measure in the causality chain that leads ultimately to powertrain modifications cannot always be clearly determined. Therefore lightweight measures should always be assessed from the perspective of the entire vehicle and not from the part perspective. As can be seen in Figure 8, the potential benefits of the various lightweight materials extend even further. The table shows the main actors – and potential actions – at the different life cycle stages. For example the material manufacturing stage offers the opportunity to significantly reduce specific CO2-emissions per kg of material produced by reducing specific energy consumption and/or through the use of renewable, low-carbon energy sources. The use of secondary (recycled) materials can likewise help to reduce environmental impacts – for example some cast alloys already use up to 90 % recycled content. On the process side, too, measures such as use of climate-friendly shielding gases as a replacement for SF6, or the reduction of offcuts and scrap, all have a part to play. In the vehicle use phase meanwhile, fuel-efficient vehicle design measures by the OEM must be complemented and maximized through the optimal use of this potential by customers e.g. by ecodriving trainings. Finally, at the recycling stage, reprocessing of lightweight materials into high-quality secondary materials will

16

Keynotes

influence the range of potential applications of such materials and thus the associated positive environmental impacts.

Figure 8: Environmentally friendly lightweight design, aspects and measures. Seen from this overall perspective therefore, it is clear that environmentally friendly lightweight product development offers a wide range of different measures. In addition to the engineers in the automotive industry, the other stakeholders in the value chain (materials manufacturers, suppliers, recycling companies) likewise have their part to play in further improving their products and enhancing the life cycle environmental impact of vehicle concepts of the future.

5

CONCLUSIONS

As demonstrated above, life cycle assessment is a powerful tool which can be used as an environmental management instrument within the product development. For successful life cycle engineering the formal incorporation of life cycle thinking into the company policy is a necessary pre-requisite. Additional success factors which have to be met are the transformation of LCA results into measurable targets for engineers. Based on given environmental targets, such as a certain target value for greenhouse gas emissions, LCA can be used to calculate a specific technical target such as the weight of a component, the fuel consumption of a vehicle or the minimum amount of recycled content in a product. The transformation of pure LCA results into measurable target values, which can be understood by engineers, will clearly show the added value which LCA can give in terms of life cycle engineering. Even for very complex products with a huge variety of different materials and a complex value chain life cycle assessment can be performed with a reasonable time demand, with good quality and integrated efficiently into business processes.

6

REFERENCES

[1]

International Organization for Standardization (2006): ISO 14040: Environmental Management – Life Cycle Assessment – Principles and Framework, International Organization for Standardization, Geneva.

[2]

International Organization for Standardization (2006): ISO 14044: Environmental Management – Life Cycle Assessment – requirements and guidelines, International Organization for Standardization, Geneva.

[3]

Schweimer, G.W.; Schuckert, M. (1996): Sachbilanz eines Golf. In: VDI Bericht 1307 Ganzheitliche Betrachtungen im Automobilbau. Wolfsburg.

[4]

Schweimer, G.W. (1998): Life cycle inventory of 3-L Lupo. Volkswagen AG, Wolfsburg.

[5]

Schweimer, G.W.; Bambl, T.; Wolfram, H. (1999): Sachbilanz Seat Ibiza. Volkswagen AG, Wolfsburg.

[6]

Schweimer, G.W.; Levin, M. (2000): Life cycle inventory of Golf A4. Volkswagen AG, Wolfsburg.

[7]

Schweimer, G.W.; Roßberg, A. (2001): Sachbilanz Seat Leon. Volkswagen AG, Wolfsburg.

[8]

Rosenau-Tornow, D.; Buchholz, P.; Riemann, A.; Wagner, M. (2009): Assessing the long-term supply risks for mineral raw materials - a combined evaluation of past and future trends. In: Resources Policy 34, 161–175.

[9]

VW standard 91100 www.vwgroupsupply.com

[10] Koffler, C.; Krinke, S.; Schebek, L.; Buchgeister, J. (2007): Volkswagen slimLCI – a procedure for streamlined inventory modelling within Life Cycle Assessment (LCA) of vehicles. In: International Journal of Vehicle Design (Special Issue on Sustainable Mobility, Vehicle Design and Development), Olney: Inderscience Publishers.

Leveraging Manufacturing for a Sustainable Future David Dornfeld Laboratory for Manufacturing and Sustainability (LMAS), University of California, Berkeley, California

Abstract Manufacturing offers many opportunities for reducing environmental impact, utilizing resources more efficiently and, overall, greening the technology of production. These opportunities are most often related to process, machine or system improvements that impact only the operation of the process, machine or system. But, there is more potential in manufacturing enhancements to have a larger impact on the life cycle impact of the product the manufactured item is used in. This is referred to as “leveraging” and several examples of this are given, along with definitions of the fundamental terms. The potential for leveraging in manufacturing to have an impact on sustainable manufacturing and some future requirements are described. Keywords: Process; Machine; System Improvement; Life Cycle Impact; Make versus Use

1

INTRODUCTION

Manufacturing offers many opportunities for reducing environmental impact, utilizing resources more efficiently and, overall, greening the technology of production. These opportunities are most often related to process, machine or system improvements that impact only the operation of the process, machine or system. But, there is more potential in manufacturing enhancements to have a larger impact on the life cycle impact of the product the manufactured item is used in. This is referred to as “leveraging” and identifies manufacturing-based efficiencies in the product that are due to improved manufacturing capability but which, in the long run, have their biggest effects on the lifetime consumption of energy or other resources or environmental impacts. First, what is meant by the term “leveraging”? We understand a lever to be a device to increase mechanical advantage, as a bar used with a fulcrum to pry a heavy load allowing a larger load to be moved than with simple force alone. Leveraging is used as a transitive verb, usually in financial discussions such as [1]: “The use of credit or borrowed funds to improve one's speculative capacity and increase the rate of return from an investment.” The general idea is to employ resources in such a way as to insure a larger return on the effort (or in financial terms, money) than might otherwise be realized. How does this relate to manufacturing? And, in specific green manufacturing? This will depend on the component being manufactured by a machine or process and its eventual use in a product. This paper will first provide some definitions so that the use of terms like green manufacturing, sustainable manufacturing, etc. will be understood. Then, the concept of leveraging manufacturing will be explained and several examples of will be given of situations that provide leveraging along with some that do not. Finally, future directions in sustainable manufacturing driven by leveraging are suggested.

2 2.1

BACKGROUND AND TERMINOLOGY Green and sustainable

The familiar Brundtland Commission definition of sustainable development - “Sustainable development is development that meets the need of the present without compromising the ability of future generations to meet their own needs” [2] does not really speak to manufacturing but makes the key point that we need to at least “do no harm.” The US Department of Commerce defines sustainable manufacturing as “the creation of manufacturing products that use materials and processes that minimize negative environmental impacts, conserve energy and natural resources, are safe for employees, communities, and consumers and are economically sound” [3]. We define green manufacturing here as a first step towards sustainability. These first steps were proposed as green manufacturing “technology wedges” in [4] after a concept proposed by Pacala and Socolow [5] to address the big gap between the present trajectory and impact of CO2 on the atmosphere (business as usual – BAU) and a sustainable level – and how to close this gap in 50 years. They argued that, rather than trying to find one solution to correct this increasing mismatch between what is required and what is being done, we should concentrate on “technology wedges” – small advances and improvements that, when added up, have the effect of a large change. These wedges make a lot of sense in the context of manufacturing and sustainability. We can visualize sustainability as a relationship between consumption or impact as part of normal business practice compared to a “sustainable level.” For example, in California we store rainfall during the winter months as snow in the Sierra Nevada mountains. The amount of snow determines the amount of water we have to use in the next season for residential, commercial and agricultural use. If we use water at a rate that will exhaust the supply before the next rainfall – that is not a sustainable situation. We are using too much and should find a way to conserve or reduce usage. We could make the same argument for impact, for example, green house gas generation. The atmosphere has a

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_3, © Springer-Verlag Berlin Heidelberg 2011

17

18

Keynotes

certain capacity to accommodate green house gases. Exceeding that risks a build up that will endanger future generations according to the predictions of atmospheric scientists. We can illustrate this as seen in Figure 1 below, from [6]. The figure illustrates the normal trend of consumption or impact over time. A small reduction of either one results in a reduced rate of impact but does not provide enough change to achieve a sustainable situation. The application of technology wedges to, collectively, bridge the gap between present rate of consumption or impact and a sustainable level is illustrated with the green triangles. With sufficient wedges, the gap can be closed.



Pollution (air, water, land)



Ecological footprint - “fair share” - footprint



Exergy (available energy) or other thermodynamic measures

To be able to understand the effect of the improvement or change being measured, these can be represented in terms of a "return on investment" - for example, greenhouse gas return on investment (GROI). Other forms of return measure include: 

Energy payback time



Water (or materials, consumables) payback time



Carbon footprint



Efficiency improvement (for example, wrt exergy)

Then, a measure of the change in the T term of the impact équation can be determined. For green manufacturing these need to be linked to traditional design and manufacturing parameters. And they need to be assessed over all three scopes of ISO 14064 (1- direct emissions from on-site or company owned assets, 2- indirect emissions created on behalf of the company from energy generation or supply, 3- all others resulting from business operation including business travel, shipping of goods, resource extraction and product disposal). 2.3

Figure 1: Illustration of sustainable consumption and technology wedges, [6]. It is our role of manufacturing researchers to develop the wedge technologies. Individual wedges might be considered as “green” manufacturing steps. If there are sufficient greening steps we can achieve sustainable manufacturing. 2.2

Tracking progress

To insure that real progress is being made it is necessary to define metrics to measure change. Recall the “master equation” for impact attributed to John Holdren and Paul Ehrich [7]. This equation, sometimes referred to as IPAT, defines human impact (I) on the environment as the product of population (P), affluence (A, measured as GDP/capita), and technology (T, measured as impact per unit of GDP). Manufacturing has its impact on the T part of the equation – the impact per unit of technology. This is the impact per GDP of manufactured products. By reducing that impact, we start to “bend the curve” of the consumption or impact curve seen in Figure 1. The challenge is to come up with technology wedges that will reduce the T part of the équation at a rate sufficiently fast to offset population growth while at the same time make a dent in the impact that is already too high. Metrics are used by engineers for analyzing information and data to enable better decision making, including trade-offs among several alternatives, and for design. For green manufacturing these metrics could include: 

Global warming gas emission (e.g. CO2, methane CH4, N2O, chlorofluorocarbons, CFC’s) 

per capita



per GDP



per area/nation



Recyclability (or percent recycled)



Reuse of materials



Energy consumption

Leveraging

We can define two different classes of leveraging of manufacturing. The difference is due to the magnitude of the impact. That is, whether it impacts only the performance of the manufacturing process, machine or system or whether it impacts the performance of the product resulting from the application of the process, machine or system. An additional distinction must be made for products used in manufacturing – for example, machine tools. In the case of an improvement, say in energy consumption of a process, we would require that, at minimum, the “cost” of the improvement (in embedded energy, carbon footprint, etc.) would be more than offset but the reduction in energy consumption or carbon footprint in operation of the “improved” process. This is the basic definition of energy payback or green house gas return on investment. The magnitude of the impact reduction can be measured simply by knowing the number of manufactured products coming from the process over the life time of the process. This is a minimum amount of leveraging for any contemplated process improvement to insure that we are making progress. A second, more impressive, leveraging is due to process (or machine or system) improvements that have an inordinately high ability to reduce the impact of the product of the manufacturing operation (or machine or system) over the lifetime of the product use. The original process improvement may not have been made as part of a greening analysis of the process but is due to the introduction of new technology, machine capability or materials. It is this second type of leveraging that is likely to have the greatest potential for reducing the T term in the impact equation – making a larger than normal reduction in the product impact/GDP during the product’s life time. Why this distinction is important is discussed in the next section. 3 3.1

WHY LEVERAGING IS IMPORTANT Does manufacturing matter?

The base of this discussion is an assessment of whether or not manufacturing is a significant component of energy and resource consumption and the impact from this consumption, and, then, whether or not changes in manufacturing can really help overall. A review of all the data, pie charts and discussions about how much

Keynotes of the world’s energy use is attributed to manufacturing is not presented here.

19 consumption, and that is worth another 20%. Now we are down to .8% (20% of 4%).

Allwood et al [8] point out that industrial carbon emissions are predominately due to production of goods in steel, cement, plastic, paper, and aluminum. With the demand for these materials expected to double at least by 2050, during which the global carbon emissions are desired to be reduced by at least 50%, simply improving process efficiency will fall far short. Allwood suggests several strategies for industrial emissions reduction in addition to process efficiency, increased recycling, and carbon sequestration and storage, as: (1) reducing demand for materials; (2) nondestructive recycling; and (3) radical process innovations which allow shorter, less energy intensive process routes to yield the completed component. These all address the T term in the IPAT equation. But, for “general product manufacturing” is there enough that can be accomplished by manufacturing improvement? Specially if we apply this to what many of use consider our core process capabilities – like machining? 3.2

Figure 2: Primary energy consumption for VW Golf manufacture [9].

Automobile manufacturing example

If we think about where the major energy consumption associated with a product occurs we can divide the space up into two regions – manufacturing and use. We see that "things that don't move or need power to operate" like bridges, furniture, etc. are dominantly manufacturing phase consumers of resources and, by extension, impact. Things that do "move and need power to operate" like automobiles, airplanes, buildings, etc. are use phase heavy. Interesting to note are the items that are close to the break-even (imagine a 45 degree line on a plot of use vs manufacturing impact graph for products). So, what about automobiles? At a presentation at the ICMC Conference in Chemnitz in September 2010 by a representative of the automaker VW, the speaker mentioned that, by their analysis, about 20% of the impact of a typical VW Golf A4 car came from manufacturing while 80% was due to the use phase. One can find data on the GolfA3 (marketed from 1991-1999, also called the Polo) from some time ago and the comparison was similar. Figure 2, from [9], shows the energy consumption during the manufacturing phase of the GolfA3 in Gj/auto. Materials and part suppliers account for much of the embedded energy in the manufacturing phase. Machined components, such as the gear box and engine are a small percentage of the total (accounting for about 10% overall or about 25% with materials and parts from suppliers included). If one looks at the impact of the auto, including car production, fuel production and use phase, Figure 3 from [9], it is clear that the fuel production and consumption in the use phase dominates all categories of emissions to air and water with the exception of dust generated by material production and casting of some components and painting of the vehicle and biological oxygen demand impacts on water. Looking a bit closer at the data above, does this make sense in terms of reducing the impact/GDP? If we focus only on the manufacturing phase we may not be encouraged - specially if the predominant impact is in the use phase. Consider the VW Golf example of 20% manufacturing phase impact versus 80% use phase impact. If we think about the areas many in our community work in a lot, machining, and we assume about 20% of the manufacturing is machining or machining related, that gives us a potential for improvement of 20% of 20% or only 4% (and then only if we get rid of all machining!). Let's assume that some of the better technology for improving machining efficiency is employed, say some specialty tooling material that reduces machining power

Figure 3: Use vs manufacturing phase impacts for VW Golf [9]. One could argue that this is hardly worth the effort it would seem. Of course, if you are paying the electricity bill for the factory and this 8% technology wedge is added to a lot of others in machine operation it can add up to real savings. But, still not impressive compared to use phase impacts. That is, impact over the full life cycle of the auto. More recent data from Volkswagen for the Golf A4 indicates that some improvements have been made (for example reduction of primary energy used in production, use and end of life due primarily to improved fuel consumption (a 20% improvement from 8.1 liter of fuel/100 km to 6.5 l/100 km for the gasoline engine) [10]. 3.3

Accounting for more of manufacturing’s impact

The question is, then, what is the true leverage effect of manufacturing on the life cycle impact of a consumer product – one that has its dominant impact in the use phase rather than the manufacturing phase? If we are speaking of a manufacturing machinery builder, like a machine tool company, then we can argue that the machine tool has its largest impact in the use phase so that improvements in energy efficiency of the machine will been seen over its life [11] since it is the “product.” The thesis here is simple. If improvements in manufacturing yield a substantial reduction in the life cycle impact of a product, should not manufacturing get some of the “credit” for this improvement. And, by similar reasoning, can we claim this as a part of “green manufacturing” contribution towards sustainability since it is a major element in reducing the technology impact of the product – the T term in the IPAT equation? The next section gives some examples of this leveraging effect.

20 4 4.1

Keynotes EXAMPLES OF LEVERAGING Basic influences

Manufacturing has a number of fundamental effects on a product. In no particular order, manufacturing can: 

guarantee a certain level of precision or accuracy of the produced component



allow the use of advanced materials (enhance strength to weight, improved surfaces, wear resistance, thermal stability, etc.)



allow reductions in process steps or sequences



combine processes for enhanced effects as in hybrid processes or mill-turn machine tools



achieve complex shapes or features to improve performance



and so on

reduction of almost 2.5 kg/km CO2. And this is over the life of the aircraft – many millions of kilometers. The next example relates to a similar impact on product use for an automobile. It is also due to enhancement in manufacturing capability due to precision manufacturing. The improvement for the Boeing aircraft example was based on tightened tolerances allowing increased structural performance by better control on dimensions - resulting in lower weight components. Looking at improvements in engine performance for automobiles we can see similar improvements. The performance (power density in kW/l) of diesel passenger car engines is shown in the graph in Figure 4 from [15]. With better tolerances, better

There are more but you can get the idea. How these manufacturing induced effects influence the life-cycle performance of the product must be clearly understood to explain the full potential of leveraging. This influence usually comes from the extension of one of the above listed effects onto the energy consumption or “environmental performance” of the product the manufactured components are used in. A simple example might be a spindle motor for a machine tool. If the production technique for the motor, using advanced magnetic materials, allows the construction of a motor that extracts more useful work from the energy supplied to it, then the manufacturing effect is leveraged over the life of the spindle. Alternatively, if the improvement in energy consumption is due to controller related performance enhancement, as the 40% reduction in energy consumption illustrated by Mori Seiki due to overall system component improvements and optimum acceleration of spindle and servo motor during machining [12], this is not due to manufacturing leveraging but, certainly, improves the life cycle impact of the machine tool – the product in this case. 4.2

Leveraging examples

Two examples are presented here that illustrate the concept of leveraging manufacturing with life cycle impacts on the product that the manufactured component(s) is (are) used in. And the life cycle impact is substantial and most of the benefits are due to manufacturing. Both of these examples relate to improved machining tolerances and their impact on product performance. On an aircraft airframe (a large one like a B747 or the A380) savings in weight correspond directly to savings in fuel. And many other aspects of an aircraft scale with weight. This is, to some extent, true also for an automobile. That is the second example If the machining process for large airframe components is under control and precision manufacturing principles applied, a reduction in machining tolerances from approximately +/- 150 microns to +/100 microns on the features of the airframe can account for a weight reduction of 4500 kg/aircraft and substantial fuel savings (8%) [13]. This allows an increase of 10% in passenger load (the engines don't need to carry as much plane), or increase in cargo payload and a substantial reduction in manufacturing cost of the aircraft (less material and improved assembly) and the accompanying reduction in scrap. And less fuel consumption means reduced CO2 impact from aircraft operation. The accumulated savings over the life of the aircraft are incredible. The fuel consumption per km is estimated as 11.88 L/km (or about 5 gallon per mile). Thus, the CO2 emission rate can be estimated at 30.64 kg/km [14]. A reduction in fuel consumption of 8% results in a

Figure 4: Change in power density over time for Diesel engines [15]. surface finishes, better control of orifice size and shape on the fuel injector nozzles (with diameters on the order of 60 microns), tighter control on cooling channels and fluid flow in the engine due to enhanced casting techniques, and so forth, the engine (still working on the same old Diesel principles) performs dramatically better. The "dog leg" in the chart above corresponds to the introduction of high performance, precision, manufacturing to the power train manufacturing in the automobile. In the years since 2000, the power density has been improved by double (in 2007) and anticipated to quadruple by 2020, Similar improvements can be seen in the transmission as well. And, with advanced sheet metai forming technologies (another manufacturing technology enhancement) and replacement of metal components with non-metallics (manufacturing and materials enhancement) more improvements would be anticipated. This is not to suggest that precision technologies had not been employed before. But, the engine and associated fuel injectors, etc. were designed to take advantage of increasing manufacturing performance and, as a result, yielded tremendous product performance as well. And that is how to reduce the technology impact per GDP. Manufacturing dramatically increased the efficiency of fuel utilization in the internal combustion engine. The small percentage of manufacturing phase improvement has a giant leverage effect on use phase impact. Since the principal element in use phase impact of the automobile, the reduction in consumption (due to increased power density of the engine), hits both the fuel production impact as well as the fuel consumption impact there is additional impact. In the Golf A3 data for emissions, Figure 3, 90% of the CO2 impact was due to the use phase (81% from driving and 9 % from fuel production). A doubling of the fuel economy, by manufacturing induced engine efficiency

Keynotes

21

improvements, by precision machining and processing will essentially halve that (same distance driven) - or account for, in the case of the Golf A3, a reduction of some 16 tons of CO2. And if, in the process of manufacturing enhancement, we save most of our 4% impact from machining, that's .4 ton of CO2. So, for our .4 ton we get a return of 16 tons (a factor of 40!).

7

4.3

REFERENCES

[1]

http://www.thefreedictionary.com/leveraging, 1/16/2011.

[2]

Brundtland Commission, i.e. World Commission Environment and Development (WCED) (1983).

[3]

http://www.trade.gov/competitiveness/sustainablemanufa cturing/how_doc_defines_SM.asp; accessed June 21, 2010.

[4]

Dornfeld, D. and Wright, P., (2007): “Technology Wedges for Implementing Green Manufacturing”, NAMRI Trans., 35, pp. 193-200.

[5]

Pacala, S. and Socolow, R., (2004): “Stabilization Wedges: Solving the Climate Problem for the Next 50 Years with Current Technologies,” Science 13 August 2004: Vol. 305. no. 5686, pp. 968 – 972.

A second issue is whether or not manufacturing can rightfully claim credit for any or all of these improvements under leveraging. Traditional design textbooks outline the design process in stages with clever designs being turned into real products through manufacturing. So, for sure, the role of manufacturing as a design enabler is undisputed. In that case, we can claim the benefits of leveraging manufacturing as well.

[6]

Dornfeld, D., (2010): “Sustainable Manufacturing – Greening Processes, Systems and Products,” Proc. ICMC Sustainable Production for Resource Efficiency and Ecomobility, Fraunhofer Institute for Machine Tools and Forming Technology, Chemnitz University of Technology, Chemnitz, September, 2010.

[7]

Ehrlich, P. R. and Holdren, J. P. (1971): Impact of population growth, Science, 171, 1212-1217.

5

[8]

Allwood, J., Cullen, J., and Milford, R. (2010): “Options for Achieving a 50% Cut in Industrial Carbon Emissions by 2050,” Environ. Sci. Technol., 44 (6), pp 1888–1894.

[9]

Volkswagen AG, and Harald Florin, PE Europe/IKP-University of Stuttgart, Germany from a presentation of A. Horvath, UCBerkeley, 1995.

The fine print

There are constraints of course. The technology enhancement (the “wedge”) needed to improve precision of the machine tool to enable some of the product performance increases may not be strictly “green” (meaning there is a cost in terms of embedded energy, energy/unit product, or other measure). Trends in machine and process design are showing that one can enhance the performance of the manufacturing process and also realize reduced impacts. Recall the Mori Seiki example cited earlier. But, this needs to be carefully accounted for.

SUMMARY

This paper has proposed a view of the potential for manufacturing to play a more significant role in reducing the environmental impact of technology. The manufacturing capabilities that yield aircraft or automobile engines with dramatically reduced fuel consumption, or structural components for aircraft that allow higher payloads per unit of aircraft structure, or advanced processes that yield lower power electronics for reduced energy consumption, and so on, are examples of leveraging manufacturing. We cannot claim all benefits in product performance stem from manufacturing. An enhanced wash cycle on a home laundry that reduces water and energy consumption has likely very little to do with manufacturing technology improvements. But we should stand up for those manufacturing driven improvements that, on their own, are responsible for substantial environmental impact reductions. The challenge raised by researchers, like Allwood, pointing out the fundamental changes needed in production technologies (specially for materials processing and efficient material use) must be complimented by the tremendous potential for leveraged manufacturing. It points out, at least, the significant role that manufacturing (broadly defined and over all processes and systems) can play in creating a sustainable future. Finally, we need some numbers! The arguments presented here are based substantially on empirical observations. A more careful analysis of the tradeoffs of competing technologies with respect to potential leveraging effects must be done for several case studies. That is on the agenda for our future work. 6

ACKNOWLEDGMENTS

The author acknowledges the researchers and affiliates of the Laboratory for Manufacturing and Automation (LMAS) and partners in the Sustainable Manufacturing Partnership (SMP) for their helpful discussions and support of this research. For more information see lmas.berkeley.edu and smp.berkeley.edu.

accessed on

[10] Schweimer, G., and Levin, M., “Life Cycle Inventory for the Golf A4” posted on line at www.volkswagenag.com/.../Golf_A4__Life_Cycle_Invento ry.../golfa4_ english.pdf; accessed 1/18/11. [11] Diaz, N., Choi, S., Helu, M., Chen, Y., Jayanathan, S., Yasui, Y., Kong, D., Pavanaskar, S., and Dornfeld, D. (2010): “Machine Tool Design and Operation Strategies for Green Manufacturing,” Proc. 4th CIRP International Conference on High Performance Cutting, Gifu, Japan. [12]

Mori, M. (2010): “Power consumption reduction of machine Tools,” présentation at 2010 CIRP General Assembly CWGEREE, August, Pisa.

[13] Thompson, D. (1995): presentation at Symposium on Research Issues in Precision Manufacturing, Univ. of California, Berkeley, September, 1995. [14]

http://micpohling.wordpress.com/2007/05/08/math-howmuch-co2-released-by-aeroplane/; accessed 1/18/11.

[15]

Berger, K. (2005): Daimler, Presentation at CIRP January 2005 Meeting, WG on Burr Formation, Paris.

Sustainability Engineering by Product-Service Systems Günther Seliger Department of Machine Tools and Factory Management, Chair of Assembly and Factory Management, Technische Universität Berlin, Berlin, Germany

Abstract Product-Service Systems offer high potentials for increasing the use productivity of resources. Functionality can be provided in specification how, on place where and in time when needed for the user by modern communication and logistics. Business models change from selling products to selling functionality due to fixed costs of under utilized products being higher than additional costs for communication on demand and supply, and for transport of artifacts to places of performance. Remanufacturing, disassembly and reassembly enables for same products and components performing as required in consecutive different usage phases thus avoiding disposal of valuable resources. Methods for product design with respective components, performance supervision, maintenance of components, configuration for different usage specifications, user’s and provider’s qualification, ubiquitous access on information about demand and supply to create efficient functionality markets, all represent product related services for the functionality business thus achieving more functionality with fewer resources. Keywords: Sustainability Engineering; Value Creation; Product-Service Systems

1

INTRODUCTION

Sustainability Engineering is on exploiting the dynamics of fair competition to achieve the required sustainability of our global living conditions by processes of knowledge creation and innovation. Product-Service Systems (PSS) exploit design potentials for new business models by shaping interrelations between tangible products and intangible services. They enable for innovative function, availability and result oriented business models. These models can help in reducing resource consumption and waste generation by fewer resources providing more functionality. Supplier’s motivation is changed from selling ever higher numbers of products to the customer with ever lower costs of manufacturing to selling ever more functionality to the customer with ever lower input of resources. The old manufacturing paradigm of producing big lot sizes for low costs per piece is challenged by providing more functionality with fewer resources. Tangible resources are partly substituted and partly supplemented by intangible services. Sustainability in its three dimensions of economic, environmental and social concern helps in directing the processes of technological innovation. Economic challenge is in market competitivity of resource saving product service design. Environmental challenge is in resource efficiency and effectiveness, e.g. no longer disposing non renewable resources by consequent adaptation for consecutive different usage phases, also in substituting non renewable by renewable resources within the constraints of sufficient renewable resource generation. Social challenge is in establishing the awareness of users and developers for mankind’s threat if not adapting ways of living to fair wealth distribution within environmental constraints. How can PSS contribute to meet the challenge of sustainability by competitive offers of minimal necessary tangible products integrated with required service functionality? The threat of ignoring the conflict potentials of unequal global wealth distribution, the saving potentials in resource exploitation for useful applications is illustrated. Chances of PSS approaches for exploiting these potentials are described.

2

CHALLENGES OF SUSTAINABILITY

Predominantly all over the world industries are still working in source-sink economic patterns relying on resource availability without limitations. Non renewable resources are often exploited for only one usage phase with consecutive disposal. However, there are huge potentials of recycling of products, components and materials. Also, substituting non renewable by renewable resources within their limits of regeneration can help avoiding upcoming shortages in resource supply for a growing population with expectations on higher standards of living. Earth’s resources are limited. Out of the present global population of about 6.7 billion people -9.5 billion are prognosed for 2050-, less than one billion belong to the industrialized world in Europe, North America, Japan, South Korea, Australia, and few islands of wealth. China with its population of 1.3 billion and India with 1.1 as well as other developing and emerging countries are striving to catch up. If the lifestyles of the upcoming nations are shaped by the existing, predominating technologies, then the resource consumption will exceed every accountable economic, environmental and social bound. The question arises, which production technologies can serve as basis for dealing with this growth, in an economically, environmentally and socially responsible manner. Independent of the exact limits of access to virgin non-renewable resources, alone due to the increasing material demands of more people with increasing standards of living, non-renewable resources worn out after usage phases of products must not be disposed any more but regained in product or material cycles. Due to limited availability and increasing demand an increasing increase in prices for non renewable resources as aluminum, copper and iron can be observed. Between 2006 and 2009 the costs for import of raw materials to Germany have grown from 31 to 86 billion Euros, including 16 billion Euros for metals. The price for copper e.g. increased from 3300 Dollars per ton in the beginning of 2009 to 6000 Dollars per ton in August 2010, an increase to 10,000 Dollars per ton is expected for 2011. Expanding application areas

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_4, © Springer-Verlag Berlin Heidelberg 2011

22

Keynotes for copper are expected in electrical vehicles and infrastructure for electrical energy supply. Rare earth materials are required for luminous diodes, batteries and photovoltaics, all areas with expected market growth in applications but limitations in raw material purchase. Recycled material becomes the only source of raw material available in the long term [1]. Already 56 percent of copper applied for manufacturing in Germany has been recycled. Keeping ownership on materials to avoid consequences of fluctuating prices for a stable functionality business might be a competitive approach for innovative PSS. Energy availability is a fundamental premise for any material wealth creation. Nearly one third of primary resources for global energy conversion presently stems from crude oil. Estimates on remaining reserves lie between 1000 and 3000 billion barrels. The date of peak-oil, i.e. the date from when on oil production remains constant or even decreases, is expected for 2020 at latest. Obviously saving primary resources for energy consumption in global dimensions is a huge challenge in responsible management of resources. The amount of primary resources for energy consumption worldwide has increased from 2000 to 2008 by 25% to over 500 EJ 18 15 (EJ = 10 Joule) or over 140 PWh (Peta Watt hour = 10 Wh). Germany with 80 million people accounting for one percent of the world's population of 6.7 billion consumes energy of 14 EJ or 4 PWh accounting for about three percent of world consumption. Crude oil with 30%, natural gas with almost 20% and coal with 25% have taken about three quarters of primary resource contribution for energy consumption and caused CO2 emissions of nearly 30 Gt 9 (10 t). Biomass with over 10%, nuclear with 6% and renewable energy are contributing another quarter of world primary resources for energy consumption [2] [3]. Figure 1 shows a gross quantitative assessment of the global energy flow without losses in transformation from primary resources to useful applications. Passenger and goods transport each account for one eighth of consumption in final application, industrial production for one third, and two fifth are for infrastructure with substantial proportions for building, heating and food production. Between primary resource input and final consumption, there are many different processes and production facilities. The key elements of this transformation are the direct fuel use in machinery and equipment with approximately three fifths and electrical generation with two fifth shares. The movement of vehicles and machinery is generated with about one third, and process heat with about half of primary energy use. The consecutive steps and different paths in conversion of primary resources to energy driven operations offer big potentials for

23 increasing efficiency and effectiveness. Often these potentials are already baled out within the balance frame of respective entrepreneurial institutional activities. By integrated product and service innovation PSS independently from traditional balance frames can create new business models of providing more functionality in application by less investment in instrumental facilities. E.g. providing customers with energy saving equipment thus saving electricity consumption can be cheaper than investing in additional power stations. Diesel engines directly driven by fuel might save conversion losses of electrical power generation required for electrical drives. Overcoming grown thinking, living and working habits requires new means of convincing people by teaching and learning, by softly integrating innovative artefacts in existing living environments. Mutual dependencies of tangible products and intangible services must be thoroughly considered for successful implementation [4]. The ecological footprint represents a measure for the consumption of renewable resources. About one quarter of earth’s surface, accounting for 11.3 billion hectares, can be considered as biologically productive area contributing to the regeneration of resources. The average amount of biocapacity per capita on earth is calculated by dividing the productive area by the number of people on earth, what results in 1.8 global hectares biocapacity per capita. Since approximately 1985, resource consumption on a global level is higher than the ecological capacity. For 2050, an impossible biocapacity of two globes would be required if the trend of increasing renewable resource consumption would be not stopped. Half of global population is still living without access on electricity and telecommunication, earning less than two Dollars per day. One fifth of global population disposes of four fifths of global wealth. Environmental damages caused by unbalanced resource exploitation and considerable lacks in human education lead to social conflicts and terror. Presently there are 25 local wars on the earth. Culture and education for billions of people have become the dominant social challenge for human survival on earth. PSS approach seems to be promising means to cope with this challenge. Also the global population growth must be stopped by better standards of living without increasing resource consumption. Social stability can only be achieved if mankind is able to create jobs and living conditions of human dignity worldwide and not only in the technologically developed regions of East Asia, North America and Western Europe. Rapid technological development, diversity, creativity, entrepreneurship and dynamism in competition and cooperation

Figure 1: Quantitative assessment of global energy conversion in primary resource shares without losses in transformation.

24

Keynotes

shape the living environments for the global citizens from the regions of prosperity, but also bring an irresponsible waste of resources. The responsibility of the wealthy minority enables for technological development based on criteria of sustainability in order to harmonize the quality of life and resource use. This challenge offers with great opportunities in sustainable services, products and processes for value creation. Sustainable development with social innovation is also important to open the hungry market of more than 5 billion people who still have not enough purchasing power.

sustainability. Referring to requirements of communication, to training and educaton, to maintenance and repair, to knowledge creation and information access for continuous improvement, to setting up competitive offers for resource saving functionality markets, PSS can considerably contribute to sustainable value creation.

Due to the unbalanced development along developed, emerging and developing countries, it is difficult to reach a new agreement after Kyoto Protocol to reduce the carbon emission. Carbon emission relates with the economic development and environmental protection. Governments are conflicting about individual national wealth development, access on resources and responsibility for climate change. But all of them are concerned about how to reduce the CO2 emissions to protect the environment. The rationally required sustainable global development can stimulate the forces of human initiative and creativity. Sustainable global development could eliminate the unfair distribution of opportunities by technological and social innovation [5]. Mankind’s wealthy minority has the responsibility to identify innovative paths for sustainability engineering. Great opportunities are opened in sustainable services, products and processes for value creation. Social innovation can help to open the new markets of more than 5 billion people. Technologies from developed and emerging countries can empower help for the poor people to help themselves. Product-Service Systems (PSS) offer chances to fulfill the challenge of sustainable development. The potentials of PSS in resource saving and qualification may succeed to develop economies and civilization in the global discourse. 3

VALUE CREATION

Value creation can be modelled considering both, actual entrepreneurial activities in globalized markets and requirements of sustainable development. Market dynamics can be powerful drivers in achieving sustainable develoment for global mankind along economical, evironmental and social criteria by technological innovation. Figure 2 describes an architecture for sustainable global value creation. Value creation factors are integrated in modules to be designed along economic, environmental and social criteria of sustainability. Cooperation and competition among entrepreneurs drive for horizontally and vertically integrating modules thus constituting value creating networks. There are different levels of hierarchy in value creation. From manufacturing tool and operation via value creating cells and systems, whole factories to national and international entrepreneurial conglomerates or knowledge generating educational communities. Each of them from top-down pespective is considered as a network consisting of modules and from a bottom-up perspective as a module together with other modules contributing to a network. Modules or networks can be set up under different infrastructural conditions in industrialized, emerging or developing countries respectively regions within countries. Value creation in an engineering perspective addresses the development of artefacts for useful applications thus shaping areas of human living. From the module view in a bottom-up perspective entrepreneurs try to get their specific value contribution integrated in higher level networks, whereas, from the network view in a top-down perspective entrepreneurs try to purchase original elements enriching their product system from lower level modules. The dynamics of demand and supply in this mutual dependency offers chances for directing global value creation to pathes of

Figure 2 : Architecture of Sustainable Value Creation.

4 4.1

POTENTIALS OF PRODUCT-SERVICE SYSTEMS Business Model

Product-Service Systems (PSS) are an integrated product and service offering that delivers values in industrial applications. PSS must be understood as a new product consisting of integrated product and service shares, which comprises the integrated and mutually determined planning, development, provision and use. PSS includes the dynamic adoption of changing customer demands and provider abilities. The partial substitution of product and service shares over the lifecycle is possible. There are different models for PSS, the individual business models can be differentiated by further criteria [6]. They differ in the responsibility of production result, personnel, service initiative and finally the ownership of the products, e.g. machine tools. This means the provider takes over responsibilities in the production process by delivering service personal, initiating services and ensuring the production quality, see Figure 3.

Figure 3: Specification of innovative use models [6].

Keynotes

25

A competitive provider offers product functionality, availability or a result in quality, time and location as required by the user. Multiple usage phases make a PSS competitive by maximizing the utilization of resources and can be achieved by disassembly, component adaptation, and reassembly. The opportunity to optimize the use phase is the key for success in consequence of more freedom of business and engineering development. The PSS business model takes as its starting point the goal of achieving an integrated functional solution to meet client demands, moves away from phase based servicing and discrete resource optimization, to system resource optimization which is utility based. The resulting PSS can produce synergies in profit, competitiveness and environmental benefits. The potential eco-efficiency of a PSS relies on system optimization in resource use and emissions because of the stakeholders’ convergence of interests [7]. Further PSS enables an equipartition for the use of technology. It allows the adoption of the right technology and a competitive production also for low-budget small medium enterprises (SMEs) and emerging countries at the time, place and in the specification which is needed. PSS can lead to reduced resource use and waste generation. The increase in sales of services can balance reductions in sold products. Employment lost in manufacturing can be balanced by jobs created in services. As a business concept, PSS have the potential to improve access to technology worldwide. With PSS, consumers worldwide would have less need to buy, maintain, dispose of, and eventually replace a product. In fact, the quality of the service, and thus consumer satisfaction, may improve with PSS because the service provider has the incentive to use and maintain equipment properly, increasing both efficiency and effectiveness. The incentive also exists for producers to design closed-loop systems for equipment based on designs for higher durability and recyclability [7]. To be competitive on the market the PSS providers have a strong interest in using a minimum of production resources, which means maximum utilization and usage of products and components. Therefore a provider will use production equipment out of a PSS in a new or other PSS. Resources will have several life cycles. This is possible because of the shift of the ownership in PSS and leads to a cycle economy. Human beings in the phases of planning, development and delivery of PSS play a major role; especially the human-machine interaction in the phase of delivery is in the focus. Different qualification of technicians and company-spanning cooperation in the field of industry demand a specific support concept during the delivery of services. Figure 4 addresses the economical, environmental and social motivation and technical progress, being sustainability contributions of PSS.

Figure 4: Contribution on Sustainability by PSS.

In developed countries, which already have a large environmental footprint arising from a high rate of per capita resource consumption, PSS can facilitate the transition toward a more service-oriented, sustainable society. The service industry gets the chance to find new and increasing market opportunities. Other benefits include reduced dependance on externally produced resources and reduced load on waste disposal facilities. For emerging countries, PSS may represent a more promising and environmentally sound path to economic development since it enables them to bypass the development stage characterized by individual ownership of goods. A cycle economy is not only environmentally reasonable but also a chance for new businesses. Selling functionality instead of selling products is advantageous once additional costs for information processing and logistics are less than costs for underutilized capacity (Figure 5).

Figure 5: Selling functionality instead of selling products. From the point of qualification the use of technology is limited. Especially in developing countries the qualification level of worker and technicians is not comparable to the one in the developed world. However, the provider has to take care that his products are usable, as promised in the contract. The challenge is to qualify the local worker and technician from the customer or contractors and supervise their work from distance. 4.2

Knowledge Management

The close co-operation with suppliers and service producers as well as with final consumers can cope with these gaps. While relationships with suppliers are addressed by ISO 14000-series standards and environmentally conscious purchasing practices, downstream practices are addressed by extended producer responsibilities and Product Stewardship concepts. Integrated Chain Management (ICM) specifically addresses the issue of involving several actors in order to improve the environmental performance of products. However, problems associated with ICM are also going to be relevant for PSS due to a similar value chain basis that is extended in PSS into a value creation network. These problems include trade-offs between co-operation and internal environmental management; the problem of choosing wrong actors who do not have the power or knowledge to change or influence events; information sharing and transparency, and barriers from material flows crossing borders and a variety of regulatory frameworks in different countries. By sharing information the provider will be enabled to identify the customer needs and enhance his business relation with new features satisfying the customer needs. By this a long relationship can be established, which has to be seen as a partnership. Due to the shift in the ownership of products PSS business models give a platform to collect information from every PSS which earlier

26

Keynotes

was only accessible for the customer or by feedbacks of service personnel. This offers providers opportunities to learn more about the PSS behavior and usage by the customer and give the chance to use it for PSS design or redesign. Knowledge generation as well as knowledge and information management is necessary. A definition of knowledge is shown in Figure 6. The adaptation of products and services to the continuously changing technical requirements, application areas and user demands is crucial for the competitiveness of the PSS business model. Different configurations have profound impact on the performance of the system in terms of reliability and productivity, product quality, capacity scalability, and costs. Adapting the functions to the customer needs, the design to reduce idle and operation costs and an ongoing adjusting of service times requires knowledge about the system behavior and prognostics about the system conditions. This knowledge needs to be generated and managed.

system that supports the supply chain and communication processes in the whole PSS life cycle with knowledge. The VLCU acquires data from the usage phase, communicate and process it with the help of data mining algorithms to knowledge about the system behavior. This includes rules about the process flow of the PSS and its operations, as well as prognoses and classification of the PSS health condition or its components [6]. The processing to knowledge can be done by using data mining algorithm. These algorithms can be used to formulate rules about the PSS system behavior, e.g. a decision tree model. Other algorithms like Support Vector Machines or Statistical Pattern Recognition can be used for condition prognostics based on the actual system condition and wear [9]. In this concept the generated knowledge is available for all actors in the PSS supply chain. Beside the VLCU concept there are product accompanying information systems, supervising the product or components condition and allow condition based maintaining [6][5]. This is crucial for a PSS as it also facilitates to reduce unseen breakdowns and so a breach of contract, e.g. the promised availability. 4.3

Figure 6 : Definition of knowledge by North [8]. The development of PSS has the challenge to handle the increased complexity of the integrated PSS products and services. To ensure an efficient development of a PSS and to provide decision support, knowledge out of the usage phase or experience from previous developments and PSS provision phases should be used. To support a competitive design of PSS, knowledge needs to be generated about correlations between product and service shares in order to fulfill the required needs and demands. This knowledge is crucial for a successful combination of product and service shares, whose influences are very complex and not always known. The PSS life cycle data, especially from the operation phase, is the source to discover this knowledge.

Performance Supervision and Maintenance

In the PSS of aircraft turbines there is a continuous condition supervision to ensure the availability, but also to schedule maintenance planning at the place and the time it is needed. Data from the engine in use are transmitted to the provider. Input factors are planned future running times and available parts on the following destinations of the engine, respective aircraft. While in earlier times the engine was owned by the airline, spare parts and technicians needed to be stationed on every airport from every airline. Nowadays costs could be reduced by having just one team and depot for every airport. An aircraft engine is a very complex machine, the knowledge about it is best on the side of the engine company, e.g. Rolls Ryoce, GE or Pratt&Whitney. Those decide best when wear parts need to be replaced and because of the PSS business model they run today, they maximize use by condition based maintenance (CBM) methods or multiple usage phases, e.g. by running the engine on different aircrafts. Figure 7 shows the typical parameters measured for engine health management on a Rolls Royce Trent Engine. Aircraft Communications Addressing and Reporting System (ACARS) digital data-link systems are used as the primary method of communication. This transmits the Aircraft Condition Monitoring System (ACMS) reports via a VHF radio or satellite link whilst the aircraft is in-flight. A worldwide ground network transfers this data to the intended destination [10].

Due to the modern IT based engineering, business communication and documentation, most data along the life cycle of a PSS are already available in digital form and worldwide accessible via internet, e.g. machine datasheets, service protocols or personal database. Companies offering machine services already document plenty of detailed data about the service processes. Currently this is being used as an information base to compare new situations with historical data. The challenge lies in accessing, acquiring, communicating and finally processing it to knowledge. The continuous supervision of products and processes as well as processing of data by intelligent algorithms is an enabler to do prognostics of the system condition. Following the Business Intelligence idea an integrated approach for all participations or companies in a supply chain network of a PSS is required. An integrated concept has been developed – the so called Virtual Life Cycle Unit (VLCU). It is an information technology

Figure 7: Engine health management sensors RR Trent Engine [11].

Keynotes 4.4

27

Education

The PSS connect the providers and customers in multifaceted work places at which people determine during their operations the sustainable impact of products and processes. Worker or technicians need knowledge to have the ability in an application do something within the required time and quality. The integrated form of services in the PSS business model also includes the humans. To get access to technology the worker or technicians need to be qualified to do this. Constant availability, different qualifications of users and company-spanning cooperation in the field of industry demand a specific support concept during the delivery of services. Therefore easy and online education systems are required. In order to cope the challenge on qualification the use of modern IT systems offer great solution potentials. One way is the support of less and insufficiently qualified users. As a part of a support concept, e.g. in a maintenance scenario, the creation of a “shared vision” can be a possibility for the diagnosis and solving of a problem (Figure 8).

generate stimuli in people of different age, cultural background and qualification to activate interest and therewith initiate a learning cycle. The state-of-the-art of information and communication technologies (ICT) offers further innovative teaching concepts. By supervising the workers action and give direct instructions to him. So called Teachtools are enablers to incorporate physical and with technical information means to coach and train skills in technological, social, environmental and managerial fields. The learning motivation is addressed and creative competencies are fostered through practical application and project oriented problem solving at the workplace. This environment is ideal for forms of action-orientedand discovery-learning, which guide the learner through a selfdefined learning process. The learner on his learning path meets different kinds of teaching objects, like pictures, drawings, movies or texts. The teachtool suggests learning objects and the learner chooses which teaching objects suites his interest best. His journey will provide him with additional information for a more sustainable design and usage of the products and processes which he is working with. The learning processes can take place in all kinds of value creating activities done in a manual workplace, for example assembly, agriculture or teaching workplaces. The regional infrastructure, education level and values of various participants are to be hereby observed, in order to indentify deficiencies in the qualification of persons. A variety of best fitting teaching material or objects can be identified, which raises the chance that the learning processes will be performed at a high level of efficiency. Web-based intelligent agents are used to identify the qualification gap of the people and to support the learner with the appropriate teaching contents and highly effective methods. In [12] such a teachtool has been presented. An image based recognition of manual work processes in combination with an expert system has been developed and verified, see Figure 9.

Figure 8: Shared Vision System [5]. During the production of a work piece the machine informs the user about a breakdown. After a detailed inspection the user realizes, that her/his qualification for the removal of the failure is insufficient. To minimize downtimes of the machine, expensive journeys of service staff and last but not least mistakes in the problem diagnosis, the user can establish an audio-visual contact to a remote service expert of the machine manufacturer by a sharedvision system. Now this service expert can analyze the problem in time. Furthermore he can guide the user to a solution of the problem. As the gaze direction shows the focus of attention the visualization of the gaze direction of both involved persons can enhance the communication. Perceiving the mutual gaze movement therefore means an additional intuitive source of information. To ensure the quality of e.g. a service, the technician might have to be supervised in a way, that his actions are documented and in case of a mistake he/she immediately be informed. This can be done under the umbrella of technician security, but of course also to ensure the quality, economically and resource consumption of the PSS. A wrong installed ball-bearing might wear faster, which means it results in higher lifetime costs because of higher resource consumption. This is not sustainable in economic and environmental way. Novel tools for education and innovation dissemination guide people during their work to reflect their operations, to gain knowledge and to generate and adopt innovative ideas. They

Figure 9: Image-based recognition of a manual work process [12]. With the help of teachtools and shared vision systems, PSS providers are enabled to qualify every person to do services on their machines or use them. This means, that the technology is available to be used for everyone, especially the in the beginning mentioned 5 billion people, having not access to such technology nowadays. 5

SUMMARY

Sustainability engineering meets the challenges of economic competitivity, of responsibly managing environmental resources and of developing social competencies for worldwide wealth generation. Technological innovation can be directed along these guidelines of sustainability. The dynamics of value creation in the framework of global markets enables for network integration of partners under different infrastructural conditions. Product-Service Systems are means to cope with the challenge of more functionality with fewer resources. Selling functionality by service integration substitutes the traditional approach of selling tangible products in innovative business models. Knowledge management and education by

28

Keynotes

modern information and communication technology helps in implementing the new paradigms of resource efficiency and effectiveness. 6

ACKNOWLEDGEMENT

We express our sincere thanks to the Deutsche Forschungsgemeinschaft (DFG) for funding this research within the Collaborative Research Project SFB/TR 29 on Industrial ProductService Systems – Dynamic Interdependencies of Products and Services in the Production Area. 7

REFERENCES

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Angerer, G. et al. (2009): Rohstoffe für Zukunftstechnologien: Einfluss des branchenspezifischen Roh-stoffbedarfs in rohstoffintensiven Zukunftstechnologien auf die zukünftige Rohstoffnachfrage, ISI-Schriftenreihe Innovationspotenziale, Fraunhofer IRB Verlag, Stuttgart.

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Cullen, Jonathan M., Allwood, Julien M. (2010): The efficient use of energy: Tracing the global flow of energy from fuel to service, in: Energy Policy Vol. 38 (2010), 75-81, Elsevier.

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VDI. (2010): Stellungnahme Energiepolitik, Berlin.

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Herrmann, C. (2010): Ganzheitliches Life Cycle Management: Nachhaltigkeit und Lebenszyklusorientie-rung in Unternehmen, Springer, Berlin.

[5]

Seliger, G. (2007): Sustainability in Manufacturing, Springer Verlag Berlin Heidelberg.

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Meier, H., Roy, R., Seliger, G. (2010): Industrial ProductService Systems – PSS, in: CIRP Annals - Manufacturing Technology, Vol. 59, Issue 2, pp. 607-627.

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United Nations Environment Program. (2002): ProductService Systems and Sustainability: Opportunities for sustainable solutions.

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North, K. (2005): Wissensorientierte Unternehmensführung: Wertschöpfung durch Wissen, 4. Auflage, Gabler Verlag, Wiesbaden.

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Lee, J., Ni, J., Djurdjanovic, D., Qiu, H., Liao, H. (2006): Intelligent Prognostics Tools and E-Maintenance, Computers in Industry 57, pp. 476-489.

[10]

Rolls Royce, Monitoring System, http://www.rollsroyce.com/technology_innovation/systems_tech/monitori ng_systems.jsp.

zu

Klimaschutz

und

[11] http://www.rolls-royce.com/Images/ehm_1_tcm9225476.jpg. [12] Postawa, A., Kleinsorge, M., Krüger, J., Seliger, G. (2010): Bildgestütztes Erkennen manueller Arbeitsprozesse Automatisierte Erkennung manueller Verrichtungsschritte im Remanufacturing von Lichtmaschinen, in: wt-online, vol. 92010.

Solvis Zero-Emission Factory – The ‘Solvis way’ – Structure and Subject 1

Helmut Jäger 1

SOLVIS GmbH & Co KG, Braunschweig, Germany

Abstract The philosophy of Solvis is simple: The optimal use of solar energy with mature technology and as little use of the environment as possible – for the good of everyone. The central pillar of the product range of this employee-run company is the SolvisMax solar boiler. It combines a solar stratified storage tank with a heating boiler in one unit, thus providing hot water and supporting heaters. To produce ecological products also in an environmentally-friendly building, Solvis moved 2002 into its zero-emissions plant. The concept and structure of this new plant are described within this keynote-paper. Keywords: Sustainable Building Concepts, Zero-Emission Factory

1

INTRODUCTION

To produce ecological products also in an environmentally-friendly building, Solvis moved 2002 into a zero-emissions plant (Figure 1). The Energy consumption was reduced by 80 percent over conventional in-dustrial plants. 100 percent of the supply of heat and power comes from regenerative energy, which is hence CO2-neutral. With a floor area of nearly 15,000 m², the building is the largest zeroemissions plant in Europe. The building has already received several awards, among them the European Solar Prize 2002 and the worldwide Energy Globe 2003 and also as the “the most energyefficient commercial property” of Germany with the Energy Performance Certificate for buildings according to the German Energy Conservation Regulations 2007.

Figure 1: The Solvis zero-emission factory

2

THE 'SOLVIS WAY' - STRUCTURE AND SUBJECT

The administrative areas included in the production site at Grotrian Steinweg Strasse personify the situation of the building's main access and an enclosed 'atrium' as a high-quality external space within the building volume, that is otherwise optimised with regard to the A / V relationship. The lengthways opening-up of the building is carried out as a central internal opening-up; internal movements of persons meet the product lines here. The internal central way, as a themed lengthways axis of the building, became the central situation of the building, the 'backbone' of the overall system, acquired its conceptual, contextual significance as 'Solvis way'.

The constructional realisation of the Solvis way and connected administrative areas was carried out as a reinforced concrete construction, for reasons of thermal storage capacity, in the direction of the nocturnal cooling possibilities of the building masses, and for reasons of optional fire safety classification. On the ground floor, all the necessary ancillary rooms for the functions and sanitary installations are enclosed in the 'Solvis way' and the complete building technical installation can be seen on the first floor.

Figure 2: Solar collectors above the atrium The Solvis way gives the building concept its specific identity, as a space for coordinated organised building technical installations, and is the identity-forming central area for Solvis, the manufacturer of building technical installations. The production and storage areas were conceived as a widespanned lightweight wood construction over 27.50 m connected on both sides to the primary reinforced concrete construction of the Solvis way, taking the primary energy contents of the building materials. The connections of the internal lengthways axes of the wooden construction to the massive construction enabled all horizontal loads from the wide-spanned roof construction to be absorbed. The two external lengthways axes of the wide-spanned wood construction were implemented as column constructions with nonbearing wooden element facades, alternatively as high-temperature insulated wooden frame constructions.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_5, © Springer-Verlag Berlin Heidelberg 2011

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Keynotes ENERGY AND DAYLIGHT CONCEPT

The goals of the planning stage were high quality workplaces with the same standard with short communication paths and production without emissions of climatic gases. Because of the production processes, emissions from the energy requirements for electricity and heat are the only potential sources of pollution, the conception of a zero-emissions factory is therefore above all an energy concept for reducing the electricity and heat requirement and a concept for a CO2-neutral energy supply. Thanks to the external supporting framework of the wooden truss construction of the production areas with the 27.50 m span, the building volume that was to be heated and ventilated was reduced by 1.20 m headroom (15 % of the complete enclosed space). Loading zones for trucks connect to the production and storage areas. These zones were integrated into the thermal shell of the production areas. The solar energy plant is built on the loading zone that is oriented to the southwest. The supports for the hall's external supporting framework hold the thermal collectors. The high-quality thermal protection and the compactness of the cubage of the overall project enable a heating requirement of < 30 kWh/m²/a. The sun (PV, collectors) is available as the supplier of energy without CO2-equivalent; as a regenerative supply of energy rapeseed oil is used as a supplementary source of electricity and heat, and a rapeseed oil fired block-type thermal power station is in use. With energy supply from excess energy from a PV generator and the substitution of electricity from conventional generation, CO2neutral energy supplies can be achieved with internal electricity generation even with conventional rapeseed oil cultivation. The target values for the heat with 40 kWh/m²/a and for the electricity consumption for the building's technical installations with 20 kWh/m²/a result from the tresholds of the federal economics ministry's subsidy concept for solar-optimised buildings. In addition, restrictions to 20 kWh/m²/a heat and 12.5 kWh/m²/a electricity for the building's technical installations and operations result from the objective of CO2-neutral energy supplies and the maximum available space of 600 m² for the installation of PV modules and solar collectors. The target values demonstrate that, together with a very low heating requirement, in particular the electricity requirement for the building's technical installations should be very low. For this reason, the main focuses for improvements are on energy-efficient ventilation, a good supply of daylight and adapted lighting, and integration of the solar energy supply. 4

ROOM AIR CONDITIONS AND THERMAL INSULATION IN SUMMER

Thermal insulation in summer in the offices is guaranteed by an external two-part heat protection. A reduction of the g-value (total energy transmittance) is achieved by using triple heat protection glass. In addition, the opening parts of the windows are designed as wooden panels with vacuum insulation, so that a reduction of the heat yield in summer is achieved without increasing heat losses. These are reduced considerably by means of a consistent reduction in internal loads, e.g. by performance management in electronic data processing and by demand-oriented lighting controls. Because of the dense layout, it is necessary to lose heat in summer through nighttime ventilation (change of air: 3/h). There is a mechanical ventilation system to make the building safe from breakins. There are 245 working hours with temperatures in excess of 25°C; this is less than 9% of the working hours.

5

HEATING REQUIREMENT

A low heating requirement is achieved on the one hand by a good thermal installation standard and on the other hand by an efficient ventilation plant with heat recovery in the production areas. Precondition for achieving the heat supply level of >75% is a very airtight building shell. The building achieves a very low change of air volume of 0.22 1/h at 50 Pa partial vacuum/excess pressure. This value was verified by a blower door measurement. A heat requirement of 220 MWh/a results for the building (determined by dynamic building simulation); this is 27 kWh/m²/a in relation to the net floor area with internal loads of 150 Wh/m²/d. 6

DAYLIGHT USE AND LIGHTING

The production halls receive an average daylight quotient of 3% through the fanlights, so that there is a supply of daylight adjusted to requirements. The lighting is dimmed automatically in dependence on the daylight by an external brightness controller; on the one hand this reduces the costs in comparison with a decentralized controller and, on the other, the dependence of the sensors on the reflection properties of the surfaces in the inside of the building is avoided. The offices are well supplied with daylight (daylight quotient in the area of the workplaces average 4.5%, daylight autonomy: 77% in 0.75 m room depth, 47% in 2.75m room depth); as in the production halls the lights are grouped with a daylight-dependent controller and dimmer. 7

ELECTRICITY REQUIREMENT

Even now, a major part of the electricity (approx. 55%) is required for lighting and computers/communications. For this reason, in the main 'conventional' energy saving measures were carried out in the field of electricity supply. These include lighting controllers, TL5 fluorescent lights, flat screens, low-energy actuators for pumps and ventilators and energy-saving operations for the computer systems. Thanks to a vacuum drainage system the water requirement is reduced by 80% in comparison with conventional drainage systems. The remaining wastewater is fed into the municipal sewer, because the clarified sludges are processed further in a block-type power station. 8

SOLAR ENERGY SUPPLY

The heating is supplied by a rapeseed oil factory heating and power station (180 MWh/a.), a collector plant (20 MWh/a.) and by the heat waste from the development department (20 MWh). The current demand is covered by a 60 kWh PV-plant (45 MWh/a.) and via the rapeseed oil factory heating and power station (115 MWh). Thus the energy supply is provided by regenerative energy sources. The primary energy demand for heating and current is 700 MWh/a., which equates to 90 kWh/m² p.a. The collector plant and the PVGenerator achieve a solar contribution of 22%. Additional expansion of the photo-voltaic current generation is limited from an economic point of view and also because of the lightweight construction of the hall. The non-insulated sprinkler tanks set up in the building serve as a buffer store for the 150 m² thermal collector system and thus as low-temperature radiant heating system. The waste heat from the burners in the development area is fed via a busbar to the buffer store of the rapeseed oil factory heating and power station. In winter, the waste heat from the EDP central office serves as a heating support for the warehouse, in summer a circulation fan is used here.

Keynotes

Figure 3: Solar collectors on top of the Solvis plant

9

BUILDING EXTENSION

By firm growth a building extension became necessary of 5.400 m². The new building part is used completely as central storage depot. By four lowerable stages it is possible to load at ground level up to 30 trucks daily. With a new automated production line, in which the smaller compact collectors are manufactured, Solvis is in the position to produce altogether annually up to 300,000 m² collector areas. Three laser welding machines make a capacity with absorber production of up to 500,000 m² possible. Additionally further offices and a training area on approx. 1,000 m² extended. For the measures the photovoltaic-plant was supplemented around 2.000 m², a thermal long term storage with 100.000 litres of volume supports the heat supply. With these additional activities Solvis invested 10 million Euros. 10 CONCLUSION The target values for heating consumption of 40 kWh/m²/a. and a current consumption of 20 kWh/m² p.a. for the building facilities are considerably undercut, the primary energy consumption being 90 kWh/m²/a. The excellent thermal insulation as well as the consistent planning and implementation of low-energy building facilities means that the new production building of the company Solvis can be completely supplied using regenerative energy sources and in the future will become a zero-emission factory with CO2-neutral rapeseed oil production. Through the minimisation of its regenerative energy resource requirements, the Solvis zero-emission factory has also become a model of how buildings could be supplied with energy within industrial and commercial construction in the future.

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Manufacturing and the Science of Sustainability Timothy G. Gutowski Massachusetts Institute of Technology, Cambrige, MA 02139

Abstract A new area, called Sustainability Science, is engaging large system scientists to address the challenges that face the future of human society on planet earth. In this paper, the methods and frameworks of diverse disciplines are reviewed and compared with those of the manufacturing community. The results show significant differences between disciplines, including the level of urgency expressed. Synthesizing these divergent viewpoints, this paper makes suggestions for needed research on “sustainable manufacturing”. The main message is that manufacturing needs to significantly increase the boundaries of its analysis to be able to understand its effect at the global scale. Keywords: Weak Sustainability; Genuine Investment; Eco-Systems Ecology; Panarchy; Resource Accounting; Triple Bottom Line; Scale; Human Well-Being

1

INTRODUCTION

Recent papers have identified an emerging area of research called sustainability science. This new area of study looks at the complex interactions between the methods of society and eco-system services and human well-being, over long time scales and at global dimensions. The earliest manifestations of this new science involve the natural sciences (biology, ecology, etc.) on the one hand, and the social sciences (sociology, economics etc.) on the other, with systems modelers of many persuasions in the middle [1], [2], [3], [4]. Manufacturing, as one of the major sub-systems that connects eco-systems services to human well-being has an important role to play in this new emerging field [5],[6], [7], [8]. In this paper, we review various approaches to understanding the concept of sustainability and compare them to sustainability initiatives in the manufacturing sector. 2

wealth, called genuine investment, must be equal to or greater than zero. Genuine investment is the sum of the values of all capital stocks including manufactured capital, human capital and natural capital. The accounting is done in dollars which means that economic equivalents of these different types of capital must be obtained. The difficulties in establishing prices for components of natural capital are acknowledged, and a representative calculation is made for countries, regions, similar economic groups, and the world, and announced yearly in the World Bank’s publication The Little Green Data Book. Figure 1 gives the recent accounting for the World [11]. The results (given in percent of gross national income – GNI) indicate that the world’s manufactured capital assets grew at 7.9 %, the human capital assets (represented by education expenditures) grew at 4.2 % and the natural capital assets declined at 5.0 %. The result is greater than zero (+7.2 %; note the rounding error) and so by this calculation the world is sustainable.

ALTERNATIVE VIEWS OF SUSTAINABILITY

A major thesis of this paper is that until there is reasonable agreement on a working idea of what sustainability means, it will be difficult or impossible to measure progress or describe a way forward. In this section, brief summaries of alternative views of the concept of sustainability within recognized scientific disciplines are offered. The reviews include; 1) economics, 2) eco-system ecology/resilience, 3) resource accounting, and 4) the business approach called the triple bottom line (TBL). 2.1

Economics

Starting from the concept of sustainability as defined in the UN document “Our Common Future” [9], economists in collaboration with ecologist have put forth an operational scheme for estimating society’s sustainability [10]. In this paper, sustainability is defined as the requirement that our so-called inter-temporal social welfare must not decrease over time. The inter-temporal social welfare is calculated as the present discounted value of the flow of utility from consumption from the present to infinity. Under certain conditions, this is equivalent to the more transparent requirement that genuine wealth per capita must not decline. Hence the change in genuine

Figure 1: Results from the 2010 Little Green Data Book produced by the World Bank indicate a positive genuine investment. This is the so-called weak form of sustainability which allows substitution between capital stocks. In other words, depletions in natural stocks can be compensated by additions to manufactured and human capital stocks. Substitutability, and its implied value

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_6, © Springer-Verlag Berlin Heidelberg 2011

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system and technical feasibility, is an issue for any aggregate measure of resources, and is not unique to economics. Economics, however, seems to take it to the farthest extreme by allowing for the compensation of lost eco-system services, with human engineered products and institutions. This is not only an extremely optimistic statement about human abilities, but also implies a vision of the future without nature, or at least with much less natural capital than we now enjoy. Because many people are uncomfortable with this vision and because the technical feasibility of substituting for ecosystem services on a global scale is in doubt, many people criticize the weak form of sustainability. See for example Daly and Daly and Farley [12], [13]. At the same time, the idea to aggregate resources in an attempt to measure some aspect of sustainability seems potentially worthwhile, and should be further explored [14]. In fact, the economists carry this approach much further than outlined here, by attempting to include the contributions to our economic productive base provided by human institutions [10]. See Dasgupta for a short, concise description of this calculation [15], and for more detail see [10], [16]. 2.2

Ecosystems Ecology

Ecosystems ecology brings a very different perspective to the issue of sustainability, one that may not be familiar to manufacturing engineers. Overall, ecosystem ecologists do not see sustainability as an equilibrium state, but rather as a process that naturally includes phases of decline and recovery. The central question is, can the system accommodate change and still retain controls on function and structure [17]. This inquiry is closely aligned with the new study of resalience, see for example the website for the resalience alliance [18]. A cornerstone of this effort is a systems dynamic conceptualization called panarchy [19]. Panarchy is a stylized representation of the dynamics of an adaptive system based upon observations from ecosystems ecology. It is hypothesized that other adaptive systems (including ecological, social and economic systems) may go through similar transitions. It places a useful emphasis on dynamics and transitions, identifying four crucial stages in the prototypical transition: 1) growth, 2) conservation, 3) release, and 4) reorganization. The scheme is shown graphically in Figure 2. The authors identify two metaparameters that can indicate where one is in this scheme; “potential” equivalent to the “y” axis in Figure 2, and “connectedness” equivalent to the “x” axis. A third variable, out of the plane of Figure 2 (the “z” axis) is “resilience”. If a system is not resilient it may move off of the pattern shown in the figure to a new pattern or to a dead end or “trap”. The researchers have identified two important traps. One is the so called “Rigidity Trap”. As described by Gunderson and Hollings, “Rigidity traps occur in social-ecological systems when institutions become highly connected, self-reinforcing and inflexible”. The other is the so called “Poverty trap”. As described in the resilience literature, “this is a situation in which connectedness and resilience are low and the potential for change is not realized” [19]. Ecosystem ecologists offer many examples of these behaviors in nature and speculate on the application of this framework to other systems. For example, in Gunderson and Holling, a testable hypothesis is proposed for applying the panarchy framework to industrial systems, for example the Bell telephone Co. in the U.S. For those who study business cycles, there seems to be some similarity with concepts such as the Kondratiev long wave, see [20], [5]. Overall the resilience literature is highly integrative bringing together scientists from different fields of study. Much of the earlier work however is mostly conceptual, such as the panarchy framework. A recent paper identifies specific global limits for several ecological problems described in the next section [21].

Figure 2: Graphic representation of an adaptive cycle for a complex system. 2.3

Resource Accounting

Resource accounting is the physical equivalent of the economics approach to counting identified resources needed to maintain some aspect of sustainability. The accounting is done in physical units, rather than monetary units, and usually employs some version of a “sources” and “sinks” view of the planet. That is, human activities interact with the planet by extracting energy resources, materials, biological entities and other sources, process them, and then deposit the residuals back to the planet that acts as a sink capable of absorbing a certain amount of these wastes. This approach may be done with varying degrees of rigor depending largely on how well the system is defined and the tools employed. Thermodynamics would be among the most rigorous physical accounting approaches [22], [23], [24], [25]. While using physical units greatly limits the degree of aggregation one can usefully accomplish, large categories of natural capital type resources are commonly counted. Prominent examples include: Primary energy resources measured in units of energy; climate change gases, measured in CO2 equivalents; water use measured in weight or volume; acidification potential measured in hydrogen ion equivalents; material resources measured in weight, and biological extinction measured in rates of species loss. In fact, all scientific investigations of sustainability ultimately resort to some form of resource accounting to state a problem or measure progress. And it is the resource accounting arguments which ultimately make the strongest and clearest statements concerning the current unsustainable practices of humanity. Examples of unsustainable trends come from a variety of sources, of particular importance are the effects on global eco-system services addressed in the International Panel on Climate Change [26], and the Millennium Ecosystems Assessment [27], [28]. These reports and others point to a broad array of disturbing and potentially disastrous trends including climate change, ocean acidification, nitrogen and phosphorous overloading, freshwater depletion, biodiversity loss and land system change. See also [21]. The most notable features of the resource accounting approach are; 1) that attention is directed predominantly to the natural environment, and 2) that much of the news is quite concerning if not alarming. This contrasts starkly with the much more optimistic view given by Arrow et al [10] and the seemingly non-committal view of Gunderson and Hollings [19]. In particular, an optimistic case can be made that humans can employ forward looking mechanisms and institutions to anticipate potential future disruptions, and plan accordingly [19]. At the same time, humans can game these very same mechanisms (as the recent financial crisis clearly illustrates) and fail to perceive potential precipitous decline. This potential

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inability to adapt would be an example of the so-called “Rigidity Trap” described by Carpenter and Brock [17] and others.

3

2.4

Here we propose three questions concerning sustainable behaviors. The questions are intended to expose the limitations of simple notions concerning sustainability.

Triple Bottom Line

The triple bottom line is a business response to the need for corporate performance measures that go beyond shareholder value, and include social responsibility and sustainability. The term is generally attributed to John Elkington writing in the California Business Review in 1994. Triple Bottom Line accounting includes not only corporate financial performance, but also an evaluation of potential impacts on people and planet. While it may appear to include some of the same topics as in the genuine wealth calculation mentioned earlier, the focus is on the firm and the accounting has not been standardized. In practice, it is more a portfolio approach, where the different spheres of activities are treated separately. While this method is indeed a step forward in terms of corporate acknowledgement of social and environmental issues, it is clearly a work in progress and whether it could actually have an impact on sustainability needs to be tested. The main problems are that the accounting is limited in scale, the methods may not be fully disclosed, and business as usual can often be dressed up to look like a new contribution to sustainability. Later examples will show this explicitly. 2.5

Summary

This brief synopsis of alternative views of sustainability is offered to illustrate the range of views on this topic and the uncertainty that faces the development of a science of sustainability. It seems that in a situation where we would all want clarity, it is not to be had. The problem resides not only in the vast complexity of the global environmental-social-economic system, and the weakness of the “unsustainable signal” as experienced by the average inhabitant of the planet, but also in the hugely ambitious agenda contained in the simple word “sustainable”. Even some of the most fundamental concepts are seen quite differently by the various disciplines engaged in this study. For example, consider the test question, would the addition of many more people to the planet improve or decrease the sustainability of human society? Those who see resources as limited will divide finite resources by a growing population and tend to answer in the negative. However a subset may say the opposite. The difference depends on whether one sees additional people as a potential resource, or primarily as consumers of the resources. An interesting contribution in this area is offered by the Harvard economist Michael Kremer who has shown that the rate of technological progress correlates very closely with population levels [29]. That is, the more people there are, the more new ideas and opportunities for development, and so the more we advance. This view is discussed in a popular book by Harford [30] to illustrate how contradictory the solution to sustainability might be. However to many, this view seems to deny any biophysical limits to growth. In fact, it may sound like a Malthusian mistake with the opposite sign. Indeed, those who come to this problem from a natural resource accounting point of view, would probably cast humans first in the role of consumers, and secondly as those who could modify the consumption process. The alternative views presented here are in stark contrast. This result, that even a most basic question, such as the role of human beings in sustainability, has no simple uncontestable answer, is not unique. Other basic questions, often the foundation for action plans in “sustainable manufacturing” are equally complex. The result is this; there is plenty to study concerning manufacturing and the science of sustainability and the sooner these produce results, the sooner manufacturing will be able to clearly address the problem.

THREE QUESTIONS PRACTICES

ON

SUSTAINABLE

INDUSTRIAL

Gulf Oil Spill in the U.S. A simple question might be to ask how would one evaluate the performance of the company BP during the recent oil spill in the Gulf of Mexico? Indeed by any measure this was a lose-lose-lose proposition. The company lost economically, the environment lost (although we do not know the extent of the damage yet) and indeed many local people lost by losing income and potentially their livelihood, and having their environment damaged. This was the largest oil spill in U.S. history, and at about 200 million gallons likely the largest of its kind in world history. At the same time BP has been known for promoting renewal technologies and providing investment funds for many of these. Also some may have seen BP’s response as proactive. So how would you rate BP’s behavior? Are they sustainable? The easy answer to this question is “no”, but as this paper is being written the investigations into the roles of the various players is currently in progress, and the extent of the ecological damages may take years to understand. Hence, in this case we may look to the bigger picture proposed by both the ecosystem ecologist and the economists and ask a larger question - not how did BP perform, but how did (or will) the overall system perform? The answer to this question may lie more in how the institutions which control deep water drilling and are charged with guarding ecosystems, while at the same time providing energy resources, respond to this disaster. Similarly we may ask the question how do the consumers, who ultimately drive the need for deep water drilling, respond? Are they aware of the consequences of their actions or is the signal too weak to produce a response? We leave the question unanswered but use it as an example of how we have to expand our analysis framework to get ultimate answers to these questions. Solid State of Lighting Consider the question – should an improvement in the energy efficiency of lighting be considered a engineering contribution to sustainability? This topic is currently of great interest because of significant new improvements to solid state lighting and recent studies concerning the life cycle energy use of solid state lighting [31], [32]. Anyone who owns an LED flashlight already knows that this form of lighting is very efficient because the batteries last for a very long time. However, it is also true that solid state devices are made by semi-conductor type manufacturing process which can be very energy intensive. So the question is, when viewed over the product life cycle i.e. manufacturing and use, is solid state lighting more efficient than incandescent and/or florescent lighting? Recent LCA studies indicate that the answer to this question is yes, the solid state devices can provide an equivalent amount of illumination for a much smaller amount of energy – something like 3 to 5 times less energy depending upon the exact nature of the comparison [31]. This would seem then, one face value, to be a very significant improvement and certainly a candidate for being called a contribution to sustainability. But there is more to this story. A further study of this issue looked more into the nature of our demand for lighting, and explores the question – “just exactly how much lighting do we want?” That is, will we be happy with what we got, and continue to use the same amount of illumination and therefore save energy with solid state lighting, or will we take advantage of this efficiency improvement and actually increase our amount of illumination and thereby potentially offset some or all of our expected savings? [33]. This is

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the kind of question that economists can address, using economic growth models and other models to connect our demand for illumination to other factors. As it turns out, the result to our question can be surmised roughly from available empirical data. That is, observations from over 300 years, for various geographic units, indicate that the demand for lighting per capita, , is directly proportional to per capita gross domestic product (gdp) divided by the cost of lighting CoL [33], as given in equation 1.

~

gdp CoL

(1)

This result, and one that can be derived from it, giving the total power used on lighting, are shown in Figure 3 [33]. The data show two things; 1) the wealthier we are, the more lighting we want, and 2) the lower the cost of lighting, the more lighting we want. Most notably, the graph shows no sign of saturation. We may saturate in the future, but that is a debatable point (and one that is discussed further in the reference [33]). The evidence so far however is not good for energy savings, and in fact the paper (using a more complex economic argument) predicts more energy use with solid state lighting not less. Efficiency data from an earlier paper puts this into perspective. Figure 4 shows historical improvements in the efficiency for two technologies: steam engines and lamps plotted on a “linearized” logistics curve [34]. Here we are interested in lamps. Current solid state lighting would appear roughly in the upper right hand corner of the figure. What becomes apparent from this figure is that while solid state lighting indeed represents a significant improvement in the energy efficiency of lighting, it is not, from a historical perspective, unique. That is, going from paraffin candles to Edition’s first lamp, or from tungsten filament incandescent lamps to sodium vapor lamps where also significant improvements in there own right. We return then to our original question, should an improvement in the energy efficiency of lighting be considered an engineering contribution to sustainability? Or does it look remarkably like business as usual? This seems as a core question for those who want to study manufacturing and sustainability. Remanufacturing and Energy The third question is, does remanufacturing save energy? In many references one can find comments that remanufacturing is the best option for end-of-life product. The obvious benefits are that remanufacturing can generally save some (usually large) portion of the invested energy used in both the materials production as well as the manufacturing. (The assumption is usually made that the

(a)

(b)

Figure 3: a) Empirical data showing the correlation between illumination and GDP divided by the cost of lighting b) Converts the data to show energy usage by illumination see [Tsao 2010].

Figure 4: Historical efficiency data for steam engines and lamps from Ausubel and Marchetti 1997. remanufactured product is a substitute for a new product.) But a recent study of remanufacturing of eight different products reveals that energy saving may not always be in favor of remanufacturing [35]. The result depends heavily on whether the product has an energy intensive use phase. That is, if the product has a power cord or an internal combustion engine attached to it, then the use phase of the life cycle will very likely dominate the energy use. Since it is a major product design trend to power-up previously “passive” products, the use phase is coming to dominate energy use for many products. Furthermore, since the first powered design will likely be inefficient, the ironic implication is that future energy efficiency improvements in the design could act to undermine remanufacturing. The study found that in 25 case studies, 8 showed clear energy savings for remanufacturing, 6 showed clear energy savings for buying new, and 11 cases were too close to call. The results depended heavily upon use phase energy efficiency trends and could change dramatically with time. For example, while it made sense from an energy savings point of view, to replace a damaged compressor and extend the life of a refrigerator in the 1960’s, in the 1990’s it was better to buy a new refrigerator. Ultimately however, if products can move asymptotically to a steady highly efficient state, the case where remanufacturing saves energy could be restored. It remains to be seen if such a scenario obtains. 4

RESEARCH QUESTIONS

A review of the sustainability science literature shows considerable uncertainty in regards to a definition of sustainability, disagreement concerning the roles of major players in this problem, and the lack of a clear path forward. This contrasts sharply with many of the ideas put forth as “sustainable manufacturing”. These are primarily programs of self improvement (and to some extent self preservation) and technology development to address market opportunities. They appear to be based upon a much clearer vision of the mission, usually involving resource accounting arguments, (but addressed at a relatively small scale). A resource accounting framework provides a clearer enunciation of the problems, and a basis for measurement and hypothesis testing. At the same time however, it must be recognized that even if one accepts the resource accounting approach, this must be woven into a larger picture that addresses how these resource depletions at various scales might interact and ultimately how they provide for human needs. Furthermore one must study the problem at a sufficient scale so that actions at the manufacturing level can be followed to higher levels, ultimately to a global scale. One can even go farther in the analysis to anticipate the temporal pattern of these actions. It appears that even when we do good, the scale of our actions can lead to new effects not anticipated. For example, consider the substitution of MTBE for TEL, and HCFC’s for CFC’s. In each case

36 an improvement on a unit basis is accompanied by an expansion in use, and a realization of yet new problems. Note that at the time of its introduction, CFC’s could have been easily characterized as “green”, an improvement, or even “sustainable”. See Allenby’s comments in [36]. The problem is that the scale of human activity is so large that whatever we do it will affect the environment. The study of sustainable manufacturing needs to reorient itself so that this concept is at the center of the discussion. Several critical areas for sustainable manufacturing research are identified below. 1. Scale – Manufacturing must expand the boundaries of analysis if it wants to understand its impact on sustainability. This does not mean just to distant components of manufacturing, but also to social and environmental effects. There are indeed many dimensions to this expansion, several of them are mentioned in the following points. See [37], [38], [39]. 2.Measuring Human Well-Being – The ultimate goal of sustainability is to maintain some level of human well being extending indefinitely into the future. While human well being is admittedly a complex topic, there are many credible studies that have explored this topic and proposed various measures. Examples range from the happiness index to the GINI coefficient of inequality, to the UN’s human development index (HDI), the index for sustainable economic welfare (ISEW) and the genuine progress indicator (GPI) [39], [16], [40], [41], [42] [43]. Additionally, some researchers are working on the development of a so-called Social Life Cycle Assessment [44]. While each of these can be challenged in some way, they all appear to offer more or additional sensitivity to the human condition compared to the usual default measure, which is the per capita gross domestic product (GDP) or some similar financial measure. In fact many of these human well being indicators show that while per capital GDP may be rising in many developed countries, measures of human well being are staying flat or even declining. These measures should be central to the sustainability discussion and need further and vigorous development. Even in their current state of development, application of these measures to the stake holders involved in manufacturing’s actions would be enlightening. The results should show both the benefits and disadvantages of manufacturing. Furthermore, they may provide important insights that would allow one to differentiate between various manufacturing activities. Given the global nature of manufacturing, one would have to address how these large geographical boundaries would be treated. 3. Measuring Resources – Resource Accounting is based upon the widely held premise that there are certain types of resources that need to be maintained in order to provide for the sustainable development of human society. These identified resources generally correspond to certain natural capital stocks and ecosystem services or the accounting is done on the anthropogenic emissions or actions that degrade and threaten these services. While sustainability issues can exist at all scales for society, primary concern must be focused on those problems that exist at the global scale. Several publications attempt to list these major global scale challenges. See [45], and [21]. Resource accounting approaches can use alternative accounting schemes. Two extreme cases would be highly aggregated measures (such as the genuine investment accounting scheme of the economists) or by considering individual levels of specific resources and emissions. Both methods have advantages and disadvantages. When using highly aggregated methods, one would need to acknowledge potential interactions or stay away from these in the accounting scheme. Highly aggregated measures would have significant advantage in modeling and developing conceptual frameworks for future evolutionary paths of society. On the other

Keynotes hand, identifying specific resource issues allows for a much more in depth analysis. These could address in greater detail potential limits of the global system and complex interactions between the various dimensions of the problem. In the aggregate resource accounting method, the issue of substitutability would need to be addressed in some detail. Note that the application of the genuine wealth calculation or some variation on this theme to manufacturing could result in the differentiation between the benefits provided to society by different products, for example infrastructure products versus consumer goods. While this is a very value laden issue, there is wide agreement in the psychological literature that all needs are not equal. That is, one could attempt to link product, to need, to sustainability. For engineers a particular attractive aggregate accounting scheme could be based upon the consequences of the second law of thermodynamics. These would include estimating exergy losses and entropy production at the global scale. See [22], [46], [24], [25], [23]. Concerning accounting schemes that address individual global scale problems, a recent paper by Rockstrom et al identifies 9 potential problems and makes a first estimate of quantified global limits for seven of them. That list includes; 1) climate change, 2) ocean acidification, 3) ozone depletion, 4) nitrogen and phosphorus cycle overloading, 5) global fresh water withdrawals, 6) land system change, 7) biological diversity, 8) atmospheric aerosol loading, and 9) chemical pollution. The paper claims that three of these, climate change, nitrogen and phosphorus cycles overloading and biological diversity, have already transgressed the safe operating space for the global environment. The obvious challenge for manufacturing is to connect their effects on these problems from the manufacturing scale to the global scale. 4. Mechanisms of Interdisciplinary Study – Increasing the scale of analysis will inevitably involve crossing interdisciplinary boundaries. How to do this gracefully and rigorously is an important challenge. In the review of sustainability science literature it seems that the ecologist and economists have started the process of successful interdisciplinary studies. This issue strongly affects the professional development of young academics. 5. Subdivisions by Topic Area – Several major themes emerge that both span the breath of the sustainability research area, but at the same time provide a focus which allows measurement and modeling. These area include: 4.1

Energy resource use and efficiency

The effect of energy efficiency on conservation and growth has been discussed since at least 1865 when Stanley Jevons published his book on coal. Since then it has been measured (the direct rebound effect), analyzed and debated primarily in the economics literature, and proposed as the driver of economic growth by Ayres. See [47], [48], [49], [50], [51]. This topic is among the most important that needs to be understood. Proposals to increase energy efficiency without an understanding about how society would use those advances could lead to surprisingly different results than expected, as illustrated in the earlier sections in this paper. 4.2

Materials use and efficiency

Materials connect manufacturing to the environment both as a source of raw materials and as a sink for the residues. And materials connect manufacturing to people by providing for their needs and quality of life. Current trends show a growing need for more materials as the world develops, the use of more elements in the periodic table (leading to complex mixtures) and increased needs for higher purity materials. Furthermore, materials are energy intensive and newer materials generally have even higher energy

Keynotes

37

requirements. While the materials with the largest use have been around for some time leaving only finite opportunities for energy and CO2 efficiency improvements, newer materials may present major opportunities. How materials are used, substituted and recycled is central to sustainable manufacturing. From the manufacturers point of view: how will materials use in future products be affected in light of potential restrictions, reporting requirements and standards, constrained supplies, fluctuations, and potential increases in prices and recycled content? See [52], [53], [54], [55]. 4.3

Technology innovation

development,

business

practices

Clark, W.C., Dickson, N.M., (2003): Sustainability science: The emerging research program, PNAS, Vol. 100, No. 14, pp 80598061.

[3]

Levin, S.A., Clark, C.W., (2009): Toward a Science of Sustainability, Report from Toward a Science of Sustainability Conference,held in Airlie Center – Warrenton, Virginia, funded by National Science Foundation.

[4]

Fiksel, J., Graedel, T., Hecht, A.D., Rejeski, D., Sayler, G.S., Senge, P.M., Swackhamer, D.L., Theis T.L., (2009): EPA at 40: Bringing Environmental Protection into the 21st Century, Environ. Sci. Technol. No. 43, pp 8716-8720.

[5]

Jovane, F., Yoshikawa, H., Alting, L., Boer, C.R., Westkamper, E., Williams, D., Tseng, M., Seliger G., Paci, A.M. (2008): The incoming global technological and industrial revolution towards competitive sustainable manufacture, CIRP Annals – Manufacturing Technology, No. 57, pp 641-659.

[6]

Seliger, G., Kim, H-J., Kernbaum, S., Zettl, M. (2008): Approaches to sustainable manufacturing. Int. Journal of Sustainable Manufacturing, Vol. 1, Nos. 1/2, pp. 58-77.

[7]

Gutowski, T., Murphy C., Allen, D., Bauer, D., Bras, B., Piwonka, T., Sheng, P., Sutherland, J., Thurston, D., and Wolff, E. (2001): WTEC Panel Report on: Environmentally Benign Manufacturing (EBM),” International Technology Research Institute, World Technology (WTEC) Division: Baltimore, Maryland, USA, and Environmentally Benign Manufacturing: Observations from Japan, Europe and the United States, Journal of Cleaner Production, Vol. 13, pp. 117.

[8]

Murphy, C.F., Allen, D., Allenby, B., Crittenden, J., Davidson, C.I., Hendrickson, C., Matthews H.S. (2009): Sustainability in Engineering Education and Research at U.S. Universities, Environ. Sci. Technol. Vol. 43, pp 5558-5564.

[9]

UN Our Common Future, Report of the World Commission on Environment and Development, (1987): World Commission on Environment and Development.

and

Many people are banking on innovating our way out of the sustainability problem. This is a major paradigm for technology optimists. Given that we have only first begun this journey, as we focus our attention many new developments can be expected. Skeptics on the other hand will counter that new technologies have never really been evaluated from a global perspective before. The game is changing, and the hurdles to success may be much higher. New technology needs to be encouraged and guided by informed social and environmental analysis. For manufactures this will be similar to concurrent engineering and the quality movement. We must move away from pampered products that only perform well in a highly constrained environment. There will be many new opportunities here for manufacturing. The bottom line is that to connect manufacturing to the new Science of Sustainability, much larger boundaries of analysis need to be considered. While an evaluation at the level of the firm is a desirable goal, without a credible framework that connects the firm to the planet the local evaluation risks being meaningless.

Kates, R.W., Clark, W.C. Corell, R., and 20 additional authors (2001): Environment and Development: Sustainability Science (Policy Forum), Science, Vol. 292, No. 5517, pp. 641-642.

[2]

Measurements, Metrics and Tools

The measurement of anthropogenic outputs and ecological and social responses are an area of considerable potential for sustainable manufacturing. Manufacturing engineers can develop these and this activity does not necessarily depend directly upon the definition of sustainability. Further manufacturing can contribute to the analysis of the data, and interpretation and use of it in models. While it is rewarding to see that LCA has grown in application, many tough problems remain concerning allocation, boundaries standardization and accuracy. At the same time tools that move beyond single product evaluations are a critical need for manufacturing. Indeed many modeling problems exist at many levels. 4.5

[1]

Geography and supply chains

The spatial arrangement of supply and demand presents a challenging and as yet largely unexplored area for sustainability research. In a recent book David Mackay analyzes the energy needs and the renewal energy resource potentials for England and comes to the conclusion that it cannot supply its own needs [56]. It must be engaged in some kind of trade to do so. This is a sobering and useful conclusion that highlights the problem; what does a sustainable world look like? Who trades with whom and for what reasons? For example, a recent study suggests that if the price for carbon goes to $100/tonne CO2, laptop and notebook computer manufacturing for the U.S. market should move back from China to the U.S. [57]. From the manufacturers point of view, how will supply chains be affected in terms of changing labor rates, shifting markets, materials availability and centers of manufacturing, and potentially increasing energy prices and carbon taxes imperfectly applied in different countries across the world? 4.4

5. REFERENCES

[10] Arrow, K. Dasgupta, P., Goulder, L., Daily, G., Ehrlich, P., Heal, G., Levin, S., Mäler, K-G., Schneider, S., Starrett, D., Walker, B., (2004): Are We Consuming Too Much?, Journal of Economic Perspectives, Vol. 18, No. 3, pp. 147-172. [11] The Little Green Data Book, World Bank, 2010. [12] Daly, H., (2005): Economics in a Full Economy, Scientific American, pp 100-105. [13] Daly, H.E., Farley, J. (2004): Ecological Economics – Principles and Applications, Island Press, Washington, Covelo, London. [14] Ayres, R.U., van den Bergh, J.C.J.M., Gowdy, J.M., (1998): Viewpoint: Weak Versus Strong Sustainability, Tinbergen Institute Discussion papers No. 98-103/3, available at: http://ideas.repec.org/p/dgr/uvatin/19980103.html. [15] Dasgupta, P., (2007): Economics – A Very Short Introduction. Oxford University Press, New York. [16]

Dasgupta, P. (2001): Human Well-Being and the Natural Environment, Oxford University Press.

[17] Carpenter, S.R., Brock, W.A., (2008): Adaptive Capacity and Traps, Insight, Ecology and Society, Vol. 13, No.2, pp.40.

38

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[18]

Resaliance Alliance webpage: www.resaliance.org.

[19]

Gunderson, L.H., Holling, C.S., (Editors), (2002): Panarchy – Understanding Transformations in Human and Natural Systems, Island Press.

[20] Grubler, A. (1990): The Rise and Fall of Infrastructures – Dynamics of Evolution and Technological Change in Transport, Physica-Verlag Heidelberg. [21]

[22]

Rockstrom, J., Steffen, W., Noone, K., Persson, A., Chaplin, F. Stuart III, Lambin, E., Lenton, T.M., Scheffer, M., Folke, C., Schellnhuber, H.J., Bykvist, B., de Wit, C.A., Hughes, T., Leeuw Sander van der, Rodhe, H., Sorlin, S., Snyder, P.K., Costanza, R., Svedin, U., Falkenmark, M., Karlberg, L., Corell, R.W., Fabry, V.J., Hensen, J., Walker, B., and Liverman, D., (2009): Planetary Boundaries: Exploring the Safe Operating Space for Humanity, in Ecology and Society 14(2): 32. Szargut, J. (2005): Exergy Method – Technical and Ecological Applications, WIT Press, Southampton, U.K., Boston, USA.

[34]

Ausubel, J.H., Marchetti, C., (1997): Electron: Electrical Systems in Retrospect and Prospect, in Technological Trajectories and the Human Environment, Ausubel, J.H., Langford, H.D. (Editors), National Academy Press, Washington D.C.

[35] Gutowski, T G., Sahni, S., Boustani, A., Graves,S.C. (2011): 'Remanufacturing and Energy Savings, submitted to Environmental Science and Technology. [36]

National Research Council (2006): Sustainability in the Chemical Industry – Grand Challenges and Research Needs, The National Academies Press, Washington D.C.

[37] Costanza, R., Cumberland, J., Harman, D., Goodland, R., Norgaard, R. (1997): An Introduction to Ecological Economics, St. Lucie Press, Boca Raton, Florida. [38]

Daly, H., Townsend, K.N. (1996): Valuing the Earth – Economics, Ecology, Ethics, The MIT Press, Cambridge, MA., and London England.

[39]

[23] Wall, G., M. Gong, (2001): On Exergy and Sustainable Development, Part I: Conditions and Concepts. Exergy, An International Journal, Vol. 1, No. 3.

Jackson, T., (2006): The Earthscan Reader in Sustainable Consumption. Earthscan U.K. and U.S.

[40]

Nordhaus, W. and J. Tobin, (1972): Is growth obsolete? Columbia University Press, New York.

[24]

Bakshi, B.R., Gutowski, T.G., Sekulic, D.P. (2011): Thermodynamics and the Destruction of Resources. Cambridge University Press.

[41]

Daly, H., Cobb, J., 1989. For the Common Good. Beacon Press, Boston.

[25]

]Gutowski, T., Sekulic, D. P., Bakshi, B.R., (2009): Preliminary Thoughts on the Application of Thermodynamics to the Development of Sustainability Criteria, IEEE International Symposium on Sustainable Systems and Technology, Tempe, AZ. May 8-20.

[26]

Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M.C., Avery, K., Tignor, M., Miller, H.L.J., editors. International Panel on Climate Change (IPCC) (2007): Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, UK.

[42] ]Diefenbacher, H. (1994): The Index of Sustainable Economic Welfare in Germany, in C. Cobb & J. Cobb (eds.), The Green National Product, University of Americas Press, 1994. [43] Hamilton, C. (1999): The Genuine Progress Indicator: methodological developments and results form Australia, Ecological Economics, vol. 30, pp.13-28. [44] Jorgensen, A., Le Bocq, A., Nazarkina, L., Hauschild, M., (2008): Methodologies for Social Life Cycle Assessment, Int. J. LCA, Vol. 13, No. 2, pp. 96-103. [45] Graedel, T.E., Allenby, B.R., (2003): Industrial Ecology, second edition, Prentice Hall.

[27]

Millennium Ecosystem Assessment (MEA). (2005a). Ecosystems and human well-being:synthesis. Island Press, Washington, D.C., USA.

[46] Hermann, W.A., (2005): Quantifying global exergy resources, Energy, No. 31, pp. 1685-1702.

[28]

Millennium Ecosystem Assessment (MEA). (2005b). Ecosystems and human well-being: biodiversity synthesis. Island Press, Washington, D.C., USA.

[48] Herring, H., Sorrell, S. (2009): Energy Efficiency and Sustainable Consumption – The Rebound Effect. Energy, Climate and the Environment Series, Palgrave, Macmillan.

[29]

Kremer, M., (1993): Population Growth And Technological Change:One Million B.C. to 1990. Quarterly Journal of Economics, Vol. 108, No 3, pp. 681-716.

[49] Sorrell, S., (2010): Energy, Growth and Sustainability: Five Propositions, SPRU Electronic Working Paper No. 185, University of Sussex, SPRU – Science and Technology Policy Research. Brighton, U.K.

[30] Harford, T., (2008): The Logic of Life – The rational economics of an irrational world, Random House, New York. [31]

[32]

[33]

OSRAM Report (2009): Life Cycle Assessment of Illuminants A Comparison of Light Bulbs, Compact Fluorescent Lamps and LED Lamps, Executive Summary by OSRAM Opto Semiconductors GmbH, Regensburg, Germany and Siemens Corporate Technology, Berlin Germany. Matthews, D.H., Matthews, H.S., Jaramilo, P., and Weber, C.L., (2009): Energy Consumption in the Production of HighBrightness Light Emitting Diodes, IEEE International Symposium on Sustainable Systems and Technology, Tempe, AZ., May 18-20. Tsao, J.Y., Saunders, H.D., Creighton, J.R., Coltrin, M.E., Simmons, J.A., (2010): Solid-state lighting: an energyeconomics perspective, Journal of Physics D: Applied Physics, No. 43, 354001, IOP Publishing Ltd.

[47] Jevons, S., (1865): The Coal Question, Macmillan, London.

[50]

Ayres, R.U., Warr, B. (2009): The Economic Growth Engine: How Energy and Work Drive Material Prosperity, Edward Elgar Cheltenham, U.K., Northampton, MA. USA.

[51] Ayres, R.U., Ayres, E.H. (2010): Crossing the Energy Divide: moving from fossil fuel dependence to a clean-energy future, Pearson Education, Inc., Wharton School Publishing. [52] Graedel, T.E., Cao, J. (2010): Metal spectra as indicators of development, PNAS, Vol. 107, No. 49, pp. 20905-20910. [53] Allwood, J.M., Cullen, J.M., Milford, R.L. (2010): Options for Achieving a 50% Cut in Industrial Carbon Emissions by 2050 Environ. Sci. Technol, 44 (6), pp 1888–1894. [54] Allwood, J.M., Ashby M.F., Gutowski, T.G., Worrell, E. (2011): Materials Efficiency, a White paper, accepted for publication, Resources, Conservation and Recycling.

Keynotes [55]

Gutowski, T.G., Liow, J.Y.H., Sekulic, D.P. (2010): Minimum Exergy Requirements for the Manufacturing of Carbon Nanotubes , IEEE/International Symposium on Sustainable Systems and Technology, Washington D.C., May 16-19.

[56]

Mackay, D. JC. ((2009): Sustainable energy – without the hot air, UIT Cambridge Ltd. England.

[57]

Colon-Jimenez, E. (2010)” CO2 Price Impact on Dell’s Supply Chain: A Framework for Carbon Footprint Economic Analysis, Master of Science and Master of Business Administration Thesis, Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA.

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Indian Solar Thermal Technology – Technology to Protect Environment and Ecology Deepak Gadhia 1

1

Green Force Enviro Pvt. Ltd., India

Abstract Rising fuel costs and global warming are pushing the development of renewable energy supplies. Solar energy is most promising as unlike wind it is evenly and uniformly spread and more predictable. 1 % of the solar energy received on earth would meet the total energy requirements of the world. It has been calculated that even if only 2 % of Indian deserts were to be used for putting up solar concentrators that would suffice to produce all present India’s power need i.e. 140,000 MW. In the near future, solar energy may become part of the total commercial energy basket with its share rising in proportion to the new challenges. This study report shall provoke readers to act in their limited “circle of influence” by using technologies that have already delivered results worldwide. India is a leader among the nations in having a special Ministry for the promotion of Renewable Energy (MNRE). Even though there is no lack of funds and ideas, the results are still not commensurate with the potential that exists in India. This paper introduces a case study for the establishment of renewable energy supplies in India. Sustainable entrepreneurship as well as potentials and challenges from a life cycle perspective are described. Keywords: Solar Concentrators; Sustainable Business Models; Renewable Energy 1

INTRODUCTION

In the 30 member countries of the OECD, where electricity markets are well developed and the economical situation as well as the size of populations are more or less stable, the growth of electricity generation is evidently slower than in the non-OECD countries. Considering the strong economic growth that is projected for the developing non-OECD countries such as China and India, where a high percentage of the population does not even have access to electricity yet, a substantial increase of electricity generation will be needed to meet the industrial as well as the residential demand. The World Energy Outlook 2008, published by the International Energy Agency (IEA), projects that China and India will account for more than half of the growing total energy demand until 2030, considering that India is the second largest country in the world and has a significant economic growth of about 8% with over 1 billion inhabitants [1]. Relying on existing patterns and the strong use of fossil energy carriers to cope with the resulting energy demand would unfavourably influence global climate conditions. India’s government recently presented an action plan which specifically focuses on an increasing usage of renewable energies to reduce environmental impact without disturbing economic growth. Certainly a continuous energy supply is crucial for long term economic growth. Having in mind that 60% of India’s rural population are not or not sufficiently connected to electricity underlines the importance of decentralized and renewable energy supply structures. Solar energy is specifically addressed by the government and with over 300 sun days a year the country is predestined for this renewable energy source. Therefore India has a special Ministry for New and Renewable Energy (MNRE). The Ministry has been working hard to develop renewable energy, widen the base of manufacturers and providing incentives for users to make renewable energy products affordable and accessible. Recently, the Ministry committed itself to the aim that by 2012 more than 10 % of India’s power shall come from renewable energy. At present, the share is about 5 %. For the first time in Indian history, the share will be higher than that of nuclear energy.

Till now, major contribution in renewable power comes from wind energy. To promote Solar Concentrator Technology, Indian government through MNRE provides subsidy of Rs 5,000 (approx 90 Euro) per square meter of Concentrator reflecting area to NGOs and non-profit institutions as well as accelerated depreciation benefits and subsidies of Rs 3,500 (approx 55 Euro) to the industry. The only drawback of going for government support and subsidies at present is that to get subsidies the buyer has to undergo a tendering procedure. The matter with MNRE has been taken up to do away with tendering as it causes delays and forces the companies to buy from someone who may quote low but has never proven his supplying capacities. In addition to the government support, the industry can sell carbon credits under the Clean Development Mechanism (CDM) of the Kyoto Protocol. 2

SOLAR CONCENTRATOR TECHNOLOGY

Solar Concentrators are one example for decentralized and renewable energy supply structures as they are demanded in India and have been known for centuries. Everyone knows that fires can be ignited using magnifying glasses. But only recently, technologies for its commercial use are being developed. There are various types of solar concentrators that can be broadly classified into Line Concentrators, Trough Concentrators, Heliostats, and Parabolic Solar Concentrators. At present, due to high costs and the complex curved mirror technology, Line Focus Concentrators are viable only in larger capacities. The same is true for Heliostats as the cost of the Central Tower is high and thus a minimum size of MW is needed. Parabolic Solar dishes can be of any size and thus having modularity can be of smaller sizes enabling its use for cooking, process heat and process cooling while they may also be scaled up to the range of a MW Power Plant. In this technology, parabolic dishes concentrate solar rays at a point achieving high temperatures. The temperature in the focus can be 500 to 2000 degree centigrade depending on the Concentration Ratio (CR). Of all solar technologies, Parabolic Dish Solar Concentrators have made maximum impact in India and have relevance and future.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_7, © Springer-Verlag Berlin Heidelberg 2011

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41

There are four applications (technologies) in Solar Concentrators that have found their foothold and made mark in India: 

For Domestic Cooking: Seifert Parabolic Solar Concentrator (SK 14) are small size parabolic dishes of 1 meter or 1.4 meter diameter in which blackened cooking vessels are put in its focus and due to temperatures above 250 degree centigrade food gets cooked fast, conveniently and free. There are thousands of such solar cookers being used in rural India.



For Community Cooking: Scheffler Concentrators (Figure 1) are concentrators made out of segments of parabola with flexible curvatures to achieve a stationary focus and thus the light can be reflected in the kitchen and cooking can take place in comfort. These advantages led to their being used for community cooking preparing food for 50-100 people.



Institutional Cooking, Process heating, and Cooling applications: With the help of the German company HTT GmbH, a solar steam generating system was developed. Now there are about 50 large systems in India that provide cooking energy at institutions for 500 to 25,000 people twice a day.



Scheffler Concentrators have also been successfully installed and tried out by Gadhia Solar for uses like solar air-conditioning ( a 100 TR= 350 KW system has been successfully installed at a Hospital by us in India), laundry and ironing, sludge drying, wastewater evaporation, incineration, food processing, desalination, and others. With this, the Solar Concentrator Systems are bound to spread and newer applications are being developed.

Figure 2: Installed Scheffler Concentrators, Project from 2001 Gadhia Solar Energy Systems is an innovative solar thermal energy company, focused on providing energy solutions by using parabolic concentrated technologies. Since its inception, Gadhia Solar has been technologically, solution focused company driven by strong passion for environmental and social contribution. Gadhia Solar has implemented some of the world's largest solar thermal systems in the last two decades (Figure 2, Figure 3). It offers cost effective, reliable hot water solutions, solutions for drinking water, water evaporation and desalination system of industrial scales, centralized solar air conditioning and heating systems, as well as complete customized solutions for industrial applications from pharmaceuticals to chemical to food processing industries [3].

Figure 3: Installed Scheffler Concentrators, Project from 2008/09 Figure 1: Scheffler Solar Concentrators.

3

ESTABLISHMENT OF TECHNOLOGY IN INDIA

SOLAR

CONCENTRATOR

After studying Process and Environmental Engineering and doing Post Graduation in Energy Consultancy and Energy Management at TU Berlin after his return to India Deepak Gadhia founded the company Gadhia Solar Energy Systems Pvt. Ltd. He discovered the potential of solar energy more by chance than by plan. Mr. Gadhia came into the field to help his wife Dr. Shirin Gadhia who runs the NGO Eco Center ICNEER and who was looking for a solution to offer to poor when she told them not to cut forest and was confronted with their question: “Than how do we cook?.” On getting in the field Deepak Gadhia realised that 50% of the world’s population cook on open fire and that pollution in the kitchen is the third largest killer. Thus he saw business opportunities and started his company that evolved and grew [2].

The company Gadhia Solar with the help of GTZ registered its Solar Kitchen Projects under the CDM Gold Standard and the CER (Certified Emission reduction Certificates) arising out of use of Solar kitchens would be purchased by GTZ for German Ministry to compensate for the CO2 emission of the Solar Meet held in Bonn making it a Carbon Neutral Conference. 3.1

Products

Systems from Gadhia Solar are built up of dishes (in sizes of 9 m², 16 m² or 32 m² depending on specific application) that incorporate the basic principle and therefore the advantage of high efficiency of the parabolic dish concentrators. However there is a major difference regarding the functional principle. While parabolic dish concentrators like dish-Sterling systems have to move the absorber unit connected to the dish during sun tracking, the Gadhia system can use stationary mounted receiver units. That means that receiver constructions and piping systems are significantly easier to design and the linking of several dishes for efficient energy generation systems is enabled [3].

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Keynotes

The design bases on the idea of the Scheffler dish, which was invented by Mr. Wolfgang Scheffler in Kenya in 1983. The basic idea that did lead to the development of the Schefflerreflectors was to make solar cooking as comfortable as possible [4] [5]. At the same time the device should be build in a way that allows it to be manufactured in any rural welding workshop in southern countries after a certain period of training with locally available materials. To make cooking simple and comfortable the cooking-place should not have to be moved, even better: it should be inside the house and the concentrating reflector outside in the sun [5]. The technology to achieve these desired requirements is based on changing the shape of the parabolic dish concentrator and led to the term fixfocus principle which shall be explained hereafter (see also Figure 4).

differing and has to be adjusted as well for a sharp and small focal area. This is only possible by shaping the reflector after another parabola for each seasonal inclination-angle of the sun, i.e. for each day of the year. This means the reflector has to change its shape at regular intervals. The reflector-frame is build for equinox. By inclining and elastically deforming the reflector-frame all other parabolas can be achieved with sufficient accuracy [5]. The dishes were already used in diverse applications in the context of decentralized cooking (with just one dish), water treatment or steam generation in systems with more than 100 dishes e.g. for cooking in pilgrim shelters or women's refugees. Besides basically a wide range of promising fields of applications is possible which typically involve larger amounts of solar concentrators to run the system efficiently, e.g. steam generation for process heat (for industrial purposes), co-generation of steam (process heat) and electricity (approx. 1 MW), and generation of electricity (power plant with at least 5MW) [3]. 3.2

a b

c

Figure 4: Gadhia Solar concentrator - functional principle (a), concentrator (b) and system with several dishes (c) [3]. The reflector is a small lateral section of a much larger paraboloid. The inclined cut produces the typical elliptical shape of the Scheffler-Reflector. The direct beam radiation falling onto this section of the paraboloid is reflected sideways to the focus located at some distance of the reflector. The concentrator system is tracking the suns’ daily movement one the one hand and the seasonal movement on the other hand. The axis of daily rotation is located exactly in north-south-direction, parallel to earth axis and runs through the centre of gravity of the reflector. The focus is located on the axis of rotation to prevent it from moving when the reflector rotates. The distance between focus and centre of the reflector depends on the selected parabola. During the day the concentrated light will only rotate around its own centre but not move sideways in any direction. That way the focal area or hot spot stays fixed and is therefore called fix focus. After sunset the system has to be set back into morning position. As previously mentioned, the unique feature of the concentrator system is the fixed hot spot near the ground. The adjustable paraboloid dish can concentrate the radiation onto a defined target area for all positions of the daily and seasonal sun movement. Adjustment of the dish shape is necessary because in the course of the seasons the incident angle of the solar radiation varies in relation with the perpendicular to earth-axis. The paraboloid has to perform the same change of inclination in order to stay directed at the sun. Changing only the inclination of the dish is not sufficient to obtain a sharp focal point. Even though the position of the focus stays fixed the focal length is

Potentials and Challenges from a Life Cycle perspective

As the previous chapters show the current and predicted economic background in context to solar thermal electricity generation is quite positive in India as well as worldwide. Gadhia Solar as leading and well known company for solar thermal solutions in India naturally wants to take part in these developments. Their products are characterized by unique technological properties like the fixed focus dishes which may give them technological advantages in terms of efficiency. However, until now Gadhia Solar has not installed power plants for large scale electricity generation yet. Quite obviously there are some challenges that have to be solved when establishing business with large scale solar power plants. Based on previous statements two critical success factors can be derived [6]: 

be able to cope with high production volumes to face capacity increase and upscaling of systems



reducing costs of electricity generation to encounter high cost pressure in competition with other energy sources

Considering economies of scale and scope it is obvious that both factors are closely connected to each other. Against this background the following paragraphs shall give a more detailed look on challenges along the life cycle of a solar thermal power plant based on Gadhia Solar concentrators (Figure 4). Thereby, while India being the home country and also primary market of Gadhia Solar it is absolutely crucial to consider the specific conditions there.

Figure 4: Life cycle of solar concentrator systems [6]. Product Design Whereas the influence on costs is mainly given in the design phase, in the sense of a “Design for X” it is naturally necessary to consciously consider all other life cycle phases already here. In order to cope with high production volumes and cost pressure specifically design for manufacturing and assembly (DFMA) is of major relevance. In this context it is important to take a look at improving the product structure, increasing the amount of common parts and the careful definition of interfaces with appropriate selection of subassemblies and joining technologies. Main objectives of DFMA are the reduction of product costs assembly

Keynotes time (enables faster product throughput/higher capacity) and the amount of parts (e.g. fewer parts in stock) both resulting in lower product costs (labor and material). Studies underline that reductions of about 50% in all categories compared to the initial state are realistic [7]. Hereby it is crucial to take certain specific critical conditions or restrictions regarding transportation (e.g. road conditions, space on trucks), qualification of personnel (e.g. easy activities, safety issues) and usable technologies (e.g. no electricity on installation site) into account. Critical points in mechanical and electrical system design in the considered system of Gadhia Solar include parts like the steam pipeline (design of all components for optimizing the system to produce superheated steam for power generation), the mirror surfaces (foils, adhesive bonding of reflective coated glass, improvement of the long time behaviour of the mirror surfaces, cleaning, weather proof coatings), the frame (redesign for light weight and carbon foot print, using of space frame, computation and optimization of the welded structure), the day time sun tracking and the seasoning adjustment (e.g. design for automatical use in power plants). [6] Production As described above the proposed fields of applications using the Scheffler solar concentrator involve a very significant increase (factor 5-10 of current production capacity per year) of the necessary number of concentrators. This larger production volume is a totally new requirement for the whole production process chain which consists of the rather manual manufacturing of parts and subassemblies in a production plant (in Valsad, Gujarat) and their final assembly on the actual installation site. Significantly higher production volumes need a redesign of the production system. However, connected technical (e.g. production system design /material flow, selection and dimensioning of specific production processes / machines) and organisational (e.g. planning and control of production, organisational structures, qualification) measures to adapt the production system will lead to economies of scale with positive effect on product costs. Again, while being quite different compared to e.g. European countries Indian specific conditions and requirements (e.g. qualification of employees, given infrastructure, cost structure/ prices for machinery and raw materials, integration of local content) need to be considered. As a final result the production process chain based in India shall be able to timely deliver as many qualitatively sound solar concentrators as needed for the proposed fields of application – under consideration of additional targets like competitive costs and also low environmental impact. [6] Product usage and End of Life As a long term investment good with a desired life span of at least 10-15 years the use phase naturally has a major impact regarding the ecological and economical performance of solar concentrators over the life cycle. Whereas current solutions considering systems with approximately 100-200 mirrors totally different approaches are needed to cope with the desired shift to power plant system with several hundred dishes. Critical aspects in this context are the significant effort needed to ensure efficient functionality of the whole system through adjusting / control (e.g. daytime and seasonal adjustment of the mirrors, control of system regarding heat usage / storage et cetera) or maintenance measures (e.g. ensuring high availability, cleaning of mirrors, strategy for monitoring and controlling of the system states) despite being strongly exposed to the elements. While large amounts of concentrators are in use, it is important to be able to appropriately dispose them after use (e.g. no hazardous materials). Additionally, aspects like reuse or material recycling should be considered in product design (e.g. common parts as spare parts) to gain advantages over the life cycle. [6]

43 4

MOTIVATION FOR FURTHER ACTIVITIES

Like all countries, India too has rolled out a very ambitious 20 GW Solar Energy Mission. This will fuel the demand but also create an increased demand for engineers, skilled workers, technicians, installers, after sales service providers, marketeers, and consultants. To overcome the shortage that will emerge Green Academies must be developed with the support of the International Labour Organisation (ILO). Muni Seva Ashram, an Indian NGO in India in which Deepak Gadhia is a trustee, plans to start a Green Academy called ASPIRE (Academy for Sustainable Practices, Innovations in Renewable Energy) to meet that demand. Green Industries and Green Jobs are the future. They offer great opportunities to Entrepreneurs who are willing to enter into fields like solar energy, biogas etc. Besides the incentives of subsidies and carbon credits for renewable energy and of saving fuel many industries and institutions are purchasing renewable energy systems with the aim to “Go Green” and contribute to the protection of the environment and to reducing the problems of global warming. They understand the need to act. While some time ago all the decisions were taken considering economics only people are now willing to pay a bit more if that helps to protect the environment and the ecology. For the survival of mankind, it is imperative that economy and ecology go hand in hand. 5

SUMMARY AND ACKNOWLEDGEMENTS

The paper presents a case study for the establishment of renewable energy supplies in India and its underlying and enabling sustainable entrepreneurship. While being a promising approach for the future, probable developments demand manufacturers of solar thermal systems to be able to cope with high production volumes and significant cost pressure. This was underlined by the case study of Gadhia Solar where additional influencing parameters were also presented. This paper was developed in context of a cooperation between Gadhia Solar Energy Systems Pvt. Ltd. And the Technische Universität Braunschweig. 6

REFERENCES

[1]

World Energy Outlook, 2008, International Energy Agency (IEA), www.worldenergyoutlook.org.

[2]

Gadhia, D. (2010): Solar Concentrators in India - Technology to Protect Environment and Ecology, in: TU INTERNATIONAL, No. 66, pp. 12-13, Berlin, Germany

[3]

Gadhia Solar Energy Systems Pvt. Ltd., 2009, company information, e.g. www.gadhia-solar.com.

[4]

Tyroller, M., 2004, Solarsterilisator für Entwicklungsländer, München.

[5]

Scheffler, W., 2009, Solare Brücke Reflektoren, www.solare-bruecke.org.

[6]

Herrmann, C., Thiede, S., Kuntzky, K., Böhm, S., Frauenhofer, M., Gadhia, D. (2009): Indian Solar Thermal Technology: Potentials and Challenges, in: Proceedings of the 7th Global Conference on Sustainable Manufacturing, pp.169-174, Chennai, India.

[7]

Boothroyd Dewhurst Inc., 2009, Design for Manufacture and Assembly (DFMA), www.dfma.com.

-

Die

Scheffler

Assessment of Energy and Resource Consumption of Processes and Process Chains within the Automotive Sector 1

1

1

2

2

2

R. Schlosser , F. Klocke , B. Döbbeler , B. Riemer ,K. Hameyer , T. Herold , 3 4 5 6 W. Zimmermann , O. Nuding , B. A. Schindler , M. Niemczyk 1

Laboratory for machine tools and production engineering (WZL) of the RWTH Aachen University, 2 Institute of Electrical Machines of the RWTH Aachen University, 3 4 5 6 Daimler AG, Robert Bosch GmbH, PE International GmbH, Effizienz-Agentur NRW

Abstract Within this paper a methodology for the assessment of energy and resource consumption within manufacturing processes is described and two case studies from the automotive sector were evaluated. On basis of the Life Cycle Assessment approach the energy and material flows within single manufacturing processes were acquired concerning the two selected case studies. With the generated knowledge about energy and material use it was possible to show up optimisation potentials for the reduction of the ecological impact of the determined products within the manufacturing phase. The work shown in the paper was conducted within the project BEAT which is kindly financed by the Federal Ministry of Education and Research in Germany (BMBF). Keywords: Manufacturing Process Evaluation and Characterisation; Total Process Efficiency; Sustainability

1

INTRODUCTION

Due to the scarcity of resources and the increasing global demand to use these resources for products and power generation, the commodity prices on the international energy and commodity market are increasing heavily as shown in Figure 1. Although the prices on the markets crushed during the last world economic crisis, as highlighted in grey in Figure 1, they are constantly growing again. This vast increase in prices emerges to one of the central problems which manufacturing industry has to face [1][2].

200 150 100 50 0

Ja n 0 Ja 0 n 0 Ja 1 n 0 Ja 2 n 0 Ja 3 n 0 Ja 4 n 0 Ja 5 n 06 Ja n 0 Ja 7 n 0 Ja 8 n 0 Ja 9 n 10

Price trend based on 2005 / %

250

crude oil (import price index) natural gas (import price index) energy (manufacturing price index for special contracted companies) steel (manufacturing price index) copper (manufacturing price index) Figure 1: Development of energy and commodity prices. In economic as well as in ecological perspective, the resource consumption of products has to be planned to be more sustainable. Therefore products have to be designed to be resource and energy efficient along the total life cycle. To achieve this aim, it is possible

to influence the energy and resource consumption in one or more product life cycle phases. The change of one product life cycle phase might also effect the energy and resource consumption in another phase in a positive or in a negative way. For this reason it is essential to evaluate all changes across the whole life cycle, to guarantee an overall reduction in energy and resource consumption [3]. The necessity for this can be shown by the following example: The manufacturing industry will primarily focus on the resource efficiency during the manufacturing process. The customers of energy or material consuming goods, like a machine tool on the other hand, intend to have low resource consumption during the use stage. The analyse of the whole life cycle including preproducts production, manufacturing itself as well as scenarios for use stage and end-of-life is therefore essential for the manufacturers of these goods [4]. With the increasing impact of material and energy costs in the use stage of a machine tool even in high wage countries, it is important to identify and optimise the energy and material demand. Former studies identified that manufacturing processes can be influenced most, if the processes with the highest average power consumption are optimised. Therefore heat treatments are generally considered with a high optimisation potential. Within this paper further investigations of the project BEAT (“Bewertung der Energieeffizienz alternativer Prozesse und Technologieketten”, engl.: Assessment of the energy efficiency of alternative processes and process chains), which is kindly supported by the Federal Ministry of Education and Research (BMBF) in Germany, are presented and it will be shown that this assumption is not sufficient for machining operations in the automotive sector. 2

A LIFE CYCLE ASSESSMENT APPROACH FOR THE EVALUATION OF THE ENERGY AND RESOURCE CONSUMPTION OF PROCESS CHAINS

Throughout recent years, the objective of manufacturing processes was to reduce the manufacturing costs. Due to a lack of data it was

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_8, © Springer-Verlag Berlin Heidelberg 2011

45

46

Automotive Life Cycle Engineering

assumed that the major cost drivers are staff and machine costs. The detailed analysis of energy and material was not in the focus of optimisation potential. This can be proven best on the basis of the available inventory data in Life Cycle Assessment. Until today the data on machining of metal parts is poor. A model for the prediction of the material and energy consumption with reasonable preciseness during a typical machining process like milling or turning is not yet available [5]. It is common practise within companies that costs for energy are assigned towards the machine tools rather by the amount of square meters used by the machine tool than by the real usage data. It is generally known that the best procedure to compare different production processes with respect to their energy and material consumption and the associated environmental impacts is done by a Life Cycle Assessment according to DIN EN ISO 14040/14044. Within the Life Cycle Assessment material and energy flows of all life cycle phases are determined (compare Figure 2) and the environmental impacts are calculated by means of using scientifically based characterisation factors. Only the relative comparison of the results for the different impact categories enables the evaluation of the values [6][7].

Energy Resource

Waste Raw material production

Energy Resource

Waste Production

Energy Resource

Emissions Waste

Use

Energy Resource

Emissions

Emissions



Detailed measurements on the machines will identify “hot spots” within the processes and help to develop options for savings even in today’s state of the art processes.



Better understanding on the material and energy consumption of different machining processes, which means the development of ecodesigns for whole process chains.

An additional benefit is a better understanding of hidden costs, in most cases declared as overhead, which also contain energy and auxiliary material (range from 5% to 50%). 3

INDUSTRIAL SECTOR

CASE

STUDIES

IN

THE

AUTOMOTIVE

Within the BEAT Project the following two industrial case studies of the partners Bosch and Daimler were investigated. The case studies were chosen due to their high volume relevance of the parts. 3.1

Gear manufacturing

The research object of the Daimler AG is a production line for the manufacturing of the 4th gear wheel (idler gear) of the front-shift transmission (type FSG) in the Rastatt (Germany) plant. The FSG is the manual transmission of the A and B class, with an annual production volume of 100,000 units. The used process chain is displayed in Figure 3. The basic structure of the process chain is soft machining of the forged part and hardening followed by hard finishing processes, such as hole and gear grinding. Within the project the process chain from turning to gear grinding is captured and evaluated as this part of the process chain is done within the Rastatt production plant.

Forging

Waste Recycling/ Disposal

Emissions

Turning Hobbing

Figure 2: Balance shell for Life Cycle Assessment with in- and outgoing energy and resource flows. As stated above, even from the cost perspective machining operations have not been in focus of the Life Cycle Assessment studies so far. Assumptions and estimations have to be used due to missing data for these processes. Recent studies have shown, that the costs of energy used in machining operations are as high as the costs for tools [8]. For this reason it is absolutely crucial to further analyse and measure the energy and material consumption of typical machining processes. Alternative processing routes may become interesting on a cost perspective as well as for ecological reasons. So far optimisations of technologies and process chains have been driven by the lowest production costs as a sum of machine costs and staff costs. This may change in future due to rising costs for material and energy. A detailed data collection for process chains with reference to the considered products is necessary. This allows the extension for comparisons to alternative process routes and for a “technical” cost calculation. While the work load for such an inventory analysis may seem to be very high, its effect may be even bigger. This approach will help the companies to reduce the consumption in two ways.

Deburring Shaping Washing Carburisation Quenching Washing Tempering Hole grinding Tooth flank grinding Washing Figure 3: Case study gear manufacturing with its process chain.

Automotive Life Cycle Engineering 3.2

47

Valve injector manufacturing

The research object of the Robert Bosch GmbH is a production line for the manufacturing of the valve injector of a magnetic common rail injector in the Bamberg (Germany) plant. Common rail systems are produced since 1997 and the total volume is clear about 50 million systems so far. The applied process chain is displayed in Figure 4. The basic structure of the process chain is soft machining of bar material and hardening followed by hard finishing processes.

Turning, Drilling Washing Heat treatment Eroding Rounding Flow Rate Check Laser marking Grinding Deburring Figure 4: Case study valve injector manufacturing with its process chain. 4

ENERGY AND RESOURCE CONSUMPTION ALONG THE PROCESS CHAIN

For the evaluation of the process chain it was essential to define the balance shell first. It is not useful to respect only the energy and resources which are needed for the process itself, as the enabling energy and resources for a machine tool cannot be neglected for the process. Within the BEAT project, the machine tools were chosen as the relevant balance shell for the evaluation. Besides it has been decided, that the first level of central systems (directly connected to the machine tool) is also measured and converted on the single machine tools by the consumption of functional units of each machine tool. Nevertheless it is not practical to measure even more layers of central systems as the influence and therefore the relevance of these systems is very small in comparison to the direct energy and resource flows. As in most manufacturing plants the real energy and resource flows in the machine tool are not known, a first step within the BEAT project was the qualitative detection of all flows in and out of each machine tool and central unit. An extract of the example of the gear manufacturing can be seen in Figure 5. Electrical energy is a major flow as it is required almost everywhere. Therefore its correct data acquisition is important and will be further investigated in the next chapter.

Figure 5: Energy and resource flows within gear manufacturing.

48 5

Automotive Life Cycle Engineering TECHNOLOGY REQUIREMENTS FOR DATA AQUISITION OF ELECTRICAL ENERGY

In general converter-fed motors are applied to modern machine tools to allow the required dynamic operation. From the electrical point of view a machine tool can be simplified as done in Figure 6, including the converter and one electrical machine, e.g. a speed variable main spindle.

the load (machine tool) and is not converted into mechanical power. The reactive power is defined as

Qn  S n2  Pn2 ,

(3)

with the apparent power:

S n  U rms ,n  I rms ,n ,

(4)

and the root-mean-squared values:

1 2 xt  dt , T T

X rms 

x  u, i .

(5)

The calculation of the root-mean-squared values has to be synchronised by the zero crossing of the voltage or the current. This synchronisation fails if the sample frequency of the measurement instrument is too small. By this reason it is not possible to use power quality analysers for power measurements at pulsed voltages behind the converter. Figure 6: Simplified electrical representation of a machine tool. For a significant data acquisition of the electrical energy flow, the voltage and current shapes have to be considered. The nearly sinusoidal input voltage of the converter is rectified in the first module. The converter feeds the connected motor with voltage pulses of a switching frequency of 2-16 kHz. These voltage pulses lead to a current flow which can be controlled in magnitude and frequency as it is required by the process. Due to the switched voltage the current has a high fraction of higher harmonics beside the fundamental wave. For a reliable data acquisition the sample frequency of the measuring instrument has to be adapted to this higher harmonics. Electrical power measurement devices can be differentiated into power analysers and power quality analysers. A major difference is the sample frequency. Modern power analysers have sample rates up to 3 MS, resulting in a sample frequency of 500 kHz per channel for a 3-phase power measurement. This sample frequency allows a power measurement at the input and at the output of the converter. Power quality analysers, which have an extensive advantage in price compared to power analysers up to a factor of 5-10, are generally used for long term power quality measurements of power grids. They have sample rates of 128 - 512 samples per cycle, resulting in a sample frequency of 6.4 kHz - 25.6 kHz for 50Hz grids [9]. To understand the impact of the sample frequency on the measurement accuracy some basic principles of electrical power measurement have to be considered. The instantaneous input power of an electrical load is given by:

1  un t   in t dt. T T

7000

(1)

The phase voltage un(t) and the phase current in(t) are sampled with the sample frequency of the measurement instrument. It has to be considered that the error of the measurement will increase for a decreasing sampling frequency. The instantaneous power can be separated into active and reactive power. The active power less the internal losses of the electrical drive, e.g. friction, switching and ohmic losses, is dissipated into motion. The active power for each phase n is defined as

Pn 

8000

(2)

For a holistic energy analysis the reactive power has to be regarded as well. The inductive behaviour of electrical machines causes a reactive current flow leading to additional ohmic losses onto the supply conductors. Reactive power oscillates between the grid and

6000 active power [W]

pn t   u n t   in t .

Beside the sampling frequency, the method of the current measurement has an arbitrative influence on the quality of the measured data. The use of serial connected high-precision shunt resistances necessitates an unacceptable disconnection of the machine tool from the grid. This interruption of the machining process can be avoided by using current probes. Current probes are often based on the principle of a transformer. Their accuracy is lower compared to shunt resistances due to stray fluxes and external influences. Compared to power analysers, which use generally shunt resistances, power quality analysers are equipped with current probes. To quantify the ability of power quality analysers to acquire the energy consumption of machine tools, a comparative measurement is performed. Using a simple configuration as depicted in Figure 6, the energy consumption is measured at the terminals of the converter. The process of a machine tool is simulated using a controlled asynchronous machine as a main spindle connected back to back to a controlled permanent magnet synchronous machine. The power analyser measures the current with Hall Effect current sensors with an accuracy of 0.3 %. The sample rate is adjusted to 500 kHz per channel. The power quality analyser works at sample frequency of 6.4 kHz per channel and uses current probes with an accuracy of ±0.7 % ± 2 mA and a phase angle error of ± 1.5º. The rms-values are averaged over a period of 1s. Figure 7 and Figure 8 depict the measured active and reactive input power at the converter terminals for different applied loads of the asynchronous machine.

5000 4000 3000 2000 Power Quality Analyser Power Analyser

1000 0

0

50

100

150 200 time [s]

250

300

350

Figure 7: Energy measurement of the active power by a power analyser compared to a power quality analyser.

Automotive Life Cycle Engineering

49

Epart, indirect:

6000

The direct manufacturing energy per part is the sum of the energies of the single manufacturing processes

reactive power [VAr]

5000

m

E part , direct   E part ,man j

4000

Epart,manu_j:

1000

Power Quality Analyser Power Analyser 0

50

100

150 200 time [s]

250

300

350

The relative deviation between the measured active energy is 0.14 %. The reactive energy has a relative deviation of 0.16 %. These matching results of the comparative measurement demonstrate the usability of power quality analysers at the terminals of machine tools within the project despite the lower sample frequency and the less accurate current measurement. Power demand and energy consumption in a turning process

Figure 9 displays the composition of power demands, forming the overall process energy depending on the process times. During one cycle several different power demands can be distinguished. The electrical energy can be divided in energy which flows directly into the balance shell, in other words in the machine tool, and in indirect energy from the periphery (central unit systems) which is necessary to enable the manufacturing process. On the one hand there is a constant portion containing periphery (illumination, air conditioning ...) and machine aggregates (basic demand = standby demand). On the other hand the variable portion depends largely on the actual process as well as on auxiliary and feed movements [10].

Power /kW12 10

direct

Process

indirect

Idle

process energy consumption energy consumption during idling

Esb,j:

energy consumption in standby mode

Eoff,j:

energy consumption while machine tool is switched off

If the idling and process mode cannot be separated, both energy consumptions can be calculated by the mean process and idling power multiplied with the time per unit. The energy consumption of the other machine tool state can be proportionally added.

E part , man j  Pprocess, mean  t process  t process  Psb , mean 

Figure 9: Power consumption in cutting processes. The energy consumption per part in manufacturing can be calculated as the sum of the direct and indirect energy per part.

energy consumption per part

Epart, direct:

direct energy consumption per part

poff p process

psb p process

 (9)

 t process  Poff , mean .

Pprocess, mean:

mean process power

Psb, mean:

mean standby power

Poff, mean:

power consumption while the machine tool is switched off

tprocess:

process time

psb:

proportion of standby

poff:

proportion of the machine tool is switched off

pprocess:

proportion of the productive time

m

i 1 j 1

Standby Illumination, air conditioning, compressed air, central coolant lubricant supply… Time /s

Epart:

(8)

Eidle,j

n

E part  E part , direct  E part , indirect

in

Eprocess,j

E part , indirect  

4

0

part

The indirect energy from the periphery has to be estimated by defining a functional unit (FU) of each auxiliary energy and resource flow. A functional unit for compressed air is for example Nm³.

6

2

per

E part ,man j  E process , j  E sb , j  Eidle , j  E off , j

Figure 8: Energy measurement of the reactive power by a power analyser compared to a power quality analyser.

8

direct energy consumption manufacturing process j

The energy of a single manufacturing process consists of the real process energy, the energy consumed in the idling mode and a proportional part of the energy consumed in standby mode and while the machine tool is switched off.

2000

5.1

(7)

j 1

3000

0

indirect energy consumption per part

(6)

Eaux ,i  FU machine tool j , part FU total ,i

(10)

Eaux,j:

energy consumption of auxiliary device j

FUtotal:

total amount of functional units

FUmachinetool, part:

amount of functional units used on a machine tool for a product

The following chapter will show the results of measurements of the direct energy for the valve injection process chain, which were generated up to now. Further research work is outstanding. 5.2

Energy consumption within valve injector manufacturing

Corresponding to the described proceeding above, every process was measured and calculated within both case studies. In the following Figure 10 and Figure 11 the results are shown for the valve injector process chain. The results are especially interesting if

50

Automotive Life Cycle Engineering

the average power consumption of the single processes is compared with the influence on the energy per part. As it can be seen, the extensively used assumption, that the optimisation of the highest power consumers would bring the best benefit, does not really make sense, if the energy per unit is taken into account.

7

ACKNOWLEDGMENTS

The authors gratefully acknowledge the financial support of the Federal Ministry of Education and Research (BMBF) and the project supervision of the Project Management Agency Forschungszentrum Karlsruhe, Division Production and Manufacturing Technologies (PTKA-PFT) for the project BEAT - Bewertung der Energieeffizienz alternativer Prozesse und Technologieketten (Assessment of the energy efficiency of alternative processes and process chains).

Turning Washing Heat treatment Eroding Rounding Flow Rate Check Laser marking Grinding Deburring

Figure 10: Distribution of power consumption along the process chain. 8

REFERENCES

[1]

Herring, H., (2000) Is Energy Efficiency Environmentally Friendly? Energy & Environment 11, No. 3, pp. 313 - 325.

[2]

Herrmann, H., Zein, A., Thiede, S., Bergmann, L. Bock, R., (2008) Bringing sustainable manufacturing into practice – the machine tool case, in: Sustainable Manufacturing VI, Global Conference on Sustainable Product Development and Life Cycle Engineering, Pusan, Korea, pp. 272 - 277.

[3]

Graedel, T., (1996) Industrial Ecology: Defnition and Implementation, in: Socolow, R. et al.: Industrial ecology and global change, Cambridge University Press, pp. 23 - 42.

[4]

Figure 11: Distribution of influence of the processes on the required energy per part.

Gerschwiler, K., Jahns, P., Klocke, F., Lingg, G., Lung, D., Schlosser, R., Werner, A. R., Zeller, R., (2008) Ressourcenschonende Produktion, in: AWK 2008 – Wettbewerbsfaktor Produktionstechnik, pp. 81 - 124.

[5]

The reason why high energetic processes, as heat treatment, in the shown case studies didn’t have such a big influence on the direct electrical energy per part is that in the heat treatment and washing process much more parts are treated at the same time than on a machine tool.

Büdicker K., (2003) Reduktion und Verwertung von Abfällen anhand ausgeführter Beispiele der Wälzlagerherstellung, VDI Berichte Nr. 1779.

[6]

N.N., (2009) Environmental management – Life cycle assessment – Principles and framework, DIN ISO EN 14040.

[7]

N.N., (2006) Environmental management – Life cycle assessment – Requirements and guidelines, DIN ISO EN 14044.

[8]

Bode, H.-O., (2007) “Einfluss einer energieeffizienten Produktion auf Planungs- und Produktprämissen am Beispiel der Motorenfertigung”; in XII. Internationales Produktionstechnisches Kolloquium, Berlin, pp. 299-305.

[9]

N.N, (2009) IEEE Recommended Practice for Monitoring Electric Power Quality, IEEE Std 1159-2009.

Turning Washing Heat treatment Eroding Rounding Flow Rate Check Laser marking Grinding Deburring

6

SUMMARY AND OUTLOOK

This paper presented and discussed research work within the framework of the BMBF supported project BEAT. It was possible to show a suitable proceeding for the assessment of energy demands of manufacturing processes with the focus on the energy per unit. The case studies showed that the energy per unit is quite different from the average power consumption of a process, as the units in a process might have an even bigger impact on the energy per unit as the amount of power consumption. Nevertheless, for a comprehensive balance of manufacturing processes further information are still missing and have to be generated in the future.

[10] Bhattacharya, A., Das, S., Majumder, P., Batish, A., (2009) Estimating the effect of cutting parameters on surface finish and power consumption during high speed machining of AISI 1045 steel using Taguchi design and ANOVA, In: Production Engineering, Vol. 3, No. 1, pp. 31 - 40.

Assessment of Alternative Propulsion Systems for Vehicles 1

2

1

1

Christoph Herrmann , Kuldip Singh Sangwan , Mark Mennenga , Philipp Halubek , Patricia Egede 1

1

Technische Universität Braunschweig, Institute of Machine Tools and Production Technology, Product- and Life-CycleManagement Research Group, Braunschweig, Germany 2

Birla Institute of Technology & Science, Pilani, India

Abstract Concern for the environment, the approaching end of fossil fuels and the dependence on oil exporting countries has revived the interest in alternative propulsion systems for vehicles. However, an assessment of alternative propulsion systems with respect to sustainability is very complex due to the variety of technologies as well as unsecure and conflicting economic, ecological and social consequences. This study provides a framework for assessing alternative propulsion systems for vehicles using the AHP methodology. A criteria catalogue is derived from existing approaches and the analysis of propulsion systems, their market situation and surrounding conditions. Its application is illustrated by the assessment of two exemplary propulsion systems. Keywords: Alternative Propulsion Systems; Technology Assessment with the Analytic Hierarchy Process; Criteria Catalogue

1

INTRODUCTION

The need and demand for automotive mobility is continuously rising. Today, around 800 million vehicles are in operation worldwide. This number has been reached during the last 100 years but could double in the next 30 years as the vehicle production augments extensively each year. Between 2002 and 2015 the number of produced vehicles is estimated to rise by 33% from 57 to 76 million vehicles a year [1]. The primary reason for these numbers is the economic development and growth of countries like Brazil, Russia, India and China. A comparison of the distribution of vehicle ownership of these countries with industrialized countries shows the present potential. For example, in Germany 566 cars are registered for 1000 people [2] whereas in India only 7 vehicles are registered [1]. Today, 90 % of the 800 million cars in service are operated with conventional engines [3]. However, concern for the environment, the approaching end of fossil fuels and the dependence on oil exporting countries has revived the interest in alternative propulsion systems [4]. The use of propulsion systems other than the fourstroke combustion engine and fuels other than diesel and petrol is not a new idea. In the beginning of the automobile history different directions were explored and pursued. For example, the original diesel engine developed by Rudolph Diesel was designed to run on vegetable oil [5]. Furthermore, the first automobile with an electric drive was introduced in 1892 [2]. However, eventually the petrol and diesel engines superseded the other options because their fuel was cheap and their efficiency superior [3]. Innovative propulsion systems (e.g. for electric or hydrogen vehicles) are expected to create a more sustainable mobility. An assessment of these systems with respect to sustainability has to cover the variety of alternatives as well as unsecure and conflicting economic, ecological and social consequences from multidimensional perspectives (e.g. consequences coming from the propulsion system itself or the energy and infrastructure supply during usage). Today, precise statements on the effectiveness and efficiency of individual propulsion systems are not yet possible.

2

OVERVIEW ON ALTERNATIVE PROPULSION SYSTEMS

Propulsion systems consist of an engine and an energy source. An overview of alternative propulsion systems is shown in Figure 1. A variety of engines is available other than the well established diesel and petrol engine. One option is the exclusive use of an electric motor with either a fuel cell or a battery as source of energy. Another option is the use of alternative combustion engines with either an external or internal combustion. Finally, two different engines can be combined to form a hybrid. The most common type is the combination of an electric motor with a combustion engine, alternative or conventional, building a hybrid electric vehicle (HEV) [1] [6]. Alternative fuels are those other than the conventional fuels based on mineral oil (petrol and diesel). They can be categorized according to the primary energy from which they originate. Two groups are distinct: non-renewable and renewable energy. Nonrenewable energy includes the fossil resources crude oil, natural

Figure 1: Alternative propulsion systems [1], [4], [6].

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_9, © Springer-Verlag Berlin Heidelberg 2011

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gas and coal along with nuclear power. Fuels converted from fossil sources like Compressed Natural Gas (CNG) are known as fossil fuels. Solar, wind and water energy as well as biomass are considered renewable. Corresponding fuels like biodiesel or biogas are referred to as renewable fuels [4].

Third, the time horizon regarding the assessment of propulsion systems can differ from system to system. Thus, considerable know-how of the development of individual technologies and markets is required when conducting the assessment.

The term alternative propulsion system refers to the use of alternative fuels or alternative engines. Petrol, (bio) diesel, (bio) gas, Liquefied Petroleum Gas (LPG), synthetic fuels and alcohols can be combined with combustion engines and hybrid engines whereas electricity can be combined with electric and hybrid engines. Hydrogen can be used for all three types of engines.

4

3

CHALLENGES OF THE ASSESSMENT

The assessment of different propulsion systems with respect to global sustainability and the suitability for a local area, e.g. an urban or rural area, is a challenging topic. In addition to the complex technical assessment, different stakeholder perspectives, life cycle phases as well as evaluation dimensions and time horizons have to be considered. First, the assessment has to incorporate different views on assessment criteria. For example, when evaluating propulsion systems regarding costs, different types of costs are relevant for different stakeholders. Development costs are important for manufactures of propulsion systems, while costs for infrastructure development, e.g. the costs for energy supply, are crucial for the participating governments. Costs occurring during the operational use are relevant for customers. Thus, an assessment method has to reflect the preference profiles of different stakeholders. Second, the impact of different propulsion systems has to be considered regarding their impact in all life cycle phases with respect to the economic, ecological and social dimension. To structure the complex life cycle orientation, it is useful to refer to frameworks, such as the Model of Total Life Cycle Management and to include the different life cycle phases from product idea to disposal in the assessment [7]. Furthermore, life cycle orientation includes the intersection of two different life cycles such as the engine and the energy source in the case of propulsion systems (see Figure 2). In the use-phase of the engine the impact of the energy source has to be considered as well, e.g. impacts resulting from the production of electricity when assessing electric vehicles. life cycle of the fuel life cycle of the engine

ASSESSMENT METHODOLOGY

An assessment of alternative propulsion systems requires methods in which different criteria can be incorporated. For that the field of Multi Criteria Decision Making (MCDM) provides Multi Attribute Decision Making (MADM) and Multi Objective Decision Making (MODM) methods. MADM methods are suitable for problems with a given number of alternatives, MODM methods are used for an infinite number of alternatives [8]. Within this study the MADM method AHP has been chosen to identify a propulsion system which is suitable for a distinct area. AHP was developed by Saaty [9] and relies on a five step procedure: (1) construction of a hierarchy, (2) pairwise comparisons of all elements, (3) determination of priorities, (4) verification of consistency, and (5) aggregation of the results. If the result of step (4) is not satisfactory the process must be revised starting from (2). Thereby comparisons should be reconsidered and possibly more information should be requested [10] [11]. Step 1 – Construction of a hierarchic structure The elements related to the decision making problem are arranged in a hierarchical structure resulting in a composition made up by the central goal, the assessment criteria and the alternatives to be ranked. Figure 3 shows an example of such a hierarchy. Starting with the goal at the top of the hierarchy tree, the decision problem is broken into clusters of criteria and sub criteria on the lower levels concluding with the alternatives at the bottom. The depth of the structure has to be chosen to suit the problem as it is the goal to give an overall view of the decision problem and to allow a comparison of elements of equal importance. Step 2 – Pairwise comparisons of all elements Pairwise comparisons are conducted by the decision maker to generate matrices of which the principal eigenvector is determined to derive priorities for each element. These comparisons are supposed to be made with the scale shown in Table 1. Comparisons are conducted on all elements of a cluster with respect to the parent criterion using integers or fractions. For a criterion the pairwise comparison indicates its importance with respect to the other criterion. For alternatives the comparison expresses the ability to fulfill the criterion. Whenever possible, the comparisons of alternatives should be based on reliable data which is proportional to desirability. If such information cannot be obtained then personal judgments can also be conducted using SAATY’s assessment scale.

Figure 3 : Hierarchy with four levels [9]. Figure 2 : Considering the impact of primary and secondary product [7].

Automotive Life Cycle Engineering Scale

53

Definition

Explanation

1

Equal importance

Two activities contribute equally to the objective

3

Moderate importance of one over another

Experience and judgment favor one activity over another

5

Essential or strong importance

Experience and judgment strongly favor one activity over another

7

Very strong importance

An activity is strongly favored and its dominance demonstrated in practice

9

Extreme importance

The evidence favoring one activity over another is of the highest possible order of affirmation

2, 4, 6, 8

Intermediate values between the two adjacent judgments

When compromise is needed

Table 1: Assessment Scale by Saaty [9]. Step 3 – Determination of priorities Three different types of priorities can be distinguished: local, global and total (or final) priority. Local priorities represent the importance of elements with regard to the next higher level and are obtained by solving the eigenvector problem of the matrices found in step 2. Global priorities give the importance of an element in the overall context of the hierarchy. To determine the global priority of an element, the local priorities of all elements leading directly up to the goal have to be multiplied. The final priority expresses the ranking or the score of the alternatives. Step 4 – Verification of consistency A distinguishing feature of AHP is the verification of the consistency of the information entered by the decision maker. This step ensures coherent data. Due to the comparisons, a consistent matrix is improbable when applying AHP even if only a few criteria are compared. In order to verify the inconsistency of a matrix, SAATY defined a ratio that expresses the percentage to which the result equals the outcome of a probability distribution. According to him an inconsistency ratio of 10 % is acceptable because it allows new information that might be added to have an impact on the decision. Step 5 – Aggregation of results In order to obtain the total priority, every path from the goal down to the alternative has to be considered. Starting at the top the global priority of the parent element is multiplied with the local priority of the element below. These products are added up until the last level is reached. By aggregating all results from each path, the final priority of each alternative can be determined. The ranking of the alternatives represents the preferences of the decision maker. 5

CRITERIA CATALOGUE FOR ASSESSING ALTERNATIVE PROPULSION SYSTEMS

To assess alternative propulsion systems with AHP, a criteria catalogue is needed. The presented criteria have been derived either from existing approaches used in previous assessments or from lists of criteria illustrating future requirements of fuels and engines, such as [1], [3], [4] and [12] to [18]. It includes the characteristics of alternative fuels and engines, the market situation and surrounding conditions in order to cover the wide range of influences and aspects of alternative propulsion systems. The criteria catalogue is presented in Table 2. It comprises the identified main and sub criteria which are relevant for the decision making process as well as a brief description. The structure of the assessment criteria includes four levels: At the top of the hierarchy is the goal of the decision process, i.e. the assessment of alternative propulsion systems. The second level

Assessment criteria

Description

Safety Fire safety Explosion safety Electrical safety Toxicity safety Environmental impact

Risks regarding fire Risks regarding explosion Risks regarding electric shock Risks regarding toxicity

Sound / noise Global warming Photo-oxidant formation Eutrophication Acidification Resource consumption Land use Economic Impact Cost of the propulsion system Costs for infrastructure development Economic benefit Availability Resource availability Infrastructure availability Staff availability Food availability Performance & capability Cruising range Performance Torque Speed Life span Temperature sensitivity Fuel Sensitivity User acceptance Useable space Intuitive operation Refuel rate

Noise (sound), which are harmful or disturbing by their volume and structure to humans and the environment. Increase in the average temperature Contamination of the atmosphere Overfertilization of an eco-system Reduction of ph-value in an eco-system Type and number of resources consumed Need of land Total costs of the development, production, distribution, usage, redistribution, recycling of the propulsion system, etc. Total costs of gas stations, supply networks, workshops, training, roads, reverse supply chains, etc. Employment, gross domestic product, welfare, etc. Access to technical and / or economically recoverable resources Existence infrastructure to bring the resources to the place of usage (gas stations, roads, workshops, …) Existence staff (workers, engineers, …) Conflicts regarding food Range per volume, range per kilogram Technical capability Max. torque Max. speed Deterioration, max. life, max. charge cycles, etc. Performance at different ambient temperatures and operating temperatures Performance with different fuels Possible reduction of cabin or trunk size Simple use, repairable Duration of charging, duration of the refueling

Table 2: Criteria for assessing alternative propulsion systems. contains six main criteria: safety, environmental impact, economic impact, availability, performance and capability as well as user acceptance. Each of these criteria is divided into sub criteria. For example, the main criterion environmental impact includes noise, global warming, photo-oxidant formation, eutrophication, acidification, resource consumption and land use. On the fourth level, these effects are divided into the different life cycle phases of a propulsion system (see Figure 4) as mentioned in chapter three. On this basis, decision makers start the weighting of the criteria according to their preferences as described in chapter four. Decision makers can be individuals as well as interest groups on the one hand or a group of people evaluating simultaneously on the other hand. The scoring of different propulsion systems is evaluated with respect to their characteristic regarding each individual criterion. This requires expertise of the decision maker or wellgrounded data on the performance of different propulsion systems. 6

CASE STUDY: ASSESSMENT OF ALTERNATIVE PROPULSION SYSTEMS IN INDIA

The proposed criteria catalogue will be used for the assessment of two propulsion systems for CNG and biodiesel made from jatropha as both fuels are currently promoted in India. As an example, the view of the Indian government is elaborated in detail. The perception is obtained from public available literature as indicated in the following section. Likewise, the views of the customers and manufacturers in India are derived from [20], [21] and [23].

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Automotive Life Cycle Engineering

Safety Environmental impact Economic impact Availability Performance & Capability User acceptance

Safety

Environ. impact

Econ. impact

−

1/5

1/4

1/3

9

9

5

−

2

4

9

9

4 3

1/2 1/4

− 1/2

2 −

9 9

9 9

1/9

1/9

1/9

1/9

−

1

1/9

1/9

1/9

1/9

1

−

Avail.

Perf. and Cap.

User accept.

Table 3: Weighting of main criteria by government. Figure 4 : Four level structure of the criteria catalogue. Problem description – CNG vs. biodiesel in Dehli The urban traffic situation in emerging countries faces major challenges. Problems like environmental and noise pollution, fatalities and injuries as well as congestion and other mobility problems are much more severe compared to Northern America or Europe. Several reasons contribute to this situation. The rapid growth of the population combined with often uncontrolled urbanization has overpowered many cities. The demand for transportation by far exceeds the capacity which can be provided. Choosing a non-motorized mode of transportation like walking or cycling is often very difficult and dangerous urging people to choose motorized vehicles [19], [20]. Even though the city of Delhi still faces difficulties, improvements have been made. In 2003 the Indian capital was awarded the Clean Cities International Award by the U.S. Department of Energy because of the immense attempt to decrease pollution [21]. In the beginning of the 1990s India’s Ministry of Environment & Forests started a series of efforts to ameliorate air quality. More rigorous emission standards for vehicles, the withdrawal of old, ill-maintained vehicles, the introduction of CNG and higher quality fuels as well as the construction of the Metro Rapid Transport Service are some of the changes introduced [19]. To make further progress and improve air quality the next step would be to change the current fleet to newer, less polluting vehicles. However, the negative impact of banning older and more polluting vehicles could be immense. Many residents depend on their mobility to reach their place of work and would not be able to afford newer vehicles [20]. Against this background biodiesel is currently also promoted in India. The government targets a blend of 20% biodiesel and 80% fossil diesel by 2011-2012. In this process the plant jatropha has been identified as a potential feedstock for biodiesel because it has several advantages. Jathropha is a shrub which makes harvesting easier in comparison to trees. The plant has a short ripening period which makes it less time consuming to grow. In addition, the seed collection is not in the monsoon period like most other plants. Thus, it allows farmers to generate an income in a time during which they usually have less work and less income. It is furthermore very robust and not edible. Hence, animals do not feed on the plant [22]. The question arises whether the use of both fuels, CNG and biodiesel from Jatropha, is meaningful or if one alternative is much more favorable than the other. Pairwise comparisons of criteria In this case study CNG and a diesel blend of 20% biodiesel made from jatropha and 80% fossil diesel are compared. In order to demonstrate the weighting of criteria, pairwise comparisons of the main criteria are displayed for the governmental view in Table 3. As stated above the measures which have been taken so far show that the government is willing and able to invest in the transport sector to decrease impacts on the environment. Thus, a special

interest in environmental concerns can be deduced [21]. The automotive industry has also been identified as an important part of the nation’s economy and the Automotive Mission Plan sets goals for the years of 2006 to 2016 to strengthen this sector of the economy. Hence, it can be assumed that economic aspects of the automotive industry are of high importance to the government. The availability of resources and labor play a crucial role in the success of economic ambitions and are ranked accordingly [23]. Safety issues of propulsion systems are currently not targeted essentially as many other sources of danger are of larger amplitude. The number of fatalities is rising because the traffic system in general is mal controlled [20] [23]. The criteria performance & capability as well as user acceptance are assumed to be of marginal importance for the government. Likewise pairwise comparisons are conducted for all sub criteria in order to derive the local priorities for each element. Pairwise comparisons of alternatives To finalize the assessment, the two alternatives CNG and biodiesel must be compared with regard to all sub criteria. For reasons of clarity the sub criteria are reduced to the second level in this case study. Thus, the assessment includes a life cycle consideration whenever possible and reasonable. Table 4 shows the results of the pairwise comparisons with respect to each sub criterion from the governmental point of view. Regarding safety, the danger of fire is higher in the case of liquid fuels because it spreads on surfaces and cannot evaporate as fast as gas. In contrast, gas is more likely to explode which requires special security measures. With respect to the electrical hazard there is no indication that one propulsion system is more dangerous than the other. However, the two substances differ significantly with respect to their hazardous effect. On the one hand natural gas has no active toxic effects on humans but it can cause affixation because it lowers the oxygen content of air [24]. In addition, it cannot be seen or smelled if no odorants are added. On the other hand the diesel blend is toxic even though biodiesel is less toxic than fossil diesel [25]. In total, CNG and the diesel blend are considered equal with respect to toxicity. Regarding the environmental impact, the combustion of the diesel blend is considered better than the use of CNG in the categories global warming and the use of resources [26] [27]. A gas engine has less harmful effects in the categories eutrophication, acidification[26] [27], photo-oxidant formation [27] [28] and land use. Regarding the category noise, only differences in the use phase are considered. A gas engine is considered less noisy than a diesel engine [29]. With respect to the costs of the propulsion system, it is assumed that differences occur only in the operational use as the engines are comparatively similar and equally mature. The cost for CNG in Delhi is lower compared to a blend of fossil diesel and jatropha diesel [22] [30] while the costs of the vehicles are very similar [31]. Thus, a natural gas vehicle is considered superior. For the development of the infrastructure elaborate programs are necessary. For example, the government plans to establish 2500 nurseries for jatropha

Automotive Life Cycle Engineering

55

plants. Furthermore, farmers must be educated and the genetic properties of the plant must be improved [22]. In contrast, natural gas is readily available [32]. Hence, it can be concluded that the cost of infrastructure development is higher for biodiesel because the required measures are much more elaborate and comprehensive. This implies that the economic benefit for the country is higher because it offers new possibilities for farmers and support for research and development [22]. With respect to the use of resources natural gas is preferred. Natural gas is made completely out of fossil resources, the diesel blend to 80%. However, natural gas is preferable because India has much larger supplies of natural gas than of crude oil [33]. Also the production of jatropha diesel is not on a commercial level, yet [22]. With regard to the availability of the required infrastructure and staff the diesel blend is preferred because it can use all systems already present. Both fuels do not compete with food as long as jatropha is not cultivated on land that is intended for food. The technical properties of the two fuels are very alike [1], [34]. However, comparing the cruising range and fuel sensitivity an engine using diesel blend is superior. The cruising range of a CNG vehicle lies in between 200 and 300 km [3], whereas the diesel blend reaches values very similar to fossil diesel. Diesel blends of different rations can be used in the same engine without alterations allowing flexibility in the choice of fuels [35]. With regard to the criterion user acceptance, it can be assumed that the diesel blend is more user friendly than the gas engine. Both can be operated intuitively but the CNG tanks reduce the usable space in the vehicle. Additionally the refuel rate with gas is slower [3].

Criterion

Diesel blend: CNG

Safety

Criterion

Diesel blend: CNG

Availability

Fire safety

1/3

Resource

1/2

Explosion safety

3

Infrastructure

4

Electrical safety

1

Staff

4

Toxicity safety

1

Food

1

Environmental impact

Performance and Capability Cruising 4 range

Noise

1/3

Global warming

3

Power

1

Photo-oxidant formation

1/2

Torque

1

Eutrophication

1/9

Rotational speed

1

Use of resources

5

Life span

1

Acidification

1/7

Use of land

1/7

Economic impact Cost of propulsion system Cost of infrastructure development Economic benefit

1/4 1/3 5

Temperature sensitivity Fuel sensitivity User acceptance Intuitive operation Useable space Refuel/ reload rate

1 4

1 4 3

Table 4: Comparison of the performances of biodiesel and CNG.

Aggregation of results

7

In order to obtain the total priority every path from the goal down to the alternatives has to be considered and the values have to be aggregated. The resulting ranking of the alternatives is presented in Figure 5. It represents the preferences of the stakeholders regarding CNG and the diesel blend. The values of all different groups have been calculated in the same way as demonstrated.

Within this study an assessment of alternative propulsion systems using the AHP methodology was presented. The underlying criteria catalogue was derived from existing approaches used in previous assessments and the analysis of alternative fuels and engines, the market situation and surrounding conditions. Thereby, a wide range of influences and aspects of alternative propulsion systems are covered. The criteria catalogue provides the possibility to assess alternative propulsion systems from economic, ecological and social perspectives on a qualitative level. Inherent in AHP is the possibility to consider preference profiles of different stakeholders. Furthermore, the impact of propulsion systems across the entire life cycle and the impact of secondary products are considered as well. The presented methodology is usable for all presented alternative propulsion systems. Its application was shown by an assessment of two different propulsions systems.

Figure 5 shows that CNG is preferred slightly by consumers and the government whereas the manufacturer has no preference regarding the alternatives. Indian consumers prefer CNG as they are very price sensitive and the operational costs for CNG are lower in comparison to the diesel blend. From the governmental perspective the main reason for preferring CNG is smaller local environmental impact regarding photo-oxidant formation, eutrophication, acidification and use of land. However, all values alternate around the value of 0.5. Thus, it can be assumed that no alternative dominates the other. The result of the comparison shows that the diesel blend can be an alternative when considering global environmental impact as it reduces the global warming potential in comparison to CNG. However, neither of the two alternatives will lead to a break through regarding the challenges of urban traffic in India. Thus, further alternatives need to be considered and assessed to make further progress in the areas of sustainability and air quality in Delhi.

Total priority

CNG

diesel blend

0,5

SUMMARY AND OUTLOOK

As stated above (see chapter 3), the assessment of propulsion systems with respect to different time horizons is challenging. It is conceivable that an assessment of propulsion systems for 2015 differs from an assessment for 2025. This leads to uncertainties and requires considerable know-how regarding the development of technologies and markets. Although AHP allows for conducting sensitivity analyses these uncertainties are not reflected adequately with the proposed method. A distinct project focus of the BMBF funded project STROM, Strategic options of the automobile industry for the migration towards sustainable propulsion systems in established and emergent markets (www.strom-sustainability.de), is therefore to incorporate insecurities such as the maturity of the technology in the decision making process. For this purpose, methodological support will be developed in future.

0

8

Figure 5: Total priorities of CNG and Biodiesel.

The presented research work is partially financed by the German Federal Ministry of Education and Research (BMBF) and the German Academic Exchange Service (DAAD). The authors would

Government Manufacturer Customer

ACKNOWLEDGEMENTS

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Automotive Life Cycle Engineering

like to acknowledge the support of the BMBF for funding the research project “STROM - Strategic options of the automobile industry for the migration towards sustainable propulsion systems in established and emergent markets” under the reference 01UN1006A and the DAAD for funding the research cooperation “Lean and Green – A new passage to India” under the reference 50082745. 9 [1]

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Concept and Development of Intelligent Production Control to enable Versatile Production in the Automotive Factories of the Future 1

1

1

Sarfraz Ul Haque Minhas , Christian Lehmann , Ulrich Berger 1

Chair of Automation Technology, Brandenburgische Technische Universität, Cottbus, Germany

Abstract The automotive industry is being confronted with numerous challenges among which the increased product customization, short product life cycles and faster time to market are inducing a lot of complexities in controlling the current production systems. Consequently, the production systems are incapable of handling changing product variety and volume in a productive way and often involve intensive redesigning and reconfiguration processes. This paper introduces the concept of versatile production setups, an intelligent approach for selecting appropriate resources and optimal parameter settings to enable fast changeability as well as for reducing quality assurance time to achieve productivity in production processes. Keywords: Versatile Production Setups; Plug and Produce; Reconfigurability Ease

1

INTRODUCTION

The European manufacturing industry particularly the automotive industry has entered a new era in which they have to compete in a global economy. This has led them to confront many challenges like fast globalization, unpredictable and heterogeneous markets, increased product customization [1] [2], short innovation and product life cycles [3], reduced development time and faster time-to -market. This situation has induced a lot of complexities in controlling the current production systems [4] by imparting negative influence on productivity. Moreover, the increase in derivatives of vehicle models and growing trend towards the integration of new materials in the car Body-in-White development to enable reduction in weight and fuel consumption as well as the eco-efficient design, the quest for new and advanced material processing and production technologies has increased. This trend can be observed from the fact that multifunctional materials [5] as well as light weight materials [6] are being integrated into the car Body-in-White to make the manufacturers more competitive. Consequently, the future automotive production systems have to handle a huge variety of materials as well as various products of individualized geometries. The current production systems are quite flexible in switching from one variant to another however they are not capable of handling their high variations in a productive manner. The main reason is that the changing product design and integration of new materials are pushing the manufacturers to redesign/modify their production setups. It has led to a situation in which they will have to rely heavily on the system developers/suppliers for redesigning/upgrading their production facilities. This increased reliance will hinder them to achieve higher production rates. This is because the production system redesigning/upgrading is highly time consuming and cost intensive process. Currently about 75% of the vehicle production and 50% of automotive research and development is being done by suppliers and technical consultants [7]. The rapid customization and reduced product life cycle [8] demands from the manufacturers to configure their production system in the shortest possible time to enable fast ramp up of materials and technologies. It also requires achieving smooth and

effective production control in order to reduce production costs and time substantially. Moreover, it also demands them significant improvement of their production processes as well as the product quality. 2 2.1

AUTOMOTIVE PRODUCTION CONTROL: LIMITATIONS AND ANALYSIS Mass Customization: A challenge for the Production

Nearly every European automotive manufacturer is experiencing increased product complexity and reduced lifecycle time, whilst manufacturing a larger number of variants within shorter time-tomarket. A dramatic shift from production-push and economy of scale towards customer-pull and economies of scope is a solution to these problems. The current situation of product customization in the automotive industry is mainly attributed to the creation of new production segments and enrichment of existing ones with more possibilities for their individualization. The idea of platform sharing among different models has enabled the automotive manufacturers to offer a much wider range of product families, with different appearances and styles. On contrary to that, the migration principle [9] is helping certain automotive manufacturers to produce many models with additional variants from different OEMs. In this context, the shift towards development of Body-in-White on modular and scalable concept aims at offering broader range of customized products whilst maintaining low development costs. It concludes that the product development process is mainly accompanied by design reuse i.e. by taking more carryover of parts or by platform sharing for various vehicle segments. Additionally, the product development and process planning of diversified products is enabled with the help of powerful CAD/CAM and PLM systems. However, the handling as well as production of these products in the production setups is still a bottleneck. This situation occurs due to frequent variation in product features and materials, and the respective inappropriate adaptation, thereby generating internal complexities in the production systems. The state of the art automotive production process comprises of the technologies for

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_10, © Springer-Verlag Berlin Heidelberg 2011

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manufacturing diversified components and technologies for joining/or assembling them to complex customized products. A clear analysis of their production setups shows that they are mainly dedicated to the process (machining/joining/assembly) technology for which they are designed. A typical example is the production setup for welding automotive Body-in-White components. It is dedicated to weld automotive components of specific material combinations and certain range of dimensions only. Similarly, the production setups for joining technologies other than Welding e.g. adhesive bonding is dedicated for joining automotive components of specific material combinations and dimensions. The increasing multifunctional and light weight materials (as mentioned already) with changing Body-in-White shapes have influenced significantly, the automotive production setups by integrating various forming, joining and assembling technologies/techniques. It has not only increased the size of automotive production setups but also the complexity in its control. The increase in size of automotive production setups has compelled the automotive manufacturers to expand their production facilities which are hindered by limited and costly space requirements. The best option left in this situation is to allow reconfiguration of production setups by making them adaptable for other technologies and to achieve systematic reconfiguration process from their design to the job sequencing at the shop floor thereby implementing intelligent production control. 2.2

State of the Art Production Setups

The state of the art automotive production setups are comprised of various but distinct production/manufacturing cells connected to single/various lines. These production setups are quite flexible in handling various variants in their respective production setups. There exist two innovative categories of the production setups known as modular production setups and cellular production setups respectively. The modular production setups are relatively advanced setups that are designed to improve throughput by increasing the efficiency of parallel joining cell/subassembly lines feeding into the final assembly lines. They involve joining /assembling separate vehicle modules such as chassis, interior, body on their dedicated assembly lines connected with process dedicated joining cells [10, 11]. Another category refers to cellular layout based automotive production setup [12] which is considered as one of the major steps in accessing JIT. They are comprised of machines and robots gathered together to carry out multiple tasks such as material handling and welding typically run by single operator or a multi-person work cell. Each one of these setups exhibits the following complexities during their adaptation/reconfiguration:  

Limited flexibility in programming of industrial robots due to the manufacturer dependent programming environment, Offline verification of industrial robot programs which in high variation would limit the adaptation and consume lot of time, leading to high production time and cost,



Complicated synchronized implementation,



Large number of interfaces within the production cell and noncompatibility issues with the centralized controller,



Fixed but highly branched program (spaghetti code) execution corresponding to the sensor data inputs and



Large volume of measured data and the resulting difficulty in database connectivity with certain Human Machine Interfaces such as Personal Digital Assistants (PDAs) for fast and remote interaction.

simulation

of

robots

and

its

In addition to all these aforementioned complexities, there are also limitations to reuse the automotive production setups dedicated to one process technology for any other technology. For example, the

production cell dedicated for adhesive gluing of car windows is inflexible to incorporate other joining technologies. It implies that in future automotive factories, the extinction of any of the process technology will require redesigning of the associated production cell to be used for some other process technology. The upgrading process will be highly cost inefficient and time consuming which may last from several weeks to several months. Moreover, the input coming to the production system in terms of nature of jobs will be of very distinct nature that will involve distinct processes/operations for distinct Body-in-White components. As a consequence, the production ramp-up time as well as the setup time will rise sharply resulting in decrease in the production throughput and increase in time-to-market. A comprehensive approach is therefore needed to resolve those complexities that the future automotive production setups are foreseen to experience. It also requires eliminating those limitations that the current production setups are having. 2.3

Derivation of Requirements Production Control

for

future

Automotive

From the discussion above, it can be further added that the market conditions and required production efficiencies of today are keeping mass production an acceptable business model for the present automotive factories. This trend is being diminished in favor of mass customization. Therefore the future automotive production setups need to be highly reactive and productive in managing change. This change is characterized by variations of the product volume (high, medium, low) as well by variations in terms of materials, forms and dimensions. It is a noteworthy fact that these variations influence greatly on the design, planning and control of these production systems. Moreover, as the high product variety is the main complexity driver in planning and controlling of the production systems, the method for sequencing of the production tasks (jobs) to achieve optimal configuration of the production setups is needed considering reduction in ramp-up time of materials and technologies. Also, an intelligent concept for production control is required to achieve reduced setup time, fast throughput, quality assurance time and their associated costs. From the requirements, it is deduced that the production system must be designed on versatile architecture where it can support the intelligent production control. It is particularly important for optimal reconfiguration of production setups using the same resources for distinct processes or operations. The intelligent production control also requires the sequencing and reordering of jobs to attain high reconfigurability ease in reconfiguration of production setups. 3 3.1

CONCEPT FOR INTELLIGENT PRODUCTION CONTROL Concept for Versatile Production Setups

The concept of versatile production setups for automotive factories of the future is derived from the idea presented in [13] which identifies their structuring into seven levels. Moreover, the factory should be designed considering the changeability enablers (modularity, scalability, adjustability, universality, compatibility, mobility, convertibility etc.). The production design based on these enablers will address the impact of product variations and frequency (volume per certain amount of time) on the design of production setups. Therefore, the versatile production setups must be characterized by their adaptable functionality and scalable capacity. It can add, remove, and change/replace software and hardware modules to support a broad product range with required cost and quality. These hardware and software modules can be related to the cells, machines, process equipments, sensors, actors, handling and fixation units etc. Figure 1 highlights the essential

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features/attributes needed to enable versatile production based on reconfigurable control. Web

Automotive manufacturer

Production planning

Configurator interface Product sequencing

Layout definition

Product Design

Design rules, components/modules libraries, control programs

Digital Simulation

Production metrics (Production throughput, cycle time, collisions, offline robot programs)

Production setup controller (Parameter Settings) Production control

Product design, rules

Actual production metrics Control parameters of the defined layout

Technology data catalog

End customers

Production Setups (Process applications: Machining/Joining/Assembly)

Figure 1 : Modules and subsystems of versatile production setups. These essential features/ attributes are the following: i)

ii)

Integration of customer in product design process to analyze their demands and offer them best matching products. It can be achieved through web based collaboration or by employing other methods for analyzing the end user requirements. Introduction of an intelligent production setup configurator as an interface between the product design phase and the production planning phase named as Configurator interface. This configurator helps in optimizing the components and modules of the production system and the features that these production setups should contain and the functions that they should perform.

iii) Integration of knowledge base with the digital simulation to analyze the production related metrics well before the production layout is configured helps in achieving the production goals. iv) Introduction of production setup controller to enable configuration or reconfiguration of the production setups based on optimal scheduling of jobs intelligently. The optimization of production resources carrying the adaptable functionality (e.g. responsive to variable range product features, various materials) as well as the scalable capacity (adaptation to different range of tasks, production volumes) against a definite customization is mathematically modeled using the Axiomatic Design approach. Compared to other available designs approaches like TRIZ, axiomatic design methodology offers a generic framework and hierarchical structure to achieved precise and simple optimization of production resources. The methodology is used to analyze a certain range of product characteristics and the selection of corresponding optimal processing technology e.g. joining technology/assembly technology. The precision in optimal selection can be achieved provided the pure knowledge base approach is adopted. However, this approach will have limited implementation due to the complexity and level of effort needed to acquire domain knowledge as well as design knowledge. So a knowledge reuse up to an achievable level is extremely important to assist the automotive manufacturers in preventing any errors that may generate in the selection process. The technology data catalog is therefore introduced to serve this purpose. It acts as an intelligent subsystem of the versatile production system that stores the application-specific knowledge and provides the best practice settings in the reconfiguration process.

The concept of versatile production setups is implemented by considering the innovative joining processes in automotive Body-inWhite development. The concrete reason behind this consideration is the increasing integration of advanced materials besides aluminum and steel to support eco-efficient design of vehicles. Foreseeing this trend, the increase in material pool will also increase the number of joining technologies with limited scope. Currently, welding process e.g. laser welding is widely used automated joining technology in Body-in-White development and is delivering best quality joining. However, new materials are limiting its scope as it is applicable only to joining of similar materials. This in turn, has enhanced the exploitation of adhesive bonding in future joining applications. Therefore, versatile production setups must support various joining processes to be carried out using the same resources with minimum changeover. This changeover can be made in process monitoring, handling systems and the process equipment while executing the sequenced tasks using versatile production setups. 3.2

Concept for Production Planning and Control

The production systems of the future will experience immense level of complexities in production planning due to distinct characteristics of individualized products. Therefore, the production system needs to be reconfigured efficiently and precisely. The reconfigurable production planning and scheduling is divided into two phases. In the first phase, the reconfigurable production setup layout is to be defined followed by the allocation of production resources and their reconfiguration in the product sequencing phase. In the layout definition phase, the structuring of the resources is made in a way to accommodate a broad range of products using the same resources. This phase takes the input from the simulation and analysis module (see Figure 1) which also gives the evaluation metrics about the overall cycle time as well as the allocation to make the layout definition phase more precise. These metrics are evaluated to achieve high throughput by minimizing the buffer and transportation time of each part. The second part is the product sequencing phase where the products are sequenced optimally using intelligent algorithms. Each mass customized product has to be produced in the given product layout, therefore jobs specifications are analyzed and sequenced in a way to achieve high reconfigurability ease in the reconfiguration process. The high reconfiguration ease is dependent upon the variation in the product specifications that are to be manufactured at the particular production setup. A similar issue but from the other domain has been addressed in [14] for generating an optimized work plan based on feature technology in NC machine tools. A further extension of this work is already implemented and mentioned in [15] for planning and scheduling of machine operations. The perspective planning and machining operations are transferred into a directed graph. The results acquired after the implementation of the Floyd-Warshall algorithm [16] (Jungnickel, 1990) deliver "cost-efficient" sequencing order of the NC operations [17]. A similar methodology is adopted for the production domain i.e. in joining and assembly processes to achieve high reconfigurability ease. It is required that the intelligent production control implements the optimal parameter settings in versatile production setups and executes the tasks in a generated sequence from the planning module. The job sequencing based on high reconfigurability ease helps reduction of setup time and ensures high throughput from the production system. Additionally, it should also assist in reducing production costs and high process reliability and product quality.

60 4 4.1

Automotive Life Cycle Engineering DEVELOPMENT OF INTELLIGENT PRODUCTION CONTROL

4.2

Development of Versatile Production Setups

Development of Intelligent Production Planning and Control

The development of versatile production setups is initiated after the optimal selection of production setup components. The crucial factors that drive the optimal selection process are the desired production goals and set of customer demands. The optimization can be done through mathematical design approach i.e. the Axiomatic Design that translates customer requirements from the customer domain into the functional requirements (functional domain) and the designed parameters. The mapping process between functional requirements (FR) and design parameters (DP) is expressed mathematically in terms of the characteristic vectors that define the design goals and design solution.

After defining the versatile production setups, the optimal sequence and ordering of the jobs is done. In this process, the Technology Data Catalogue (TDC) which acts as a knowledge base provides all relevant applicable technologies corresponding to the joining tasks. The sequencing system has manifold access to the PPR (process, product, resource) hub to get information about the produced mass customized product and other relevant information such as materials, joining technique applicability and tolerances. The sequencing (see Figure 3) classifies joining cells as:

 FR1   X    FR2   0

0   DP1    X   DP2 

(1)

Some of the functional requirements from the functional domain are the following:



Capability: At this joining cell, the joining task can be executed



Incapability: At this joining cell, the joining task cannot be executed due to certain constraints (productivity issues)



Non-designated: The assignment of tasks at this particular joining cell is not possible at the desired allocation time; therefore this alternative branch will be assigned higher weight.



Selected: This particular joining cell is selected for sequencing along with parameter settings.

‫ܴܨ‬ଵ = respond to market quickly (delivery time)

Joining Layout

‫ܴܨ‬ଶ = perform joining operations for Body-in-White with high accuracy ‫ܲܦ‬ଵ = short setup time

Sequencing & Parameter Settings (PS)

‫ܲܦ‬ଶ = reconfiguration of the joining cell

I) Identifying the relevant process incapability

II) Determining the allocation

Joining cell with three alternative parameter settings Selected

III) Selecting the joining cell with parameter settings

Capability

Non-designated

Incapability

Figure 3 : Sequencing of product workflow in production layout.

Figure 2 : Versatile joining cell (conceptual and virtual model). The functional requirements are further decomposed at different levels to determine the detailed design parameters. The information axiom of the axiomatic design selects the appropriate components of the versatile production setups. The versatile production setup (versatile joining cell) is developed on modular and scalable architecture with plug and produce components to enable quick and error-free configuration/reconfiguration of the cell (see Figure 2). These components are related to process equipment, handling and process monitoring systems as well as actuators. For versatile joining cell, the changeover can be made from one joining technology to another, similar to the CNC machines where different machining operations are carried out by changing the tool. It means that the adhesive dispenser is replaced by laser welding head upon requirement considering the safety standards. The adhesive dispensing nozzles can be exchanged during the joining operation if adhesive beads of different forms and dimensions are to be applied. Variant flexible gripper adapts itself in case it has to handle parts of distinct forms and sizes.

The product information as well as the joining task is taken into the processes of the joining layout (see Figure 3(I)) with the help of the variant process planning documents which are stored in the PPR hub. At this point, the system can determine the capable joining cells that can contribute in accomplishing various joining tasks. The branches with the incapable joining cells are marked as nonsequenced. The capable joining cells with different parameter settings are then assigned. In the second step (see Figure 3(II)), the designation of each joining cell is checked for the desired allocation time. If the cell is not allocated, then the effort of the corresponding branch will be increased sharply provided that the other alternatives are incapable of doing the same task. In the third step, the effort of the remaining joining cells with concrete parameter settings is designated (III) with the help of introduced metrics. Thus, each parameter settings of every remaining joining cell are assigned with individual effort. The application of Johnson’s algorithms known from graph theory determines the sequence of joining cells with configuration that has in total the least sum of efforts (high reconfigurability ease). The sequenced work plan is used to process the mass customized products in the selected joining setup. The calculation of this optimal work plan can be done in realtime, because of the low runtime of algorithms.

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In the versatile joining cell, each of the joining tasks (JT) can be split into more than one sub tasks (ST). This is however, mainly dependent upon the type (form) of joining interface (JI) as well as its dimensions. Joining tasks (JT) can be mathematically described as n

JT   JSTi

(2)

i 1

A subtask in this particular case is defined as an activity performed in which no alteration is made in the configuration (related to hardware/software) of the subsystems of the joining cell. The joining sub task is a set of 7-tuple and can be mathematically described as JST= {M, T, P, HU, F, S, JI}

(3)

Where M= manipulator, T= technology, P= path, HU= handling unit F= fixture, S= sensoric, JI= joining interface It is important to mention here that every JST (3) provides the parameters of the joining process and can be named as changeover (reconfigurability) parameter setup. The production is controlled by quick reconfigurability (high reconfigurability ease) by taking up the products with minimum change in JT tuple parameter values between two consecutive tasks in the sequence as well as delivery time of the product. This concludes that the reconfigurability effort is strongly dependent upon the minimum change in JT tuple and the delivery time of the product. By this approach, the setup time of the joining cell is reduced significantly. 5

KR16 takes the subassembly floor module components and moves them under the stationary dispenser for adhesive application. The KR15 robot takes the glued components from the turn table and places it outside the joining cell (in a heating oven or conveyor). To achieve efficient reconfiguration, distributed control architecture is adopted in which the cell controller is separated from an additional controller. This additional controller is directly connected to the process sensors and actuators and handles the measurement data from the joining process separately to enable quick reconfiguration of process sensors and actors. The Cell controller is mainly responsible for controlling the sequential operation of the cell components. It is a standardized embedded controller SIMATIC S7 and is connected to the cell components over Profibus/ProfiNet as a standardized interface. The measurement controller is a programmable automotion controller from National instruments that provides the PC based functionalities. Its user friendly graphical programming environment i.e. Labview, is particularly suitable for analyzing measurement data as well as developing real time control programs in a short time. Hence, the fast configuration/reconfiguration of the cell is achieved. The on-process quality assurance is a highlighting topic of this development to control the adhesive bead form and position in real time scenario. The sensor actor head unit as a plug and produce device (see Figure 4 (b)) is an independent solution for online correction of the robot path and therefore can be reconfigured quickly.

TECHNICAL IMPLEMENTATION: VERSATILE PRODUCTION SETUPS AND PRODUCTION CONTROL

The scenario for the implementation of versatile production setups and respective reconfigurable control is based on production cell development for joining automotive subassemblies. The cell setup (hardware and software) is grouped into modules to achieve versatility in the setups. This means that the cell can be configured from adhesive bonding to laser welding in a very short time depending upon the material combinations selected as well as the required quality. The commonality between cell components required for both processes is determined to enable easy and fast configuration. The current state of the art joining cell is flexible in handling and fixturing systems only. The innovative aspect of the implementation is on versatile production setups in which different cell subsystems such as the process equipment, manipulators, handling units as well as monitoring unit are divided into modules and sub modules to allow easy replacement of components during reconfiguration. To lower complexity in first place, a semi automatic and modular adhesive bonding cell (see Figure 4(a)) is implemented to allow joining multi-variant subassemblies of automotive Body-in-White floor module components. The cell consists of KUKA KR 16 and KR 15 robots assembled around a turn table KUKA KPF1-MB1000. The KUKA KR 16 robot can be configured or reconfigured for two purposes. It can be a part of handling system to take the sub assembly (adapter and seat cross members) under the stationary process application head i.e. either adhesive dispenser or laser welding head. It can also be configured by either taking the adhesive dispenser or laser welding head to enable joining of parts. The process application unit i.e. adhesive dispenser can be reconfigured by exchanging various different nozzles (round, triangular, semi rectangular), allowing application of adhesive beads of variable forms and dimensions, thus enabling a wide range of subassemblies to be glued together in the same facility. The second robot KR15 can be used for transporting the material in or out of the cell as well as to the next cell. A turn table transports the subassemblies from one robot to the other. Additionally, it also serves as an extra axis to the robot to achieve application of adhesive on complex surfaces. The KUKA robot

Figure 4 : (a) Joining cell setup (b) Sensor-actor head unit. The independent solution in this context means that it can be attached to any robot type or installed on the stationary dispenser to influence the adhesive bead position and form. This solution saves time and associated costs involved in post visual checking processes that are currently carried out in adhesive and sealing applications in the automotive industry. Thus, there is a significant reduction of quality assurance time in Body-in-White joining processes in future. It is imperative to highlight that this particular setup supports the foreseen layout of the future automotive production setups in which production will be carried out in the reconfigurable cells. Moreover, the role of automated guided vehicles for material transport will be expanded as they will replace current conveyor systems. It will not only make them smart but also scalable to allow reconfiguration of factory space. 6

CONCLUSIONS AND OUTLOOK

The increasing new materials integration in automotive vehicles as well as the related processing technologies is reducing the life span

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Automotive Life Cycle Engineering

of automotive production setups. Furthermore, the reduced product life cycle and the faster delivery are also influencing negatively to the ramp-up of technologies and processes in the automotive industry. Therefore, the automotive industries of the future need versatile production setups to cope with the huge investment and the time involved in redesigning them. These setups are developed on modular and scalable hardware and software components. These components act as plug and produce devices and modules respectively, thereby enabling quick reconfiguration. The production setups design needs to be optimized based on the product requirements from the market. Axiomatic design methodologies through knowledge exchange from the technology data catalog can optimize the design of the versatile production setups. The intelligent production control approach handles changing product variety and volume in a productive way. This is done by intelligent planning of the resources to achieve optimize layout in the production system. This is followed by the product sequencing with minimum reconfigurability effort combined with optimal parameter settings of the versatile production. This concept is implemented on the versatile joining cell for joining Body-in-White components, achieving lower ramp-up time, setup time as well as quality assurance time, thereby elevating productivity. An extension to this work is of much wider scope in context of resolving mass customization induced complexities in future automotive production systems. The work aims at reaching an efficient level of decentralization in production. Therefore, the productivity will be enhanced by configuring the production system through web based collaboration mechanism. 7

ACKNOWLEDGMENTS

The work reported in this paper is regarded as a part of dissemination activity and is supported by European Commission FP6 NMP Program, "Integration Multi-functional materials and related production technologies integrated into the Automotive industry of the future" (FP6-2004-NMP-NI-4-026621). A further development that is currently being made on this work will be supported in future by EC FP7 Factories of the FUTURE Research Project e-Custom "A Web-based Collaboration System for Mass Customization" (NMP2-SL-2010-260067), to control production systems through web based collaboration among its participating actors. 8

REFERENCES

[1]

Molina A., Rodriguez C. A., Ahuett H., Cortés J. A, Ramirez M., Jiménez G., Martinez S. (2005): Next-generation manufacturing systems: key research issues in developing and integrating reconfigurable and intelligent machines, International Journal of Computer Integrated Manufacturing, vol. 18, no. 7, pp. 525-536.

[2]

Gerwin D., Barrowman N. J. (2002): An evaluation of research on integrated product development, Management Science, vol. 48, no. 7, pp. 938-953.

[3]

Mallick D. N., Schroeder R. G. (2005): An integrated framework for measuring product development performance in high technology industries, Production and Operations Management, vol. 2, no. 14, pp. 142-158.

[4]

Blecker T., Abdelkafi N., Kaluza B., Kreutler G. (2004): Mass customization vs. complexity: A Gordian Knot?, Proceedings of 2nd International Conference "An Enterprise Odyssey: Building Competitive Advantage" pp. 890-903.

[5]

Salonitis K.,Pandremenos J.,Paralikas J., Chryssolourics G. (2009): Multifunctional Materials Used in Automotive Industry: A Critical Review, Engineering Against Fracture: Proceedings of the 1st Conference, Springer Science & Business Media B.V.

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Goede M., Stehlin M., Rafflenbeul L., Kopp G., Beeh E. (2009): Super Light Car-lightweight construction thanks to a multi-material design and function integration, Journal of European Transport Research Review, vol. 1, no.1, pp.5-10.

[7]

Christensen T. B. (2009): Integration of Environmental Technology in Modularized Production Systems in the Automotive Industry, Proceedings of Joint Action on Climate Changes conference.

[8]

Kuhn, A. (Editor), Wiendahl, H.-P., Eversheim, W., Schuh, G. (2002): Schneller Produktionsanlauf von Serienprodukten, Ergebnisbericht der Untersuchung (Fast Production startup from serial production, Findings from the investigation) "fast ramp-up", Dortmund: Verlag Praxiswissen.

[9]

Meichsner T. P. (2009): Migration Manufacturing – A New Concept for Automotive Body Production, Book Chapter in Changeable and Reconfigurable Manufacturing Systems, pp. 373-387.

[10] Marinin K. J., Davis T. R.V. (2002): Modular assembly strategy in international automotive manufacturing, International Journal of Automotive Technology and Management, vol. 2, no. 3-4, pp. 353-362. [11] Fredriksson P. (2002): Modular assembly in the car industry an analysis of organizational forms’ influence on performance, European Journal of Purchasing & Supply Management, vol. 8, no. 4, pp. 221-233. [12] Kirk S.,Tebaldi E. (1997): Design of robotic facilities for agile automobile manufacturing, Journal of Industrial Robot, vol. 24, no. 1, pp. 72-77. [13] Wiendahl H.-P., ElMaraghy H.A., Nyhuis P., Zäh M.F., Wiendahl H.-H., Duffie N., Brieke M. (2007): Changeable Manufacturing - Classification, Design and Operation, CIRP Annals - Manufacturing Technology, vol. 56, no. 2, pp. 783809. [14] Cai, J., Weyrich, M., Berger, U. (2005): Ontological Machining Process Data Modelling for Powertrain Production in Extended Enterprise, Journal of Advanced Manufacturing System (JAMS), vol. 4, no. 1, pp. 69-82. [15] Berger, U., Kretzschmann, R. (2007): Development of a holistic guidance system for the NC process chain for benchmarking machining operations, Proceedings of the 12th IEEE Conference on Emerging Technologies and Factory Automation. [16] Jungnickel D. (2008): Graphs, Networks and Algorithms, 3rd ed., Springer. [17] Hamelmann S. (1996): Systementwicklung zur Automatisierung der Arbeitsplanung (System development for the automation of work planning), Fortschriftberichte VDIReihe 20 Nr. 195, VDI Verlag Düsseldorf.

Resource Efficiency – what are the Objectives? Marko Gernuks 1

1

Volkswagen AG, Group Research Environmental Affairs Product; Wolfsburg, Germany

Abstract This paper shows that resource efficiency pursues the three objectives reducing environmental impacts, improving supply security and saving costs. Firstly, a differentiation is established between objectives and measures to achieve them. Secondly, methods to assess improvements relating to these objectives are discussed and applied to the case study of vehicle lightweight design. The presented example of substitution of steel by aluminum illustrates that trade-off between objectives may occur. Thus, a reliable assessment of measures to enhance resource efficiency must consider impacts on each objective separately. An aggregation to only one resource efficiency indicator lacks transparency and is not appropriate. Keywords: Resource Efficiency; Life Cycle Assessment; Methodology

1

INTRODUCTION

There is general agreement regarding the importance of resource efficiency, and almost every company can point to resource-efficient products. But more detailed discussion reveals that resource efficiency has many different meanings, which vary depending on the particular standpoint. In a range of presentations and publications, techniques such as substitution, recycling, lightweight design etc. are presented as resource-efficient, even though no commonly accepted definition of the term exists, as yet. This paper does not intend to provide a definition of resource efficiency, but aims to clarify the objectives of resource efficiency. The term "resources" as used here refers to non-energetic raw materials. Furthermore, the challenges of defining appropriate assessment indicators for resource efficiency are described and aspects that have to be taken into account are discussed. 2

OBJECTIVE OR MEASURE?

In the absence of general agreement on what resource efficiency really is, no differentiation has yet been established between resource efficiency objectives on the one hand and measures to achieve them on the other. Taking recycling as an example, it is first necessary to ask the question – why recycle? Why is it desirable to strive for closed-loop material use? Essentially the assumption is that closed-loop recycling will have a reduced environmental impact compared to primary production. Cost savings are also expected, as well as enhanced resource supply security. It follows from this that recycling is a measure to achieve the objectives: 

reducing environmental impacts,



improving resource supply security, including lowering import dependency, e.g. for metals, and



cost savings in production.

Besides recycling, other potential measures to achieve the above-

mentioned objectives include substitution, extended product lifetime or use of renewable raw materials. But none of these measures are objectives themselves, as it makes no sense to recycle material without reducing environmental impacts, improving supply security or saving costs. Taking the proposed differentiation between objectives and measures as a basis, as a next step a framework for the assessment of resource efficiency can be developed. I.e. measures can be assessed with regard to their efficiency in achieving improvements with regard to the three objectives. The following sections discuss challenges with regard to the respective assessment procedures and provide proposals as to how to tackle these. 3

ASSESSMENT OF ENVIRONMENTAL IMPACT

An important aspect in assessing environmental impacts is the definition of system boundaries. For raw materials often only the impact of the production phase is considered when performing such assessments. However, materials choices may significantly influence environmental impacts during the product use phase as well. This can be demonstrated by the practical example of lightweight vehicle design (cf. Figure 1). The aim of the car manufacturers is to reduce vehicle weight in order to reduce fuel consumption and thus also CO2 emissions. In this context the substitution of steel by the lightweight material aluminum is a promising measure. Depending on the specific vehicle part that is substituted by aluminum, a weight reduction of 10 to 40% compared to steel is possible [1]. At first sight, this might be thought to represent a big improvement in resource efficiency. Looking at the CO2 emissions during production, however (Figure 1), it becomes clear that aluminum causes significantly higher CO2 emissions than steel at this stage, even if the full lightweight design potential of 40% is realized. If the system boundaries were restricted to material production, steel would clearly be the preferable alternative to aluminum. However, a

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_11, © Springer-Verlag Berlin Heidelberg 2011

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[kg CO2-eq] 20

Production

Use phase

15

10

5

0

Aluminum Aluminium Steel Stahl Steel (1 kg)

Al Al Al (1 kg) (0.8 kg) (0.6 kg)

0 km

150,000 km

Figure 1: Greenhouse gas emissions of lightweight vehicle design based on replacing steel with aluminum (data source: GaBi 4.3). broader view taking into account the entire life cycle, including production and the product use phase, reveals a different picture. A 40% weight reduction would result in the additional CO2 emissions from aluminum production (compared to steel) being offset in the course of the product use phase. If only a 20% weight reduction were implemented, a break-even would not be achieved within the assumed lifetime of 150,000 km. From this example two conclusions can be derived: 1. Materials that cause higher emissions in production can nevertheless be environmentally beneficial overall, due to advantages during the product use phase. 2. No material is inherently "good" or "bad". It depends on the specific application of the material, and thus a case-specific analysis is indispensable. In this example the realized weight reduction when substituting steel by aluminum is crucial. Apart from the definition of system boundaries, for the assessment of environmental impacts it must be decided what impacts to take into consideration. As well as looking at greenhouse gas emissions (measured in kg CO2-equivalent), cf. Figure 1, further impacts such as acidification, photochemical ozone creation or land use should also be taken into account for a full assessment of environmental performance. For all these topics the ISO standard 14040 and 14044 for Life Cycle Assessment [2] provides very sophisticated and clear guidelines. Certainly, LCA studies based on ISO 14040 require a considerable effort, but the procedure is indispensable for a reliable assessment of the environmental impacts of raw materials and their applications. 4

ECONOMIC ASSESSMENT

As with the assessment of environmental impacts, for the economic assessment too system boundaries must be defined. This is very much dependent on perspective. For companies, the economic assessment might at first sight appear straightforward. Raw materials prices are readily available. Taking the example of aluminum versus steel, aluminum results in

significantly higher costs: steel prices recently stood at around € 0.60 per kg [3] whereas aluminum cost about € 1.7 per kg [4]. Taking the 40% weight reduction into account, 0.6 kg aluminum would still cost € 1. In this simple economic comparison steel would be preferable. However, again this is only part of the story. In car manufacturing, further economic aspects must be taken into consideration – for example the cost impact of different body-in-white assembly technologies. In addition to production costs alone, depending on the perspective of the analysis more comprehensive approaches may be appropriate when making the economic assessment. For instance, the Total Cost of Ownership (TCO) approach could be of interest from the standpoint of customers. The probable higher price of a car with more aluminum parts might be economically acceptable if lower costs during utilization, due to lower fuel consumption, would lead to lower total costs over the life cycle as a whole. 5

ASSESSMENT OF RESOURCE SECURITY

In the current debate on resource efficiency, it is often claimed that it is necessary to reduce resource consumption due to the increasing scarcity of raw materials. However, geologists from various European countries who were part of the European expert group on defining critical raw materials concluded that in general there is no geological scarcity of raw materials [5]. Nevertheless, raw materials prices have increased enormously over recent years and the reasons must be examined. In cooperation with the Federal Institute for Geosciences and Natural Resources (BGR) Volkswagen has developed a methodology to assess raw materials risks [6]. This comprises 5 risk indicators: 

Current supply / demand situation,



Raw material production costs,



Geostrategic risks,

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65



Risk through mining company concentration, and

6



The future trend in supply / demand.

For the implementation of resource efficiency in corporate management systems a common understanding of the term itself, and also clear objectives, are crucial.

Figure 2 illustrates the criteria for the geostrategic risks indicator. The x-axis shows country concentration, the calculation of which is based on the number of countries in which a particular raw material is produced. The highest possible value of 10,000 would mean 100% of a raw material is produced in only one country. On the yaxis the result of weighted country risk, based on the World Bank Index (WBI), is displayed. The WBI consists of six criteria, such as a corruption index, which are aggregated to a risk value for each country. The country risk for a raw material is then weighted according to the respective country's share of world production.

CONCLUSIONS

As a first step this paper establishes a clear differentiation between objectives and measures to achieve them. As a second step, assessment methods for the objectives reducing environmental impacts, improving supply security and costs savings are discussed. The discussed methods are in common use and often already part of corporate management systems. Although the use of these methods might be time-consuming and requires expert knowledge, they are indispensable for the reliable assessment of resource efficiency. A further key conclusion of this article is that measures aimed at enhancing resource efficiency may involve trade-offs. The presented case study of steel substitution by aluminum to reduce vehicle weight shows potential reduction of environmental impacts on the one hand, but possible negative economic effects on the other. An aggregation of the assessment results for the three objectives to a single indicator, which is the practice currently followed in the resource strategy of the German government [8], is not meaningful, due to the resulting lack of transparency about possible negative effects.

Taking again the example of aluminum versus steel, the criteria used in figure 2 reveal no significant risk for either metal, be it with regard to country concentration or country risk. However, a disaggregated assessment taking into account all five indicators mentioned above might reveal some specific risks for the metals in question. To summarize, although there is generally no risk of geological depletion of raw materials, industry's access to them could nevertheless be subject to a variety of other risks. Therefore, a range of risk indicators should be applied to identify specific risks for the raw material under consideration. Given the diversity of risks, a corresponding variety of specific measures is necessary to reduce the supply risk. The risk may be reduced through measures such as hedging, diversifying suppliers, substitution or enhanced recycling. However, there is no universal solution; appropriate measures must be considered on a case-specific basis for each raw material.

Before any reasonable regulatory measures on resource efficiency can be introduced, it will first be necessary to achieve general agreement on objectives, measures and their effects. This should be a main task of further research work. Companies will have to decide if a specific management system for resource efficiency is reasonable, especially if they have already established sustainability monitoring instruments which pursue almost similar objectives.

-1.5

Weighted country risk of production (based on World Bank Index)

high

metal (refined)

metal (ore)

-1.0

Sn

0.0

Au

Ag Ni Ni

0.5

Cu

1.0

1.5 400

REE

Sn

-0.5

Mn Zn Cd

Fe Bauxit Al Pb Pb Zn Cu

Te

Co Bi FeCr Cr Si Mo

V

W

Sb Mg Nb

Pd Pt

Zr

Ti

Bi

Ta Li high

low 1,000

2,000

Country concentration (Herfindahl -Hirschman Index of production 2008) Figure 2: Supply risk criteria, based on [7].

10,000

66 7

Automotive Life Cycle Engineering REFERENCES

[1]

International Organization for Standardization - ISO 14040 (2006): Environmental Management Life Cycle Assessment – Principles and Framework. 2nd ed. Geneva: International Organization for Standardization.

[2]

Krinke, S., Koffler, C., Deinzer, G., Heil, U., (2010): An integrated life cycle approach to lightweight automotive design, in: ATZ, Volume 112. pp. 36-42.

[3]

Metal Bulletin (2010): EU domestic prices for hot rolled coil, Metal Bulletin, 6 December, Number 9178, p. 24.

[4]

Metal Bulletin (2010): LME settlement prices for Aluminum high grade, Metal Bulletin, 6 December, Number 9178, p. 20.

[5]

European Commission (2010): Report of the Ad-hoc Working Group on defining critical raw materials, Version of 30th July 2010.

[6]

Rosenau-Tornow, D., Buchholz, P., Riemann, A., Wagner, M. (2009): Assessing the long-term supply risk for mineral raw materials – a combined evaluation of past and future trends, in Resource Policy 34 (2009), pp. 161-175.

[7]

Steinbach, V.: Verfügbarkeit von Hightech-Rohstoffen. Presentation of the BGR at the Euroforum conference Technologiemetalle. Frankfurt, 21-22nd September 2010.

[8]

Statistisches Bundesamt (2010): Nachhaltige Entwicklung in Deutschland – Daten zum Indikatorensystem 2010. Statistisches Bundesamt, Wiesbaden, p. 7.

Comparative Life Cycle Assessment of Remanufacturing and New Manufacturing of a Manual Transmission 1

1

Jens Warsen , Marlisa Laumer , Wolfgang Momberg 1

2

Volkswagen AG, Group Research Environmental Affairs Product, Wolfsburg, Germany 2

Volkswagen AG, Remanufacturing Powertrain, Kassel, Germany

Abstract A newly manufactured 5-speed manual transmission is compared with a genuine remanufactured transmission of identical design. The Life Cycle Assessment covers the entire product life cycle from production through to disposal. In all the environmental impact categories considered, the remanufactured transmission performs significantly better than the newly manufactured unit. The environmental improvements are attributable to the substantial reduction in material and energy consumption. Transport of used transmissions to the remanufacturing facility accounts for only a small fraction of total life cycle environmental impacts. Energy consumption is reduced by 33 % for the remanufactured transmission compared with a newly manufactured transmission. Keywords: Comparative LCA; Remanufacturing; Transmission

1

INTRODUCTION

Volkswagen is committed to developing vehicles and components with better environmental properties than their predecessors over the entire life cycle. Life Cycle Assessments (LCA) are used to document the environmental performance of vehicles, technologies and processes. We have been using Life Cycle Assessments to enhance the environmental compatibility of our cars and their individual components since 1996. As part of an integrated product policy, the LCA considers not only individual environmental aspects such as the driving emissions of the vehicle but its entire life cycle. The Life Cycle Assessment issued by Volkswagen are in accordance with ISO 14040/44 [1, 2] and are verified by independent experts, e.g. by TÜV NORD. Volkswagen today has a 60 year history of remanufacturing. The so called „Exchange Parts Programme“, a take-back scheme for used vehicle components, was launched back in 1947 in order to meet raw material shortages in the post-war era. Initially the scheme was confined to five product groups: fuel pumps, clutch pressure plates, steering boxes, carburettors and cylinders with front and rear axles and industrial engines following during the subsequent years. Being extremely successful, the programme saved substantial amounts of raw material and energy as a large part of the components usually can be directly reused. For these component parts the complex production process of smelting, casting and forming is saved. Nonetheless genuine part quality is guaranteed for all remanufactured components. The aim of this LCA-study is to analyse and compare the environmental impacts of a newly manufactured transmission model with a genuine remanufactured transmission of identical design. More detailed information about this analysis can be found at www.mobility-and-sustainability.com. 2 2.1

MATERIALS AND METHODS Data origin of LCI analysis

The data used for preparing the Life Cycle Assessment can be

subdivided into product data and process data. “Product data” describes the product itself, and among other things includes information on parts, quantities, weights and materials. “Process data” includes information on manufacturing and processing steps such as the production of materials and semifinished goods, fabrication and the provision of electricity and other consumables. This information is either obtained from commercial databases or compiled by Volkswagen as required [3, 4]. The data selected are as representative as possible. This means that the data represent the materials, production and other processes as accurately as possible from a technological, temporal and geographical point of view. For the production processes carried out at the Kassel plant chiefly primary data is used. Upstream supply chains and external production steps are modelled using published industrial data. As the transmissions are remanufactured centrally by Volkswagen in Kassel, as far as possible data related to Germany is applied. Where German data is not available, European and occasionally global conditions are reflected. The Life Cycle Assessment model for transmission production was developed using Volkswagen‘s slimLCI methodology [5]. The transmission parts list was used as data source for product data, and data on weight and materials was taken from the Volkswagen material information system (MISS). This information was then linked to the corresponding process data in the Life Cycle Assessment software GaBi. 2.2

Data quality

Material inputs, processing procedures and the selection of data in GaBi are standardised to the greatest possible extent, ensuring that the information provided by VW slimLCI is consistent and transparent. In sum, all information relevant to the aims of this study was collected and modeled completely. The modelling of components on the basis of transmission parts lists ensures that the model is complete, especially with respect to the manufacturing phase. In addition, as the work processes required are automated to a great extent, any differences in the results are due solely to

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_12, © Springer-Verlag Berlin Heidelberg 2011

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changes in product data and not to deviations in the modelling system. 2.3

Impact assessment

The Impact Assessment is based on CML methodology [6]. The assessment of environmental impact potentials in accordance with this method is based on recognized scientific models. A total of five environmental impact categories were identified as relevant and were then assessed in this study:

key technical data of this transmission. The two transmissions are comparable as the remanufactured unit is guaranteed to have the same quality as a genuine newly manufactured gearbox. 5-speed front wheel drive car transmission Torque

250 [Nm]

Max Power

132 [kW]

Length

370 [mm] 41.3 [kg] , with oil



eutrophication potential (EP)

Weight



ozone depletion potential (ODP)

Design

Twin-shaft gearbox



photochemical ozone creation potential (POCP)

Synchromesh

3rd to 5th gears: single-cone Borg-Warner,



global warming potential (GWP) for a reference period of 100 years



acidification potential (AP)

3.1

CASE STUDY Objective and target group of the assessment

The objective of this Life Cycle Assessment was to compare the environmental profiles of newly manufactured and remanufactured transmissions. For this purpose, a manual 5-speed MQ 250 transmission, currently Volkswagen`s highest-volume transmission, and a corresponding remanufactured unit have been assessed. 3.2

Reverse gear Reverse brake (input shaft) Housing

Besides this, primary energy demand has been also recognized. These six categories were chosen because they are particularly important for the automotive sector, and are also regularly used in other automotive related Life Cycle Assessments [7, 8, 9]. 3

1st and 2nd gears: triple-cone Smith

Function and functional unit

The functional unit for the Life Cycle Assessment was defined as the manufacture of a Type MQ 250 transmission. Table 1 shows the

Diecast aluminium

Table 1: Technical data of MQ 250 transmission. 3.3

Scope of assessment

Figure 1 shows the scope of this Life Cycle Assessment. It was defined in such a way that all relevant processes and substances are considered, traced back to the furthest possible extent and modeled at the level of elementary flows. The material fractions generated during recycling are the only exception. The manufacturing phase was modelled including all manufacturing and processing stages for all transmission parts and components. The model includes the transport of the old transmission to the plant, the dismantling, cleaning and testing of the old transmission, the production of replacement parts and the reassembly of the transmission. The model therefore covers all steps from the extraction of raw materials and the manufacture of semifinished products right through to assembly.

Figure 1: Scope of Life Cycle Assessment.

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69

Figure 2 shows a more detailed plan of the transmission remanufacturing process. The model includes the transport of the old transmissions from main distribution warehouses of the individual markets to the central remanufacturing plant at Kassel. The average distance travelled by an old transmission is 1,086 km. The national collection process is not considered as details of workshops dealing with transmissions in the individual countries are not known and the environmental impact of transport is, in any case, negligible (cf. Figure 5). The model reflects the means of transport mainly used in the markets and the distances concerned. The average distances for each means of transport are shown in Table 2.

Truck Train Ship (overseas)

The service life phase is identical for both transmission types as remanufactured transmissions are reprocessed to genuine component quality and therefore meet the same technical requirements as newly manufactured units. Within the differential approach adopted for the Life Cycle Assessment, the service life phase is therefore not relevant and is outside the scope of the assessment (see Figure 1). The recycling phases of the two transmission types are also identical and are therefore also excluded from the scope of the assessment. This applies both to the separate consideration of a new and a remanufactured transmission which have reached the end of their useful lives and are consigned to recycling and to such transmissions which are remanufactured.

Overall share in transport (rounded)

Distance considered [km]

35.6 %

387

4

170

4.1

529

Figure 3 presents the Life Cycle Inventory results for selected parameters during the manufacturing phase of the production of a new transmission and the remanufacturing of a transmission. The emissions of all the gases considered are significantly reduced by remanufacturing. In absolute terms, the emission values are very different, but the relative reductions are of the same order of magnitude. The greatest savings are achieved with respect to carbon monoxide (a reduction of 47 %), which is a key factor in local air quality (photochemical ozone creation potential). Regarding the emission of carbon dioxide the remanufacturing leads to a reduction of 73 kg CO2

15.7 % 48.7 %

Table 2: Average transport distance for a returned transmission. The model is based on the data records of the GaBi software. As regards the respective assumptions concerning capacity utilisation, consumption, etc., the parameters described in the software documentation [10] apply. On average, experience indicates that the parts which are found to be reusable on inspection account for at least 50 % of the mass of a transmission. The remaining parts are consigned to recycling and replaced by new parts. These new parts include a large number of small wear parts, which are replaced on all transmissions as a standard part of the process.

RESULTS Life Cycle Inventory

Figure 2: Transmission remanufacturing process.

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Figure 3: Life Cycle Inventory Values. 4.2

Life Cycle Impact Assessment

On the basis of the Life Cycle Inventory data, the Life Cycle Impact Assessment is drawn up for all the environmental impact categories. The interactions of all the emissions recorded are considered and potential environmental impacts are determined based on CML methodology. Figure 4 compares the absolute environmental impacts of the production of a new transmission with those caused by transmission remanufacturing. The relative reductions in environmentally relevant emissions are also indicated. For example, global warming potential can be reduced by 28 %, or 63 kg of CO2 equivalents, on average by the reuse of components in a remanufactured transmission. The greatest savings are in the area of eutrophication potential (minus 42 %), followed by local air quality (represented by photochemical ozone creation potential) with minus 41 %). Energy consumption is reduced by 33% for the remanufactured transmission compared with a newly manufactured MQ 250. Figure 5 compares the environmental impacts of the various stages in the production of a new transmission and transmission

remanufacturing. The environmental impacts shown in each of the categories have been normalised using the normalisation factors in Table 3. The environmental impact of transmission remanufacturing is due mainly to the energy and materials required for producing new parts to replace components of the old transmission which cannot be reused. The remanufacturing process itself, including dismantling, cleaning, testing and reassembly, accounts for a substantially lower share of the environmental impacts. Environmental category

Unit

EP

15906

ODP

31

PO4 equivalents R11 equivalents

POCP

7228

C2H4 equivalents

GWP

4440050

CO2 equivalents

AP

21553

SO2 equivalents

Table 3: EU 15 normalisation factors (in thousand metric tons).

Figure 4: Environmental impacts of transmission production.

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71

Figure 5: Normalised environmental impacts of the various production stages. 5

CONCLUSION

This study demonstrates the benefits of the remanufacturing of transmissions with regard to the environmental profile of the components. The remanufactured transmission performs significantly better than the newly manufactured component in terms of all environmental impact categories considered. The savings are chiefly due to lower power consumption and material requirements as a result of the reuse of components. The remaining environmental impact of transmission remanufacturing is largely determined by electric power and material requirement for the manufacture of new replacement parts. Thus, for further optimization, subsequent analyses and activities will have to focus on these two aspects. 6 [1]

REFERENCES International Organization for Standardization (2006): ISO 14040: Environmental Management – Life Cycle Assessment – Principles and Framework, International Organization for Standardization, Geneva.

[2]

International Organization for Standardization (2006): ISO 14044: Environmental Management – Life Cycle Assessment – requirements and guidelines, International Organization for Standardization, Geneva.

[3]

Arning, S. (2005): Identifikation Ergebnisbeeinflussender Größen bei Getriebe-Ökobilanzen, Diploma thesis, Volkswagen AG, Wolfsburg.

[4]

Laumer, M. (2011): Vergleichende Umweltbilanz gemäß DIN ISO 14040 über die Wiederaufbereitung eines PkwSchaltgetriebes gegenüber der Neufertigung, Diploma thesis, Volkswagen AG, Wolfsburg.

[5]

Koffler, C.; Krinke, S.; Schebek, L.; Buchgeister, J. (2007): Volkswagen slimLCI – a procedure for streamlined inventory modelling within Life Cycle Assessment (LCA) of vehicles. In: International Journal of Vehicle Design (Special Issue on Sustainable Mobility, Vehicle Design and Development), Olney: Inderscience Publishers.

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[6]

Guinée, J. B.; Lindeijer, E. (2002): Handbook on Life Cycle Assessment: Operational guide to the ISO standards, Dordrecht [et al.], Kluwer Academic Publishers.

[7]

Krinke, S.; Bossdorf-Zimmer, B.; Goldmann, D. (2005): Ökobilanz Altfahrzeugrecycling – Vergleich des VW-SiConVerfahrens und der Demontage von Kunststoffbauteilen mit nachfolgender werkstofflicher Verwertung. Volkswagen AG, Wolfsburg.

[8]

Krinke, S.; Nannen, H.; Degen, W.; Hoffmann, R.; Rudloff, M.; Baitz, M. (2005): SunDiesel – a new promising biofuel for sustainable mobility. Presentation at the 2nd Life-Cycle Management Conference Barcelona.

[9]

Schmidt, W. P.; Dahlquist, E.; Finkbeiner, M.; Krinke, S.; Lazzari, S.; Oschmann, D.; Pichon, S.; Thiel, C. (2004): Life Cycle Assessment of Lightweight and End-Of-Life Scenarios for Generic Compact Class Vehicles. In: IntJLCA (6), pp. 405416.

[10] http://documentation.gabi-software.com

Coordination of Design-for-Recycling Activities in Decentralized Product Design Processes in the Automotive Industry 1

1

Kerstin Schmidt , Thomas Volling , Thomas S. Spengler 1

1

Institute of Automotive Management and Industrial Production, Technische Universität Braunschweig, Braunschweig, Germany

Abstract Design processes in the automotive industry are distributed over various companies. If inappropriate contract structures are used within such collaborations, inefficiencies in the design process occur due to existing uncertainties and differing objectives of the partners. To coordinate design-for-recycling activities in collaborative design processes a mathematical model for the analysis of those processes is developed. We apply the model to a fixed-price and an incentive contract. The analysis shows that fixed-price contracts lead to inefficiencies, while incentive contracts can reduce inefficiencies. We demonstrate the use of this model based upon an illustrative example to show its applicability. Keywords: New Product Development; Design-for-Recycling; Automotive Industry

MOTIVATION

Recycling is an important issue for a sustainable economic management in the automotive industry. In recent years, 8 to 9 million tons of waste from used cars were generated in the European Union. On average, 25 % of this waste could not be recycled and needed to be brought to landfill. Furthermore, it is expected that the amount of waste will increase to somewhere between 14 and 17 million tons until 2015. [1, 2] In order to improve the management of end-of life vehicles, the European Union adopted the Directive on end-of life vehicles [3] in 2000. Among other things, the directive aims at setting specific targets on the 1 2 3 reuse , recycling and recovery of waste from end-of life vehicles for 2006 and 2015. For 2006, reuse and recovery rates of at least 85 % and reuse and recycling rates of at least 80 % are required. From January 2015 these rates shall be increased to a minimum of 95 % and 85 %, respectively. The greatest impact on the reusability, the recyclability and 4 recoverability of a vehicle is given in the design phase of this new vehicle. For this reason, a variety of Design-for-Recycling activities exist in the automotive industry. The legislator tries to impair the product design as well: in 2005 the European Union adopted the Directive on type-approval of motor vehicles with regard to their reusability, recyclability and recoverability [4]. Due to this directive, since December 2008 automotive manufacturers (OEMs) are obligated to demonstrate the statutory rates when the type-approval of a new vehicle is done. While the OEM bears responsibility for the compliance with the recycling rates, his influence is often limited. In current practice, 1

‘Reuse’ means any operation by which components of end-of life vehicles are used for the same purpose for which they were conceived. [3] 2 ‘Recycling’ means the reprocessing in a production process of the waste materials for the original purpose or for other purposes but excluding energy recovery. [3] 3 ‘Recovery’ means the use of combustible waste as a means to generate energy through direct incineration with or without other waste but with recovery of the heat. [3] 4 In the following, for shortening, we only speak of ‘Recyclability’. The same holds for ‘recycling rates’ and ‘recycling-relevant’.

design processes are distributed over various companies. Figure 1 shows the increasing relocation of the development performance to suppliers over the last ten years. OEM 2000 2005 *2010

Supplier 67% 57% 49%

33% 43% 51%

*Estimation

1

Figure 1: Relocation of development performance to suppliers. [5] Hence, the components of a vehicle are not designed centrally at the OEM, but at a variety of specialized suppliers. For this reason, the recycling rates depend on the specifications of each component of the vehicle and thus on the design effort of the suppliers. To ensure the compliance with the recycling rates, the collaboration between OEM and suppliers is based on contracts. These contracts include recycling-relevant specifications of the components the suppliers develop. The design of appropriate contracts for these collaborations poses a challenge. Reasons can be found in differing objectives of the legally and economically independent companies. Furthermore, uncertainties exist due to the fact that the contracting is done at the beginning of the design process, when no accurate assertions about the future components’ specifications are available. If inappropriate contracts are used in these collaborations, inefficiencies can occur. On the one hand, statutory recycling rates can be exceeded, resulting in additional design effort for the suppliers, without any additional utility for the OEM. On the other hand, recycling rates can be violated, which means that the new vehicle cannot be certified to the intended date, resulting in a loss of utility for the OEM and additional design effort of suppliers. Thus, the economic risk for suppliers and OEM increases. Overcoming these difficulties requires an improved coordination between the partners before and during the design process. A formal modeling approach for the analysis of contracts and their coordination ability in distributed design processes, to best of our

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_13, © Springer-Verlag Berlin Heidelberg 2011

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knowledge, is still missing. The economics of contracts have been studied in a variety of quantitative academic contributions [6, 7]. Particularly in supply chain management settings of independent OEMs and suppliers are analyzed. A comprehensive review of contract analysis in this field is provided by [7]. In the context of supply chain management, a central phenomenon causing inefficiencies is uncertainty. In these situations the flexibility to change a chosen course of action is usually associated with better performance [8]. Accordingly, uncertainty and thus risk is being shared with respect to the contractual agreement. Of particular interest for the research presented are flexible contract types [8, 9]. However, differences between supply chain management and design processes currently prevent an easy adoption of the mentioned flexible contracts. First approaches to the flexibilization of contracts in design processes are given by [10, 11, 12]. Since these contributions focus on a general analysis of the effectiveness of incentive contracts, a formal modeling approach for the analysis of contracts and their coordination ability in distributed design processes is still missing. To this end, a mathematical model for the analysis of decentralized design processes in the automotive industry is presented and applied to the case of the efficient compliance with recycling rates. The rest of the paper is structured as follows. After modeling and analyzing decentralized design processes in the next section, we present an approach to improve decentralized design processes in section 3. In section 4 we demonstrate the use of this approach based upon an illustrative example to show its applicability. Finally, we draw our conclusions and give a short outlook on our future research in section 5.

vehicle are fully detailed until they have the readiness for start of production (SOP). [13] Since the development of a new vehicle is distributed between the OEM and his suppliers, the suppliers need to be integrated into the OEM’s design process. The integration of the suppliers as well as the conclusion of the contracts is done in the first phase of the design process (see Figure 2). At this early point of time, the contracting is done although only first assertions about the product specifications and thus about the component specifications are available. For this reason, uncertainties arise in the design process, since the component specifications, resulting at the end of the design process, cannot be predicted with certainty. To support the cooperation between the OEM and his suppliers during the design process, at fixed points in time the development status of the components is evaluated, necessary coordination is done and decisions are made [14, 15]. At the end of the design process, in the fourth phase, the integration of the suppliers’ components is done (see Figure 2). Based on the realized specifications of the developed components the determination of the recycling rates is conducted. The compliance with the statutory recycling rates is an important precondition for the conferral of the type-approval for the new developed vehicle and thus for its market launch. The determination of the recycling rates is based on the four steps of an assumed recycling process: pre-treatment ( pt ), removal ( re ), metal removal ( mr ) and treatment of non-metallic residue ( nm ). In each step, the sum of the masses m is determined, which are considered to be recyclable. Thus, simplified the recycling rate R rec results from the following equation [16]: R rec 

2

MODELING AND ANALYSIS OF DECENTRALIZED DESIGN PROCESSES

In this section we study current decentralized design processes in the automotive industry. We focus on the characteristics of current design processes in the first step and present a model for the analysis of these processes in the second step. In the third step we concentrate on the analysis of decentralized design processes. 2.1

Design processes in the automotive industry

Design processes in the automotive industry mainly consist, with the exception of company-specific deviations, of four phases: goal alignment, concept, preliminary development and serial development (see Figure 2). Integration of suppliers, conclusion of contracts Goal alignment Integration of components, Concept Type-approval of new vehicle Preliminary development Serial development 84 78 72 Month before SOP

60

48

40

36

30

24

20

12 10

6

SOP

Figure 2: Illustrative design process in the automotive industry. [13] In the first phase (goal alignment), the vehicle parameters as well as the vehicle targets are to be defined as part of the product specifications. In the second phase (concept), first vehicle designs are developed based on the product specifications. In the third phase (preliminary development), vehicle designs from the previous phase are analyzed and compared. A final vehicle design is selected and refined. Furthermore, legal requirements like recycling rates are taken into account. At the end of this phase, the prototype construction of the vehicle begins. In the fourth phase (serial development), the engineering drawings of all components of the

m pt  mre  mmr  m nm mvehicle

100

(1)

This method cannot only be applied to the calculation of the recycling rate of the vehicle itself, but also to the calculation of the recycling rate of the components. Therefore, the sum of the recyclable masses mi of each step of each component is divided by the mass of the component itself. The recycling rate of the entire vehicle R rec then results from the following equation, with Rirec indicating the recycling rates of n different components, i  1,..., n , under the assumption, that the vehicle consists of n components: R rec 

m1  R1rec  m2  R2rec  ...  m n  Rnrec m1  m 2  ...  m n

(2)

The recyclability of a vehicle does not depend on all components to the same degree. For example, all fluids, batteries, oil filters, tires, catalytic converters and airbags are considered to be 100 % recyclable, when calculating the recycling rates. The recycling of the metallic parts of end-of life vehicles succeeds by the effective separation in the shredder and in the subsequent sorting steps (magnetic separators, eddy current separators, float-sink systems) to about 97 %. Currently, the high-quality recycling of plastics, vehicle glass and shredder light fraction, resulting from the shredding process, is improvable. For example, the recycling rate of the shredder light fraction is only at 54 %, despite a weight percentage of 20 % on end-of life vehicles. Another challenge is the specific removal and recovery of the increasingly occurring precious-metalliferous car electronic components. [16, 17] Thus, the highest influence on the recyclability of a new vehicle is given by the components with a high share of polymer and composite materials and electronic components. In particular, components like the instrument panel and the underbody protection play a decisive role for the recyclability of a new vehicle. Due to these facts, the high complexity of current automotive design processes can be reduced by concentrating only on those

Automotive Life Cycle Engineering - Recycling components, which have a high influence on the recyclability of the vehicle, when modeling decentralized design processes in the next section. 2.2

Model description

We consider three independent actors with full information: one OEM and two suppliers. The two suppliers S i each develop one component with a recycling-relevant specification s i  [ s imin , s imax ] , with i  1, 2 indicating the two different suppliers/components, of a new vehicle for the OEM. For example, the recycling-relevant specification si of a component can be equal to a specific recycling rate Rirec . Since the OEM and his suppliers are legally and economically independent companies, the collaboration is regularized by contracts. In the automotive industry, contracts are usually based on unit price and amounts, while the development costs of the suppliers are included into the unit price. Since we firstly want to concentrate on the design phase, we assume that the OEM pays a lump-sum transfer payment t i to the suppliers at the end of the design process. The transfer payment functions can differ depending on the contract type that regularizes the collaboration. For example, the transfer payment functions can have a step-wise, a linear or an exponential shape. The compliance with the statutory recycling rates for the new vehicle, the OEM bears responsibility for, depends on the recyclingrelevant specifications si of the two components. Different combinations of the recycling-relevant specifications si lead to the compliance with the statutory recycling rates. We assume that these combinations, can be described approximatively by the functional relationship s 2  r (s1 ) .

75 density function P ( s1 , s 2 ) and integrating on the two intervals, with the interval limits depending on the efforts of the suppliers. This results in the following expected utility function n( w1 , w2 ) of the OEM, with d specifying the slope of the turning point, d   : n ( w1 , w2 )  s1max

The expected utility of the OEM depends on the compliance with the recycling rates of the new vehicle and thus on the expected specifications s i of the suppliers’ components. If the recycling rates are met, the utility of the OEM is one, otherwise it is reduced by the costs related to a deferred start of production. To model this stepwise character of the utility in a continuously and differentiable manner, it is approximated by a Sigmoid-function, which is normalized to the interval [0,1] . Through the turning point of the Sigmoid-function the function r ( s1 ) is running, so that the substitutional interdependencies between the two component specifications are taken into account. Since the efforts wi of the suppliers are stochastically independent, the existing uncertainties get included by multiplying the Sigmoid-function with the combined

1  P ( s1 , s 2 ) d ( s 2 ) d ( s1 ) 1  exp( d  r ( s1 ))  exp(  d  s 2 )

(3)

An overview of the model is given in Figure 3. s1 n(w1,w2)

OEM s2

S1

c1(w1)

S2

c2(w2)

t1 t2

Figure 3: Model of decentralized design processes. Figure 4 shows the course of events within the model for decentralized design processes: The OEM determines the transfer payment functions t i in the first step. Based on the transfer payment function the suppliers decide about their optimal effort wi and start the development of their component in the second step. Due to the chosen effort the interval limits for the component specification are realized and thus the expected component specifications s i are resulting in the third step. Dependent on the realized component specifications the transfer payments t i ( s i ) paid to the suppliers by the OEM as well as the utility of the OEM are resulting in the last step. ti ( s i )

The recycling-relevant specifications si of the two components, resulting at the end of the design process, depend on the design effort wi of the suppliers. Furthermore, the design effort wi quantifies the development costs ci ( wi ) of the suppliers, which are normalized to the interval [0,1] . Since uncertainties exist in the design process, the resulting recycling-relevant specification s i achievable with a specific design effort wi cannot be predicted with certainty. We assume, that the probability f ( si ) of achieving a certain specification s i is uniformly distributed in the interval [ s imin , simax ] . However, the suppliers may influence the expected component specification s i with their efforts wi . Due to practical relevance it has to be assured that the expected component specification is zero, if the effort is zero. Furthermore, the interval nearly shall remain the same size and the component specification shall converge to a technological threshold with increasing effort. According to these requirements, the coherence between component specification and effort is implemented as follows: The interval limits depend on wi : simin  ln( ai  wi  1) and simax  ln(bi  wi  1) , with bi > a i > 0. Thus, a greater effort shifts the interval limits to the right, so that an increase in effort leads to a higher expected value s i .

s 2max

s1min s2min

OEM: Decision about transfer payment function

wi

si

Supplier: Decision about effort

Supplier: Realization of component specification

wi

si

OEM: Resulting transfer payment and utility

ti ( si )

t i ( si )

Figure 4: Course of events within the decentralized design process. Based on this model, an illustrative model analysis is done in the next section. 2.3

Illustrative model analysis

Centralized setting In the centralized setting ( c ) one decision maker, who has full information, develops and integrates both components (see Figure 5). s1 n(w1,w2)

OEM s2

S1

c1(w1)

S2

c2(w2)

t1 t2

Figure 5: Decision situation in the centralized setting. Hence, his aim is to maximize the total profit  of the design process. His profit function results from the expected utility n minus the development costs ci as follows:

 ( w1 , w2 )  n ( w1 , w2 )  c1 ( w1 )  c 2 ( w2 )

(4)

The optimal efforts wi ,c as well as the resulting expected component specifications s i ,c result from the analytical determination of the extreme point of the profit function  .

76

Automotive Life Cycle Engineering - Recycling

These results provide as a benchmark for the analysis of the coordination ability of different kinds of contracts in the decentralized setting. Decentralized setting In the decentralized setting, the decision situation of the suppliers is considered when collaboration is based on contracts (see Figure 6). s1 n(w1,w2)

OEM s2

S1

c1(w1)

S2

c2(w2)

t1 t2

tih,iin

ŝi

si

Figure 7: Fixed-price contract.

hi

simin

simax

s max

ˆ

i

i

(5)

To analyze the decentralized setting with fixed-price contract ( fp ) the decision situation of the suppliers is considered. We assume that the OEM chooses the required component specification sˆi according to the optimal specification s i ,c in the central case. The ˆ profit functions  is,i fp of the suppliers are based on the transfer payment functions minus their development costs. The suppliers then determine their effort wi by maximizing their profit function: ˆ

ˆ

 is,i fp ( wi )  t is,i fp ( wi )  ci ( wi )

(6) ˆ

Since the realized specifications, and thus the resulting transfer payments, depend on the suppliers’ effort, the expected transfer payment function arises as follows: The existing uncertainties are included by multiplying the transfer payment function hi ( s i ) with the density function P ( s i ) and integrating on the interval, with the interval limits depending on the effort of the supplier. The expected transfer payment function t ih,iin results as follows: s max

Figure 8: Incentive contract.

1  P ( si ) d ( si ) 1  exp( k  sˆi )  exp(  k  s i )

In incentive contracts not a certain design specification is set by the OEM, but an interval on design specifications. For every specification within the interval the suppliers get an agreed transfer payment hi ( si ) (e.g., the transfer payment function increases linear with respect to the achieved specification). Additionally, the suppliers are able to select a component specification within this interval and thus an effort to achieve this specification, which fits best to their structure of development costs and hence to their uncertainties. Figure 8 outlines a simplified incentive contract.

i t ih,iin ( wi )  s min hi ( si )  P ( si ) d ( si )

si

Since the realized specifications and thus the resulting transfer payment depend on the suppliers’ effort, the expected transfer payment functions arise as follows: To model the binary-character of the transfer payment in a continuously and differentiable manner, it is approximated by a Sigmoid-function, which is normalized to [0,1] . The turning point of the Sigmoid-function is described by the required component specification sˆi . The existing uncertainties are included by multiplying the Sigmoid-function with the density function P ( s i ) and integrating on the interval, with the interval limits depending on the effort of the supplier. The expected transfer ˆ payment function t is,i fp , with k specifying the slope in the turning point, k   , results as follows: i t is,i fp ( wi )  s min

IMPROVING DECENTRALIZED DESIGN PROCESSES

In this section we present the conceptual design of an incentive contract to make decentralized design processes in the automotive industry more flexible and thus less inefficient.

Figure 6: Decision situation in the decentralized setting.

ˆ

Hence, new types of contracts are necessary to improve the cooperation between OEM and suppliers in distributed design processes. For this purpose, we present the conceptual design of an incentive contract in the next section. 3

Currently, in the automotive industry fixed-price contracts are most commonly used. In these contracts the OEM determines certain recycling-relevant specifications sˆi for the components that have to be fulfilled by the suppliers. Based on these parameters, the OEM then specifies the transfer payment function determining the amount to be paid by him to the suppliers. In this fixed-price contract, a component specification equal or higher than the required specification leads to a payment equal or higher compared to the development costs of the suppliers, while a specification lower than the required specification leads to a payment corresponding to the development costs reduced by the penalty costs. Figure 7 outlines a simplified fixed-price contract.

tis,i fp

specifications sˆi and thus get the agreed transfer payment with certainty. Consequently, inefficiencies in the design process occur and increased development costs and overdesigned components are resulting.

The analysis shows, that the optimal efforts wis, ifp and thus the ˆ expected component specifications sis,ifp are higher than in the centralized setting. Due to the fixed-price contract the suppliers choose a higher effort than necessary to achieve at least the design

(7)

To analyze the decentralized setting with incentive contract ( in ) the decision situation of the suppliers is considered. The profit functions  i,hiin of the suppliers are based on the transfer payment functions minus their development costs. The suppliers then determine their effort wi by maximizing their profit function:

 ih,iin ( wi )  t ih,iin ( wi )  ci ( wi )

(8)

The analysis shows, that the optimal efforts wih,ini and the resulting expected component specifications sih,ini are higher than in the centralized setting, but lower than in the decentralized setting with fixed-price contract. Thus, using incentive contracts enables to reduce the overdesign of the components and to make a contribution to the coordination of decentralized design processes. The reason for the reduced overdesign of the suppliers is their higher flexibility and the missing risk to get no transfer payment. Due to the higher flexibility for the suppliers the risk of the OEM increases, since the chosen efforts of the suppliers can lead to the non-compliance with the statutory recycling rates. Therefore it is necessary for him to set the contract parameters hi ( si ) advisedly. The application of the model will be illustrated in the next section. 4

ILLUSTRATIVE EXAMPLE

To show the applicability of the previously presented model to analyze different kinds of contracts towards their coordination ability, we employ it in an illustrative example of a decentralized design process in the automotive industry in this section. In the first step, the setting of this example is specified. In the second step we concentrate on the analysis of this illustrative example.

Automotive Life Cycle Engineering - Recycling 4.1

Setting of the illustrative example

In the considered setting, two independent suppliers each develop one component for a new vehicle of an OEM: the underbody protection and the instrument panel. To grant the type-approval of the new vehicle at the end of the design process, the OEM has to demonstrate that the vehicle is able to achieve the statutory recycling rates. For the sake of simplicity it is assumed that the recycling rates of all components, except the underbody protection and the instrument panel, cannot be improved. Thus, the resulting recycling rate of the vehicle only depends on the recycling rates of the two components developed by the suppliers. To meet the statutory recycling rates for the vehicle, the combined recycling rate of the two components needs to be 60 %. To achieve this goal, specific recycling-relevant specifications s i of the components are required. In this illustrative example, the recycling-relevant specifications are equal to the recycling rates of the components: s i  Rirec . Until now a coating with mineral-filled PVC has been provided by supplier S1 to protect the underbody. Since such a protective layer cannot be removed from steel with a tolerable outlay, only the steel could be recycled. Thus, nearly 100 % of the mineral/plastic mixture of the underbody protection is going to landfill. To improve the recyclability and thus the recycling rate of the underbody protection, the supplier identified two options. On the one hand a suitable and partially distinguishable layer thickness and alternative materials can lead to the reduction of the proportion of nonrecycable materials. The implementation of this option leads to a recycling rate of s1min for the underbody protection. However, the basic problem of the nondetachable connection between the underbody and the underbody protection remains. Thus, on the other hand the protective layer applied to the underbody can be substituted by underbody cladding made of glass-fiber reinforced polypropylene. Furthermore, the cladding is fixed to the underbody by means of screws and thus in a detachable way. The implementation of this option leads to a recycling rate of s1max for the underbody protection. In addition to these two options combinations of these two options are possible. As a result the following interval on the recycling rate s1 results for supplier S1 : s1  [ s1min , s1max ] . [18] Currently, the instrument panel of supplier S 2 consists of plastic materials, which lead to a recycling rate of s 2min . To improve the recyclability and thus the recycling rate of the instrument panel, those materials can be provided which can be used again as ground material in the production of equivalent parts or can be supplied to a production residue recycling system. In case of the instrument panel for example materials like thermo-plastic SMA-GF 10 recyclate meet these demands. The implementation of these materials leads to a recycling rate of s 2max for the instrument panel. Depending on the extent to which these materials can be used for the instrument panel, the recycling rate s 2 resulting for supplier S 2 lies in the following interval: s 2  [ s 2min , s 2max ] . [18] The achievable recycling rates s i as well as the interval limits depend on the design efforts wi of the supplier. Although the technologies to improve the recycling rates of the two components are known by the suppliers, uncertainties exist with regard to the recycling rates s i achievable with a specific design effort wi . We assume, that the probability f ( si ) of achieving a certain recycling rate si is uniformly distributed in the interval [ s imin , simax ] , with the interval limits depending on the effort wi : s imin ( wi ) and s imax ( wi ) . Since the design effort wi determines the development costs c iex ( wi ) of the suppliers, it is assumed that the development costs of supplier S1 and supplier S 2 can be approximated by linear functions: c1ex ( w1 )  0.013  w1 and c 2ex ( w2 )  0.016  w2 .

77 The combined recycling rate of 60 % of the two components, the OEM aims at, can be achieved by a variety of combinations of the recycling rates of the two components. Under the assumption that the masses mi of the underbody protection and the instrument panel are 10 kg and 50 kg respectively these combinations can be described by the following functional relationship:

0 .6 

m1  s1  m 2  s 2

 0 .6 

m1  m 2

10  s1  50  s 2  s 2  0.72  0.2  s1 (9) 10  50

Thus, the expected utility function n ex ( w1 , w2 ) of the OEM in this illustrative example results as follows: n ex ( w1 , w2 ) 

s 2max

4.2

s1max s 2max

1

s1min s2min  1  exp( d  (0.72  0.2  s 

1 1   s 2min s1max  s1min

1

))  exp(  d  s 2 )



   d ( s 2 ) d ( s1 )  

(10)

Analysis of the illustrative example

In this section the centralized setting is analyzed first to determine a benchmark. Afterwards the coordination ability of a fixed-price and an incentive contract is analyzed in the decentralized setting. Centralized setting In the centralized setting ( c ) the OEM develops the underbody protection as well as the instrument panel and integrates both components into the new vehicle. His aim is to meet a recycling rate of 60 %, which maximizes his utility, with minimal effort and thus with minimal costs. His profit function results as follows:



ex

( w1 , w2 )  n ex ( w1 , w2 )  c1ex ( w1 )  c 2ex ( w2 )

(11)

The following optimal efforts w1ex,c  6.45 , w2ex,c  5.53 and thus the following expected recycling rates s1ex,c  83 % , s 2ex,c  79 % of the suppliers components are resulting. They provide as a benchmark for the analysis in the decentralized setting. Decentralized setting with fixed-price contract ( fp ) In this decentralized setting the OEM determines the transfer payment function for the fixed-price contracts concluded with the suppliers. Since the OEM has full information, he chooses the required recycling rates sˆiex for the components developed by the suppliers as well as the maximal transfer payment in accordance to the optimal expected specification in the centralized setting. For the sake of simplicity it is assumed, that the suppliers accept the contract in any case. ˆ

The expected transfer payment functions t is,i fp,ex result as follows: ˆ

t1s,1fp,ex ( w1 ) 

max

s max

ˆ

1

1

s1 s1min 1  exp( k  0.83)  exp(  k  s )  s max  s min d ( s1 ) 1 1 1

2 t 2s2, fp,ex ( w2 )  s min 2

1 1  d (s2 ) 1  exp( k  0.79 )  exp(  k  s 2 ) s 2max  s 2min

(12)

(13)

To analyze the decision situation of the suppliers the profit function ˆ  is,i fp,ex of the suppliers is considered as follows: ˆ

ˆ

 is,i fp,ex ( wi )  t is,i fp,ex ( wi )  ciex ( wi )

(14) ˆ

ˆ

The following optimal efforts w1s,1fp,ex  13.94 , w2s,2fp,ex  9.53 and thus ˆ ˆ the following expected recycling rates s1s,1fp, ex  100 % , s 2s,2fp,ex  100 % of the suppliers components are resulting. Compared to the results of the centralized setting fixed-price contracts lead to an increase in effort of about 116.12 % and 72.33 %, respectively. The suppliers choose such a high effort to maximize the probability to achieve the

78

Automotive Life Cycle Engineering - Recycling

required recycling rate sˆiex and thus to get the agreed transfer payment, taking into account the development costs. Consequently, increased development costs and overdesigned components are resulting. Decentralized setting with incentive contract ( in ) In this decentralized setting the OEM determines the transfer payment function hiex ( s i ) as well as the interval limits for the inventive contracts concluded with the suppliers in dependence to the structure of their development costs: h1ex ( s1 )  0.188  s1

for s1  [57 %, 100 %]

(15)

h 2ex ( s 2 )  0.272  s 2

for s 2  [60 %, 98 %]

(16)

The expected transfer payment functions t ih,iin,ex result as follows: s max

1 t1h,1in,ex ( w1 )  s min h1ex ( s1 )  1

s max

1 d ( s1 ) s1max  s1min

2 t 2h,2in,ex ( w2 )  s min h2ex ( s2 )  2

1 d ( s2 ) s2max  s2min

(17)

(18)

To analyze the decision situation of the suppliers the profit function  ih,iin,ex of the suppliers is considered as follows:

 ih,iin,ex ( wi )  t ih,iin,ex ( wi )  ciex ( wi )

(19)

The following optimal efforts w1h,in1 , ex  7.2 , w2h,2in,ex  6.31 and the following expected recycling rates s1h,1in,ex  89 % , s 2h,2in, ex  86 % of the suppliers components are resulting. Compared to the results of the centralized setting incentive contracts lead to an increase in effort of

6

REFERENCES

about 11.63 % and 14.11 %, respectively. Compared to the results of the decentralized setting incentive contracts lead to a decrease in effort. Reasons for the reduced overdesign of the suppliers can be found in their higher flexibility and their missing risk to get no transfer payment. Consequently, incentive contracts contribute towards a reduced overdesign of the components and thus contribute to the coordination of decentralized design processes. 5

CONCLUSION AND OUTLOOK

In this paper we presented a mathematical model for the analysis of decentralized design processes in the automotive industry and applied it to the case of the efficient compliance with recycling rates. We analyzed a centralized setting and compared the results to a decentralized setting with a fixed-price contract. The analysis showed that fixed-price contracts lead to inefficiencies. We then introduced the conceptual design of incentive contracts to make decentralized design processes in the automotive industry more flexible. Inefficiencies could be decreased by dividing the development risk between the OEM and his suppliers. Finally, we demonstrated the use of this concept based upon an illustrative example to show its applicability. Although the scope of the analysis lies on rather general characteristics, it captures the key elements of design processes in the automotive industry in both structural as well as logical respects. Our future research will concentrate on the mathematical analysis and evaluation of further contract types. This lays the basis for empirical testing using case study methodology. The vision is to support automotive companies in the design of efficient development contracts.

[1]

Andersen, F.M.; Larsen, H.V.; Skovgaard, M. (2008): Projection of end-of-life vehicles: Development of a projection model and estimates of ELVs for 2005-2030, in: ETC/RWM working paper 2008/2.

[10] Kruse, J.; Thomsen, C.; Ernst, R.; Volling, T.; Spengler T.S. (2005): Introducing flexible quantity contracts into distributed SoC and embedded system design processes, in: Proceedings of the conference on Design, Automation and Test in Europe, pp. 938-943.

[2]

Fergusson, M. (2007): End of Life Vehicles (ELV) Directive: An assessment of the current state of implementation by Member States, Study requested by the European Parliament's Committee on the Environment, Public Health and Food Safety (IP/A/ENVI/FWC/2006-172/Lot 1/C1/SC2).

[11] Kruse, J.; Thomsen, C.; Ernst, R.; Volling, T.; Spengler T.S. (2005): Towards flexible systems engineering by using flexible quantity contracts, in: Proceedings of the conference on Automation, Assistance and Embedded Real Time Platforms for Transportation, pp. 480-488.

[3]

Directive 2000/53/EC of the European Parliament and of the Council of 18 September 2000 on end-of life vehicles.

[4]

Directive 2005/64/EC of the European Parliament and of the Council of 26 October 2005 on the type-approval of motor vehicles with regard to their reusability, recyclability and recoverability.

[12] Rox, J.; Schmidt, K.; Winter, A.; Spengler, T.S.; Ernst, R. (2010): Estimating and mitigating design risk in a flexible distributed design process, in: IEEE Embedded Systems Letters, Vol. 2, No. 2, pp. 35-38.

[5]

Roland Berger & Partner (2000).

[6]

Bolton, P.; Dewatripont, M. (2005): Contract theory, The MIT Press, Cambridge.

[7]

Tsay, A.A.; Nahmias, S.; Agrawal, N. (1999): Modeling supply chain contracts: A review, in: Quantitative models for supply chain management, Kluwer Academic Publishers, Norwell, pp. 299-336.

[8]

[9]

Anupindi, R.; Bassok, Y. (1999): Supply contracts with quantity commitments and stochastic demand, in: Quantitative models for supply chain management, Kluwer Academic Publishers, Norwell, pp. 197-232. Tsay, A.A. (1999): The quantity flexibility contract and supplier-customer incentives, in: Management Science, Vol. 45, No. 10, pp. 1339-1358.

[13] Böhme, M. (2004): Ein methodischer Ansatz zur parametrischen Produktmodellierung in der Fahrzeugentwicklung, VDI Verlag, Düsseldorf. [14] Frad, A. (2009): Umwelt- und Recyclingbewertung als Bestandteil des Automotive Product Lifecycle Management, Vulkan-Verlag GmbH, Essen Ruhr. [15] Hab, G.; Wagner, R. (2006): Projektmanagement in der Automobilindustrie, GWV Fachverlage GmbH, Wiesbaden. [16] DIN ISO 22628 (2002): Straßenfahrzeuge - Recyclingfähigkeit und Verwertbarkeit - Berechnungsmethode, Beuth Verlag GmbH, Berlin. [17] Umweltbundesamt (2010): Altfahrzeugaufkommen und -verwertung. [18] VDI Richtlinie 2243 (2002): Recyclingorientierte Produktentwicklung, Verein Deutscher Ingenieure, Beuth Verlag GmbH, Düsseldorf.

A Strategic Framework for the Design of Recycling Networks for Lithium-Ion Batteries from Electric Vehicles 1

1

1

Claas Hoyer , Karsten Kieckhäfer , Thomas S. Spengler 1

Institute of Automotive Management and Industrial Production, Technische Universität Braunschweig, Braunschweig, Germany

Abstract In this paper, we develop a strategic framework for the design of recycling networks for spent lithium-ion batteries from electric vehicles. The framework provides an overview of possible configuration alternatives and an integrated approach for network planning and process configuration tasks. It describes requirements on a network as well as on a process level. For that purpose, we analyse general framework conditions concerning battery return, materials, and recycling processes. On that basis, it is possible to develop a mathematical optimisation model which enables decision support concerning the optimal evolvement of recycling sites, capacities, and processes over time. Keywords: Strategic Network Planning; Recycling; Spent Lithium-Ion Batteries

1

INTRODUCTION

Efficient and reliable lithium-ion batteries are a key technology for electric mobility due to their high specific power, energy density, and lifetime [1]. For the production of lithium-ion batteries, nonferrous metals like copper, cobalt, nickel, and lithium are required, which leads to two main problems. On the one hand, the extraction or production of these metals is partly associated with high environmental impacts. On the other hand, the mining deposits are geographically concentrated and partially scarce. In 2008, seven countries accounted for 85 % of the world’s production of mined cobalt, nearly the same holds for lithium [2]. Particularly for the EU this may lead to a shift of dependency from oil-producing countries to countries that are producing cobalt, lithium, or their alloys. Recycling of the batteries has two main benefits. First, recycling may extend the reserves-to-production ratio of scarce resources, reduce energy-intensive primary production and therefore defer the opening or extension of mines. Natural resource savings of more than 50 % are possible [3]. Second, from a national point of view, recycling may have a stabilising, damping or even reducing effect on prices of and dependency on primary raw materials by providing a secondary feedstock. Beyond that, landfill and incineration of traction batteries are forbidden, and all batteries must be orderly recycled. For Germany, a recycling efficiency of 50 % by weight has to be achieved as from September 2011 [4; 5]. Up to now, neither recycling processes nor the necessary infrastructure exist that would allow for an industrial recycling of these batteries. Thus, a powerful recycling network must be established. Decisions about the evolvement of recycling sites, capacities, processes, and transportation links over time must be made. This is complicated due to heavy uncertainties about the development of the electric vehicle market and battery technology, as well as immature recycling processes. Against this background, the objective of this paper is to deliver a framework for the design of a recycling network for spent lithium-ion batteries from electric vehicles. To build up the framework, in a first step we analyse specific problem characteristics. Based on this

analysis, we develop a framework including the description of actors and requirements that need to be considered to design recycling networks for spent lithium-ion batteries. A planning approach will be presented. Different network constellations in dependence of identified decoupling points and two extreme market scenarios are examined. The results are discussed in a last step. 2 2.1

TERMINOLOGY AND BATTERY CONSTRUCTION Electric Vehicles

In this contribution, the term electric vehicles includes any electric vehicle with a lithium-ion battery used for traction. Electric vehicles may be classified into hybrid-electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV) and battery electric vehicles (BEV). The most important differences between the vehicle types are specifications like mass and materials, costs, and the lifetime of the required battery. 2.2

Lithium-ion batteries

Lithium-ion batteries are rechargeable batteries with promising properties for electric mobility, which is mainly due to their high power density and specific energy [1]. In this paper, the term lithium-ion battery embraces all rechargeable secondary batteries based on the exchange of lithium ions to produce electrical energy. A lithium-ion battery used for traction is constructed on three fabrication levels: cell, module, and system level. Multiple cells are connected in series to raise voltage, resulting in modules. Modules are connected in series and in parallel to raise voltage and capacity. The resulting battery system additionally includes thermal management, monitoring, protection, charge/discharge balancing, and car integration components [1]. Lithium-ion battery cells consist of a cathode, an anode, a separator, an electrolyte, and a casing. Cathode and anode conductors are usually made of aluminium and copper foil, respectively. The cathode is coated with either a mix of lithium and other metals (LiMeO2) or lithium-iron-phosphate (LiFePO4). Metals (Me) used in the former are cobalt, nickel, manganese, and

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_14, © Springer-Verlag Berlin Heidelberg 2011

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aluminium. The anode is usually coated with graphitic or amorphous carbon, or lithium-alloying metals [6]. Anode and cathode material can be combined almost freely. All of them have both specific advantages and disadvantages related to power, lifetime, safety, and costs of the cells. Lithium-ion cells can further be classified by their type of electrolyte: liquid-type, gel-type and solid-type cells. The latter two are often referred to as lithiumpolymer batteries. The type of electrolyte used determines the type of separator and vice versa.

essentially influence decisions about total capacity, sites, and required equipment of the recycling network. Sink-related uncertainties can be classified into the three categories product reuse, component reuse, and material reuse opportunities. To design the network infrastructure connecting sources and sinks, the transforming processes and the resulting material flows have to be considered. Process-related uncertainties exist with respect to the optimal combination and configuration of processes.

Since hybrid electric vehicles and battery electric vehicles substantially differ in their requirements regarding power and energy, lithium-ion cells can be divided into high-power cells for HEVs and high-energy cells for BEVs. Table 1 summarises typical materials and mass portions for lithium-ion batteries. For highenergy batteries, the active materials of the anode and cathode make out the largest portion of the battery mass, followed by the electrolyte. The same holds for the costs of the materials [1]. Part

Material(s) [1; 6; 7]

Mass portions [1] HighEnergy

HighPower

Cell level Cathode conductor

Aluminium foil

Cathode active material

Lithium and cobalt, nickel, manganese, or aluminium, or a mix of them, or Lithium-IronPhosphate; Carbon black; Binder (PVDF)

Anode conductor

Copper foil

2%

5%

41 %

19 %

4%

10 %

Anode active Graphitic carbon, amorphous material carbon, or lithium-titanate; Binder (PVDF)

17 %

4%

Electrolyte

Lithium salts (e. g. LiPF6) dissolved in organic solvents

16 %

11 %

Separator

Polyolefins or Polyvynilidenfluorid

2%

4%

9%

28 %

9%

19 %

Cell package Aluminium, stainless and others and/or plastics

steel,

Module and system level Electric conductors

Copper cables

Electronics

Printed circuit assemblies including semiconductors

Module packaging

Polypropylene

System packaging

Aluminium, stainless and/or plastics

Total

3.1

Uniqueness of the Planning Situation

Different recycling networks exist which could serve as a basis for a recycling network for lithium-ion batteries, including legally independent networks for vehicles, lead-acid starter batteries, portable batteries, and electronic waste. However, these networks are not fully qualified for an efficient and environmental recycling of lithium-ion batteries. On the one hand, a high amount of spent batteries would overstrain the capacities of the mostly smallest businesses. Lithium-ion batteries are more complex, heavier, and more hazardous, hence, more difficult to treat than the mentioned products. The dangerous-good property of the batteries complicates the usage of existing transport links. On the other hand, novel and unexplored processes with high economies of scale are required which contravenes the mostly decentralised organisational form of the networks. New actors like battery material producers come into play. These circumstances would demand a restructuring of existing networks anyway. Moreover, a particular challenge to the planning of the recycling network is the directive 2006/66/EC of the European Union. It forces battery and electric vehicle producers to conceive and establish an effective collection and recycling solution before market penetration. Because neither the electric vehicle market nor the battery technology are evolved to a steady state, this planning and investment situation is heavily uncertain. 3.2

steel,

Source-related uncertainties

Quantity of battery returns 100 %

100 %

Table 1: Typical materials for lithium-ion batteries. 3

Figure 1: Generic network structure for lithium-ion battery recycling.

GENERAL CONDITIONS

Figure 1 shows the generic structure of a recycling network connecting material flows between sources and sinks with different transforming processes. Sources, sinks, and processes of the recycling network are fraught with uncertainties. Source-related uncertainties can be classified into quantity, spatial distribution, and specifications of the battery returns. These parameters

Lithium-ion batteries from electric vehicles become available for recycling at the end of life of the electric vehicle or the end of life of the battery itself. Given that, the quantity of spent battery returns is particularly driven by the development of the electric vehicle market over time and the battery lifetime. The forecast of the electric vehicle market is currently subject to many market studies. These most often use scenario technique to determine sales and stocks for specific points in time on an aggregate level [8]. For Germany, the government aims at a market penetration of 1,000,000 PHEVs and BEVs in 2020 [9]. The forecasts are significantly depending on assumptions about oil

Automotive Life Cycle Engineering - Recycling

81

prices, energy supply, public interest in climate change, and more stringent greenhouse gas legislation [8].

3.4

The battery lifetime is expected to be highly dependent on the used active materials and the type of vehicle the battery is used in [10]. It is estimated to be around five years for BEVs, ten years for PHEVs, and up to fifteen years for HEVs [10; 11]. However, these numbers are based on extrapolation, not experience, and it remains unclear how the lifetime will be distributed.

Basically, recycling processes for lithium-ion batteries can be classified into disassembly, mechanical conditioning, hydrometallurgical conditioning, and pyrometallurgical conditioning. In disassembly, battery systems are broken down subsequently to module and cell level which is the prerequisite for a remanufacturing of batteries. Reusable components and large material fractions, for example the battery casing and electronics, are separated before further conditioning processes are applied to the cell materials. In mechanical conditioning, materials of the cells are separated by different comminution, sizing, and concentration processes. Examples are crushing, screening, and magnetic separation. Pyrometallurgical conditioning involves the thermal treatment of the materials at high temperatures. It can be combined with the production of steel, and of ferromanganese or other alloys. Hydrometallurgical conditioning typically combines leaching, solution concentration and purification, and metal recovery methods, including electrometallurgy. With hydrometallurgical processes, pure non-ferrous metals can be recovered from active materials after mechanical conditioning or from the slag of pyrometallurgical processes.

The spatial distribution of battery returns determines transport distances and therefore costs. Decisions about sites for the collection of spent batteries and for the recycling facilities are influenced by that, given that cost minimisation or profit maximisation is preferred and all batteries must be collected. It is not clear yet whether electric vehicles with low cruising ranges will be sold rather in urbanised than in rural areas. Based on that, not only the amount but also the spatial distribution of battery returns can be considered as highly uncertain. Composition of battery return Mass, size, construction, and materials of lithium-ion batteries vary dependent on their application. To give an example, a battery for a mid-sized all electric vehicles with a range of about 200 kilometres would weigh about 300 kilograms [12]. A battery for a plug-in hybrid vehicle with an electric range of 50 kilometres would weigh just about 100 kilograms [13]. This diversity and the highly uncertain technology development demands either highly flexible equipment or manual work, which tends to result in high investments or costs, respectively. 3.3

Sink-related uncertainties

Product reuse opportunities Spent batteries from electric cars which may not be suitable for powering vehicles anymore are expected to be qualified for further stationary use, e. g. storage of energy from fluctuant power generation like wind or solar power [1]. Direct product reuse then would decelerate the return of spent batteries. However, it is not expected to happen in a large scale while the batteries are not further standardised so that they can be easily stocked, connected, and monitored outside of vehicles. Component reuse opportunities

Process combinations As listed in chapter 2.2, lithium-ion batteries can consist of a variety of different materials. Single materials can be recovered selectively with certain processes. Therefore, a combination of different processes is necessary to recover all relevant materials [14]. Figure 2 depicts a comprehensive overview of different process combination possibilities and the recovered materials. It includes potential decoupling points that by way of example occur if a disassembly or mechanical conditioning is intended or necessary. The prerequisite for spatial decoupling is the transportability of the intermediate products, which appears to apply mainly for cells as well as for the coating powder, and, to a less extent, for the intermediate products from pyro- and hydrometallurgical processes. Batteries Disassembly

Mechanical Conditioning

Pyrometallurgy

Hydrometallurgy

Disassembly

Mechanical Conditioning

Hydrometallurgy

Hydrometallurgy

Pyrometallurgy

Hydrometallurgy

Pyrometallurgy

Hydrometallurgy

Disassembly

Material reuse opportunities The high cobalt-price of approximately 40 USD per kilogramme was the driver for the recycling of smaller lithium-ion batteries, but also one important reason to replace parts of the cobalt with other metals [1] or entirely move away from cobalt-containing cathode active materials. By that, the economical incentive of recycling may diminish. Especially lithium-iron-phosphate does not contain any cobalt or nickel (which is priced at about 20 USD per kilogramme). Lithium, in the form of lithium carbonate, is much cheaper at about 6 USD per kilogramme and the mass fraction of it on cell level is just about 3 %. From today’s point of view, the costs of conditioning may excess the revenues. However, lithium prices are expected to rise as the demand is growing dramatically.

Recycling processes

← Decoupling Point

Standardisation is also important to enable component reuse. With standardised battery constructions, electronic interfaces, and cell types, spent batteries could be remanufactured easily by replacing worn components with new ones, resulting in as-good-as-new batteries. Additionally, cells with a similar state from different spent batteries could be assembled to lower-quality batteries, and electronic components could be used as spare parts.

Recycling processes

Casing, Electronics

Recovered materials

Spatial distribution of battery returns

Process-related uncertainties

Copper, Aluminium

Pyrometallurgy

Cobalt, Nickel

Lithium

Figure 2: Combination possibilities of conditioning processes and recovered materials, based on [15]. Exemplary process combinations A promising process to recover all valuable materials is currently subject of investigation at LithoRec. The analysed process begins with demounting the spent battery from the car. After transportation to a disassembly line, the battery will be disassembled to cell level. Cells will be dismantled and the volatile liquids (electrolyte with conductive salts) are absorbed for further conditioning. The coated electrodes will be separated with mechanical processes, resulting in aluminium and copper fractions and coating powder. The coating

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powder, which contains the active material, will be treated in chemical conditioning processes to recover lithium, nickel, cobalt, and manganese, or lithium-iron-phosphate, which will then be available for production again. See Figure 3 for an illustration. The LithoRec process promises to be suitable for large-scale recycling, since a large amount of materials is recovered, including battery components, all metals, and the valuable electrolyte. However, the process is still under investigation.

treatment of the cells could then be realised centrally, exploiting high economies of scale. In summary, the processes chosen and the battery types processed determine the remanufacturing option, recoverable materials and their degree of purity as well as the spatial decoupling potential. While some combinations of processes would be able to recover new active material like LiCoO2, some would result in pure cobalt and lithium-carbonate, among copper and aluminium. Thus, different sinks must be considered in each case. By this means, the decision about processes considerably influences the network structure and must be integrated into strategic network planning. 4 4.1

FRAMEWORK Scope and corporative actors

The framework for the design of a network for the recycling of spent lithium-ion batteries involves different kinds of actors of the economy, namely the battery material producers, battery producers, vehicle producers, vehicle dealers, and vehicle treatment operators. The battery material producer is predestined to recover the materials, since this would be near to his core competence. By this means he can influence the characterisation of the raw materials directly and, concurrently, prevent potential competitors.

Figure 3: Combined mechanical and hydrometallurgical processes. [3] describe a combined pyrometallurgical and hydrometallurgical recycling process for lithium-ion batteries, amongst others, which is already applied at Umicore in Sweden and Belgium. Here, a mix of different consumer lithium-ion batteries is treated in a pyrometallurgical smelting process located in Sweden, ending in a slag containing aluminium, silicium, calcium, and lithium, and an alloy of cobalt, nickel, copper, and iron. The alloy is then transported to Belgium and treated with hydrometallurgical processes to separate the materials, while the materials in the slag may be consumed in lower value production processes. Although this process is already applied, it appears to be less suitable for recycling vehicle batteries in large scale, because valuable materials like aluminium and lithium are lost in the slag. However, in combination with subsequent hydrometallurgical processes, the recovering of these materials should be possible. 3.5

Network design and process configuration

As shown, the quantity and material specifications of the batteries which are to be used as educts fundamentally influence the eligible processes and their products (recovered materials, components, etc.). The configuration of processes, in turn, determines the spatial decoupling potential. In centralised concepts, all batteries would be treated in a single facility to realise economies of scale, resulting in low average costs due to high capacity utilisation. In contrast, a decentralised concept with many small facilities would enable short transportation links and thus low transportation costs. Processes with spatial decoupling points can provide both advantages. Decentralised pre-treatment with low economies of scale, e. g. manual disassembly, would allow for a concentration of the material flow to reduce transportation costs while reducing transport mass and volume by the separation of casings. The subsequent

Although the production of batteries may not be the core competence of vehicle producers today, it will most probably be in the future. Both, battery producers and vehicle producers, can be in charge for the correct treatment of the batteries by law, and both rely on the continuous supply with raw battery materials. So, a clear distinction is not necessary. From the producer’s point of view, the recycling must be carried out in a cost-minimising or profitmaximising manner. At the same time, he is bound to collect and recycle every battery that is given to him by the end-users. Thus, he cannot minimise costs by cherry-picking, but he can share his fixed costs and use economies of scale by the joint operation of a crossproducer network. All mentioned actors of the production chain are reliant on a continuous supply of raw materials. As mentioned in chapter 1, this may become a problem in the light of scarce and geographically concentrated resources. Given that, all producers will be interested in the supply from a secondary feedstock, even though the recovered materials may be costlier or a little less capable than primary materials. The vehicle dealer is involved since he will be the first address for users of electric vehicles if their battery is spent. His task will be the replacement of the spent battery with a new one. Thus, he is interested in an easy and free-of-charge solution for the redistribution of the received spent battery, without wanting to relevantly participate in the network. Nevertheless, his participation will be needed to gather information about the battery conditions. Exactly the same holds for the treatment operator who is engaged with the treatment of end-of-life vehicles. He, however, will try to charge the vehicle manufacturer with additional fees for the demounting of the battery, or alternatively sell it to others. These deliberations show that all actors should be interested in an optimised collection and recycling of spent batteries because the requirements of the actors mostly converge. This can only be achieved by planning and operating the network collaboratively. For the actors, economic interests are prior. Beyond that, they have to respect legal conditions and customer requirements. Therefore, environmental aspects have to be considered as well. For this reason, this framework addresses the design of a sustainable cooperative recycling network with focus on the producers who are legally responsible for its provision.

Automotive Life Cycle Engineering - Recycling 4.2

Requirements

As shown in chapter 3, a recycling network for lithium-ion batteries is subject to many uncertain factors that change over time. This requires a long-term planning horizon, in which uncertainties must be represented adequately. Decisions with respect to the design of the network include the selection of facility locations, processes, capacities, and the point in time of their implementation. Due to the described interdependencies between optimal network structure and recycling processes, these decisions must be done simultaneously. Possible synergy effects by the inclusion of existing sites and processes of recycling networks for vehicles, starter batteries, portable batteries, and electronic waste as well as their actors have to be examined. Sites of treatment operators and vehicle dealers are sources of the networks and could be used for regional collection and even for the disassembly of spent batteries. The processes for the recycling of the batteries, including mechanical, chemical, and thermal treatment, differ in many aspects. They must be represented in an adequately aggregated manner. Their eligibility must be assessed with respect to their differences in: 

material flows, including educts, raw materials and supplies, products, and their quality;



energy consumption;



environmental impacts in terms of pollutant emissions;

83 their prices, sources, production and mining methods, reuse potentials, and their scarcity will be analysed. Next, known and promising conditioning processes for these materials and the possible combinations will be screened. A preselection is necessary to narrow down the choice. This will be done by a comparison of the processes with respect to multiple criteria, namely monetary, ecological, social, flexibility, and safety criteria. For that purpose, aggregated material and energy flow sheet models of the processes will be used. For the equipment of the preselected processes, investment needs and costs depending on different capacities will be estimated in a pre-calculation, unless they are known. Potential decoupling points of the processes will be identified to determine the possibility of a decentralised recycling network. Transportation costs regarding the batteries and the different intermediate products will be estimated. Sources and sinks of the network will be identified. Subsequently, location factors for the collection and recycling sites will be established. Appropriate sites for recycling facilities will be classified regarding the different requirements of the various recycling processes. Again, a pre-selection of sites will be necessary. The inclusion of site-specific investments and costs will be investigated to couple interdependencies between expenses for sites, buildings, and equipment. To give decision support, a multi-staged dynamic facility location problem with the specific requirements of reverse logistics problems will be developed and then used in a mathematical optimisation. Input data are:



investments and costs, influenced by economies of scale;



subsequent expandability;



degree of flexibility regarding the processable materials and volumes;



long-term battery return estimations;



costs for transportation and storage of the batteries;



potential spatial decoupling of single process steps;



locations of existing sources and sinks;



hazard potential, particularly for the employees.



distances between these locations and potential collection and recycling sites;



costs and investment needs for facilities and processes;



ecological factors, e. g. CO2-emissions.

To represent centralised and decentralised installation concepts, a multi-stage recycling network must be considered. Processdependent material flows between sources and sinks have to be included. The structure of the network should be flexible to enable subsequent changes with respect to the combination of processes, their spatial decoupling, and capacity expansions. Furthermore, an option to store batteries to delay expenses, balance capacity utilisation, and use economies of scale has to be assessed. 4.3

Approach

The objective of our approach is to give decision support to investors regarding the provision of an optimised sustainable recycling network for lithium-ion batteries, including the selection of facility locations, processes, capacities, and the point in time of their implementation. Thus, this planning task can be classified into strategic network planning within the APS matrix. Strategic network planning approaches have been discussed in the literature for related recycling networks with similar characteristics, for instance, vehicle recycling [16], portable battery recycling [17], electrical equipment recycling [18], and large household appliances recycling [19]. Further similarities can be found in the strategic planning of a biofuel production network presented in [20]. These approaches mainly include location, transport, and capacity decisions; the latter is explicitly regarding uncertainties and process decisions. They provide the basis for the following approach, whereas some of the requirements listed in chapter 4.2 are not satisfied. E. g. none of the approaches considers a multiple objective optimisation. In the first step of our approach the materials which have to be recovered from the batteries due to economical, ecological, or strategic reasons will be identified. For that, the development of

The optimisation will be done with respect to different objective functions. Prevailing uncertainties will be considered by the application of scenario technique, robust optimisation, and sensitivity analysis. The findings will end in an extensive robust investment plan for the design of a sustainable recycling network for spent lithium-ion batteries. 4.4

Exemplary Network Alternatives

Scenario A: Centralised Network In scenario A, a centralised network with a combined pyrometallurgical and hydrometallurgical recycling process is established. Based on an unimportant electric vehicle market, the battery technology is not further developed or standardised. Because of the low amount of lithium-ion vehicle batteries produced, a shortage of resources does not occur, and cobaltbased active materials are prevalent. Only few batteries are available for recycling; consequently, a dedicated recycling network is not economical. In the network, batteries are collected from few specialised garages and brought to a centralised recycling facility that recovers materials from any kind of batteries containing cobalt or nickel to realise high capacity utilisation. Lithium, aluminium, and manganese are not recovered. The more valuable materials cobalt, nickel, and copper are recovered in high purities in a subsequent hydrometallurgical process at the same location and are sold to any kind of markets. Scenario B: Decentralised Network In scenario B, a decentralised network with a combined disassembly, mechanical and hydrometallurgical recycling process

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is established. A prospering electric vehicle market leads to strong technology advances regarding the lithium-ion batteries. These are produced at large scale, which leads to temporary shortages of raw materials. While miscellaneous compositions are used for the production of the cells, lithium-iron-phosphate emerges as the prevailing active material. The spent batteries are collected from dealers all over the country and are brought to decentralised disassembly facilities. Here, they are first used for energy storage until depletion. Afterwards, the batteries are disassembled to cell level. All materials except for the cells are brought to regional recycling facilities. The cells are transported to a centralised recycling facility where they are subject to mechanical and hydrometallurgical recycling. New active material is produced from the recovered lithium, nickel, manganese, and cobalt, and is sold to battery producers, as well as the recovered lithium salts and the electrolyte. 5

CONCLUSION AND OUTLOOK

In this paper, we presented a strategic framework for the design of recycling networks for lithium-ion batteries from electric vehicles. We analysed prevalent uncertainties related to potential sources, sinks, and processes for the recycling. The analysis showed that in particular the quantity of the return of batteries can be considered as uncertain, due to the early development stage of the electric vehicle market and missing experience regarding the lifetime of batteries. This complicates decisions about capacities in the network. Additionally, the uncertainties in the battery material composition and the price development for recoverable materials complicate process decisions. It is not clear which processes will emerge as eligible options for the sustainable recycling of batteries. We highlighted that the decision about processes considerably influences the network structure and must be integrated into the planning of the network. Based on that, we derived a framework, including an analysis of potential actors and requirements that must be considered designing a recycling network for lithium-ion batteries, and an integrated planning approach. Our future research will concentrate on the analysis of eligible processes and the implementation of the approach in a mathematical multi-objective optimisation model. 6

ACKNOWLEDGEMENT

The presented research work is part of the project “LithoRec – Recycling von Lithium-Ionen-Batterien”. LithoRec aims at developing and assessing sustainable processes and full life-cycle concepts for the recycling of spent lithium-ion batteries in Germany. We would like to acknowledge the support of the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety for funding the research cooperation under the reference 16EM0023. 7

REFERENCES

[1]

Gaines, L., Cuenca, R. (2000): Costs of Lithium-Ion Batteries for Vehicles. Operated by The University of Chicago, under Contract W-31-109-Eng-38, for the United States Department of Energy, Argonne, Illinois. http://www.doe.gov/bridge.

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U.S. Geological Survey (2010): Mineral commodity summaries 2010, Washington. http://minerals.usgs.gov/ minerals/pubs/mcs/2010/mcs2010.pdf (accessed October 26, 2010).

[3]

Dewulf, J., van der Vorst, G., Denturck, K., van Langenhove, H., Ghyoot, W., Tytgat, J., Vandeputte, K. (2010): Recycling rechargeable lithium ion batteries: Critical analysis of natural

resource savings, in: Resources, Recycling, Vol. 54, pp. 229–234.

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Deutscher Bundestag (2009): BattG. June 25, 2009.

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Shukla, A. K., Prem Kumar, T. (2008): Materials for nextgeneration lithium batteries, in: Current Science, Vol. 94, No. 3, pp. 314–330.

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Arora, P., Zhang, Z. J. (2004): Battery Separators, in: Chemical Review, Vol. 104, pp. 4419–4462.

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Book, M., Groll, M., Mosquet, X., Rizoulis, D., Sticher, G. (2009): The Comeback of The Electric Car? How Real, How Soon, and What Must Happen Next, 1/09 Rev.2.

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Bundesministerium für Umwelt (2009): Programm Marktaktivierung für Elektrofahrzeuge, Berlin.

zur

[10] Sarre, G., Blanchard, P., Brouselly, M. (2004): Aging of lithium-ion batteries, in: Journal of Power Sources, Vol. 127, pp. 65–71. [11] Marano, V., Onori, S., Guezennec, Y., Rizzoni, G., Madella, N. (2009): Lithium-ion Batteries Life Estimation for Plug-in Hybrid Electric Vehicles, in: 5th IEEE Vehicle Power and Propulsion Conference, VPPC '09, pp. 536–543. [12] Notter, D. A., Gauch, M., Widmer, R., Wäger, P., Stamp, A., Zah, R., Althaus, H.-J. (2010): Contribution of Li-Ion Batteries to the Environmental Impact of Electric Vehicles, in: Environmental Science & Technology, Vol. 44, pp. 6550– 6556. [13] Zackrisson, M., Avellán, L., Orlenius, J. (2010): Life cycle assessment of lithium-ion batteries for plug-in hybrid electric vehicles - Critical issues, in: Journal of Cleaner Production, Vol. 18, pp. 1517–1527. [14] Xu, J., Thomas, H. R. F. R. W., Lum, K. R., Wang, J., Liang, B. (2008): A review of processes and technologies for the recycling of lithium-ion secondary batteries, in: Journal of Power Sources, Vol. 177, pp. 512–527. [15] Kwade, A. (2010): LithoRec - auf dem Weg zum "intelligenten" Recycling von Traktionsbatterien, in: 7. Braunschweiger Symposium Hybrid-, Elektrofahrzeuge und Energiemanagement, Braunschweig. [16] Püchert, H. (1996): Ein Ansatz zur strategischen Planung von Kreislaufwirtschaftssystemen: dargestellt für das Altautorecycling und die Eisen- und Stahlindustrie. Mit einem Geleitw. von Otto Rentz, Dt. Univ.-Vlg., Wiesbaden. [17] Schultmann, F., Engels, B., Rentz, O. (2003): Closed-Loop Supply Chains for Spent Batteries, in: Interfaces, Vol. 33, No. 6, pp. 57–71. [18] Walther, G., Spengler, T. S. (2005): Impact of WEEE-directive on reverse logistics in Germany, in: International Journal of Physical Distribution & Logistics Management, Vol. 35, No. 5, pp. 337–361. [19] Walther, G., Spengler, T. S., Queiruga Dios, D. A. (2008): Facility location planning for treatment of large household appliances in Spain, in: International Journal of Environmental Technology and Management, Vol. 8, No. 4, pp. 405–425. [20] Walther, G., Schatka, A., Spengler, T. S. (2007): Gestaltung von Netzwerken zur Produktion von synthetischen Biokraftstoffen der zweiten Generation, in: UWF Umweltwirtschaftsforum, Vol. 18, No. 1, pp. 61–69.

Recovery of Active Materials from Spent Lithium-Ion Electrodes and Electrode Production Rejects 1

1

Christian Hanisch , Wolfgang Haselrieder , Arno Kwade 1

1

Institute for Particle Technology, Technische Universität Braunschweig, Braunschweig, Germany

Abstract This article describes two ways to recover valuable and ecologically critical active materials from spent lithium-ion electrodes and electrode production rejects, using the example of a system containing LiNi0.33Co0.33Mn0.33O2 (NMC) active material and a polyvinylidene fluoride (PVdF) binder. First, a physical process using thermal treatment and mechanical stressing to separate the coating from the aluminum foil is discussed. Furthermore, a wet chemical processing using the solvent n-methyl-2-pyrrolidone (NMP) is presented. Recovered coating materials from both processes were characterized by laser diffraction spectroscopy and atomic absorption spectroscopy. Additionally, recycling electrodes were produced and successfully tested in battery test cells. Keywords: Electrode Recycling; Lithium-Ion-Batteries; Production Rejects

1

INTRODUCTION

The increasing demand of lithium-ion traction batteries implies the need for recovering active materials from spent lithium-ion-batteries (LIB) as well as from electrode production rejects to prevent a future shortage and to minimize the dependence on imported key raw materials for lithium battery production. Lithium-ion-battery cells consist of several layers of cathodes and anodes, which are electrically isolated by an ion permeable separator to form several compartments where the electrochemical reactions can take place. These electrode-separator assemblies are embedded in a housing filled with an organic electrolyte containing a lithium rich salt. Wetting the electrodes and separators with electrolyte allows the transfer of lithium-ions between the electrodes. During the discharging process lithium-ions are transferred from the anode to the cathode, where these are inserted in a metal containing lattice structure in order to gain electrons. The electrons are transferred through the composite particle coating of the electrode towards to the current collector (anode-copper, cathode-aluminum), which itself is connected to the external electrical circuit of the battery. The described charging and discharging processes cause electrochemically, chemically and mechanically induced aging effects with a major influence on the battery performance. Since traction battery applications require extended life times of 12 – 15 years or of 4000 up to 5000 charge/discharge cycles these effects are of high significance. Active materials, predominately used on the anode side, are porous graphite hosts. While lithium mixed metal oxides (e.g. LiNi0.33Co0.33Mn0.33O2, NMC) are state of the art for cathodes in the first generation of lithium-ion traction batteries. Therefore, they will be the first materials to be recycled. This research concentrates on the recycling of cathode materials since beside lithium valuable metals such as cobalt, nickel and manganese are contained. To lower the battery material investment costs material researchers try to replace these metals. A good example is lithium-iron-phosphate, which already has been established in industrial electrode production during the last two years. One has to take into account that without valuable metals lithium is the only economical concern

to develop recovering processes. Therefore a recycling process, including a hydrometallurgical processing of the coating powder, is the only pathway to recover of lithium rich products such as LiOH and Li2CO3. These are educts for the synthesis of active materials or can be reused in secondary markets. In pure pyro-metallurgical processes lithium is lost. Selective recycling of the electrodes is of high economic interest, taken into account that 

the proportion of active materials is significantly higher in traction batteries compared to smaller consumer batteries,



the current collectors and especially the electrochemically active materials are the components of greatest economic value in the cell,



approximately 75% of the costs of a electric vehicle battery system are determined by the battery cell investment.

Therefore, systematic disassembling of battery systems and the following separation of the coating materials from current collector foil as well as the hydrometallurgically reprocessing of the re-won coating powder may be economically and ecologically in advance to classical pyro-metallurgical processes. This is the approach of the research project LithoRec in whose framework this research was done. There are lots of research and development activities concerning the recycling of lithium-ion-batteries. Recent studies [1],[2],[3], and [4] give a good review about the state of the art. These processes are designed to recycle aged lithium ion secondary batteries in order to recover the valuable metals and partly to re-synthesize the active materials. In contrast to the approach of this research they are intended to recycle smaller consumer batteries. In these processes complete battery systems are destroyed mechanically or thermally to recover valuable metals subsequently by combining pyro- and hydrometallurgical processes. The purpose is to regain materials with a minimal effort and highest quality requirements, which also allow the reuse in the field of LIB, especially directly as recovered cathode material. On the other

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_15, © Springer-Verlag Berlin Heidelberg 2011

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hand, the developed processes can result in highly concentrated suspensions, which can be used as educts for hydrometallurgical processes to recover lithium, cobalt and other purified products. Therefore, the aim was to recover the coating powder from electrode production rejects and cycled NMC electrodes. A direct recoating of the active material applying a merely mechanical process, an alternative wet chemical recovering process or a combination of both is the main focus of this research. Basic process engineering principles were applied to separate the current collector mechanically from the particle coating. By varying the process parameters and the pretreatment of the cathodes, the coating should be separated with the highest possible yield. Additionally, the quality criteria for a use in a direct recoating process had to be achieved. At first, the particle size distribution of the re-won powder should be similar to the one of the original powder. Bigger agglomerates would result in irregularities in a recoated electrode or would have a smaller specific surface for a following hydrometallurgical process. Whereas smaller particles would imply, that the NMC particles had been broken during the deagglomeration process. The aluminum contamination should be minimal, because aluminum can react with hydrochloric acid during the leaching step and detonating gas could degas. Furthermore, the later removal of aluminum reduces the efficiency of the hydrometallurgical step. 2

EXPERIMENTAL

At the LithoRec project two process paths were developed to separate the current collector from the coating in order to gain both fractions in the best purity. Both processes were developed using NMC cathode production rejects, which had not been cycled electrochemically before. The production rejects consist of a 20 µm aluminum foil and a coating composed of NMC, a PVDF based binder and conducting agents. Later, these processes were validated by using electrodes from spent battery cells. These electrodes had been pre-dried for 10 minutes at 120 °C to evaporate the volatile fraction of the electrolyte. 2.1

Figure 1: Physical separation process. 2.2

Wet chemical separation process

The wet chemical process used for this research consists of the steps presented in Figure 2. A pre-cutting step, either manual or using a cutting mill, is necessary to allow stirring of the foil-solvent mixture (step 2). In this research the pre-cut electrode rejects were stirred batch-wise in n-methyl-2-pyrrolidone (NMP) at a temperature of 90 °C for 10-20 minutes. An amount of 200 g NMP had to be used to process 100 g shredded electrode production rejects. The solving procedure was repeated six times with the same foil fraction. Afterwards, the pieces of foil were screened at 50 µm and the fine fraction was centrifuged. The centrifugal sediment was dried at 150 °C and pulverized by an ultra centrifugal mill. Finally, the product was a powder which can be used in a direct recoating process on the one hand or processed hydro-metallurgically on the other hand.

Physical separation process

The developed physical separation process (Figure 1) can be subdivided into 4 parts: pretreatment, mechanical stress, separation, and deagglomeration. Drying for 12 hours at 150 °C or calcination at 500 °C for 15 minutes in a muffle oven turned out to be effective pretreatment steps. During the second step the pretreated production rejects were stressed in a cutting mill with a rotor peripheral speed of up to 10 m/s using a 2 mm trapezoid sieve affecting the product grit size. Afterwards the product was sieved at a mesh size of 200 µm and the resulting fine fraction was deagglomerated in an ultra centrifugal mill with a rotor peripheral speed of up to 60 m/s. Thus, the specific surface of the resulting particles was enlarged to accelerate the following leaching process if a further hydrometallurgical treatment is carried out. Moreover, the pulverization of agglomerates results in a better coating quality regarding a direct recoating process since micron sized agglomerates bound by the PVdF binder are deagglomerated. Without this treatment agglomerates of approximately 200 µm up to 300 µm were observed as irregularities in the recycled coating layer. Being considered the main recycling product only the active material was balanced to quantify the separation results. Thus the fine fraction below 200 µm was accounted as separation product.

Figure 2: Wet chemical separation process.

Automotive Life Cycle Engineering - Recycling 2.3

87

Analysis

Electrode material suspensions and recycling electrodes had been prepared by dissolving the recovered materials with and without small amounts of additional binder and finally applying a standardized electrode blade coating process using NMP as solvent. The adhesive strength and the structure of the recycled electrodes were analyzed in addition to an electrochemical characterization. Furthermore, laser diffraction spectroscopy and atomic absorption spectroscopy had been applied to detect the particle size distribution of the recovered active materials and the aluminum contamination. 3 3.1

RESULTS AND DISCUSSION

Spent NMC Electrodes Cutting Mill: RCS = 10 m/s, Six Disc Rotor, 2mm Trapezoid Sieve

-1

< 200 µm

Yield of Recycling YR / kg*kg

The aluminum contamination of the fine fraction was measured by atomic absorption spectrometry. It was determined to 0,7-1% by weight. Since the contamination did not increase with higher rotational speed even higher stress intensities could be tested in further studies. After the deagglomeration step in the ultra centrifugal mill the remaining aluminum foil pieces and agglomerates below 200 µm are pulverized from a medium particle size of 90 µm to 13 µm. Thus, the resulting powder had a particle size distribution (PSD) similar to the one of the industrial standard. Here the PSD was measured by dry dispersed laser diffraction spectrometry.

Physical process

1,0

caused by higher specific stress intensities with increasing rotational speed. Rotor/electrode and stator/electrode impacts become more intensive and higher fracture energy is provided. Thus, the coating layer breaks and flakes off the foil. At lower rotational speeds the stress mechanisms tend to shear and cut with lower specific stress intensities. Whereas a bottom sieve determines the maximum product size so that the foil pieces are stressed until they reach the separation size in any case.

Following, electrodes were made from the recovered coating material by using a standardized NMP based electrode coating process. No supplementary binder was necessary while coating non-calcinated active materials from electrode production rejects. Whereas, for spent electrode materials an amount of 1 wt% PVdF binder had to be added in order to get a mechanical stable coating. This process yet has to be validated for calcinated active materials.

0,8

0,6

0,4

However, adhesion tests of these recycled electrodes indicated that the binder had not lost its functionality by processing.

0,2

0,0

Without

Drying

Calcination

Pretreatment Figure 3: Influence of thermal pretreatment strategies on the Yield of Recycling of spent NMC electrodes. The influence of different thermal strategies on the separation grade of spent NMC electrodes is shown in Figure 3. The Yield of Recycling YR should be defined as the mass of rewon active material, in this research study NMC, in relation to the mass of inserted active material. Processing spent electrodes only pre-dried for 10 minutes at 120 °C results in a separation yield lower than 30% of the inserted active material. Whereas drying for 12 hours at 150 °C with a loss of mass of only 0,4wt% already increases the yield to over 80wt%. This can be explained by embrittlement of the PVdF binder by some chemical reactions with the electrolyte. A calcination of the spent electrodes at 500 °C for 15 minutes before stressing them in the cutting mill leads to a yield of over 99.5wt%. According to thermogravimetric analysis the PVdF binder volatizes at 500 °C. This lowers the adhesion between coating and foil to a minimum and thus coating material and aluminum foil can be separated easily. The parameterization of the milling step, especially concerning the rotor circumferential speed, was carried out with production rejects not pretreated and coated on one side only. The rotor’s circumferential speed (RCS) was varied from 1.2 to 10 m/s and the Yield of Recycling was determined by sieve analysis as shown in Figure 4. The fine fractions increase with the rotor’s rising circumferential speed, e.g. the fraction below 200 µm shows an increase from 51% at 1.2 m/s to 78% by weight at 10 m/s. This is

These cathodes were electrochemically cycled in stacked pouch cells cells containing a recycling cathode of 25 cm², a ceramic separator, a graphite anode and LiPF6 as electrolyte. The specific capacity of the recovered NMC from production rejects measured 150 mAh/g at discharge rates of 0.5C and 125 mAh/g at discharge rates of 3C. Due to the variance in electrode preparation and in the cell assembly process these results have to be considered in the same order of magnitude like the capacity of the commercial reference material. Furthermore, the recycling cells had 87.5 % of their initial capacity after 500 cycles at charge/discharge rates of 3C/3C. In comparison, the reference electrode still had 95% of its initial capacity after 500 cycles, as shown in Figure 6. The active material, removed from spent electrodes, had a capacity of 82 mAh/g at a cycling rate of 0.5 C and a capacity of 42 mAh/g at cycling rates of 3C. The cycle stability tests showed no further capacity reduction during the next 500 cycles. And Atomic absorption spectroscopy showed a loss of lithium of about 6 %. Additionally the capacity of 0.5 C is twice as high as the one at 3 C. Due to these facts the reason for the lower capacity of the recycled electrode is seen in structural deformation of the active material and reduced electrical conductivity of the electrode coating layer. The latter is caused by the insufficient use of the conducting agents (acetylene black and conducting graphite). Calcination of these materials and replacing them by new ones will validate this theory in further studies. Another explanation for the reduced capacity is an immobilization of lithium during the formation of the solid electrolyte interface (SEI). The SEI formation occurs during the first cycles on the anode side, where lithium is lost by the SEI film formation on the boundary layer between the electrolyte and the solid particles of the electrode Therefore, it could be that the second delithation of the NMC material leads to a critical amount of lithium in the lattice structure which contributes to the partial destruction of the layered structure of the metal oxide.

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.

advantage for a leaching process if a hydrometallurgical processing is performed later. Sieve Fractions < 200 µm < 160 µm < 100 µm < 75 µm < 50 µm < 20 µm

100 90

Yield of Recycling YR / kg*kg

-1

80 70

NMC - Electrode Production Rejects Oneside Coated, Not Pretreated Cutting Mill: Six Disc Rotor, 2mm Trapezoid Perforated Sieve

As already described for the physio-mechanical process electrodes were made from the recovered coating material using a standardized electrode coating process. To coat the chemically separated powder PVdF binder was added this time in the dose of the original formula to replace the binder lost in the dilution during the recycling process. These cathodes were built into pouch cells containing one recycling cathode, a ceramic separator, a graphite anode and LiPF6 as electrolyte. Electrochemically tested, these cells still had 92.9 % of their initial capacity after 500 cycles at charge/discharge rates of 3C/3C.

60 50 40 30 20

140

10 120

2

4

6

8

10 -1

Rotor's Circumferential Speed (RCS) / m*s

Figure 4: Influence of the Rotor Circumferential Speed on the Yield of Recycling. Wet chemical separation process

1,0

NMC Electrode Production Rejects Wet Chemical Separation Process

Specific Capacity / mAh*g

0

-1

0

3.2

Electrochemical Testing Charge / Discharge Rate 3C/3C 25 cm² Pouch Cell, C = 44 mAh, T = 21 °C

100

Material / Separation method Reference rejects / mechanical rejects / chemical cycled / mechanical

80

60

40

20

Solvent NMP, 90 °C, Stirred 15 min

R

-1 Yield of Recycling Y / kg*kg

0 0

0,9

100

200

300

400

500

Cycle / -

0,8

Figure 6: Electrochemical test results of re-coated NMC electrodes.

0,7

4

0,6

0,5 1

2

3

4

5

6

Number of treatment steps [-]

Figure 5 : Recycling yield of batchwise wet chemical separation. As shown in Figure 5 the absolute yield of active material recycling increases with the number of treatments the foil receives. And it reaches 97wt% after the sixth treatment. The main problem of this segmented process is represented by the lack of solvent in the final phase of separation. The already detached active material partly adheres to the remaining foil when the last solvent has drained through the sieve. Thus, a process with a circulating solvent should be used to wash the remaining active material off the foil in the future. The re-won material exhibits a PSD being similar to industrial standard after pulverization by ultra centrifugal milling. The aluminum contamination measured only 0.06 wt%, which is ten times less than in the mechanical process. This represents an

SUMMARY AND CONCLUSION

In this study two processes to recover active materials from spent lithium ion battery electrodes and electrode production rejects have been developed in this study. On the one hand the physical process using thermal treatment and mechanical stressing to separate the coating from the aluminum foil seems to be the easier and economically more feasible way to separate active materials from the current collector foil. This is mainly because no expensive, unhealthy and chemically aggressive solvent is needed. Further, the equipment to realize this process is simple and thus less costly. By varying the process parameters and by calcinating the cathodes in a pre-treatment step, the coating could be separated with a yield of 98 percent and higher, achieving the quality criteria for a direct recoating process. On the other hand the main advantage of the wet chemical process is the less aluminium contamination of the product. Recycling electrodes from both processes were successfully tested in pouch cells and the first recycling electrodes made of the powder recycled by the wet chemical process had the better electrochemical cycle stability with 92.9% of the initial capacity after 500 cycles at charge/discharge rates of 3C/3C. Considering, the discussed separation of the coating will most likely become a preparation step for a hydrometallurgical treatment, the physical separation fulfils the requirements better. Only in case of a

Automotive Life Cycle Engineering - Recycling direct reuse of the solvent solution for re-coating the wet chemical separation has an advantage. 5

ACKNOWLEDGMENTS

The presented work was generated as part of the research project LithoRec, which is funded by the German Federal Environment Ministry (BMU). The authors would like to thank the BMU for the financial support. 6

REFERENCES

[1]

Bernardes, A.M.; Espinosa, D.C.R.; Tenório, J.A.S (2004): Recycling of batteries: a review of current processes and technologies, in: Journal of Power Sources, Vol.130, pp. 291– 298.

[2]

Espinosa, D. C. R.; Bernardes , A. M.; Tenório, J. A. S. (2004): An overview on the current processes for the recycling of batteries, in: Journal of Power Sources, Vol.135, pp. 311–319.

[3]

Heegn, H.; Rutz, M.(2008): Rückgewinnung der Rohstoffe aus Li-Ionen-Akkumulatoren, in: Teilvorhaben 3 Batterie- und Schlackenaufbereitung. Freiberg, p. 35 ff.

[4]

Xu, J.; Thomas, H.R.; Francis, R.W.; Lumb, K.R. (2008): A review of processes and technologies for the recycling of lithium-ion secondary batteries, in: Journal of Power Sources, Vol.177, pp. 512–527.

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New Technologies for Remanufacturing of Automotive Systems Communicating via CAN Bus 1

1

1

1

2

Rolf Steinhilper , Stefan Freiberger , Matthias Albrecht , Josef Käufl , Eberhard Binder , Constantin Brückner 1

2

Chair of Manufacturing and Remanufacturing Technology, Bayreuth University, Germany 2

University of Applied Sciences Coburg, Germany

Abstract The present paper summarizes the recent methodologies, technologies, results and opportunities in the field of analyzing and extending the life cycle of automotive systems by remanufacturing that have been developed within the European research project “CAN REMAN”, conducted by Bayreuth University in cooperation with two other universities and eight industrial partners. The aim of this project is to develop appropriate and affordable testing and diagnostics technologies that enable small and medium sized enterprises (SME) to remanufacture mechatronic vehicle components. Keywords: Remanufacturing; Testing Automotive Components; CAN Bus Communication

1

INTRODUCTION

Raising requirements on occupant safety and comfort on the one hand and the introduction of new emission regulations on the other hand, forces the automotive manufacturers to enhance their products continuously. In order to achieve these improvements, electronic systems, based on microcontrollers, have found their way into modern cars and they contributed considerably to many new advantages in terms of safety and comfort such as ESP/ESC (Electronic Stability Program), ABS (Antilock Breaking System), PAS (Parking Assist System), EHPS (Electro Hydraulic Power Steering) or EAS (Electro Assisted Steering). Nevertheless, the new trend of modernization has an immense impact on the remanufacturing business. It can be seen that new branches in electronic remanufacturing arise. In contrast to that, the knowhow of traditional remanufacturing companies has eroded rapidly and even the industrial principle of remanufacturing is at risk. Due to the fact that modern cars incorporate up to 80 of these mechatronic and electronic systems that are communicating with each other e.g. via the vehicle controller area network (CAN), remanufacturing of these automotive systems requires innovative reverse engineering knowhow, methodological innovations and new technologies, especially focussing on the tasks testing and diagnostics of systems and their subassemblies. Since traditional remanufacturing companies do not have much capacity to build up the appropriate knowhow, the Chair of Manufacturing and Remanufacturing Technologies at Bayreuth University assists these companies in reverse engineering, as well as finding new methodologies and technologies for remanufacturing [1] [2]. In the following chapters, recent methodologies and technologies for automotive components will be presented on the example of an electro-hydraulic power steering (EHPS) pump. The results have been obtained within the European research project “CAN REMAN” which is conducted by Bayreuth University, Linköping University (Sweden), the University of Applied Sciences Coburg, Fraunhofer Project Group Process Innovation and eight industrial partners. The target of this project is to enable independent aftermarket (IAM) companies to remanufacture modern automotive mechatronics for

multiple life cycles and electronics with innovative reverse engineering skills as well as to develop appropriate and affordable testing and diagnostics technologies. 2

REMANUFACTURING TODAY

Remanufacturing is defined and known as the industrial manufacturing of “good as new” products from used and returned products. This means, that remanufacturing is the process of restoring a non-functional, discarded or traded-in part to like-new condition, giving the product a further life. The products, also known as “cores”, are brought to a shop floor, where they run through the five steps of remanufacturing [3] [4]. 2.1

The Remanufacturing Market - A hidden Giant

While early remanufacturing was limited to a hand full of expensive capital (so called “investment”) goods, the number and variety of remanufactured products is tremendous nowadays and it is still increasing [5]. Even though the estimations about the current scope of remanufacturing activities vary, two comprehensive studies discovered the impact on the economy in the US. The first study, published in 1996 and updated in 2003 by Lund of Boston University is summarized in Table 1. Lund divided the great variety of currently remanufactured products into six major classes as pointed out by Table 1 [3] [6]. Categories Automotive components Electrical devices Office furniture Machines Tires Toner cartridges Others Summation

Companies [Amount]

Annual Turnover [Mio. $]

Employees [Number]

50.538

36.546

337.571

13.231 720 685 1.390 6.501 250 73.315

4.633 1.663 1.272 4.308 2.475 2.009 52.906

47.280 12.148 10610 27.907 31.872 14.372 481.760

Table 1: Main remanufacturing categories and their magnitude in USA [6].

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_16, © Springer-Verlag Berlin Heidelberg 2011

90

Automotive Life Cycle Engineering - Recycling The second and more reliable study, conducted by the OEM Product-Service Institute (OPI), is based on a different methodology to fill in the gaps from the Lund study. The idea was to use the current replacement value (CRV) of actual products as basis for estimating the remanufacturing expenditures. These remanufacturing costs were estimated by experts from each industry as a percentage of the CRV. The benefit of this study, which does not make extensive use of real data, such as in Lund’s study, is that a broader range of industries was addressed [7]. The results of the OPI study can be found in Figure 1.

91 measures are applied in every step [1] [4]. At the end of the process chain, each remanufactured product has to pass a 100 % test which should be seen as an integrated part of the whole process chain rather than as an independent “sixth step” [4]. At the bottom line, all remanufactured products arrive at the customers with the same quality level compared to the factory brand new counterpart, or even better [1]. 3

AUTOMOTIVE MECHATRONICS REMANUFACTURING

CHANGE

TODAY’S

The term “mechatronics” was formulated in 1969 in Japan and it is an artifice that describes a system which combines mechanics, electronics and information technologies. A typical mechatronic system gathers data, processes the information and outputs signals that are for instance converted into forces or movements [8]. 3.1

Figure 1: Remanufacturing expenditures by industry [7]. Although the estimates differ to a certain extent, the conclusion given is clear. Remanufacturing offers tremendous untapped opportunities. One of the most beneficial area for remanufacturing is the automotive sector that covers 70 % of all remanufacturing companies and that has an annual turnover of 36 Billion US-$. The background of these companies highly differs. While in some cases OEMs and OEs remanufacture their own products, the plurality of remanufacturers is of smaller subcontractor or “third party” nature. Those smaller companies need to reverse engineer the products themselves. 2.2

Remanufacturing in a five-step-process

As stated before, remanufacturing, also referred to as product recycling, is organized in an industrial process, in order to have the same advantages and benefits as series production. Among others, the remanufacturing process in five steps (Figure 2) aims to maintain a constant quality level as well as to formulate a rational and reproducible production process. Quality Assurance 1. Complete Disassembly of the Product 2. Through Cleaning of all Parts 3. Inspection and Sorting of all Parts 4. Reconditioning of Parts and/or Replenishment by new Parts 5. Product Reassembly

Final Testing Figure 2: Traditional remanufacturing process chain [4]. In order to reach the same quality level, product reliability, safety and lifetime level, to meet current safety standards and to provide the same warranty like a new product, adequate quality assurance

Technological Change of Vehicles

Automotive parts should not longer be seen as isolated standalone applications with few mechanical and electrical inputs and outputs. Now, they have the capability to communicate to each other and to share the same sensor information. Subsequently, the communication of the different automotive subsystems helps the OEMs to reduce weight and cost by sharing the same sensors and reducing cable doubling (cable length) in modern vehicles. For the driver the network and communication within the car remains invisible and he feels the car behaving like ten years ago despite of some additional comfort functions. But if we take a closer look, modern vehicles resemble more or less a distributed system. Several embedded computers – often referred to as electronic control units (ECUs) – communicate, share information and verify each other over the vehicle network. One of the commonly used communication networks in vehicles is the CAN-Bus (Controller Area Network). Within this network structure, each control unit has at least one unique identifier (ID) on which it broadcasts messages that again incorporate different signals and information [8]. Easily speaking, in case of a missing or faulty participant in the network, all other controllers will notice the participant as they have a lack of information. The lack of information or errors on the CAN bus force the other systems to operate in a “safe mode”. In reverse, a controller not connected to the specific vehicle network stops its operation patterns and falls into “safe mode”. 3.2

Difficulties for Remanufacturers

As stated before, the introduction of electronic networks into modern cars entails enormous problems for remanufacturers. Modern electronic and mechatronic vehicle components cannot be tested as easily as traditional electrical and mechanical ones. While it was usually sufficient to link electrical systems to the power supply (battery), modern mechatronic and electronic systems gather a lot of information from the vehicle environment and driving conditions using plenty sensors and the CAN bus network of the vehicle. As a consequence, connecting all sensors and the power plug to the device under test (DUT) is insufficient unless the device is connected to the network of a real car or an adequate simulation of the communication in the vehicle. Following these statements, the key for successful remanufacturing and testing of a certain automotive system lies in the simulation of the complete network communication in the vehicle. Unfortunately, there are no tools available in the market that allow the remanufacturers to simulate a complete car of a specific type and model easily. In each case, the car matrix (CAN database) of the specific vehicle model is required to build a simulation of the CAN communication in a vehicle. However, the OEMs will not release any information on the communication parameters to non-OEs and

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therefore they will not support the independent remanufacturing business. As a consequence, the independent remanufactures (onto which this paper focuses) have to do a lot of reverse engineering themselves or in cooperation with others in order to design their remanufacturing process chain and to come up with test solutions to ensure the quality of their products. The reverse engineering activities focus on the system, its components, the system behavior in the vehicle and the vehicle CAN bus communication. 3.3

The Remanufacturing Process Chain for Automotive Mechatronics

Following the previous aspects, the state-of-the-art process chain for remanufacturing, presented in chapter 2.2., needs to be reconsidered when it comes to mechatronics. Regarding the process steps, disassembly, cleaning and reassembly, great progress has been made, as it can be found in the literature [10] [11] [12]. Primarily, the diagnostics and testing differs to a certain extend from the traditional (final) testing of mechanics, as it has already been discussed before. In addition to this, it was found that a lot of failures of parts and its subassemblies can only be detected or isolated with a test of the completely assembled mechatronic system [1], e.g. by utilization of the onboard-diagnostics and the fault memory of a mechatronic system. This means that the process chain for remanufacturing of mechatronic systems should be extended by an additional first step. The initial (entrance) diagnostics of the system to be remanufactured imply that the product itself and its communication patterns have been reverse engineered before and the appropriate simulation model of the reference vehicle has been developed so that the tested product “feels” like in its original environment. 4

UNDERSTANDING AN AUTOMOTIVE SYSTEM BY REVERSE ENGINEERING

MECHATRONIC

The term “reverse engineering” has its origin in the mechanical engineering and describes in the original meaning the analysis of hardware by somebody else than the developer of a certain product and without the benefit of the original documentation or drawings. However, reverse engineering was usually applied to enhance the own products or to analyze the competitor’s products [13]. Chikovsky describes reverse engineering in the context with software development and the software life cycle as an analysis process of a system, in order to identify the system (sub-) components, to investigate their interaction and to represent the system at a higher level of abstraction [13]. In this context, he also clarifies the terms “redocumentation” and “design recovery”. “Redocumentation” is the generation or revision of a semantically equivalent description at the same abstraction level. That means that the results are an alternative representation form for an existing system description. However, redocumentation is often used in the context of recovering “lost” information [13]. The term “design recovery” defines a subset of reverse engineering that includes domain knowledge, external information (of third parties) and conclusions additionally to the original observations and analyses in order derive meaningful abstractions of the system at a higher level [13]. Overall, reverse engineering of software in the development focuses on the following six targets [13]: 

Coping with the system complexity



Generation of alternative views



Recovery of lost information



Detection of side effects

software



Synthesis of higher abstractions



Facilitation of reuse

These targets, that have originally been defined for software reverse engineering, can also be transferred to a certain extend to the reverse engineering of automotive mechatronic systems and hence to the remanufacturing of these systems. First, remanufacturers face the same problem that they usually have to cope with complex mechatronic systems as stated before. “Cope” means in this context, that it must be possible to operate an automotive mechatronic system independently from its original environment (the vehicle). Second, it is possible to detect universal taxonomies which can then be abstracted and used in order to transfer the gained knowledge to similar mechatronic systems or to other variants of the system. Especially the high degree of variation of similarly looking mechatronic systems and control units makes it difficult for the remanufacturers to cope with the complexity of automotive components that usually differ by a slight detail [14]. Third, recovery of missing information rather than lost is one of the most important aspects for the remanufacturing. The following chapter demonstrates how a reverse engineering analysis can be conducted for an automotive mechatronic system. 5

ANALYZING AN AUTOMOTIVE SYSTEM IN FIVE STEPS

After a reference system for the analysis has been chosen it is necessary to procure at least one, ideally brand-new, system to grant correct functionality, for all following investigations. In order to analyze the system in its normal working environment, the original vehicle, in which the reference system commonly is built in, should be procured as well. This investment might be unavoidable, because a mechatronic system communicating via CAN, detached from all other vehicle communication will not work anyway, as essential input information, transmitted via CAN, is missing otherwise (refer to chapter 3). In this case it is very difficult to understand the ECU communication and put up the system into operation isolated from the vehicle. A cheaper way to investigate the communication between vehicle and reference system is to create a CAN trace using a software tool such as “CANoe” from Vector Informatics. This tool allows easily recording of the complete vehicle communication for instance while doing a test drive with a vehicle that may be available only once. Whatever strategy is chosen, it is essential to figure out which input (CAN data) is required to start, operate and control the system. 5.1

Electrical Wiring

After having obtained a reference system, it is essential to know the pinout of all connectors of the system. Therefore, the very first step is to find out which pin belongs to which wire and signal. First of all, the power connector (ground and positive terminal), including ignition, must be identified. One opportunity to obtain this information is the utilization of wiring diagrams or similar credentials. If such documents are not available, for example a visual inspection of the connectors and wire harness in the vehicle or continuity measurements can be beneficial. Afterwards, it is indispensible to identify the CAN connection pins. These can easily be recognized by inspection of the cable harness. In most cases two twisted wires indicate a CAN bus connection, but single wire CAN connection is possible, too. Finally, all connectors for sensors and actuators (auxiliary power and sensor/ actuator signal) must be known as well to go further in the analysis process.

Automotive Life Cycle Engineering - Recycling 5.2

Vehicle Network Topology

The investigation of the structure of all bus systems in the vehicle is placed in front of the proper CAN bus analysis step. It is necessary to determine how many (CAN) bus networks are established and in which network the references system is located. Additionally, the network speed, the presence of a separate diagnosis network (e.g. K-Line), and all ECUs of the specific networks must be found out. Especially those ECUs that provide essential input as mentioned before. Furthermore, possible gateway ECUs should be identified. A feasible solution to gain this information can be for example a web inquiry, documents from the manufacturer of the vehicle or the system, third party documents or technical journals. 5.3

CAN Bus Communication

Having collected all information about the (bus) network structure of the vehicle, detailed knowledge about the received CAN messages and transmitted CAN data is necessary. In the first step, all ECUs and its associated CAN message IDs must be determined. For this purpose CANoe can be used. First of all, a physical connection to access the CAN bus using CANoe has to be installed in the vehicle, ideally nearby the reference system ECU. With the “trace functionality” of CANoe the bus communication and all CAN messages of all ECUs can be displayed easily. Beside of the CAN IDs, the cycle time and the length of each message can be analyzed. This information is relevant for a later rest bus simulation of all participating ECUs to ensure correct functionality of the reference system. The assignment of CAN ID and the associated ECU is more difficult. One possibility to gather this information is, to locate all ECUs which provide relevant data on the CAN bus and to separate the CAN wires out of the cable harness. Afterwards, a kind of software gateway is installed in between the DUT and the other ECUs using CANoe and a simple CAPL (CAN Access Programming Language) program. Each end of the CAN wires in the vehicle must be connected to a computer via CAN hardware (Figure 3). By this means, it is now possible to detect the messages on the bus as well as the transmit direction – receive or transmit. In addition to this, it is also possible

Figure 3: CANoe as software-gateway. to add some filters to the CAPL program in order to filter out unnecessary messages and hence to reduce data complexity. This step is repeated for each ECU which provides relevant input data for the reference system. After having identified the relevant CAN messages, it is inevitable to examine the message data bytes in detail to determine the physical signals. This can be achieved by generating physical inputs manually (e.g. open the throttle, drive, break …) and observe the particular CAN messages as well as its bytes in parallel. After that, a correlation between a certain CAN message, its CAN data and a physical input value can be established.

93 Having performed the steps above, it is possible to setup the desired restbus simulation for the reference system. 5.4

Sensors

Besides the CAN data, analog inputs of sensors and analog outputs of actuators are important in order to ensure correct functionality of the reference system. Therefore, each sensor and nearly each actuator has to be analyzed and simulated, too. The sensors can be analyzed using an oscilloscope and a multimeter in order to characterize current consumption, supply voltage and signal transmission. Typically, sensor output signals are analog to: 

Current / voltage, amplitude



Frequency / cycle time



Pulse width / duty cycle

Or they are discrete in the following forms: 

Binary



Multi-staged (different scaled)



Multi-staged (equidistant)  digital

For the simulation, the measured values must be interpreted and emulated. For example, the internal resistance of a sensor can be calculated from the sensor current consumption. Afterwards, the presence of the sensor can be simulated by a (simple) resistor. The simulation of the sensor signal can be realized using a waveform generator, an analog circuit, a microcontroller or a combination of them. 5.5

Diagnostics

Finally, to test the reference system completely detached from the vehicle, it is necessary to know how the diagnosis communication works in order to check the fault memory and to read internal sensor information of the ECU (e.g. for temperature). First, the applied protocols for transport and application layer must be identified. Often, standardized communication protocols for ECU diagnostics are used (e.g. ISO TP, KWP2000 or UDS). In some cases OEMs use proprietary self-developed keyword protocols (e.g. KWP1281). Thus, it is more difficult to build up a diagnosis connection to the reference system because the protocol specification is unknown to the remanufacturer. Hence, a detailed analysis of the CAN or K-Line communication during a diagnosis session is essential. Sophisticated reverse engineering capabilities are necessary to analyze, understand and recreate such a diagnosis communication. The message IDs, used for the communication, must be investigated independently by observing the diagnosis communication with CANoe. If the CAN IDs and protocols are known, the diagnose communication can be reproduced for example in CANoe. After a remanufacturing company has accomplished all mentioned steps for the reference system, it is able to operate this system detached from all analog (sensor signals) or digital (CAN) inputs. Finally, a test bench can be developed for entrance and final testing in series production scale. 6

EXAMPLE: REMANUFACTURING OF AN EHPS

The following six steps describe the reverse engineering process on the basis of an electro-hydraulic power steering (EHPS) pump that is used in a VW Polo. 6.1

Physical Analysis and Electrical Wiring of the EHPS

At the beginning, the EHPS has to be perceived as a black box with inputs and outputs. Because of the mechanical design and the general function of a hydraulic power steering, the output can be

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determined as the flow rate of the fluid. The inputs are composed of an information about the internal combustion engine state (running or not running) and direct or indirect information about the necessary oil flow rate.

CAN bus data is also accessible through the vehicle on-board diagnosis (OBD) connector. This data can contain the IDs of the EHPS inside the car and further ECUs. Unfortunately, the CAN bus was not linked to the OBD connection of the test vehicle (Figure 5). Therefore, the CAN wires of the EHPS were disconnected in order to use CANoe as gateway for CAN messages. As a consequence, it was possible to differentiate between received and transmitted messages. This test verified the previous observations on the CAN IDs sent by the EHPS. 6.3

CAN Bus Communication Investigations

This step can always be split into two parts. The first one is the analysis of the communication in order to filter out and understand the relevant messages for the EHPS sent by other ECUs. The second one is the simulation of the necessary CAN communication, which is called “restbus” in the following. Figure 4: Examination of the CAN Reman test vehicle. To get a first overview about the electrical connections of the device, a reference unit was completely disassembled. Large connector pins were good indicators for the general power supply by reason that the power consumption of the electric motor is supposed to be high. The ground pin of this connector was found by searching for a direct linkage between those pins and the ground plate of the circuit board. The color of the connected cable usually indicates the ground connection (GND). The other cable on the connector is the positive power supply (Vcc). At this point, the connection of the steering angle sensor, which is directly mounted on the steering shaft, was disregarded. The third connector contained three cables. Two of them were twisted in the following cable harness. That was a perfect indication for CAN cables. The CAN-high cable rises from 2.5 V to 3.5 V and the CAN-low cable falls from 2.5 V to 1.5 V during active communication. When operating the vehicle, the last cable was on 12 V level and therefore it was assumed to be the signal for “ignition on”. At this point the electrical analysis of the device was completed. 6.2

Vehicle Network Topology

The most important questions in this step are: “How does the EHPS communicate in the vehicle network? Will the device communicate outside the car?”

First, the start signal, transmitted to the EHPS via CAN bus, must be discovered as described in step 2. Therefore, a recording of the in-car CAN communication was made at a stationary test. After that, the recording was replayed to the test device outside the car and it started its operation. Next, CAN messages were successively filtered out until the motor of the test device stopped. Hence, the last filtered message contained some kind of a start signal. After some tests, this signal was identified to be the RPM signal of the internal combustion engine. In order to eliminate or to find other input parameters, the same test was made with a recording of a real-road test. It was found that the vehicle speed is another input parameter for the EHPS. Second, the required input parameters were simulated with CANoe. Using a third party diagnosis garage tester (Bosch KTS 650), it was discovered that the fault memory of the external EHPS can only be erased when at least the presence of the missing messages of the in-car communication is simulated, too. This simulation of messages with and without data content is called restbus. At this point the EHPS can completely be operated outside the car, but with a real steering angle sensor. 6.4

Simulation of Sensors

In order to operate the EHPS in a completely simulated environment, the angular velocity sensor had to be simulated. Analog to step one, Vcc and GND were identified on the sensor terminal using a multimeter. The third cable transferred the information about the angular velocity of the steering wheel. This signal was analyzed with an oscilloscope. A pulse width modulated signal was detected and simulated with a waveform generator. Furthermore, the sensor presence had to be emulated by a simple resistor matching the power consumption of the original sensor. 6.5

Figure 5: CAN bus topology of the test vehicle. To get answers for these questions, the reference EHPS, outside the car, was connected to a power supply and an ignition signal. In this configuration, the electric motor of the EHPS was not started by the control unit. By connecting the EHPS via CAN hardware to a computer running CANoe (version 7.2), the message IDs sent by the EHPS were displayed in the trace-window. Usually, selected

Diagnostic Functions of the Device

Most devices, including the present EHPS, can be diagnosed over CAN bus with an external diagnosis garage tester. This tester can, as mentioned above, directly communicate with ECUs using a transport and a keyword protocol. The protocols are only partially defined and the communication differs from brand to brand tremendously. Therefore, the most efficient way to understand how e.g. the fault memory can be erased, is to erase the fault memory with one of those testers and to try projecting the sequence onto known standards. In the present case, it were the standards KWP1281 and TP1.6. Even though the understanding of the diagnosis communication was very time-consuming, it was possible to erase and read the fault memory, to read the internal sensor data or duty cycles, to parameterize the device for different car models or even to completely reprogram the software. Finally, all functions were implemented in CANoe using CAPL which can be controlled by a graphical user interface (GUI).

Automotive Life Cycle Engineering - Recycling 6.6

95

Operation Range

At last, the correlations between input and output values were determined in detail. For this reason, the input parameters angular velocity, vehicle speed, RPM and the outputted oil flow rate were recorded simultaneously. In this case the RPM signal only started the EHPS and was disregarded for the measurement. The vehicle speed was found in a particular message on the CAN bus as figured out in step 3. The angular velocity value is part of the sensor data provided by the EHPS in a diagnosis communication session as mentioned in step 5. The resulting oil flow rate was measured by adding an oil flowmeter to the low pressure side of the EHPS in the test vehicle. This flowmeter generates a frequency modulated signal which was converted to a CAN message by a microcontroller and broadcasted to the local in-car CAN network in a separate CAN message. Finally, all necessary input and output values were recorded from the CAN network time simultaneously using CANoe. Figure 6 depicts the flow rate of the steering oil as a result of vehicle speed and angular velocity, measured in a real-road test.

1

same principle can also be applied with some effort to further automotive systems, so that everyone wins, regardless of perspective. 8

9

Steinhilper, R., Rosemann B., Freiberger, S. (2006): “Product and Process Assessment for Remanufacturing of Computer Controlled Automotive Components”, in: Proceedings of the 13th CIRP International Conference on Life Cycle Engineering (LCE2006), pp. 441-446, Leuven, Belgium.

[2]

Steinhilper, R. (2008): “Automotive Service Engineering and Remanufacturing: New Technologies and Opportunities”, in: Proceedings of the 15th CIRP International Conference on Life Cycle Engineering (LCE2008), pp. 2-8, Sidney, Australia.

[3]

Lund, R. T., Hauser, W. (2003): The Remanufacturing Industry: Anatomy of a Giant, Department of Manufacturing Engineering, Boston University, Boston.

[4]

Steinhilper, R. (1999): Remanufacturing: The ultimate form of recycling, Fraunhofer IRB Verlag Press, Stuttgart, Germany.

[5]

Ferrer, G., Whybark, D.C. (2000): “From Garbage to Goods: Successful Remanufacturing Systems and Skills”,in: Business Horizons, Volume 43, Issue 6, pp. 55-64.

[6]

Lund, R. T. (1996): The Remanufacturing Industry: Hidden Giant, Boston University Study, funded by Argonne National Laboratory, Boston, Massachusetts.

[7]

Giuntini R., Gaudette K. (2003): “Remanufacturing: The next great opportunity for boosting US productivity”, in: Business Horizons, Volume 46, Issue 6, pp. 41-48.

[8]

Roddeck, W. (2006): Einführung in die Mechatronik, 3rd Edition, B.G. Teubner Verlag / GWV Fachverlage GmbH, Wiesbaden, Germany.

[9]

Zimmermann, W., Schmidgall, R. (2008): Bussysteme in der Fahrzeugtechnik, 3rd Edition, Vieweg + Teubner / GWV Fachverlage GmbH, Wiesbaden, Germany.

Flow rate

0,8 0,6 0,5 0,4 0,3 1

0,8

0,6

Vehicle speed

0,4

0,2

0 0

0,2

0,4

0,6

0,8

1

Angular velocity

Figure 6: Flow rate as a function of vehicle speed and angular velocity. 7

CONCLUSION

A still increasing number of mechatronic and electronic systems is built into today’s vehicles. In the future, even more of these systems will be introduced to the cars as a result of increasing demand for comfort, safety and reduced fuel consumption. Remanufacturing of failing mechatronic systems offers a great opportunity for all, the OEMs and OEs which can safe resources; the remanufacturing companies as they can make a growing new business with these systems; and the customers that are benefitting from cheaper, but as good as new, spare parts. Progress is not possible without its challenges, but it is achievable. Therefore, remanufacturing companies have to build up new reverse engineering knowhow, have to find methodological innovations and they need to develop new technologies, especially focusing on the tasks testing and diagnostics of automotive systems and their subassemblies. The paper outlines challenges, possible solutions and technological progress for the reverse engineering process of mechatronic automotive systems that are communicating via CAN bus. In addition to this, the reverse engineering process is demonstrated on the example of an EHPS which is used in a VW Polo. Obviously, it was possible to completely understand the steering system of the VW Polo by reverse engineering. Even though the reverse engineering effort was time consuming, it is now possible to run and test the mechatronic system outside the car as well as to adopt the results for remanufacturing the system in series production scale. The

REFERENCES

[1]

0,9 0,7

ACKNOWLEDGEMENT

The research project “CAN REMAN” and the activities described in this paper have been financed by the German Federal Government Department for Education and Research, support code 16INE014. The responsibility for the content of the paper lies with the authors.

[10] Johnson, M. R., Wang, M. H. (1998): “Economical evaluation of disassembly operations for recycling, remanufacturing and reuse”, in: International Journal of Production Research, Volume 36, Issue 12, pp. 3227-3252. [11] Seliger, G., Grudzien, W., Zaidi, H. (1999): “New Methods of Product Data Provision for a simplified Disassembly” in: Proceedings of the 6th International Seminar on Life Cycle Engineering 1999, pp. 250-259, Kingston, Canada. [12] Westkämper, E., Alting, L., Arndt, G. (2000): “Life Cycle Management and Assessment: Approaches and Visions Towards Sustainable Manufacturing”, in: CIRP Annals Manufacturing Technology, Volume 49, Issue 2, pp. 501-526. [13] Chikofsky, E. J., Cross, J. H. II (1990): “Reverse Engineering and Design Recovery: A Taxonomy”, in: IEEE Software, IEEE Computer Society, pp. 13-17. [14]

Haumann, M., Köhler, D. C. F. (2009): “Coping with complexity in remanufacturing“, Rematec News, Volume 9, Issue 3, pp. 32-33.

LCM applied to Auto Shredder Residue (ASR) 1

1

1

1

Luciano Morselli , Alessandro Santini , Fabrizio Passarini , Ivano Vassura , Luca Ciacci 1

1

University of Bologna, Dept. Industrial Chemistry and Materials, Viale Risorgimento 4, I-40136 Bologna, Italy

Abstract Auto Shredder Residue (ASR) is the waste generated from End of Life Vehicles (ELVs) pre-treatment, dismantling, shredding and metals recovery operations. ASR consists of plastics, rubber, textiles, glass, fines, dirt, etc. and many time is contaminated with heavy metals, hydrocarbons and PCBs. ASR is currently landfilled or incinerated but, due to the coming into force of Directive 2000/53/EC, it must be treated aiming at material and energy recovery to reach recycling targets by 2015. This work aims at a sustainable ASR management by using LCA as a decision tool, improved car design and innovative plastic recycling technologies. Keywords: Auto Shredder Residue (ASR); Life Cycle Assessment (LCA); Pyrolysis

1

INTRODUCTION

Automotive industry is one of the most resource-consuming sectors of the industrial production [1]. This holds that its products have both a high content of precious materials, such as steel and other non-ferrous metals, and an embedded energetic content, especially in plastics and rubbers. Consequently, end-of-life-vehicles (ELVs) are a particularly valuable waste stream, amounting to more than 9 million tons per year in Europe, an extent which needs to be properly managed [2]. A correct and efficient management of this kind of waste is thus of great importance in Europe and several other Countries, from environmental, economical and technological points of view. In Europe, at first fluids and other hazardous components (such as batteries) are mandatory removed. Then, according to the market rules, components may be dismantled and further reused and recycled, if it proves to be profitable. After these operations, hulks are baled and transported to a shredding plant where cars are reduced into pieces. The embodied materials are liberated and then sorted for recycling. Metals account for up to 75% of a vehicle mass and, especially ferrous ones, are very easy and profitable to be

sorted, and thus to be recycled. On the contrary, the non-metallic residue, called “car fluff” or “automobile shredder residue” (ASR), is mostly landfilled in Italy, as it happens in many other European Countries [3]. Automobile shredder residue (ASR), the residual fraction of a vehicle obtained after shredder and metal separation steps (named also ‘‘car fluff”), requires a particular attention. ASR is an agglomerate of plastic (19–31%), rubber (20%), textiles and fibre materials (10–42%) and wood (2–5%), which are contaminated with metals (8%), oils (5%), and other substances, some of which may be hazardous (about 10%), e.g., PCB, cadmium and lead [4]. Its composition may vary strongly depending on the shredding input mix (vehicles, white goods and ferrous waste combination) and on the depollution operation carried out. Since some years, even under the pressure of European Community, through the Directive 2000/53/EC which imposes the achievement of specific targets of recycling and recovery in fixed time periods (at least 80% of recycling and 85% of total recovery, by 2006; at least 85% of recycling and 95% of total recovery, by 2015), different possible ways of ASR valorization have been investigated, both aimed to material recovery (e.g., in cement

Figure 1: ASR composition analysis results [6].

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_17, © Springer-Verlag Berlin Heidelberg 2011

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97

concretes), and to energy recovery such as co-combustion in cement works, pyrolysis and/or gasification [4] [5] [6] [7]. The average weight of a vehicle is about 1 ton and 25% of its mass consists of ASR. This corresponds to about 2.5 million tons yearly generated and almost totally landfilled in Europe-25 (with an estimation of 3.5 million tons within 2015), with economical (due to the expenses related to this type of disposal) and environmental problems (associated to the physical–chemical processes of contamination which can occur in this situation). This work aims at applying LCM to automotive sector, in particular to car fluff recycling. Screening LCA results are followed by laboratory-scale experiments of both plastic sorting and thermochemical conversion, which are the two most promising ASR recycling technologies. Expected results are mainly both to understand technical feasibility and “state of the art” of the most sustainable ASR recycling technologies and both to integrate this know-how into new vehicles design. 2 2.1

ASR CHARACTERIZATION ASR Composition analysis

In order to recycle materials contained into ASR it is necessary to know its composition and recyclables share. Thus, a composition analysis was performed on the fluff samples in order to study ASR for future thermo-chemical and separation trials [5]. As it can be easily observed in figure 1, fines (0–20 mm fraction) represent almost a half of the total sample. For the fine fraction, a thorough composition analysis cannot be performed, because of the very small size of the materials included. Anyway, it is possible to identify glass pieces, plastics and metals, blended together with dust and dirt. The remaining fluff mainly consists of polymers, up to 45%, such as polyurethane (foam rubber), plastics and rubbers. Textiles accounts for about 10% on the total and together with polyurethane foam (PUF) are strictly related to car seats and carpeting. 2.2

Chemical-physical analysis

ASR revealed a rough 30% of ashes, LHV equal to 13.8 kJ/kg and heavy metals such as As, Cr, Mn, Ni, and Pb exceeding Italian RDF

law limits [6]. These parameters will be taken into account during LCA study. 3

LCA AS DECISION TOOL

Life Cycle Assessment was applied in this study as a scientific approach aimed to characterize and quantify environmental damages and impacts resulting from different ASR management methods: 1) landfill, 2) nonFe metals recovery, 3) incineration, 4) plastic sorting&recycling plus residue incineration and 5) gasification. Methodology, assumptions and scenarios are fully reported in reference [7]. The results show that industrial processes aimed at matter recovery are not only a necessary solution to fit European recycling and recovery targets for ELVs, but also the options that can obtain greater environmental benefits compared to present practices. Furthermore: (i) ASR landfilling is the worst scenario due to the direct impacts resulting from the disposal of polluted and hazardous waste as such ASR commonly appears, without any treatment aimed at energy or material recovery; thus, it results in a net loss of material. However, the nonferrous metals fraction recovery carried out commonly by most shredders at present allows a reduction of environmental loads, even if strictly for resources consumption. (ii) ASR co-combustion in incinerator would allow a decrease in damages related to plastics landfilling, and further benefits related to energy recovery processes, like waste volume reduction and organic pollutants destruction. In spite of the advantage resulting from the opportunity to operate in co-combustion with MSW (at the rate of 5%, any significant variations in outputs were not observed), ASR incineration should not be considered as a long-term alternative to landfill since this end-of-life strategy do not allow the achievement of 85% recycling target fixed by the European Community. (iii) In terms of environmental impact, better results characterize post-shredder technologies modeled by scenarios 4 and 5, with a little advantage for “feedstock recycling”. It is

Figure 2: LCA results [7].

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interesting to compare results even on the recycling and recovery rates gained by those scenarios: both allow the attainment of European targets, but scenario 4 reaches a higher recycling score than the other, competing with the other strategy in being considered the best solution. Hence, identifying the best way to treat ASR waste may be quite difficult even as a consequence of the frequent variations that occur in ASR composition. Thermochemical plastics conversion and mechanical plastics recycling revealed to be the best environmental solution due mainly to the production of either chemicals (or polymers) and energy which compensates environmental impacts related to disposal with avoided impact coming from the production of goods. Consequently, we decided to study ASR pretreatment and thermochemical conversion via pyrolysis in order to separate and recovery polymers and chemicals from ASR. 4

HYDRO-MECHANICAL ASR PRETREATMENT

At first, ASR has been sieved by means of a 20 mm sieve, obtaining a fine and a coarse sample. Fine, coarse and raw ASR samples have been then floated with a lab-scale equipment with d=1.4 kg/l aiming at polymers separation from the non-organic residue. ASR floating/sinking ratio is 40/60 for coarse fraction and raw samples while it is 25/75 for fines, revealing fines to contain the heaviest materials: metals, heavy rubber, glass and soil. After that, the floating fraction has been floated again with water in order to separate polyolefin, PP and PE (according to figure 3). Density (g/cm³) 0,9

1,0

1,1

1,2

1,3

1,4

1,5

PVC PET PP PE PS PA

Water

Figure 3: density distribution in selected plastics [8]. Polyolefin fraction amounts to a rough 8% of the total ASR mass while plastics with 1 < d< 1.4 kgl/l represent 11% of the ASR raw sample. Further separated poliolefines mechanical recycling trials are still going on in order to understand if this poliolefines mixture can be successfully palletized and re-extruded (as it was in scenario 4, chapter 3). The main benefits of this practice are plastics landfill avoidance and replacement of crude-derived virgin poliolefines with up to 50% recycled materials. 5

PYROLYSIS TRIAL

Thermochemical plastic conversion into hydrocarbons-rich oils is a very promising process in plastics waste management. Aiming at feedstock recycling, different sorted plastic fraction created in chapter 4 have undergone a pyrolysis process. 5.1

Uncondensed gases were collected in a gas sampling bag and analyzed. Once cooled down, reactor was opened and solid char residues taken out and weighted. Liquids were weighted and characterized as well by GC-MS. 5.2

Pyrolysis results

Results show that raw ASR sample has a total conversion (meaning gas + liquid yield) of 22%. Floating samples with d<1.4 kg/l rise total conversion to almost 60%. Moreover, polyolefin alone reach 90% conversion with low liquid viscosity and optimal refining potential. Pyrolysis oil chain length is influenced by waste input. The goal is to achieve light compound for chemical recycling. Polyolefins oil consist of: 16% molecules with more than 14 carbon atoms, olefins and paraffins represents a rough 25% while aromatics only 5%. Unknown compounds are quite high, 35%, but further GC-MS analysis will be carried out in the next future. If compared to mixed plastics oil, the poliolefines one looks much more suitable for further refining due to reduced viscosity and shorter hydrocarbons chain. 6

FEEDBACK TO VEHICLES ECO-DESIGN

DfR and DfD are tools belonging to the set of techniques named Design for Environment (DfE), aimed at the reduction of impacts deriving from EOL treatment and at the maximum product recycling and recovery. These tools can provide better product recyclability, determining the conditions for an increased added value, in a life cycle perspective. Thus, the design of each component must be performed by choosing recyclable or renewable materials, without toxic or hazardous substances, mono-material or composite parts of a high compatibility with recycling processes, low energy consumption materials, according to a life cycle concept. Furthermore, complex products (as automobiles) must be designed in order to simplify as much as possible assembly and disassembly operations, resulting in significant advantages from easiness and quickness standpoints. It can be reminded that actually disassembly is still far to be considered as a reversal of the assembly, thus next years DfD techniques should carefully consider joining parts, structure priority and the correct product dismantling sequence, to reduce disassembly costs, increasing effectiveness, limiting the time employed. Focusing on the recycling and recovery rates claimed by ELVs Directive for year 2015, it appears fundamental to improve recovery processes for non-metallic fraction. Intuitively, the increase in removal efficiency for these materials from ELVs, combined with a required spread of markets for secondary products, will allow the achievement of EC targets and economical profits for the stakeholders involved. Equally important will be the choice of materials employed in vehicle design, since the use of monomaterials and composites with high separation efficiency from vehicle waste, is a nodal point towards a sustainable ELVs management. In a previous work we applied design for dismantling (DfD) guidelines to a car seat [9]. This allows reducing dismantling time to one third whit respect to the baseline model. Applying now also design for recycling (DfR) guidelines, it means that different families of plastics would be substituted by polyolefins, characterized by higher sorting and recycling easiness, when technically feasible.

Pyrolysis reactor

Floated ASR samples were loaded in the pyrolysis reactor under a constant nitrogen flow. The reactor was then heated and, at cracking temperature, volatiles compound created were carried out of the reactor by the N2 flow and condensed in two coolers.

7

CONCLUSIONS

Life-cycle-oriented products development describes the process of systematic consideration and optimization of a product’s technical, economic and ecological characteristics and effects during the

Automotive Life Cycle Engineering - Recycling entire life cycle, within the frame of the product development process. The goal is to meet the requirements of an Extended Product Responsibility (EPR) by using the scope for decisionmaking during the product development to realize a maximum product benefit for costumers and producers during the life cycle and to minimize its economic, ecologic and social cost risks. During 2009 Italian ELVs recycling rate (Rr) was 80.6% [10]. Thus, ASR represents a rough 20% of a vehicle mass since no further treatments are currently carried out on ASR in Italy. So far, in order to reach 85% Recycling rate in 2015, it is necessary to recycle at least 25% of ASR mass. Plastics floatation and pyrolysis may lead to a rough 30% yield that, by summing up residual 5-6% metals in the heavy sinking residue, may lead to a total 35% ASR recycling, corresponding to 88% final Rr. ASR floatation and pyrolysis are feasible but further research are necessary for improving both separation efficiency and refining pyrolysis oil. 8

REFERENCES

[1]

Jody, B.J., Daniels, E.J., (2006): End of-Life Vehicle Recycling: The State of the Art of Resource Recovery from Shredder Residue, Energy Systems Division, Argonne National Laboratory.

[2]

EC, (2000): Directive 2000/53/EC of the European parliament and of the council of 18 September 2000 on end-of life vehicles––commission statements. Off. J. Eur. Comm. L269, 0034-0043 (Brussels).

[3]

Santini A., Morselli L., Passarini F., Vassura I., Di Carlo S., Bonino F., (2010a): End-of-Life Vehicles management. Italian material and energy recovery efficiency, Waste Manage, in press.

[4]

Srogi, K., (2008): An overview of current processes for the thermochemical treatment of automobile shredder residue. Clean Technol. Environ. Policy 10, 235–244.

[5]

Boughton, B., Horvath, A., (2006): Environmental assessment of shredder residue management. Resour. Conserv. Recycl. 47, 1–25.

[6]

Morselli L, Santini A, Passarini F, Vassura I (2010): Automotive shredder residue (ASR) characterization for a valuable management. Waste Management, in press.

[7]

Ciacci L., Morselli L., Passarini F., Santini A., Vassura I. (2010): A comparison among different Automotive Shredder Residue treatment processes, Int J LCA.

[8]

La Mantia, F. (2002): Handbook of plastics recycling, Rapra Technology, Shrewsbury UK.

[9]

Santini A., Morselli L., Passarini F., Vassura I., Herrmann, C., Luger, T. (2010): Assessment of Ecodesign potential in reaching new recycling targets, Resources, Conservation and Recycling, 54, 1128-1134.

[10]

GHK/Bios (2006): A study to examine the benefits of the End of Life Vehicles Directive and the cost and benefits of a revision of the 2015 targets for recycling, re-use and recovery under the ELV Directive. Final Report to DG Environment, Birmingham.

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Eco-Innovation by Integrating Biomimetic with TRIZ Ideality and Evolution Rules 1

Jahau Lewis Chen , Yung-Chiuan Yang 1

1

Department of Mechanical Engineering, National Cheng Kung University, Tainan, Taiwan

Abstract Scientists believe that products can get innovated through inspiration by nature with the eco-friendly concepts. The major objective is that the designer can really get ideas from biological phenomena and apply them to engineering problems or products. This paper presents an eco-innovative method by integrating biological cases with the TRIZ ideality method, the trends of evolution and the FAST (Function Analysis System Technique) method. This method can systemically help designers to solve problems or execute product innovation by mimicking nature’s wisdom in a smart way. An example is illustrated to demonstrate the capability of the proposed method. Keywords: Eco-innovation; Biomimetics; TRIZ

1

INTRODUCTION

The development of technology plays a crucial role in modern economic growth but it is also the key factor of environmental crisis. It is usually emphasizing the novelty and economic usefulness of an innovated product but neglects its environmental impacts. Currently, many eco-design methods have been developed to support the designer in reducing the environmental impact of the product throughout its life cycle. However, those methods are focused on the redesign or optimization of existing products. Therefore, there is a need to develop a product eco-innovative design method for this situation. This paper describes a new method of applying biomimetics into product eco-innovation. The Biomimicry Institute [1] proposed “The Design Spiral” concept to find solutions for the design from nature. Hacco and Shu [2] used key words to find corresponding biologic features to generate bionic ideas and applied them to the design at remanufacture tasks. Vincent and his co-authors [3-7] collected a biological effects database and integrated it with the TRIZ method. Mann [8] tried to develop the biological TRIZ contradiction matrix. Chiu and Shu [911] developed a biomimetic design method through natural language analysis to bridge engineering and biology terminology. Chen and Huang [12] proposed a biomimetic design process for eco-product design by adding the biomimetic design cases into the “Innovative Principles for Single Engineering Parameter” TRIZ approach as a “Biomimetic Principle” to offer biomimetic solutions for designers. Chen and Jian [13] presented an eco-innovation process for eco-product design by linking engineering terminology with biological terminology and using the method of keyword searching to find suitable bionic cases for eco-innovation problems. A table of keywords compiled from inventive principles and related bionic cases are proposed to offer the designer a quick searching tool. This paper presents an eco-innovative method by integrating biological cases with the TRIZ ideality method, the trends of evolution and the FAST (Function Analysis System Technique) method. An example is illustrated to demonstrate its capability.

2

BIOMIMETICS

Biomimetics [14-15] is a subject to mimic the organic characteristics and to adopt them in the product design. From ancient times to the present, a lot of successful bionic designs have been made. These design concepts from nature have recently become more and more important. Furthermore, more and more designers try to find the design solution for their problems in nature. 3

TRIZ IDEALITY AND EVOLUTION RULES

The TRIZ method [16-18] is a tool for designers and engineers to handle conflicts. The method was developed in the former Soviet Union by Altshuller, who has analyzed over 400,000 patents. The most fascinating and amazing part of the TRIZ method is the contradiction matrix constructed through investigating and classifying the patents. The contradiction matrix is composed of 39 engineering parameters and 40 inventive principles. When people face design contradictions, they can search for the appropriate parameters, and then locate 1-4 suitable design principles for resolving the particular problem. 3.1

Ideality

The ideal system is a non-existent system with all of its functions still being executed. In other words, function is ideally carried out by already existing resources. Nevertheless, actual systems approach the ideal by increasing their beneficial functions and eliminating harmful factors. In the field of eco-design, the harmful factors are the materials, components or processes during the life cycle of the products that produce severe environmental impacts. The ideal final result (IFR) of eco-products is to perform desired functions without any environmental impacts. Therefore, looking at eco-innovative design problems of products from an ideal final result perspective is usually a very good first step towards success. The green evolution rules can provide assistance in formulating the ideal final result. Six methods for increasing the ideality of a system [18] are as follows: 1. Exclude auxiliary functions. 2. Exclude elements.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_18, © Springer-Verlag Berlin Heidelberg 2011

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3. Identify self-service.

4

INTEGRATING BIOMIMETICS EVOLUTION RULES

4. Replace elements, parts or total systems. 6. Utilize resources. Evolution rules

Identify the current position of today’s design within an evolutionary pattern and the designer can predict future designs along this pattern. It is obvious that there exist some patterns of evolution rules for eco-products. These green evolution rules provide the designer a useful tool for filtering and selecting solutions of ecoinnovative design problems. These technical evolution trends determine the direction and character of the technical revolution in the next generation. Hence, it can help the designer forecast the future of the technique and concentrate research and development in the most promising directions. Some patterns of the green evolution rules for different green products have been observed and identified [19]. Mann [20] collected 31 different types of trends of evolution. In this paper, 25 of them have been chosen as the useful evolution rules to link with biological cases, as shown in the left side of Table 1. Trends of Evolution

TRIZ Inventive Principles

Smart Materials

31, 40

Space Segmentation

2, 31

Surface Segmentation

1, 31

Object Segmentation

1, 2

Evolution Macro to Nano Scale

1

Webs and Fibers

31

Decreasing Density

8, 35

Increasing Asymmetry

4, 5

Boundary Breakdown

5

Geometric Evolution (Linear)

14, 17

4.1

Trends of Evolution and Biomimetics

Evolution Line: Point 1D Line 2D Plane 3D Surface Inventive Principles 14, 17

17

Trend of Evolution

15, 28

Action Co-ordination

19, 20

Geometric Evolution (Linear)

to

19, 20

External)

Non-

Mono-Bi-Poly Mono-Bi-Poly Difference)

15

Point 1D Line 2D Plane

5, 6 (Increasing

Reduced Damping

Vocabulary Spherical, ball, line, horizontal, plane, arch

Dynamization

(Matching Linearities

AND

It is difficult for designer to find suitable bionic design cases for his eco-innovation problem. However, key vocabulary can help searching related cases which are associated with each vocabulary [21]. Therefore, this paper used an eco-innovative process for ecoproduct design by linking engineering terminology with biological terminology and using methods of searching keywords to find suitable bionic cases for eco-innovative problems [13]. A table of inventive principles, corresponding keywords and related bionic cases is used in this paper to offer the designer a quick searching tool. The first step is to analyze the TRIZ 40 inventive principles and its associated descriptions to find a “verb” with similar meaning as the key vocabulary of this inventive principle. Then, one can use the “WordNet3.0” web [22] to find synonyms for the key vocabulary. The “Biology-Online” web [23] can be used as a tool to check the “biologically significance” of each vocabulary by searching the number of data in this web. Finally, related biological cases can be obtained by searching key vocabulary in biology books, such as Life [24], Biology Demystified [25], and Biology [26]. Table 1 shows the associated TRIZ inventive principles related to 25 trends of evolution. Table 2 shows the key and corresponding vocabulary and associated biological cases related to the TRIZ inventive principles 14 and 17 which are associated with the “Geometric Evolution (Linear)” trend of the evolution rule. A detailed list of all 25 trends of the evolution rule related to the biological cases can be found in Reference 27.

Geometric Evolution (Volumetric)

Rhythm Co-ordination

IDEALITY

This section proposes the techniques to integrate the ideality, the trends of evolution, the inventive principles and the biological cases to provide the designer with some useful tables for the use of the biomimetics concept for eco-innovation.

5. Change the principle of operation. 3.2

WITH

5, 6, 7 11, 29

Biological Cases In blood's red blood cell, white blood cell, blood platelet. …. …. As blood flows from the heart, it will pass a big bend, the aortic arch, and is redistributed when going out. The 180 degrees turn in the artery works analog to a voltage transformation substation which raises the voltage before delivering the current. …. The DNA double helix structure is composed of a 3D structure. ….

Increasing Use of Senses

23

Increasing Use of Color

32

Increasing Transparency

32

Degrees of Freedom

15, 17

Trimming

2, 6, 22

4.2

Controllability

22, 23, 24

Reducing Number of Energy Conversions (Trending to Zero)

35

For helping the designer select the suitable trend of evolution, a method of thinking from ideality is proposed in this paper. The relationship between the six methods for increasing ideality of a system and trends of evolution is investigated and identified. The trends of evolution related to one of the six methods for increasing ideality of a system (5. Change the principle of operation) are identified as shown in Table 3. Detail lists of all 25 trends of

Table 1: Inventive principles related to trends of evolution.

3D Surface

Table 2: Partial list of biological cases related to “Geometric Evolution (Linear)” trend of evolution rule. Ideality and Trends of Evolution

Life Cycle Design - Methods and Tools

103

evolution rule related to six methods for increasing ideality of a system can be found in Reference 27. 5. Change the principle of operation

Reasons Evolution

for

Trends Evolution

of

Suggestion of Evolution Stage

….

….

….

Improve drainage

Surface Segmentatio n

Smooth Surface to Surface with Rib Protrusions

Combining the two pieces to improve the position and integrity

Geometric Evolution (Linear)

Point to Plane

Increase the aerodynamic control

Surface Segmentatio n

Surface with Rib Protrusions to 3D Roughened Surface

….

….

….

5

FAST-Function Analysis System Technique

The FAST (function analysis system technique) diagram [28] is a systematic function analysis method as shown in Figure 1. Each rectangular block in Figure 1 represents a function. The objective function (higher order function) is placed at the left hand side of the FAST diagram. Through answering the question “What is the basic function to achieve the objective function (How)?” one can identify the basic function and place it at the right hand side of the objective function. Then the same technique is used for the secondary

THE PROCEDURES OF ECO-INNOVATION

Figure 2 illustrates the design processes of including biomimetic concepts with the TRIZ method through key vocabulary in ecoinnovation. The TRIZ tools used in this process include the ideality and the evolution rules. The procedures can be explained by five steps as follows: 5.1

Table 3: Partial list of trends of evolution related to the six methods for increasing ideality of a system (5. Change the principle of operation). 4.3

function till it reaches the lowest order function (at the right hand side of the FAST diagram). One can check the FAST diagram by answering the question “Why does it need to achieve a higher order function?” from right to left in the FAST diagram. This method can help the designer to identify the function.

Step 1: ideal final result (IFR) problem definition

First, the designer can identify the ideal final result (IFR) of each product design to assess a function which requires improvement. 5.2. Step 2: establish FAST diagram Next, if the designer cannot find a function in step 1, then one can identify the “significant” function by establishing the FAST diagram. 5.3. Step 3: find suitable evolution line Moreover, if the evolution line is not easy to identify, then the designer can use the ideality concept through the trends of evolution related to six methods for increasing ideality of a system table, such as Table 3, to find a suitable evolution line. After finding the suitable evolution rule, one can analyze the problem’s evolution block to identify the right block. All evolution blocks in the following right hand side of this evolution line can be used for innovation. 5.4. Step 4: search biological cases After obtaining the suitable evolution line, the designer can search related biological cases through the biological cases related to the evolution line table, such as Table 2.

Figure 1: An example of FAST diagram [29].

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5.5. Step 5: eco-innovation Finally, after obtaining the suitable biological case, the designer can use it to perform eco-innovation. The designer can use any

qualitative or quantitative environmental evaluation tool to check the environmental improvement of new concepts.

Figure 2: The design processes including biomimetic concepts with TRIZ method.

Life Cycle Design - Methods and Tools 6 6.1

105

EXAMPLE Problem description

The design example tries to create an innovative, environmentally friendly electrical fan. The electrical fan consumes less energy than an air-conditioner. Noise, efficiency and safety are the problems of current electrical fans of which the designer has the opportunity to improve. 6.2

Ideality and function analysis

The ideal role model of an electrical fan is the natural wind. The natural wind has the same effect as the electrical fan, just without any energy consumption. However, the natural wind is nonpredictable and cannot be used at any time. Therefore, one can take one step back to the intermediate solution of ideality, “an electrical fan can have wind without fan blades”. Next, the FAST diagram of the electrical fan is analyzed as shown in Figure 3. The objective function (higher order function) and the lowest order function are “produce wind” and “transport current”, respectively, as illustrated in the output and input of Figure 3. In Figure 3, the rotation of fan will be “cut air flow” and produce the harmful effect of “distribution of wind” and “noise”. One can select “cut air flow” as the key function for design improvement. 6.3

designer can use the trend of evolution rule (Geometric Evolution (Linear)) related to the biological cases table to search related biological case for this design problem, such as shown in Table 2. As illustrated by Table 2, the suitable biological case is “As blood flows from the heart, it will pass a big bend, the aortic arch, and is redistributed when going out. The 180 degrees turn in the artery works analog to a voltage transformation substation which raises the voltage before delivering the current”. 6.4

Eco-innovation by biomimetics design

The concept of “pressure difference” in the biological case of blood transportation of the heart provides the innovative idea that air can flow from high pressure to low pressure to generate wind from “pressure difference”. The eco-innovative idea is to put the motor and fan blades into the base of the electrical fan so that the fan blades can rotate inside the base to reduce “cut air flow”. Furthermore, a design in the upper part of the electrical fan to change the wind direction and the surrounding pressure difference of air can achieve our design goal. The electrical fan generates wind without visible fan blades [30], as shown in Figure 4, and is reducing the area of ring outlet so that the inner air velocity is higher than the outer air velocity. Therefore, the air behind the fan will automatically be sucked in and steady wind blowing at high speed.

Find suitable evolution line and biological cases

After selecting the key function “cut air flow”, the designer can use the ideality concept through the trends of evolution related to six methods for increasing ideality of a system table, such as Table 3, to find the suitable evolution line. In this example, number 5 of six methods for increasing ideality of a system, “Change the principle of operation”, is selected. As shown in Table 3, reasons for evolution, “Combining the two pieces to improve the position and integrity” is chosen to find the suitable evolution line, “Geometric Evolution (Linear)”. The suggestion of evolution stage is “Point to Plane”.

Evolution Line: Point 1D Line 2D Plane 3D Surface

Figure 4: The electrical fan generates wind without fan blades [30].

From the above evolution line, one can identify the electrical fan problem’s evolution block is the “2D Plane” block. Next, the

 

Figure 3: FAST diagram of the electrical fan design problem.

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This new design can be evaluated by any qualitative or quantitative environmental evaluation tools, such as Matrix LCA or full LCA, to check whether it is environmentally friendly and has lower environmental impacts. 7

[1]

Chen, J. L., Huang, L.-C. (2007): Eco-Innovation of Products by Biomimetic Concepts, In: proceedings of the Fifth International Symposium on Environmentally Conscious Design and Inverse Manufacturing, Ecodesign07, Tokyo, Japan, December 10-12.

[13]

Chen, J. L., Jian, Y.-H. (2009): Eco-Innovation by Biological Terminology, Biomimetic Concepts and TRIZ Techniques, In: Proceedings of the Sixth International Symposium on Environmentally Conscious Design and Inverse Manufacturing, Ecodesign09, Sapporo, Japan, December 79.

[14]

Benyus, J. M. (1997): Biomimicry: Innovation Inspired by Nature, William Morrow & Co., New York

[15]

Bar-Cohen, Y. (2006): Biomimetics-Using Nature to Inspire Human Innovation, In: Bioinspiration & Biomimetics, Vol. 1, pp. 1-12, Institute of Physics Publishing

[16]

Altshuller, G. (1998): 40 Principles–TRIZ Key to Technical Innovation, Worcester, MA: Technical Innovation Center, Inc.,8.

[17]

Savransky, S. D. (2000): Engineering of Creativity– Introduction to TRIZ Methodology of Inventive Problem Solving, CRC Press LLC.

[18]

Terninko, J., Zusman, A., Zlotin, B, (1998): Systematic Innovation-An Introduction to TRIZ, St. Lucie Press.

[19]

Chen, J.L. (2002): Green Evolution Rules and Ideality Laws for Green Innovative Design of Products, In: Proceedings of Going Green - Care Innovation 2002, 4th International Symposium, Vienna, November 25-28.

ACKNOWLEDGMENTS

This study is supported by The National Science Council of Taiwan, Republic of China, grant number: NSC-97-2221-E-006-055. 9

[12]

CONCLUSIONS

This paper presented an eco-innovative product improvement method by integrating the biological cases with the TRIZ ideality method, the trends of evolution and the FAST (Function Analysis System Technique) method. This method can systemically help designers solve problems or execute product innovation by mimicking nature’s wisdom in a smart way. An example was illustrated to demonstrate the capability of the proposed method. It is required that further research work is carried out on the development of a suitable environmental evaluation tool for the identification of eco-improvements of new design concepts. 8

Retrival, In: Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 21, pp. 45-59.

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Hacco E., Shu, L. H. (2002): Biomimetic Concept Generation Applied to Design for remanufacture, In: Proceedings of DETC’02, ASME 2002 Design Engineering Technical Conferences, Montreal, Canada, September 29- October 2.

[3]

Vincent, J. F. V. , Bogatyreva, O. A., Pahl, A.-K., Bogatyrev N. R., Bowyer, A. (2006): Putting Biology into TRIZ: A Database of Biological Effects, In: Creativity and Innovation Management, Vol. 14, Issue 1, March, pp. 66.

[4]

Bogatyreva, O., Phal, A.-K., Bowter, A ., Vincent, J. (2003): Data Gathering for Putting Biology in TRIZ, in: The 5th Annual Conference of the Altshuller Institute for TRIZ Studies.

[5]

Bogatyrev N., Bogatyreva, O. (2003): TRIZ and Biology: Rules and Restrictions, In: Proceedings of International TRIZ Conference, Philadelphia, USA, 16-18 March, p. 19/1 -19/4.

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Chiu, I., Shu, L. H. (2007): Usingl Language as related Stimuli for Concept Generation, In: Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 21, pp. 103-121.

[22] WordNet 3.0, (2009): access June 17.

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(2001):

http://wordnet.princeton.edu,

[23]

Biology Online, online.org .

Accessed

at

www.biology-

Purves, W.K., Sadava, D., Orians, G.H., Heller, H.C. (2003): Life-The Science of Biology, Sinauer Associates.

[6]

Vincent, J. F. V., Mann, D. L. ( 2002): Systematic Technology Transfer from Biology to Engineering, In: The Royal Society.

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Vincent, J. F. V., Bogatyreva, O., Bogatyrev, N., Bowyer, A. , Pahl, A.-K. (2006): Biomimetics – its practice and theory, In: Journal of the Royal Society Interface, 3, pp. 471-482.

[25]

Dale, L. (2003): Biology Demystified, Mc Graw Hill.

[26]

Peter, R., George, J. (2002): Biology, Mc Graw Hill.

[8]

Mann, D. L. (2006): National World Contradiction Matrix: How Biological Systems Resolve Trade-offs and Compromised, In: Proceedings of the ETRIA TRIZ Future Conference 2006, Vil. 1, kortrijk, Belgium, 9-11 November,, pp. 99-108.

[27]

Yang, Y.-C. (2010): Eco-Innovative Design Method by Integrating Bionics with TRIZ Ideality and Evolution Rules, Master Thesis, Department of Mechanical Engineering, National Cheng Kung University, June (in Chinese).

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Chiu, I., Shu, L. H. (2004): Natural Language Analysis for Biomimetic Design, In: proceedings of the ASME 2004 Design Engineering Technical Conferences and Computer and Information in Engineering Conference, Sep. 28-Oct. 2.

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Otto, K., Wood, K. (2001): Product Design-Techniques in Reverse Engineering and New Product Development, London, Prentice-Hall.

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Chiu, I., Shu, L. H. (2005): Bridging Cross-Domain Terminology for Biomimetic Design, In: Proceedings of the ASME 2005 Design Engineering Technical Conferences and Computer and Information in Engineering Conference, Sep. 24-28.

Wixson, J. R. (1999): Function Analysis and Decomposition Using Function Analysis Systems Technique, In: Proceedings of the International Council on Systems Engineering Annual Conference, INCOSE, June 6-10.

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Dyson Air Multiplier, (2009): http://www.dyson.com/fans/

[11]

Chiu, I., Shu, L. H. (2007): Biomimetic Design through Natural Language Analysis to Facilitate Cross-Domain Information

Reasoning New Eco-Products by Integrating TRIZ with CBR and Simple LCA Methods 1

Cheng Jung Yang , Jahau Lewis Chen 1

1

Department of Mechanical Engineering, Nation Cheng Kung University, Tainan, Taiwan

Abstract The concept of eco-design in product design has been developed for several years. In this study, we proposed a new reasoning model to obtain innovative ideas more easily for designing eco products, which was followed by evaluating whether the proposed design here was more effective than currently available ones. The innovative solution to solving design problems was based on TRIZ evolution patterns. The index system of case-based reasoning then connected the innovative idea to cases located in a database, realizing the promising idea. Finally, simple life cycle assessment was utilized to determine the feasibility of this solution in comparison with the current ones. Meanwhile, an eco-innovative example was also applied to demonstrate the utility of the proposed model. Keywords: TRIZ Evolution Patterns; CBR; Simple LCA

1

INTRODUCTION

Many things change in our life because of a certain demand. For instance, biological organisms adapt them to their surrounding environments. This phenomenon is also similar to the product development. Much effort is being exerted in the quest for products with high performances, multi-functions, low cost and fashion trends. Therefore, engineers should concern about the successful experiences to increase their design feelings. Additionally, the introduction of the systematic methods into the evolution trend can speed up a new design. TRIZ evolution patterns [1-3] are an effective means of forecasting future trends and developments. Cavallucci [4] introduced these patterns to propose an operative application framework in order to analyze their impact in the design process. Petrov [5] reviewed many papers about the laws of technical system evolution and presented a system of laws to makes it possible to perform forecasts of technology evolution more thoroughly. Zlotin and Zusman [6] used knowledge of the evolution patterns to correlate with analytical methods. In the case of eco-design, Low et al. [7] used TRIZ evolution patterns to explain the relationship between product function and service. Mann and Jones [8] showed a successful case that improved the product service, use-service and resulting service concepts in the energy system. Chen [9] proposed an innovative eco design method by introducing green evolution rules and ideality laws to invent “novelty, usefulness, and no environmental burden” new products. Justel et al. [10] utilized TRIZ evolution rules to reason the evolution of the joint parameters for disassembly. Chang [11] integrated the idea of biological evolution with TRIZ evolution rules and inventive principles to develop future eco-products. Although TRIZ evolution patterns can facilitate the production of innovative ideas, forming such ideas still relies strongly on the user experiences. A method called case-based reasoning, CBR, which is beneficial for utilizing prior experiences to solve new problems, was introduced to this approach. CBR originated from the work of Schank and Abelson [12] on dynamic memory and the central role

that they play in recalling earlier situations and situation patterns during problem solving and learning. Some papers have integrated TRIZ with CBR to solve engineering problems in recent years. Estevez et al. [13] increased the level of abstraction of the CBR to extend CBR from routine to inventive design. They used TRIZ problem solving reasoning process to apply the pairing of generic resolution rules. Lee [14] utilized TRIZ method as an assist to increase the performance of CBR in the product design. They made a software about wall lighting design to assist designers in retrieving useful cases efficiently and to give designers systematically creative ideas for a new design. Gao et al. [15] developed a prototype of computer-aided design system to interpret the usefulness and meaning of CBR for innovative design automation based on TRIZ tools (Contradiction matrix, separation principles and the 76 standard solutions) and Generalized Location Pattern. Robles et al. [16] presented an approach based on the synergy between CBR and TRIZ to accelerate inventive preliminary design for chemical engineering. Their presented model offers a way (by CBR) to transfer the solution from an identified analogous problem to a new problem, and to combine the TRIZ ability to get inventive problem solving strategies applicable across domains. Chen et al. [17] proposed a method that first used CBR to obtain a prototype, and then redesigned part of it by using TRIZ to achieve eco-innovation. Yang and Chen [18] proposed a new innovative design method that integrated examples of effective energy-efficient practices in the industry, CBR method, and TRIZ tools to achieve the eco-innovation objective. The impact of products on the environment can be calculated by softwares such as SimaPro and GaBi. Preliminary work involved collecting information with respect to factors such as material properties, weights, and manufacturing processes. However, the necessary quantitative data is hard to get in the stage of concept design. In order to overcome this problem, some kinds of simple life cycle assessment methods have been proposed, such as screening life cycle assessment [19], streamlined life cycle assessment [20], screening and streamlined life cycle assessment [21], iteration screening life cycle assessment [22] and streamlined life cycle

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_19, © Springer-Verlag Berlin Heidelberg 2011

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assessment matrix approaches [21,22]. In this study, we used one qualitative matrix LCA method to evaluate the product environment impacts in the concept design. The paper was organized as following: Chapter 2 illustrated the concept of TRIZ evolution patterns. Chapter 3 presented the framework of CBR including the definition of case retrieve, reuse, revise and retain. Chapter 4 explained the simple LCA methods used in this approach. Chapter 5 proposed a flowchart that combined TRIZ, CBR and simple LCA method for the eco-product design. Chapter 6 showed an eco-innovative example to demonstrate the utility of the proposed model. Finally, some conclusions and future research directions were provided in Chapter 7. 2

PATTERNS OF EVOLUTION – TRIZ TOOL

A technology may evolve into a mature level gradually. TRIZ experts observed the evolution of technology from a wild of patents and formulated several patterns of evolution. These patterns could aid designers to predict the future evolution of products and to solve the inventive problems. This approach used five patterns of evolution for solving eco-innovation design problems [23]. They are shown in Table 1 to Table 5. Patterns of Evolution

Evolution toward increase dynamism and controllability

Exposition

Increasing system dynamism allows functions to be performed with greater flexibility or variety. Increasing system dynamism requires increasing controllability.

Table 1: The exposition of evolution pattern -1. Patterns of Evolution

Exposition

Increase complexity followed by simplification Technological systems tends to develop first toward increased complexity (i.e., increased quality and quantity of system functions) and then toward simplification (where the same or better performance is provided by a less complex system).

Table 2: The exposition of evolution pattern -2. Patterns of Evolution

Evolution with matching and mismatching elements

Exposition

As a system evolves, system elements are matched or mismatched to improve performance or to compensate for undesired effects.

Table 3: The exposition of evolution pattern -3. Patterns of Evolution

Evolution toward micro-levels and increased use of field

Exposition

Technological systems tend to transition from macro-system to micro-system. During this transition, different types of energy fields are used to achieve better performance or control.

Table 4: The exposition of evolution pattern -4.

Patterns of Evolution

Evolution toward involvement

decreased

human

Exposition

Systems develop to perform tedious functions that free people to do more intellectual work. It means to substitute the human but maintain the action on control level or decision-making level of human’s method.

Table 5: The exposition of evolution pattern -5. 3

CASE-BASED REASONING

CBR is a problem solving method. The method utilizes prior cases stored in the database to solve new problems. The main process of CBR to solve problems is illustrated as following: a. Retrieval: Users get the most similar prior case from the database after selecting some certain parameters. The retrieved case is evaluated by calculating the similarity function. The information of the most similar case is the basis to solve the new problem. b. Reuse: In many cases, the retrieved case can likely match the problem to a certain extent, implying that the related solution is a sub-optimal one. There is a gap between them and lead into some revise ways for help. c. Revise: Revision adjusts the parameters of the retrieved solution to conform to those of the current problem. The techniques may generate certain rules, heuristics or domain knowledge. d. Retain: When the new problem is resolved, the related information would be saved as a new case in the database to increase the ability of solving new problems. 4

SIMPLE LCA

Under ISO 14040 [24] and 14044 [25] standards, a full LCA evaluation includes four stages called (1) Goal and scope, (2) Life cycle inventory, (3) Life cycle impact assessment and (4) Interpretation. Using a full LCA method to evaluate a product can clearly know the information of raw materials regarding production, manufacturing, distribution, use and disposal, while including all intervening transportation steps. Although results using the conventional LCA are accurate and acceptable, the conceptual design stage has incomplete information, thus making this method infeasible for use. Therefore, with the help of a method called the AT&T abridged life-cycle assessment [22], this study evaluated how the environment impacts a product at the concept design stage, as described in the following. This method used a 5x5 matrix to evaluate the environment impacts of a product (Table 6). The vertical parameters in the matrix comprise the five life cycle stages, i.e., pre-manufacture, product manufacture, product delivery, product use, and disposal. The horizontal parameters in the matrix address the environmental concerns, i.e., materials chosen, energy used, solid residues, liquid residues, and gaseous residues. Each cell in the matrix is represented by the lowest impact (value 4) to the highest impact (value 0). Refer to the evaluation standard in the textbook [21], designers can assess the value of each cell themselves.

Life Cycle Design - Methods and Tools

109 5.1

Environmental Concerns Life stages Premanufacture Product manufacture Product delivery Product use

Materials

Energy

Solid

Liquid

Gaseous

chosen

use

residues

residues

residues

1,1

1,2

1,3

1,4

1,5

2,1

2,2

2,3

2,4

2,5

3,1

3,2

3,3

3,4

3,5

4,1

4,2

4,3

4,4

4,5

5,1

5,2

5,3

5,4

5,5

Refurbishment, Recycling, Disposal

Table 6: 5x5 assessment matrix proposed by AT&T [21]. 5

THE MODEL FOR REASONING NEW ECO-PRODUCTS BY INTEGRATING TRIZ WITH CBR AND SIMPLE LCA METHODS

In the beginning, this approach introduced TRIZ patterns of evolution to help engineers to select the most promising directions for an innovative design. Next, CBR framework was used to quickly realize a novel concept. This study adopted an index system to link TRIZ evolution patterns with a database to enable engineers to know clearly and comprehensively how similar design problems were solved. Finally, matrix LCA was introduced to check if the new design is better than the current one. The following procedure is displayed in the design flowchart (see Figure 1) and the main stages are illustrated in the following sections.

Make the eco-design objective and a redesign part of the product

Get innovation idea from patterns of evolutions (TRIZ)

Eco-design is responsible for reducing the environmental impact of a product during its whole life cycle. Most of the available approaches to achieving this goal share the three product features─ materials, energy and toxicity. Designers should thus focus initially on improving a product feature. Product information is then analyzed, followed by determining how to redesign a certain portion of the product. This approach emphasizes how to improve two of the product features in order to achieve eco-design, i.e., materials and energy. Additionally, the prior cases stored in the database of CBR framework are also from these two fields. The case information will be described in next section. 5.2

New design

Evaluate by the simple LCA method

No

Satisfy? Yes New Eco Product

Figure 1: The design flowchart of making new eco-products.

Connect CBR framework to quickly realize the idea

The basic description of evolution patterns has been already illustrated in Chapter 2. First of all, the designers select the desired evolution pattern after they analyze information related to what they want to redesign. After selecting a certain TRIZ evolution pattern, the CBR framework will be introduced to accelerate the implementation process. The major works for establishing CBR framework build up a database, in turn setting up an index system and making the revised rules for modifying retrieve cases. For the first task, this approach collects 75 products which vary with the fields of technology innovation in material and energy. These cases are also used as the foundation for implementing the TRIZ evolution patterns. The second task, setting up an index system, is the key role for guiding the design problem to search useful prior cases for help. This study classifies five characters to describe a case and to make a typical formulation for calculating case similarity. The characters are TRIZ evolution patterns (index 1) featuring the function about the design problem (index 2 to index 4) and the improvement function of the product for new design (index 5). The detail description for each index is shown in Table7. The similarity formula in the CBR method generally refers to the similarity between a current problem and a previous one in problem space. This paper makes a formulation (1) to calculate the case similarity. n

 w  sim ( D , C ) i 1

Connect CBR framework to quickly realize the idea

Make the eco-design objective and a redesign part of the product

i

i

i

i

(1)

Where n is the total numbers of character in an index system and wi is the weighting value of character i. Each weighting value is from 0 to 1 and the sum of weighting values is equal to 1. Di means the selection of Arabic numeral for a new case and Ci is the Arabic numeral for the prior case; simi (Di, Ci) means the individual similarity between Di and Ci; simi (Di, Ci) refers to on of two values (0 or 1). If Di is equal Ci , then simi (Di, Ci) is 1, else simi (Di, Ci) is 0. The total similarity is to sum the multiplication value of each weighting value with its individual similarity. If the retrieve case could not help designers to practice the innovative idea, this study supports three rules for revising. The first one is to refer to the cases that have second and third high similarity under the same TRIZ evolution pattern. The second one will be utilized if the first one is not helpful. The second one is considering the highest similarity of case resulting from different TRIZ evolution patterns firstly. The cases having the second and third high similarity under different TRIZ evolution pattern would use later if deemed necessary. The last one is to use the basic definition of TRIZ evolution pattern to derive a possible solution when both of the first and second rules are not useful.

110

Life Cycle Design - Methods and Tools

Index

Illustration

Selection 1.Evolution toward increase dynamism and controllability

1

The TRIZ evolution patterns for changing a product function

2.Increase complexity followed by simplification 3.Evolution with matching and mismatching elements 4.Evolution toward micro-levels and increased use of field 5.Evolution toward decreased human involvement

2

3

The element is determine by the source of energy that is applied to the part of index 4

The field that interacts or acts upon on the substances (index 2 and 4)

1. Material 2. Tool 3. Part 5. Environment

Index 1

(4) Evolution toward micro-levels and increased use of field

1. Mechanical

Index 2

(5) Environment (Thermal)

2. Thermal

Index 3

(8) Thermal-Electrical

3. Chemical

Index 4

(5) Environment (Electricity)

4. Electrical

Index 5

(3) Harmfulness (Side effect)

5. Magnetic 6. Light-Electrical 7. Fluid dynamics 9.Gas field

4

Index description

4. Person

8. Thermal-Electrical

The part which is acted on or changed index 2

researchers have proposed to apply renewable energy like solar energy, full cell and human power to supply electricity to these handsets. Therefore, this study aims to demonstrate the feasibility to use the recyclable resource to produce extra electricity. The proposed TRIZ evolution patterns “Evolution toward micro-levels and increased use of field” is relevant to our idea. Additionally, based on the design objective, the new functional performance is to utilize wasted heat which is recyclable to generate electricity by using a thermal-electricity device. The limitation of present mobile phone is the side effect. Converting the information to the index system, index 1 could be the “Evolution toward micro-levels and increased use of field”, index 2 could be the “Environment (Thermal)”, index 3 could be the “Thermal-Electrical”, index 4 could be the “Environment (electricity)” and index 5 could be the “Harmfulness”. Table 8 is the index selection of the new design.

1. Material 2. Tool 3. Part 4. Person

Table 8: The index selection of the new design. In this example, the importance of each weighting is set at one of the levels: the most important, moderately important, and the least important, by assigning values of 3, 2, and 1, respectively. The importance levels of all weights in this work are w1＞w5＞w2＝w3＝ w4. Therefore, the weighting value of w1 is 0.375(3/8), w5 is 0.25(2/8) and w2 to w4 are both 0.125(1/8). Table 9 is the highest similarity case found from database. Case description

5. Environment

(4) Evolution toward micro-levels and increased use of field

1. Geometric

5

The limitations of the product’s function.

2. Resource 3. harmfulness

Index description

4. Physics

Evaluate by the simple LCA method

The presented new solution and the current product would be both evaluated by the simple LCA method which has been proposed by AT&T for concept design. Designers can know which one is better for the environment by calculating total values from the matrix table. Moreover, they can also discuss the advantages and disadvantages of a new design in each life cycle stage. The new design has significant contribution to the environment if the total values are much higher than the current one. On the other hand, if the value gap is not sufficiently high or even the new design has lower values, designers could use the matrix table to discuss the improvement direction and then to propose a better solution. 6

EXAMPLE ILLUSTRATION

Mobile phone has become a living necessity in our daily life. From the eco-design viewpoint, there is a trend to minimize some product features (volume, component and weight). For energy saving, some

(8) Thermal-Electrical (3) Harmfulness (Side effect)

6. Control

5.3

(5) Environment (Thermal) (5) Environment (Electricity)

5. Capability

Table 7: The description of classified index.

Drive the mouse from the waste heat of a notebook (Case num: 59)

Similarity value

1*0.375+1*0.125+1*0.125+1*0.125+1* 0.25=1

The limitation of the product function.

Waste heat operation.

The knowledge for technology innovation

Utilize a device to collect waste heat to produce electricity.

is

produced

during

Table 9: The highest similarity case found from database. Case 59 introduces a heat-electricity transfer device to collect waste heat to produce electricity for a mouse. This innovation idea can be used to another product which also emits useless heat to air. The advantage of adding this device to current mobile phone not only extends the working time of battery but also reduce the discomfort from high temperature. It is a good design idea to new mobile phone. However, there is no reported example that a remarkable quantity of heat is produced in using and how the energy can be retrieved to recharge the battery. Therefore, this new design and current one should both be evaluated by simple LCA to clarify if this idea can be used to make a prototype or not. The meaning for the environmental impact is analyzed via the matrix

Life Cycle Design - Methods and Tools

111

and the guidelines proposed in [21]. For instance, both designs get rating of “3” in product delivery process because of using the same metals. Table 10 shows the result of all evaluation values for both designs. Table 11 calculates the total simple LCA value for both designs.

Premanufacture Product manufacture Product delivery Product use

Mann, D.L. (2002): Hands on Systematic Innovation, CREAX Press, Belgium.

[2]

Clausing D., Fey V. (2004): Effective Innovation, ASME Press.

[3]

Fey V., Rivin E. (2005): Innovation on Demand, Cambridge University Press.

[4]

Cavallucci, D. (2001): Integrating Altshuller’s Development Laws for Technical Systems into the Design Process, in Annals of The CIRP, Vol. 50, pp. 115-120.

Materials

Energy

Solid

Liquid

Gaseous

chosen

use

residues

residues

residues

3 / 2.9

3 / 2.9

3 / 2.9

3 / 2.9

3 / 2.9

2 / 1.9

2 / 1.9

2 / 1.9

2 / 1.9

2 / 1.9

3/3

3/3

3/3

3/3

3/3

4/4

2 / 2.5

4/4

4/4

4/4

[5]

Petrov, V.M. (2002): The Laws of System Evolution, in The TRIZ Journal, March. http://www.trizjournal.com.

3/3

3/3

3/3

3/3

3/3

[6]

Zlotin B., Zusman, A. (2006): Patterns of Evolution: Recent Findings on Structure and Origin, TRIZCON2006, Milwaukee, WI, USA.

[7]

Low, M.K., Lamvik, T., Walsh, K., Myklebust, O. (2000): Product to Service Ecoinnovation: The TRIZ Model of Creativity Explored, in: Proceedings of International Symposium on Electronics and the Environment, IEEE, pp. 209-214, San Francisco, California.

[8]

Mann. D., Jones E. (2002): Sustainable Services & Systems (3s) through Systematic Innovation Methods, The Journal of Sustainable Product Design Vol.2, No. 3-4, pp.131–139.

[9]

Chen, J. L. (2002): Green Evolution Rules and Ideality Laws for Green Innovative Design of Products, In: Proceedings of Going Green-Care Innovation 2002, Fourth International Symposium, Vienna, Austria.

[10]

Justel, D., Vidal, R., Chiner, M. (2005): TRIZ Applied to Innovate in Design for Disassembly, 1st IFIP TC-5 Working Conference on CAI, IFIP-TC5 ULM, Germany.

[11]

Chang, H. T. (2006): A Study of Develop and Predict Ecoproducts from Evolution, in: Proceedings of the Symposium on Sustainable Products and Industrial Management. (in Chinese)

[12]

Schank, R., Abelson, R. (1977): Scripts, Plans, Goals and Understanding. Hillsdale, N.J.: L. Erlbaum Associates.

[13]

Estevez, I., Dubois, S., Gartiser, N., Renaud, J., Caillaud, E. (2006): Le raisonnement `a partir de cas est il utilisable pour l’aide `a la conception inventive, in: Proceedings of 14 Atelier de Raisonnement `a Partir de Cas Besancon, pp. 123–129.

[14]

Lee, Y. C. (2007): Integrating the TRIZ Method within a Casebased System for Product Design Problem Approach, Master Thesis, Department of Computational design, National Yunlin University.

[15]

Gao, C., Huang, K., Chen, H., Wang, W. (2006): Case-Based Reasoning Technology Based on TRIZ and Generalized Location Pattern. Journal of TRIZ in Engineering Design, Vol.2, No.1, pp.40-58.

[16]

Robles, G. C., Negny, S., Lann, J. M. L. (2009): Case-based Reasoning and TRIZ: a Coupling for Innovative Conception in Chemical Engineering. Chemical Engineering and Processing Vol.48, No.1, pp.239-249.

[17]

Chen, J. L., Huang, L. C., Yang, C. J. (2008): Two TRIZ based Eco-innovation Methods by Biomimetic Concepts and

Disposal Current product / New product

Table 10: Environmental assessments for current and new design of the mobile phone. simple LCA total value

Current design

New design

73

72.5

Table 11: Total simple LCA value between current and new design of the mobile phone. From table 10, since new design requires adding a heat-electricity transfer device, the rating of new product in all environmental concerns are lower than the current one in pre-manufacture and manufacture process. On the other hand, the heat-electricity transfer device reduces the electricity demand in product use stage. The overall rating for the new design is 72.5, lower than the current design. Therefore, this new design needs to be revised for worth making a prototype for further study. The ways to improve the new design for better environment assessment can be performed from two directions. One is reducing the amounts of material usage and the complexity of composition. The other is to find another device which reduces energy use in product usage stage. 7

REFERENCES

[1]

Refurbishment, Recycling,

ACKNOWLEDGMENTS

This work is supported by the National Science Council, Taiwan, under grant numbers: NSC96-2621-Z-006-001-MY3. 9

Environmental Concerns Life stages

8

CONCLUSIONS AND FUTURE RESEARCH DIRECTIONS

From the demonstrated example, integrating TRIZ evolution patterns, CBR and simple LCA methods to make new eco-products is practicable. TRIZ evolution patterns make engineers easily decide the way for product innovation. Prior cases from the CBR framework help designers quickly to realize the product ecoinnovation in material and energy field. Matrix table of simple LCA method supports sufficient confidence for designers to make a prototype. For the future research, some continuing works should be undertaken. Increasing the number of evolution patterns is the first priority, which will support engineers more innovation ideas for solving design problems. Continuous modification of the character definition of index system is the second future work. It will increase the ability of CBR framework to support more appropriate cases. Adding new cases from a variety of domains is the third future work. It can increase the ability of solving different types of domain problems. In addition to the material and energy problems, there is still an environment problem from products’ toxicity. The last future work is to include the topic to this approach.

112

Life Cycle Design - Methods and Tools Case-based Reasoning, in: Proceedings of Electronics Goes Green 2008+, pp.707-712.

[18]

Yang, C. J., Chen, J. L. (2009): An Eco-innovation Method for Product Design based on TRIZ and Case-based Reasoning, in: Proceedings of the 16th CIRP International Conference on Life Cycle Engineering (LCE2009), pp.65-70.

[19]

Svensson, G., Ekvall, T. (1995): LCA – A Fair and Cost Effective Way to Compare Two Products?, SAE Technical Paper 951827, Society of Automotive Engineering.

[20]

Christiansen, K., (1997): Simplifying LCA: Just A Cut, Final Report from the SETAC - Europe LCA screening and streaming working group, SETAC-Europe, Brussels, Belgium.

[21]

Graedel, T. E. (1998): Streamlined Life-Cycle Assessment, Prentice Hall, New Jersey.

[22]

Graedel, T. E., Alleyby, B. R., Comrie, P. R. (1995): Matrix Approaches to Abridged Life Cycle Assessment, Environmental Science & Technology, Vol.29, No.3, pp.134A139A.

[23]

Ideation International Inc., (1999): Tools of Classical TRIZ, Ideation International Inc., Southfield, MI.

[24]

ISO 14040, (2006): Environmental Management - Life Cycle Assessment - Principles and Framework, International Organisation for Standardisation (ISO), Geneve.

[25]

ISO 14044, (2006): Environmental Management - Life Cycle Assessment - Requirements and Guidelines, International Organisation for Standardisation (ISO), Geneve.

Proposal of an Integrated Eco-Design Framework of Products and Processes 1

Shinsuke Kondoh , Nozomu Mishima 1

1

National Institute of Advanced Industrial Science and Technology (AIST), 1-2-1, Namiki, Tsukuba, Ibaraki, Japan

Abstract The objective of this study is to propose an integrated eco-design framework of products and processes aiming to support decision making and communication among multiple divisions in manufacturing firms to improve sustainability of their products. Especially, this paper focuses on the integration of three different methods calculating environmental load, cost, and customer utility value, so that manufacturers can simultaneously improve environmental and economic performance of their final products. To do so, Total Performance Indicator (TPI), which has been developed by the authors' group, is introduced and utilized as a glue for connecting these methods by interrelating their inputs and outputs. Keywords: Integrated Eco-Design Framework; Total Performance Indicator; User Value

1

INTRODUCTION

Due to growing concern about environmental problems, manufacturing industry is confronting increasing pressure to improve its environmental performance with increasing (or maintaining) economic value of its final products. Especially for reducing CO2 emission to prevent global warming, improving energy efficiency in production processes as well as product usage stage is quite important. In order to help decision making in product and process design aiming at improving sustainability of manufacturing businesses, many tools and concepts have been proposed recent years. Life cycle assessment (LCA) and eco-efficiency assessment methods (e.g., MIPS [1], Factor X [2]) are popular means for evaluating environmental performance of products and their life cycle (including production processes) and identifying the bottlenecks to be improved from the environmental viewpoint. Industrial engineering (IE) tools [3] and value analysis (VA) [4] method, which help to screen out the bottlenecks from the economical viewpoints, are also popular among production engineers. Although these tools are effective for their own purposes, it is not sufficient to utilize each individual tool alone. LCA is quite useful for evaluating the environmental load of products and services throughout whole life cycle. However, LCA only deals with the environmental aspect of products and services, although the economic aspects are as important as the environmental aspects from the viewpoint of manufacturing businesses. The improvement targets and their potential benefit suggested by LCA should be considered together those from the other aspects. In order to overcome the limitation of each individual method, adequate and integrated utilization of multiple tools for different purposes is quite promising. The objective of this study is to propose an integrated eco-design framework of products and processes aiming to support decision making and communication among multiple divisions in manufacturing firms to improve sustainability of their products. Especially, this paper focuses on the integration of three different methods calculating environmental

load, cost, and customer utility value, so that manufacturing firms can simultaneously improve environmental and economic performance of their final products and services. To do so, Total Performance Indicator (TPI), which has been developed by the author's group [5], is utilized as a glue for connecting these tools by interrelating their inputs and outputs. The paper is organized as follows. Section 2 discusses what kinds of requirements should be satisfied by integration of multiple tools and clarifies the focus of this study. Section 3 introduces TPI to connect three different evaluation tools for environmental load, life cycle cost, and customer utility value of a product, and illustrates how to use these tools together to meet the requirements described in section 2. Section 4 presents a simplified case study of a digital camera to illustrate our method. Section 5 summarizes our methods and discusses future challenges and expansions of our framework. 2

REQUIREMENTS FRAMEWORK

FOR

INTEGRATED

ECO-DESIGN

The requirements for integration of multiple tools are summarized as follows. 2.1

Simultaneous thinking of environmental and economic factors throughout whole product life cycle

Since all businesses have to make profit, both of environmental and economic factors should be considered simultaneously. In addition to that, environmental load and cost should be evaluated from the viewpoint of entire product life cycle, even when the manufacturing firms are not directly responsible for those in after-sale products. 2.2

Representation and consideration of interdependency

There generally exists complicated interdependency among multiple decision variables in manufacturing businesses. Some decisions in product design may cause significant increase (or decrease) in the cost and environmental load at production processes and others in production may cause the improved (or deteriorated) quality (or physical life time) of a target product. For example, application of a new manufacturing technology to improve

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_20, © Springer-Verlag Berlin Heidelberg 2011

113

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Life Cycle Design - Methods and Tools

the smoothness of the sliding surfaces in mechanical equipment may extend its physical lifetime with slight increase in the manufacturing cost. In this case, investment for this technology can be justified only when management and marketing divisions understand its contribution to product lifetime and value for the customers. Therefore, explicit representation and consideration of interdependency among various decision variables in different divisions with different interests is quite important. 2.3

Communicability and understandability

Communication among different divisions with different interests (e.g., environmental performance, production performance, financial performance etc.) is also important. Since the different divisions use the different tools, performance measures, and terminologies, a common and easily understandable performance measure should be established. 3

PROPOSAL OF FRAMEWORK

3.1

AN

INTEGRATED

ECO-DESIGN

Introduction of TPI as a single integrated performance measure

In order to support simultaneous thinking of environmental and economic aspects of products and processes, we introduce a single performance indicator, TPI, in this study. TPI is a measure that represents the combined efficiency of utility value production from environmental and economic viewpoints. TPI is defined as the balance of customer utility value (UV) and its resulting environmental load and cost of the products as follows: TPI 

UV LCE  LCC

(1)

where LCE and LCC denote environmental load and cost throughout the entire life cycle, respectively. Using TPI as an objective function (and a common performance measure) of products and process design, both of environmental and economical aspects are simultaneously taken into account. 3.2

Tools for calculating UV, LCE, and LCC

In order to calculate the value for UV, LCE and LCC in equation 1, we employ three different methods in this study. For calculation of LCE and LCC, conventional LCA and Life Cycle Costing (LCC) methods are employed, respectively. For calculating UV, we have employed multi-attribute utility theory (MAUT) [6] and extended it to represent the deterioration and obsolescence of a product value along time [5]. 3.3

Representation and consideration of interdependency by using QFD

As discussed in section 2, there generally exists interdependency among multiple decision variables in different divisions. Therefore, in order to support adequate design considering this interdependency, causality among these parameters should be identified and represented explicitly. To do that, the Quality Function Deployment (QFD) [7] technique is employed. QFD is a systematic method widely used for translating true customer needs of product/service into technical requirements for design, development, and delivery of a product, by correlating these items with each other 3.4

Design flow and integration of multiple tools

Figure 1 summarizes a design flow of the proposed method. Detail of each step and applicable methods and tools other than LCA, LCC, and UV calculation tools are described as follows;

(i) Definition of a product and its life cycle First, manufacturing firms should define a target product and its life cycle scenario which describes the every flows and life cycle options (e.g., reuse, recycling, landfill etc.) for its constituting components based on their current business model. (ii) Estimation of LCE, LCC and UV Next step is calculation of LCE, LCC and UV of a product. To estimate LCE and LCC, conventional LCA and LCC tools are utilized. In order to reduce the time for conducting LCA, it is effective to simplify life cycle process model of a target products by referring the conventional life cycle inventory database. UV is calculated based on MAUT, which represents the customer utility value of a product as a weighted sum of its dominant functional requirements (FRs). The weighting factors for each FR are generally calculated by conjoint analysis method [8]. Regression analysis of product functional performance and its market price is also usable for this calculation. (iii) Identification of causality/interdependency among various decision variables In addition to the values for LCE, LCC and UV, interdependency of various decision variables are identified and represented by QFD. Interdependency among parameters, which construct UV, LCE, and LCC, is represented by using relational matrix in QFD. First, UV of a product is allocated to its dominant FRs. LCE and LCC of a product are also allocated to its constituent components. Then, relations between (a) FRs and components and (b) components and production processes are identified and represented as FRscomponents relation matrix and components-processes relation matrix, respectively. By using these matrix, a possible increase (or decrease) in environmental load and cost at each production process caused by changes in product design (FRs performance) is calculated. A possible increase (or decrease) in performance of each FR caused by the changes in production processes is also calculated. In this way, interdependency among decision variables for product designers and production engineers are considered. (iv) Identification of bottlenecks After calculation of environmental load and cost for each life cycle stage, bottleneck processes in the product life cycle (including production processes) can be identified from the environmental and economic viewpoints, respectively. Using UV values and calculating TPI of each component, FR, and production process, improvement targets from both of environmental and economic viewpoints are also screened out. Since components or processes with low TPI produce relatively low utility value comparing to their corresponding environmental load and cost, these components and processes should be focused on. In addition to that, it is quite promising to enhance the performance of FRs with high TPI, because these FRs provide high utility value to the customer with relatively small environmental load and cost. (v) Generation of redesign solution and its evaluation After screening out improvement targets, redesign solutions should be generated in terms of EOL options, production process design, and product design. Table 1 summarizes the design guideline for screened out targets in previous step. Although the design guideline gives useful suggestions to the designer, it doesn’t give him/her any practical design of a target product. Adequate utilization of multiple DfX methods (e.g., design for reuse, design for recycling, design for maintenance, design for disassembly etc) in combination with the guideline will be quite effective.

Life Cycle Design - Methods and Tools

115 (i) Definition of a product and its life cycle

(ii) Estimation of environmental load (LCE), cost (LCC), and utility value (UV) Multi Attribute Utility Theory (MAUT)

LCA

(iii) Identification of causality / relationships/ interdependency among UV, functional performance, product design, processes, environmental load, and cost.

LCC QFD Calculation of TPI

(iv) Identification / screening out of target FRs, components, and processes from both of environmental and economic viewpoints

Sustainable business case base (v) Generate redesign solution and its evaluation

Yes

DfX

(vi) More detailed Life cycle model creation Montecarlo simulation

No

Uncertainty / time variation etc. have great effect on the result?

Life cycle simulation (LCS)

Figure 1: Design flow and integration of multiple tools. In addition to that, consideration of different business models (e.g., function selling etc.) from the current one is also promising in some cases. Provision of the design guidelines of sustainable businesses with existing sustainable business cases is also quite helpful for the designer. (vi) Detailed life cycle model creation (if necessary) Sometimes, there exist significant uncertainties in calculation of LCE, LCC and UV. The exact values for some parameters might not be known and stochastic distribution of other parameters might also cause the significant variations in LCE, LCC, and UV values. If the uncertainties of the parameters have a significant impact on the result of calculation, detailed life cycle process model handling these uncertainties should be developed. For this purpose, discrete event simulation method is quite suitable. Examples of this approach include Life Cycle Simulation method [9]. To finding out adequate design solution under significant uncertainty, montecarlo simulation method and robust design method can be also effectively utilized. Reduction of cost and E.L.. Components with low TPI Design options

Reuse Recycling Reduce

Components Components with low CP with low PP

Enhancement of value FRs with high TPI

FRs with high obsolescence rate

X X X

Prolongment of physical life

X

Upgrading Enhancement of functionality

FRs with high deterioration rate

X X

Table 1: Design guidelines based on TPI of each component, process, and FR.

4

CASE STUDY: A DIGITAL CAMERA

In order to illustrate how to use each method and integrate them together, a simplified case study of a digital camera is conducted. The target product is an imaginary compact digital camera with rechargeable battery. LCE and LCC of the product are dominated by those in production stage, which are further divided into production of each component as shown in Figure 2. From the result of LCA and LCC, production processes of main board and lens unit should be improved, respectively. TPI of each component and FR is calculated by using the result of LCA and LCC, considering the causal relationships between environmental load and cost of components and UV of a product. Figure 3 shows the TPI of each FR and component. Considering the both of environmental and economic aspects, production processes of LCD unit and body should be focused on due to their low TPI values. In addition to that, this result suggest that enhancement of functional performance of "FR: Clear picture" is quite promising to improve its customer utility value. Improvement potentials in TPI are also calculated based on two redesign solutions, namely, (i) enhancement of "FR: clear picture" and (ii) reuse of LCD unit and body. Estimated improvement in TPI of these solutions is 26% and 19%, respectively. LCA and LCC results suggested a different improvement targets in this example. In order to prioritize improvement targets, environmental and economic aspects should be considered simultaneously. This problem is solved by using TPI. TPI results suggested most promising FRs to improve environmental and economic performance of a target product in addition to bottleneck production processes, while LCA and LCC only suggested bottleneck production processes. Integrating LCE, LCC and UV into one single indicator and interpreting TPI calculation results with design guidelines proposed in section 3 are quite effective. Estimating improvement potential of each redesign solution is also effective for prioritizing them. Since decision making in product

116

Life Cycle Design - Methods and Tools

E.L. at Production [kgCO2]

LCE [kgCO2]

Lense unit CCD unit Production Distribution

Unti-blurring mechanism

Use

Main board

LCD unit

Collection

Flash unit

EOL

Production process of a main board should be improved.

Body Battery

Production cost [kJPY]

LCC [kJPY]

Lense unit Production

CCD unit

Distribution

Unti-blurring mechanism

Use

LCD unit

Collection

Main board

EOL

Production process of Lens unit should be improved.

Flash unit Body Battery

Figure 2: LCA and LCC results and suggested improvement targets.

TPI of FRs

400.00

FR with high TPI

300.00 200.00 100.00 0.00 Clear

Applicability

picture (high to multiple resolution) 350.00 300.00 250.00 200.00 150.00 100.00

Less

Beautiful

Overall

blurring

portrait

product

•Production processes of LCD unit and body should be improved. •Reuse or recycling of LCD unit and body is promising. •Performance of FR: “Clear picture“ should be enhanced.

situations

TPI of components

50.00 0.00

Components with low TPI Figure 3: TPI of FRs and components and suggested improvement targets. design and production (or service) process design are executed by different people and there sometimes exists trade-off among these decision variables, prioritizing design solutions proposed by different divisions based on an easily understandable single indicator is very promising. 5

CONCLUSION

This paper proposed an integrated eco-design framework using a TPI as a glue for connecting different tools focusing on

environmental load, cost and utility value calculation, so as to support decision making and communication in manufacturing firms to improve the environmental and economical performance of their products and services. This paper also illustrated how to combine these tools with a simplified example of a digital camera, and compared redesign solutions derived by each LCA, LCC, and TPI method to clarify advantages of our method. As shown in the case study, TPI was successfully utilized to find out bottlenecks in product and process design simultaneously. Proposed integrated

Life Cycle Design - Methods and Tools framework for utilizing multiple tools for sustainable product and process design is concluded to be effective. In addition to LCA, LCC, MAUT, and QFD, integrated utilization of other design methods is also quite promising. For example, in order to handle significant uncertainties in product life cycle (e.g., collection rate for recycling, product usage condition and duration etc.), robust design method that derives adequate design solutions considering the variations in given parameters can be effectively utilized [10]. In order to design upgradable products, modular design method is quite useful [11]. Existing various eco-design guidelines [12] and their case base are also useful to generate improvement ideas of product, process, and eco-business design, when their applicable conditions are interrelated to the TPI calculation results [13]. Expansion of our methods and integration of these tools will be executed as our future work. Future work also includes implementation of the method and framework and their application to real industrial cases. 6

117 operations, Kingston, R. S. Means Company, Inc. [5]

Kondoh, S.; Masui, K.; Hattori, M.; Mishima, N. (2008): Total performance analysis of product life cycle considering the deterioration and obsolescence of product value, in: Int. J. Product Development, Vol. 6, Nos. 3/4, pp.334-352.

[6]

Winterfeld, D. V.; Edwards, W.; (1986): Decision Analysis and Behavioral Research, Cambridge University Press, Cambridge, England.

[7]

Akao K. (1990): Quality function deployment, Productivity Process, Cambridge, M.A.

[8]

Green, P. E.; Srinivasan, V. (1978): Conjoint Analysis in Consumer Research: Issues and Outlook, in: J. of Marketing Research, XV, pp.132-136.

[9]

Komoto, H.; Tomiyama, T. (2009): Integration of a service CAD and life cycle simulator, in: Annals of the CIRP 57(1), pp.9-12.

[10]

Kondoh, S.; Mishima, N.; Masui, K.; Matsumoto, M. (2009) Total performance design of product life cycle considering future uncertainties, in: Int. J. Design Engineering, Vol. 2, No. 3, pp.278-298.

REFERENCES

[1]

Schmidt-Bleek, F. (1993): Wieviel Umwelt Braucht der Mensch? (How much environment does man need?), Birkhauser Verlag, Berlin.

[11]

[2]

Reijnders, L. (1998): The Factor X Debate: Setting Targets for Eco-Efficiency, in: Journal of Industrial Ecology, Vol. 2, No. 2, pp.13-22.

Kimura, F.; Kato, S.; Hata, T.; Masuda, T. (2001): Product Modularization for Parts Reuse in Inverse Manufacturing, in: Annals of the CIRP 50(1), pp.89-92.

[12]

[3]

Salvendy, G. (Ed.) (2001): Handbook of industrial engineering: Technology and operations management, WileyInterscience.

UNEP (1997): ECODESIGN: a promising approach to sustainable product and consumption, UNITED NATIONS PUBLICATION.

[13]

Kondoh, S.; Mishima, N. (2010): Strategic decision-making method for eco-business planning. In: CIRP AnnalsManufacturing Technology, 59(1), pp.41-44.

[4]

Dell'Isola, A. (1997): Value Engineering: Practical applications, for design, construction, maintenance &

Development of CAD System for Life Cycle Scenario-Based Product Design 1

1

Eisuke Kunii , Shinichi Fukushige , Yasushi Umeda 1

1

Department of Mechanical Engineering, Graduate School of Engineering, Osaka University, Japan

Abstract Life Cycle Management (LCM) has established as research area to foster sustainability in all fields of action of organizations. To provide an understanding for this broad research area suitable teaching methods are required. This paper presents the concept for a business game based on the Framework for Total Life Cycle Management (TLCM). It enables participators to understand the interdependencies of four different management disciplines: product, production, after sales and end-of-life management. The educational objective is to continuously develop a holistic life cycle strategy. The game requires communication of all actors and reasonable activities towards sustainability. By that prospective managers can understand relationships and interdependencies of TLCM. Keywords: Life Cycle Scenario; Product Design; CAD

1

INTRODUCTION

In order to increase value and reduce environmental loads of a product life cycle, it is important to design the product considering its life cycle. We refer to this approach as life cycle design. In such design, it is necessary to plan a life cycle strategy based on the characteristics of the product and its market and to design the product so as to realize this strategy. For instance, to reduce the consumption of materials in a product, the implementation of lightweight design may be efficient. However, if a product has a long life, a design that resists abrasion and degradation and offers a longer life is a more reasonable strategy. We therefore believe that designing product based on the life cycle strategy results in successful design solutions both environmentally and economically. This paper proposes an integrated design system to support both life cycle strategy planning and product design based on the life cycle strategy. As the first step for this purpose, this paper proposes as integrated representational scheme of a product and its life cycle strategy. This paper is organized as follows. Section 2 briefly summarizes literature review and then shows the concept of an integrated life cycle design system. Section 3 proposes the integrated representational scheme of a product and its life cycle strategy. Section 4 proposes an integrated design method to support life cycle scenario-based product design. Section 5 outlines a life cycle scenariobased product design support system. Section 6 concludes this paper. 2 2.1

TOTAL LIFE CYCLE MANAGEMENT Literature Review on Life Cycle Design

Life cycle design has been proposed as a new approach in which a product is designed with considering its entire life cycle from the stage of product conception to final reuse/recycling or disposal [1]. In the life cycle design, a life cycle of a product should be designed as well as the product itself.

We previously proposed the procedure for the life cycle design shown in Figure 1 [2]. First, a designer analyzes the present condition of society, markets, etc. Second, the designer determines business strategies, environmental targets and product concepts based on the results of this data analysis. Third, the designer formulates a life cycle strategy according to these business strategies, environmental targets and product concepts. Then, the designer designs the product and its various life cycle processes (including, manufacturing process, sales process, and recycling process) so as to realize the life cycle strategy. Finally, the designer evaluates the life cycle of the product in order to check that the life cycle strategy can be achieved. In short, the life cycle strategy is planned at an early stage of life cycle design, and the product is designed so as to realize this strategy. With the life cycle design, the designer can propose a product optimizing environmental loads and costs throughout its life cycle. Many studies focus on the support of life cycle design. Kobayashi [3] proposed the Life Cycle Planning, which supports the choice of life cycle options of parts through the linkage of QFD and LCA data. Kwak [4] proposed a framework for evaluation of the relationship between product design and resource circulation flow with Transition Matrix. Phang et al. [5] proposed a life cycle design method Present data analysis

Business strategy

Environmental target

Product concept

Life cycle strategy planning

Product design

Process design

Life cycle evaluation

Figure 1: Life cycle design procedure [2].

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_21, © Springer-Verlag Berlin Heidelberg 2011

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119

using Distributed Oriented Modeling and Environment (DOME). A number of studies have also addressed environmentally conscious design technologies including design for recycling, and such technologies have been practically adapted to product design [6]. However, the relationship between life cycle strategy and product design has not been clarified, and the integrated support environment for both life cycle strategy planning and product design remains insufficient.



2.2

In this paper, we propose an integrated representation scheme of a product and its life cycle for supporting product design based on life cycle strategy.

Fundamental Concepts of Life Cycle Scenario-Based Product Design

As mentioned in Section 2.1, a life cycle strategy should be planned at an early stage of the product design. The life cycle strategy should be determined depending on the characteristics and the structure of the product. For example, it is inappropriate to decide the maintenance strategy for the product which has a short value life. An integrated computational design environment with managing the interaction between the life cycle strategy and the product is required. In this paper, we employ the life cycle scenario as a representational scheme of a life cycle strategy to support life cycle strategy planning. As shown in Figure 1, life cycle strategy is planned prior to product design, and a product is designed based on the life cycle scenario. Here, we call a series of the design from life cycle strategy planning to product design “life cycle scenario-based product design”. In order to support such design, this paper provides a workspace for a designer to plan the life cycle strategy and to design a product based on this strategy in an integrated manner. Therefore, we identified four requirements for the support method of the life cycle design as follows: 

The representational scheme of a product and its life cycle strategy A product and its life cycle strategy should be modeled in an integrated manner. In this paper, we propose an integrated representational scheme in Section 3.



To maintain the relationship between a product and its life cycle strategy Life cycle design should be support by managing the consistency between them and evaluating a life cycle. In this paper, we propose the method of linkage between two topological models: the product model and the life cycle scenario.



The product should be designed so as to realize the life cycle strategy. We propose an integrated product design method based on the life cycle scenario. 3

3.1

Structure model

:

Module node, Part node

:

Hierarchical structure

:

Connection structure

MODELING OF A PRODUCT AND ITS LIFE CYCLE STRATEGY

Product Model

In this method, a product model consists of two sub-models; namely, a structure model and a geometrie model (see Figure 2). The structure model represents the hierarchical relationship and the structure connection between modules and parts. In the structure model, we define three kinds of constituent nodes: product node, module node and part node. A product node represents the whole product at the top of the hierarchical structure, a part node at the bottom, and a module node represents an assembly of parts or other modules in the middle of the hierarchy. Here, the module node is related to the activities of assembling or disassembling in the product life cycle. Each node has attributes such as constituents, lifetime, weight, etc. The connection structure is represented in the form of topology between modules or parts in the same level of hierarchy. The geometric model is drawn with 3D CAD, and each part has links with correspondent nodes of the structure model. The link enables to construct a product model with correspondence between structural and geometrical information. 3.2

Life Cycle Scenario

Describing a life cycle scenario is an effective method for planning the life cycle strategy. Here, a life cycle scenario is defined as a description of the anticipated product life cycle. In other words, by describing a life cycle scenario, a designer can easily identify appropriate life cycle options and requirements for product design. In the method for life cycle scenario description [2], a life cycle scenario consists of the following four items. In this approach, we employ this representation for describing the life cycle strategy. 

Objective of the life cycle The objective of the life cycle highlights objectives for life cycle strategy planning. We represent the objectives by using sentences and parameter values that quantify the sentences.

Planning method of a life cycle strategy In this paper, the life cycle strategy is defined as a combination of life cycle options for a product and its components (e.g., upgrading, spare parts reuse, material recycling), which should be logically planned based on the business strategies, environmental targets and the product concept (as shown in Figure 1). We employ the method for life cycle scenario description [2].

The product design method based on the life cycle strategy



Life cycle scenario concept The life cycle scenario concept indicates the basic direction for constructing a life cycle scenario by using brief sentences (e.g., rapid circulation scenario). This item plays an important role as a medium between the objectives and the life cycle option.

Geometry model

Life Cycle Flow

Situation

Product

Manufacturing

Distribution

Maintenance

Use

Discarded products are collected from users by a secondhand goods dealer at a second hand dealer shop.

Collection

Attribute values e.g.,Constituent, Lifetime, Weight, etc.

Reuse

Disassembly

Landfill

Recycling

Figure 2: Example of a product model.

Figure 3: Example of a life cycle flow.

120 

Life Cycle Design - Methods and Tools 

Life cycle option The life cycle option is an alternative of a life cycle for the product and its components, and determines the basic structure of the life cycle scenario. The most critical target of the life cycle scenario description is to select the life cycle options that are most appropriate for the product.



A designer should describe the product model, the life cycle scenario and the linkage between them without physical inconsistencies. An example of the inconsistencies is the wrong connection between the life cycle flow model and the structure model shown in Figure 5; a certain module node of the structure model cannot be linked to the next link of the process which disassembles this module.

Life cycle flow model The life cycle flow model is the central model of a life cycle scenario and represents the flows of products, components and materials as a network of life cycle processes (see Figure 3). Each life cycle process has a situation formulated using the 4W1H (When, Where, Who, What and How) approach and a description of the income and expenditure of the operator of the process for use in evaluating the economic aspect of the life cycle.

In order to embody the life cycle strategy in a product in the later stages of life cycle design, it is essential to clarify requirements for product design. We therefore describe such requirements in the situation (e.g., the lifetime of a module for reuse must be at least twice that of the product). 3.3

Linkage between the Product Model and the Life Cycle Scenario

To support integrated management of a product and its life cycle toward the fulfillment of such requirements, we link two topological models: the product model (outlined in Section 3.1) and the life cycle scenario (outlined in Section 3.2). The linkage between the two models is shown in Figure 4. Here, each link of the life cycle flow model in the life cycle scenario links to the corresponding node of a structure model for mutual information reference. Through such linkages, a designer can identify which node of the structure model passes through which process of the life cycle flow model. Through this linkage, a designer can easily check the following two elements, which is important for the life cycle scenario-based product design.

In the life cycle scenario-based product design, the product model must fulfill the requirements of the life cycle strategy in order to enhance the feasibility of a life cycle scenario. For instance, when a certain module will be reused, its lifetime should be designed to fulfill the lifetime set in the scenario. 4 4.1

LIFE CYCLE SCENARIO-BASED SUPPORT METHOD

PRODUCT

DESIGN

Outline

In this paper, we propose an integrated design method to support life cycle design by using the model outlined in Section 3. The integrated design method consists of two phases: life cycle strategy planning phase and product design phase. In the first phase, we describe the life cycle strategy by using the life cycle scenario as outlined in Section 3.2 and the method supports the description of a life cycle scenario. In this phase, it is important to describe a life cycle scenario so as to enhance its effectiveness, which is defined as the evaluation results of the life cycle scenario. In the second phase, the method supports product design based on the life cycle scenario determined in the first phase while maintaining consistency between the product model and the life cycle scenario. In this phase, product design should be performed in order to enhance the feasibility of the life cycle scenario.

4.2

Life Cycle Flow model

Structure model

Figure 4: Correspondence between structure model and life cycle flow.

Transportation

Recycling

Fulfillment of life cycle strategy requirements:

The main aim of the proposed method is to manage the interaction between these two phases; in other words, the method enables a designer to design and modify the product and/or the life cycle scenario interactively according to the evaluation results.

Landfill

Recycling

Disassembly



In these phases, the method enables the life cycle evaluation of environmental loads and costs by providing the evaluator with the information of the product model and the life cycle scenario.

Transportation Disassembly

Maintenance of consistency on a topological level:

Landfill

Since most product characteristics (e.g., recyclability) are mainly decided in the design phase, the life cycle strategy should be planned prior to product design. As outlined in Section 3.2, a designer describes the life cycle strategy in the form of the life cycle scenario. In the proposed method, we assume that business strategies, environmental targets and the product concept are given (which should be determined prior to planning the life cycle strategy as described in Figure 1). Here, the product concept includes the main modules of the product; that is to say, the main modules are determined prior to the life cycle scenario description phase. To support the life cycle strategy planning phase, we developed a life cycle scenario description methodology in a previous work [2]. In this methodology, a designer describes the life cycle scenario in a trial and error manner using a top-down approach as follows:

Inconsistency!!

I.

Life Cycle Flow model

Life Cycle Strategy Planning Phase

Structure model

Figure 5: Example of an inconsistency.

The designer sets the objectives of the life cycle to be planned, based on various kinds of information such as the target product and market in order to identify the target of the life cycle scenario.

Life Cycle Design - Methods and Tools

121

II. The designer clarifies one or more life cycle concepts based on these objectives in order to determine an outline of the life cycle scenario.



III. The designer selects life cycle options for each main module based on the life cycle concept by using the external support resources such as Life Cycle Option Selection Support Tools [7].

When the designer makes design changes, the consistency on the topological level must be checked in order to support the design changes without inconsistency on a topological level. If the fulfillment of the requirements cannot be expected even with design changes, it is necessary to return to the life cycle strategy planning phase and revise the life cycle scenario with the reason for this revision as a new design rationale.

IV. The designer draws up a life cycle flow model of the main modules and specifies the situation of each process. In this phase, it is necessary to clarify the requirements for product design in order to embody the life cycle strategy in the product design phase. We describe the requirements as the situations of the life cycle flow model in step IV above. 4.3

Product Design Phase

In this phase, the designer designs the product based on the life cycle scenario determined in the life cycle strategy planning phase. According to the progress of product design, the designer improves the life cycle scenario (especially the life cycle flow model) as needed. The main purpose of this phase is to design a product structure so as to enhance the feasibility of the life cycle scenario. In the proposed method, the designer designs the product as follows (see Figure 7). I.

The designer determines attributive values of a certain module or part, and creates its geometric model, and then makes the module or part node of a structure model.

Addition to the life cycle flow model of new processes that the created module or part passes independently of the node selected in the second step (see Figure 6)

Whenever a new module or part is designed, the designer follows steps I-V. Here, the design of the geometric model and the attributive values (performed in step I) is performed arbitrarily according to the various requirements to be considered in product design (e.g., function, design, etc.). That is to say, the proposed method does not interfere with the adaptation of existing design method. 4.4

II. The designer selects the node of the structure model that contains the module or part as its component created in the first step. And then, the node corresponding to the created module or part is automatically added to the structure model with hierarchical connection between the parent node and the new child node added in this step. III. The designer determines the connection structure between the added node and the other existent nodes in the structure model as needed. IV. The designer checks whether the designed module or part fulfill the requirements of the life cycle scenario described in the life cycle strategy planning phase comparing the product model (geometric model and structure model) with the life cycle scenario.

Evaluation of a Life Cycle

The overall environmental loads throughout the product life cycle are the most critical indicator in estimating the product life cycle. On the other hand, the feasibility of the life cycle design depends heavily on the related costs. Accordingly, both the environmental loads and the costs should be evaluated in life cycle evaluation. To this end, we employ Life Cycle Simulator (LCS) [8], which can evaluate environmental loads and costs throughout the entire product life cycle using a discrete event simulation technique and LCA data Product

Landfill

Disassembly Recycling

Design change This node cannot be applied to recycling by a certain reason!

Can the life cycle flow of the parent node apply to the child node?

IV. Check requirements

Use Collection

Reuse

Improvement of the attributive values or the geometric model of the designed module or part Product

Distribution

Maintenance

Product

A designer decide to separate and landfill the offending node.

Distribution

Manufacturing Maintenance

If the designer decides that improvements are needed because the requirements remain unsatisfied, he or she makes one or more of the following design changes.  Improvement of the hierarchical structure; in other words, selection of another node of the structure model, containing the module or part designed in the first step 

Manufacturing

Use Collection Disassembly

Reuse

Landfill

Disassembly Recycling

Added process and links

Figure 6: Example of an addition of new processes and links.

Manufacturing Maintenance

Distribution Use

Parent node Collection

II. Add hierarchical connection I. Create new node III. Add connection structure

Reuse

New child node

Figure 7: Flow of a product design based on a life cycle scenario.

Disassembly Recycling

Landfill

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Life Cycle Design - Methods and Tools

such as intensities for LCA. For this simulation, the life cycle flow model of a life cycle scenario is used. Entering information on a product model and a life cycle scenario enables interactive evaluation of the designed life cycle. 5 5.1









Management of the linkage between the product model and the life cycle scenario: In the life cycle scenario-based product design, it is important to link the product model with the life cycle scenario and to manage such linkage. The system provides integrated management of this linkage to allow mutual information reference.

Consistency Manager: 

Evaluation of life cycle: In the life cycle scenario-based product design, life cycle evaluation should be performed at all stages of the process for design with verification of life cycle scenario effectiveness and feasibility with LCS.

Structure Model Editor and 3D Solid Modeler: Allow the designer to draw and modify structure models and geometric models.



Checking of consistency on a topological level: In order to prevent the designer from creating inconsistencies on a topological level, the system automatically checks consistency. If the system finds out inconsistencies created by the designer, the system issues a warning and highlights the offending part.

System Architecture

Manages the consistency on a topological level between the product model and the life cycle scenario.

Main Function of the System

To support the life cycle design cycle, the proposed system includes the following three functions:

LIFE CYCLE SCENARIO-BASED PRODUCT DESIGN SUPPORT SYSTEM

We propose an integrated design support system for both life cycle strategy planning and product design based on life cycle strategy. The architecture of the proposed system is shown in Figure 8. The system consists of five sub-modules: Consistency Manager, Structure Model Editor, 3D Solid Modeler, Life Cycle Scenario Editor and Life Cycle Simulator. 

5.2

Life Cycle Scenario Editor: Helps the designer to describe and revise life cycle scenarios.

6

Life Cycle Simulator:

With the aim of supporting life cycle scenario-based product design, this paper proposed a procedure of describing life cycle scenarios and designing products, and outlined a related design support system. A product model and life cycle scenario are defined to describe the product and life cycle strategy, and the product model is linked to the life cycle scenario. In future work, we plan to propose a framework that allows the application of suitable environmentally conscious design technologies (such as design for recycling) using the proposed description and linkage method for products and their life cycles.

Evaluate environmental loads and costs throughout the entire product life cycle. In this paper, we employ LCS as mentioned in Section 4.4. There are also three databases: the material database, the process database, and the LCA database. The material database stores information on various materials data such as specific gravity, market price and recycling costs. The process database stores various types of process model such as those for collection, land transportation, and recycling. And the LCA database stores information on intensities for LCA such as CO2 emission in electricity generation (kgCO2/kWh). The system supports life cycle design systematically and effectively by accelerating the cycle of life cycle strategy planning, product design, and life cycle evaluation through these components.

CONCLUSION

Designer designs a product while comparing three models (3D Solid Model, Structure Model and Life Cycle Flow) visually!!

Designer

Consistency Manager

Product

Manufacturing Maintenance

Distribution Use Collection

Link

Link

Reuse

Disassembly

Landfill

Recycling

3D Solid Modeler

Structure Model Editor

Life Cycle Scenario Editor

Product Model

Database

Material DB

Process DB

LCA DB

Figure 8: System architecture.

Life Cycle Simulator

Life Cycle Design - Methods and Tools 7

REFERENCES

[1]

Kimura, F., (1999): Life cycle design for inverse manufacturing, The Institute of Electrical and Electronics Engineers, Tokyo, in: Proceedings of Eco Design 1999, pp. 995-999.

[2]

Suesada, R., Itamochi, Y., Kondoh, S., Fukushige, S., and Umeda, Y., (2007): Development of Description Support System for Life Cycle Scenario, in: Proceedings of CIRP LCE 2007, Springer, pp. 29-34.

[3]

Kobayashi, H., (2000): A Method of Life Cycle Planning for Product Eco-improvement, in: International Journal of Environmentally Conscious Design & Manufacturing, No.8, pp. 2737.

[4]

Minjung Kwak, Harrison M. Kim, (2010): Evaluating End-ofLife Recovery Profit by a Simultaneous Consideration of Product Design and Recovery Network Design, in: Journal of Mechanical Design, ASME, Vol.132, No.7, 071001.

[5]

K. F. Phang, N. Senin, and D. R. Wallace, (1998): Distributed modeling and evaluation of product design problems, in: Computer-Aided Design, Vol.30, No.6, pp. 411-423.

[6]

Keijiro M., (2009): Current Status of Environmentally Conscious Design among Japanese Manufacturers, in: International Journal of Automation Technology, Vol.3, No.1.

[7]

Umeda, Y., Life Cycle Design Committee, (2001): Toward a Life Cycle Design Guideline for Inverse Manufacturing, in: Proceedings of Eco Design 2001, pp. 143-148.

[8]

Umeda, Y. et al., (2000): Study on Life-cycle Design for the Post Mass Production Paradigm, in: Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol.14, No.2, pp. 149-161.

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Environmental Impact Assessment Model for Wireless Sensor Networks 1

1

1

Jérémy Bonvoisin , Alan Lelah , Fabrice Mathieux , Daniel Brissaud 1

1

G-SCOP Laboratory, Grenoble University, Grenoble, France

Abstract The aim of our research is to understand what design parameters are responsible for the environmental impacts of deployment and operation of wireless sensor networks (WSN), with the underlying aim to support their ecodesign. In this paper, we propose an environmental impact assessment model for WSN based on lifecycle assessment (LCA) and network energy analysis. It is based on a two-level approach, given that environmental impacts of WSN are generated by both the network elements and their synergetic effects. This model will help analyse the sensibility of the environmental impacts to parameter changes, and compare different solutions. Keywords: Lifecycle Assessment (LCA); Machine-to-Machine (M2M); Energy

1 1.1

INTRODUCTION Wireless Sensors Networks (WSN)

Information and Communication technology (ICT) is changing the world we are living in. Electronic devices surround us, processing information which is influencing the way we carry our every day businesses. Their spread has led to the idea of an “information society” which is seen as very promising for a rational management of human organisations, based on the idea that information about a process allows for better control [1]. Wireless Sensor Networks (WSN) is part of these promising technologies. WSN consists of communicating autonomous sensors that cooperate to monitor physical phenomenon, e.g. temperature or noise. Recently, linked to WSN, concepts such as “Ambient Intelligence”, “Smart Environments” [2] or “Ubiquitous society” [3] have grown. WSN could potentially be applied to a broad range of applications in several domains such as military, home, health and environment [4]. WSN could be embedded in buildings, automotive, clothes and even in vivo [2]. At a city scale, it could be used to enhance efficiency of urban services such as energy and water supply or transport management [5]. According to outlooks [2, 4], WSN will tend to be more and more used, as their production costs go below the economic benefits they are supposed to generate. 1.2

WSN and the environment

Many commentators tend to be optimistic on the ability of ICT to address optimization problems, particularly in the field of environmental protection [6]. Many industrial publications try to show economic and environmental benefits of ICT [3, 7]. However, as Erkman, Berkhout, Yi and Loerincik [8-11] temper, the environmental impacts and benefits of ICT are not yet well understood. There is overconfidence on the belief that ICT will help us to deal with complexity and help us in our way to sustainability [12]. It is a promising technology, but it is not neutral, as electronic production generates important environmental impacts [13]. We can not nowadays predict the effects of ICT, as they will depend on our ability to use them in a sustainable way [11, 14]. The question just goes as well for WSN as an ICT amongst others.

Wireless sensors are small objects, and their individual impact seems very low. However, the deployment of large scale WSN will lead to the spreading of thousand (or even millions) of devices [4], merely in a “deploy and forget” way [2]: which means that they may not be retrieved at the end of their service life. It seems therefore relevant to study their environmental impacts. Some examples show interesting benefits [5, 15], but studies tend to be optimistic, presenting benefits and forgetting the drawbacks. Some others, trying to draw the whole picture, conclude in the same way [11, 16], while other draw a more nuanced picture [17, 18]. 1.3

Research objective

The aim of our research is to understand the environmental impacts of WSN, which have been until now less often considered as their potential benefits. We want to identify the most influent design parameters regarding the environmental impacts of WSN, in order to support their eco-design. We adopt a two-level approach, at product level (WSN node) and at system level (network) and we set up a calculation model based on lifecycle assessment (LCA) and energy modelling. Based on the exploratory research done by Hoang [17], we go into further details in the definition of an impact assessment method for WSN. The aim of this paper is to present this method, and to propose a calculation model for environmental impacts of WSN. We will first explore the WSN infrastructure and its lifecycle. Then we will present our WSN environmental impact assessment model in details. Finally, we will apply the model on an example to show its possible results. 2 2.1

WSN AND THEIR LIFECYCLES Infrastructures of WSN services

Services based on WSN rely on cooperation of different product types, as follows: 

Sensor/actuator nodes: small electronic devices embedded in the phenomenon that needs to be monitored. They can gather physical information due to one or more sensors, and can

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_22, © Springer-Verlag Berlin Heidelberg 2011

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

Repeaters: small electronic devices that transmit information across the network. They help concentrate information from the sensors towards the gateways. They are simply composed of a communication module and a power supply unit. As for sensors, the power supply is most of the time an irreplaceable battery.



Gateways: electronic devices that gather the information generated by the sensors. These are more complex devices that link the WSN to the service platform. They manage communication with two different communication protocols, one to gather information from the WSN (IEEE 802.15.4), the other to reach the service platform (IP, GPRS). Each gateway may thus consume more energy than the sensors and repeaters. The power supply unit can be of various technologies (battery, photovoltaic, connected to the mains, etc.).





Telecommunication network: once gathered by the gateway, information is concentrated and may be too heavy to be handled by WSN protocols that have limited capacities. After the gateway, conventional telecommunication networks (IP, GPRS), which can transmit information at higher rates, relays the WSN protocols.

WSN Lifecycle

Whatever the energy supply unit is, a device consumes energy, and this has an influence on its environmental impact. It is quite obvious for plugged devices: they take energy from the mains, which has environmental impacts due to the electricity production. It is more indirect for battery-driven devices: the energy consumption, along with the battery capacity, highly conditions the lifespan of products. The more battery-driven nodes consume energy, the shorter their lifespan, the more often they need to be replaced, and the greater the environmental impacts of the WSN become. Energy is known to be the major technical limiting factor of WSN in terms of computing power and lifespan, as “sensor nodes carry limited, generally irreplaceable power sources” [4]. Research is therefore active to look for techniques to enhance the nodes’ autonomies. Several directions are explored, such as efficient network protocols [19], or energy scavenging technologies [2]. We adopt a new point of view, identifying the system design parameters that decrease nodes’ energy consumption, and thus have an effect on the overall environmental impact of the WSN. The network lifecycle

In order to calculate the environmental impact of the WSN, we have to take into account the environmental impacts of the lifecycles of its components (nodes), and the synergetic effects. Thus, as shown

Deployment

Exploitation

Manufacturing





Transport





Installation





End-of-life

Usage



Removal





End-of-life





Table 1: The two interconnected lifecycles of the WSN and of its composing nodes. According to these lifecycle considerations, the environmental impact of the overall WSN can be represented by the equation (1):

I

A System Level Approach

The environmental impact of a WSN is more than just the sum of the individual environmental impacts of its components. The networking of these communicating objects creates synergetic effects: the more a sensor stimulates its neighbours, the more they consume energy. Impacts of WSN can not be assessed by a simple product-based approach: a system-wide approach is needed to take synergetic effects into account.

2.3

In the first stage of its lifecycle, the network is set up. To do so, WSN nodes need to be manufactured, transported and installed on site. In the following stage, the network is operated. In that phase, the nodes consume energy, and the battery-driven ones may be replaced by new ones once their battery discharged. Therefore, new nodes need to be manufactured, transported and installed, while the old ones need to be removed and processed for their end of life. Note that no impact is counted for the usage phase of battery driven nodes, as energy is used to produce the battery during production phase and no extra energy is needed during usage. In the case of a mains-driven node, usage impact consists in supply grid energy consumption. At the network end of life, it is dismantled, and each node is removed to undergo end of life processing.

Service platform: servers that concentrate and transform information in order to provide a service to users.

In this paper, we focus only on the environmental impact of the WSN, meaning that we do not consider the environmental impact of the service platform and telecommunication network. This will be the object of future publications. 2.2

in the Table 1, we have to consider two interconnected lifecycles: those of the components (WSN nodes lifecycles), and those of the infrastructure itself (WSN lifecycle)

Nodes lifecycles

eventually respond with actuating capability. It is in the least composed of a sensing unit, a processing unit, a transmitting unit, a power supply unit, and eventually other modules [4]. The power supply is usually a battery, which is often difficult, if not impossible, to replace.

125



  DEP

node e



e

   REPe 

  P     CON e   DIS e    Le   

(1)

Where: 

I is the total environmental impact of the WSN lifecycle, expressed as the sum of the environmental impacts of the nodes (including synergetic effects) which compose the WSN;



DEPe is the environmental impact of the node e during the deployment stage of the WSN, which corresponds to manufacturing, transportation and installation of the node e;



REPe is the environmental impact of the replacement of the node e during the exploitation stage of the WSN, which corresponds to the whole lifecycle of the new node replacing the node e;



CONe is the environmental impact of the energy consumption of the node e during exploitation;



DISe is the environmental impact of the node e during the dismantling stage of the WSN, which corresponds to the removal and the end of life of the node e;



Le is the lifespan of node e;



P is the WSN exploitation period considered.

3

PROPOSED MODEL

ENVIRONMENTAL

IMPACT

ASSESSMENT

We base the calculation of environmental impacts on equation (1). In this equation, DEPe, REPe and DISe can be quantified by performing a classic lifecycle assessment (LCA). However, in order to determine Le and CONe, further calculi on energy are necessary. We therefore set up a calculation model based on three phases: 1.

perform LCA for each product composing the WSN;

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2.

perform energy analysis and determine Le and CONe;

3.

aggregate environmental impacts to get a final figure.

PRX  PTX  G RX  GTX  L

The first phase is well defined by the scientific community [20], so it won’t be detailed in this paper. The third is represented by equation (1). The purpose of the following section is to detail the second step: determination of Le and CONe. This will be detailed in three sub-steps: 1.

determine the electromagnetic neighborhood of each node;

2.

calculate the energy consumption of each node;

3.

derive corresponding Le and CONe.

3.1

Determine the neighborhood of each node

Where: 

PTX and PRX are respectively the logarithmic expressions of the emitted and the received powers;



GTX and GRX are respectively the logarithmic expressions of the emitting and receiving antennas gains;



L is the logarithmic expression of the losses due to propagation of radio waves. This can be calculated using the Okumura-Hata model.

3.2

The energy consumption of a node is dependent on network events, which are determined by the node’s surroundings. One particularity of wireless networks is that the logical network does not exactly match to the physical network: data are not sent though a wire, but via radio waves, which are not directional, are evanescent, and may encounter obstacles. This creates two problems: 

communication between nodes may fail due to losses in wave propagation;



nodes may receive information not intended for them. This phenomenon is called overhearing.



N  P   i  1  P  i 0

Where: 

N is the mean number of tries that are needed to be realized to transmit a data without fail;



P is the probability to transmit the data successfully in one try.

This last term (the probability to transmit a data successfully in one try) is dependant on the physical position of both concerned nodes. It depends on their distance and on the surrounding obstacles. It can be estimated using the empirical Okumura-Hata model, which is the most widely used model for predicting radio waves propagation in urban areas.

This is taken into account in the environmental impact assessment model by listing for each node the neighbors it can hear. We consider that a node can hear a message if the signal has not been attenuated to a level below the reception sensibility of the node. The received power is calculated with a standard link budget:

i

 ni

(4)

activity i

Where: 

E is the energy consumed by the device during a considered time period;



ei is the energy consumed by the device to perform the elementary task i, it is a physical property of the node;



ni is the number of times the task i is repeated during the considered period. It is both determined by the node, its environment and the network.

More precisely, we can consider three types of tasks: 

Environment-driven tasks, which are provoked by the environment, the phenomenon monitored by the sensors. They are by nature probabilistic, as deterministic phenomenon does not need to be monitored.



Self-driven tasks, which are provoked by the node itself. They are by nature periodic.



Network-driven tasks, which are provoked by the radio signals sent by the neighborhood. They are probabilistic, as they are the combination of deterministic and probabilistic phenomenon (e.g. the number of measures sent by a sensor may be deterministic whereas the number of tries to send them is probabilistic).

3.3

Determine Le and CONe

The energy consumptions calculated will allow us to determine the missing terms of equation (1): 

CONe, for mains-driven devices: the environmental impact of energy consumption is given directly by multiplying the impacts per kWh by the quantity of energy taken from the mains.



Le, for battery-driven devices: the environmental impact is given by their lifespan. It is defined as the minimum of the lifespan of its components, including the battery, whose lifespan is calculated by the following differential equation :

Overhearing As waves do not propagate in just one direction, nodes can hear radio waves they are not intended to. Each time a message is sent between two nodes, all the nodes in the neighborhood of the sending node are awakened by the message, they have to understand they are not concerned, and then stop listening. This means that, each time a communication occurs between two nodes, some others consume a little bit of energy.

e

E

i 1

(2)

Calculate energy consumption

Wireless network nodes are simple electronic devices. They can generally perform only one task at a time. Therefore, we can consider that their energy consumption is the sum of those of the tasks they perform. Moreover, they perform only a small number of basic repetitive tasks. Their energy consumption can be considered as the sum of the consumption of the elementary tasks multiplied by the number of times they are repeated:

Communication quality Communication between two nodes may fail due to signal dispersion. Links are probabilistic. A communication must then be seen as a probabilistic series of tries. The mean number of tries for successful communication is defined as the probability to succeed at the first try, plus two times the probability to fail the first try and to succeed the second try, plus three times the probability to fail the two firsts tries and to succeed the third try, and so on. This can be expressed by equation (2), which represents the number of tries to realize in order to transmit a data without fail:

(3)

dxt       xt  dt Where: 

x(t) is the remaining energy in the battery at time t;



α is the mean consumption;



β is the battery self-discharge factor.

(5)

Life Cycle Design - Methods and Tools 4 4.1

APPLICATION IN THE EXAMPLE OF WASTE COLLECTION Waste collection service

In many cities, the glass waste collection has inefficiencies due to uncertainty on the glass levels in the containers: collector trucks have to visit each container in order to know how full it is. When trucks have to visit empty containers, time and kilometres are spent unnecessarily. This is an example in which having the information can help to reduce energy consumption.

127 

c) the reply is given to the intermediary node;



d) the reply is transmitted to the requesting node.

Each of these transmissions is realized by two-way communication between nodes. Each time a message is sent, the receiving node sends an acknowledgment. In case of transmission error, no acknowledgment is received by the requesting node, and the transmission/acknowledgment is repeated.

To do so, WSN-based service can be set up: glass containers at bring-in points in a city are provided with sensors that monitor the glass levels. The sensors are included in a wireless networks that concentrates the information on individual containers to a service platform. The collected data is used to calculate the optimal way to collect glass in the city. The simulated example

In order to show the possible results of our environmental impact assessment model, we applied it to the example of optimization for of glass waste collection. We made a simulation based on the real locations of the glass waste bring-in points in the city of Grenoble, France. We applied our model on an hypothetic WSN based on equipment provided by three industrial partners of the SensCity project [21]: BH Environment (who offers WSN urban services and produces the container’ sensors), Coronis (who designs and produces equipment for the Wavenis wireless communication protocol, particularly repeaters) and Webdyn (who designs and produces gateways for Wavenis networks). Calculations are done based on the construction of a simplified hypothetic network and LCA we performed on sensors, repeaters and gateways. We used the EIME LCA software and its database v.10 (www.codde.fr). We chose to compare two different network topologies that can be applied to the glass collection example (Figure 1): 

a four-level tree network composed of 287 sensors, 60 first level repeaters, 7 second level repeaters and one gateway;



a three-level tree network composed of 287 sensors, 60 repeaters and 7 gateways.

Sensors and repeaters are battery-driven, while gateways are plugged to the mains. The calculation is done for a 10 years exploitation period of the WSN.

Figure 2: Simplified communication protocol synopsis. 4.3

Results

Results are only presented here in terms of global warming potential. Our model provides results for other environmental indicators usually used in LCA, such as raw material depletion, energy depletion, hazardous waste production, etc, but for better clarity, these results are not shown in this paper. Moreover, in this example, results are almost equivalent for all the indicators. Figure 3 shows a comparison of the results for the two scenarios. The impacts of the deployment and dismantling stages put together are about equal for both scenarios. We call them “static impacts”, as they are frozen at the beginning of deployment of the network, and cover the entire product lifecycle, excluding use (see Table 1). The difference between the two scenarios comes from the exploitation phase, whose impacts are much higher in the case of the four-level network. The synergetic effects created by communication between nodes lead to different results between the two topologies. 8 7 6 t eq. CO2

4.2

5

Exploitation

4 Deployment Dismantling

3 2 1 0 3 Levels

4 Levels

Figure 3: Comparative results for both computed scenarios. Static impacts

Figure 1: Two computed network scenarios (a) 4-level scenario (b) 3-level scenario. Each sensor is required to make a measure every hour and to send the data through the network. We modeled a simplified communication protocol based on request/response mechanism. Figure 2 illustrates this for a three-level network: 

a) a request is sent by the top-level node to the intermediary node;



b) the request is relayed to the leaf node;

Figure 4 shows detailed results for both the deployment and dismantling stages of the network lifecycle put together. The results are roughly equal as the two deployments show only small differences: in a total number of 355 nodes, only 8 differ between the two scenarios. The most noticeable result is that sensors, due to their greater number (80% of the deployed nodes in this example), represent a large part of the environmental impact. Impacts of synergetic effects Figure 5 shows the exploitation phase impacts’ breakdown for both scenarios. It can be seen that the difference earlier noticed in exploitation phase impacts is mainly due to replacement of sensors and second level repeaters.

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Table 2 shows the details of these differences. In the three-level network, only eight sensors are replaced, while all the sensors are replaced once in the four-level network. This is due to a dramatic increase of overhearing in this last scenario. Sensors are awakened five times more often by signals they are not intended for than in the three-level scenario. Energy spent in communications remains the same in the two scenarios, but energy spent in overhearing in the four-level scenario shortens the average lifespan of sensors from 9.7 years to 6.3 years.

5

In the two previous sections, we have presented both the proposed environmental impact assessment model and its results on an application example. This model has several limits that can introduce bias in the results: 

It does not take into account what are called “collisions”: when two nodes send a message at the same time, radio signals merge together and are not decodable. Depending on the communication protocol, this may generate information losses or additional communication due to message repetition. Taking this into account would require more than an analytic model, but a real simulation model, which is out of the scope of our project. The influence of this omission is not of great importance when dealing with non flooded radio frequencies (less than ten percent of time occupation of the bandwidth), but may become critical for higher utilization rates.



It is limited to the WSN itself, and does not take into account the impacts of other equipment beyond the gateway, namely the telecommunication infrastructure, the application servers and the end-user equipments. This is a quite different research topic which will be the purpose of future publications.

6

CONCLUSION AND PERSPECTIVES

This difference is less significant for first level repeaters: they spend the most of their energy in communication, and overhearing only represents a small part of their consumption. Their lifespan is thus less affected by an increase in overhearing. While the average lifespan of sensors is shortened by more than a third, the average lifespan of the repeaters is only reduced by a tenth. This increase in the number of overhearing events is due to a higher number of communications between nodes: in the four-level network, information has to be relayed two times, and thus more radio messages are sent across the area, and nodes are awakened more often. The supplementary level in the four-level scenario is moreover at a high level, which means that it concentrates and transmits a lot of information, which overloads the network. Table 2 also shows that the second level repeaters are overloaded in terms of energy: they transmit too much information for their battery capacity, and their average lifespan drops under a year.We can derive from these results that second level repeaters may not be relevant regarding energy and environmental impacts.

LIMITATIONS

In this paper, we have presented a calculation model for assessing the environmental impacts of wireless sensor networks. This model, 5 4,5 4 t eq. CO2

3,5 Gateways Repeaters 2 Repeaters 1 Sensors

3 2,5 2 1,5 1 0,5 0 3 Levels

Figure 4: Impacts of the deployment and dismantling phases (static impacts). Replacements unit

-

Lifespan years

4 Levels

Figure 5: Detailed impacts of the exploitation phase for both scenarios (synergetic effects).

Communication

Overhearing

Energy spent in

Energy spent in

frequency

frequency

communicating

overhearing

-/day

-/day

mA.h

(%)

mA.h

(%)

3 Levels Network Sensors

180

9,7

24

1600

500

(15)

1000

(30)

Repeaters

130

4

116

2400

32100

(90)

1500

(4)

4 Levels Network Sensors

310

6,3

24

4900

500

(9)

3200

(56)

Repeaters L1

150

3,7

116

7100

32100

(84)

4500

(12)

Repeaters L2

100

0,7

1142

16000

184000

(94)

10000

(5)

Table 2: Energy consumption and lifespan of nodes from both scenarios (mean values).

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129

applied on an example, allowed us to compare two different network topologies, and conclude on their respective relevance.

speculations and evidence. Report to OECD, University of Sussex, SPRU - Science and Technology Policy Research.

Deployment of wireless sensor networks results from the choices on a high number of design parameters of different levels, and done by distributed actors. The environmental impacts can be reduced by working on both product and system levels. The aim of this model is first to help us understanding what product and system parameters have an influence on the impact of wireless sensor networks, in order to be able to provide recommendations for eco-design.

[10] Yi, L., Thomas, H.R. (2007): A review of research on the environmental impact of e-business and ICT, Environment International, Vol. 33, No. 6, pp. 841-849.

Based on this model, future research will be led in order to determine, with the help of the industrial partners of the SensCity project, design alternatives that may lead to decreased environmental impacts. This model will thus provide a basis for defining design guidelines for product and network designers. Further, this model can also be used as a test bench for networks, and be used as a design tool.

[12] Mulvihill, P.R., Milan, M.J. (2007): Subtle world: Beyond sustainability, beyond information, Futures, Vol. 39, No. 6, pp. 657-668.

Finally, further research have to be addressed in order to broaden the scope of the environmental assessment of WSN beyond the gateway, in order to include telecommunication, servers, and enduse of the services created due to WSN. 7

ACKNOWLEDGMENTS

The project SensCity is co-funded by the French Ministry of Economy. The authors want to thank the participants of the project, with the help of whom this research is led, with a special mention to Michel Courtitarat and François-Régis Meugniot (BH Environnement), Lydie Desperben (Coronis), Vincent Gimeno and Madhusudan Giyyarpuram (Orange Labs). We also would like to thank Marwane Bouznif, Susan Shrenk and Julien Darlay to have offered their technical skills to help the authors. 8

REFERENCES

[1]

Tsoukas, H. (1997): The tyranny of light: The temptations and the paradoxes of the information society, Futures, Vol. 29, No. 9, pp. 827-843.

[2]

Mathúna, C.Ó. (2008): Energy scavenging for long-term deployable wireless sensor networks, Talanta, Vol. 75, No. 3, pp. 613-623.

[3]

Nakamura, J. (2006): Analysis of the Potential Contribution of ICT Services to a Sustainable Society, in: Proceedings of the 2006 IEEE International Symposium on Electronics and the Environment, Scottsdale, AZ USA.

[4]

Akyildiz, I.F. (2002): Wireless sensor networks: a survey, Computer Networks, Vol. 38, No. 4: pp. 393-422.

[5]

Watson, B.J. (2009): Creating a sustainable IT ecosystem: Enabling next-generation urban infrastructures, IEEE International Symposium on Sustainable Systems and Technology, Tempe, AZ, USA.

[6]

Abukhader, S.M. (2008): Eco-efficiency in the era of electronic commerce - should `Eco-Effectiveness' approach be adopted, Journal of Cleaner Production, Vol. 16, No. 7, pp. 801-808.

[7]

The Climate Group - Global e-Sustainability Initiative (2008): SMART 2020: Enabling the low carbon economy in the information age.

[8]

Erkman, S. (2004) : Vers une écologie industrielle, Mayer Charles Leopold Eds.

[9]

Berkhout, F., Hertin, J. (2001): Impacts of information and communication technologies on environmental sustainability -

[11] Loerincik, Y. (2006): Environmental impacts and benefits of information and communication technology infrastructure and services, using process and input-output life cycle assessment, École polytechnique fédérale de Lausanne.

[13] Williams, E. (2002): The 1.7 kilogram microchip: Energy and material use in the production of semiconductor devices, Environmental science & technology, Vol. 36, No. 24, pp. 5504-5510. [14] Köhler, A., Erdmann, L. (2004) Expected Environmental Impacts of Pervasive Computing, Human & Ecological Risk Assessment, Vol. 10, No. 5, pp. 831-852. [15] Beucker, S., Clausen, J., Schischke K. (2008): Wireless Sensor Networks for Agriculture and Automation: Challenges and Chances for Sustainability, Electronics Goes Green 2008+, Fraunhofer IZM, Berlin, Germany. [16] Dubberley, M., Agogino, A.M., Horvath, A. (2004): Life-cycle assessment of an intelligent lighting system using a distributed wireless mote network, in: Conference record of the 2004 IEEE International Symposium on Electronics and the Environment, Scottsdale, AZ, USA. [17] Hoang, T. (2010): Environmental evaluation of machine-tomachine services: the case of kerbside collection of glass waste, CIRP IPS2 Conference, Linköping, Sweden. [18] Bouzin, E. (2008) : Analyse de Cycle de Vie comparative: relève manuelle et télérelève de compteurs d'eau. CityPulse Project, Agro Paris Tech, Orange Labs. [19] Suri, A., Iyengar, S.S., Cho, E. (2006): Ecoinformatics using wireless sensor networks: An overview, Ecological Informatics, Vol. 1, No. 3, pp. 287-293. [20] Rebitzer, G. (2004): Life cycle assessment: Part 1: Framework, goal and scope definition, inventory analysis, and applications, Environment International, Vol. 30, No. 5, pp. 701-720. [21] Lelah, A. (2010): SensCity: a new project opening the way for sustainable services in the city based on a mutualised M2M infrastructure, CIRP IPS2 Conference, Linköping, Sweden.

9

CONTACT

Jérémy Bonvoisin G-SCOP Laboratory [email protected]

Considering the Social Dimension in Environmental Design 1

Berenice Dreux-Gerphagnon , Nizar Haoues 1

2

Université Lyon 3 Faculté de Philosophie, Ecole Nationale Supérieure des Mines de Saint-Etienne, France ² Eco-design Center and Life Cycle Management, France

Abstract Designers are facing a new challenge: the integration of all the sustainable development dimensions in the product design. We can find tools and methods taking into account the environmental, economic and technical aspects in product design, but the social dimension is not yet considered enough. However, the integration of social aspects is more and more seen, by institutional and industrials actors, as the future of a responsible design. In this paper we propose a new method so as to associate the social dimension and the rational framework it implies to the technical rationality which prevails in tools for EcoDesign and Life Cycle Assessment. Keywords: Product Design; Sustainable Development Dimensions; Product Life Cycle

1

INTRODUCTION

The recognition of the environment in product design is a first step towards a responsible design. However, this first march, though necessary, is not sufficient to make possible a product design which complies with the different standards of sustainable development. Traditionally the organisation considers, in the specifications of a product, technical and economical measures. For about ten years tools serving for an approach of EcoDesign have been developed and improved. Although, how about the social dimension? How can we assess the impacts of an organisation on its different stakeholders, whether it be the employees, the consumers or the supply chain actors? Whereas the ecological dimension can be estimated with quantitative measurement that can be sometimes used regardless of the context, which corresponds to an analytic rationality, the relation of the organisation with its various stakeholders, especially with the different actors of the life cycle of a product, can not be assessed every time with the same measurement. Rather than imposing international social standards, isn’t it necessary to create the conditions of a dialogue between international texts universally oriented and the various social and cultural environments of the life cycle actors of a product? The challenge of a methodology of eco-socio-design is thus neither to avoid reducing the social dimension to a strictly analytic approach nor to deal with this dimension as a horizon which can not be assessed in a scientific way. We could, on the contrary, keep at the same time an analytic and a more comprehensive or subjective approach. And we make the hypothesis that it is by relying on a complex rationality or rationality of the activities [1] which transcends the division of the two approaches that we will manage to connect the different dimensions of sustainability in a methodology for product design. 2

BACKGROUND

In order to meet sustainable development demands as they are formulated in the Brundtland report it is necessary to consider, as

well as environmental and economic aspects, the social dimension. The Brundtland report defines sustainable development as ”a development that meets the needs of the present without compromising the ability of future generations to meet their own needs” [2]. But how can we adapt such a concept to a product design methodology? Indeed as Labuschagne et al. write it: “although the concept is understood intuitively it remains difficult to express in concrete operational terms” [3]. Over the past decades the environmental aspects has been more emphasized, considering the whole life cycle, than the social ones. Following on from the Club of Rome concerns focus has mainly been on the quantitative assessment of the environmental impacts: emissions from the product system, consumption of energy and other resources [4]. A Life Cycle Assessment methodology has been developed in accordance with the ISO 14040 and ISO 14044 standards. This methodology aims to translate the type of consumption and the emission into their potential impacts on the environment [4]. But it is with the tools and methods for EcoDesign that industries can get the opportunities not only to assess the impacts of their products but also to make the right choices in order to innovate by integrating the environmental aspects, as well as the technical and economic ones. Considering these different aspects allows the industries to increase their eco-efficiency. As we can understand it, through the Figure 1, eco-efficiency is located at the intersection of the environmental and the economic dimension. Fair trade products are, on their side, designed with an attention given to the economic and social aspects at the level of the production stage. However, in order to contribute to the improvement of the living conditions at local scale and worldwide, in the present and for the future generations, it is necessary to consider, in product assessment and product design, environmental and social standards simultaneously all along the life cycle of the product. As such the objectives are, on the one hand to develop methodologies that would offer the opportunities to assess the

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_23, © Springer-Verlag Berlin Heidelberg 2011

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three dimensions of sustainability, on the other hand to create tools that would help to take into account these three dimensions in a changing competitive context.

Eco-efficiency Environment

The Table 1 below indicates for each phase identified for conducting a LCA the general description and the social specificities. The conditions required for Social LCA (S-LCA) are mentioned by the Guidelines [6] but we can add, in the goal and scope phase, a questioning about the ethical acceptability of the product. This deals with the question of knowing whether a product should be produced or not. 3.2

Main issues of the integration of the social dimension

This second chapter of the third part deals with the description of the social dimension specificities related to the ISO standards. Lake of methods and tools

Goal and scope

Economic Fair trade

Social

It is necessary, at this level, to identify the various stakeholders of the organization which wants to assess one of its products. These stakeholders can be verticals: the actors of the life cycle and those who are particularly affected or affecting the functioning of these actors. They also can be horizontals. The horizontal stakeholders include for example the employees of the organization, the local communities, the shareholders or the authorities. The identification of the stakeholders will help to determine the boundaries of the study. See the Figure 2 next to the text.

Figure 1: The need to connect environment and social in product assessment and design. 3 3.1

Vertical   stakeholders

METHODOLOGY

Actors of the   life cycle

A Social Life Cycle Assessment

The thinking about the integration of the social dimension in Life Cycle Assessment (LCA) has begun with the creation of a task group inside the Life Cycle Initiative (LCI), an initiative from the United Nations Environment Program (UNEP) and the Society of Environmental Toxicology and Chemistry (SETAC). Since 2004 ten meetings of this task group have taken place and a feasibility study about the integration of social aspects into LCA have been conducted [5]. This has led to the publication of the Guidelines for Social Life Cycle Assessment of Products [6] in June 2009. By referring to this document we get the opportunity to consider the social dimension through the four phases identified by the ISO 14040 and ISO 14044. This will help us to define the specificities of the assessment of the social aspects.

Horizontal   stakeholders

  Entrepriser

Actors of the   life cycle Figure 2: The different types of stakeholders.

PHASES FOR LCA

GENERAL DESCRIPTION

SOCIAL SPECIFICITIES

Goal and scope

Boundaries of the product system

Ethical Acceptability

Functional unit

Function (not necessarily functional unit) Identification of the stakeholders

Life Cycle Inventory

Inventory indicators Data collection

Identification of social hotspots Global issues

Life Cycle Impact Assessment

Selection of impacts categories Characterization models Normalization

Interpretation

Horizontal   stakeholders

Subcategories Characterization: scoring system based on performance reference points

Valuation

The knowledge of the stakeholder is helpful

Identification of the significant issues

Level of engagement with stakeholders

Recommendations Table 1: Integration of the social dimension in LCA.

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If the data collected cannot be expressed in terms of quantity there is no way to define a functional unit. However we need to determine the function of the product, its social role. This rule can be socially beneficial or harmful, or it can be both of them, depending on the use. Let us take the example of a technical object: the television. On the one hand it can be a means of being informed about what happens in the world, on the other hand one can be exposed to isolation and manipulation with this object.

for and of the treatment of the people resettled. Privileging in most of cases qualitative indicators, combining qualitative and quantitative indicators does not allow realizing a characterization model in S-LCA similar to the type of characterization model which prevails in LCA. S-LCA characterization models are not an objective multiplication between data collected and a characterization factor. They above all consist in scoring system based on performance reference points.

Life Cycle Inventory

Characterization models need to be established depending on the sectors and contexts. The normalization is not possible yet because no software or tools are available to organize the information according to data basis and characterization models which would already exist.

Identifying the stakeholders leads to take into account the various contexts where they are located. Indeed, when considering the social dimension, information about economy, culture, regulations, level of technological development can be required. One could say that Social Life Cycle Assessment has an interest to the environment, not from a physical point of view but as long as human being has a cultural, technological and economical relationship to this environment. This relationship is called “ecoumene” by Augustin Berque [7]. Considering the social dimension in environmental assessment leads to a more comprehensive understanding of the environment. But to obtain a social assessment in which the uncertainty will be reduced as far as possible one needs to consider, as well as the local contexts of the stakeholders, the global issues or the main issues of the part of the world where some of the actors of the life cycle are located. To illustrate this point we can take the example of some European merchants who call on producers of handmade carpets in Afghanistan. Most of these producers are employing children. A NGO which is settled in this country has negotiated with the producers so that they make work the children only in the morning. On the afternoon some lessons are organized for them. Considering the global context leads to questions like this: is it socially and environmentally desirable that some carpets produced in Afghanistan be sailed in Europe? Does the wool come from Afghanistan? Is it a local know-how? Does the handmade carpet contributes to the economical and social development of the country or does it represent a marginal activity? If it doesn’t, a socially beneficial choice could be to give training for the children in the sector which represents the future of the country. Life Cycle Impact Assessment Depending on the sector studied and on the contexts where the life cycle actors are located the stakes will be different. Identifying the main stakeholder, verticals and horizontals, of the organization and the social hotspots is necessary to determine the stakes. The social hotspots are considered as problems, risks or opportunities in relation to social themes of interest such as human rights, work conditions, poverty and so on [6]. These social themes are drawn on in the subcategories. Those are classified according to stakeholders and impacts categories. The Life Cycle Initiative proposes a methodological sheet for each one of the thirty-one subcategories. A methodological sheet contains a definition of the subcategory and it presents a list of generics and specifics indicators. The generics indicators are relying on data that are indicated on national or international organisms websites whereas the specific indicators require interviews carried out among stakeholders. We need though to identify the subcategories that will be relevant to sector studied and to chose some indicators related to the subcategories. Most of the indicators are qualitative or semi-quantitative. When assessing the social impacts one could not try to replace a qualitative indicator by a quantitative or more objective one. This would introduce more uncertainty in the assessment. For example, if we take the subcategory “Delocalization and Migration” we cannot satisfy ourselves with a quantitative specific indicator as the number of people who resettle that can be attributed to the organization. We mostly need to know the description of the causes

The valuation step is regarded as a step which introduces a great amount of uncertainty in the study because the different points of view of the stakeholders are taken into account. These points of view are favoring some parts of the study in a subjective way. But, precisely, the fact of identifying the stakeholders and their points of view from the beginning of the assessment isn’t it a good means to reduce uncertainty? Interpretation Considering the level of engagement with stakeholders allows entering in an iterative process. The responsibility of the organization towards its stakeholders is better identified at the end of the study. 4

PROPOSITION OF A METHOD AND A TOOL

We have indicated, in the precedent part, the specificities of the assessment of the social dimension. This dimension introduces more subjectivity in the assessment but it helps to understand the complexity of reality. Integrating the social aspects to the LCA does not lead to confusion or to a less scientific approach. On the opposite it allows to associate, to an analytic rationality, a more comprehensive one. This is what Paul Ricœur calls the dialectic of the interpretation [8]; it offers a better understanding of the reality. The local and global contexts are taken into account in order to identify the stakes of the sector. The point of view of the stakeholders, once identified, are some more manageable parameters. Hence one has the opportunity to get information on which relying to make a right choice. It is precisely about not only the assessment but also the product design considering the environmental and social dimensions in the whole life cycle that it can be interesting to develop a method et a tool: this is what we can call Eco Socio Design. 4.1

The existing tools

In order to develop a method for Eco Socio Design we need to lean, as it has been explained before, upon the Guidelines for Social Life Cycle Assessment of Products. But the different elements of assessment proposed in the Guidelines are not sufficient to integrate the social dimension to the Eco Design tools and methods. Furthermore, as we have already mentioned it, they do not discuss of the ethical acceptance of a product. But they propose a good basis for the creation of social indicators through the subcategories list. Each subcategory can be assessed thanks to generic and specific indicators presented by the Life Cycle Initiative. The list of indicators hence obtained can be enhanced by the fields of actions of the ISO 26000 standard on social responsibility [9]. This standard has a site specific approach but it is interesting to cross its fields of actions with the indicators of the Life Cycle Initiative and so to organize them according to a life cycle perspective. We will finally rely on the SD 21000 guide for sustainable development and social responsibility [10] which is required so as to identify and to prioritize the stakes of the organization and, as far as

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Eco Socio Design is concerned, of the whole life cycle. The consideration of the stakes hence identified and prioritized can be assessed in a qualitative way and recommendations can be made in order to improve this consideration, given the goals of sustainable development. 4.2

The approach

We can imitate the different step of the method we want to propose.

Stakeholders identification Environmental stakes

level, the extraction of one kilogram of aluminum can be estimated in CO2 equivalent according to an energetic mix regardless of the context, which is peculiar to technical rationality, this operation requires various different indicators so as its social impact could be correctly assessed. The practical rationality implies that one knows the economic, cultural and technical context of its interlocutor. Understanding the realities which are under the words allows them to get a language shared in an intersubjective way which differs from the abstract language of the technical rationality [11]. Hence the rational framework of the environmental approach finds itself enhanced by the rational framework to the social approach. Realizing a checklist

Dialogue with stakeholders

Social stakes

Representing the impacts and the positive externalities

Reduction of the impacts Checklist Ex: toxicity, health at work…

Production of externalities

The main subcategories and their indicators once chosen, the next step consists in establishing a checklist which will contain two parts. One of these parts will bear upon the environmental aspects and the other upon the social ones. This checklist could gather the social indicators and some environmental indicators so as to present the trouble spots and the potential segment of growth.

positive

Figure 3: The Eco Socio Design steps. Crossing the life cycle and stakeholder approach In a first time, we need to describe the various different phases of the life cycle of a product. For each one of these phases we could identify the actors and their main stakeholders. We hence obtain a figure representing the vertical stakeholders of the life cycle of the product and the horizontal stakeholders who are the stakeholders of each actors of the life cycle. Identifying the main stakes In order to determine these stakes one needs to get information about the local contexts of the actors of the life cycle and about the main issues of the part of the world where they are located. Knowing the sector and having identified the stakeholders help to determine the social hotspots. This knowledge will give a first basis to prioritize some subcategories. Each subcategory can be assessed with at least seven indicators. By having crossed the fields of action of the ISO 26000 standards and the indicators proposed by the Life Cycle Initiative we have obtained a list of three hundred and forty-nine indicators. It is then essential to prioritize some subcategories. This will allow us to concentrate on a reduced number of indicators which will be more adapted to the challenges of the sector. Dialoguing with the stakeholders So as to take into account the social dimension and to reduce the uncertainty of the results it seems essential to establish the conditions of a dialogue with the stakeholders through a collaborative platform. This will allows the actors of the life cycle of the product and, as far as possible, their stakeholders to discuss about the choice of the subcategories and about the way they would answer to the questions asked by the qualitative indicators. The dialogue aspect is fundamental in order to understand the social dimension. This dimension belongs to what Habermas could call the practical rationality [11]. Whereas, at the environmental

The results of the checklist can be presented in different types of figures but what is really important is that the figure could show not only the impact or reduced impacts but also the positive externalities. There is positive externality when the activity of an organization has positive effects on groups or individuals who are not implied by this activity, without these groups or individuals need to pay for the benefices received. For example if a firm is settling in an economically disaster town that can contributes to the development and to the reinforcement of the town’s economy, that can helps to the immigration of new workers and to the improvement of the local employment. As the town will have a less strong emigration rate perhaps the town council will decide to renovate schools and to enhance the transport infrastructures. These two actions can be seen as positive externalities. EcoDesign is supposed to offer a help to improve the use value of the product in terms of length, diversity of functions and efficacity while giving recommendations to reduce the impacts on the environment. U Use value of a product

Improvement of the use value  

Positive externalities  

 

Impacts on the stakeholders I

Reduction of the impact on the stakeholders  

Figure 4: The production of positive externalities. Eco Socio Design, as the Figure 4 above shows it, is also supposed to allow an improvement of the use value of the product not only while reducing the impacts on the stakeholders, but also while producing positive externalities. Not having impact is the goal of the environmental approach but environmental positive externalities can exist as well, like the CO2 uptake in the growth of plants [6].

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Life Cycle Design - Methods and Tools CASE STUDY

After having proposed a method we would like to apply it to a product: a snack pocket for children which can be used to contain the packaging wastes. We have identified, in a first time, the different actors of the life cycle of the snack pocket. See the Figure 5 below. From the cultivation to the distribution we need to consider the employees and the working conditions, the local communities, the authorities and the economic partners. As many chosen indicators will be qualitative, especially at the level of the use, it seems difficult to find a functional unit. We can only define one or more functions for the product. Indeed the children will appropriate the pocket. Some of them will put inside the snack prepared by their parents, other will tide their industrial snack in it and use the little bin pocket to put the packaging wastes. The function of this product is to contain the snack and to collect the packaging wastes of the snack. The social role, especially if the pocket is distributed to children by the local authority through the intermediary of schools, is to increase children and parents awareness of some issues. These issues are the fact of throwing wastes in a bin, even a portable bin in this case, the waste sorting, the fact of preparing a snack to the child instead of giving him an industrial snack and the possibility of keeping the object which contains the snack and to reuse it.

Raw materials Cultivation and spinning Transport

Cotton Certified Ecocert

Hemp

+

Certified Bio IMO control China (Mongolie)

Benin

scop Boat

Boat

Weaving

public awareness of the waste sorting or even the type of substances used for the printing of the pockets. The raised points can be related to social or environmental concerns or to both of them. Concerning the social aspect we can then prioritize subcategories such as the local employment, the contribution to economic development or even the end of life responsibility related to the consumer or user stakeholders. This third subcategory is at the junction of social and environmental concerns. We will then dispose of a few questions concerning the social and the environmental aspects, questions which will include quantitative, qualitative, generic and specific indicators. For example: is the part of the product made in France contributes to the local economic development? We need generic indicators like the economical situation of the sector or the interest of the sector for the (local) economy and some specific indicators such as the contribution of the product to the economical development of the French organizations considered and the support of these organizations to the emergence of local enterprisers. We can also wonder if one of the steps of the life cycle of the product executed in France such as silkscreen uses toxic substances for the environment or organic substances and less energy-greedy processes. From the chosen questions the organization will be able to elaborate a strategy in order to communicate on its actions or to improve these mains fields of action which are raised by the analysis of the life cycle steps, by the identification of the stakeholders and by a phase of dialogue. The following figure (Figure 6) helps to understand that the product’s role is to contribute to the reduction of the impacts of the waste packaging. The impacts can be reduced at the level of the other steps of the life cycle of the product with regard, notably, to the substances used. The value of use of this packaging made of cotton and hemp is improved because this object can have at least two functions: carrying the snack and collecting the snack wastes. It contributes as well to the production of positive externalities at the level of the textile sector in the Loire department.

France (Roanne) scop

Fashioning

France (Roanne) Asset stripping

Silkscreen

U Use value of a product

France (St Etienne)

Improvement of the use value  

Artist from a scop Sale and monitoring Distributors

 

France (St Etienne)

 

Artist Designer Shops

Local authorities

Impacts I

Users End of life

Improvement of the economic situation of the textile sector in Loire department.

Children Rag

Figure 5: The life cycle and the different stakeholders of the pocket. So as to improve transparency between the actors of the life cycle of the product and the stakeholders it is important to organize a task group on a collaborative platform. This will help to choose the most appropriate indicators. The main stakes brought to light by such a task group can eventually be the questions of the working conditions in China and in Benin, the economic development of a disaster sector in a region of France, the increase of the

Reduction of the waste packaging impacts  

Figure 6: Example of the representation of a positive externality in the life cycle of the pocket. An Eco Socio Design method allows the organization to invent a strategy which aims to improve the social role and the functions of the product by reducing the environmental and social impacts but also by creating positive externalities all along the life cycle of the product. With such a method the organization gets the portray of the steps, actors and stakeholders of the life cycle of its product and it can chose to communicate on one of these points or to improve some of them.

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CONCLUSION

If innovation can be defined as “establishing new combinations” [12] we can conclude, with Seliger, G. [13] that the fact of associating different fields can enhance innovation potentials in cross disciplinary cooperation. Associating environmental, social and economic concerns opens more potentialities for innovation. We could then design a last figure (Figure 7), not only for Eco Socio Design but also for the Eco Socio Innovation.

Perspectives, Technology.

-Technological performance

-Reduction of

Innovation

the emissions

- Marketing

the social role

Figure 7: The Eco Socio Innovation. Indeed, the integration of the social dimension brings a strong potential of creativity and it helps to establish a link between engineer sciences and social sciences. If we really want to take into account the social dimension and to integrate it into the EcoDesign tools we need to localize ones approaches in a the framework of a complex rationality. According to Edgar Morin complex rationality implies a dialogic principle [14]. This principle designates the interaction between different logics and concerns as the environmental, the social, the technological and the economic ones. Furthermore the knowledge of the contexts, of the sectors and of the main issues requires a more practical rationality and a more comprehensive perspective which can help to identify the potential segment of change and improvement. 7

ACKNOWLEDGMENTS

We extend our sincere thanks to the members of the Eco-Design Center, of the CIRIDD, of the Université Lyon 3 and of the Ecole des Mines de Saint-Etienne who are helping us in the development of our reflections and methods. 8

REFERENCES

[1]

Pierron, J.-P., (2009): Penser le développement durable, ellipses, Paris.

[2]

Brundtland, G., (1987): Our common future: the world commission on environment and development, Oxford University Press, Oxford.

[3]

Labuschagne, C.; Brent, A. C. (2008): An industry perspective of the completeness and relevance of a social assessment framework for project and technology management in the manufacturing sector, in: Journal of the Cleaner Production 16, pp. 253-262.

[4]

Hauschild, M.; Jeswiet, J.; Alting, L. (2005): From Life Cycle Assessment to Sustainable Production: Status and

CIRP,

Manufacturing

PNUE; SETAC; LCI (2009): Guidelines for Social Life Cycle Assessment of Products.

[7]

Berque, A. (1987): Ecoumène, Introduction à l’étude des milieux humains, Belin.

[8]

Ricœur, P. (1986) : Du texte à l’action, d’herméneutique, II, Editions du Seuil, Paris.

Essais

[9]

ISO (2010) : ISO 26000, Guidance on social responsibility.

[10]

AFNOR (2003) : Guide SD 21000, Développement durable – Responsabilité sociétale des entreprises – Guide pour la prise en compte des enjeux du développement durable dans la stratégie et le management de l’entreprise, FDX30-021.

[11]

Habermas, J. (1968), La technique et la science comme « idéologie », Editions Gallimard, 1973, translated from German to French by Jean-René Ladmiral.

[12]

Schumpeter, J., A. (1912), La théorie de l’évolution économique, translated from German to French by J. J. Ansttet.

[13]

Seliger, G. (2001), Product Innovation – Industrial Approach, in: Annals of the CIRP, Manufacturing Technology.

[14]

Morin, E. (2005), Introduction à la pensée complexe, Editions du Seuil.

approach

-Questioning on

the

[6]

the energy

-Stakeholders

of

Rainer, G.; Benoît, C.; Dreyer, L. C.; Flysiö A.; Manhart A.; Mazjin B.; Méthot A.-L.; Weidema B. (2006): Feasability Study: Integration of social aspects into LCA, Öko-Institut, Freiburg.

-Better use of Social:

Annals

[5]

Environmental:

Economic:

in:

Proposal of an Ecodesign Maturity Model: supporting Companies to improve Environmental Sustainability 1

Daniela C. A. Pigosso , Henrique Rozenfeld

1

Department of Production Engineering, University of São Paulo, São Carlos, Brazil

Abstract Ecodesign is a strategic design activity for conceiving and developing sustainable solutions. The implementation of ecodesign in product lifecycle management (PLM) is still a challenge today because companies find it very difficult to determine which practices are the most suitable for their reality, drivers and current maturity level. This paper presents an Ecodesign Maturity Model that aims to support the application of ecodesign practices in PLM, improving the environmental performance of products. The model comprises three elements: Ecodesign Maturity Levels, Ecodesign Practices, and Application Method. Keywords: Ecodesign Maturity Model; Ecodesign Practices; Product Development Process

1

INTRODUCTION

Ecodesign can be defined as a proactive approach to environmental management which involves the inclusion of environmental issues in product life cycle management (PLM) in order to minimize environmental impacts during the product’s life cycle (from material extraction to end-of-life), without compromising other essential criteria such as performance, functionality, esthetics, quality and cost [1] [2]. The application of Ecodesign practices is essential to companies that recognize the importance of environmental responsibility for long term success, since it enhances their reputation, reduces their cost and risks, leads to product innovation and attracts new consumers [3]. However, companies are still unsure about the strategies, guidelines and methods/tools they should adopt and about how to manage the process of integration in the product development process and of continuous improvement. In this sense, it can be argued that the application of ecodesign has not reached companies worldwide over the last decade mainly due to the following factors:

companies effectively implement ecodesign in their product development processes. Such a model should be based on the systematization of existing ecodesign practices, linking them to the company’s development process and strategy and providing guidelines on how to implement them according to the company’s maturity level. In this context, the main goal of this paper is to present the development of an Ecodesign Maturity Model, which aims to guide companies in the effective implementation of ecodesign practices in their product life cycle management in line with their strategic objectives and drivers. The next section presents the methodology used in the development of the Ecodesign Maturity Model. The model is detailed in Section 3, which describes the goal and the elements of the Ecodesign Maturity Model, i.e., Ecodesign Practices, Ecodesign Maturity Levels and Application Method. The Summary and Outlook, Acknowledgments and References are presented in sections 4, 5 and 6, respectively.

(1) Existing ecodesign practices are not systematized;

2

(2) There is intense development of new ecodesign methods and tools in detriment to the study and improvement of existing ones [4];

The Ecodesign Maturity Model was developed based on the following activities:

(3) There is a lack of integration between ecodesign and the broad context of the product development process and product life cycle management [5][6][7][8];

The ecodesign practices were obtained and classified based on a systematic review of the literature, enabling the researcher to map the existing knowledge and initiatives developed in a specific area of research. In addition to the analysis of previous discovery, techniques, ideas and ways to explore topics, the systematic review also allows for an evaluation of the relevance of the information to the issue, its synthesis and summarization [9] [10].

(4) Ecodesign is poorly integrated into corporate strategy and management [4]; (5) No roadmap for continuous improvement is available for companies that want to implement ecodesign; (6) Companies usually fail to adopt ecodesign because the selection of practices is not in line with their current maturity level. Consequently, there is a need to propose models that help

2.1

METHODOLOGY

Systematization of Ecodesign Practices

The ecodesign practices identified in the systematic literature review were divided into three groups: Ecodesign Management Practices, Ecodesign Operational Practices and Ecodesign Methods and Tools. The description of these practices is presented in section 3.2: Ecodesign Practices.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_24, © Springer-Verlag Berlin Heidelberg 2011

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137

Establishment of Ecodesign Maturity Levels

Structured collection of practices classified according to the Maturity Levels

To ascertain maturity levels in ecodesign, a review was made to understand the evolution of companies in adopting Ecodesign and the dimensions that influence this evolution. The most appropriate practices for each maturity level were analyzed and the correlation and dependencies between practices were also determined. The maturity levels defined in the Ecodesign Maturity Model are presented in section 3.3. 2.3

Ecodesign Practices

Development of the Application Method

An Application Method was developed to determine how a company can apply the Ecodesign Maturity Model, based on the literature about business process management (BPM), which provides guidelines for process improvement. This Application Method is presented in section 3.1. 3

Sequence for developing maturity in Ecodesign

Application Method

ECODESIGN MATURITY MODEL

The Ecodesign Maturity Model is a conceptual framework composed of a structured collection of ecodesign practices that can be used to develop and improve an organization's product life cycle management (PLM) in terms of environmental issues. The model provides: 

a benchmark in ecodesign best practices;



an assessment of strengths and weaknesses in the application of ecodesign practices;



a common language and a shared vision across the organization;



a guide for integrating ecodesign practices into PLM; and



a roadmap for PLM improvement towards environmental sustainability.

The goal of the Ecodesign Maturity Model (EcoM2) is to guide companies in the effective implementation of ecodesign practices in product life cycle management (PLM) and the related process in accordance with their strategic objectives and drivers. The Ecodesign Maturity Model is composed of three main elements (Figure 1): 

Application method: explains how companies can use the model for process improvement. It contains a scheme for continuous improvement (such as PDCA – plan, cycle) based on the Business Process Management (BPM) approach.



Ecodesign practices: these are the best practices currently adopted by companies and developed by universities for the integration of environmental concerns into the product development process. These practices comprise management practices (involving the management of ecodesign), operational practices (related to technical design issues) and ecodesign methods and tools which support the application of management and operational practices.



Maturity levels: indicate the company’s level of evolution in including environmental issues in their business processes.

The elements of the Ecodesign Maturity Model are detailed in sections 3.1, 3.2 and 3.3. 3.1

Ecodesign Application Method

The Ecodesign Maturity Model Application Method (Figure 2) was developed based on the BPM (Business Process Management) approach for process improvement. Its purpose is to guide the application of the Ecodesign Maturity Model. This method comprises six steps.

Maturity Levels

How to use the model, evaluate the maturity, select and apply the improvement projects

Figure 1: Elements of the Ecodesign Maturity Model. 

Diagnosis of the current Maturity Level: the first step is to assess the current situation of an organization in terms of its attention to environmental issues. This assessment involves a diagnosis of the company’s current maturity level based on the Ecodesign Management Practices it applies and at which capability level (see section 3.3).



Proposition of Ecodesign Management Practices to be implemented: once the current Maturity Level is determined, the most suitable practices for the company to adopt are proposed according to its maturity level (first filter of the practices), as well as the strategic drivers for the adoption of ecodesign (which include environmental laws and regulations, cost reductions, consumer environmental awareness, new business opportunities, value creation and opportunities for innovation).



Selection of practices to be implemented: the company then selects Ecodesign Management Practices following the weighting method for ecodesign practices developed by Charter and Tischner [13], which classifies these practices into the following groups: 

Rejected 0: the option is rejected; moreover, it holds no future interest for the company.



Of interest 1: the option is studied in greater depth but its implementation is still rejected; 2: the option has not yet been studied, but the company’s future interest in it is ensured. 3: the option is under study and its implementation is still uncertain.

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Continuous Improvement

Performance Measurement

People Change Management

Diagnosis of the current maturity level

Assessment of the results

Proposition of practices to be implemented

Selection of practices to be implemented

Implementation of improvement projects

Planning of improvement projects: scope, resources, schedule, responsibilities, etc.

Assessment of the application of ecodesign practices

Definition of improvement projects

Maturity Level Drivers

Management, operational and methods/tools

Portfolio management of improvement projects

Figure 2: Ecodesign Maturity Model Application Method. 

Prioritized

3.2

4: the option has been implemented; its realization is expected within three years;

Ecodesign practice is the generic name for ecodesign activities, strategies, methods and tools, etc. aimed at integrating environmental issues into the product development process. The Ecodesign Maturity Model divides ecodesign practices into the following three groups:

5: the option has been implemented; its realization is expected within one year; 6: the option has been implemented or will be implemented very soon (the option is effectuated). 



Ecodesign Management Practices: related to the management activities and tasks of the product development process that address environmental issues. These practices serve to evaluate the maturity levels of companies in applying ecodesign. The 75 Ecodesign Management Practices identified are classified according to the maturity levels (see section 3.3) and to the phases of the reference model for product development [11] (strategic product planning, project planning, informational design, conceptual design, detailed design, production preparation, product launch, product monitoring and product takeback). The application of ecodesign management practices can be supported by Operational Practices and/or by Ecodesign Methods and Tools.



Ecodesign Operational Practices: This is a compendium of ecodesign guidelines for product design containing more than 480 identified and systematized practices. This compilation is divided into three levels of detail: ecodesign strategies (minimize energy consumption, minimize material consumption, extend material lifetime, optimize product lifetime, select low impact resources and processes, and facilitate disassembly – adapted from [12]), ecodesign guidelines (which provide detailed ecodesign strategies), and design options (to support the creation of solutions to meet the guidelines). Ecodesign Operational Practices involve the technical issues of product design and are linked to Ecodesign Management Practices. The guidelines can also be applied by using the Ecodesign Methods and Tools.



Ecodesign Methods and Tools: a systematic means to apply ecodesign that can support the application of both Ecodesign Management and Operational Practices. Based on a systematic review of the literature, more than 100 ecodesign methods and tools were identified and classified into six criteria to support the selection of the most suitable ones for companies according to their needs and current maturity level: (1) Nature of the main goal of the method/tool (Prescriptive/ Comparative/Analytical); (2) Type of the tool used (Checklist/ Guideline/Matrix/Software);

Not considered 7: the option has not received special attention because it is considered a bottom-line matter in product development and is therefore of ongoing interest to the company; 8: the option has not been studied because it is considered irrelevant.

The information about the classification of the company’s practices will be applied in the subsequent process improvement cycles. For example, if a practice is rejected in a given cycle, it will not be proposed for application in the subsequent cycles. 

Definition of improvement projects: after defining the prioritized Ecodesign Management Practices to be applied by the company, an analysis is made of the correlation between the selected Ecodesign Management Practices within the Ecodesign Operational Practices and the Ecodesign Methods and Tools (see section 3.2). The company’s improvement projects should include a set of Ecodesign Management Practices, Operational Practices, and Methods and Tools to support the application of Ecodesign Management Practices. A portfolio management of these improvement projects should be set up, as well as project planning to define schedules, responsibilities, resources, etc.



Implementation of improvement projects: during the implementation of the ecodesign practices selected for improvement projects, special care should focus on People Change Management, since people are crucial to the process.



Assessment of the results: performance indicators for the practices must be determined in order to evaluate the results of the improvement projects.

The improvement cycle can be repeated as many times as necessary for the company to maintain its continuous improvement towards higher maturity levels in Ecodesign.

Ecodesign Practices

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(3) Nature of input and output data (Qualitative/Quantitative); (4) Considered Product Life Cycle Phases (Raw material extraction, manufacturing, use, end-of-life), (5) Evolution of the application (Theoretical/Experimental/ Consolidated); (6) Evaluation of Environmental Impacts (Yes/No). The classification criteria used in the Ecodesign Maturity Model are presented in detail in this paper [13]. The Ecodesign methods and tools can support the application of ecodesign management and operational practices. The practices are organized on a spreadsheet containing all the information displayed together in an interrelated way. For a broader view of the interrelationships among Ecodesign Management Practices, Ecodesign Operational Practices and Ecodesign Methods and Tools, an example is presented in Figure 3. One of the Ecodesign Management Practices is “20001: Assess the environmental impact of products.” Numerous ecodesign methods and tools can be used to support the application of this management practice, e.g., Life Cycle Assessment (LCA) [14][15][16][17], MET (Material, Energy and Toxicity) matrix [18][19], MECO (Material, Energy, Chemicals and Others) matrix [20][21], etc. The most suitable ecodesign method/tool can be determined based on a selection according to the company’s needs, current maturity level and the method classification criteria [11]. The 20001 practice is also a prerequisite for the application of the “80001 practice: Analyze and select the most suitable ecodesign strategies according to the environmental goals and phases/environmental aspects of the product life cycle that offer the greatest opportunities for environmental improvement,” since these opportunities underpin the identification of the environmental hot spots of the product under analysis. Ecodesign operational practices must be analyzed in order to select the most suitable ecodesign strategies. For example, if the hot spot occurs at the product’s end-of-life, thus involving its disposal, the “Facilitating Disassembly” and “Product Lifetime Optimization” strategies are probably the most suitable. Based on “Product Lifetime Optimization” and an evaluation of its guidelines, it can be concluded that “Facilitating Remanufacturing” is of higher importance. The application of this guideline is also supported by a set of ecodesign methods and tools such as EDIT (Environmental Industrial Template) [22], ELDA (End-of-Life Advisor) [23] and LCP (Life Cycle Planning) [24]. 3.3

Ecodesign Maturity Levels

The Ecodesign Maturity Model is composed of five maturity levels that represent the evolution from an absence of awareness of and

consideration for environmental issues to the integration of environmental concern into the company’s strategic planning and decision-making process. The Ecodesign Maturity Model indicates the steps a company should take to improve the environmental performance of its processes and products. The maturity levels were developed by combining two dimensions: level of knowledge about ecodesign (adapted from [25] [26]) and level of innovation in ecodesign (adapted from [12][26][27][28]). The ecodesign maturity levels defined in the Ecodesign Maturity Model are: 

Level 1: The company has no experience in ecodesign and does not yet apply ecodesign practices to improve the environmental performance of its products. The environmental issues of its products and the benefits of adopting ecodesign are so far not exploited. At this level, the company must understand the concept of ecodesign, define its internal and external drivers for the adoption of ecodesign, carry out a benchmark test to understand what competitors are doing in this area, and make a compilation of all the legal issues and standards related to the environmental performance of its products.



Level 2: The company has taken the first steps in the application of Ecodesign and is familiar with some of its practices and potential benefits. Pilot and punctual projects are implemented focusing on the incremental improvement of the environmental performance of existing products, with emphasis on specific phases of the products’ life cycle. The company uses punctual and non-consolidated approaches to ecodesign practices that emphasize the application of the practices involved in product design (operational practices). At this level, company endeavors to generate awareness of and motivation for ecodesign and begins a formal Ecodesign Program.



Level 3: At this level, the company recognizes the importance and benefits of Ecodesign based on the results if its application. Projects are implemented to improve the environmental performance of its products (e.g., materials and energy intensity), considering all the phases of the life cycle from the extraction of raw material to the product’s end-of-life. Ecodesign is integrated technically into the Detailed Design phase, ecodesign practices begin to be inserted into the processes, and the first steps are taken to structure the environmental approach and common patterns. At this level, ecodesign projects begin to focus on redesigning existing products

Figure 3: Inter-relationship among the ecodesign practices.

140 





Life Cycle Design - Methods and Tools Level 4: Ecodesign practices are incorporated systematically into the product development process starting from the initial phases (e.g., idea generation and portfolio management). Functionality analysis is now applied to conduct ecodesign. New concepts (products, services or PSS) are developed to satisfy consumer needs with better environmental performance. Level 5: Environmental issues are fully incorporated into the company's corporate, business and product strategies. Environmental issues are considered jointly with technical and economic issues to underpin the decision-making process. The company aims at system innovation through the development of new products and services that require changes in its productrelated infrastructure.

In addition to the Maturity Levels, the Ecodesign Maturity Model also considers the Capability Level in applying a specific management practice. The capability levels (adapted from [29]) are: 

1: do not apply;



2: apply ad hoc;



3: apply in a formal way;



4: apply in a controlled way;



5: ongoing improvement of the application.

4001540016 40014 5 40003 110005 110004 110003 110002

SUMMARY AND OUTLOOK

This paper presented the general concept of the Ecodesign Maturity Model and its constituent elements: Application Method, Ecodesign Practices and Ecodesign Maturity Levels. The Ecodesign Maturity Model is innovative and aims to guide companies in the continuous improvement of their PLM process with the incorporation of the environmental dimension aimed at achieving sustainability in their business. The model considers the individual needs, drivers, characteristics, maturity levels and strategies of companies to support their decision-making process. In addition to its contribution to companies, the Ecodesign Maturity Model should also contribute to the organization of knowledge in the areas of ecodesign and PLM research, structuring existing practices and establishing interrelationships among them. The theoretical concept of the Ecodesign Maturity Model was validated by 15 experts on Ecodesign from Europe, the United States and Brazil between March and August 2010. The concept is currently being applied in companies with different levels of maturity. The results of its validation and application are slated for presentation in future papers. 5

Figure 4 presents a graphical representation of maturity levels considering the Ecodesign Management Practices that are applied (represented by codes in the figure) and the Capability Level of the application of each practice. For example, to be classified as Maturity Level 1, the company must apply the Ecodesign Management Practices of Level 1 with Capability Level 3 (applied formally). A company is classified as Maturity Level 2 if it applies the Ecodesign Management Practices of Level 1 with Capability Level 4 and the practices of Level 2 with Capability Level 3. The subsequent maturity levels follow the same logic. A company is classified at Maturity Level 5 if all the Ecodesign Management Practices are applied with Capability Level 5. Level 1 Level 2 Level 3 Level 4 Level 5

4

ACKNOWLEDGMENTS

We extend our sincere thanks to the following experts on Ecodesign who agreed to participate in the validation of the Ecodesign Maturity Model: Ab Stevels, Aguinaldo Silva, Anna Hedlund-Åström, Casper Boks, Conrad Luttropp, Dorothy Maxwell, Erik Sundin, Fabrice Mathieux, Han Brezet, Mark Goedkoop, Martin Charter, Mattias Finkbeiner, Mattias Lindahl, Tom Swarr, Tracy Bhamra and Vicky Lofthouse. We also gratefully acknowledge FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo) and CAPES (Coordenação de Aperfeiçoamento do Pessoal de Nível Superior) for their financial support of this work.

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Figure 4: Graphical Representation of Ecodesign Maturity Levels.

Life Cycle Design - Methods and Tools 6

REFERENCES

[1]

Weenen, J. C. (1995): Towards sustainable product development. Journal of Cleaner Production, 3, 95-100.

[2]

Johansson, G. (2002): Success Factors for Integration of ecodesign in product development: a review of state of the art. Environmental Management and Health, 13, 98-107.

[3]

Bakshi BR, Fiksel J. (2003): The Quest for Sustainability: challenges for process systems engineering. AIChe Journal, 49(6): 1350-8.

[4]

Baumann H, Boons F, Bragd A. (2002): Mapping the green product development field: engineering, policy and business perspectives. Journal of Cleaner Production, 10:409-25.

[5]

Bakshi BR, Fiksel J. (2003): The Quest for Sustainability: challenges for process systems engineering. AIChe Journal: 49(6): 1350-8.

[6]

Luttropp, C.; Lagerstedt, J. (2006): Ecodesign and The Ten Golden Rules: generic advice for merging environmental aspects into product development. Journal of Cleaner Production, 1-13

[7]

[8]

[9]

Poole, S. et al. (1999): Integrating Environmental Decisions into the Product Development Process: Part 2 The Later Stages, in: Proceedings First International Symposium on Environmentally Conscious Design and Inverse Manufacturing, p. 334-337. Guelere Filho, A.; Rozenfeld, H. (2006): Integrating Ecodesign Methods and Tools into a Reference Model for Product Development, in: IV Global Conference on Sustainable Product Development and Life Cycle Engineering. São Carlos: Suprema. Biolchini, J.; Mian, P. G.; Natali, A. C. C.; Travassos, G. H. (2005): Systematic Review in Software Engineering. Rio de Janeiro.

[10] Brereton, P.; Kitchenham, B. A.; Budgen, D.; Turner, M.; Khalil, M. (2007): Lessons from applying the systematic literature review process within the software engineering domain. In: The Journal of Systems and Software. [11] Rozenfeld, H. et al. (2006): Gestão de Desenvolvimento de Produtos. 1a. Edição. ed. [S.l.]: Saraiva. [12] Vezzoli, C.; Manzini, E. (2008): Design for Environmental Sustainability. London: Springer. [13] Pigosso, D.C.A.; Rozenfeld, H.; Seliger, G. (2010): Ecodesign Maturity Model: criteria for methods and tools classification, in: Proceedings of the 8th CIRP Global Conference on Sustainable Manufacturing (GCSM 2010), Abu Dhabi, United Arab Emirates. [14] Tingstrom, J., Karlsson, R. (2006): The relationship between environmental analyses and the dialogue process in product development. Journal of Cleaner Production, 14, 1409-1419. [15] Guinée, J. B., Huppes, G., Heijungs, R. (2001): Developing an LCA guide for decision support. Environment Management and Health, 12, 301-311. [16] Brezet, H., Stevels, A., Rombouts, J. (1999): LCA for ecodesign: the Dutch experience, in: First International Symposium on Environmentally Conscious Design and Inverse Manufacturing, pp. 36-40. [17] Andersson, K., Eide, H. M., Lundqvist, U., Mattsson, B. (1998): The feasibility of including sustainability in LCA for product development. Journal of Cleaner Production, 6, 289298.

141 [18] Byggeth, S., Hochschorner, E. (2006): Handling trade-offs in Ecodesign tools for sustainable product development and procurement. Journal of Cleaner Production, 14, 1420-1430. [19] Ueno, K., Takahashi, T., Oyama, T., Shimamura, K., Matsumoto, T., Hasebe, Y. (2001): Efforts to improve the ecoefficiency for products of Mitsubishi Electric Corporation-factor x by using MET indicators, in: Proceedings Ecodesign 2001: Second International Symposium on Environmentally Conscious Design and Inverse Manufacturing, pp. 836-841. [20] Hochschorner, E. (2004): Assessment of tools for Environmentally Preferable Procurement with a Life Cycle Perspective. Royal Institute of Technology. [21] Hochschorner, E., Finnveden, G. (2003): Evaluation of Two Simplified Life Cycle Assessment Methods. International Journal of Life Cycle Assessment, 119-128. [22] Spicer A, Wang M. (1997): Environmental Design Industrial Template (EDIT) a software tool for analysis of product retirement. Journal of Cleaner Production, 5(3): 193-8. [23] Sun, J., Han, B., Ekwaro-Osire, S., Zhang, H.C. (2003): Design for Environment: Methodologies, Tools and Implementation. Journal of Integrated Design and Process Science, 7, 59-75. [24] Kobayashi H. (2005): Strategic evolution of eco-products: a product life cycle planning methodology. Research in Engineering Design, 16: 1–16. [25] Hemel, C. V.; Cramer, J. (2002): Barriers and stimuli for ecodesign in SMEs. Journal of Cleaner Production, p. 439– 453. [26] Stevels, A. L. N. (2007): Adventures in Ecodesign of Electronic Products. Delft: Delft University of Technology. [27] Charter, M.; Tischner, U. (Eds.). (2001): Sustainable Solutions: developing products and services for the future. Sheriffield: Greenleaf Publishing. [28] Brezet, J. C.; Van Hemel, C. (1997): Ecodesign: A Promising Approach. UNEP Working Group on Sustainable Product Development. Paris: [s.n.] [29] Chrissis, M. B.; Konrad, M.; Shrum, S. (2003): CMMI: Guidelines for Process Integration and Product Improvement. Boston: Person Education, Inc.

Environmental and Operational Analysis of Ecodesign Methods Based on QFD and FMEA 1

Fabio Neves Puglieri , Aldo Roberto Ometto 1

1

Universidade de São Paulo, Departamento de Engenharia de Produção, São Carlos, Brazil

Abstract In 1990s began a scattering of methods and tools aimed at the environmental suitability of products whose application is performed at certain stages of development. However, many of these published methods do not incorporate important environmental issues, often resulting in inefficient product development from the standpoint of ecodesign. This study aims to propose environmental and operational criteria for ecodesign methods, especially that based on QFD and FMEA (which are numerous), and analyze these methods. In order to achieve this goal, it was carried out a questionnaire application with experts that allowed us to identify characteristics that these methods must meet from the environmental and operational point of view. Keywords: Ecodesign; Criteria; QFD

1

INTRODUCTION

With the increasing of population and demand for manufactured goods, designers began to consider as an alternative to creating competitive advantage for their products not only reduce costs and improve quality, but also environmental issues, which became known as design for environment (DfE) or eco-design. Eco-design has received much attention from companies due to increased demand for environmental goods [1]. According to [2] the reasons that companies are taking interest in development of socalled "green" products are: cost reduction by optimizing the use of resources and processes, customer loyalty, improve image organization and reduction of violations through the reduction of environmental impacts. Some authors [3] present as an early contribution to the emergence of eco-design the text "Design for the Real World: Human Ecology and Social Change" by Papanek in 1971, where the author criticizes the focus given only for the aesthetic and stylistic development product rather than considering other issues such as environmental and social aspects, functionality and repair ability. Only since the 1990s that eco-design became more studied [4] mainly through the Life Cycle Assessment (LCA). It was possible to observe between the years 1990’s and 2000’s the publication of a large amount of eco-design methods, some based on software, checklists, guidelines and even adaptations of other methodologies already applied in product development, such as FMEA (Failure Mode and Effect Analysis) and QFD (Quality Function Deployment). However, faced with an excess of a hundred methods / tools for eco-design published in this period [5], some questions arise: These methods really allow the minimization of environmental impacts and natural resource consumption in various stages of the product’s life cycle? Can eco-design methods be easily adopted and applied by business? These issues have become a motivator for writing this work, whose main objective is to determine a set of criteria for analysis of eco-design methods. These criteria are divided into two groups: environmental criteria, i.e., based on those

requirements that the methods should consider to reduce environmental impacts at all stages of the life-cycle, and criteria related to the applicability of these methods, here defined as operational in order to identify which characteristics must meet i to facilitate adoption and implementation. The methodology employed is a qualitative approach with exploration goals, made through a literature search to identify the main eco-design requirements and eco-design methods based on QFD and FMEA, methods which were chosen to be analyzed in this paper. 2

ECODESIGN AND CRITERIA

According to [6] eco-design can be defined as "the development of products through the application of environmental criteria aimed at reducing environmental impacts throughout all stages of the life cycle of the product." Other concept for eco-design is "designing products considering environmental issues, minimizing its environmental impacts at every opportunity possible" [3]. Other authors [4] state that the eco-design refers to "actions taken in developing products aimed at minimizing the environmental impacts of products throughout their whole life cycle, without compromising other essential characteristics such as performance and cost." Based on these statements, we can say briefly that eco-design is an approach to product development concerned with the reduction of environmental impacts at all stages of the life cycle. However, often using eco-design does not guarantee the development of better products through environmental point of view [7]. Despite of the apparent benefits brought by eco-design methods, we cannot say that they are applied and do not even have any effect on product development [8]. These statements suggest that many eco-design methods fail to consider important criteria, whether related to the environmental suitability of the products (environmental standards) or even to respect the applicability of the method (operational criteria). Based on the definition of criteria, we can think of it as being requirements for deciding if something meets a specific function /

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_25, © Springer-Verlag Berlin Heidelberg 2011

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Life Cycle Design - Methods and Tools specification. Thus it is understood that eco-design criteria should consider a set of requirements that methods and tools for environmental product development needs in order to minimize environmental impacts at all stages of product life cycle, and to facilitate its use in the Product Development Process (PDP), called here operational criteria. Tables 1 and 2 present these requirements as some authors suggest. 3

CRITERIA DEFINITION

From the requirements and criteria presented on tables 1 and 2, proposals were made for these criteria and requirements already identified in order to allow the analysis of eco-design methods based on QFD and FMEA. Considering the particularities of each method, as its structure, characteristics and application, it was proposed the following criteria for QFD and FMEA eco-design methods, divided into environmental criteria and operational criteria. 3.1

Environmental Criteria

143 Regulations QFD: the environmental legislation and environmental standards are considered as a product requirement? FMEA: the method considers environmental legislation as a failure mode? Environmental Impacts QFD: the environmental impacts are considered as technical requirements (quality characteristic) that allow to be correlated with the quality required by the client? FMEA: are environmental impacts associated with potential failure modes and are they evaluated quantitatively and objectively? 3.2

Operational Criteria

Easy to use QFD and FMEA: the method has its stages of implementation detailed and does not use complex mathematical language (not known by the designers)? Cost

Life-cycle phases QFD: environmental requirements are considered in whole product’s life cycle (not only the use phase)?

QFD and FMEA: the method requires the purchase of software, hiring of experts and / or training?

FMEA: are life cycle phases related to each failure mode? Requirement/criterion Life-cycle phases

Description The method should consider all phases of the product’s life cycle to meet this criterion, i.e., the extraction of raw materials, product manufacturing, use and disposal. It should also include strategies for end-of-life product, such as recycling, remanufacturing and reuse, and its requirements.

References [5]; [7]; [9]; [10]; [11]; [12]; [13]; [14]

Regulations

The method should consider the product of environmental legislation for the [8]; [9] countries / regions where they are produced, used and disposed.

Environmental impacts

The method should identify and assess all environmental impacts during the [5]; [9]; [10]; [11]; whole life-cycle of the product such as natural resources and energy [12]; [14]; [15] conservation, human toxicity, effects and emissions in the air, water and soil. Table 1: Environmental requirements and criteria for eco-design methods.

Requirement/criterion Easy to use

Description References The method is considered easy to use when the procedures for application [7]; [8]; [16]; [17]; are presented very detailed, using pictures / images, describing each activity [18]; [19]; [20] and avoiding mathematical models and complex calculations involving the use of scientific language.

Cost

A method is considered expensive when there is need for training, experts, [5]; [8]; [16] consulting or software purchase.

Validated

Validation will be proven when there is a case study in the literature about its [8]; [16] application in business.

Time

The method can be considered fast when its application time is less when [5]; [18]; [19] compared to quantitative methods, such as those based on LCA and does not require a large amount of data.

Benefits of visualization

When the method shows which are the main benefits and results of its [18] application.

Trade-offs analysis

When there is analysis of trade-offs between environmental requirements, [15] between product’s requirements and between product and environmental requirements of product. Table 2: Environmental requirements and criteria for eco-design methods.

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Time QFD and FMEA: the method has a higher number of steps that its traditional version? Validated QFD and FMEA: the method was applied to businesses? Benefits of visualization QFD and FMEA: does the method presents the main results and benefits of its application? Trade-offs analysis

QFD: can the method identify relationships / conflicts between environmental requirements and product quality required and the quality characteristics? FMEA: can the method identify relationships / conflicts between the proposed recommendations? These three environmental criteria and six operational criteria were sent and answered by eight experts using questionnaires in order to identify which are more important. Experts were chosen from areas such as product development, eco-design and QFD/FMEA methods. Figures 1 and 2 shows the importance level obtained for each criterion.

Figure1: Answers of questionnaire application with specialists for environmental criteria.

Figure 2: Answers of questionnaire application with specialists for operational criteria.

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According to Figure 1 and Figure 2, it was defined weights for each environmental and operational criterion. Environmental criterion which had higher priority (related to environmental impacts) received weight 3, the second more important received weight 2 and the less important weight 1. The same idea was also used for operational criteria considering the number of criteria, so “Validated” criterion which had higher priority by specialists, received weight 6, “Time” received weight 5 and successively. The correlation between the criteria and eco-design methods based on QFD and FMEA were defined using the following table: Likert Scale Criterion is totally considered

3

Criterion is parcially considered

2

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1

(IGQFD) [30], Integration between QFDE/LCA/TRIZ [31], Integration QFDE/LCA [32], QFD-DfE [33], QFD by Wolniak and Sędek [34], QFD based on RSP [35], Eco-QFD by Kuo [36], and Eco-QFD by Utne [37]. The only two eco-design methods based on FMEA identified were Environmental Effect Analysis (or E-FMEA) [1] and integration FMEA-TRIZ [38]. As Figure 3 shows, among the environmental criteria, regulations was the less considered by all nineteen methods, i.e., it was not considered by 74% of the methods. This criterion is followed by environmental impacts (not considered by 42% of the methods). The criterion about life-cycle phases was identified in 63% of the methods. Among the operational criteria, the majority of the methods analyzed were considered easy to use and low cost. 21% of the methods were not considered fast to use, 63% did not consider trade-off analysis situation and 53% were not applied in companies.

Table 3: Likert scale for methods analysis. It was used a correlation matrix based on the same example of Quality House, as follows on the Figure 3. Methods analyzed based on QFD were: Quality Function Deployment for Environment (QFDE) [21], Environmental QFD [22], QFD by Hochman and O’Connell [23], Eco-QFD by Ernzer and Birkhofer [24], Green Quality Function Deployment (GQFD) [25], 3D-QFDE [26], Eco-VoC [27], EI2QFD [28], Green QFD-II [29], Integrated Green QFD

Another result of this analysis is related to environmental/operational situation, as Figure 4 presents. This situation reveals that the better possibility of the method to bring environmental benefits in the product development, many times it reflects in problems related to application, i.e., cost, time and hard to use. Figure 4 presents in % the maximum score which each method achieved for both environmental and operational criteria.

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Ecodesign methods based on QFD

Figure 3: Analysis of ecodesign methods based on QFD and FMEA.

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Figure 4: Comparison between QFD and FMEA methods considering environmental and operational criteria.

4

CONCLUSION

It was noted normally the operational requirements such as time and cost are related to ease of use, since one affects the other. In other words, the more difficult is the application of a method, longer and more costly it will be. Another conclusion is that the greater its ability to objectively assess environmental impacts in the product’s life cycle, the greater the difficulties in its implementation because of training costs, software purchase, specialists hiring, application time due to the increased number of steps and activities, mathematical language, and other information not known by designers. The identification of many methods that are not validated shows that there is no concern of testing methods in real cases with product development professionals. When considering the main concepts of what eco-design means, in general the authors define the term as a way to develop products in order to reduce environmental impacts throughout the product’s life cycle. So, from this definition we conclude that at least 37% of the eco-design methods based on QFD and FMEA could not be considered an eco-design method, since they do not consider the whole lifecycle of the product. This percentage may even be greater since only two of the nineteen methods allow to identify and to assess the environmental impacts generated by the products, thus

enabling to reduce environmental impacts more effectively. Thus, we conclude that the methods of eco-design need to consider a set of factors, requirements and criteria during its conceptualization and development, so they can be more easily inserted in the process of product development and allow environmental gains, contributing to the reduction of environmental impacts in the whole product’s life cycle. 5

REFERENCES

[1]

Lindahl, M. (2000): Environmental Effect Analysis (EEA) - an Approach to Design for Environment. Royal Institute of Technology, Stockholm.

[2]

Associação Brasileira De Normas Técnicas (2004): NBR ISO 14062: Gestão ambiental – Integração de aspectos ambientais no projeto e desenvolvimento do produto. Rio de Janeiro.

[3]

Lewis, H., Gertsakis, J., Grant, T., Morelli, N., Sweatman, A. (2001): Design + environment - a global guide to designing greener goods. United Kigdom: Greenleaf Publishing Ltd, 200 pp.

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Johansson, G. (2002): Success factors for integration of Ecodesign in product development: A review of state of the art. Environmental Management and Health, v. 13, n. 1, p. 98 – 107pp.

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Synergico: a new “Design for Energy Efficiency” Method enhancing the Design of more environmentally friendly Electr(on)ic Equipments 1

1

1

Lucie Domingo , Damien Evrard , Fabrice Mathieux , Guillaume Moenne-Loccoz 1

2

Laboratory G-SCOP, University of Grenoble, Grenoble, France 2

Neopost Technologies, Bagneux, France

Abstract One strategy to face the challenge of energy consumption has been the promotion of more efficient products and infrastructures. For the electr(on)ic industry, in-use energy consumption is a significant contributor to environmental impacts of a product lifecycle. Synergico is a contribution to the Design for Energy Efficiency of electr(on)ic equipments focusing on the use phase. This paper presents one of the Synergico tools that verifies that a higher in-use energy efficiency indeed decreases the environmental impacts of the product lifecycle and our method to be articulated with corporate design processes. Both are illustrated with a case study from the industry. Keywords: Ecodesign; Use Phase; Energy Related Product

1

INTRODUCTION

When assessing the environmental impacts of an electr(on)ic product through a lifecycle assessment, the energy consumption in use phase is often the main contributor to a majority of impact categories ([1-3]). Energy consumption has also been a great challenge for modern society for the last two decades. The scarcity of fuel resources and polluting means of production are serious issues that have to be dealt with. Policies and regulations both are important means to handle these problems. The ErP – Energy-related Product – directive [4] is a response to those two challenges which aims at enabling citizens to access more environmentally friendly electric and electronic appliances and to decrease the energetic demand at the European level. Design for Energy Efficiency – DfEE – is a way to decrease the overall energy demand of systems, such as mobile devices [5], or manufacturing processes [6]. The method we propose in this paper is a DfEE in use phase meant to contribute to the design for environment of electr(on)ic product. This method and its tools have been developed in the framework of the Synergico (Synergy Energy Design) project. This joint project has been funded by the French Environmental Protection Agency – ADEME – and is based on a partnership between two research laboratories and two industrial partners from the electr(on)ic industry: Neopost , and Sagemcom. From this collaboration, three tools and one method have been developed: 

An indicator of energy consumption in use phase – IUE – based on the functions and components of the product. The unit used is the watt per hour over the product time of use; the tool has already been presented in [7],



A guideline-based tool, to sort out the strategies to meet energy efficiency target of the project by criteria; the tool has already been presented in [8],



A simplified lifecycle assessment – LCA – tool, to check that the choices made to improve the energy efficiency in use phase do

not generate environmental transfers on other phases, or on other impacts. 

A method to gather the relevant information, detailing the Who?, What?, Where?, When?, Why?, How? of the design for energy efficiency in use phase process.

This paper introduces the lifecycle verification tool, illustrated by the case study of a microcontroller on a postage meter. It then presents the global Synergico design method. This section is an illustration with a proposition of integration of the Synergico method into the design procedures of Neopost, one of the leading companies in the design and manufacturing of mailing solutions (postage meters, folding inserting systems, addressing systems, etc.). Conclusions are finally presented. 2

LIFECYCLE CHECK TOOL

A Lifecycle Assessment, as defined in the ISO 14040 [9], is useful to assess the environmental impacts of a product during its lifecycle. Since several impact categories and lifecycle phases are considered, it is possible to compare two products with similar functions and to identify impact tradeoffs. The central specification for our simplified LCA tool was to help verify that the design of implemented solutions for energy efficiency in the product actually implies a better environmental performance. It is meant, as required for example by the ISO 14062 [10], to confirm that the modifications made to improve the energy efficiency do not generate unexpected additional environmental impacts on any other lifecycle stages or on any other environmental impacts. 2.1

Environmental Impact of solutions for Energy Efficiency

In order to have an overview of the best available and non-available technologies for energy efficiency, we based our list of solutions on the analysis of the preparatory studies for the development of specific ecodesign requirements for the ErP directive [4]. The sixth task of those reports is dedicated to viable technologies for the improvements of energy efficiency of the product category under

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_26, © Springer-Verlag Berlin Heidelberg 2011

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Life Cycle Design - Methods and Tools study. The review was based on the following product categories: Boilers and Combi-boilers (Lot 1), Personal Computers and Computer monitors (Lot 3), Imaging equipment (Lot 4), Televisions (Lot 5), Stand-by and off modes losses of EuPs (Lot 6), Battery chargers and external power supplies (Lot 7), Tertiary Lighting (Lots 8-9), Electric Motors (Lot 11), Commercial and Domestic refrigerators and freezers (lots 12-13), Domestic dishwashers (Lot 14) and Complex Set top boxes (lot 18). We then classified the solutions into three categories according to the following hypotheses in order to simplify the tool: 

Impact transfers are caused by physical changes in the components, hence software modifications are not supposed to imply any impact transfers;



New technologies will not be assessed by the tool due to the confidentiality or the lack of available information;



The suppression of a component leads to a reduction of the product impact.

In this classification, we sorted the solutions in two categories whether it is a solution with a: 



“Need to be assessed for impact transfers”: the solution for energy efficiency seems to generate an impact transfer toward another impact category, another lifecycle phase or another part of the product “No need to be assessed for impact transfers”: the solution for energy efficiency does not seem to generate an additional environmental impact on another impact category, another lifecycle phase or another part of the product.

Need to be assessed for impact transfers:

149 representative of usual impact transfers for the categories 1 and 2 defined above. To select the right indicators, we explored the subject of the environmental impact of electronic products while resorting to three different approach angles. The first one was based on a general assessment of products in Europe [12]. It showed that the influence of electr(on)ic goods was significant on two indicators: on non-renewable resources depletion and energy consumption (as well as a correlated impact: global warming). The second one focused on literature about the environmental assessment of electr(on)ic products, to reveal a pattern in the types of indicators and was based on the result of joint initiatives between governmental bodies and industrials from the electr(on)ic sector. Two projects, in Denmark [13] and in France [14], were of particular interest. Even if their goals were different, their conclusions on the most interesting indicators to follow were the same. According to these studies, the most appropriate indicators to assess [13] and to communicate [14] on environmental impacts are related to two environmental issues: energy consumption and non-renewable resources depletion over the entire lifecycle. The third one was based on the Synergico assessment of a solution implemented for energy efficiency by our industrial partner: a microcontroller, which is an electronic component. The impact assessment of this component was done using SimaPro V7.1 with EcoInvent Lifecycle Inventory database and evaluated according to the commonly used methods: Eco-indicator 99 E (see Figure 1) and the CML 2 baseline 2000 (see Figure 2). This modelling helped highlight the most relevant impact categories for this component, therefore we considered it as representative for other electronic components.

1. Changes in material, coating or manufacturing shaping: mostly for insulation, heat dissipation material, coating or shaping can be modified. 2. Component inclusion: the addition of electronic components which enable a better, finest control of product energy consumption. No need to be assessed for impact transfers: 3. Software insertion: the addition of software code to manage the energy or to communicate information to the user is a common practice for energy efficiency. We stand that this kind of improvement will generate few or no impact transfers. 4. New technology: more efficient technologies are developed continually. Nevertheless, modelling their environmental impact is difficult due to the confidentiality or the instability of the techniques [11]. For that purpose, if a new technology is used to enhance the energy efficiency, its environmental impact calculation will not be supported by our tool. 5. Component suppression: unnecessary components might be implemented on some products. Their suppression will not generate additional environmental impacts.

Table 1: Classification of the solutions for the lifecycle check tool. A classic problem in integrated design is to handle tradeoffs between different design objectives: energy efficiency often needs for example to be balanced with manufacturing costs or user safety. A similar issue applies in lifecycle assessment. Choices are difficult to make when there are many indicators to weigh the pros and cons. To overcome this problem, we had to limit the number of indicators in our tool. Nevertheless, those few indicators had to be

Figure 1: Environmental impacts of the microcontroller lifecycle with Eco Indicator 99 E. Figure 1 shows that the main impacts of the microcontroller are on fossil fuels, respiratory inorganics, radiation, climate change, and minerals. The last one of this list can be described by the category “raw material depletion”. The contribution to fossil fuels, climate change and radiation comes from the energy production.

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Life Cycle Design - Methods and Tools 

A comparison with a base case product, in order to plot a result based on understandable references



A raw modelling of the component architecture to be implemented.

For each component, we predefined scenarios for the phases which are difficult to assess during design, namely distribution and end-oflife [17]. For the use phase, we modelled it as the energetic gain generated by the implemented architecture. This last value can be obtained in the IUE tool (Indicator for in-Use Energy Consumption) [7]. The recycling phase includes the recovery of materials such as precious metals which enables the saving of primary raw materials. In order to simplify the model, each electronic component has been associated with a soldering process and a piece of electronic board and each material is linked to a shaping process. The following section shows the input information needed to assess the environmental transfers generated by the implementation of a microcontroller on a postage meter. Figure 2: Environmental impacts of the microcontroller lifecycle with CML 2 baseline 2000. In Figure 2 the main impacts are marine aquatic ecotoxicity, Abiotic depletion, fresh water aquatic ecotoxicity, global warming, and acidification. The lifecycle of the microcontroller highlighted the influence of the following impacts: 

Toxicity (Eco- and Human)



Acidification



Abiotic resources depletion / Raw material depletion



Global warming / Climate change

After a concertation with our industrial partners, we decided not to consider the toxicity impacts because they are already taken into account in both the RoHS and the REACH directives. As for the acidification impact for which transportation is the main contributor and is very low if reported to the functional unit considered in the study of the whole product.

2.3

Application to the case study of the microcontroller on a postage meter

The available data for the modelling of the microcontroller were: the architecture of such a component and the potential savings of this solution. In this case study, the microcontroller was used to influence the energy consumption in standby mode, hence a gain of 7.5 W with the same level of performance for the product by adding a card of 2.25 cm². First, we chose the product architecture that represented the best the actual product design. Secondly, the modelling of the components of the microcontroller was done. Thirdly, the amount of energy saved over the product use-time by this solution was documented (in kWh). After modelling the data, the assessment was carried out. Figure 3 shows the comparison between the environmental impacts of the base case product and the under-design product.

Finally, to keep a simplified tool, it appeared that two impact categories were actually significant for our purpose. All those approaches pointed out two environmental issues that are significantly influenced by the addition of solutions for energy efficiency such as the addition of electr(on)ic: raw material depletion and energy depletion (which reflects global warming). 2.2

Simplified LCA-based tool to be used during design for supporting design activities

This tool is meant to assess a product or a module in its earliest stages of design when the information on the product lifecycle is still incomplete. Simplified LCA approaches are based on different assumptions: [15] proposed to group a product and its components according to their material and energy efficiency in order to support environmental decision making in the early stages of the design process. Other simplified LCA propose excluding phases with nonsignificant contribution to the entire lifecycle [16]. Our approach is based on a combination of these two approaches: finding the most relevant information on environmental impact for designers (see paragraph 2.1) and restricting the number of information to be used in the model. The most reliable available information is about the physical architecture of components and previous or concurrent products with a similar lifecycle. This is why we decided to quantify environmental impact transfers based on:

Figure 3: Result of the assessment of the impact transfers for the microcontroller implemented on a postage meter. For the manufacturing and the end-of-life phases, the new product has slightly higher impacts of about 1%, for both raw material depletion and energy depletion. The contribution of the microcontroller on raw material depletion during recycling is negative because of the increase of potentiality for recycling due to the addition of the microcontroller, which means that the new design has a better performance than the base case study. It is all the more visible during the use phase with both

Life Cycle Design - Methods and Tools impact categories around -60%, which overcomes the loss of performance during the manufacturing and the end of life. The largest contribution is generated by the saved energy thanks to the microcontroller. The suggested lifecycle check tool is not meant to replace an LCA but to support designers in a rapid way for analyzing the environmental impacts of the product architecture. Therefore, it can be viewed as an alternative to a full lifecycle assessment when a comparison between energy savings and the addition of components is needed during design.

3

SYNERGICO METHOD: INTEGRATING THE TOOLS INTO THE PRODUCT DESIGN PROCESS

In order to drive the tool described above and the other two tools developed for this project [7], [8], the Synergico method has been written as a means to support the design management in the implementation of the tools in the design process by specifying the Who?, What?, Where?, When?, Why?, How? of the tools. 3.1

Design process of electr(on)ic products

A preliminary condition to define a design method is to observe and to identify the form of the actual design process for the development of electr(on)ic products. Various design processes exist and many companies have their own procedure. One of our objectives was to ensure the compatibility of the Synergico method with the corporate design processes. Our choice had been to base our work on existing generic models for product development like [10], [18]. We then assessed their compatibility with the design process used by our industrial partners and [10]. Eventually, we chose the most appropriate form of process with the following steps: Planning, Preliminary design, Detailed design, Test, Industrialization. Those design steps define the milestones of the method and will be the five values that the When? can take. The chosen design process is linear (see Figure 5) with no possibility to go back to previous steps, since we considered in the method, that the design steps are milestones and Synergico helps validate a step before entering to the following one. To define Who?, our approach has mostly been based on the departments implied in the design activities of our partners. Seven different competences were identified in the following departments: 

Electronic design: in charge of the design of the boards, their drivers, power supplies and all other electronic components,



Mechanical design: in charge of the design of the kinematic sets (engines, actuators, sensors…) and the structure of the product (shell…)



Software design: in charge of the software coding and its implementation on the hardware structure



Project management: managing the different actors of the design project, fulfilling the objectives and coordinating the relations between the different departments



Marketing: in charge of the interface between client and design team by means of specification and product requirements.

151 

Purchase: in charge of finding the adequate suppliers for components, materials, machinery, etc. according to project management specifications



Ecodesign expertise: in order to go deeper in the DfE, such an expert may be useful.

In order to simplify Figure 5, we used in this paper only two actors, namely the “designers” (electronic, mechanical, and software design) and the “transverse functions” (project management, marketing, purchase, and ecodesign expertise). To define Where?, a list of the key “places” in the Synergico toolbox was defined: Lifecycle Check Tool, Guidelines, Indicator of in-use energy consumption, Specification, Functional splitting, Physical splitting, Use scenario, Power. We named those “places” sub-tools. 3.2

Integration of the tools in the design process

The What?, Why?, How? are highly dependent on the tool we consider. In Synergico, What? refers to the input data to be processed at this stage, Why? refers to the expected results, i.e. the output and How? refers to the way the input data are processed to obtain output data. The structure of the method is defined in two diagrams with the same axes: the different sub-tools (Where?) and the steps of the design process (When?). The first one presents the actors (Who?) (see Figure 5) and in the second one, which is not illustrated in this article, the data flows (What? and Why?). The association of a design process step with a sub-tool defines what we call a “block”. For each block, the method specifies Who?, What?, Where?, When?, Why?, How?, which correspond to the input / output data, the actors involved at this step whose skills are needed to fill in the tools. The Synergico method is composed of 23 blocks indexed according to the design stage and the sub-tool considered. For example, the block 3.C (see Figure 4) represents the sub-tool “power” during detailed design. In this case, the input data are the IUE results from the power subtool and the datasheets of the components providing information about the power they require. The electronic, software and mechanical departments are the ones involved in this step. They can use the help of the Guidelines tool to drive the design of the prototype. The outputs are new specifications for a prototype and new IUE results.

Figure 4: Block 3.C Power during detailed design.

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Life Cycle Design - Methods and Tools

Figure 5: Articulation between Synergico, the design process and the actors of the project. 3.3

Implementation at Neopost

Once we had defined a generic method, some adjustments had to be done to fit in the design process of our project partners. This section presents the integration of Synergico in the design process of Neopost. This part of the project involved the corporate Quality,Health, Safety & Environment manager and the Ecodesign Expert. The first step was to adjust the general method to the actual practices of Neopost and especially, an adaptation of the vocabulary used in the method and tools has been necessary. Thus, the generic terminology was adapted to the one currently used in the company concerning the departments and the design phases. The second step consisted in specifying the interaction of the Synergico tools with other Neopost’s design practices, tools and methods in terms of: 

Where to find the external input information?



Where to use the external output information?

We defined, as external input, data such as the information contained in the customers’ requirements and the capitalization

data. During the implementation process we defined who, in a design project team, was the most adequate department or person to provide such information and to mediate its use in the design process. We defined, as external output information, the results of the InUse-Energy consumption indicator, for example. The aim of the implementation was to define how this data can be used outside design to support communication and marketing experts. After adapting and connecting Synergico with other design procedures of Neopost, Design for Energy Efficiency was integrated in Neopost strategy as part of the tool kit for integrated design of postage meters. 4

CONCLUSIONS

This paper presents a tool whose purpose is to validate, from a lifecycle perspective and considering two impacts, the modifications of an electr(on)ic product during its design or redesign in order to increase its energy efficiency. It also introduces the method developed to coordinate the tools indicator for In Use energy consumption [7], Guidelines [8], and Impact transfers.

Life Cycle Design - Methods and Tools As stated earlier, energy efficiency in use is a central issue for electr(on)ic products and their environmental performances can be highly modified by decreasing their energy consumption. It is the reason why considering this aspect as early as possible in the design process is essential. Synergico method is aimed at driving design toward a more efficient product in use phase by providing a step-by-step methodology based on three complementary specifically tailored for the design process of electr(on)ic equipments. The proposed case study happened during the redesign of a product and, in order to validate the Synergico method, the implementation of the method and tools. The collaboration with both industrial partners, Neopost and Sagemcom, a manufacturer of telecommunication equipments, has been essential to insure the practicability and relevance of the tools and method for the electr(on)ic industry. Further developments are ongoing to improve the reliability of the tools and to make them robust enough to be used by the whole sector of electr(on)ic equipments. In order to verify the universality of the method, other applications with other industrial partners will be carried out. A new manufacturer has already been identified to test the Synergico method from the early stages of the design of a new electr(on)ic product to its final market launch. 5

[7]

Domingo L., Mathieux F., Bonvoisin J., Brissaud D. (2010): Indicator for in Use Energy Consumption (IUE): a tool enhancing Design for Energy Efficiency of products, In: IDMME - Virtual Concept 2010.

[8]

Bonvoisin J., Mathieux F., Domingo L., Brissaud D. (2010): Design for energy efficiency: proposition of a guidelinesbased tool, In International Design Conference- Design 2010.

[9]

International Standard Association (2006): ISO 14040: Life cycle assessment, principle and framework.

[10]

International Standard Association (2003.): XP ISO/TR 14062: Environmental management -Integrating environmental aspects into product design and development.

[11]

European Commission (2006): Proceedings of the Workshop on Nanotechnology and Life Cycle Assessment.

[12]

Tukker A. , Jansen B. (2006): Environmental Impacts of Products: A Detailed Review of Studies, In: Journal of Industrial Ecology, vol. 10, n°. 3, p. 159-182.

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Institute for Product Development DTU Denmark, Danish Toxicology Center (2005): Eco-conscious design of electrical and electronic product.

[14]

ADEME, AFNOR (2010): Environmental label of consumer market's product.

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Kaebernick H., Sun M., Kara S. (2003): Simplified Lifecycle Assessment for the Early Design Stages of Industrial Products, In: CIRP Annals - Manufacturing Technology, vol. 52, n°. 1, p. 25-28.

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Hur T., Lee J., Ryu J., Kwon E. (2005): Simplified LCA and matrix methods in identifying the environmental aspects of a product system, In: Journal of Environmental Management, vol. 75, n°. 3, p. 229-237.

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Nielsen P. H. , Wenzel H. (2002): Integration of environmental aspects in product development: a stepwise procedure based on quantitative life cycle assessment, In: Journal of Cleaner Production, vol. 10, n°. 3, p. 247-257.

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Pahl G., Beitz W., Wallace K., Feldhusen J., Blessing L.( 2007): Engineering design, In: Springer.

ACKNOWLEDGMENTS

We acknowledge the financial support of the French EPA ADEME (Contract #0877C0032) in the framework of the 2008 call for proposal on “Research,development and innovation in Ecodesign.” We also want to thank our industrial partners and especially, the entire design team at Neopost Technologies that collaborated in the construction of the Synergico method and tools. 6

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Improving Product Design based on Energy Considerations Yingying Seow, Shahin Rahimifard Centre for Sustainable Manufacturing and Reuse/Recycling Technologies, Loughborough University, UK

Abstract The industrial sector consumes a significant amount of the world’s energy supply; the rationalisation of energy consumption would provide the most effective method of reducing greenhouse gas emissions attributed to manufacturing and use of products. Energy consumed across the various stages of a product’s lifecycle varies significantly depending on the product design and its application. In non-energy using products such as furniture, food, and clothing, the material preparation and production phases represent a significant proportion of energy consumption over the product lifecycle. This paper proposes a new design methodology targeted at these products to minimise energy consumption during ‘production’ phase. Keywords: Energy Efficiency; Design for the Environment; Low Carbon Manufacturing

1

INTRODUCTION

Increasingly, energy consumption of products has become the focus of environmental concerns due to carbon emissions from the combustion of fossil fuels for energy generation. As energy demand continues to grow and fossil fuels remain the main source for power generation in the foreseeable future [1] the most effective method of CO2 reduction is still through the rationalisation of energy consumption. This has led governing bodies to introduce a number of energy auditing and accreditation standards, such as European directives on the ‘Eco-Design of Energy using Products (EU Directive 2005/32/EC)’ and ‘Energy End-Use Efficiency and Energy Services (EU Directive 2006/32/EC)’.

Cumulative lock-in of environmental impact

According to Otto and Wood [2], 80% of the environmental damage of a product is established after 20% of the design activity is completed. Decisions made early in the conceptual design phase can influence the outcome of a design exercise more significantly than any optimisation step later on in the design process [3]. Therefore environmental considerations should be integrated early in the design phase during the product development process, see Figure 1 [4]. The most commonly adopted method is ‘Design for Environment’ (DfE) which is concerned with the impact of design throughout the lifecycle, from material preparation and manufacture to use and end-of-life management of a product [5].

STRATEGIC PRODUCT AND MARKET RESEARCH

Cumulative ‘lock-in’ of environmental impact arising from decisions made along the product development cycle

DfE considers a range of environmental issues associated with a product including resource consumption, end-of-life disposal, waste management, recyclability reusability and use of toxic and hazardous materials. Energy is clearly consumed across the various stages of a product lifecycle; furthermore the level of energy consumed in each lifecycle phase significantly varies depending on the product. For example in the case of electrical products, the greatest contributor to environmental impact is often due to the consumption of electricity during the ‘Use’ phase, thus the reduction of this energy use during this stage has been the focus of most design tools and guidelines. However in the majority of manufacturing applications, the production phase still represents a significant proportion of energy consumed over a product’s lifecycle, in particular for non-energy consuming products. This highlights the need to investigate the opportunities for optimisation of energy consumption during the production through design improvements. This paper proposes a new design methodology which aims to minimise the energy consumption during the manufacturing phase of a product. This is achieved by providing a detailed breakdown of energy flows attributed to the production of a product and utilise this energy data to improve the design process. The initial section of the paper provides an overview of ‘Design for X’ approaches, together with an overview of the established design methodologies used in most applications. The latter part of this paper describes the Design for Energy Minimisation (DfEM), during manufacture and outlines its application in the design of a chair. 2

Environmental improvement strategies DESIGN FOR ENVIRONMENT LIFE-CYCLE ASSESSMENT

CLEANER PRODUCTION

CONSUMER EDUCATION

WASTE MAMAGEMENT AND RECYCLING

Figure 1: Conceptual representation of environmental ‘lock-in’ over a product’s development cycle [4].

2.1

PRODUCT DESIGN AND THE APPLICATION OF DFX TOOLS Product Design Process

A common design model as proposed by Pugh [6] consists of four generic stages: 1) Specification, 2) Conceptual Design, 3) Detail Design and 4) Manufacture. As illustrated in Figure 2. The first stage involves planning of the design task by collecting

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_27, © Springer-Verlag Berlin Heidelberg 2011

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information about the customer requirements and creating a product design specification. The next step is to generate ideas by searching for essential problems and combining working principles and selecting a suitable concept. The third stage is detail design which develops the concept chosen at the previous stage into a more concrete proposal with specifications of geometry, materials and tolerances of all parts in the product. Production costs and robust performance are the main concern at this stage. Finally the last stage is manufacturing and typically at this stage the main design aim is to minimize the component and assembly cost. Various design for ‘X’ (DfX) tools can be applied to each design stage. DfX is a term that is used to represent a variety of considerations that must be made whilst designing a product and stems from the fact that designers cannot be subject experts on every factor that arises during the design process. It can be used in the early stages of concept design as a benchmarking tool as well as helping to simplify new un-built concepts [2]. For example Design for Life Cycle which considers the environmental impact of a product from cradle to grave, may mean a radical design change to a vehicle such as powering a car from renewable energy to minimize the impacts from the use of fossil fuels. Other DfX tools like Design for Manufacture and Assembly might be considered to minimize the number of parts thereby reducing manufacturing and assembly costs and time. Figure 3 shows an example of how the various DFX tools alongside others, can support the different phases in the product development process. More recently with the increasing concern about climate change and the environmental impact of products, a new generation of DfX tools have been developed to help designers reduce these impacts through their design. These tools aim to integrate environmental considerations in the design of new products to reduce the overall environmental impact of a product [8,9] as most of the environmental impact in a product’s lifecycle is ‘locked in’ into the product at the design stage when materials and production process are selected, and product performance is largely determined.

Figure 3: Application of various design tools in problem solving, product synthesis and in product development [7]. As there is no single measure for environmental impact, various tools and techniques have been developed under the DfE strategy some of which are: Design for recyclability [10], Design for disassembly [11], Design for Lifecycle [12], Lifecycle Costing [13], Sustainable design [14] and Design for End-of-life [15]. This research paper is proposing a new framework for improving product design through energy considerations. To demonstrate how a Design for Energy Minimisation approach can be adopted across the various design stages, 3 generic phases of Concept design (CD), Detail design (DD) and Manufacture (M) in line with Pugh’s [6] design methods have been used. 2.2

Design for Energy Minimisation Approach

DfEM is a wide ranging consideration that not only includes energy consumed during the Use phase, but also considers the other stages in the lifecycle. This is currently supported by Life Cycle Assessment (LCA) which is used to compile and evaluate the environmental burdens of the product from the material production to part manufacture, product assembly, operation, servicing, maintenance and end-of-life disposition [16]. However there are two main shortcomings with conducting a LCA: 1) The inventory analysis required in a LCA is time consuming due to the complexity and data intensive nature of the process. In various studies conducted [17,18,19] the industry found this process to be too complex and requiring a great deal of effort for existing products. The data intensive nature of a LCA coupled with the lack of accurate data related to the energy consumption across the entire lifecycle of a product often results in significant assumptions and simplifications [19]. This is perhaps even greater for a product that does not yet exist as it is unrealistic for a designer to have access to all the specific information about the materials and processes required for a comprehensive LCA at the early stages of product design i.e. concept design phase.

Figure 2: Pugh’s product design model showing the 4 central stages of the product design process [6].

2) On a more specific level, the energy data available in existing Life cycle inventory (LCI) databases such as the Ecoinvent [21] database is based mainly on industry sectors located in Switzerland and Western Europe and is therefore not always relevant for products that are manufactured in a different location. In addition, much of the process energy data is indicated as kJ per unit weight of material processed which does not provide any indication of how much energy was used by the manufacturing facility, how much

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was for the actual processing and how much was from the supporting auxiliary processes. The total energy consideration established through the LCI can only provide a generic ballpark energy consumption value which may not be reliable for processes which are executed in a different way in other manufacturing environments. Hence there is a need to consider the energy flow modelling during the ‘manufacturing’ phase in more detail. For these reasons, there have been a number of recent developments in the following two areas: a. In order to minimize the complexity and time taken to conduct a full LCA, simplified models and additional assumptions have been used to reduce the evaluation effort in traditional LCA. These condensed LCA are known as streamlined LCA (S-LCA) which encompasses a group of approaches designed to simplify and reduce the time, cost and effect involved in conducting a full LCA while still facilitating accurate and effective decisions. For example, Granta Design [22] has developed a simplified LCA tool called the Eco Audit tool (part of the Cambridge Engineering Selector (CES) suite of software) which uses information about product composition, processing, usage, transportation, and disposal. The tool then combines this with eco property data on the materials and processes used in the design to calculate the energy usage and CO2 output resulting from each stage in the product lifecycle, see Figure 4. This high level overview is particularly useful during the first stage of product design (i.e. concept design) which can guide the design strategy by the identifying the lifecycle phase which has highest environmental impact.

In this context, the authors argue that a holistic DfEM approach should first provide support across the design process from concept design to manufacture and should secondly consider the energy consumption throughout the entire product life cycle. S-LCA tools such as CES mostly provides support during the concept design stage by providing high level energy information of each phase of a product lifecycle whilst AEMS provides support at the manufacture stage through the monitoring and tracking of energy consumption within the manufacturing facility. This highlights the need for a tool at the detail design phase that can provide energy data that is sufficiently detailed to correlate production processes and operation parameters to energy consumption. It is therefore proposed that an Energy Simulation Model (ESM) can be used at the detail design phase to bridge the gap between high level simplified LCA tools used at conceptual design and those used to monitor energy consumption as part of the manufacturing stage, as illustrated in Figure 5. This is achieved through a framework to model energy flows within the manufacturing phase of a product lifecycle and to support the detail design activities within the product design process which is described in the next section. 3

ENERGY SIMULATION MODELLING FRAMEWORK

b. In order to gain an accurate picture of the energy consumption in manufacturing, energy management systems are now used to track and measure the energy used in a production facility, providing a breakdown of energy consumption by various elements in a production system including both the buildings and production facilities.

Much of the current work on energy consumption within production or manufacturing can be broadly viewed under two different perspectives of ‘plant’ and ‘process’. The work directed at the ‘plant’ level has focused on the energy consumed by infrastructure and other high level services that are responsible for maintaining the required production conditions/environment [24, 25]. Examples of such energy consuming activities would be heating and lighting, transportation equipment and ventilation systems [26 ]. On the other hand, research concentrating on the ‘Process’ levels have targeted energy consumption of the individual equipment, machinery and workstation within a production system [27, 28].

An example of energy management software is Optima developed by Optima Energy Management [23]. It can track and monitor real time energy consumption, buys energy at best available prices and allows budgets and targets to be set for cost savings. Whilst AEMS provides correlation with external factors affecting energy use such as weather and building occupancy, much of the data is related to building energy consumption and only provides a high level breakdown of a plant’s energy consumption by generic areas.

This research proposes a third perspective which considers the energy consumed by a product as it is being manufactured and attributes the energy used on the plant and process levels to single unit of product made. This also includes energy that is required for pre-production (i.e. material preparation), production (i.e machining) and post production (i.e. packaging). This ‘product’ perspective along with the other two ‘plant’ and ‘process’ viewpoints on energy modelling are depicted in Figure 6. Currently most energy analysis of a product is conducted through a LCA methodology which typically uses the weight of the material

Figure 4: Inputs and outputs for the Eco Audit Tool [21].

Figure 5: DfEM should support the design process as well as the product’s lifecycle.

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being processed as the basis for the calculation. This paper proposes a different approach to energy modelling which differs from traditional LCA calculations by taking into account the amount of material being processed as well as the processing time required to convert these materials to finished products. For example in the case of machining processes, it is not only the weight of the material removed but also the complexity of the required operations (e.g. number of holes or slots), hence the total processing time, can greatly influence the energy consumption.

The energy simulation model consists of a simulation engine, an energy database, and a decision support tool, see Figure 7. The simulation engine is based on the framework and has been developed to allow a number of ‘what-if’ scenarios for the analysis and evaluation of energy consumption during the manufacturing phase of a product life-cycle. The simulation engine which has been TM developed using Arena , a discrete event simulation and automation software from Rockwell Automation is capable of modelling various manufacturing process flows for different products and can be expanded to include product or process variations. Additional production variations such as batch sizing, lead times and queue times can also be included. The energy database also provides the simulation engine with the primary energy information such as energy values associated with the manufacturing processes and auxiliary activities. Initial data can be determined either theoretically or empirically and statistical relationships can eventually be established to train the simulation engine to predict the amount of energy consumed by the processes and activities for different production parameters such as batching, queue times, process routing and process set ups.

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Figure 7: Energy simulation model consists of the decision support tool, the energy model data base and the modelling engine. As the energy model becomes more robust, the data output from the predictive models can in turn be added into the energy database to build up a comprehensive understanding of the energy requirements of processes and production systems. It should be noted that the data related to energy consumption within logistics and reverse logistics activities can also be included. The final aspect of the energy simulation model is the decision support tool which correlates various design and processing parameters with energy consumption data derived from the energy database. Using a correlation matrix, the energy intensity and efficiency of various manufacturing parameters can be evaluated against the functional requirements of the product to derive at a design that has minimal energy consumption during manufacturing. This energy simulation model not only supports operational decisions but also provides energy transparency right back to the design process, enabling designers to select the most energy efficient materials and processes whilst fulfilling the requirements in the product specification. Such an approach will potentially enable businesses to go beyond the incremental improvements achievable via existing energy management systems to consider energy efficiency and utilisation across both the design and manufacturing phases of a product life cycle. 4 4.1

Figure 6: Different Perspectives of Energy Modelling.

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In this framework, the energy consumed within a manufacturing facility is categorised into Direct Energy and Indirect Energy. The Direct Energy (DE) represents the energy utilised by the manufacturing processes used to produce the product. This includes pre-production, production and post-production processes (e.g. casting, machining, spray painting, inspection, etc). The Indirect Energy (IE) is the energy consumed by activities required to maintain the ‘environment’ in which the production processes are carried out within a manufacturing plant (e.g. lighting, heating, ventilation, etc.). Further details of this framework can be found in Rahimifard and Seow [29]. In this approach, the EPE model is not only able to detail the energy consumption for the various processes, but also highlights the energy hotspots within a manufacturing facility to support energy efficient manufacturing [30]. Energy intensive or energy inefficient processes can be identified for replacement or improvement.

Energy Simulation Model

APPLYING DFEM TO PRODUCT DESIGN Tools to aid DfEM

As mentioned before, the adoption of DfEM methodology involves a series of tools that can be applied at the different stages in the product design process. For example at the conceptual design phase where high level decisions are required for concept selection a simplified LCA package like CES Eco Selector could be adopted to provide an overview of the energy requirements for a new design within a product lifecycle. CES Selector can provide support to determine the appropriate materials based on specific product specification [31] and relate the energy consumption to the selected materials. It can also provide designers with a rough estimate of the energy requirements of processes which can aid decision making when short listing suitable processes.

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Figure 8: Application of various tools in a product design process to aid energy minimisation. In the second phase- detail design, where product structure, assemblies and components are established, there is a need for more detailed considerations of the relationships between product attributes and production processes required for manufacturing. At this stage the decision support tool can be used to identify tradeoffs between energy intensity of processes and functional requirements. After a process has been chosen, the energy simulation model can be used to evaluate the energy consumption during the manufacture, and hence provide appropriate information during the selection of least energy intensive processes or setting process parameters so that they consumed the least energy. In a similar manner during the final phase (i.e. manufacturing stage), production machinery and facilities need to be monitored to improve energy flows and efficiency. Advance energy management systems can be used to measure, record and improve the energy consumption within a production system and track energy demand of the manufacturing site. 4.2

Application of DfEM to a Product

DfEM was applied to the design and manufacture of a plastic chair to evaluate the areas where energy consumption could be minimised. In the case of a simple product like a plastic chair, various energy considerations and goals can be defined for the product at the start of the development phase and while creating a Product Design Specification (PDS). In this case, the CES Eco Selector can be used to assess the energy requirements for extraction, preparation and processing of various plastics to further narrow down the list of materials that meet the functional requirements of this product. This evaluation may show that of the Acrylonitrile-ButadieneStyrene (ABS) and reinforced Polypropylene (PP) can both fulfil the product specification, but PP is the least energy intensive to extract and prepare. After selection of the material, the energy simulation model can then be used to evaluate the various production processes that can be used to manufacture the chair using the PP, and provide an indication of the least energy intensive processes. In this case due to specific product geometry, the feasible processes that can be adopted are high impact injection moulding and gas

assisted injection moulding. The evaluation of these two processes indicates that the gas assisted injection moulding will potentially consume more energy due to the high energy requirements for compressed air. The energy model is therefore able to determine energy hotspots at the same time provide a breakdown of the energy consumed by the direct processes, auxiliary processes as well as the indirect processes from the facility. This information could aid the decision making when deciding on the best method of manufacturing of the product and provide designers with a greater insight into energy consumption. Finally during the actual production of the chair, AEMS can be used to monitor the real time energy consumption by injection moulding, process cooling, drying ovens, heating and ventilation systems as well as lighting to improve the efficiency of the production facility. Although these tools can be used independently within each phase of the design process, clearly greater benefits could be achieved through integration of these tools, as the data/knowledge generated by each can support the decision made in other phases. For example, the data collected from the AEMS can help to improve and expand the database used by the ESM, providing more accurate energy consumption values for the actual production facility rather than a generic plant. Likewise, ESM can help CES by providing more customised data for the processes carried out at the facility so that an accurate streamlined LCA can be carried out for subsequent products designed and manufactured at the plant. 5

CONCLUSIONS

Design is an integral part of any product development process and much of the decisions taken at this stage accounts for majority of the financial and environmental cost of a product. Therefore to reduce the energy consumption of a product during the manufacturing stage, energy considerations need to be included at the design stage. By identifying where the energy is used during production and how productively it is used, the designer gains an insight into the energy effectiveness of the process in relation to a product. This knowledge can empower the designer to intelligently

Life Cycle Design - Methods and Tools explore the suitability of a product feature, a material and consequently the chosen manufacturing process with energy minimisation in mind. The DfEM methodology presented in this paper together with the simulation tool would enable designers to do ‘what if’ scenarios to identify the most practical and economically feasible design improvements that could reduce the need for energy consumption during manufacture. As with most DfX tools which improves design from just one perspective, DfEM only provides a singular view focusing on energy consumption during production. The reduction of energy consumption in the manufacture phase may have an adverse effect on the other stages of the life cycle. Clearly the scope of this approach has to be extended to consider the energy considerations related to wider issues within a product life cycle such as the energy requirements during the use phase, logistics and reverse logistics and end-of-life. As such this approach should be used in conjunction with other LCM tools to evaluate the overall life cycle impact of the product to ensure that the absolute environmental impact is reduced and not increased. The matter of minimising energy consumption of a production system must be addressed as part of a multi objective optimization problem. 6 [1]

World Resource Institute (2005): Greenhouse Gas Emissions: 2005, Available at: http://www.wri.org/chart/worldgreenhouse-gas-emissions-2005, [Accessed 10 August 2009]. Otto, K. N. and Wood, K. L. (2001): Product Design Techniques in Reverse Engineering and New Product Development, Prentice Hall, New Jersey.

[3]

Duflou, J. R. and Dewulf, J. (2004): Eco-Impact anticipation by Parametric Screening of Machine System Components, In Product Engineering (Eds, Talaba, D. and Roche, T.) Springer, Netherlands, pp. 17-30.

[5]

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[15]

Rose, C., Stevels, A. and Ishii, K. (2000) A new approach to end-of-life design advisor (ELDA): Proceedings of the 2000 IEEE international symposium on electronics and the environment, San Francisco, CA, pp. 99-104.

[16]

Guinée, J. B., Gorree, M., Heijungs, R., Huppes, G., Kleijn, R., van Oers, L. et al., (2002): Handbook on life cycle assessment-operational guide to the ISO standard-, Kluwer Academic Publishing., Dordrecht, The Netherlands

[17]

McAloone, T. C. (2000): Industrial Application of Environmentally Concious Design, Professional Engineering Publishing, London.

[18]

Fitzgerald, D. P., Herrmann, J. W., Sandborn, P. A., Schimdt, L. C. and Gogoll, T. H. (2007): Design for Environment (DfE): Strategies, practices, guidelines, methods and tools, In Environmentally Conscious Mechanical Design(Ed, Kutz, M.) John Wiley & Sons, New Jersey.

[19]

Knight, P. and Jenkins, J. O. (2009): Adopting and applying eco-design techniques: a practitioners perspective, Journal of Cleaner Production, 17, (5) 549-558.

[20]

Hauschild, M., Jeswiet, J. and Alting, L. (2005): From Life Cycle Assessment to Sustainable Production: Status and Perspectives, CIRP Annals - Manufacturing Technology, 54, (2) 1-21.

[21]

Swiss Centre for Life Cycle Inventories, Ecoinvent, Available at: http://www.ecoinvent.ch/ [Accessed 8 June 2010].

[22]

Granta Design Ltd. (2010), Available http://www.grantadesign.com/ [Accessed 1 July 2010].

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Subramani, A. K. and Dewhurst, P. (1991) Automatic generation of product disassembly sequence, CIRP Annals Manufacturing Technology, 40, (1) 115-118.

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[23] Optima Energy Management, Available at: http://www.optimaenergy.net/ [Accessed 20 April 2010]. [24] Boyd, G., Dutrow, E. and Tunnessen, W., (2008): The evolution of the ENERGY STAR® energy performance indicator for benchmarking industrial plant manufacturing use, Journal of Cleaner Production, 16, 709-715 [25] Kissock, K. J. and Eger, C. (2008): Measuring Industrial Energy Savings, Applied Energy, 85, (5) 347-361. [26] Harvey, L. D. D. (2009): Reducing energy use in the buildings sector: measures, costs, and examples, Energy Efficiency, 2, (2) 139-163. [27] Gutowski, T., J. Dahmus, and Thiriez, A., (2006): Electrical Energy Requirements for a Manufacturing Process. Proceedings of 13th CIRP International Conference on Life Cycle Engineering, Leuven, Belgium, 623-627. [28] Herrmann, C. and Thiede, S. (2009): Process chain simulation to foster energy efficiency in manufacturing, CIRP Journal of Manufacturing Science and Technology Life Cycle Engineering, 1, (4) 221-229. [29] Seow, Y. and Rahimifard, S., (2010): A Framework for Modelling Energy Consumption within Manufacturing Systems, Proceedings of 43rd CIRP International Conference on Manufacturing Systems, Vienna, Austria. pp. 222-227. [30]

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Eco-Design Tool to support the Use of Renewable Polymers within Packaging Applications James Colwill, Shahin Rahimifard, Allen Clegg Centre for Sustainable Manufacturing and Reuse/Recycling Technologies (SMART), Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University, UK

Abstract Bioplastics derived from renewable polymers such as sugars, starches and cellulose, have attracted significant interest from companies looking to reduce their environmental footprint. New production capacity and improved materials have resulted in their increasing adoption for mainstream consumer products packaging. However questions remain regarding their overall environmental benefits and how the maximum environmental gain can be achieved. These uncertainties highlight the need for a decision support tool to aid the packaging design process. This paper examines the issues surrounding bio-derived polymer use and discusses the development of an eco-design tool to assist in their rapid and efficient adoption. Keywords: Eco-design; Renewable Materials; Biopolymer Packaging

INTRODUCTION

Unfortunately, the current level of scientific understanding of the environmental benefits achievable from these materials, particularly post gate (use and end of life stages), is inadequate or simply nonexistent [4]. This is supported by the findings of a review of 25 published LCA reports from the academic and commercial literature, spanning the period between 1997 and 2009, Figure1 [2]. Specific questions, regarding the impact on food production, genetic modification, consistency of supply, technical performance, contamination of conventional polymer waste streams and biodegradability, remain unanswered. Whilst government support for renewable materials is desirable if not essential, caution should be taken to avoid the premature or inappropriate adoption of a particular BDP or technology, which in turn could hinder future development, particularly if the environmental claims are later proven to be false or vacuous. This paper begins with an overview of the main BDPs used as packaging, their key applications and potential market growth. It then considers the various issues that surround the use of BDPs and identifies the key barriers and drivers to wider and greater adoption. In light of the growing need for sustainable manufacturing,

of Studies 

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The annual global production capacity of bio-derived polymers (BDPs) has been forecast to grow annually by 37 percent, reaching 2.33 Million tonnes by 2013 [1]. This rapid growth has been sustained as BDP packaging markets expand from the early adopters producing niche and synergetic items such as organic drinks and whole foods, to global mainstream products and brands such as cola, crisps and chocolate [2]. A key driver of this success has been the desire for environmentally friendly, sustainable packaging and the belief that BDPs meet this requirement. To a large degree this view has been fostered both from the claims made by manufacturers, and the obvious emotional attraction towards a material with a natural, renewable pedigree. More recently this market demand has been further encouraged by various government initiatives which promote and support the procurement of ‘bio-based’ and ‘sustainable’ products [3].

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Figure 1: Findings of LCA study against review criteria (2009) [2]. we then consider the range of eco design and decision support tools that are available to industry to assist in the identification, selection, application and assessment of BDP packaging. This study, through an assessment of the key strengths and weaknesses of each tool, aims to identify the key unfulfilled needs in this area and thus establish both the need and the framework for the new eco-design tool. The paper concludes with an overview of this new tool, its proposed structure, and how this will meet the unfulfilled needs of industry. 2 2.1

BIO DERIVED POLYMERS IN PACKAGING Key BDPs: Their Origins and Evolution

Whilst a small number of BDPs, such as cellulose film, have maintained a commercial presence in the packaging market, the resurgence in interest of BDPs as a viable alternative to conventional polymers began during the 1990’s in response to increasing pressure from both consumers and government to reduce the environmental impact of packaging culminating in the EU directive 94/62/EC on Packaging and Packaging Waste [5]. Whilst the direc-

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_28, © Springer-Verlag Berlin Heidelberg 2011

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tive and subsequent legislation does not promote the use of bio derived materials over conventional ones, it obligates companies to formally consider the environmental aspects of their packaging designs in addition to the commercial and technical ones.

Polymers extracted from biomass

BIO-DERIVED POLYMERS

Starch Lignocellulose

It is an expected and an accepted limitation of this review that as a material becomes established, i.e. first generation bio-polymers such as cellulose film and foamed starch chips, it will probably become less noteworthy of comment and so its frequency will decline even if use actually increases. Also, the results recorded launch activity, not ongoing use, and so should not be viewed accumulatively. When these new introductions are plotted against their launch dates, a picture emerges of a gradual annual growth in use, see Figure 3 lower line. However, this only shows the frequency of product launches and does not consider the individual significance of each new introduction in terms of the BDP used. As it is not possible from these announcements alone to ascertain accurate data with regard to the volume of sales, material use, specific barrier properties, transmission rates etc, a simple weighting factor was applied instead. The factor used was allocated based on five easily assessable key criteria: Brand awareness, Company size, Launch market size, Potential market size and Application complexity. A weighting factor was applied for the first four criteria of 1x for local, 3x for national or 5x for global. For the fifth criteria, application complexity, a weighting of 1x for low complexity, 3x for medium (thermoformed/ laminated), 5x for high complexity (injection molded, blown, high barrier). Once applied the sum total was divided by five to a final value of between 1 and 5 for each application. When this data is re-plotted with the weighting factor it shows a much sharper growth curve (figure 3, upper line) particularly during the last two years, which might indicate that BDPs are entering a new accelerated growth phase. This would lead to higher growth than other data has previously suggested, such as BDP production capacity investments [1], which forecast growth by 2020 to reach 3.5 Mt capacity and earlier projections which forecast volumes of between 2.5Mt and 4.17Mt by 2020 [6]. In addition, when the two graphs are compared it suggests that in addition to a general increase in use, these new BDPs are gaining wider market acceptance, moving from niche, synergetic applications such as organic, fair-trade and health food products to mainstream, high profile brands.

Modified starch-based Modified cellulose-based Modified lignin-based

Polymers synthesised from bio-derived intermediates Polylactide (PLA) BD-polyolefins (e.g. polyethylene) BD-polyamides (e.g. nylon) BD-polyurethanes BD-polyesters

Packaging Applications Study

To understand how the application of BDPs for packaging has evolved, an online review of published announcements for new product launches in BDP packaging was undertaken. This included searching the websites and press archives of all the main BDP manufacturers, associated trade press and the key industry bodies, associations and institutes for; the environment, packaging and plastics industries, dating back to 2004.

Proteins

Polymers produced by microorganisms

 

2.2

Lipids

Polysaccharides

The first generation of BDPs were limited to low technical performance applications, in the past decade a new generation of materials have been developed, capable of being used for processed, long shelf life products such as crisps, cereals, chocolate and beverages. Figure 2 identifies the key BDPs used in packaging and the main source/route to production [5]. As their availability and costs have improved, so their uptake has increased. The most commercially successful of these to date are PolyLactic Acid (PLA) and Bioethylene based PE and PET. Both these materials have been used in full or in part across a wide range of pack formats and processes such as; stretch blow molded bottles, injection molded components, thermoformed trays and flexible films (including high barrier laminated films for coffee and crisps).

Bacterial compounds Polyhydroxyalkanoates (PHAs)

Figure 2: Overview of principal bio-derived polymers (adapted from [6]). Flows in bold indicate routes to the principal BDPs. New Introductions of BDP Packaged Products 70 60 50 40 30 20 10 0

2004

2005

2006 2007 Year Introduced

2008

2009

Figure 3: New Introductions of BDPs based on company announcements from Jan 04 to May 09 - Colwill et al [1] 2.3

Capacity and New Investments

In anticipation of the future demand, a number of companies have invested in plant for the production of BDP’s The annual global production capacity of BDPs, based on company announcements, is now forecast to grow from 0.36 Mt (million metric tonnes) in 2007 to 2.33 Mt in 2013, an annual increase of 37 percent [1]. Figure 4 shows the projected growth in the production capacity of Class A and Class B BDPs. Class A BDPs include PLA, PHA. TPS and cellulose, whilst class B BDP’s are those which are identical to conventional polymers apart from the original monomer source, such as PE and PET derived from bio-ethylene. 3 3.1

THE KEY ISSUES TO USING BDPS IN PACKAGING Drivers and Barriers

There are a number of factors which to a greater or lesser degree have had or will continue to have an influence on the development, uptake and growth of bio-derived polymers within the packaging

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Factors influencing BDP adoption

BDP Production Capacity Increases

3000

Class A BDPs

2500

Class B BDPs

The limited availability and increasing cost of fossil resources (oil and gas) and the need to secure National energy supplies.

Positive

Kt/PA

3500

2000 1500 1000

2003

2007

2009

Year

2011 2013 2020 [ ------- Projected -------]

BDP Production capacity Increases Figure 4: Global production capacity of bio-derived polymers based on company announcements up to May 2009 [2]. sector. The most significant of these are listed in Table 1, however whilst many of these have a foreseeable resolution as technology or commercial advances are made, there are two key issues that in our view will require a much more substantial and collaborative effort to resolve, these are: 



Development of alternative feedstocks to avoid direct competition with food production (materials and land use) in order to provide a sustainable and scalable polymer source. Development of new technologies and infrastructure to enable the conservation of this resource and to avoid contamination and disruption of existing conventional polymer recycling.

In terms of positive influences, policy and government initiatives such as the EU’s “Lead Market Initiative”, the ADEME’s “Bioproducts Guidebook for Greener Procurements” and the USA’s “Federal Bio-based Products Preferred Procurement Program” have the potential to be a major influence on BDP growth and uptake. The other major driver will be cost and performance parity as the gap between BDPs and conventional plastics narrows. 3.2

Packaging Design and Development

The varied and cross departmental responsibilities for packaging functions within a business add yet further complexity to the packaging development process, (Figure 5). Whilst the majority of functions are clearly aligned to a particular hierarchical structure, e.g. Finance and Accounting, Sales and Marketing, Engineering and Production, packaging impacts on almost all aspects of the business and often the control hierarchy will change on a regular basis as a means to adjusting an imbalance caused by that particular departmental bias, (finance, marketing, operations etc). This has often resulted in the packaging function ‘ownership’ being rotated through different business functions on an almost cyclical basis, Manufacturing, Marketing, Finance/Purchasing etc. One approach some companies have taken is to break the packaging functions into three separate groups as shown in Figure 5. This allows each function to be more closely aligned with the most appropriate business functions. However this then creates the problem of ensuring that communication and cooperation between the groups maintains the skills and potential of the whole, particularly important in the development of new packaging.

Consumer demand driven by the growing awareness of the need for sustainable management of natural resources. Other factors include: Organic and green brands, Retailer pressure, anti litter action and increasing environmental problems and severe climate changes. Higher costs and more complex supply chains, including capacity limitations and a restricted supplier base. Technical performance limitations compared to conventional polymers. Lack of clarity and quality of data on the overall environmental impacts. Other factors include: Greater recycling of conventional polymers and problems of waste stream contamination by BDPs, Land availability and food production. Bio-Fuel developments compete for limited feedstock resources but also provide volume, a secure market, and commercial scale.

Both

0

Negative

500

Policy and legislation, particularly within the area of climate change, sustainability and economics.

Pressure groups can influence public opinion and government policy. However, views are polarised for and against at present. New technologies such as genetic modification and nano engineering bring huge potential benefits but also huge potential risks. Tend to polarise opinion particularly within an already sensitized and sceptical public.

Table 1: Barriers and Drivers to increased BDP adoption. It is clear that the decision to adopt BDPs for packaging within an organization will not be restricted to any one group, function or skill set. For the tool to be fully inclusive it needs to engage actors at all levels and stages depending on their abilities and needs. This is true not just within the company but also throughout the wider supply chain and where possible engaging the consumer. 4

AN OVERVIEW OF CURRENT ECO DESIGN TOOLS

A study of academic papers and industrial reports was carried out across a range of eco-design tools. This included individual [7, 8] as well as multiple [9,10] tool reviews. The main focus was on packaging but general eco-design tools that could be used for packaging design were also considered. The review focused on a number of criteria, four of which have been selected for comparison in Table 2 and Figure 6. These are: Sustainability Considerations (Which of the three key pillars of Sustainability, Environmental, Economic and Social, were considered by the tool), Life Cycle Approach (What life cycle stages were considered), User Guidance (Which of the 5 guidance criteria listed were output to the user) and User Inclusiveness (of the user groups listed, how many would the tool be useful and accessible to). In all, 40 tools were assessed using a combination of previous design tool studies and individual tool reviews. The main criteria and sub divisions are listed below in Table 2. It is clear that significant interest exists, within a range of industries operating at various stages along the supply chain, in the development of tools for the purpose of improving the environmental design of packaging as well as using renewable materials.

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163

High

Business Functions Low

Support

P   otential Business Impact

C   ost of Change

Packaging Management Short term focus – Current

Tactical Packaging Development Mid term focus – 1-2 year

Strategic Low

Packaging Research Long term focus – 3+ years

Engineering

Operations

Installation, Maintenance, Repair, Improvement

Efficiency, quality, production cost, output, Capacit

Quality Control

Logistics

Efficiency, Damage, Supply, Storage.

Control, Testing, Compliance

Purchasing

Supply, Costs, Quotes, Availability, Control.

NPD Formulate, Specification, Prototyping.

Finance

Costings, Justification, Capex, Approval.

Marketing / Sales Product, markets, consumer, formats.

Legal / CSR

Local M   anagement and Control

Packaging Functions

Legislation, compliance IP protection, enforcement

High

Central

Figure 5: Key functions of a packaging dept and their relation to other key business areas. 5

FRAMEWORK FOR THE TOOL

5.1

Feature

Introduction to the tool

The development of the proposed tool arose from the recognition of the necessity to ensure that the limited capacity of bio-polymers needs to be directed towards applications where the greatest overall environmental benefit can be achieved. It was envisaged that a tool which could help achieve this through the appropriate selection and application of materials within the pack design and development process, would be widely welcomed by industry. [11]. It is also clear that a direct comparison of BDPs with their conventional counterparts would be misleading as to the future potential that could be achieved once the BDP industry and markets mature. The ability of the tool to evaluate the pack based on future potential, as well as current performance, is essential if it is to play a strategic role [12]. 5.2

Key requirements of the tool

The requirements for the eco-design tool were identified from both a literature review and through industry consultation. Six key requirements are listed in Table 3. The features highlighted in bold are those which are considered to be absent or inadequately provided for in existing tools. These are supported by similar findings in a recent Canadian Government report [10].

Assessment Criteria Sustainability Considerations: Environmental (En), Economic (Ec), Social (So) Life Cycle Approach: Full (C2C), Cradle to Gate (C2G), Gate to Cradle (G2C), None User Guidance: Descriptive, Selective, Prescriptive, Assessment, Comparative

Should consider performance across the whole life cycle, cradle to cradle.

Sustainable Focus

The tool should consider all three pillars of sustainability: Social as well as Environmental and Economic.

Strategic and Tactical

The tool should support strategic decision making looking at future performance as well as current properties and performance.

Holistic and Inclusive

Should be usable and provide guidance across the whole supply chain, including consumers.

Total Stage Support

Should provide support at each stage of the design / development process through a series of individually targeted but connected tools.

Feedback

Tool should provide feedback which allows progress to be measured and improved.

Table 3: Key features, requirements and intended users of the tool. 5.3

Proposed Structure for the Packaging Eco-Design Tool

The tool aims to support the decision process at three different levels depending on the expertise of the user, availability of input data and required detail of output data as shown in Figure 6. This will include; type of application or product to be packaged, selection and use of the BDP material, pack construction, manufacturing process, distribution and retail methods, consumer use and ‘end of life’ management.

En 20 50.0%

En & Ec 13 32.5%

None 16 40.0%

C2G 6 15.0%

G2C 11 27.5%

C2C 7 17.5%

The three separate but interlinked tools, which can be used independently or in combination, are as follows:

1 21 52.5%

2 18 45.0%

3 or 4 1 2.5%

all 5 0 0.0%

Assesses the potential for including BDP packaging as part of the company’s overall packaging / corporate sustainability strategy:

SC 5 12.5%

SC&C 0 0.0%

User Inclusiveness: Specialist Business 24 11 Specialist, Bussiness, Supply Chain (SC), 60.0% 27.5% Supply Chain & Consumer (SC&C)

En & So En, Ec & So 6 1 15.0% 2.5%

Requirements

Full Life Cycle Perspective

Table 2: Results of Ecodesign Tool Study against review criteria.

EcoD2 Part 1 - Justification Level

Method: A series of questions, in the form of a decision tree, are asked which highlight the key threats and opportunities, strengths and weakness for the adoption of BDPs by the company, both short and long term. Result: The results from the questions will give a top level guidance on how the company should proceed. This might include statements such as:

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Life Cycle Design - Methods and Tools



BDPs are not compatible with your current business practice and strategy.



BDPs will provide significant benefits but not within current cost limits.



BDPs are a viable option for your company, proceed to next level.

EcoD2 Part 2 - Specification Level Identify specifically which BDPs will meet the essential and desirable requirements of the specific application regarding technical, commercial and operational feasibility: Method: A technical relational database of all BDPs commercially available will allow specific requirements to be searched and the suitable polymers to be identified. Each of the key known factors can be entered via a series of blank forms or lists, e.g. Barrier, Strength, Elasticity, Compression, Melt temperature, Process etc.

logical therefore that the packaging should reflect those product values. The category manager of the retailer and the marketing director of the manufacturer/supplier arranged a working meeting to discuss and agree a way forward to achieving this goal. During the meeting the Eco-design Tool (EcoD2) Part 1 was used to investigate whether BDPs might provide a viable packaging solution. EcoD2 Part 1 - Justification for Using BDP Packaging. With only a limited time available a quick answer was required to be derived from information that was readily available to the two ‘high level’ experienced but not technical business people. Method: The company’s Marketing director accessed the tool online to assess the suitability of BDPs as a means to package their product in a ‘carbon neutral’ way. Following a decision tree based question and answer process, he input top line information about the company, its product and overall aims and objectives, a process that took approximately 10-15 minutes. Result: The tool provided guidance as to the suitability of BDPs, the main implications of its use and recommended next steps on how the company should proceed: 

Based on the product’s brand values, market positioning, premium price, technical/performance requirements and potential end of life disposal options, there is a strong possibility that BDPs could provide a suitable packaging medium for this product



The BDPs which meet the product requirements and are within a viable geographic range would be Starch, Cellulose or PLA based. Option buttons would be provided which would allow the company to produce a chart comparing specific properties of these ‘base’ materials on factors such as cost, bio-degradability and technical properties. A list of suppliers could also be generated within a given geographic range.



The suggested next steps, assuming that the commercial and technical requirements fell within the given range, would be to select and contact the suppliers of these materials initially with a specification / brief to be prepared from the information added to the system so far and to be further populated by the technical and operational staff within the two organizations.



The specification is sent to the supplier and linked to the tool. The supplier’s response is entered into the tool online. This allows comparisons between the different supplier/material options to be compared.

Figure 6: The relationship between User time and skill levels with the three separate Tools parts 1 - 3. Result: The results from this stage will be in the form of single datasheets and comparative performance graphs to include: 

Data sheet for each BDP that meets or exceeds entered criteria.



Multiple BDPs can be plotted against single or multiple criteria.



Potential future scenarios can be used to give a predicted performance potential.

EcoD2 Part 3 – Comparison Level Compares different pack concepts across a range of criteria and supports the final selection process as part of existing new pack development procedures. Method: Each concept is measured in terms of its material content, material type, performance, size, dimensions, weight and key features. These are input into a program via a menu system which performs the necessary calculations. Result: The final concepts will be measured in terms of their individual material components, total pack performance, construction costs, cube, environmental footprint etc. The results from this stage will be in the form of single page report that summarises the key benefits, costs and performance of each concept. 6

CASE STUDY – A BAG FOR ORGANIC SALAD

The following example illustrates how this proposed eco-design tool might have been used during the decision, design and development process for a possible packaging development project. We created the following scenario as the basis for the case study: A company (UKCM) supplies a leading UK supermarket with pre-washed mixed organic salad. Both the manufacturer and retailer had been meticulous in ensuring that the product meets the highest standards of purity, quality and environmental performance. It was desirable and

EcoD2 Part 2 - Specification Level In order to complete the specification, the technical/packaging manager/technologist identifies specifically which commercially available grades of BDPs from which suppliers meet the technical and performance product requirements. The materials that fulfill these needs are added to the specification. Method: A technical relational database of all BDPs commercially available allows for specific requirements to be searched and the suitable polymers to be identified. Each of the key known factors can be entered via a series of blank forms or lists. e.g. Barrier, Strength, Elasticity, Compression, Melt temperature, Process etc. Result: The results from this stage will be in the form of datasheets and comparative performance graphs. In addition the qualifying materials and supplier information can be transferred from the database to the specification sheet for transmission to the supplier. This can also be used to automatically request quotes, technical data and trial sample materials. EcoD2 Part 3 – Comparison Level Following initial trials of the different materials, the comparison tool is used by the designer to compare the different pack concepts

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165

across a range of criteria and to use this data to support the final selection process as part of in-house new pack development procedures. The outputs of this information can be stored and made available to consumers via the tool or other medium such as the retailer’s website.

ing for packaging will be a significant step towards achieving these goals.

Method: Each concept is measured in terms of its material content, material type, performance, size, dimensions, weight and key features. These are input into a program via a menu system which performs the necessary calculations.

[1]

Shen, L., Haufe, J., Patel, M. (2009): Product overview and market projection of emerging bio-based plastics, PRO-BIP 2009, Group Science, Technology and Society (STS), Copernicus Institute for Sustainable Development and Innovation Utrecht University.

[2]

Colwill, J et al (2009): Opportunities for bio-polymer resource conservation through closed loop recycling, in: Proceedings of GPEC 2010 on Sustainability & Recycling: Raising the Bar in Today’s Economy, Orlando, Florida USA.

[3]

Skibar W., Grogan G., Pitts M., Higson A., (2009): Analysis of the UK Capabilities in Industrial Biotechnology in Relation to the Rest of the World, a sector assessment for the (IB-IGT) prepared by Bioscience for Business KTN, Chemistry Innovation KTN and the NNFCC.

Whilst the growth and development of bio-derived polymers has continued to gain momentum over the past few years, there is a clear danger that this could stall if confusion regarding their overall environmental impact is not removed. A number of methods for categorizing BDPs have been suggested, such as by feedstock type or production method, however in terms of application and end of life management there are two main divisions: Class A, unconventional polymers extracted or synthesized from renewable feedstock but not compatible with conventional plastics and Class B, conventional polymers synthesized from bio-ethylene e.g. polyethylene and PET. It is these former class A bio-polymers, such as PLA, Cellulose, PHA and TPS, that require further investigation in this area in order for them to achieve their environmental potential.

[4]

Song, B., Lee, R.J., Lu, W.F. (2010): A Study on the EcoPerformance of Plastics in the Injection Molding Process, Proceedings of 17th CIRP International Conference on Life Cycle Engineering, Hefei, China, 180-185.

[5]

European Parliament and Council Directive 94/62/EC of 20 December 1994 on packaging and packaging waste, Accessed online at http://eurlex.europa.eu/LexUriServ/LexUriServ.do?uri=CONSLEG:1 994L0062:20090420:EN:PDF

[6]

Quieroz A.U.B. and Collares-Quieroz F.P. (2009): Innovation and Industrial Trends in Bioplastics, Journal of Macromolecular Science, Part C: Polymer Reviews 49 65-78.

In parallel with the growth of BDPs, there has been the pressure on companies to reduce their manufacturing environmental footprint particularly that associated with their packaging. To-date this has focused primarily on waste reduction and recycling and in some instances materials substitution, such as replacement of PVC with PET. As a result, a number of guides and tools have been developed to assist companies in achieving these goals; including Life Cycle Assessment, Retailer Scorecards and Green Design Guides. However these guides tend to be limited in the guidance that they give, strategic and early design stage use, the range of impacts measured, the cost and complexity of use and/or the over simplification of the results. In particular for BDPs, it is important to consider the likely future impacts as technologies, costs and methods advance.

[7]

Crank, M., Patel, M.K., Marscheider-Weidemann, F., Schleich, J., Hüsing, B., Angerer,G. (2005): Techno-economic feasibility of large-scale production of bio-based polymers in Europe. Report No. EUR No: 22103 EN, Catalogue (OPOCE): LFNA-22103-EN-C.

[8]

Walmart (2009), Sustainable Product Index: Fact Sheet, accessed online at www.walmartstores.com/Sustainability/9292.aspx, 5th October 2009.

[9]

Huo, L., Saito, K. (2007): Concept Identification and Implementation of Sustainable Packaging Systems, Journal of Packaging Science Technology, Vol. 16 No. 4 P269-281.

[10]

Five Winds International (2008): Inventory of Sustainable Packaging Initiatives and Proposed Approach to Develop Sustainable Packaging Guidelines, prepared for the extended Producer Responsibility Task Group CCME (Canadian Council of Ministers of the Environment).

[11]

Novkov, S. (2008): Sustainability Management of Industrial Enterprises Advanced Concepts, Techniques and Tools, presented at the 5th International Scientific Conference ‘Business and Management’ Vilnius, Lithuania, 16-17 May 2008.

[12]

Sonneveld, K., James, K., Fitzpatrick, L., Lewis, H., (2005): Sustainable Packaging: How do we Define and Measure It?, presented at the 22nd IAPRI, Symposium, Campinas, Brazil, 22-24 May 2005.

Result: The final concepts will be measured in terms of their individual material components, total pack performance, construction costs, cube, environmental footprint etc. The results from this stage will be in the form of single page report that summarises the key benefits: environmental, commercial, social and physical performance for each concept. In addition, comparative charts and graphs can be produced for each of these key criteria. 7

8

SUMMARY AND CONCLUDING DISCUSSIONS

As packaging is a multi disciplinary function that extends across the majority of traditional business departmental boundaries, it is essential that this tool provides a mechanism for a wide range of users with different skills and requirements to input into and benefit from its use. Furthermore, the use of the tool should extend beyond the traditional business operations and be available to the whole supply chain. In particular the information should be available to the consumer to enable them to make informed choices about the products they buy which in turn will drive further environmental investment and development by industry. It is clear therefore that a holistic approach is needed to eco packaging design if the future challenges of sustainability are to be achieved. It is also clear that better guidance at both the strategic and tactical level on the selection and use of bio-derived polymers in packaging applications is required by industry to avoid ‘green wash’ and ensure the greatest environmental, sustainable and ecological return is achieved from this renewable but ultimately finite resource. The eco-design decision tool which we are develop-

REFERENCES

State-of-the-art Ecodesign on the Electronics Shop Shelves? A Quantitative Analysis of Developments in Ecodesign of TV Sets 1

2

Casper Boks , Renee Wever , Ab Stevels 1

2

Department of Product Design, Norwegian University of Science and Technology (NTNU), Norway 2

Faculty of Industrial Design Engineering, Delft University of Technology, The Netherlands

Abstract From 2005 to 2010, environmentally relevant data was collected on mainstream television sets to select the yearly EISA Green Award winner. As the sets represent state-of-the-art developments in application of ecodesign principles, the data is used to sketch progress in ecodesign application in mainstream development of television sets. It is concluded that improvements in energy consumption were substantial, fuelled by application of new physical principles, from CRT to LCD and plasma, to LED. This has also enabled thinner screens, lower weight, and more efficient product architecture and packaging. For chemical substances and recycling implications, progress is less evident. Keywords: Progress in Ecodesign; Environmental Assessment; Environmental Benchmarking; Energy Consumption

1

INTRODUCTION

The European Imaging and Sound Association (EISA) is an association of 50 special interest magazines from 19 European countries. EISA started in 1982 when the editors-in-chief from five European photo magazines came together to select “The Camera of the Year” for the first time [1]. Since then, EISA has evolved to the organization as it is known today, perhaps best for the European EISA Awards. In addition to many other technological awards, each year awarded during the IFA fair in Berlin [2], the main electronics fair in Europe, EISA gives, since 2005, the EISA Green Award to a television set which is environmentally superior to competing products. These products are selected and entered into the competition by electronics manufacturers themselves and can therefore be assumed to be the state-of-the-art in ecodesign at the time of entering the competition; since each product needs to be available on the European market in at least 10 countries, the products can also be assumed to be commercially viable. EISA’s first Green Award went to a conventional, bulky analogue television, but later, flat TVs became common and although a few years back, there was a serious attempt to shelter both Plasma and LCD under the same umbrella; the winner ultimately was always LCD-based. In 2009, the winning design was based on LED technology for the first time. Clearly, in only 6 years, the state of the art in ecodesign of TV sets has progressed enormously. According to the EISA Green Award Jury, the most recent winner of the Green Award is, for the first time, a truly ecodesign product (Figure 1). 2

they have designed, this data provides a unique source for charting developments in ‘commercially viable ecodesign’ of television sets in this period. The paper has three aims: 

To quantitatively illustrate the development of ‘commercially viable ecodesign’ since 2005. Based on this historical data, this paper points out the main developments over time by illustrating how and to what extent progression has been made on aspects of energy consumption, material application, packaging, product chemical substances, and end-of-life related characteristics such as disassemblability.



To discuss the challenges in the relative assessment and weighting of different aspects of environmental performance of products, especially within a limited time frame.



To reflect on the relevance of the findings for ecodesign and green supply management in general,

The paper is structured as follows. Section 3 addresses background information on the measurements. Section 4 presents, for each of the main criteria, the developments of the various product characteristics over time. In section 5 these are further discussed and section 6 concludes with observations about progress in ecodesign of television sets in the period 2005-2010.

GOAL OF THE PAPER

This paper, written by two EISA Green Award jury members, is based on the collected data from 2005-2010, on basis of which the EISA Green Awards have been awarded. This data consists of product data relevant for the determination of the products’ environmental performance. For each year, data from 3 to 6 television sets are available with a total of 27 sets over 6 years. Based on the supposition that OEMs indeed enter into the competition the most environmentally friendly, commercial product

Figure 1: EISA Green Award winner 2010.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_29, © Springer-Verlag Berlin Heidelberg 2011

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Life Cycle Design - Selected Applications ENVIRONMENTAL ASSESSMENT

For the EISA Green Award jury, the main challenge has been to develop a scorecard that does justice to the environmental performance of the candidate products, given the limited time available; jury membership is unpaid resulting in a maximum of a few days available for the job. In 2005 it was decided that the environmental performance of the products would be most fairly represented by scoring scheme addressing a number of categories representing environmental focus areas such as energy consumption, material application, recyclability, chemical substances, and packaging. Each year an additional category, the so-called bonus category, was added to allow the jury to award bonus points for smart design solutions reflecting an innovative ecodesign spirit. It was well realized that the environmental performance as determined by the jury would never 100% reflect a true scientific environmental assessment based on Life Cycle Assessment (LCA). The rationale for this decision was on the one hand a lack of time, data and resources to perform such an assessment, and on the other hand the opinion that superior environmental performance cannot always be covered 100% by LCA, and is for example also partly determined by a positive, innovative environmental attitude. Such an attitude might at first not result in the lowest environmental performance for a certain criteria, but might for example have positive rebound effects over time, or positively influence user attitudes and behavior. This way, ‘green’ was to reflect a fair balance between different understandings of what ‘green’ is. The presence of the EISA Green award can be regarded as recognition for environmental excellence in product design, the importance thereof, and may even contribute to stimulating environmental innovation in design of consumer electronics. Of course, having an environmental award for a large, energy consuming piece of equipment mainly offering ‘mere entertainment’ may by some be considered as a contradiction in terms. It can be argued that the design and sale of such products are contrary to basic ecodesign principles, in particular dematerialization (“the best TV is no TV at all”). However, the presence of these products on today’s market is a fact of life, and it is not within the scope of this paper to discuss today’s negative effects of ‘consumerism’ Each year, only television sets of a certain screen size are eligible for the EISA Green Award; sets with this screen size reflected what were at that time considered mainstream products aimed at a large share of the market (not high- or low-end products), and not specifically aimed at environmentally very conscious users. The Award as such does not aim at awarding very basic products with superior environmental but low functional quality. Future EISA Green Awards may therefore take into account more explicit considerations of eco-value (environmental impact per monetary value) [3]. The subsequent subparagraphs discuss in more detail the data collected for the various scorecard items, and reflect on the process for doing so. 3.1 General comments on data collection. A recurring issue has been the comparison of different sized television sets. Each year, contesting OEMs may enter sets in the most commonly sold size range (Table 1). In order to allow for a fair comparison, in practice data has been normalized using the screen surface area as a normalization constant. Year

2005

2006

2007

2008

2009

2010

Allowed set size range

28”-32”

37”-42”

40”-42”

40”-42”

40”-42”

42”-46”

Table 1: Screen size of sets in the competition per year.

Each year, individual product scores for each scorecard were used to determine a score on an interpolated scale from 1 to 5. For each of the five scorecard items weighting factors were assigned based on EcoIndicator’99 calculations, resulting in a total one-figure score determining the winner. Both the scoring system and the data collection process did change to a certain extent over the years, as certain aspects became more or less relevant as technology, legislation and recycling infrastructure changed. This resulted among other things in changing weighting factors. However, for the paper at hand this is not relevant, as the main focus is not the determination of winners, but to discuss the development of environmental performance of television sets over time. For the preparation of this paper, using the normalization constants, it was possible to derive a coherent set of data allowing for fair comparison over time. 3.2 Energy consumption Over the years, a number of observations were made: energy consumption figures for default settings provided by the brands themselves were in some cases not in line with actual measurements for the same settings, which is why the jury performed energy measurements themselves. In some cases, our measurements were considerably above the provided figures, in other cases, measurements were considerably under the provided figures. It was also found that for the best scoring sets, often the most accurate measurements were provided by the OEMs. Consultation with OEMs learned that energy consumption data as provided in official documentation may be much higher than in reality, due to official measurements being done based on maximum power conditions for reasons of safety margins. For measuring the energy consumption, over the years different usage profiles have been applied for comparing scores for individual sets. These usage profiles generally consisted of four hours per day “on mode” in various settings. These settings included standard out-of-the-box settings, vivid or dynamic settings if present (from 2009), so-called ‘dark measurements’, allowing for including for automatic brightness settings (from 2009), and socalled eco-modes (from 2009), and 20 hours in standby. Because the usage profiles have not been consistently the same for year to year as new settings were included (for example, eco modes have only been observed since 2009), Figure 2 displays the development of energy consumption in W per square dm screen size measured using the standard out-of-the-box setting only. For the determination of energy consumption of TV sets, complex standards exist prescribing the required tests. These standards are intended to ensure comparable results from independently executed measurements by different OEMs themselves. As for the EISA awards all competing products can be measured under the same conditions, and only the relative performance is relevant for the determination of the scoring, a simplified approach was utilized by the jury, based on measuring the total energy dissipation over a period of time while displaying the same content. Figure 2 shows that, after an initial increase in energy consumption due to the change from CRT technology to LCD/plasma technology in 2006, the energy consumption has decreased considerably. In addition, the scores for the different entries per year show less variance over time, which indicates perhaps maturing technology and/or toughening competition. However, variance has slightly increased again in 2010, mainly due to one outstanding entry (the eventual winner for 2010) that was able to reduce energy consumption to an impressive 45 W with standard settings, whereas measurements for the other entries were in the range of 80-90 W.

Life Cycle Design - Selected Applications

169 the 40” sets was on average not smaller than the 42” sets. The decline of the volume is not so much due to improvements in packaging technology, but rather due to the maturing of the technology of the TVs themselves. The newer products are likely less fragile, and most importantly, slimmer. As screen size determines to a large extent the height and width of the product, only the depth presents potential for improvement. Figure 5 shows the decline in depth of all packaging (in dm), clearly indicating a substantial reduction in thickness. Also the introduction of the detachable foot (which none of the products had in 2006, but all in 2010) has allowed for packaging optimization.

2

Figure 2: Energy consumption in Watt per dm over time. 3.3 Material application In determining relative scores for the environmental impact of materials for structural elements (such as housings, trays, brackets) that represent the main contribution to the weight of the television sets, weight of the total product has been considered as a guidelines as a more detailed analysis is not possible. This decision was partly based on years of experience at Delft University of Technology and Philips Consumer Electronics with environmental benchmarking of products [4]; this practice, which included both the collection of physical data (kilograms, watts, seconds) and Life Cycle Assessment suggested that the relative total environmental impact of material compositions in this type of consumer electronics products corresponds well with the weight of the products (without packaging).

In terms of packaging technology used, little improvement has been observed over time, as the vast majority of products was consistently packed in the same way, utilizing expanded foam cushioning.

  3

Figure 4: Trend in packaging volume (in dm ) for 40” and 42” sets.

2

Figure 3: Weight in kg per dm over time. Figure 3 shows the development of the minimum, average and maximum weight (per square dm to adjust for the set size differences) of the entered sets over the years. In the three years where the set sizes were stable (2007-2009) a clear decline can be observed. However, the figure suggests that, even when measurements are normalized for set size, an increase in set size may imply no decrease or even an increase in weight per square dm in the first year after the wide-scale implementation of a new technology (2007 and 2010).

  Figure 5: Trend in packaging thickness for flat TV sets 2005-2010.

3.4 Packaging and transport

3.5 Chemical substances

Packaging has mainly been judged on volume efficiency, expressed in both volume index (packaging volume/product volume) and container loading (number of products in a standard 40' sea container), adjusted for different screens sizes. Additional considerations included (the variety of) material use and accessories. As regards packaging, it is interesting to observe two parameters. Figure 4 shows the trend line for the volume (in liters) of the packages of 40” and 42” TV sets over time. Here a clear decline over time can be observed. Interestingly, the packaging for

Although a full Life Cycle Assessment would be preferable to determine the environmental performance on this specialist issue, because of time and data restrictions a more pragmatic way had to be found in order to arrive at a fair comparison. As the jury was mainly interested in relative rather than absolute scores, it was decided that scoring on chemical substances would be done based on size and design of printed circuit boards, and the presence and size of various electric components.

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3.5.1 Size and design of printed circuit boards (PCBs) In practice, up until 2010, most television sets include both traditional PCBs (dominated by sizable transformers and capacitors) and modern PCBs (dominated by ICs (integrated circuits) and SMDs (surface mounted devices)), although there appears to be little correlation between them: using smaller traditional PCBs does in many cases not necessarily mean using larger modern PCBs or vice versa. To arrive at relative one figure scores, the surface area of the PCBs has been measured as a strong correlation appears to be present between size and number/weight of (in particular smaller) components. Due to different chemical composition, traditional PCBs have over the years been attributed double weight in comparison to modern PCBs.

3.5.2 The presence and size of electrolytic capacitors, transformers, and other electric components. Although a relation between PCB size and components is clearly present, differences in number and density of large components such as electrolytic capacitors and transformers do exist. This is why over the years the number of such components of different sizes has been calculated. Analysis of the data does not show a clear pattern over time. The amount and size of transformators on PCBs (environmentally relevant because of high copper content in the coils) have been largely constant over the years, with most sets having 5-9 such components present, with few sets showing 3-4, and negative outliers showing as much as 24 transformators (the latter was seen in 2009). The same impression exists for electrolytic capacitors. Throughout the years, the average number of large ones has been 1-3 components, and on average 16-19 mediumsized or smaller ones. Differences between the best scoring sets in each year have been fairly small as well, though some sets choose different solutions, using several smaller components instead of few large ones and vice versa. This lack of clear distinction between sets has also been the reason why, in terms of relative scoring for the chemical substances scorecard item, the main attention has been paid to PCB size and design as discussed in the previous subparagraph. 3.6 General Product architecture The product architecture scores have been based on a general comparative impression of the sophistication used in the design, taking into account presence and location of the main components, including electronics, speakers, supporting structures and cabling.

2

2

Figure 6: Classic PCB surface area (cm ) per cm of screen size over time. 2

Figure 6 shows the classic PCB surface area per cm screen size, where it should be noted that the similar values for 2008 and 2009 are no mistake in the analysis. It is striking that in 2010 for the first time one of the entries did not give evidence of any classic designed PCB as it only contained modern PCBs.

The most striking development in product architecture in flat screen TV sets has been the reduction in thickness of the screens. This is not only a result of improved technology (i.e. less electronics required) but also a result of lowered energy consumption, which has reduced the need of heat dissipation. As of 2010 the screen thickness has reduced to an extent that a design change can be observed in the housing. The back cover of the sets was plastic for many years, but with the very thin LEDbased screens this was changed to metal covers (steel or aluminum), apparently due to the required stiffness. Over the period studied a clear improvement could be observed with regard to the amount of wiring. Early sets seemed to be the result of a design process where different components were designed separately, and then joined together. In early flat-screens, a ‘spaghetti’ of wiring was not uncommon. For a new technology this is also not surprising. However, over the years a vast improvement has been observed in general product architecture. 3.7 End of life

2

2

Figure 7: Modern PCB surface area (cm ) per cm of screen size over time. Figure 7 shows the same data, but for modern PCBs. The reduction 2 in size per cm screen size for classical design PCBs does not seem to have led to an increase in size for modern PCBs. In fact, the only increase observed (for 2009) corresponds with a period where no reduction in classic PCBs was achieved. Since the average set sizes in 2008 and 2009 were similar (40”-42”), a change in set size can be eliminated as reason for this. It should be noted that in 2010, the largest area score (0.28) for 2010 was observed in the set that had reduced classic PCB area to zero.

The development of applied physical principles (from CRT to LCD and plasma, to LED) has made rethinking of the scorecard criteria for recycling and end-of-life necessary. For LCD sets in the period 2006-2009 there was a clear issue with the back mercury containing lights. Mercury is prohibited by the European Directive on Restriction of Hazardous Substances (RoHS), but LCD TVs are exempted. Nevertheless, the Waste of Electrical and Electronic Equipment Directive (WEEE), which has been implemented in all member states of the EU, requires in its Annex II that mercury containing parts be removed in the end-of-life stage. For all sets this is theoretically possible, but practically not. If the TVs are shredded one cannot recover the mercury, hence the only option would be manual disassembly. However, due to the use of many screws (fairly consistent over the years, between 22-25 on average per set) and also different types of screws (3 to 5) in one TV set, and alternating directions (the set would have to be turned several types to unscrew all layers to get to the back lights), this is economically

Life Cycle Design - Selected Applications

171

not realistic, as it would take more than 20 minutes to perform per set. Also, the return logistics by which the sets arrive at the recycling center would have to be of such carefulness as not to break any of the fragile backlights. Current collection systems do not achieve this standard as economically feasible demercurisation units that can handle large screens including backlight are lacking. However, since all sets show this problem, it has in general not been a major distinctive aspect in the considerations of the jury. As of 2010, all entries have LED-based backlights. Hence this problem no longer occurs. As for ease of disassembly, the jury did therefore not see reason to distinguish the scoring, hence all sets scored equal. However, because there will be a mixed stream of mercurybased LCD TVs and LED-based TVs in future electronics recycling, it would be good if current LED-based TVs themselves would be clearly marked as “mercury free” or “LED-based”. In 2010 this was the case for none of the entries. 3.8 Bonus category and development of environmental features

Figure 8: Last CRT-based design (2005).

In each year, in addition to the more easy to quantify scorecard items, ‘bonus credits’ could be earned if entries gave evidence of smart design solutions, such as related to (but not limited to) inventive approaches regarding product architecture backlights, shielding plates, solutions for smart and safe disassembly, influencing consumer behavior regarding use of various on-modes, et cetera. This was especially relevant in cases where such smart design solutions could not be rewarded through any of the other scorecard items. Credits could also be earned through credible statements about environmental friendly production. Table 2 gives an overview of when new environmentally friendly features became integrated in the contesting sets. Bonus credits were in some cases granted because features were unique for a particular set. Also a number of more general developments have been included. Pictures of insides from the sets have been included to provide a visual impression of efficiency developments over the years. Year

 

Last year with CRT-only designs (Figure 8) Fully flame retardant cabinet

 

Use of water based paints Use of vegetable based inks



From CRT to LCD and plasma; emerging issue with mercury containing backlights in LCD sets



relative ease for the user to make power saving adjustment to default settings

2007

 

Inclusion of automated brightness settings First detachable feet allowing for more efficient packaging

2008

  

Inclusion of (non-automatic) reduced power mode General improvement in printed circuit board design Reduction in screen thickness

2009

 

First LED TV, hence slim design (Figure 10) Still insufficient improvement on mercury backlights in LCD sets

2010

   

Eco settings in the standard out-of-the-box setting Solar powered remote control. Bold rethinking of the total concept. Smart use of a small back panel to cover the electronics is smart (Figure 10).

2005

2006

 

Environmentally relevant design developments



Double function for the standard and wall-mount.

Table 2: Overview of new environmental features in TVs.

Figure 9: First LED TV (2009).

Figure 10: 2010 LED-based Green Award winner. 4

DISCUSSION AND CONCLUSIONS

In the period 2005-2010, environmentally relevant data was collected on mainstream television sets to select the yearly winner of the EISA Green Award. It is argued that the sets can be considered to give evidence of state-of-the-art developments in application of ecodesign principles – otherwise, the competing OEMs would have entered other, or no sets to the competition.

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Life Cycle Design - Selected Applications

The process for collecting the data has been characterised by pragmatism due to the comparative, relative nature of the assessments, and due to lack of time and resources to perform a thorough environmental assessment based on scientific life cycle impact assessment. At the same time, a pragmatic, holistic method has allowed for the inclusion of considerations which are not easily quantified scientifically. One such consideration is progress in product architecture, which reflects a more integrated design approach, which presumably has a positive effect on overall design efficiency leading to environmentally preferred design solutions. Another consideration is the inclusion of bonus credits, which were used to award individual features that give evidence of smart design, but may not show up in the standard scorecard items. To nevertheless improve data collection, from 2011, the jury for the EISA Green Award will cooperate with an established electronics recycler and thus be able to obtain data from material analyses of the shredded printed circuit boards. This process has been used already for the jury evaluation for the EISA Green Award for Mobile Phones, awarded for the first time in 2010, since for this product category environmental impact is to a much larger extent determined by PWB material composition, in particular precious metals and beryllium. The same process for PCBs of television sets will allow for a more precise analysis for the chemical substances scorecard. The data thus collected has been used to sketch an overview of how ecodesign application in mainstream development of television sets has progressed over this period. Summing up the results, it is concluded that: 



 



Improvements in energy consumption have been considerable, since 2007, fuelled by application of new physical principles, from CRT, to LCD and plasma, to LED. The results also show increasingly less variation between brands, suggesting a higher general standard of attention for energy consumption. The successive shifts in technology have also enabled thinner screens, resulting in lower weight, especially from the year after the first implementation. New screen technology has also allowed for more efficient packaging. A clear improvement has been observed related to product architecture. This is partly allowed by using new screen technologies, but it is the impression of the jury that OEMs have become increasingly more successful in applying an integrated design approach, aligning electronic, mechanic and aesthetic requirements rather than addressing these separately. As regards chemical substances and implications for recycling, progress is less evident based on the data available. Whereas printed circuit board design has certainly become more modern, the amount of most relevant components related to the use of chemical substances does not seem to have decreased significantly. Whereas the use of LED technology may have done away with the complicated issue of removal of mercury containing backlights in LCD based sets, there is not yet evidence of a clear brand-wide improvement in attention for disassembly friendliness, give the continuing large number of screws, type of screws, and screw directions still present in most sets.

Reflecting on the relevance of these findings for ecodesign and green supply management in general, a number of issues are relevant. The mentioned improvements are assumed to be partly because of a drive to make television sets more environmentally friendly (whether it be because of legal compliance motives, normal competitiveness, or a more proactive attitude), and partly because of autonomous progress in technology development. What has

been the major factor in general, is unclear. A closer examination of the EISA Green Award winner in 2010 reveals that about half of the items why this TV scores well are related to the smart application of, classical applied ecodesign principles, namely smart design of the electronics, material application, and packaging design. One quarter of the solutions is related to upstream (chemical content) and downstream (recycled materials) green supply chain management, and about one quarter is directly related to applying the latest technology. This last factor has clearly gained importance in the last two years. It may also explain, to some extent, the lack of progress for recyclability and chemical substances as this at least partly due to a design dilemma, where progress in the environmental impact reduction of these focal areas needs to be sacrificed for enabling advances in smart energy and material technology applications. It is also striking that in the latter two areas, differences between brands have become much smaller (possibly indicating a competitive issue) than in the case of recyclability and chemical substances. Over the years, eight brands have participated at least once in the competition, of which five three times or more. The performance of competing individual brands has fluctuated considerably over the years. It took until 2010 for a brand to take its second victory, All winners from the past five years have also been ranked at least once as the worst in another year; in fact, at two occasions the winner scored worst in the year after the victory. As such, television sets clearly have seen an improvement overall, but it is unclear to what extent companies systematically have improved their performance throughout their product portfolio. But it is positive that, for the first time, the 2010 EISA Green Award set showed evidence of an intentional, holistic approach to ecodesign, evident from many details such as the unorthodox product architecture, the solar powered remote control, a double-function stand and wall-mount, and the e-manual. With this approach, the set scored very well on all relevant environmental aspects, and outperforming the competition in particular on energy efficiency. The authors hope that this design will be an inspiration for, and set the standard for future ecodesign of consumer electronics. In any case, EISA itself has indicated that the Green Award has led to increased environmental awareness among its members [5]. 5

ACKNOWLEDGEMENTS

The authors wish to acknowledge the European Imaging and Sound Association (EISA), and in particular EISA Vice-President Han Avôt, for his support for this paper, allowing the use of the data collected during the jury evaluations for the EISA Green Award in the period 2005-2010. It should be noted that the opinions and reflections in the paper are those of the authors only, not necessarily those of EISA. 6

REFERENCES

[1]

http://www.eisa.eu/about.html

[2]

www.ifa-berlin.com

[3]

Pascual, O. and Stevels, A. (2006). Maximizing profitability with ecovalue. Proceedings of Eco Design 2006 Asia Pacific Symposium, Tokyo, NPO EcoDesign Promotion Network.

[4]

Boks, C. and Stevels, A. (2003) “Theory and Practice of Environmental Benchmarking for Consumer Electronics”, Benchmarking - an International Journal, Vol. 10, No. 2.

[5]

Cole, G. (2007) EISA, looking back, moving forward. European Imaging and Sound Association, Lisbao, Portugal.

Simultaneous Application of Design for Sustainable Behavior and Linked Benefit Strategies in Practice 1,2

Johannes Schmalz , Casper Boks 1 2

2

Institute for Engineering Design and Industrial Design (IKTD), University of Stuttgart, Germany

Department of Product Design, Norwegian University of Science and Technology, Trondheim, Norway

Abstract Design for sustainable behavior implies applying design strategies that explicitly take into account human behavior, thereby minimizing user-related environmental losses. In addition, the application of linked-benefit strategies has been suggested to ensure the design of commercially interesting products, linking sustainability benefits to financial, functionality, aesthetical or convenience benefits. However, no case studies have been identified that apply both design strategies in one particular product design. Since a methodology for doing so is lacking, this paper, based on the development of a desk lamp, suggests, discusses, and evaluates possible directions for such an approach. Keywords: Design for Sustainable Behavior; Ecodesign; User-centered Design

1

BACKGROUND

Sustainable design research has until recently mainly focused on the environmental impact of the product itself. End-of-life issues have always played a dominant role, resulting in redesign strategies dominated by material and product-architecture based solutions. Even when the use-phase was concerned, redesign strategies have mainly focused on applying more energy-efficient technologies. Recently it has been realized however that user behavior itself may considerably affect the life-cycle environmental impact of products; For some product categories, around 30 percent of the energy consumption of a product may be due to user-related losses [1]. Consequently, a growing research community is focusing on how to minimize avoidable environmental impacts due to user-related losses [2]. Several design for sustainable behavior strategies have been suggested based on mechanisms such as feedback, persuasion, seduction or automatic control to create desired behavioral change [3-6,8-9]. Commercially available products, and product features using principles of design for sustainable behavior include for example dual-mode flushing buttons, eco-buttons, and television sets with automatic brightness settings. A range of products also exists that remain within the gadget domain. However, a well-researched framework for the development of such products is not yet established, and many design problems are likely to exist for which no obvious design solution exists for altering user behavior. An aspect that may be crucial in developing successful design for sustainable behavior strategies, especially for products where existing habits are not easily broken, could be the consideration of so-called ‘linked benefits’ [10]. This implies searching for design solutions than benefit users and producers in more ways than just providing an environmental benefit; rather, products should offer economical, convenience and emotional (for users) and strategic (for producers) benefits as well.. Designing with that philosophy in mined may increase the chances for products to become commercially successful as a commodity product, beyond the gadget level.

2

GOAL AND APPROACH

Although academic activity in developing design for sustainable behavior methodology is increasing, few practical design projects have been reported on, and none of them explicitly consider linkedbenefit strategies. This paper presents a project where both linkedbenefits and sustainable behavior aspects were to be considered explicitly. This means that "sustainability" was added as a criterion of product development alongside other classical criteria of functionality, profitability, safety, reliability, ergonomics, technical feasibility, and last but not least aesthetics. Although a prototype was developed, the main project goal was not to design a product per se, but to gain experience with this type of design exercise, as a clear cut method for doing so not yet exists. One of the considerations beforehand was whether to use a common or a customized design approach. In order to investigate this further it was decided to take an explorative approach building on existing insights, and to focus and reflect on user-benefits and their possible correlations, and on ways to influence users towards more sustainable ways of use. Accordingly, the paper presents the considerations about the approach that was to be taken parallel to results obtained from following that approach. After careful consideration of various practices to potentially focus on, domestic (desk) lighting was chosen as a theme for this study. Even though lighting on an individual product level may have negligible impact, in broader context it is a huge factor in most energy surveys. At the same time, the environmental impact of domestic lighting heavily depends on user practices in terms of purchasing different types of light bulbs, switching lights on and off, and even ways to discard bulbs. Also, a wide range of design solutions and prices already exist for domestic desk lighting, but no desk lamps were identified featuring multiple design solutions to influence the user towards a more sustainable way of use. Lastly, the emergence of Light Emitting Diode (LED) technology, as an increasingly affordable and environmentally friendly alternative to conventional technologies may open up new opportunities for innovative design.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_30, © Springer-Verlag Berlin Heidelberg 2011

173

174 3 3.1

Life Cycle Design - Selected Applications EXPLORATIVE DEVELOPMENT OF A DESIGN APPROACH

To chart the benefits people may possibly expect from a lamp, interviews were done with 25 subjects in the age between 20 and 65. Issues addressed were awareness of environmental issues caused by lamps, benefits that people expect from a lamp, alternative ways to realize these benefits, anticipated behavior in operating lamps, as well as purchase decision factors. The main findings are summarized below: 

Price was found to be a major factor in considering purchase of a lamp or not. Trade-offs were identified between price and material choice, and aesthetics/exclusivity of the lamp.



Safety was mentioned from two perspectives: lamps/light makes people feeling safer, and lamps should be safe themselves. Adjustment of brightness and direction of light for reasons of adjusting to various activities and/or (desired) atmospheres also came out as an important benefit that the subjects were after.

Regarding sustainability were the subjects partly, but not completely aware of the environmental impacts of lighting solutions, suggesting that even a rather simple product like a lamp may reflect a complex issue for most users. The subjects did in fact prefer sustainable solutions, suggesting that relieving people from the responsibility of environmentally responsible use may be a relevant design problem to address. 3.2

The lamp should be a desk lamp for daily use, in the price range of 50 euro (IKEA 2010 oriented)



It can be used for decorative, leisure as well as professional activities at home (meaning that the lamp can be found on any table or furniture of a household)



The lamp should also allow for use by children

User definition and screening

User interviews were chosen as the most appropriate method to gather more insights in what different user groups expect of a lighting product in terms of functionality and benefits, and to define the target audience for the lamp. Once a target audience would have been chosen, both the behavioral patterns to be analysed and the types of functionality benefits most relevant for this audience would become clearer. A semi-structured interview approach was taken, in order to scan the main issues, opportunities and challenges that would need to be dealt with. It was considered that answers from prospective users may not accurately reflect their actions, behavior or even preferences in daily life. In the context of the project, it was considered that people may often have a false estimation about the environmental impact of their actions [11]. Also, it was considered that it may be challenging to make people talk about what could be regarded as ‘bad’ or undesirable behavior in the given (sustainability) context. To tackle such challenges, some special techniques of interviewing exist, such as first asking people about bad behaviors in general using fictive scenario/personas [12].





Defining the target audience

It was decided that the lamp design should target a broad audience, as relatively larger sales numbers would result in a meaningful contribution to environmental impact reduction, even though the impact of a single lamp is negligible in a societal context. Secondly, a large audience would enable mass production, and reduce production costs (and environmental impacts) per product, and therefore sale price. Thirdly, design solutions for a broad audience were considered to potentially increase the robustness and generalizability of any result that would be achieved. The target audience for the desk lamp project was defined to be young families with working parents in the beginning of their 30’s), living in a European country, and averagely interested in design and aesthetics with an open mind towards unconventional design solutions. This was translated into a design brief including the following design requirements:

Additional functional requirements are presented in Table 4. 3.3

Matching benefits and behavior

As literature does not provide much guidance in how to do so, the central and most challenging (and probably most innovative) step of the process would be the decision how to correlate the linkedbenefits perspective with the insights gained from design for sustainable behavior research. It was decided to categorise the different types of behavior into four ways of influencing the user. Based on recent literature on design for sustainable behavior strategies, where different possibilities of categorization of user influencing have been proposed, this was assumed to provide design suggestions. For the categorization, the subdivision proposed by Wever et al. was used [6]: 

Functionality matching aims at adapting the function of a product in a way that the existing (bad) behavior of the user is absorbed.



Eco-feedback aims at just informing the user about the impacts of his action, leaving the decision to act upon this to the user



Scripting aims at realizing that sustainable use of a product ‘coincidentally’ is the most simple and comfortable way of using the product fort he user, allowing intuitive sustainable use



Forced functionality aims at either making sure that the product is intelligent and adapts to changing environmental conditions, or at designing the product in a way that non-sustainable use is made impossible.

Several other divisions of dividing the freedom of control over behavior between the product and the user have been proposed discussed in recent literature as well [3,13-15] but as a starting point for demonstrating the principle, it was considered sufficient to cover all these divisions with these four umbrella terms. Extending the analysis with more or more detailed strategies, or with a selection of strategies appropriate to the problem at hand, could lead to additional design suggestions and therefore be subject of study, but would not principally alter the approach discussed here. Once a number of potential benefits of a product would have been derived, these could be linked to the mentioned design strategy categories. An important input for this process would be to investigate to what extent the potential benefits would be correlated. To this end, it was suggested to develop a matrix correlating potential benefits, to assess to what extent they might agree or disagree with each other.. Benefits not principally excluding each other could then be allocated to different types of behaviour to get a feeling about their influence on the user and his environment. In the project, this was very helpful to get a keen understanding of the system, and provided input for deriving possible design solutions, presented in Table 1. The solutions are categorized according to each type of design for sustainable behavior strategy discussed above. The solutions were then used to determine what kind of benefits could be expected from them. For example, whether adapting to the surrounding light could be seen as the benefit of being able to dim the lamp (as the adaption to the light could be combined with a dimmer). With the above considerations in mind, a benefit correlation matrix was derived in the context of the lamp project (see sample in Table

Eco feedback

Scripting and/or Steering Forced functionality

Standardized socket

-

…

+

…

-

…

Timeless design Directional light Standardized socket Etc…

-

3.4

+

-

…

…

…

…

emotional

X X X X …

…

X X X …

X …

X X X X X …

X X …

Setting up requirements

List of requirements and wishes to be included in the prototype  Dimming possible  Adaption to light in surrounding  Not attract flies and mosquitoes  Lamp should not get hot  Long durability  Recyclable materials  Directing lighting possible  Switch off when not in use  Not fall down when someone stumbles over the cable  Hinder incorrect and excessive use  Modifications not possible

… …

X

It was expected that within the context of this project, setting up a conventional “list of demands and wishes” might be an insufficient approach for reaching an optimal result. It was expected that, towards a first conceptual design, the balancing act of including as many benefits as possible for as many people as possible, and taking into account aspects as well, would be less straightforward. From the designer it would ask for a keen sense in balancing the different benefits given the challenge of covering all the interactions between the benefits. One aspect of this challenge is the uncertainty whether technical implementation will be possible due to interactions between the different technical and economical requirements.

…

-

X

Table 3: Evaluation of benefits matrix sample.

Etc…

Timeless design

-

-

Price

X

For the desk lamp design project, based on the previous analyses, the following functionalities were selected into the list of requirements for the lamp (see Table 4 – although some of them were included as wishes rather than requirements.

Directional light

Dimming

Price

Dimming

Table 1: Possible design solutions sorted after design for sustainable behavior strategy.

X X

physical

Functionality matching

Possible design solution  Lamp gives only the amount of light that is needed  Lamp is able to adapt to user’s needs  Lamp shows user actual impact caused by using the lamp (energy, CO2, etc.)  User is shown how the durability of the lamp is changing due to his use  Show user how much energy was needed to produce the lamp  Design the lamp in a way, that using it eco friendly is fun/easy, most convenient  Design the lamp that user can show of with the functionalities of the lamp  The lamp burns only when user is around  The lamp adapts to the light around  The lamp gains energy from surrounding without influence of the user

Dimming Price Timeless design Sustainable materials Directional light Standardized socket Etc…

social

Main strategy

economical

2), where benefits as identified from the user interviews were compared side by side, systematically evaluating how each aspects may affect other aspects; thus revealing where win-win situations may occur, and where design trade-offs may need to be made. For example, the inclusion of a standardized socket may reduce the price for the product, whereas adding a dimming option may increase the price.

functional

175

ecological

Life Cycle Design - Selected Applications

…

Table 2: Benefit correlation matrix sample. A next step was included to systematically check each potential benefit according to the effect it may have on economical, ecological, functional/technical, emotional, social or physical performance of the product (see sample in Table 3). This proved to be helpful in balancing the evaluation of including different design features in the final concept. This was mainly done through discussion; for example: including a dimming option may affect price negatively, but may lead to ecological benefits as it may reduce total energy consumption, it would add to the functionality of the lamp, and enable adjusting to the mood a user desires, thus providing emotional benefits. These two matrix exercises provided insights about which dilemmas and challenges should be addressed towards conceptualization, and as such guided the exploration of the system boundaries. They became input for determining the list of requirements (paragraph 3.4) and finally the conceptualization step (paragraph 4).

        

Easy to control Handling should be fun Safe for children to operate Opening only possible with tools Light adaptable to user’s mood The illumination level should be >500Lx The Unified Glare Rating (UGR) should be < 22 Function of the lamp shown by the design/aesthetics Design/aesthetics should attract broad audiences

Table 4: List of requirements and wishes. 4

CONCEPTUALIZATION AND TECHNICAL REALIZATION OF THE LAMP

In this section is tried to realize all the functions listed in the list of requirements, the challenge being in the shift from the functional description to a technical implementation that fits with all the factors or at least the must factors listed in the list of requirements. Again it seemed to be preferable to do first some “technical” brainstorming (with the factors as system boundaries) and afterwards indexing these ideas. Indexing is a good tool in this case as it does not only give the process a traceable structure but also the possibility to combine completely different approaches to a completely new, innovative approach. One method used for this was a

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morphological box, allowing to quickly combine several possible solutions while rating them with the list of requirements.

the USA, as it was not available with the needed configuration in neither Germany nor Norway.

Especially the economical requirements drew the range of possible solutions pretty narrow. The most important features realized in the final prototype are the following: 

Dimmable LED light



Safety release cable



Directional light



Motion detector with several sub features like timer etc.



Light detector



Due to safety reasons is whole system realized in 12V



Less flies and mosquitoes being attracted



90-98% less energy consumption than equivalent lamp

4.1

Description of the prototype

Figure 1: Safety release cable. Directional light:

The system itself can be seen from a functional perspective be divided into five subparts: all the sensors, the electronics to dim the LED, the LED itself, the safety release cable and the part to allow directional light. Each of these subparts is only briefly discussed as the main focus of the project was on discussing the methodology.

The origin of this idea originates from the ability to have directional light as well as non-directional light coming from one single lamp. This was realized with a removable piece of metal in tree shape which avoids the light from going into one direction while the illumination on the other side of the lamp is being increased due to the reflections coming from the tree.

Sensor system:

4.2

Translating the list of requirements, the following functions were wanted from the sensor system:

In a strict form-follows-function approach it was now considered how to embed the functions into the aesthetics. Therefore several different cardboard mock-ups were built to investigate different possibilities of realizing the functions in an aesthetically pleasing and ergonomical system.



Measure light intensity



Check if human in surrounding



Possibility to adapt to different environments



Timer

An interesting fact is the possibility of adapting the module to different environments as well as the customization of the whole responding behaviors (in a defined range). Electronics: A challenge is the fact that is it not possible to dim a LED with a normal dimmer used in lamps with bulbs. The reason is in the physical properties of the LED [16]. It is therefore necessary to use other electronic circuits to dim LED lights. One possibility is the use of the so-called “pulse width modulation” [17]. This device basically modulates the current that it is changing between two values what allows to steer the output signal. This is what is installed in the prototype.

Aesthetics and realization

Within the lamp project several factors were considered are more important than the aesthetics of the lamp. At the same time it relates to several other factors like attractiveness, lifetime, quality properties, the usability etc. As there are some parameters determined due to the bought-in parts there is not as much freedom as designing a completely self produced product. The mock-ups were then tested on their characteristics, especially the functional and ergonomical ones. This was especially important to ensure sufficient illumination. After an iterative process of eliminating different problems one conceptual model was chosen. Based on this there a working prototype was built which was called LOGI, after the god of fire in Norwegian mythology.

The LED: There has been quite some progress in the LED industry in the last years. From glaring, white light that was not comparable to normal bulbs to all kinds of illuminants with the same lighting properties as normal bulbs. Most of these new illuminants are made for standard bulb sockets and 220V. As it was decided that, due to safety reasons, the design should be realized in 12V, finding such as solution was quite time consuming. Closely linked to the LED is the socket. In this case a small standard socket was chosen to ensure maximum design freedom with all the benefits of a standard socket. The chosen LED provides light comparable to a 40W bulb (what is used in most desk lamps on the market). The superior environmental qualities of LED made it a priori clear that LED would be a logical choice of technology to base the prototype on. The safety release cable: The idea of the safety release cable (a cable that releases when being pulled no matter in which direction it is intentionally or unintentionally pulled, instead of making the whole lamp falling) may sound obvious, but such a cable needed to be shipped from

Figure 2: LOGI prototype.

Life Cycle Design - Selected Applications 5 5.1

EVALUATION OF THE LAMP Linked-benefits

In the working prototype, the following linked-benefits were realised: 

The electronics (motion detector as well as the timer) render the installation of a switch unnecessary, saving on cost and material use. Convenience for the user is increased as the lamp does not to have to be switched on or off.. However, the switching of the lamp is possible via the dimmer.



Implementing a safety release cable and using timeless aesthetics, the life-time of the lamp may be increased as it became less likely that the lamp will need to be replaced because of being out-of-date or because of accidental damage. An additional benefit is a higher safety level



The adjustable light reduces the energy consumption at the same time as it increases convenience for the user as the light can be adjusted for the purpose it is needed for.



The possibility of direction light to where it is most needed also creates the possibility to create aesthetically pleasing shadows on the wall.



If the light detector was configured in the right way, it could assure that the user always has the right amount of light that is ergonomically needed. This could, especially in professional environments, make sure that there is a perfect balance between energy efficiency and the avoidance of tiredness or even damage to the eye of the user due to insufficient light.



LED light does not only significantly reduce the energy consumption, but seems also to not attract flies and mosquitoes in a way normal lamps do. This offers completely new userbehaviors concerning the use of artificial light during summer time. Another benefit of the LED is the long life expectancy when compared to a normal bulb, which means that the user does not have to change the LED for a long time. The reduced heat-development of the LED increases the safety of the whole system. Furthermore this affects the whole design, for there is less space between LED and surrounding materials needed.

5.2

177 6

REFLECTION ON THE PROCESS

The intention of the project was to explore ways for successfully combining design for sustainable behavior and linked benefit strategies in product design. Reflecting on the process, good use has been made of a variety of established (user screening, context mapping, morphological box) and more hands-on methods (benefitcorrelation matrix, benefit-interaction matrix). Evaluating the approach it was considered that this could be more structured, especially for application in more complicated projects. It is therefore suggested that in future similar projects, linking the two perspectives could be done with a matrix based on cross comparison of potential benefits (abstracted wishes voiced by the customer) and different ways to influence behavior as explicit design parameters; a structure very similar to what is known from Quality Function Deployment (QFD) methodology. Figure 3 proposes such a tool, linking possible solutions for each design strategy with identified benefits from the user screening. A positive correlation would mean that the solution is expected to influence the benefit in a positive way, negative the other way round. To rate the intensity of the interaction figures like 3 for low interaction, 6 for middle interaction, 9 for strong interaction (in the positive as well as the negative direction) could be used. Adding up these correlations would then allow a ranking of possible solutions. It could also be a possibility to rank the benefits beforehand and bringing this into the process by giving the benefits different weights which would then be multiplied with the specific benefit-solution interaction. An extra source of information for the next steps is the comparison of the benefits and the solutions, which happens in the “roof-like” parts of the matrix. Again, plus means that the benefits respectively the solutions correlate in a positive way, negative that the influence each other in a bad way. This allows being aware of possible clashes right from the outset and can help when considering which functions to realize or not. It is also suggested explore the use of TRIZ-like methods to find ways of avoiding possible clashes.

User-related losses

The lamp is an intelligent product able to reduce user-related losses to a minimum. The problem of rebound effects is rather low as only few, if any possibilities exist to by-pass the electronics mechanism but incentives to do so neither exist. This might be the most important and most interesting fact of the whole process and the product. As such, the prototype would be a highly sustainable product, delivering exceptional service, without being invasive, and for a reasonable price. 5.3

Sustainability

The lamp is thought to use 90-95% less energy than a comparable lamp. Most of the savings are realized by the use of the LED: 

The amount of light given by the used LED (3W), which is equal to a 40W bulb, is equal to 92,5% savings.



Taking into account the percentages stated by Palmborg [18] or Gram-Hansen [19] considering user-related losses, there might be another 3,25% savings possible.

The lamp is designed in a way that makes the use of laser cutting machines possible. This ensures on one hand fast, cheap and high quality production, but on the other hand could also be used to customize the lamp. As mentioned before are low (production) costs vital for the success or failing of a product. An important aspect could therefore be a production-geared design of the product in the future to ensure a cheap and possibly automated production of the product.

Figure 3: QFD-type matrix for matching behavior and benefits.

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In the process of developing the lamp some aspects were discovered quite late in the process, some even after finishing the prototype (such as the use of the directional light tree to gain nice shadows on the wall). The aim has to be to pull those aspects to the earlier parts of the development process. One could say that control over the benefits from the beginning allows the control over the product and the process from the beginning on. This also allows new benefit combinations to be embedded early on in the design process. 7

CONCLUSIONS

This article has described a design project with the aim of developing a lighting solution that addresses both design for sustainable behavior and linked-benefit considerations as a starting point. The project resulted in a prototype that exhibits a unique set of features for a desk lamp, such as very low energy consumption and very limited electronics, combined with dimming, safety features, directional light, less attraction of flies and mosquitoes, and at relatively low costs. As no explicit methodology such a project existed yet, it was found useful to use established methods in combination with pragmatic approaches developed such as using a benefit-correlation matrix and a benefit-interaction matrix. This eventually led to a proposal for a QFD-type matrix that would allow for a more systematical simultaneous consideration of incorporating linked benefit and design for sustainable behavior strategies. Future research will look into testing this approach, using additional case studies. The 2011 spring semester at NTNU’s Department for Product Design will have ca. 40 students working explicitly with Design for Sustainable Behavior projects, and the desk lamp project is expected to be of inspiration to them. One of the goals of these projects is to provide further input for methodology development for design for sustainable behavior, contributing to ongoing research at the department. 8

ACKNOWLEDGEMENTS

[5]

Lockton, D., D. Harrison, and N. Stanton (2008). “Making the user more efficient: design for sustainable behaviour”, International Journal of Sustainable Engineering, 2008, 1(1), 3–8.

[6]

Wever, R., J. van Kuijk, and C. Boks (2008). ”User-centred design for sustainable behaviour”, International Journal of Sustainable Engineering, 2008, 1(1), 9–20.

[7]

Mazé, R., and J. Redström (2008). ”Switch! Energy Ecologies in Everyday Life”, Int. Journal of Design, 2008, 2(3), 55-70.

[8]

Lilley, D. (2009). “Design for sustainable behaviour: strategies and perceptions”, Design Studies, 2009.

[9]

Scott, K., J. Quist, and C. Bakker (2009). “Co-design, social practices and sustainable innovation: involving users in a living lab exploratory study on bathing”, Joint Actions on Climate Change, Aalborg, Denmark, 8-10 June 2009.

[10]

Stevels, A. (2000). ‘Green marketing of consumer electronics’, Proceedings of the ‘Electronics Goes Green’ Conference, Berlin, Germany, September, pp.539–544.

[11]

Mansouri-Azar I., Newborough M., Probert D. (1996). Energyconsumption in UK domestic households: impact of domestic electrical appliances. In: Applied Energy 54/3, pp. 211–285.

[12]

Blythe, M. and Dearden, A. (2008). Representing older people: Towards meaningful images of the user in design scenarios, Universal Access in the Information Society, Volume 8, number 1, pp. 21-32.

[13]

Lilley, D., Lofthouse, V. and Bhamra, T. (2005). Towards instinctive sustainable product use. Presented at the 2nd International Conference: Sustainability Creating the Culture, 2-4th November 2005, Aberdeen Exhibition & Conference Centre, Aberdeen.

[14]

Lockton, D., Harrison, D.J., Stanton, N.A. (2010). Design with Intent: 101 patterns for influencing behaviour through design (v.1.0), Windsor: Equifine 2010 (ISBN 978-0-9565421-0-6 print; 978-0-9565421-1-3 eBook).

[15]

Elias, E., DeKoninck, E. and Culley, S. (2007). The potential for domestic energy savings through assessing user behaviour and changes in design In: EcoDesign 2007: 5th International Symposium on Environmentally Conscious Design and Inverse Manufacturing, 10-13 December 2007, Tokyo, Japan.

[16]

Dyble M., Narendran N., Bierman A., Klein T. (2005). Impacts of Dimming White LEDs: Chromaticity Shifts Due to Different Dimming Methods. In: Proceedings SPIE 5941, pp.291-299.

[17]

Wallentowitz H., Reif K. (2006). Handbuch Kraftfahrzeugelektronik: Grundlagen, Komponenten, Systeme, Anwendungen. Vieweg Verlag, Wiesbaden.

[18]

Palmborg, C. (1986). Social habits and energy consuming behaviour in single-family houses. Stockholm: Swedish Council for Building Research.

[19]

Gram-Hansen, K. (2003). Domestic electricity consumption— consumers and appliances. Paper, Nordic Conference on Environmental Social Sciences (NESS), June, Turku/Åbo.

The authors are grateful for those that participated in the interviews, They also wish to acknowledge Ida Nilstad Pettersen for sharing the supervision of this project. Øyvind Kurisaki-Sagberg is acknowledged for the photo of the LOGI desk lamp. 9 [1]

[2]

REFERENCES Wood, G., Newborough (2003). Dynamic energy-consumption indicators for domestic appliances: environment, behaviour and design, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, Scotland, UK. Pettersen, I.N., Boks, C. (2009). The future of design for sustainable behaviour. Ecodesign 2009: Sixth International Symposium on Environmentally Conscious Design and Inverse Manufacturing, December 7-9. 2009, Sapporo, Japan.

[3]

Jelsma, J. (2006). “Designing ‘Moralized’ products: theory and practice”. In: Verbeek, P.-P., and A. Slob, eds., User behavior and technology development, Springer, Berlin, 2006, 221–231.

[4]

Fogg, B.J., (2004). Persuasive technology: using computers to change what we think and do, Morgan Kaufmann Publishers, San Francisco, CA.

Strategic Evaluation of Manufacturing Technologies 1

1

Gunther Reinhart , Sebastian Schindler , Pascal Krebs 1

1

Institute for Machine Tools and Industrial Management, Technische Universitaet Muenchen, Muenchen, Germany

Abstract Strategic technology planning sets the course for the future production of a manufacturer. Therefore, paying attention to market trends and new emerging technologies is indispensable. In order to compare different technologies from a longterm perspective, this paper presents an approach for the strategic selection of manufacturing technologies. Thereby, a multi-criteria evaluation is employed to incorporate the strategy of a producing company and consider quantitative and qualitative influencing factors. Because most factors are uncertain and the result of expert estimations, the approach includes the consideration of intrinsic uncertainties. Keywords: Manufacturing Technology Life Cycle; Maturity Assessment; Strategic Technology Planning

INTRODUCTION

Manufacturers are compelled to use the most effective and efficient production processes and structures [1]. Producing companies located in high-wage countries, in particular, must permanently ensure that their technologies will fit future requirements, such as fast adaptations to market demand or economies of scope [2]. The term “technology” denotes, in this context, all manufacturing processes and techniques which are needed to produce a special product [3]. This also includes all essential value-adding assembly operations. The decision of which technology to use in future production depends on several influencing factors, such as competitive potential or expected production cost. However, the competitive potential or the profitability of a technology is changing continually. Individualized customer requirements or shortened product life cycles intensify this trend [4]. In the scientific literature, this circumstance is called “turbulent production environment” [5]. From a long-term perspective, there exists a dynamic range of potentially available technologies in the production planning process. Each technology passes through an evolutionary development [6]. During this dynamic change, the competitive potential or the maturity of a technology varies as well as profitability compared to alternative technologies. Competitive potential means, in this context, the possibility of gaining advantages vis-à-vis competitors, such as reduced processing times, decreased production costs or new product features. This evolution can be described as a kind of technology life cycle [7]. In order to hold technological leadership and to increase competitive advantages, companies must decide when to change to a new emerging technology. Figure 1 shows the curves of the technology maturity and the competitive potential over time. The technology life cycle model according to Sommerlatte and Deschamps inspires this coherency [7]. The technology maturity increases over time while the competitive potential decreases. Depending on the maturity, the life cycle of a technology can be classified into one of four different strategic states. An innovation technology offers great potential in gaining competitive advantages while managing organizational and technical risks.

Standard technologies are commonly used. Producing companies will not enhance their competitive position by employing standard technologies, however, neglecting them will cause a loss in market share. Displaced technologies have become obsolete and offer few advantages because of inefficiency. New planning methods are needed in order to decide which technology is suitable for future production and when to change to a new alternative [8]. For selecting with the most efficiency and the lowest risk, producing companies must consider the current state of the technology life cycle. Moreover, the different dynamic changing factors which influence the suitability of a technology must also be contemplated. Some of the influencing factors can be described quantitatively, such as increasing product units. Other factors are more qualitative because they are the result of forecasts and expert estimations, for example, the assessment of the technology maturity [9]. However, the future development of both kinds of factors involves an intrinsic uncertainty. This paper presents an approach for the strategic evaluation of manufacturing technologies. The approach considers the uncertainty of the planning data and considers both quantitative as well as qualitative factors. A multi-criteria evaluation, in particular, focuses on the dynamic change of the influencing factors. Technology Maturity and Competitive Potential [%]

1

Innovation Technology

Key Technology

Standard Technology

Competitive Potential

Displaced Technology

Maturity

Time [Years]

Figure 1: Technology Life Cycle (based on [6] and [7]).

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_31, © Springer-Verlag Berlin Heidelberg 2011

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Operational Technology Planning • • • •

Rough Unit Quantities Several Material Types Approximate Dimensions Innovative Technologies

Short-term Planning Horizon  Low Uncertainty

Long-term Planning Horizon  High Uncertainty

Uncertainty

Defined Unit Quantities Determined Materials Detailed Geometries Established Technologies

Uncertainty

• • • •

Strategic Technology Planning

Time

2.3

Time

Figure 2: Uncertainty due to different planning horizons relating to operational and strategic technology planning (based on [8]). In this approach, the criteria product feasibility, competitive potential, resource efficiency, technology maturity and profitability are valuated and flow into the suitability of a technology, which is the main target value. In this paper, the valuations of profitability and technology maturity are presented in more detail. By studying selected application examples, the valuation of the two criteria can be better understood. This approach results in a technology suitability evaluation as well as a dedicated interpretation of expected risks. A comparison of the evaluation results from several alternatives helps producing companies to choose the most suitable technology for future production requirements. 2 2.1

MANUFACTURING TECHNOLOGY PLANNING Operational Technology Planning

Regarding the planning process of manufacturing technologies, the planning horizon can be roughly divided into short- and long-terms. Operational technology planning takes place in the short-term. The information, available for operational planning tasks, consists of accurate product data, such as defined unit quantities, specified alloy materials or detailed geometric dimensions, and employable production resources and structures, such as the quantity of installed robots or useable machine tools. The main objective of operational technology planning is to concretely determine which product features will be manufactured using what kind of technology installed in which kind of production resource [8]. 2.2

Hence, new external technologies often need a further development. By considering and especially integrating company external technologies in the existing production environment significant research and development efforts arise. Here, the company has to contemplate organizational as well as technical properties and requirements of the technology. However, building up know-how can be very time-consuming and expensive. Therefore, the decision of eliminating an established technology or following up a new one is crucial. In order to select the right technologies in terms of strategic planning, companies need to evaluate the existing alternatives. Within this evaluation, important time-dependent and uncertain criteria must be considered [6].

Strategic Technology Planning

Criteria for Strategic Technology Evaluation

The suitability of a technology to future requirements depends on several influencing factors. Most common methods for technology evaluation focus on production cost calculations, product feasibility studies or a strength and weakness analysis [11]. From a strategic point of view, the technology maturity should also be integrated into the evaluation process [12]. Furthermore, trend-setting technology properties such as competitive potential [8] and savings of resources [14] should also be considered. The following describes the evaluation criteria used in this approach. Product Feasibility This criterion contains relevant data about the product to be fabricated. Herein, rough product properties are contemplated, such as geometric dimensions, alternative alloy materials as well as important tolerance values of functional surfaces. Furthermore, future product quantities are estimated along the product life cycle. Based on the product properties, the feasibility is finally valuated. Competitive Potential Within strategic technology planning, competitive potential contemplates all technological potentials for reaching lower cost per unit, shorter processing times and higher productivity [8]. Furthermore, technology attributes are considered helping to achieve higher product qualities, such as smoother surfaces, or completely new product features, such as brand new processable materials. Resource Efficiency Because raw materials or water are growing scarce, the resource efficiency of a technology must be contemplated within the strategic planning process [13]. This criterion concentrates on product and production resource flows and is based on a process balancing method. In this context, an index estimating the future resource efficiency is used leaning on methods employed within the resource efficiency valuation of established manufacturing processes [14].

Strategic technology planning focuses on the long-term orientation of a producing company [8]. As shown in Figure 2, the uncertainty of the available planning data for this challenge is very high compared to the short-term planning horizon. The accuracy of known information on future production requirements and necessary product features is rather low. For example, only rough unit quantities, approximate product dimensions or potentially useable types of material are available for the planning tasks. In contrast to operational technology planning, the strategic aspect includes the possibility of considering a company’s internal as well as external manufacturing processes for future production.

Technology Maturity

Innovative external technologies, in particular, are often not mature enough to be efficiently used in the production environment [9]. However, these technologies are perceived by producing companies to be important enablers for reaching competitiveness although their implementation often fails to achieve the expected benefits [10].

In order to calculate important future production costs, such as expected costs per unit and investments for new production resources and structures, this criterion takes the economic aspects of a technology into account. From a strategic point of view, future costs can only be estimated [15]. Therefore, the method for the profitability valuation roughly calculates expected production costs per unit with consideration for employee and machine hour rates.

This criterion focuses on the current stage of development of a manufacturing technique or process. The technology maturity correlates with technical and organizational risks [12]. In order to estimate the maturity of a technology, a method is employed using different maturity stages. The technology maturity valuation is based on the concepts of “technology readiness level” (TRL) as used by the National Aeronautics and Space Administration (NASA) and the “technology maturity assessment” (TMA) [9]. Technology’s Profitability

Life Cycle Design - Selected Applications 3 3.1

181

UNCERTAIN INFLUENCE FACTORS Qualitative and Quantitative Influence Factors

Quantitative factors are numerically measurable in their nature and level of occurrence [16]. In contrast to the quantitative factors, qualitative factors are often expressed in ordinal scales that allow, for example, the assessment by terms such as “high” or “low” [17]. An assignment of specific numerical values is, however, not possible and they exist often as expert estimates [15]. Both quantitative and qualitative influence factors in the evaluation can be uncertain and pose some risk for producing companies [15]. 3.2

Modelling of Uncertainties

Quantitative uncertainties can be integrated into the evaluation model using probability distributions [18]. By using different distribution types, mean values and variations, multiple uncertainties can be modelled. Qualitative uncertainties cannot be directly modelled as probability distributions. In the course of a technology evaluation, these so-called weak factors exist only based on studies or as statements from experts. Such ambiguous statements are described as linguistic uncertainties [15]. Hence, all qualitative parameters can be interpreted as uncertain. One method to evaluate qualitative, linguistic statements is to use Fuzzy Logic. Fuzzy Logic is especially powerful when linguistic variables are represented in words or sentences whereby each linguistic value can be modelled by a fuzzy set [19]. These fuzzy linguistic variables are extensions of numerical variables because they are able to represent the condition of an attribute at any given interval by taking fuzzy sets as their values [20]. An element in Fuzzy Logic can be partially or totally inside or outside of a specific set. Therefore, each position of the element is described by the membership value μ that has a value of one (μ=1) if the element belongs completely to the set and a value of zero (μ=0) if the element does not belong to the fuzzy set. Any value between zero and one (0<μ<1) is possible when the element belongs partially to the fuzzy set. Although the inputs to the Fuzzy Logic models are always linguistic variables and their fuzzy sets, the outputs can either be linguistic variables described by fuzzy sets or linear functions [21]. In a Fuzzy Logic based model, If-Then rules between the input and output fuzzy sets describe the heuristic knowledge about the behaviour of the system. The process of fuzzification of the inputs, definition and aggregation of the If-Then rules is known as fuzzy inference. For the integration of qualitative uncertainties into a quantitative evaluation method, Fuzzy Logic is a proper approach.

e1 High Middle Low

Fuzzification µ 0,4 e2 µ 0,6 High 0,3 0,2 ei Middle 0,4 High 0,2 Low Middle Low

Defuzzification P

P

x xs P: Probability x: Value xs: Centre of Mass

µ 0,1 0,2 0,4

x

Therefore, Reinhart et al. [23] developed a so-called Fuzzy Evaluation Net which transforms qualitative parameters available in linguistic statements into measurable values as shown in Figure 4. In this evaluation net, a so-called inference calculates the membership values of the output neurons based on weighted connections between the neurons ei and a certain rule base. Thereby, all rules and connections are evaluated simultaneously and the results are combined. At this stage, an aggregate output neuron is derived in an output layer. In order to obtain a precise (i. e. measurable) variable as output data, the output neuron has to be defuzzified using the so-called Centre of Mass method. This method consists of three steps. The first step is the assignment of membership functions to the linguistic terms describing the output neuron. The most common membership function has the graph of a triangle. Hence, for each linguistic term a triangle function has to be defined for this methodology. The x-coordinate of the peak of each triangle is the most likely value described by a linguistic term. In the second step, the membership functions of the output data are cut at the respective straight line of the membership value μ assigned. The third step contains the calculation of the x-coordinate of the area’s Centre of Mass. Afterwards, the transformed qualitative uncertainties can be integrated in the evaluation model. The integration of multiple uncertainties increases the complexity of the calculation model. Hence, a Monte Carlo simulation is a valid technique to calculate and combine uncertainties in order to determine the range of a result. Out of the defined probability distributions for the uncertainties, the simulation executes a random sampling and integrates it into the evaluation model. 4 4.1

STRATEGIC EVALUATION OF TECHNOLOGY Technology Evaluation Methodology

In order to enable producing companies to select the optimal technology for future production requirements, this approach provides a structured methodology for strategic evaluation. The methodology consists of three different steps built on each other and depicted in Figure 4. In the first step, important product properties for technology evaluation have to be defined, such as geometry dimensions or potentially usable alloy materials. Furthermore, potential technological alternatives are considered. Herein, methods for technology screening and trend forecasting can be used as recommended by Bullinger [11]. In the second step, the technology evaluation takes place where five evaluation criteria, in particular, are calculated. Herein, qualitative and quantitative influencing factors are integrated. Some of the factors are quite uncertain and interact with each other. For example, if the maturity of a technology were “high”, loss rates would be “low”. Thereby, factors influencing different evaluation criteria also interfere among themselves. Hence, the valuation of the five criteria cannot be done independently, but rather must be accomplished regarding the interactions and developments of all influencing factors.

Step 1

Step 2

e1 High Middle Low

µ 0,4 0,6 0,2

e2 High Middle Low

µ 0,3 0,4 0,2

ei High Middle Low

µ 0,1 0,2 0,4

Rule Base ei: Output Neuron µ: Membership Value Figure 3: Integration of qualitative uncertainties using Fuzzy Logic.

Probability

Inference

Step 3

Product Properties

Suitability Alternative Technologies

Multi-Criteria Evaluation

Comparison and Selection

Figure 4: Methodology for Strategic Technology Evaluation Consisting of three Steps.

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P

P

P

P

Competitive Potential

Resource Efficiency

w1

w2

w3

Technology Profitability Maturity w4

w5

Probability

Product Feasibility

Technology Readiness Level Quantifier [-]

P

7. Serial Production

q7 = 0,20 mTRL,7 25

6. Production Environment

q6 = 0,20 mTRL,6 30

5. Production Resource

q5 = 0,20 mTRL,5

4. Technology Demonstration

q4 = 0,15 mTRL,4

3. Technology Development

q3 = 0,15 mTRL,3

70

2. Feasibility Studies

q2 = 0,05 mTRL,2

69

1. Basic Technology Research q1 = 0,05 mTRL,1 Maturity of Technology: MT = 47,3%

Technology Suitability P: Probability wi: Weighting Factor Figure 5: Aggregation of the Evaluation Criteria to the Technology Suitability Histogram. The uncertainties and interdependencies are integrated in the valuation using probability distributions and Fuzzy Logic. The results of the several valuations finally flow into the target value described as technology suitability. The aggregation of the five evaluation criteria is pictured in Figure 5. Each valuation result consists of a distributed histogram of the particular target value, such as technology maturity. Depending on the weighting factors wi, the aggregation of the multi-criteria evaluation constitutes a histogram of technology suitability. Finally, the evaluation results of alternative technologies can be compared in the third step of the methodology. Thereby, the selection of the optimal technology depends on the interpretation of the suitability histogram. Following this, the two evaluation criteria “technology maturity” and “profitability” are examined. The procedure for valuation is also contemplated in more detail. Thereby, relevant influencing factors are described. Furthermore, the modelling of the quantitative and qualitative factors influencing the focused valuation is explained. 4.2

Valuation of Technology Maturity

The method for valuating the technology’s maturity is based on the concepts of “technology readiness level” (TRL) according to the NASA [12] and the “technology maturity assessment” (TMA) according to Brousseau et al. [9]. In this approach, these concepts are combined and enlarged by considering the time-dependent change of technology maturity [22]. Furthermore, indicators and limits are introduced in order to permit maturity definition and impartial quantification. The method for maturity valuation employed in this approach is based on seven different TRLs, shown in Figure 6. Beginning with basic technology research activities (TRL 1), the development of a technology passes through several feasibility and demonstration stages (TRL 2-4). After integration into real production resources (TRL 5) and environments (TRL 6), the technology is finally used in a company’s serial production (TRL 7). The further development of a technology does not proceed in one stage alone, but rather in all seven levels. Hence, the maturity of each TRL mTRL,i has to be estimated. The TRL maturities arise out of a questionnaire consisting of TRL specific demands that help to assess the maturity development at each stage. The questions also aim to determine the limits of factors and indicators influencing the technology maturity, such as loss rates or changes in process costs [22]. Because they stem from expert estimations, the questionnaire responses are somewhat vague and are therefore viewed as a kind of uncertainty.

Maturity [%]

55 45

91

Specific Maturity Limit lspec,i

Figure 6: Exemplary Calculation of Technology Maturity depending on the Maturity of each TRL (based on [14]). Depending on the technological strategy of a company, another specific maturity limit lspec,i may be introduced in order to determine the minimum grade of maturity at each stage. A technology is not applicable in a company’s production environment before having passed all specific maturity limits. In order to weight the different TRL, quantifiers qi have to be defined in each TRL. The determination of the seven quantifiers is company specific and can vary by case. Normally, higher TRLs have to be rated higher than lower ones, because these TRLs influence the application of the technology in reality much more. Finally, the technology maturity MT is the result from the calculation of the seven maturities of the different TRLs mTRL,i according to equation (1). Figure 6 shows the principle of an exemplary calculation of the technology maturity. Reinhart and Schindler [22] introduce further information concerning technology maturity valuation employed in this approach. Thereby, the detailed framework of the maturity valuation model and the structured procedure are presented and explained. The result of the technology maturity calculation finally delivers a maturity histogram as is shown in Figure 5. The fluctuation of this histogram depends on technology maturity representing technical as well as organizational risks. This histogram finally flows into the evaluation of the technology suitability.

  7   MT  1   1  mTRL ,i   q i    100 %   i 1   4.3

(1)

Valuation of the Technology’s Profitability

The valuation of the profitability of a technology generally focuses on estimated production cost per unit. As shown in Figure 7, production cost divides into material and manufacturing costs. Material cost consists of material prices and preceding value add, which are not done inside the company such as alloying or forging. Manufacturing cost is composed of forecasted man and machine hour rates. Based on this cost structure, the technology’s profitability is calculated. From a strategic perspective, not only single costs per unit must be contemplated, but also influencing quantitative and qualitative factors to ensure a chargeable valuation. Figure 7 illustrates the way influencing uncertainties are integrated. In the profitability valuation model of this approach, quantitative uncertainties, such as future product quantities or forecasted material prices, are implemented using different kinds of probability distributions. Qualitative Uncertainties such as competitive potentials first are quantified using Fuzzy Logic. After the fuzzification, the qualitative uncertainties are then modelled in the same way as quantitative ones.

Life Cycle Design - Selected Applications

183

0,05

Production Cost

0,04

Material Cost

Probability [-]

Profitability Valuation Model

Manufacturing Cost

Mean A: 77,8%

Mean B: 95,6% Technology A Technology B

0,03 0,02 0,01

...

...

Quantitative Uncertainties P A P B

Machine Hour Rates

0

e1 High Middle Low

µ 0,4 0,6 0,2

e1 High Middle Low

e1 High Middle Low

µ 0,4 0,6 0,2

µ 0,4 0,6 0,2

P

P

xsα

xsβ

α

β

Probability Quantitative Uncertainties Qualitative Uncertainties Centre of Mass Output Neuron Membership Value

Figure 7: Composition of Estimated Production Cost influenced by Quantitative and Qualitative Uncertainties. The complexity of valuating the technology’s profitability increases because the different production cost influencing factors interact with each other. The technology maturity represents a qualitative influence for the profitability valuation, for example. If the technology maturity is high, the uncertainty of processing time estimations tends to be low. In the same way, maintenance costs decrease with increasing technology maturity. These existing interactions and resulting impacts between influencing factors as well as entailed uncertainties affect the result of the profitability valuation. Interactions between quantitative factors can be implemented by defining correlations [15]. Interdependencies of several qualitative factors as well as dependencies between qualitative and quantitative factors are modelled by using Fuzzy Logic. Due to integrating qualitative and quantitative uncertainties, the result of technology’s profitability valuation consists in a profitability histogram as it is pictured in Figure 5. Depending on the influencing uncertainties, the range of the profitability target value varies considerably. The histogram of the technology’s profitability finally flows into the technology suitability evaluation. 4.4

50 100 150 Technology Suitability [%]

200

Figure 8: Evaluation Results of Alternative Technologies A and B.

Qualitative Uncertainties

...

... P: A, B: α, β: xs: ei: µ:

Man Hour Rates

...

Value Add Forging

...

Value Add Alloying

Strategic Evaluation Results

In order to select the optimal technology, the technology evaluations of the existing alternatives have to be compared. As shown in Figure 5, the result consists of an aggregation of the outcomes from the weighted criteria valuations. Thereby, the suitability of a single technology represents the target value and is constituted as a histogram. Figure 8 displays the result of the Monte Carlo simulation for two alternative technologies A and B. The diagram plots the probability against the technology suitability histogram based on random sampling.

Because the histograms of technology A and B result from the same simulation and exhibit the same quantity of drawings, the area integral of both is equal. The fluctuation range of one single histogram permits conclusions regarding expected risks. The more a histogram disperses the higher the uncertainty is. Regarding the means of both alternatives, technology B has to be preferred as it has about 17,8% better technology suitability than technology A. However, a look at the fluctuation range of technology B highlights the risks entailed with technology B. As there exist several drawings of technology B being placed worse than technology A, the risk of B is significantly higher. Nevertheless, technology B also offers a great chance to get more suitability, because of drawings up to 150% of technology suitability. Generally, technology A is rated worse than the alternative B, but it shows a comparably low-risk property. Technology B offers a greater potential in reaching higher suitability although it involves higher risks. In order to decide which technology to select, further analyses have to be done. Firstly, sensitivity analyses need to be contemplated in order to find out which uncertainties are responsible for each fluctuation result. 5

SUMMARY AND OUTLOOK

As producing companies located in high-wage countries continually have to ensure that their technologies fit future requirements, new methods for evaluating technologies are needed from a strategic point of view. Therefore, this paper presents an approach for the strategic technological evaluation of uncertainties. First, the individual evaluation criteria are described and it is explained that quantitative or qualitative uncertainties may underlie the evaluation of integrated factors. Quantitative uncertainties can be modelled using probability distributions; qualitative uncertainties with Fuzzy Logic. Subsequently, the evaluation model is described in general and it is clarified that the individual evaluation criteria may also affect one another. Finally, the evaluation of two criteria – maturity and profitability – is explained in more detail and it is described how to interpret the results of the strategic technology evaluation. The approach presented in this paper concentrates on the strategic evaluation and comparison of a single technology alternative at a particularly date. As products are only produced using a combination of several technologies, the strategic evaluation needs to be expanded focusing on a so-called technology chain. However, strategic technology planning has to cover the long-term horizon. Therefore, not only one single point of time needs to be considered but also the whole future period of the technology chain. Further research activities must therefore find out how to integrate this timedependent and long-term contemplation into the presented approach. Latest investigations show that the use of recurrent Fuzzy Systems is a suitable aid to meet this challenge [24].

184 6

Life Cycle Design - Selected Applications ACKNOWLEDGMENTS

The German Research Foundation (DFG) funds this research and development project. We extend our sincere thanks to the DFG for the generous support of the work described in this paper. The research project is part of the Collaborative Research Centre 768 ”Managing cycles in innovation processes – Integrated development of product services systems based on technical products”. The goal of the Collaborative Research Centre 768 is to reduce the knowledge gap regarding cycles and cyclic influences within the innovation process. 7 [1]

[2]

REFERENCES Tolio, T.; Ceglarek, D.; ElMaraghy, H. A.; Fischer, A.; Hu, S. J.; Laperrière, L.; Newman, S. T.; Váncza, J. (2010): SPECIES – Co-evolution of products, processes and production systems. Annals of the CIRP, Vol. 59, No. 2, pp. 672-693. Klocke, F. (2009): Production Technology in High-Wage Countries – From Ideas of Today to Products of Tomorrow. in: Schlick, C. M. (Ed.): Industrial Engineering and Ergonomics – Visions, Concepts, Methods and Tools Festschrift in Honor of Professor Holger Luczak. Springer, Berlin, New York, pp. 1330.

[3]

DIN 8580 (2002) Manufacturing processes – terms and definitions, division. Beuth, Berlin.

[4]

Zaeh, M. F.; Reinhart, G.; Pohl, J.; Schindler, S.; Karl, F.; Rimpau, C. (2009): Modelling, Anticipating and Managing Cyclic Behaviour in Industry. in: Proceedings of the 3rd International Conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV2009), pp. 16-43, Munich, Germany.

[5]

[6]

[7]

Wiendahl, H. P.; ElMaraghy, H. A.; Nyhuis P.; Zaeh, M. F.; Wiendahl, H. H.; Duffie, N.; Kolakowski M. (2007): Changeable Manufacturing – Classification, Design and Operation. Annals of the CIRP, Vol. 56, No. 2, pp. 1-25. Reinhart, G.; Schindler, S.; Pohl, J.; Rimpau, C. (2009): Cycle-Oriented Manufacturing Technology Chain Planning. in: Proceedings of the 3rd International Conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV 2009), pp. 702-711, Munich, Germany. Sommerlatte, T.; Deschamps, J. P. (1985): Der strategische Einsatz von Technologien. in: Little, A. D. (Ed.): Management im Zeitalter der strategischen Führung. Gabler, Wiesbaden, pp. 39-76.

[8]

Eversheim, W.; Schuh, G. (1996): Betriebshütte – Produktion und Management. Springer, Berlin, Heidelberg, New York, 1996, pp. 10.36-10.72.

[9]

Brousseau, E.; Barton, R.; Dimov, S.; Bigot, S. (2010): Methodology for Evaluating the Technological Maturity Micro and Nano Fabrication Processes. IFIP, Advances Information and Communication Technology, Vol. 315, No. Springer, Boston, pp. 329-336.

A of in 1,

[10] Gouvea Da Costa, S. E.; Platts, K. W.; Fleury, A. (2006): Strategic selection of advanced manufacturing technologies (AMT), based on the manufacturing vision. International Journal of Computer Applications in Technology, Vol. 27, No. 1, pp. 12-23. [11] Bullinger, H. J. (2008): Fokus Technologie – Chancen erkennen – Leistungen entwickeln. Carl Hanser Verlag, Munich, Vienna.

[12] Mankins, J. C. (1995): Technology Readiness Level – A White Paper, Advanced Concepts Office, Office of Space Access and Technology. [13] Herrmann, C.; Thiede, S. (2009): Process chain simulation to foster energy efficiency in manufacturing. CIRP Journal of Manufacturing Science and Technology, Vol. 4, No. 1, pp. 221-229. [14] Reinhardt, S.; Reinhart, G. (2009): Resource Efficiency Valuation of Manufacturing Processes. in: Digiesi, S.; Mossa, G.; Mummolo, G.; Ranieri, L. (Ed.): Quaderni della XIV Summer School 'Fancesco Turco'. pp. IV.84-IV.91, Monopoli, Italy. [15] Krebs, P.; Müller, N.; Schellmann, H.; Reinhardt, S.; Bredow von, M.; Reinhart, G. (2009): Risikobewertung produzierender Unternehmen. ZWF – Zeitschrift für wirtschaftlichen Fabrikbetrieb, Vol. 104, No. 3, pp. 174-180. [16] Rosenkranz, F.; Missler-Behr, M. (2005): Unternehmensrisiken erkennen und managen – Einführung in die quantitative Planung. Berlin: Springer. [17] Brieke, M. (2009): Erweiterte Wirtschaftlichkeitsrechnung in der Fabrikplanung (EWR). Diss. Hannover. Leibniz Universitaet Hannover. [18] Korves, B.; Krebs, P. (2008): Planung und Bewertung von Flexibilität in Fabrikplanungsprojekten bei der Siemens AG. in: Tagungsband Muenchener Kolloquium – Innovationen für die Produktion, pp. 57-67. [19] Zimmermann, H. J. (1991): Fuzzy set theory - and its applications, Boston: Kluwer. [20] Wang, L. X. (1997): A course in fuzzy systems and control, Upper Saddle River N. J.: Prentice Hall. [21] Yen, J.; Langari, R. (1999): Fuzzy logic: Intelligence, control, and information, Upper Saddle River N. J.: Prentice Hall. [22] Reinhart, G; Schindler; S. (2010): A Strategic Evaluation Approach for Defining the Maturity of Manufacturing Technologies. in: Proceedings of the International Conference on Engineering and Technology Management (ICETM2010), Venice, Italy, Vol. 6, No. 71, pp. 920-925. [23] Reinhart, G.; Krebs, P.; Zaeh, M. F. (2009): Fuzzy Logicbased Integration of Qualitative Uncertainties into Monetary Factory Evaluations. in: Proceedings of the IEEE International Conference on Control and Automation (ICCA2009), pp. 385391, Christchurch, New Zealand. [24] Dieplold, K., J.; Lohmann, B. (2010): Transient Probabilistic Recurrent Fuzzy Systems. IEEE International Conference on Systems, Man, and Cybernetics (SMC2010), pp. 3529-3536, Istanbul, Turkey.

Consideration of the Precautionary Principle – the Responsible Development of Nano Technologies Marcel Weil 1

1

Institute for Technology Assessment and Systems Analysis (ITAS), Karlsruhe Institut of Technologie (KIT), Karlsruhe, Germany

Abstract Carbon nanotube papers, referred to as bucky papers, are attracting a growing attention in different disciplines and application fields. The production of bucky papers is still considered to be too elaborate and costly for a broader application. Additional there are nano particle emission during production with unknown effects on environment and human health. For a planed upscale a carbon nanotube paper production is analysed, not only to identify optimisation potentials regarding technical and economic but also environmental and health aspects. For known environmental impacts, a streamlined Life Cycle Assessment (LCA) is conducted. Whereas for the unknown impact of nanotube emissions on environment and human health a qualitative method is used within a optimisation process, to foster the prevention of nano particle emissions, in respect of the precautionary principle. Keywords: Carbon Nanotube Paper; Streamlined LCA; Economic Assessment; Precautionary Principle

1

INTRODUCTION

In the presented prospective approach, system analysis is used to optimise the manufacturing process of carbon nanotube (CNT) paper by the consideration of technical, but also economic and ecological aspects, including nano specifics.

of uncertainty and unknown effects, but on the other hand has the chance to use the high degree of freedom (for development options) to guide the development itself in a more sustainable direction. Life Cycle Assessment (LCA) is an appropriate tool to analyse the environmental impact of a technology or product (cf. Figure 1). Due to uncertainties, inconsistent scientific results and the lack of knowledge about the eco- and human toxicity of nano particle, the potential environmental and health impact of nano particle is not covered by traditional LCA. Therefore the chosen approach includes a qualitative method (ABC-method) to ensure that also potential environmental and health risks will be minimized during an optimisation process by reducing or even preventing the emissions of nano particles to the environment (Figure 1). The minimization of nano particle emission with unknown risks is a requirement of the precautionary principle. In parallel to LCA (cradle to gate) also an economic assessment is carried out to identify overall more sustainable options. The described approach is focused exemplarily on the production of CNT-paper production.

2

3

New materials on a nano scale have the potential to overwhelm existing technical barriers and are one of the most promising key technologies to enable the decoupling of economic growth and resource consumption. Developing these materials for industrial application means facing a complex qualification profile, which includes among others technical, economic, and ecological aspects. The two latter aspects are not sufficiently included in material development, especially from a life cycle point of view [1]. If and when economic/ecological assessment is carried out in material development, it is performed after technical investigations are finished. Quite often, these assessments are postponed until the subsequent phase of product development.

APPROACH

3.1

PRODUCTION OF CNT AND BUCKY PAPERS Production of CNT

Carbon Nano Tubes (CNT) belong to a interesting material group with very promising technological properties, like very low optical reflection, high tensile strength (by low weight), good electric and heat conductivity. They can be produced basically by three different methods: 

Figure 1: Different levels of uncertainties regarding new technologies require the selection and combination of different methods and tools. The integration of system analysis in the early phase of technology development has one the one hand to struggle with the high degree

arc discharge



laser ablation



chemical vapour deposition (CVD)

The CVD process shows the greatest promise for a large-scale manufacturing of CNT, in particular fluidized bed CVD techniques [2]. Due to the fact that to date the quality of CNT from fluidized bed CVD has not met all the requirements for bucky paper production, a CVD in the batch mode is considered and used for the production of multi-walled carbon nano tubes (MWNT) for the presented work.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_32, © Springer-Verlag Berlin Heidelberg 2011

185

186 3.2

Life Cycle Design - Selected Applications Production Process of Bucky Papers

The synthesized MWCNT are purified in a liquid medium. After the separation of the liquide medium and the MWCNT by the help of vacuum filtering technique, the MWCNT are dispersed in a solvent, supported by the use of an ultrasonic treatment. Only well dispersed MWCNT are useful for CNT paper production. CNT Synthese

CNT Purification

CNT Dispersion

Filtering 1

Filtering 2

CNT Paper cut to order

CNT Paper

Global warming or greenhouse effect is quantified by using GWP for substances having the same effect as CO2 in reflection of heat radiation. GWP for greenhouse gases are expressed as CO2equivalents. Hence the impact indicator GWP describes the potential greenhouse effect of a product/process by calculating all emitted greenhouse gases (e.g. CO2) per functional unit, in this specific case, the production of bucky paper. In Figure 4 the shares of all process steps and pre-chains (e.g. electric energy) in the GWP are presented. It reveals that the dispersion process of MWNT contributes most to the GWP result. Responsible for the GWP contribution is mostly the use of a solvent. In addition, the transport of the dispersion medium (solvent) has a significant contribution. Other impact categories [3, 4] demonstrate results similar to GWP, beside “photo-oxidant formation”.

Global Warming Potential

Figure 2: Manufacturing process of CNT paper.

dispersion

By using again filtration techniques, MWCNT build up a layer on the top of a filter medium. After drying under room temperature and separation of the filter medium and the MWCNT layer, a free standing paper is produced. The manufacturing process is shown in Figure 2. This paper consists of 100% MWNT, meaning that no supporting fibres are contained.

transport of solvent others purification

4

ANALYSIS OF CNT-PAPER PRODUCTION

4.1

transport acid (purification)

System boundary of economic and life cycle assessment

electric energy

resources system boundary

catalyst

mixing

Figure 4: Shares of all process steps and pre-chains in GWP.

processing

4.3 MWNT

CNT synthesis

purification

filtration I

dispersing

filtration II

drying

bucky paper

emissions (air, water, earth)

Figure 3: System boundary for economic and ecological assessment. The system boundaries for economic and ecological investigations are shown in Figure 3. The results of the assessment are used both to identify the economic and ecological hot spots and to select the most favourable optimisation strategy. The manufacturing process can be divided into three main steps: synthesis of catalyst, synthesis of MWNT, and production of bucky paper, conf. Figure 3. For the investigation all prechains of inputs (e.g. electric energy) or services (e.g. transport) which are necessary for the whole manufacturing process are considered. 4.2

Economic assessment

Figure 5 display the shares in production costs of bucky papers (including supplies). The costs for labour, leasing and depreciation are not included.

LCA

For the understanding of the ecological implications of bucky paper production a streamlined Life Cycle Assessment (LCA) is conducted. The CML method [3, 4] is used for the ecological impact assessment. Human and eco toxicity of nano-materials are not included in this investigation. In the presented contribution, we display only one impact indicator: Global Warming Potential (GWP).

It indicates that the dispersion process of MWNT contributes most to the production costs. Again the use of solvents is the most important cost driver. The filtration process has a noteworthy contribution. All the other processes have only a small share to the production costs.

Material Costs dispersion synthesis MW NT purification catalyst filtration others

Figure 5: Shares in production costs.

Life Cycle Design - Selected Applications 5

187

DEVELOPMENT OF OPTIMISATION STRATEGIES

5.1

Lessons learned

Both the economic and ecological assessment identified the dispersion process, especially the use of solvent, as a major driver. Hence an optimisation strategy has to be developed, which allows the minimization of solvent use, or alternatively which substitutes the use of the solvent. But to focus during the optimization process only on economic and ecological goals can be described as insufficient, because the technical performance could be reduced or nano particle emissions increased. Thus the optimisation considers the following aspects: 

Stabilisation of the production process and stabilisation of the product quality (only minimal reduced technical performance is acceptable)



Reduction of the production costs



Reduction of the environmental impact



Reduction (or prevention) of nano particle emission to the environment

Subsequently it was investigated if a continuously recycling of the solvent causes an accumulation of substances, which might have a negative impact on the bucky paper quality. But also a continuous recycling of the solvent over more than 30 cycles doesn’t have any quantifiable negative effects on the produced quality of the buck papers. 6

QUANTITATIVE OPTION

OF

CHOSEN

OPTIMIZATION

90 80 70 60 50 40 30 20 10 0

reference

Comparison of alternative optimization strategies

Together with the industry partners six different optimization strategies were developed (Table 1): 

Use of an alternative solvent



Replacement of solvent by water (up to 30 %)



Use of a water tensideX1 mixture



Use of a water tensideX2 mixture



Use of a water tensideX3 mixture



Recycling of solvent

All six alternatives are analyzed and qualitative evaluated regarding the mention aspects mentioned above (Table 1).

100% Solvent (Reference)

RESULT

100

It hast to be stated, that the latter focused on the nano particle emissions to water. Without any doubts, the CNT paper production process also causes nano particles emissions to air, but due to very efficient air cleaning machines, the nano particle concentration in the laboratory is lower than outside (background concentration of nano particle). This is shown by nano particle air measurements (10-1000 nm) of a German labour protection organisation. 5.2

The comparison of the six different optimization options reveals that the last option, recycling of solvent, shows the best overall performance and is in addition the only option, which reaches a comparable technical quality of the gained CNT paper, which is an important requirement.

recycling solvent

reference

Global Warming Potential

recycling solvent

Material Costs

reference

recycling solvent

CNT Emissions to Water (Dispersion)

Figure 6: Quantitative effect of the optimisation process At comparable bucky paper quality, the recycling of solvent represents the best of six investigated optimisation option. Within the dispersion process, up to 70% of the solvent can be recycled with low efforts for reprocessing. The quantitative effects of the optimisation option “recycling solvent” are shown in Figure 6. The Global Warming Potential (GWP) is reduced by 65%, the production costs are decreased by 59% (total costs by 16%) in comparison to the reference case (status quo of CNT paper production) [5]. In addition by a continuously recycling of the solvent the nano particle emission to the water path could be prevented.

Solvent Solvent Solvent Solvent replacement by Solvent replacement by replacement by replacement by 100% replacement up 100% 100% 100% alternative to 30% by water water/tensideX1 water/tensideX2 water/tensideX3 solvent mixture mixture mixture

Recycling of reference solvent

Quality bucky paper

A

A/B

B/C

B

C

C

A

Economic profile

C

A/B

B

A/B

A/B

C

A/B

Ecological profile

C

C

B

A/B

A/B

A/B

A/B

CNT emissions (to water)

C

C

C

C

C

C

A/B

Table 1: Qualitative comparison of optimisation strategies.

188 7

Life Cycle Design - Selected Applications SUMMARY

The use of multi-walled carbon nanotubes for the production of bucky papers has opened up new application fields. But the production of bucky papers still is considered to be too elaborated and costly for a broader application. Furthermore the ecological implications of the bucky paper production are unknown. The economic and ecological assessment of the carbon nanotube paper production on a laboratory scale reveals that the dispersion of the MWNT has a great impact on the ecological profile and the costs. Mainly responsible is the use of solvents for dispersing nanotubes. The economic and ecological results concerning the status quo of bucky paper production is essential for the development of optimisation strategies. Different optimisation strategies are investigated and qualitative evaluated. The selection of the most promising optimisation option is based on technical, economic, and ecological aspects, including nano particle emissions. A substantial decrease of costs and ecological impact with good product quality (of bucky paper) is reached by the optimisation option “recycling of solvent”. The gained information is essential for an upscale of bucky paper production in a continuous mode. Further investigations are needed to compare bucky papers with traditional materials in different application fields over the entire life cycle. The presented work showed one possible approach enabling a more responsible development of a new technology, which might bear some unknown risks. 8

REFERENCES

[1]

Weil, M., Buchwald, A., Dombrowski, K., Jeske, U., Buchgeister, J. - Eds. - (2007): Materials Design and Systems Analysis, Shaker-Verlag, p. 321.

[2]

See, C. H., Harri, A.T. (2007): A Review of Carbon Nanotube Synthesis via Fluidized-Bed Chemical Vapor Deposition. Ind. Eng. Chem. Res., 46 (4), pp 997–1012.

[3]

Guinée, J.B. - Eds - (2002): Life cycle assessment. An operational guide to the ISO standards, CML Leiden, p. 708.

[4]

Heijungs, R., Guinée, J.B., Huppes, G., Lankreijer, R.M., Udo de Haes, H.A., Wegener Sleeswijk, A., Ansems, A.M.M., Eggels, P.G., Duin, R. van, Goede, H.P. de (1992): Environmental Life Cycle Assessment of Products; Guide & Backgrounds, CML Leiden.

[5]

Weil, M., Schebek, L., Forero, S., Crizeli, S. (2009): Bucky papers - a prospective economic and ecological investigation for the upscale of the production process. SETAC Europe 19th Annual Meeting. Göteborg, Sweden.

Proposal of a Design Support Method for Sustainability Scenarios 1st Report: Designing Forecasting Scenarios 1

1

1

1

1

Haruna Wada , Yusuke Kishita , Yuji Mizuno , Maki Hirosaki , Shinichi Fukushige , Yasushi Umeda 1

1

Department of Mechanical Engineering, Graduate School of Engineering, Osaka University, Osaka, Japan

Abstract Although there are many scenario description methods, computational support has not been provided for scenario design. This paper proposes a method for supporting design of forecasting scenarios. This method supports determining storylines, which are key assumptions of sub scenarios, and describing sub scenarios based on the causal network and storyline. As a case study for verifying feasibility of this method, we described a forecasting scenario about changes of automobile industry when electric vehicles are diffused. Results illustrate that the usage of causal networks effectively supports generating storylines. Also, describing scenario texts is supported by detailing causal networks and the storylines. Keywords: Sustainability Scenarios; Scenario Design; Forecasting Scenario

1

INTRODUCTION

The manufacturing industry must be changed so as to contribute to constructing a sustainable society by solving a range of problems, such as resource exhaustion. However, it is difficult to achieve sustainable manufacturing only by piling up individual techniques. Rather, we should clarify future visions of sustainable manufacturing and integrate various key technologies, socioeconomic factors, and policy framework toward them. In Life Cycle Engineering, we thus should clarify the relationship between technological opportunity and visions of sustainable manufacturing. This leads to grasping the direction of Life Cycle Engineering. One of hopeful approaches for drawing such future visions is to describe scenarios. Besides scenario planning, there are several methods for drawing futures including trend analysis, simulation modeling, historical analysis, and visioning [1]. Nevertheless, since scenario planning is more comprehensive than others, this paper chose scenario planning as its approach. A scenario is a story that connects a description of future to present realities in a series of causality [2]. Numerous scenarios have already been described in order to draw visions of future societies, such as IPCC’s emissions scenarios [3] and IEA’s World Energy Outlook [4]. However, scenario description processes have not yet been well formalized and sufficient computational support has not been provided for them. As the first step to solve these problems, this paper proposes the concept of “scenario design,” which means a sequence of activities required to describe scenarios. It should contain not only scenario description, but also analyses and verification of scenarios. Based on this concept, this paper proposes a method for supporting the design of scenarios. For this purpose, we formalize a scenario design process. In general, description processes of sustainability scenarios are categorized into two types; that is, forecasting and backcasting [5]. In forecasting process, scenarios are written by envisioning various futures from the present, while in backcasting process a scenario writer firstly describes a future end-point and then describes pathways from the end-point to the present. This paper focuses on

the design of forecasting scenarios (a scenario designed by the forecasting process), because the backcasting process involves the forecasting and, therefore, the forecasting process is a fundamental element in scenario design. This paper is organized as follows. Section 2 briefly summarizes literature reviews regarding sustainability scenario design and then shows problems of existing scenario description methods. Section 3 proposes a method for designing forecasting scenarios. Section 4 presents a system for supporting the proposed method. Section 5 illustrates a case study. Section 6 discusses advantages and issues of the proposed method based on the case study. Section 7 concludes this paper. 2 2.1

DESIGNING SCENARIOS Requirements for designing forecasting scenarios

Designing forecasting scenarios involves, at least, three tasks; describing forecasting scenarios, reviewing and evaluating scenarios, and feeding the evaluation back to scenario description [6]. There tasks lead to the following four requirements for designing forecasting scenarios: I.

To describe scenario texts by detailing the texts gradually.

II. To describe several sub scenarios, each of which describes a specific future, in order to envision different futures from the current situation [7]. III. To collect abundant information to describe scenarios [8]. IV. To clarify the logical structure of scenarios for enabling us to rationally understand and review scenarios. Requirement IV is related to scenario representations, while the other three requirements concern the design process of scenarios. 2.2

Existing scenario description methods

There are a number of methods for describing forecasting scenarios, such as Story and Simulation Approach [7], Scenario Development and Analysis [9], Dynamic Scenarios [10] and Scenario planning [11]. For example, Story and Simulation

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_33, © Springer-Verlag Berlin Heidelberg 2011

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Approach [7] is a method for description based on narrative stories and quantitative simulations and Scenario Development and Analysis [9] extends Story and Simulation Approach [7]. In this method, scenarios are described by four steps; (1) clarifying the purpose and structure of the scenario, (2) laying the foundation for the scenarios, (3) developing and testing the actual scenarios and (4) communication and outreach. In Dynamic Scenarios [10], a scenario is expressed as a system dynamics model, which is a kind of causal networks.

Node

Link

In describing scenarios, other general methods are used, such as Probability trees [6], Morphological analysis [6], SWOT analysis [12] and PEST analysis [11]. However, existing scenario description methods do not provide computational support of the scenario design and scenario’s logical structure is not clearly described. 3

element positive(A, B)

Node A causes a positive (+) effect on node B.

negative(A, B)

Node A causes a negative (-) effect on node B.

related(A, B)

Node A causes and effect on node B, where the polarity (+/-) is undetermined.

Table 1: Types of nodes and links in Word Level.

Approach

This study mainly supports a first task mentioned in Section 2.1 and this paper proposes a design method for forecasting scenarios in order to satisfy the four requirements mentioned in Section 2.1 by tackling the following two tasks:

ii.

Definition A constituent of the object world of the scenario.

Type

Definition

deploy(A, B)

Node A (Word level node, i.e., a node of a causal network) is deployed to a description of node B (Expression Level node, i.e., a clause of a sub scenario texts).

DESIGN METHOD FOR FORECASTING SCENARIOS

3.1

i.

Type

To formalize the process of scenario design as four steps, that is, setting a problem, construction of rough causal network, describing storylines, and describing sub scenarios, as shown in Figure 1. With this process, the design team can gradually detail a scenario to be designed in the form of causal networks, storylines, and scenario texts. After setting a problem for recognizing the main theme of the scenario, the team describes the present situation of the theme as two causal networks in different levels of granularity as described in Section 3.3. A storyline represents a set of key assumptions of future direction to describe a sub scenario. A storyline is described by detailing critical elements of the causal network. And scenario texts are composed in order to understand the scenario easily. In order to formalize the format of scenario expression, this paper employs the structural scenario description method [13] [14]. The structural description method clarifies logical structure of scenario texts in a computable manner well as enable us to rationally understand scenarios (see Section 3.2 for details).

Table 2: A type of a link between Expression and Word Level. 3.2



Scenario Level: expresses relationships among sub scenarios, including the hierarchical relation between a parent scenario and its sub scenarios.



Expression Level: expresses logical relations of clauses in a sub scenario.



Word Level: expresses causal networks of the target world.



Data Level: expresses simulations used descriptions and their input and output data.

Problem

I.

Rough causal network

Design process of forecasting scenarios

Setting a problem

As the first step, a scenario design team set a problem of a scenario to be designed. For describing the problem, we define a template as shown in Table 3. This step intends to make sure that the team can organize their ideas and recognize what to describe in the scenario. II. Constructing rough causal network

Storyline

Detailed causal network

scenario

In this method, we model the design process for forecasting scenarios as follows (see Figure 1):

Ⅱ Constructing rough causal network

Ⅲ Describing storylines

for

In this paper, we express sub scenarios and storylines using Expression Level, while we represent causal networks using Word Level (see Table 1). And we define the relation between Expression and Word Level, which are used for describing sub scenarios, as shown in Table 2. 3.3

Ⅰ Setting a problem

Structural scenario description method

We have proposed a structural scenario description method for explicitly representing logical structure of a scenario on a computer. To represent a scenario structure from macroscopic and microscopic viewpoints, this method represents a scenario in the following four levels [13] [14]:

In this step, the design team expresses the target world of the scenario as causal networks.

Sub scenario

Ⅳ Describing sub scenarios Figure 1: Design process for forecasting scenarios.

According to our preliminary study, it is effective to describe the target world by using two causal networks different in granularity; namely, a rough causal network, which is described in this step, and a detailed causal network that is made by detailing the rough causal network in step IV (see Figure 1). On one hand, describing the rough causal network helps the design team to examine different directions of visions. On the other hand, constructing the

Life Cycle Design - Selected Applications Item

Description Title of the scenario

Title

Objective

Background

Time horizon

In this process, we assume that the team selects key drivers based on uncertainty and impact on elements. Then, the team describes a storyline by assuming states of the key drivers.

Objective for describing the scenario

IV. Describing sub scenarios

E.g. To discuss changes of automotive industry. To calculate CO2 emissions when EV is diffused.

The scenario design team describes each sub scenario in the form of structured scenario shown in Section 3.2, by detailing the storyline and the detailed causal network.

Motivation for describing the scenario

In this step, the team constructs a detailed causal network from the rough causal network constructed in step II. The detailed causal network guides the team; the team describes a sub scenario by detailing elements of the causal network and its relation.

E.g. For achieving the low carbon society, EVs will be diffused. Policy makers want to look how this diffusion changes structure of automobile industry. Starting year of the scenario

End year

End year of the scenario

E.g. 2010 E.g. 2030 Targeted region in the scenario E.g. Japan

Main actors

Main stakeholders in the scenario E.g. Automotive industry Stakeholders involved in the scenario, other than the main actors

Actors

elements that affect futures and have high uncertainty in the causal network.

E.g. Electric vehicles (EV) diffused society scenario

Start year

Region

191

E.g. Japanese automotive companies, Japanese electric and electronics manufacturers, automotive companies in developing countries Table 3: Problem description of a scenario.

detailed causal network is helpful for supporting composition of the sub scenario texts in Step IV. III. Describing storylines In this step, the scenario design team describes storylines, which are key assumptions of sub scenarios by extracting key drivers of the rough causal network. These key drivers are the crucial

For example, assuming a part of a detailed causal network as shown in Figure 2, we can describe a sub scenario consisting of node (A) “If the supply of rare earth decrease,” from node (a) and describe node (B) “the Japanese manufacturing industry will be less competitive,” from node (b). Then, nodes (A) and (B) are connected to nodes (a) and (b) by the link ‘deploy,’ respectively. In this case, we put a link of “logical_jump” in Expression Level, because node (B) is derived from node (A) with a leap of logic. This relation between nodes does not fill the necessary and sufficient condition. In this way, we describe sub scenarios with the structural scenario description method. Finally, the scenario design team organizes scenario texts by changing order of sentences and classifying them into their meanings. 4

SCENARIO DESIGN SUPPORT SYSTEM

In this study, we developed Scenario Design Support System for supporting the design of forecasting scenarios based on the method proposed in Section 3. Figure 3 depicts the architecture of this system, which consists of five elements; Scenario Design Manager, Problem Editor, Causal Network Editor, Storyline Editor, and Scenario Structural Description Support System. Scenario Design Manager manages the three sub systems of Problem Editor, Causal Network Editor, and Storyline Editor. The design team describes problems, causal networks, and storylines of scenarios with these sub systems. Scenario Structural Description Support System supports describing sub scenarios from these scenario elements (i.e., storylines and causal networks).

Figure 3: Scenario Design Support System. Figure 2: Example of describing sub scenarios.

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Storyline Item

Urban Centralization Sub Scenario

Compact City Sub Scenario

Form of city

There are some metropolitan areas of 10 million people living there.

Form of many cities is Compact City. Compact cities about 30 km in diameter disperse over Japan.

Transportation

In urban area: Mainly public transportation. In rural area: Community buses and automobiles. Between urban and rural areas: Public transportation and automobiles.

In city: Small EVs at low speed, LRT, and bicycle. Most of automobiles are used on a park-and-ride basis. Between cities: Mainly public transportation.

Table 5: Storylines of two sub scenarios. 5

CASE STUDY

1

We execute a case study for verifying advantages and issues of the proposed method. This case study targets diffusion of Electric Vehicles (EVs) in Japan, because the diffusion of EVs is effective for achieving a low carbon society. We here assume that policy makers design a scenario to discuss changes in the structure of automotive industry when EVs are diffused. 5.1

Scenario design process in the case study

The scenario design process in this case study was carried out as follows: I.

Setting a problem

We set the problem as the example shown in Table 3. We set automotive industry as the main actor and Japanese automotive companies, Japanese electric and electronics manufacturers, automotive companies from developing countries as actors. In steps II, III and IV, we discussed particularly about automotive industry set in this problem setting.

II. Constructing rough causal network According to the problem setting, we picked up elements about automotive industry, such as “Energy supply for vehicles,” “Energy price,” “Users’ needs for mobility,” and “Form of city” by brainstorming and constructed a rough causal network by relating them as shown in Figure 4. Here, we constructed the relations between these elements by “related” links, because we considered that node (a) effects on node (b) and that nodes (b) and (c) effect on node (d). III. Describing storylines In this step, we described storylines by detailing key drivers chosen from the causal network. First, we set uncertainty and weight values of each element and our system calculated impact values of each element based on each weight. We select key drivers according to product of uncertainty and impact. Table 4 lists five highest elements out of all 20 elements in terms of the product. We selected “Form of city” as a key driver based on fourth in Table 4. In terms of “Form of city”, we identified two patterns of concentration and disintegration and we made two storylines, namely, the storyline of “Urban Centralization Sub Scenario” and one of “Compact City Sub Scenario” as shown in Table 5. IV. Describing sub scenarios In this step, we constructed two detailed causal networks by detailing the rough causal network so as to follow the two storylines. For example, since we considered that how to use cars is especially important in “Compact City Sub Scenario,” we put elements of the detailed causal network “How to use cars” and “Needs for cars” by detailing an element of “Users’ needs for mobility” in the rough causal network. As a result, we created 66 elements of the detailed causal networks in “Urban Centralization Sub Scenario” and 96

Uncertainty

Impact

Uncertainty X Impact

Global Political Cooperation

2

6.4

12.8

Global Economic Cooperation e.g. ETA

2

6.2

12.4

Energy Supply for Vehicles

5

1.4

7.0

Form of City

4

1.3

5.2

Energy Price

2

1.4

2.8

Element

Figure 4: Elements of the rough causal network (partially). 1

Full texts of the scenario designed in this case study can be downloaded from the 3S homepage (http://www-lce.mech.eng.osaka-u.ac.jp/3s/).

Table 4: Elements of the rough causal network (partially).

Life Cycle Design - Selected Applications

193

Figure 5: A part of structured scenario of Compact City Scenario. elements in “Compact City Sub Scenario” from 20 elements of the common rough causal network. We described two sub scenarios from the detailed causal networks and the storylines. For example, Figure 5 illustrates a part of structured sub scenario developed from the causal network in “Compact City Sub Scenario”. Node (A) is a part of the storyline of the sub scenario and nodes (a) and (b) are a part of the causal network. For example, we wrote a sentence of node (B) “Since the density of population in each city is high, roads and passages are narrow.” by deploying node (A) and node (a). We express the relation between nodes (A) and (B) by a link of “logical_jump”, because node (B) is derived from not node (A) rationally but our assumption. This representation enables to distinguish logical part of a scenario from logically uncertain part in deriving hypotheses or conclusions, such as node (B), (C) or (D). Also, we express relations between the causal network and sentences of sub scenario by the link of “deploy”. Then, we made node (C) “Mid-sized cars are not useful in narrow roads and passages in cities.” by deploying nodes (B) and (b), and node (D) “Small cars will only be used in the compact city.” by derived from nodes (C) and (b). 5.2

Conclusions of the scenario

The conclusions of the designed scenario are summarized as follows. In “Urban Centralization Sub Scenario,” EVs and GVs are used in the same way as the current and Japanese automotive companies have advantages similarly to the current situation. Therefore, it is concluded that structural changes of automotive industry are moderate and CO2 emissions from the automobile sector does not decrease so much. On the other hand, in “Compact City Sub Scenario,” various manufactures develops small EVs and

each EV is owned not per family but per individual. In the end, in 2030, the number of automobiles increases and small EVs are diffused explosively. As a result, changes of industrial structure are large. Since EVs are diffused, CO2 emissions decreases compared with 2010. But, as a side-effect, the number of discarded automobiles will increase as the result of increased number of small EVs. It is found out that automotive related industry expands in this society in 2030, as the spread diffused EVs. About material industry, we concluded that it is necessary to secure rare metals and rare earths and to develop alternative materials. About energy industry, development of the electric power supply system adaptive to changes of electric demand of EVs is needed. 6

DISCUSSION

Using the proposed method, we succeeded in designing a scenario consisting of two sub scenarios as described in the previous section. The method supported constructing two levels of causal networks (i.e., rough and detailed), extracting key drivers from the rough causal network, making storylines, and deploying scenario texts from the causal networks and the storylines. By extracting key drivers from a rough causal network, we described storylines. As a result, we have shown two sub scenarios that indicate different worlds. Table 6 depicts the ratio of nodes in Expression Level deployed from the detailed causal network to all nodes in Expression Level, which consists of scenario texts. This ratio indicates how much we can describe the scenario texts systematically in this method. Table 6 shows that 90% of nodes in Expression Level in “Urban Centralization Sub Scenario” and 91% in “Compact City Sub

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Scenario” are deployed from the causal network. The result indicates that causal networks are useful in describing scenarios. Since the causal networks constructed in our method basically targets the present situation, we cannot describe scenarios that contains a quantum leap from the present. Proposing a method for composing such scenarios is one of our future works. A scenario design method based on backcasting is one of leading candidate of it

[7]

Alcamo, J. (2001): Scenarios as Tools for International Environmental Assessments, Environmental Issue Report No. 24, European Environmental Agency, Copenhagen.

[8]

Matsuoka, Y., Harasawa, H. and Takahashi, K. (2001): Scenario Approach on Global Environmental Problems, in: J. Environmental Systems and Engineering, No. 678 / VII -19, pp. 1-11. (in Japanese)

[9]

Jäger, J., Rothman, D., Anastasi, C., Kartha, S. and Notten, P. (2007): Scenario Development and Analysis, GEO Resource Book: A Training Manual on Integrated Environmental Assessment and Reporting, UNEP and IISD, Winnipeg, Canada.

[10]

Ward, E. and Schriefer, A.E. (1998): Dynamic Scenarios: System Thinking Meets Scenario Planning, in: Fahey, L. and Randall, R.M. (eds.), Learning from the Future, John Wiley & Sons, New York, pp. 140-156.

[11]

O’Brien, F.A. (2004): Scenario planning – lessons for practice from teaching and learning, in: European Journal of Operational Research 152, pp. 709-722.

[12]

Weihrich, H. (1993): Daimler-Benz’s Move towards the Next Century with the TOWS Matrix, in: European Business Review, Vol. 93, pp. 4-11.

[13]

Kishita, Y., Yamasaki, Y., Mizuno, Y., Fukushige, S. and Umeda, Y. (2009): Development of Sustainable Society Scenario Simulator – Structural Scenario Description and Logical Structure Analysis, in: Proc. of 16th CIRP Int. Conf. on Life Cycle Engineering 2009, pp. 361-366.

[14]

Kishita, Y., Mizuno, Y., Fukushige, S. and Umeda, Y. (2010): Development of Sustainable Society Scenario Simulator – Connecting Scenarios with Associated Simulators, in: Proc. of 17th CIRP Int. Conf. on Life Cycle Engineering 2010, pp. 402407.

By representing scenario texts by the structural scenario description method, we can utilize the representation as follows: 

To trace reasons of scenario’s conclusion and therefore, to facilitate our review.



To make sure of consistency in scenarios by tracing relations between the causal networks and the scenario texts.

For example, when we verify the contents of node (D) in Figure 5, we trace the link of “logical_jump” and we check the hypothesis of node (C). We trace relation and finally we can reach node (A), which is the hypothesis of node (D). We believe that this method is useful for supporting modification of scenario texts by clarifying rationales for scenario descriptions. 7

CONCLUSION

Based on the structural scenario description method, we proposed a design support method for sustainability scenarios based on forecasting, which employs storyline and causal network. The case study clarified that the proposed method is useful for supporting scenario design process in a stepwise manner. The method can support developing scenario texts. Moreover, the relations between scenario texts and causal network enable the designer to trace rationales of scenario texts. Future works include development of a scenario design support method based on backcasting, which can support describing changes in a larger scale. ACKNOWLEDGMENTS This research is financially supported by Grant-in-Aid for Scientific Research (No. 20246130), JSPS, Japan. REFERENCES [1]

Duinker, P.N. and Greig, L.A. (2007): Scenario analysis in environmental impact assessment: Improving explorations, in: Environmental Impact Assessment Review 27 (2007), pp. 206-219.

[2]

Glenn J. and the Futures Group International (2003): Scenarios, in: J.C. Glenn and T.J. Gordon (eds.), Futures Research Methodology – V2.0, AC/UNU Millennium Project, Washington, D.C.

[3]

IPCC (2007): Climate Change 2007, Synthesis Report, Contribution of Working Groups I, II, III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), Geneva, Switzerland.

[4]

International Energy Agency (IEA) (2009): World Energy Outlook 2009, IEA Publications, Paris.

[5]

Dreborg, K. (1996): Essence of Backcasting, in: Futures, Vol. 28, No. 9, pp. 813-828.

[6]

Bishop, P., Hines, A. and Collins, T. (2007): The Current State of Scenario Development: An Overview of Techniques, in: Foresight, 9/1, pp. 5-25.

Evaluating Trade-Offs Between Sustainability, Performance, and Cost of Green Machining Technologies 1

2

1

2

Moneer Helu , Jan Rühl , David Dornfeld , Patrick Werner , Gisela Lanza 1 2

2

Laboratory for Manufacturing and Sustainability, University of California, Berkeley, USA Institute for Production Science, Karlsruhe Institute of Technology, Karlsruhe, Germany

Abstract The growing demand to reduce environmental impacts has encouraged manufacturers to pursue various green manufacturing technologies and strategies. These solutions, though, may have a direct impact on several productivity metrics including availability, quality, service life, and cost. This study presents an approach to evaluate the trade-offs between the environmental, performance, and financial impacts of green machining technologies by combining green manufacturing principles into life cycle performance evaluation. The approach is validated by investigating the implications of reducing the processing time by increasing the cutting speed and chip load to green a horizontal milling process. Keywords: Life Cycle Cost; Green Machining; Data Acquisition

1

INTRODUCTION

Machine tool development has historically focused on reducing operating costs while simultaneously improving performance as measured by several metrics including availability, reliability, dimensional accuracy, and precision. To increase performance, machine tools have become more complex and automated in design, which has resulted in higher resource demands that have generally conflicted with rising resource costs due to growing scarcity and regulation. These trends have encouraged manufacturers and users to pursue various green machining strategies and technologies that enable increasingly efficient use of limited resources. Design and operation for the environment, though, has a direct impact on several factors including availability, quality, service life, and cost. Thus, it is important to quantify resource flows in machining to enable manufacturers to better guarantee performance as well as provide decision makers with tools that evaluate the tradeoffs between the environmental, performance, and financial impact of any potential technology decision. 2 2.1

CURRENT ASSESSMENT TECHNIQUES Environmental impact assessments

Life cycle assessment (LCA) has been traditionally used in the literature to quantify several resource flows (typically electrical energy) in machining. LCA is a quantitative tool that measures the resource and waste flows of a product from its fabrication to its endof-life [1]. Much of the early LCA work focused on assessments of different green machining strategies and technologies. There was also an observed need to establish a set of quantifiable dimensions to determine the trade-offs in process planning decisions. This area of work focused on the development of models to capture the effects of machining physics on environmental and public health impacts. Munoz and Sheng [2] provided the seminal model that comprehensively links machining parameters (e.g. speed, feed, depth of cut) to the environmental impacts of a machining process (e.g. energy consumption, process rate, mass flow of generated wastes). This approach was extended to energy by developing a

web-based energy estimation tool [3]. Subsequent work has connected LCA results from the literature to process planning to enable its use in the design of products [4]. While this research has provided initial tools for decision makers to evaluate current green machining strategies, these tools are based on theoretical models instead of captured data, which may limit the accuracy of these tools when gauging the trade-offs in process planning decisions [5], [6]. More recent work has addressed the deficiencies in previous process planning tools by developing methods to physically measure the environmental impacts of machine tools. Vijayaraghavan and Dornfeld [6] propose automated energy monitoring of machine tools using event stream processing to correlate measured energy consumption to machine tool usage. This enables full characterization of the machining process and the drivers of energy consumption. Similarly, Kuhrke, et al. [7] advocate a methodology to estimate the overall yearly energy consumption of a machine tool and any related costs by either measuring or calculating the energy consumption of individual components of the machine tool and considering the actual usage instead of assuming a constant power consumption. While calculating energy consumption inherently introduces inaccuracy into this approach, Kuhrke, et al. [7] argue that the feasibility of power measurements for highly specialized machine tools demands that calculations be used to simplify the approach for purchasing decisions. Dietmair and Verl [8] propose a nodular, component approach that also considers the actual usage of the machine tool to drive a modeling framework that estimates overall energy consumption using characteristic relationships between process parameters and energy consumption and other resource flows for each component. These characteristic relationships should be measured and can be found in the literature (e.g. Draganescu, et al. [9] modeled the specific energy of milling processes, and Klocke, et al. [10] modeled the specific energy of milling and drilling processes). 2.2

Performance and financial impact assessments

Increased competition and reduced profit margins have forced manufacturers to find ways to reduce operating costs and improve

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_34, © Springer-Verlag Berlin Heidelberg 2011

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the performance of their facilities and equipment. So, many manufacturers have used life cycle cost (LCC) analysis as the primary tool to evaluate the performance and financial impact of their equipment and facilities. LCC analysis is a quantitative tool that compares the cost-effectiveness of different investment options from the perspective of a manufacturer or other business decision maker [11]. It takes into account all business costs over the life of the investment option including those costs associated with acquisition (e.g. sales price), ownership (e.g. maintenance), and disposal. The automotive sector has been one of the biggest drivers of LCC analysis techniques to help establish warranty demands with their suppliers [12]. Many approaches that seek to optimize the LCC of manufacturing equipment have focused on maintenance since these activities typically dominate costs. This has driven the development of life cycle performance (LCP) evaluation, which relates the overall equipment effectiveness (OEE) – a performance metric that combines reliability, availability, and quality – to the total monetary costs from the initial investment to disposal to generate an efficiency metric for a manufacturing system [13]. Thus, LCP evaluation broadens LCC analysis by relating the results of an LCC analysis to the performance of an investment option. LCP evaluation has been primarily used to optimize technical services (e.g. maintenance intervals and spare part provisions) and assess and control the risks associated with establishing warranty and servicing contracts [12], [13]. While the development of LCP evaluation from LCC analysis represented an important first step towards combining performance and financial assessments, neither approach addressed resource flows or environmental impacts, which can be highly significant to the OEE and financial costs of a manufacturing system. So, it has become very important to capture environmental impacts within both LCP and LCC approaches. Early attempts addressed these limitations by integrating LCA into LCC analyses. One example of this approach is economic input-output LCA (EIO-LCA), which was developed at Carnegie Mellon University. This approach relates the environmental impacts of each sector of an economy to the monetary value of that sector as defined by government economic inputoutput tables [1]. Norris [11] describes other approaches referred to as “partial solutions” that combine a full LCA with a partial LCC or vice-versa. The first type of partial solutions (full LCA and partial LCC) involves adding cost flows to a traditional LCA. The second type of partial solutions (partial LCA and full LCC) adds a truncated LCA (e.g. some resource flows from the main facility plus some first tier suppliers) to a full LCC. Norris [11] also highlights two “full solutions,” PTLaser and TCAce. PTLaser includes dynamic LCA (i.e. time-varying flows), variable cost functions, and flexible investment, depreciation, accounting, and discounting tools in order to combine a full LCA with a full LCC. TCAce extends current LCA and LCC approaches to include all external costs including those that are less tangible (e.g. societal costs). Eco-efficiency is a last approach to combine LCA and LCC by normalizing the metrics from each analysis to enable an equal comparison [15]. 2.3

Combined assessments and proposed approach

The current literature contains many tools that incorporate financial costs into either an environmental or performance assessment. However, these tools do not generally address all three factors simultaneously, which neglects their inherent interdependence. Recent work, though, has begun to develop methods that enable consideration of all three impacts. For example, Kuhrke, et al. [7] and Dietmair and Verl [8] demand a full understanding of actual machine usage even though the aim of both is to measure overall energy consumption. Similarly, Thiede and Herrmann [16] evaluate production criteria as well as energy consumption and related costs,

but it is based on a simulation rather than a measurement approach. Also, Inamasu, et al. [17] include environmental (energy), performance (tool life), and financial factors when physically measuring the effect of cutting conditions on the energy consumption of a machine tool. Niggeschmidt, et al. [13] provided a basic framework to incorporate green manufacturing principles into LCP evaluation so that environmental, performance, and financial impacts could be simultaneously considered. This framework comprised three steps: 1. Design and integration of appropriately targeted process monitoring systems to measure relevant data sources. 2. Characterization of the manufacturing system based on the collected data. 3. Optimization of the manufacturing system based on the developed characterization. The goal of this paper is to apply the framework developed by Niggeschmidt, et al. [13] to develop a methodology that quantifies changes in environmental impact with respect to performance and cost. The approach is presented in Figure 1 and is based on data acquisition rather than modeling or simulation to ensure accurate calculation of impacts. By applying this approach to a baseline scenario (defined as “machining as usual”) and other alternatives that implement a green machining strategy, the true costs of these technologies can be determined.

Figure 1: Proposed methodology to combine environmental, performance, and financial impacts when evaluating investment options. 3

GREEN MACHINING TECHNOLOGIES

Many green machining approaches have focused on process and design level improvements through new technologies and machining strategies. To validate the approach described in Figure 1, though, this study focuses on processing time reductions [3]. The power demand of a machine tool can be divided into three components: constant, variable, and processing (or cutting) power (see Figure 2). Constant power demand is due to auxiliary components that are always powered and have a demand irrespective of the selected machining parameters (e.g. computer panels and lights). Variable power demand is due to those components that have a constant baseline demand but that may not always be active (e.g. spindle and drive motors). Finally, processing or cutting power demand is the power demand dependent on the material removal process. Constant and variable power demand are together referred to as tare power demand since this is the minimum amount of power that is required to run the machine tool whether or not chips are formed. Dahmus and Gutowski [18] found that the tare power demand increases with automation, which means that the energy consump-

Sustainability in Manufacturing tion of many modern machine tools is dominated by this constant power demand. Thus, reducing the processing time better amortizes these constant charges and may effectively reduce the specific cutting energy.

197 parameter was increased independently to better study the effects of each on the overall environmental and performance impacts. Two scenarios were considered for each parameter to initially validate our approach. The cutting speed was increased to 55 m/min and 60 m/min, which represented a feed rate increase of 10% and 20% respectively. Each chip load was increased by a 20% and 40% for the increased chip load scenarios, which represented a feed rate increase of 20% and 40% respectively. The chip load was increased further than the cutting speed due to stability limitations (increased cutting speed without an increase in feed rate typically induces chatter). 4.2

Figure 2: The typical power demand of a machine tool [3]. 4

METHODOLOGY

Machining experiments were conducted on a Haas VF-0 vertical milling machine tool to study the impacts of a reduced processing time strategy. A baseline scenario was selected as well as alternative scenarios that reduce processing time by increasing the feed rate. Relevant data for a performance and environmental analysis were collected during each machining experiment. 4.1

Energy based environmental assessment

The overall power demand of the machine tool was measured to evaluate the environmental impact of each machining scenario by determining the electrical energy consumption. A Yokogawa CW240 wattmeter was used in a three-phase, three-wire, three-current setup. The current transducers and voltage clamps were installed at the power input and a sampling frequency of 10 Hz was used. Figure 4 shows the measured power demand for the baseline scenario.

Baseline and alternative scenario design

The test piece chosen for this investigation was developed by Behrendt [19] (see Figure 3). This part is meant to compare the energy consumption of various three-axis machine tools that have a work 2 area (defined by the x- and y-travel) between 0.1 and 1 m . It has been designed to fully exercise the machine tool by requiring every combination of axes to create eighteen different features using four tools: a 50 mm, 5 insert face mill; an 8 mm end mill; a 16 mm end mill; and an 8 mm drill. The initial workpiece material is an 82 mm x 82 mm x 25.4 mm 1018 AISI steel blank. The cutting speed is kept constant at 50 m/min. The chip load is kept constant for every feature except the face cut, which requires a chip load of 0.1 mm/tooth, and the small and large grooves sets, which require a chip load of 0.5, 0.6, and 0.7 mm/tooth for each subsequent groove. The depth of cut is also incrementally increased for each of the three machining passes used to machine each feature except the drilled holes.

Figure 4: Measured power demand for the baseline scenario (a 2 second moving average was used to smooth the plot). The power demand was assumed to be constant for the 0.1 seconds immediately after a measurement. This allowed the total electrical energy consumption to be estimated using Equation 1: k  0.1Pi  Etotal    , i 1  3600 

Figure 3: Standard part machined for each machining scenario (units in mm) [19]. The baseline scenario followed the standard presented by Behrendt [19]. To reduce the processing time, one may increase the number of flutes on the tool, increase the cutting speed, or increase the chip load. The latter two options were pursued in this study since they are typically the parameters that a machinist has most control over. While the cutting speed and chip load should be simultaneously increased to ensure a stable cut and good surface quality, each

(1)

where Etotal is the total electrical energy consumed (in kWh), k is the total number of data samples, and Pi is the ith measured real power demand. Real power (the portion of power used towards productive work) was used as opposed to apparent power (the total power including any losses in the electrical system) since power companies charge facilities based on real power as long as the power factor (a measure of efficiency defined as real to apparent power) of a facility is above a defined threshold (85% in California) [20]. Equation 1 was then used to estimate the change in total electrical energy consumption caused by each alternative scenario. 4.3

Load based performance evaluation

An LCP evaluation requires an understanding of the failure behavior of machine tool components. The failure behavior can be estimated using a reliability analysis that begins with the load profile on the machine tool components. Because these load profiles were difficult

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to obtain, the overall cutting forces were measured and assumed to affect all components equally. The cutting forces were measured for each scenario using a Kistler 9257A three-component dynamometer on which the workpiece was mounted. A Kistler 5004 dual mode amplifier set to a sensitivity of 200 N/V converted the dynamometer charge output to a voltage signal that was then recorded using LabVIEW Signal Express via a National Instruments NI USB-6009 multifunction I/O card. The load profile was generated using a sampling frequency of 1 kHz. Figure 5 shows the measured load profile for the baseline scenario.

where tj is the measuring interval, and Xij is the transformation of the characteristic load value measured over tj. Equations 2 and 4 were then used to estimate the change in cumulative damage caused by each alternative scenario. For a given conditional probability based on previous loads and a predicted future load profile, the cumulative damage then allows for a calculation of the remaining service life of the machine tool. 5

RESULTS

5.1

Energy based environmental assessment

The total electrical energy consumed during the baseline scenario was 0.387 kWh and the maximum power recorded was 13.1 kW. Table 1 summarizes the total electrical energy consumed and maximum power demanded during each alternative scenario relative to the baseline scenario. As expected, the total electrical energy consumed by the machine tool decreased for every scenario since it is most strongly dependent on the processing time. The slight difference between both 20% increase scenarios is likely due to measurement error. The greater decrease in energy consumption for larger increases in feed rate occurred because the effect on energy amortization per part is greater than that of the increased power required to run the higher feed rate. This suggests that an operating point exists that requires minimal specific cutting energy consumption [3], [10]. Also, the maximum power demanded by the machine tool increased for every scenario due to the increased power that the spindle and axes motors require for higher speeds. ∆Etoal Figure 5: Measured load profile for the baseline scenario (a 5th order Butterworth filter with cutoff frequency 0.005 Hz has been used to smooth the plot). A Weibull distribution approach is typically used to describe the stochastic failure behavior of machine tool components and statistically estimate their service life, but an alternative approach was required since the load profile on a machine tool is expected to vary with different machining processes [14]. So, the load-dependent reliability model was derived using an approach based on the Weibull Cumulative Damage Model, which relates the cumulative damage of varied loads to the Weibull distribution, and the Generalized Log-Linear Model. Cumulative damage, or cumulative exposure, is the effect caused by different stresses that decrease the service life of equipment. The general form of the Weibull Cumulative Damage Model is given by Equation 2: 

 W t,L  Ft,L   1 e  ,

(2)

where F is the probability of failure due to cumulative damage, t is time, L is the load vector, W is the normalized cumulative damage, and  is the shape parameter. W is written in the Generalized LogLinear Model as given by Equation 3: t

W t,L  

e

a0 

 a i X i t' i

dt',

(3)

0

where a0 and ai are model parameters, and Xi is a transformation of the load levels, Li, that depends on the type of load. For example, the power law offers that the natural logarithm is the appropriate transformation for mechanical stresses. The normalized cumulative damage presented in Equation 3 can be simplified to Equation 4:

W t,L 

 j

 a 0  a i X ij  e i  t j ,    

(4)

∆Pmax

Increased cutting speed scenarios 10% increase

-26.0%

+5.6%

20% increase

-29.7%

+12.6%

20% increase

-31.0%

+7.6%

40% increase

-40.7%

+13.8%

Increased chip load scenarios

Table 1: % change in total electrical energy consumption and filtered maximum power demand of the machine tool for each alternative scenario relative to the baseline case. 5.2

Load based performance evaluation

Table 2 summarizes the cumulative damage on each axis of the machine tool for each alternative scenario relative to the baseline scenario. These values were calculated by considering the stresslife relationship of bearings as an initial validation of our approach since bearings are an important part of many machine tool components. The cumulative damage on the x and y axes decreased with increased cutting speed. This was due to the slight decrease in cutting force created by the increased heat generation at the toolchip interface. Conversely, the cumulative damage on the z-axis increased with increased cutting speed despite the previously noted trend. This was due to the added stresses on the z-axis during the face mill cut created by run out of the face mill tool. Finally, the cumulative damage of all axes increased with increased chip load because of the strong, direct dependence of the cutting force on the chip load. The y-axis was unique in that increasing the chip load seemed to initially decrease the cumulative damage. This could likely be due to a suboptimal choice for the chip load for the baseline scenario from the perspective of cutting forces.

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∆Damagex

∆Damagey

∆Damagez

Increased cutting speed scenarios 10% increase

-8.7%

-37.9%

+39.8%

20% increase

-12.5%

-39.8%

+33.2%

Increased chip load scenarios 20% increase

+18.7%

-14.1%

+52.9%

40% increase

+31.2%

-0.2%

+113.2%

Table 2: % change in cumulative damage on each axis of the machine tool for each alternative scenario relative to the baseline case. 5.3

Total costs of alternative scenarios

Industrial facilities are typically charged for electricity based on both overall usage and peak power demand. In addition, the rates for both charges differ depending on the time of day (peak, off-peak, or partial-peak) and the time of year (summer or winter). Using the current rate schedule for the Pacific Gas and Electric Company (PG&E) in California [21], Table 3 shows how each alternative scenario may affect the electrical energy price per part. To determine the amount to which the increased power demand shown in Table 1 becomes amortized per part, it was assumed that a machine tool creates only the test piece for 12 hours per day (6 hours during peak and 6 hours during partial-peak in the summer; all 12 hours during partial-peak in the winter), 20 days per month, and that set up requires 30 seconds per part. Summer ∆Cost/Part

Winter

% Diff

∆Cost/Part

% Diff

Increased cutting speed scenarios 10% increase

-$0.001

-0.2%

-$0.008

-16.4%

20% increase

+$0.010

+4.3%

-$0.009

-17.6%

Increased chip load scenarios 20% increase

$0

0%

-$0.010

-19.9%

40% increase

+$0.004

+1.9%

-$0.013

-26.6%

Table 3: Electricity cost to produce 1 part using each alternative scenario relative to baseline scenario. The absolute cost difference per part was low for both the summer and winter pricing periods because the test piece is a simple part that is relatively cheap to produce. Also, the Haas VF-0 does not have too much auxiliary equipment, which means that the processing power is a relatively large portion of the overall power demand. So, reducing the processing time should not have had as significant an effect on the Haas VF-0 as it would have had on a larger or more automated machine tool where the processing power can be as little as 10% of the overall power demand [18]. Nonetheless, the percentage difference in electricity costs may still be substantial and did generally increase with increasing processing rate as seen in the winter pricing period. This trend should continue until a minimal operating point is reached due to the greater power required to operate the machine tool at greater loads. The summer pricing period did not have the same trend as the winter pricing period because of the relatively high demand costs ($12.67/kW and $2.81/kW for peak and partial-peak periods respectively [24]). Again, though, the summer pricing period would have more closely followed the winter pricing period if a larger or more automated machine tool were considered. The increase in damage that is shown in Table 2 also impacts costs because of its indirect relationship with the lifetime of a machine tool component. For example, the spindle bearings should be strongly affected by the increased damage in the z-axis for both of the increased cutting speed scenarios. So, a 20% increase in the

cutting speed increased the damage in the z-axis by 33.2%, which will decrease the service life of the spindle bearings by about 75% (that is, the machine tool will be able to machine 75% less parts before the spindle bearings will need to be replaced). In fact, because service life is measured in terms of parts produced in this approach, the relative change in damage is exactly equal to the cost of a component per part produced (e.g. if a spindle bearing costs $100 and has a life of 1000 parts, then they would cost $0.10/part for the baseline scenario and $0.133/part when the cutting speed is increased 20%, which is an increase of 33.2%). Thus, the increased cutting speed scenarios should generally decrease maintenance costs (if the damage in the z-axis is neglected since it was likely due to run out of the face mill), while the increased chip load scenarios should generally increase maintenance costs. 6

SUMMARY AND FUTURE WORK

This paper has presented an approach that considers environmental, performance, and financial impacts when evaluating green machining technologies and strategies. To begin the validation of this approach, a series of cutting experiments were performed to study the true costs of a reduced processing time strategy. The initial results indicate that such an approach may not provide great benefit for smaller machines or those will lower levels of automation such as the Haas VF-0 due to the increased loads on the bearings and other components of the machine tools and the marginal reductions in the electricity costs. However, these initial results do suggest that increasing the process rate could have significant benefits to larger and/or more automated machine tools were the processing power is a much smaller percentage of overall power demand and the machine tool components are designed to withstand greater forces. There are also other potentially significant costs that have yet to be included in this approach such as tool wear (which should be important for increased processing time strategies) and power factor. Furthermore, the performance evaluation should be improved to provide greater detail on the extent to which increased loads affect individual machine tool components. The preliminary results of this study suggest that power factors could be a promising green machining strategy since power companies provide many financial benefits to ensure a high power factor so that the electricity grid is most efficiently utilized. For example, for facilities that have greater than 400 kW demand, PG&E rewards power factors above 85% by reducing its fees by 0.06% for each percentage point above 85% [20]. Similarly, PG&E also discourages power factors below 85% by increasing its fees in the same manner. Many facilities generally operate at or above 85% when all powered systems are considered. However, machine tools tend to reduce the power factor due to the high resistive losses typical in motors. For example, a power factor of ~68% was typical for the Haas VF-0. There are two general ways to increase the power factor of equipment: use more power towards productive work, or change electrical components (e.g. motors) to higher efficiency models. Both are technologies that should be investigated further, especially the former option as many existing strategies may serve to promote this effect. Future work will focus on extending the current approach to consider other environmental impacts (e.g. water and machining fluid consumption, compressed air) and tool wear in addition to load and energy data on individual machine tool components to provide greater detail in characterizing the costs of green machining strategies. In addition, useful metrics such as energy reduction per Dollar of cost to implement the technology will be developed so that decision makers have the most relevant information when considering investment options. Through continued development, this approach

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may hopefully contribute towards existing cataloguing efforts such as the CO2PE! Initiative by providing true cost information for machining technologies and tools. 7

[11]

Norris, G. A. (2001): Integrating Life Cycle Cost Analysis and LCA, in: International Journal of Life Cycle Assessment, Vol. 6, No. 2, pp. 118-120.

[12]

Fleischer, J.; Wawerla, M. (2007): Risk Management of Warranty Contracts in Machine Building Industry, in: International Applied Reliability Symposium, Frankfurt, Germany.

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Niggeschmidt, S.; Helu, M.; Diaz, N.; Behmann, B.; Lanza, G.; Dornfeld, D. A. (2010): Integrating Green and Sustainability Aspects into Life Cycle Performance Evaluation, in: Proceedings of the 17th CIRP International Conference on Life Cycle Engineering, pp. 366-371, Heifei, China.

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Lanza, G.; Niggeschmidt, S.; Werner, P. (2009): Optimization of Preventative Maintenance and Spare Part Provision for Machine Tools Based on Variable Operational Conditions, in: Annals of the CIRP, Vol. 58, No. 1, pp. 429-432.

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Hendrickson, C. T.; Horvath, A.; Joshi, S.; Lave, L. B. (1998): Economic Input-Output Models for Environmental Life-Cycle Assessment, in: Environmental Science and Technology, Vol. 32, No. 4, pp. 184A-191A.

Kicherer, A.; Schaltegger, S.; Tschochohei, H.; Pozo, B. F. (2007): Eco-Efficiency: Combining Life Cycle Assessment and Life Cycle Costs via Normalization, in: International Journal of Life Cycle Assessment, Vol. 12, No. 7, pp. 537-543.

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Munoz, A. A.; Sheng, P. (1995): An Analytical Approach for Determining the Environmental Impact of Machining Processes, in: Journal of Materials Processing Technology, Vol. 53, pp. 736-758.

Thiede, S.; Herrmann, C. (2010): Simulation-based Energy Flow Evaluation for Sustainable Manufacturing Systems, in: Proceedings of the 17th CIRP International Conference on Life Cycle Engineering, pp. 99-104, Hefei, China.

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Diaz, N.; Choi, S.; Helu, M.; Chen, Y.; Jayanathan, S.; Yasui Y.; Kong, D.; Pavanaskar, S.; Dornfeld, D. (2010): Machine Tool Design and Operation Strategies for Green Manufacturing, in: Proceedings of the 4th CIRP International Conference on High Performance Cutting, pp. 271-276, Gifu, Japan.

Inamasu, Y.; Fujishima, M.; Hideta, H.; Noguchi, K. (2010): The Effects of Cutting Condition on Power Consumption of Machine Tools, in: Proceedings of the 4th CIRP International Conference on High Performance Cutting, Vol. 1, pp. 267270, Gifu, Japan.

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Narita, H., Desmira, N., Fujimoto, H. (2008): Environmental Burden Analysis for Machining Operation Using LCA Method, in: Proceedings of the 41st CIRP Conference on Manufacturing Systems, pp. 65-68, Tokyo, Japan.

Dahmus, J. B.; Gutowski, T. G. (2004): An Environmental Analysis of Machining, in: Proceedings of the 2004 ASME International Mechanical Engineering Congress and RD&D Expo, IMECE2004-62600, Anaheim, CA, USA.

[19]

Behrendt, T. (2010): Development of a Simulation-Based Application to Derive and Estimate Potentials of Efficiency Measures for Diverse Machine Tool Processes, Diploma Thesis, Braunschweig University of Technology.

[20]

Pacific Gas and Electric Company (2007): Economics of Power Factor Correction in Large Facilites >400kW, accessed 11/10/10, from: http://www.pge.com/includes/docs/pdfs/ mybusiness/customerservice/energystatus/powerquality/ power%20factor--revised-8-9-07.pdf.

[21]

Pacific Gas and Electric Company (2010): Industrial (JUNE 1, 2010 – Present), in: Pacific Gas and Electric – Tariff Book, accessed 11/17/10, from: http://www.pge.com/tariffs/ IndustrialCurrent.xls

ACKNOWLEDGEMENTS

This work was supported in part by Mori Seiki, the Digital Technology Laboratory (DTL), the Machine Tool Technology Research Foundation (MTTRF), Sandvik and other industrial partners of the Laboratory for Manufacturing and Sustainability (LMAS). The authors would also like to thank Thomas Behrendt, Andrew Waterbury, Edwin Wibowo, and the UC Berkeley Mechanical Engineering Department’s Student Machine Shop for providing valuable insight and advice. For more information, please see http://lmas.berkeley. edu/. 8 [1]

[2]

[3]

[4]

[5]

REFERENCES

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Klocke, F.; Schlosser, R.; Lung, D. (2010): Energy and Resource Consumption of Cutting Processes – How Process Parameter Variations can Optimise the Total Process Efficiency, in: Proceedings of the 17th CIRP International Conference on Life Cycle Engineering, pp. 111-115, Hefei, China.

Sustainable Production by Integrating Business Models of Manufacturing and Recycling Industries 1, 2

Christopher Jonsson

2

3

, Johan Felix , Anders Sundelin , Björn Johansson

1

1

Department of Product and Product Development, Chalmers University of Technology, Gothenburg, Sweden 2

CIT Recycling Development AB, Gothenburg, Sweden 3

CIP Professional Services AB, Gothenburg, Sweden

Abstract Future raw material shortage, high price levels and environmental regulations requires increased reuse of materials and components. This will substantially influence conditions for both manufacturing and recycling industries, which need to innovate their business models. Our hypothesis is that an integrated co-operation between organizations within these industries, employing symbiotic business models will increase the profitability and reduce the total environmental impact. Findings from interaction with manufacturing and recycling industries using a business model framework as baseline are presented. Results indicate that profit and decreased environmental effects can be achieved through symbiotic business models, but further development and implementation is needed. Keywords: Business Models; Sustainable Production; Industrial Ecology

1

INTRODUCTION

Future shortage of raw materials, high price levels and environmental regulations will require recycling of materials, as well as an increased level of re-use, repair and remanufacturing of components, than is currently the case today. This will substantially influence the conditions for both the manufacturing industry and the recycling industry where companies are starting to rethink their business models. Just as products can be designed for remanufacture, organizations can be designed to reduce the total environmental impact. The business model concept is based on the idea to illustrate how value is created and captured by an organization. It is a holistic concept that includes an organization’s value propositions and customers, how products and services are delivered, how revenues are generated, what resources, activities, and partners that is required, and the resulting cost structure [1]. It represents a new dimension of innovation and source of competitive advantage, and is seen as a new unit of analysis in addition to the product, firm, industry or network [2]. The purpose of this paper is to investigate if organizations within the manufacturing industry and the recycling industry could co-operate and align their business models, to increase the profitability and reduce the total environmental impact. The objective is also to identify incentives to work closer between the recycling and the manufacturing industry, and potential constraints to a closer interaction between the two industries. The definition used for the described closer collaboration in a business perspective is: symbiotic business model which will be used in this paper. The term symbiotic business model is used when two or more actors together strive to increase the total value creation and value capture over company boundaries. It is a hypothesis of the authors that an integrated co-operation between organizations within the manufacturing industry and the recycling industry can increase profitability and reduce the total environmental impact. The paper is organized as follows: Section 2 presents state of the art on manufacturing and recycling industries and their possibility to

work integrated in terms of business models and industrial ecology. Section 3 states the problem addressed in the paper. Section 4 describes the work done to achieve the results which are presented in section 5. Section 6 discusses the results in terms of closed and open loops of the business models. Section 7 concludes this work. 2

PROBLEM STATEMENT

The purpose of this paper is to investigate if organizations within the manufacturing industry and the recycling industry could co-operate and align their business models to increase the profitability and reduce the total environmental impact. The hypothesis stated for the research project from which this paper stems is: An integrated co-operation between manufacturing, refurbishing and recycling industries employing symbiotic business models will increase the profitability for the partaking parties and reduces the total environmental impact. The hypothesis was approached using the methodology described below. 3

BACKGROUND

The business model, how an organization creates and captures value, is often said to represent a new dimension of innovation and source of competitive advantage that spans the traditional models of process, product and organizational innovation. When a for-profit organization analyzes and changes its business model it assumedly does so with the intention to increase its own revenues, or reduce its costs or risk. Even though the business model literature has provided a more holistic and systemic perspective than traditional theory in strategic management the focal point is one organization, its resources, activities and position in the value chain, and not the system of stakeholders or the business models of other organizations involved in the full life cycle of the products or services provided.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_35, © Springer-Verlag Berlin Heidelberg 2011

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The manufacturing industry and the recycling industry are generally thought of as separate entities with limited interaction and collaboration. Could this be an ancient way of looking at the industries? How well connected are the industries today? In order to examine this we have to explore how evolved they are today when it comes to recycling and reuse. 3.1

The manufacturing industry

The access of raw material and components to reasonable prices is going to be a challenge for manufacturing companies in the future. The supplies of natural resources are decreasing and the costs to extract those increases. Incremental prices of the raw material and components are to expect, which could trigger some companies to rethink their needs and therefore secure the access of material from different industrial areas. In order to secure the accessibility, the prices can be kept low and the price of the products can continue to be acceptable. The companies that do not secure the access of raw material or components will most probably have to increase the price of their products. Hence, the company will not be as competitive as others. One area which is well developed when it comes to reuse of components and recycling of material is in the end-of-life vehicles industry. Because of resent legislations, it is more important now than ever for the car industry to recycle more of the materials from cars (ELV-directive) [3]. End-of-life vehicles are transported to dismantling companies (i.e. scrapyards), where reusable parts are removed from the cars. The rest of the cars is sent to a recycling company to be recycled as material. This network consists of car production companies, dismantling companies, recycling companies and BIL Sweden. This network is a result of the ELVdirective, and it is called Refero [4]. This organization was developed to assure the 85% recycling regulation put by the ELVdirective. The idea is to make it more convenient for car users to get rid of their ELV. It will be even more important for the car companies to make this organization work hence the ELV-directive states that in the year 2015 the recycling regulation will be 95% [3][4]. 3.2

The recycling industry

Waste management is an important part of our modern society. The waste manage industry have evolved from collecting garbage from households to be put on a land fill, to be an important provider of “raw” material to the production industry. Today’s recycling companies usually collect waste from both households and industry. In 2009 about 98.5% of the waste from households was recycled, and 48.4% was recycled as energy through incineration in Sweden [5]. Unfortunately waste management companies are still looked upon by many as companies only handling waste that is put on a landfill instead of important companies with recycling capabilities. But as Pongrácz [6] argues that the description of waste management companies should be revised to “waste management control of waste-related activities, with the purpose of resources conservation and environmental protection”. Waste management companies are not only collecting waste but are also a source of raw material to the production industries. The main focus of the waste management industry is to recycle large and uniform flow of material to the industry as “raw” material. This is highly dependent on the price and market demand for the specific fraction of material. The highest demand of material has been, looking at a short time frame, the energy industry. It is more economically favorable to sell many of the waste fractions to the energy industry to become energy through incineration, than to sell it as “raw” material. To sort and separate some of the different materials from each other in a batch of waste, in order to create homogenous material fractions, and then sell it as raw material to a

production industry is very labor intense. It is usually more easily justified to sell it directly to an energy company for energy through incineration. From the manufacturing industries point of view, it is more “safe” to buy “new” raw material to produce their products with. One reason for the production industries to buy “new” raw material is the continuous access to material, which the recycling companies can’t secure. Another reason is the quality of the material that is provided by the recycling companies. If the quality isn’t high enough then the production companies can’t keep the same standard on their products as with using “new” raw material. This way of treating recyclable material is not a good foundation for a sustainable society. Unfortunately, waste that could be disassembled and where components could be reused, are not reused to a high extent. One of these waste categories is electrical and electronic equipment (WEEE). In general WEEE is recycled as material, e.g. shredded, crushed or treated in a similar way, and not recycled through reuse of components after disassembling [7][8][9]. This is very unfortunate, since a lot of components from WEEE could be reused in new products. This could decrease the environmental impact compared to producing new components from “new” raw material. There is an organization called Stålkretsloppet [10] that are working on closing the steel eco-cycle. The organization manages a program that is divided into different projects. The different projects is Improved steel scrap quality, Surface cleaning of steel scrap, New Metallurgical technologies, Product design and new steel products, Recycling of steel in the society, and Evaluation of environmental values. The program is financed by MISTRA and gives the opportunity to develop the steel industry [10] to further recycling and reuse of products in a constructive way. Symbiotic business models are one solution which might fit into Stålkretsloppet. 3.3

Integration

By integrating the different actors during a products lifecycle a more sustainable and holistic viewpoint is possible. When this integration is not present sub-optimization will occur and hence more easily resulting in additional environmental pollutions, higher cost, longer lead-times etc. Industrial ecology is a relatively new concept in the industry and the business world over all. Industrial ecology is defined as: “Industrial ecology is an emerging science which provides the conceptual tools to analyze and optimize the flow of energy and material in our production system” by the Interagency Working Group on Industrial Ecology, Material and Energy Flows of the U.S. federal government [11]. Symbiotic business models can be seen as a part of Industrial Ecology in the way that Cohen-Rosenthal describes it: “The power of industrial ecology as a conceptual framework is not the description of mass flow and their consequences but in applying human intention to explore potential connections so that we create interactions with more value and less waste” [11]. By making new connections between companies the evolution of business models can be made. Hence a more integrated involvement between companies can create a symbiosis which can lead to a decrease in environmental impact, secure flow of material, and increase the profit for everyone involved. One example which works great since a long time back is recycling of glass bottles in Sweden. They are recycled by rinsing/washing and then sent back to the brewery to be refilled. But those examples which are implemented in such a large scale are rare. Recycling and remanufacturing views waste as a resource. It is the hypothesis of the authors that taking an even more holistic

Sustainability in Manufacturing approach, to not only looking at the business model of one organization but many; new symbiotic opportunities could be identified. What one organization considers to be waste another organization might use as input for their processes. In addition reasoning about how to a route for recyclable products might most easily be created, maintained and used by actors throughout the product lifecycle results in a conclusion that the lesser number of actors involved the more possibility for success to recycle the product. If comparing this reasoning with Figure 1 one can say that the shorter route from the original product creation, the more easy will it be to maintain control for the products quality, location and hence its lifecycle. 4

METHOD

The presented paper and its results are based on state-of-the-art reviews, interviews with both manufacturing-, refurbishing- and recycling industries, as well as a workshop where key persons from manufacturing-, refurbishing- and recycling industries were invited to participate. State-of-the-art in each of the areas manufacturing, remanufacturing, refurbishing, sustainability over a product lifecycle and business models is each a very large area by their own.

203 However, when looking at the combination of these into one single multidisciplinary research area sets the scene for state-of-the-art to significantly less, see section 2 for some examples. The interviews were performed with company representatives from manufacturing-, refurbishing- and recycling industries which had good knowledge on the business models and products the companies manufactured, refurbished, and recycled respectively. The interviews with the company representatives were conducted as approximately one hour semi-structured interviews by using open but structured questions, according to Kvale [14]. The major categories of questions used were planned ahead of the interviews, one set for manufacturing companies and one set for refurbishing/recycling companies. A total of seven company interviews were conducted and during the majority of these interviews there were more than one person from the company present, which vouches for good insight on the business models and product lifecycles. The workshop was conducted after the interviews and the findings from them were discussed and summarized into one more generic consensus documentations on which all 22 workshop participants actively contributed. Contributions were for example business models which are working now, problem statements, possible solutions, law regulations as hindrance etc. Parts of these results are showed in section 5.

Figure 1: Schematics over possible product lifecycle routing options [12] adopted from [13].

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In order to investigate if, and potentially how, organizations within the manufacturing industry and the recycling industry could cooperate and align their business models we needed a business model framework. Using a business model framework we believe a more structured analysis of what elements of a business model that is relevant to further analyze and what elements to discard for future research, in contrast to a business case narrative. We decided to use Alexander Osterwalder’s business model framework based on nine different elements, to structure the analysis, discussion and recommendations [1]. The nine elements being: Customer Segments, Value Propositions, Channels, Customer Relationships, Resources, Activities, Partners, Revenue Streams and Cost Structure. In addition we use the business model framework as a structure for our observations and results in this article. However, this effort on symbiotic business models is fairly small research wise (half a man year in total effort), which is why this paper is more to be viewed upon as a pre-study where future research projects will stem from. It is also limited on the number of industries partaking in the interviews (seven) and in the workshop (ten), which makes the results more indication like than strong research based and validated. In any way the results shown below will shine light upon upcoming challenges present in industry and also some of the large potentials for future symbiotic business models, both in terms of economy and environmental effect. 5

RESULTS

Through the different interviews and workshops a number of observations were made regarding the business models of manufacturing and recycling industries. Below is a summary of the observations and discussions in relation to each of the nine elements of the chosen business model framework. 5.1

Customer segments

The customer segment element represents the different groups of organizations or individuals that the analyzed organization aims to reach and serve. It is the buyers of the products being manufactured, or the buyers of material or components being recycled. Both actors from the manufacturing industry and the recycling industry see challenges in the existing and potential customers segments. Actors in the manufacturing industry were most concerned with their customers’ perception that remanufactured and re-used components could mean a lower quality product. At the same time some of the respondents saw that remanufactured components could have an even higher level of quality due to manual inspection and adjustments. Recycling industries express the difficulty in knowing the customer demand and the stability in demand and prices. New potential customer segments are component buyers, renovators, spare part actors but also the manufacturing industry directly in some cases. 5.2

Value propositions

The value proposition element represents the bundle of products and services, offered by the analyzed organization, that create value for a specific customer segment. With an increased level of re-manufacturing and re-use components several actors in both the manufacturing industry and in the recycling industry saw potentially new value propositions to be offered to their existing and new customer segments. Recycling industries saw an opportunity to provide value adding services identifying, separating, renovating and quality assuring components and even supporting the design of new products. In some areas stable and secured material flow together with lower cost components was thought of as clear value propositions towards component buyers, renovators and spare part actors. Interviewed companies producing products saw potential

value propositions in providing “green” sustainable products at both premium but also potentially lower prices. Another discussion that got the attention of the manufacturing companies was the concept of providing products and services, maintaining ownership and control over products and components. One of the respondents expressed frustration that the market is not appreciating re-use, that green products are associated with low energy consumption and environmentally friendly materials, and re-manufactured products are perceived less valuable, “second-hand”. 5.3

Channels

Channels represent how the analyzed organization communicates with and reaches its customer segments to deliver a value proposition. For actors in the manufacturing industry the main issues that were discussed were the reverse logistics and the logistical challenges linked to getting products back from customers. Potential new types of intermediaries were discussed in the workshop in which some participants were concerned with the high costs, and the potentially increased costs with even more actors to split the pie with. For recycling industries new customer channels would potentially need to be set up, in order to reach and serve new customers providing value adding services. Existing and potential co-location of recycling industries within the facilities of the manufacturing companies were discussed. A concern raised by the recycling industries was the increased interest from manufacturing companies to bring more of the recycling services in-house to secure the access to raw materials and components. 5.4

Customer relationship

This element represents the types of relationships the analyzed organization establishes with its customer segments. With an increased level of re-manufacturing and re-use of components manufacturing companies increasingly turn into customers for the recycling industries. In some cases, such as in co-location situations or when one company is responsible to collect used products for the manufacturing company, closer relationship are being developed. One opportunity and risk that recycling industries foresee is the increased responsibility of being a component supplier. For the actors in the manufacturing industry they had limited expectations that their customer relationships would change. One exception that was discussed in interviews and the workshop was the concept of providing products as services and by that move from one-time transactions to long-term relationships. 5.5

Resources

This element represents the most important physical, intellectual, human and financial assets of the analyzed organization. Besides the investments needed by recycling industries in dismantling facilities and warehouses, the main resource that was discussed were human resources and the competencies needed. One respondent said that they shipped components for re-manufacturing from around the world to one country where they had the competence for disassembling and renovation the products. With the competence available in more locations, the level of shipping components around was expected to decrease. An interesting discussion regarding resources that manufacturing companies shared was their concern for the existing and future shortage of rare metals and the view that today’s products might need to be the raw material of tomorrow’s products. 5.6

Activities

This element represents the main things the analyzed company must do to make its business model work. For manufacturing companies examples of new activities that were mentioned in relation to re-manufacturing were design for remanufacturing, retake of products, warehouse logistics but also co-development

Sustainability in Manufacturing with partners. For recycling industries activities such as dismantling, separation, renovation and design support where mentioned. 5.7

Partners

This element represents the network of suppliers and partners that make the business model work. During the interviews and workshop different ideas were discussed on whom could partner with whom in the specific case of each respondent. Also, actors from both the manufacturing industry and the recycling industry saw room for new actors, new intermediaries and new types of relationships between them. Different forms of partnerships were discussed and the participants of the workshop were inspired by the development within industrial ecology and the partnerships that are being developed. 5.8

Revenue streams

The revenue model element represents the cash a company generates from each customer segment. For actors in the manufacturing industry the revenue models are not expected to change, even though the products might be less expensive to produce, or enables premium pricing. The exception being if moving towards products as services, as one-time transactions would be replaced by per-use payments, subscription models or other revenue models. Recycling industries mentioned new sources of revenues, and for example components instead of materials as products, but not new revenue models except for services that could be paid for in new ways. During the workshop there was an interesting discussion about who should own the material and component in the process of re-manufacturing or even re-cycling of materials. With an increased shortage of some raw materials one idea was that manufacturers would continue to own the material or component, and only lend it to recycling industries or remanufacturers. 5.9

Cost structure

This element represents all costs incurred to operate the business model of the analyzed organization. The obvious cost with increased level of re-manufacturing is the increased costs and the need for investments in equipment, warehouse space and personnel by the recycling industries. Actors from the manufacturing industry did not express any concern for an increased cost structure. A discussion that really got attention with the respondents was the idea that today most components are designed to sustain the life of the product, and by that the life of the least sustainable component. Knowing that components that could be made more sustainable would be re-used and that the value in some form returned to the manufacturer, more environmentally and economically sound components could be produced to sustain more than one product life. 6

DISCUSSION

Studying the results we can answer the questions that were asked in the introduction of this article: Is it an ancient way of looking at the manufacturing and the recycling industry as separate entities? To some extent this is true. But the industries are now changing and becoming more integrated, toward symbiotic business models. To be able to secure the resources to produce new products, symbiotic business models could be the best alternative so far. The connections between companies are pretty week and manufacturing companies’ changes subcontractors easy. Maybe this is the best way to trigger evolvement in different sectors, but is this a sustainable way of doing business when the natural resources are running out? Perhaps it is, perhaps it’s not. Even if manufacturing companies change subcontractors easy, the symbiotic business model should be in focus and implemented.

205 What come out of a number of discussions were open and closed loops of the products. Should the manufacturing companies own the products through the whole lifecycle or should the costumer own the product. Many companies think, when looking in to the future, that they see them self leasing out a product or only selling a service. This would secure the access of material and components. In this case they could even use more expensive material for some components to increase the lifetime of it, and they could also be able to reuse the component in a new product. This would change the current business model for both manufacturing and recycling companies. The recycling industries would get a different role in the products lifecycle. They would provide a service to be the experts in dismantling the product, sorting the different materials and secure the quality of the material and components. To be able to get a closer interaction between the recycling industry and the manufacturing industry, will put demands on both of the industries. Because of the lack of close collaboration between the industries, the long-term agreements that secure the market is of big concern. These agreements are very important otherwise the recycling industry doesn’t have the motivation to invest and implement new techniques for dismantling products. Since these investments are expensive it is also important to receive large volumes and that the price of the component doesn’t fluctuate much. To create a more sustainable recycling of components and material, the recycling companies should be more involved at an earlier stage of designing a product. The recycling companies are experts on recycling and it would be a natural stage in product development to take advantage of their knowledge. This would increase the recyclability of the products and strengthen the relationship between the companies. The manufacturing industry in general could be triggered to compete against each other by introducing a specific branding which proves that the specific product contains a high amount of reused components or material. A branding like this could provoke an increased use of components in products and hence create a more sustainable future for the companies. The government could affect the market for reuse of components through e.g. legislation, changes in tax or producer responsibility. Changes like this could generate a more wide use of refurbished component. The companies that have been involved in this project were intrigued by symbiotic business models. The project group is investigating the possibilities to concretize one or more pilot cases where symbiotic business models could be implemented. Discussions with interested companies are now underway to determine what value chain to investigate, which parties to invite to cover the full lifecycle of one product for a new research effort on symbiotic business models. 7

CONCLUSIONS

To conclude the findings from interviews, literature studies and the workshop we found the following to be most interesting: Some overall conclusions from the interviews: 

Limited collaboration between manufacturer and recycling company is done today. The reason is explained as: The distance between the two parties is too far from each other in terms of the products lifecycle.



The responsibility to produce green products is on the subcontractor, which means that the assembler of sub components to a product for end user feels “stuck” in-between the subcomponent manufacturer and the recycling industries.

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

There is no obvious incitement for the manufacturer to work closer to the recycling industries today.

[4]

REFERO. www.stenametall.com/refero, accessed 2010-1108.



The costumer’s interest in paying extra for a recyclable product is limited.

[5]

Svensk avfallshantering (2010). Report (In Swedish) by Avfall Sverige.



The producer does not get any extra benefits when producing products that are recyclable.

[6]



Environmental branding does not take recyclability in to account, most of the branding is done on a cradle to gate calculation, which means that recycling is not included.

Pongrácz, E. (2006) ”Industrial ecology and waste management: from theories to applications”. Progress in Industrial Ecology – An International Journal, vol. 3, Nos. 1/2.



Quality and access of components to reuse in new products is uncertain in most cases, which means that the manufacturer is not interested in taking risks on possible future remanufacturing businesses.

During the workshop discussions on how to integrate business models were lively discussed, a consensus on that it is needed and that it is possible was reached. However, several hindrances to reach the target were also identified, such as: 

Laws and legislations hindering companies to take back sold products when they reach end of usable life e.g. when they were sold between two different countries.



Personal interests from employees who are not in line with what the companies actually are striving for, i.e. change is easy to plan but harder to perform in reality.



Traditions and current business models are set and the work procedures are defacto-standards for trading and communicating. Those traditions are not easy to change.

If it would be possible to create a positive trend among manufacturing companies to be able to reuse components, maybe in order to show off the quality of the refurbished products, it could change the consumption of raw material and reduce the pollution to the environment. However, to reach such a trend, a new view on recycled products is needed. The status of a recycled product needs to be increased to the eye of the beholder, or else a recycled component will always be second after a new one. When summarizing the findings on reviewing literature, conducting interviews with manufacturing, refurbishing, and recycling industries as well as findings from the joint workshop, we can see that there is a need for development of more symbiotic business models in order to utilize resources more efficiently, both for a more sustainable environment as well as for a more sustainable economy. 8

ACKNOWLEDGMENTS

The funding for this research is granted by VINNOVA (Swedish Agency for Innovation Systems, integrates research and development in technology, transport and working life.). This work has been carried out within the Sustainable Production Initiative and the Production Area of Advance at Chalmers. The support is gratefully acknowledged. 9

REFERENCES

[1]

Osterwalder, A., Pigneur, Y. (2010): Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers. Modderman Drukwerk, Amsterdam.

[2]

Zott, C., Amit, R., Massa, L. (2010): The Business Model: Theoretical Roots, Recent Developments, and Future Research. IESE Business School, Madrid, Spain.

[3]

DIRECTIVE 2000/53/EC of the European Parliament and of the Council, on waste electrical and electronic equipment (WEEE), 18 September 2000.

[7]

Ragnsells AB. www.ragnsells.se, accessed 2010-11-08.

[8]

SITA. www.sita.se, accessed 2010-11-08.

[9]

Stena Metall AB. www.stenametall.com, accessed 2010-1108.

[10]

Stålkretsloppet. www.stalkretsloppet.se, accessed 2010-1108.

[11]

Cohen-Rosenthal, E. (2000) American Behavioral Scientist. Vol. 44 No. 2 (245-264)

[12]

Amaya, J., Zwolinski, P., Brissaud, D. (2010): Environmental Benefits of Parts Remanufacturing: The Truck Injector Case. In: IMS Summer School on Sustainable Manufacturing, ETH Zurich, May 26-28.

[13]

Gehin A., Zwolinski P., Brissaud D. (2008): A tool to implement sustainable end-of-life strategies in the product development phase, In: Journal of Cleaner Production, Vol 16, No. 5, pp. 566-576.

[14]

Kvale, S. (1997): Den kvalitativa forskningsintervjun, Studentlitteratur AB, Stockholm, Sweden.

Life Cycle Engineering – Integration of New Products on Existing Production Systems in Automotive Industry 1

Waldemar Walla , Jens Kiefer 1

1

Daimler AG, Group Research & Advanced Engineering, Integrated Product Validation, Ulm, Germany

Abstract Today, the life time of production systems is often longer than the product life cycle of the products manufactured on these production systems. Hence, during the whole life cycle of the production equipment a, redesign and rebuilding of the production line is necessary again and again in order to integrate new products. This contribution will take a look on the whole life cycle of a manufacturing system, showing that major benefits of reusing the production equipment can only be achieved if new products can smoothly be integrated on existing production systems. Keywords: Life Cycle of Production Systems; Reuse of Production Equipment; Virtual Commissioning

1

INTRODUCTION

During the last decades, the model cycle in the automotive industry decreased from 10 to 6 years or even less [1]. At the same time the demand for individualized and configurable cars has increased. This has led to a huge number of product variants together with a high complexity of products.

2

The following chapter presents the life cycle of a typical production system for the body-in-white production. Figure 1 shows the single steps of the life cycle which contains the phases planning, operation (intermitted by product integrations) and deconstruction.

The huge number of product variants, the product complexity and the time pressure lead to big challenges in production. One of the commonly accepted solutions for the increasing product complexity is the improvement of production flexibility. Flexibility of production lines can be seen as the ability to manufacture different products on one production line. E.g. a sedan car, a station wagon or a SUV can be produced on one and the same line.

Planning Phase

Designing the production system Ramp up Maintenance

Operation Phase

In order to deal with the high product variety flexible technologies in production has been developed. Manufacturing systems offer a certain degree of flexibility in order to achieve optimal performance over their complete life cycle [2]. The life time of these production systems is often longer than the product life cycle of the products manufactured on these production systems. Hence, during the whole life cycle of the production equipment a redesign and rebuilding of the production line is necessary again and again in order to integrate new products. Major benefits of reusing the production equipment can only be achieved if new products can smoothly be integrated on existing production systems. For this, a methodology has been developed which collects the relevant requirements of the production system and influences the new product design in order to fit into the production system. But this does not ensure a smooth integration process. In order not to disturb the current production the production system and especially its ramp-up has to be assessed virtually. Therefore, a concept of virtual product integration will be described in this paper. According to the virtual commissioning, the interaction between mechanics, electronics and automation technology (e.g. Programmable Logic Controller, Robotics) of production systems has to be evaluated in an early stage of the product development process.

LIFE CYCLE OF A PRODUCTION SYSTEM

Integration of a new product Maintenance Integration of a new product Maintenance

Deconstruction Phase

Deconstruction  Reuse of components

Figure 1: Life cycle of a production system. The different phases of the production life cycle will be discussed in the following chapter. 2.1

Designing the production system

Future oriented planning is essential in order to design a production system on which further products can be integrated. For the production process of the further products additional equipment and tools could be necessary. Examples for those can be: 

Product dependent fixing and clamping devices



Robot tools (e.g. weld guns, fold tool, …)



Product dependent grippers

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_36, © Springer-Verlag Berlin Heidelberg 2011

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For this, additional equipment and free space in the factory layout is necessary. This space has to be taken into account already during the designing phase of the production system. Further, free space is needed for the additional raw material feed (e.g. part carrier and insertion gates). During the design phase of the production system the clear-sighted technologies have to be defined. The planners have to decide which materials (e.g. steel or aluminum) can be handled by the system (welding robots). Planning the production system the production planner has to decide which technologies (e.g. resistance or laser welding) will be used. This has an impact on future products which will be later integrated on this line. In order to be able to handle different product geometries the use of flexible grippers and fixing devices is recommended. 2.2

Operation Phase

After a successful manufacturing ramp-up the production system can be modified for various reasons. During the running production the engineers can assert that a modification of the production system is advantageous. If the advantages overweight the modifications costs, the production system can be changed and optimized. Furthermore, the production system can also be modified during maintenance and repair works. It is imperative for future reconstruction and adjustment works to document all changes during the whole life cycle of the production system. 2.3

Integration Phase

Due to the high complexity and the huge amount of the product variants car manufacturers introduce new products onto the market successively. In order not to disturb the running production the integration process has to be performed smoothly and quickly. 2.4

Deconstruction

Some day new product integrations are not profitable anymore. The effort for retooling and upgrading the production system is too big. Thus, a deconstruction of the production system is inevitable. Nevertheless, in certain circumstances every single production tool can be reused for future production systems. In this case all modifications of each tool have to be documented as well. 2.5

Traditional methods such as photogrammetry or conventional measurement reach their technical and economical limitations with complex object geometry which can occur in industrial systems. The use of high-performance 3D-laser scanners makes it possible to captures very large amounts of data in a short time, but the setup costs are quite high. 3D-laser scanning: Especially in the area of the “as-is” documentation, 3D-laser scanners are applied because of their high absorption rate and good geometry recognition. The laser beam scans the object vertically and horizontally with a constant step size. Characteristics of laser scanning: 

Contactless recording during production is possible



The recording with the laser technology is not dependent on natural light (it works even in complete darkness)



During a scan up to 625 000 measurement points per second can be determined. Depending on the resolution a complete scan consists of 25 to 100 million data points



The accuracy of a scanned point is ± 3mm

3D-tacheometry: A tacheometer is an angle and distance measuring device. Laser tacheometers are used to measure horizontal and vertical angle and distances. Unlike laser scanning, the 3D-tacheometry is a single point measurement system. In industry 3D-tacheometry is used for precise measurement and control surveys. This includes the single point measurement of production halls, facades and very large objects. Characteristics of 3D-tacheometry: 

Pointwise measurement of length and angles



Delivery of 3D coordinates with the highest accuracy



Precise detection of edges and corners of inaccessible objects



Combinations of tacheometer with other instruments, e.g. GPS, Bluetooth, additional lasers, cameras, etc.

4

INTEGRATED PRODUCT DEVELOPMENT & PRODUCTION PLANNING

Conclusion

The importance of product integration on existing production lines plays a major role during the life cycle of a production system. For a smooth integration process a close collaboration between the product designers and production planners is essential. Furthermore, the digital validation of the integration process is necessary. This implies also a virtual integration. 3

conventional measurement with folding rule and capiler, photogrammetry, laser scanning and tacheometry. Depending on the task these methods have their advantages and disadvantages.

GEOMETRY CAPTURING OF THE PRODUCTION SYSTEM

The initial step in an integration procedure is the acquisition of the actual “as-is” state of the system. Thereby, the existing production system has to be analyzed regarding mechanical, electrical and software aspects. An overall methodology how that can be realized efficiently has not been developed yet [3]. However, the geometrical information is the starting point for the design and production planning process of the new product. This chapter summarizes the widely-used technologies for geometry capturing. For the three-dimensional measurements of objects, installations and factories, various measuring methods exists, such as

For smooth product integration the structure of the new product has to be similar to the old one. Hence, production requirements have to be taken into account in a very early phase of the product development process [4]. In this manner the effort for the reconstruction of the production line can be reduced. Nevertheless, in many cases the production system will have to be modified. In order to do this an efficient re-planning of the system is necessary. Figure 2 shows an overview of a product integration process on an existing production system. 4.1

Product development

In order to integrate a new product in an existing production system a methodology has been developed which collects the relevant requirements of the production system and influences the new product design in order to fit into the production system.

Sustainability in Manufacturing

209

Production Product A

Ramp up

Virtual commissioning

Production planning Product A

Production Products A & B

t Reconfiguration etc.

Layout

Cycle time

Production planning Product B (and A)

SOP Product A

Start Product development Product A

Accessibility

Product structure Material

Information

Product development Product B

etc.

Accessibility

Product structure Material

Product development Product A

Reconfiguration

Virtual product integration

Start Product development/ Production planning Product B

Start SOP Reconfiguration Product B

Figure 2 : Information exchange during the life cycle of a production system. As shown in Figure 2, the origin of these requirements can be found at any time in the life cycle of the production system. The possibilities and constraints of a production system are already defined in the system designing phase. The following information has to be considered in the product development process: 

Technologies: If the product developer knows about the existing production system, he will design the new product accordingly to the available technologies.



Assembly sequence: The assembly sequence has a strong impact on the product structure. Hence, the number of components and the product structure of the new product have to be similar to the old one.



Geometry of the fixing, clamping and gripping devices: The geometry of the production resources which contact the product directly has to take into account. In order to fit the new product to the existing devices the product design has to be adapted to the geometry. Furthermore, the flexibility of the devices has to be known by the product developer.



Cycle time: The cycle time has to be identical for each production cell and can not be changed by implication. This constriction has to be shown to the product developer.

This Information can be provided to the product designer using an approach which is shown in Figure 3. 1. Collecting information about the current production • Documentation of the production system • Adjustment of the digital model of the production line • Data management 4. Identification of reconstruction activities for the production system • Redesign of the production system (if necessary) • Digital validation of the production system

2. Filtering, editing and analysing of the data • Which information is necessary? • Which consequences have to be deduced?

3. Supporting the product development process • Visualization of the consequences • Influence on the product design

Figure 3: Consideration of production requirements in the product design phase.

The concept can be divided into four steps that are directed in a circle. In order to integrate new products on existing production lines information about the production system has to be collected firstly. All resource geometries, process times or parameters must be known. In the second step, this information must be analysed. The results of the analysis have to be shown to the product development engineer. Knowing the manufacturing potential of the production system the product developer is able to influence the product design in order to realize an integration of the new product on an existing production line. In this manner the production system doesn’t have to be reconstructed. In some cases a reconstruction of the production line will be indispensable. This may be the case if the new product can not meet safety, lawful or styling requirements without special production systems. In this case the production planner has to trigger the re-planning process. The four steps approach supports the product developer with information like tool accessibility, sequence time, joining technology and factory layout. If another product needs to be integrated on this production line, the integration process will to be repeated starting with the first step. 4.2

Production planning

For the product integration on an existing line a modification of the production system can be necessary. This has to be planned accurately in order not to disturb the running production system at the integration process. A re-planning of the production system contains the following issues: 

Change the factory layout



Install additional resources



Replace production equipment



Adapt the logistic concept of the parts

By validating the new designed production system virtually problems during the integration process can be avoided. For this the common known tool of the Digital Factory can be utilized: 

Tool accessibility checks



Offline robot programming



Collision detection

Before rebuilding the production system and stopping the current production the re-planned system has to be commissioned virtually

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in order to avoid ramp up problems. In the final step, the production system will be reconstructed. 5



two separate data models (as depicted in Figure 4), which communicate over corresponding system interfaces during the execution phase (Tools: e.g. WinMOD & Invision).

VIRTUAL PRODUCT INTEGRATION

In this chapter, the simulation method of virtual commissioning as central technology to realize efficient integration processes is introduced. Apart from a general description of the topic virtual commissioning, the needed virtual data models, their development processes and the individual steps for accomplishing virtual product integrations used the method of virtual commissioning is presented. 5.1

Virtual commissioning – Goals and concept

As published in [5], virtual commissioning describes a methodology for validating and optimizing real control programs (e.g. PLC, RC, HMI) and the whole system behavior (e.g. the cross-function interaction inside a production system) without having the real production facilities. Due to the necessary hybrid data inputs in the form of digital product and resource as well as real control data, the simulation method of virtual commissioning is also frequently referred to a transfer from the digital to the real factory. Compared to the technology life cycle model published in [6], the method of virtual commissioning is a so-called key methodology that will be an important competitive advantage in the future. However, this new methodology is still an expert application that is currently only used for special production facilities in a selective way. Although much progress has been made in this topic in recent years, there are still some open issues that have to be solved in order to develop all benefits that can be gained by using this new simulation methodology. Relating to the entire production life cycle, the main benefits of virtual commissioning are for example: 

More efficient PLC programming and debugging



Accelerated and more robust production ramp-ups



Higher degree of soft- and hardware maturity at start of production (SOP)



Operator trainings before SOP



Higher availability of the manufacturing systems during running production



More efficient integration processes during running production

As already mentioned, the key goal of virtual commissioning is the early validation and optimization of real control programs and the whole system behavior. To do this without having the real production facilities, a digital data model is needed that represents the mechanical, electrical and functional portions of the real equipment in a sufficiently exact way. Due to its contained information, this data model is to be called mechatronic cell model. 5.2

Mechatronic cell model – Components and development process

As shown in Figure 4, the mechatronic cell model is fundamentally composed of two corresponding parts: the extended 3D geometry model on the one hand and the control-oriented behavior model on the other hand. Depending on the company-specific strategy (goals of virtual commissioning, used IT architecture etc.), the mechatronic cell model can either consist of: 

one integrated data model as integration of the extended 3D geometry model and the control-oriented behavior model in one common data model (Tools: e.g. DELMIA Automation, Process Simulate Commissioning) or

Figure 4: Components and interfaces of the mechatronic cell model. As presented in [7], each of these two strategies has their individual strengths and weaknesses. Last but not least, the strategic decision depends both on company- and tool-specific boundary conditions and can therefore only be made individually by each company. Today, the crucial factor in accomplishing virtual commissioning projects as profitable as possible is not the technical execution itself but the development process of the needed mechatronic cell model: This preparation phase is currently characterized by a mostly manual, error-prone and time-consuming process. At Daimler Research & Development, an engineering workflow for generating the mechatronic cell model as efficient as possible was developed, which main characteristics are illustrated in the following sections. Basis of this development process of the extended 3D geometry model is the existence of standardized resource components. According to a typical frontloading procedure, the 3D CAD models normally used in mechanical design (e.g. fixtures, grippers) have to be enhanced with additional mechatronic information. Base of this mechatronic-oriented design process is the existence of standardized mechatronic components (e.g. clamps, robots, sensors). In order to allow a company-wide access to these newly configured objects, all these mechatronic units are made available to the related departments in the form of a centrally organized mechatronic component library. In contrast to today's mechanical CAD models, the mechatronic components does not just solely consists of the pure 3D CAD model but also of kinematics (including end positions) and electrical information as for example the electrical name of the respective device. After taking the projectneutral mechatronic components from the library, the responsible department (e.g. the Tooling Design) only has to tailor them to their special installation situations in the respective production system (e.g. adaptation of the electrical name). The development of the control-oriented behavior model based on standardized behavior components, which describe the behavior of the production facility compared to the control equipment. Company-specific standards in the field of electrical/automation engineering have to be considered in developing the behavior models. According to their main tasks, these data models consist of organizational data as for instance names, behavioral description data as well as specific interface data. On the basis of so-called function group lists (output from the electrical design) that describes what kind and how many function groups are used in the respective robot cell, the preconfigured function group specific behavior

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models are combined to the control-oriented behavior model in an automatic way. More information regarding this development process is given in [5]. In a last process step, the extended 3D geometry model and the control-oriented behavior model are coupled to the overall mechatronic cell model. Basis of this connection are predefined interfaces of the two data models in the form of in- and outputs. Due to the same name conventions in both data models, this process step can be realized in an automatic way. 5.3

Capturing and feedback of real data as base for virtual product integrations

As published in [8], product integrations during the running production can be significantly accelerated using the method of virtual commissioning. In order to use virtual commissioning for integration processes in a most profitable way, in a first step, the current data of the real production system have to be captured and feedbacked to the respective data models in the digital world. In this context, as pictured in Figure 5, at least four different data types have to be distinguished: geometry, PLC, robot and HMI data. While the capturing of the needed control data (PLC, robot and HMI) is quite easy (copy of the real software), the situation to adapt the extended 3D geometry model according to the current situation of the real production system is much more difficult. To capture real geometry data (geometry and positions of used components), there are different approaches as for example 3D laser scanning. As already mentioned in chapter 3, each of these data capturing methods has individual strengths and weaknesses (e.g. costs, accuracies) and their efficient use depends on different conditions as for example the complexity and the accessibility to the real production system. In a second step, the captured geometry data have to be feedbacked into the existing 3D geometry model. According to the requirements, this process step can be either done in a manual or (semi-)automatic way. After adapting the mechatronic cell model according to the real production system, the mechatronic cell model can be coupled with

the respective control equipment and the virtual product integration can be simulated in a realistic way. So, real product integrations can be accomplished in shorter time periods, the degree of software maturity (PLC, HMI and robot programs) can be significantly improved and the re-ramp-up can be realized in a more robust and faster way. 6

SUMMARY AND OUTLOOK

Due to a soaring number of product variants with many product derivates manufacturing of several products on one production line is necessary. Therefore longer production life cycles with highly flexible and agile manufacturing systems are necessary. The single product variants come into the market at different times; hence an integration process of new products is necessary several times during the whole life cycle of the production system. In order to guarantee a smooth and quick integration process new methods are necessary which consider the production requirements from the whole life cycle. This paper takes a look on the whole life cycle of a production system and shows the importance of an early product influence in order to integrate a new product variant on an existing production system. Furthermore an approach of virtual product integration has been presented which is based on the virtual rump commissioning. Although much progress has been made in these topic fields, the following issues still remain to be addressed in future research activities: 

Capturing and feedback of the current geometry and the real data has to be improved.



The product developer has to consider production requirements coming from the real production system. Hence, a structured and continuous support is required.



Production planning processes have to be modified. According to “brown field” the production planning process has to be modified.

Figure 5: Virtual commissioning as base for efficient integration processes.

212 7

Sustainability in Manufacturing ACKNOWLEDGEMENT

Parts of the presented activities and results are developed within the scope of the European Union research grant MyCar – Flexible Assembly Processes for the Car of the Third Millennium (NMP2-CT2006-026631). More information about this project is available at: http://www.mycar-project.eu. 8

REFERENCES

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Bär, T., Kiefer, J., Schmidgall, G., Burr, H. (2005): Objectives of a Seamless Digital Process Chain in the Automotive Industry, in: Proceedings of the 1st International Conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV2005).

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Schuh, G., Wemhöner, N., Friedrich, C. (2006): Scenariobased Lifecycle Analysis of Manufacturing Systems, in: CIRP Journal of Manufacturing Systems, Vol. 35, pp. 129-135.

[3]

Reinhart, G., Meling, F., Zuber, E. (2009): Line Equipment in Asynchronous Life Cycles – Future Challenge fort he Automotive Body-Shop, in: Proceedings of the 3rd International Conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV2009), pp. 642-650.

[4]

Mantwill, F. (2007): A New Approach to Applying Manufacturing Requirements within a Modern 3D-CAD System, in: Proceedings of the 2nd International Conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV2007).

[5]

Kiefer, J., Ollinger, L., Bergert, M. (2009): Virtuelle Inbetriebnahme – Standardisierte Verhaltensmodellierung mechatronischer Betriebsmittel im automobilen Karosserierohbau, in: atp – Automatisierungstechnische Praxis, 7/2009, pp. 40-46.

[6]

Gausemeier, J., Ebbesmeyer, P., Kallmeyer, F. (2001): Produktinnovation, Carl Hanser Verlag, Munich.

[7]

Bergert, M.; Kiefer, J.; Höme, S.; Fedrowitz, C. (2009): Einsatz der Virtuellen Inbetriebnahme im automobilen Karosserierohbau – Ein Erfahrungsbericht, in: Tagungsband der 9. Magdeburger Maschinenbau-Tage, pp. 388-397.

[8]

Kiefer, J. (2007): Mechatronikorientierte Planung automatisierter Fertigungszellen im Bereich Karosserierohbau, Schriftenreihe Produktionstechnik, Band 43, Universität des Saarlandes.

Managing Sustainability in Product Design and Manufacturing 1

Klimis Ioannou , Alireza Veshagh 1

1

Manufacturing Department, University of Warwick, Coventry, UK

Abstract This paper identifies and discusses key management issues associated with the integration of sustainability criteria in the design of new products and manufacturing processes. Alternative strategies are compared and the business case is examined based on the drivers and barriers of sustainable product design and manufacturing. The paper also discusses the results of a survey conducted to examine the position of the manufacturing industry in the UK who have already implemented sustainability principles in their operations, and provides an insight into the salient features of sustainability management in terms of implementing and managing sustainability in the long run. Keywords: Sustainable Manufacturing; Survey; Management

1

INTRODUCTION

The unfavourable impact of development has led to the need for creating a balance between economic growth, environmental preservation and social equity. These three dimensions are equally important and they should be managed as a whole on the basis of a triple bottom line. Economic growth and environmental conservation have been traditionally regarded as two incompatible factors, but linked together on a trade-off basis. Sustainable development was introduced as a concept to reconcile this conflicting relationship. Since early 1970s environmental, social and economic criteria have been institutionalised as the guiding principles and therefore growth and development are not measured solely by the real income per capita or the gross national product; welfare is not perceived purely in economic terms, but emphasis is placed on quality of life, healthy living conditions, equal opportunities and social wellbeing. Sustainability is being increasingly integrated into business processes, activities and operations, such as product design and manufacturing to meet with environmental and social challenges faced by manufacturing industry. 2 2.1

SUSTAINABLE PRODUCT DESIGN Definition

A number of approaches to environmentally conscious product design have been developed and several new terms and terminologies have emerged. The most common terms appearing in bibliography are in chronological order green design, eco design or design for the environment, and sustainable product design. Green design mainly addresses single environmental issues and is based on design for “X” concepts, where “X” may stand for energy efficiency, recycling, modularity, disassembly.

by taking a wider view of the impact of product design process on humanity, and integrates ethical and social considerations alongside environmental issues into the design process. Drawing on the basic definition of eco design, SPD can be defined as the systematic consideration of design performance with respect to environmental and social objectives over the full product life cycle (Figure 1). 2.2

Principles of SPD

The principles of SPD can be summarised in the following rules: 

Waste Equals Food: All products at the end of their life should become nourishment for something else.



Use Current Solar Income: SPD provides for efficient use of clean and renewable energy on a life-cycle basis, during manufacturing, transportation and use of products.



Respect Diversity: SPD accounts for the uniqueness of places, adjusts to local conditions, and considers diversity in human communities.

The five principles of SPD, namely products should be cyclic, efficient, solar, safe and social, can be mapped on a matrix table illustrating the relationship between the above approach, and the triple bottom line concept (Figure 2). 2.3

Strategies for SPD

There are an number of alternative approaches to SPD which can be divided into environmental, social and economic strategies. Environmental strategies include reduciton of materal usage, pollution prevention, energy efficiency and life cycle design. Product design strategies such as human factor engineering, health and safety, and fair trade aim to address the social aspect of design and manufacturing operations [1].

Eco design, which extends beyond green design, was introduced in the 1980s as a strategy to integrate environmental considerations in the product development process based on a life-cycle approach. Sustainable product design (SPD) widens the scope of eco design

Figure 1: Sustainable product design framework.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_37, © Springer-Verlag Berlin Heidelberg 2011

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Sustainability in Manufacturing between manufacturing sub-systems, thus reducing unexploited energy and materials leaving production units. Cleaner Production aims to clean up industrial and manufacturing processes that take place in production units through the use of environmentally friendly machining technology and the utilization of renewable energy resources during manufacturing [7]. The Service-Oriented Business Model aims at decoupling economic growth from resource consumption and waste creation, by improving functionality of products [8], [9] and/or by increasing their utilization ratio [10]. Relevant strategies include leasing and renting services provided by manufacturers. Maintenance can also be considered as a service offered by manufacturers to improve and upgrade product’s functionality. Overall, alternative SM strategies can be mapped as shown in Figure 3. Closed-loop manufacturing links the production unit with final products at the end of their life; industrial ecology links the production unit with industrial waste; cleaner production takes place inside the boundaries of the production unit; finally, the serviceoriented business model integrates the whole process of manufacturing products and making them available to customers.

Figure 2: Principles of sustainable product design.

3 3.1

SUSTAINABLE MANUFACTURING Definition

4

Sustainable Manufacturing (SM) integrates sustainability life-cycle issues in the production process, and aims at effective use of materials, energy, knowledge and capacity for work [2]. Chronologically sustainable manufacturing followed green and lean manufacturing [3]. Quinn et al. [4] define SM as “systems of production that integrate concerns for the long-term viability of the environment, workers health and safety, the community, and the economic life of a particular firm”. 3.2

Principles of SM

The principles of SM can be summarised as follows [4]: 

Reduce quantity of resources: energy, materials and water.



Improve environmental quality of resources: ecologically incompatible chemical substances.



Design for multiple and longer life-cycles: material loop systems; resource intensity and product’s service intensity.



Improve manufacturing technology: environmentally sound production technologies and processes.



Improve working conditions: ergonomic criteria, health and safety requirements; equity and fairness; employees’ personal development .



Support local communities: economical, social and cultural support.

3.3

toxic

The business case for integrating the principles of sustainability in a company’s operations is to create business opportunities by combating ecological and social problems threatening the world. Articulating the relationship between sustainability performance and profitability is crucial for integrating environmental and social aspects in business strategies. Integrating sustainability concerns in decision-making requires that efficient risk management is applied so that companies will protect themselves from sustainability threats and will capitalize on sustainability opportunities (Figure 4). 4.1

and

Strategies for SM

Alternative approaches to manufacturing have evolved from traditional to lean practices, and later to green manufacturing. Sustainable manufacturing includes strategies that go beyond lean and green practices by applying a holistic and innovative approach to manufacturing; key strategies are:

THE BUSINESS CASE FOR SUSTAINABLE PRODUCT DESIGN AND MANUFACTURING

Advantages of Manufacturing

Sustainable

Product

Design

Cost benefits and financial performance SPD allows cost benefits to be realised along the whole product life-cycle. Reduction in the quantity of resource requirements for goods to be produced results in reducing the cost of materials, the storage and distribution cost, the cost of production, and the quantity of waste to be managed. Manufacturing techniques that allow more efficient use of energy and materials, and require fewer consumables, reduce the cost of production and allow higher profit margins. Management of risks and opportunities Sustainability issues are at the forefront of the risk management agenda for most companies [11].

Closed-loop manufacturing is a manufacturing system where “products are made from used products, parts and materials takenback from market” [5]. This involves the 6R strategies, namely reduce, re-use, recycle, recover, redesign and remanufacture [6]. Recovery of products at the end of their life is the key link between conventional and closed-loop manufacturing. Modular design is a major enabler and requirement for closed-loop manufacturing. Industrial Ecology aims at closing the life-cycle by applying the closed-loop concept to industrial waste and by-products which is different to closed-loop manufacturing. Industrial residuals circulate

and

Figure 3: Sustainable manufacturing strategies

Sustainability in Manufacturing

215 Strict adherence to regulatory requirements Environmental legislation is a major driver for most companies, but when legal compliance is considered as separate from the opportunity to create competitive advantage, end-of-pipe solutions are preferred instead of holistic approaches that promote preventative strategies. Functional requirements

Figure 4: The business case for sustainability. Companies that apply carefully structured sustainability risk management systems are considered to be less risky businesses and are more attractive to insurance companies and financial organisations. Position in the market Public awareness has introduced ethical criteria to form customers’ purchase and consumption behaviour. The integration of sustainability principles in corporate strategy is important not only for expanding but also for retaining existing market share, as environmentally and socially conscious companies can participate in supply chain networks that set environmental and social requirements. Attract Investments Socially responsible companies are considered to pay off better and react more effectively in difficult economic times compared to their counterparts that focus solely on profit [12]. This makes these companies more attractive to socially responsible investors, who wish to invest in generating economic as well as sustainability values. Legal compliance Legal frameworks articulated at institutional level by governments and local authorities get increasingly strict requirements for manufacturers and retailers. Compliant companies are better prepared for future reviews of the environmental legislation. Development of innovative solutions Integration of sustainability principles in product design and manufacturing allows benefits to be realised by means of eco innovation [13]. 4.2

Barriers to Manufacturing

Sustainable

Product

Design

and

New innovative solutions that integrate environmental requirements are not always as functional as the conventional ones. Customers may be skeptical about the performance of green products or their poor quality [11]. Lack of support Lack of sufficient technical support and expertise prevents companies from realising sustainable solutions in product design and manufacturing. 5 5.1

SURVEY OF INDUSTRY Survey objectives

In order to compare and contrast literature review findings with industrial practice, a survey of manufacturing companies was conducted by means of questionnaire [15], [16]. This research focuses on a holistic approach to managerial issues and techniques that support sustainability in product design and manufacturing. The main objectives of the survey were: 

To identify how companies regard sustainability issues in product design and manufacturing,



To identify what the most popular sustainability strategies in product design and manufacturing are,



To identify what the perception is about the favourable and unfavourable aspects of integrating sustainability in organisations, and



To identify what the managerial approach is to the integration of sustainability in product design and manufacturing.

5.2

Results and analysis

The survey was conducted by interviewing or sending the questionnaire to companies; 75% of which were small or medium enterprises.

The cost of development and long pay back period is regarded as a major barrier for companies to integrate sustainability in product design and manufacturing.

Over 90% of the sample companies had already integrated sustainability principles in their product design and manufacturing operations, which means that the survey results should be in line with the viewpoint of environmentally and socially conscious companies. Senior managers provided response to the survey questionnaire.

Market pull strategies

Alternative strategies for sustainable product design

Lack of awareness about market trends and the uncertainty about customers’ response to sustainability initiatives tend to prevent companies from integrating environmental and social considerations.

The most widely adopted strategies are those that deal with the consumption of resources during the life-cycle of a product (Figure 5).

The main barriers are [14]: Financial issues and commercial disadvantage

Time constraints The time required for the realisation of changes towards sustainability may be in conflict with fundamental activities of the company. Lack of accountability Owners of the company may consider that taking environmental and social initiatives is a matter of charitable action beyond their scope of responsibility. Figure 5: Most commonly adopted SPD strategies.

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Figure 6: SM strategies. Strategies aiming at improving the environmental quality and reducing the quantity of resources are of equal popularity, as selected by 74% of the companies responded to the survey. Such strategies involve practices to reduce the use of energy, materials, and water, as well as solutions that promote the use of recyclable, recycled, nontoxic, and nonpolluting materials. In addition, 57% of the companies participating in the survey take end-of-life issues into consideration during their product design process by providing for disassembly, recycling, reusability, and remanufacturing of products at the end of their life. Social issues receive less attention compared to other strategies with 43% but still remain a significant consideration. Alternative strategies for sustainable manufacturing Strategies aiming to reduce the quantity of resources used during manufacturing are highly popular, as 71% of the companies indicate that they have implemented strategies to reduce the use of materials, energy and water during manufacturing processes (Figure 6). However, fewer companies (55%) appear to have implemented strategies that improve the quality of resources used during the manufacturing process. End-of-life issues are more popular, as 61% of the companies apply strategies such as reuse, recycling and remanufacturing. The use of industrial residuals as input to manufacturing processes, and service-oriented business strategies are less widely applied, as only 26% of the companies apply such strategies. Finally, 71% of the companies have implemented measures to improve the working conditions of their employees in terms of health and safety. Business drivers for sustainability Market trends are considered to be the most dominant driver for sustainability (33%) as shown in Figure 7. Cost savings and financial benefits have influenced 24% of the companies towards sustainability, while 18% of the companies selected brand image and reputation of the firm. 14% of the companies identified innovation as a factor that encourages them to integrate sustainability in their business strategy.

Figure 7: Drivers to SPD and SM.

Figure 8: Barriers to SPD and SM. Legal requirements was the least strong driver towards sustainability, on the contrary to what was expected according to the literature review, as only 11% of the companies selected this barrier. This can be explained by the fact that most of the companies participating in the survey are compliant and strive to reach sustainability beyond legal compliance. Barriers to sustainability Financial constraints are the most important barrier to integrating sustainability principles in their strategy (31%) (Figure 8). The next more influential barriers to sustainability are time constraints (27%), lack of market awareness (15%), excessive drive towards shortterm profitability (11%), lack of technical support and expertise (7%), and weak involvement of stakeholders (4%). Some companies also regarded lack of governmental support as a major barrier to sustainability. Another point raised was the tough competition created by companies that enter market for a short period of time in an opportunistic way, offer their products in competitive prices and then disappear. Advantages of sustainability Developing innovative solutions is the benefit identified by most companies (24%) (Figure 9). 20% of the companies believe that they have managed to strengthen their position in the market by either growing their market share or creating new market opportunities. 18% of the companies participating in the survey state that they have gained financial returns from the reduced use of resources, and identify legal compliance as a benefit of integrating sustainability in their strategy. However, only 4% of the companies identify a relationship between sustainability actions and improvement of their relationships with stakeholders.

Figure 9: Benefits from SPD and SM.

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Management and practice This section of the questionnaire was designed to find out about the size of change in organisational aspects, such as strategy, culture and structure, in order companies to implement sustainability. A linear rating scale ranging from 1 to 4 was used in order to measure this change, where 1 indicates no change and 4 stands for a large change. The mean values for strategy, structure and culture are 2.4, 2.1, and 2.6 respectively (Figure 10). On average, this indicates a considerable change in all of these three organisational aspects for the companies participating in the survey. The highest level of change is for culture, followed by strategy and then structure. This can be attributed to the fact that structural changes require greater practical implications than changes in softer issues such as strategy and culture. In addition, changes in softer aspects are not easily measurable and thus managers may overestimate such transformations. Implementation and practice Companies were also asked to assess how the integration of sustainability principles in their product design and manufacturing strategies had affected their activities and operations such as supply chain management, risk management, performance management and human resources management. The scale of change was measured according to a four level scale and mean value results are 2.1, 2.1, 2.4 and 2.3 respectively (Figure 10). This indicates that the greatest change on average has occurred in performance management by integrating eco-social indicators, as well as in human resources aspects, such as recruitment, training and rewarding system. Activities concerning supply chain and risk management operations are considered to have changed at a lower scale. 6 6.1

DISCUSSIONS, CONCLUSSIONS AND RECOMMENDATIONS Industry survey

Considering the responses to questions about strategies in sustainable product design and manufacturing, more emphasis is given on strategies that focus on environmental aspects rather than on social issues. Strategies dealing with the quality and quantity of resources, as well as with end-of-life issues are amongst the most popular strategies for SPD and SM results.

Figure 11: Holistic approach to product design. Taking into account that this survey focused on companies that have already implemented sustainability, it can be argued that environmentally and socially conscious companies consider sustainability as a long-term strategy that goes beyond short-term legal compliance. Benefits from integrating sustainability principles in product design and manufacturing differ considerably from the drivers that push companies towards SPD and SM. Although innovation is low in the list of drivers, it is the benefit most companies gain. The managers’ assessment on the changes in organisational and management aspects indicate that although their companies have made a considerable progress towards sustainability, yet there is still progress to be made in order to achieve the highest level of integration and get the most out of sustainability. 6.2

SPD and SM: The link and integration

Sustainable product design requires that life-cycle thinking is projected to integrate economical, environmental and social considerations in product specifications as depicted in Figure 11. Product design and manufacturing are linked by sustainability through the life-cycle interface. Life-cycle design provides for product specifications such as modularity, recyclability and reusability, which enable sustainable manufacturing. On the other hand, sustainable manufacturing affects product life-cycle by means of the closed-loop and service strategies, which allow multiple life-cycles for products and extension of their useful life respectively (Figure 12). 6.3

Managing SPD and SM

Contrary to what was identified in the literature review, the survey results indicate that legal requirements and cost savings are not high in the list of drivers for integrating sustainability in product design and manufacturing. Market trends are considered as a stronger motive for companies to change course towards sustainability.

Sustainable organisations support product design and manufacturing by integrating economic, environmental and social considerations at both operational and strategic levels. The operational level includes tools, techniques and methodologies to enable sustainability in product design and manufacturing, while the strategic level refers to organisational issues such as product strategy, structure and culture of the company (Figure 13).

Figure 10: Scale of change in organisational aspects.

Figure 12: The link between SPD and SM.

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Sustainability in Manufacturing [5]

Soma, M, Kondoh, S. and Umeda, Y. (2003): Simulation of Closed-loop Manufacturing Systems Focused on Material Balances, in: Proceedings of Eco design 2003: Third Internatiorial Symposium on Environmentally Conscious Design and inverse Manufacturing, Tokyo, Japan, December 8-11, 2003.

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Esty, D.C. and Winston, A.S. (2006): Green to Gold: How Smart Companies Use Environmental Strategy to Innovate, Create Value, and Build Competitive Advantage, Yale University Press, London.

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[17]

Epstein M. (2008): Making Sustainability Work: Best Practices in Managing and Measuring Corporate Social, Environmental and Economic Impacts, Greenleaf Publishing, UK.

Figure 13: The sustainable organisation. The type of strategy to be adopted is determined by the sustainability targets set by top management, in concert with a sound business case to support them. According to Epstein [17] sustainability strategy encompasses three clearly discrete levels, which aim at:  Managing regulatory compliance,  Achieving competitive advantage,  Complete social, economic, and environmental integration. Depending on the strategy followed, sustainability initiatives may focus on the value chain of the company, on its competitive context, or on general social issues (Figure 14). The holistic approach considers employees as key assets with emphasis on training and understanding of sustainability principles, and innovative thinking. In addition, the rewarding system should encourage sustainable practices and empower employees to take sustainability initiatives.

Figure 14: Sustainability integration strategies.

7 [1]

[2]

[3]

[4]

REFERENCES

Jawahir, I.S. and Dillon Jr O.W. (2007): Sustainable Manufacturing Processes: New Challenges for Developing Predictive Models and Optimization Techniques, in: Proceedings of the 1st International Conference on Sustainable Manufacturing, SM1, Montreal, Canada. Quinn, M.M, Kriebel, D, Geiser, K. and Moure-Eraso, R. (1998): Sustainable Production: A Proposed Strategy for the Work Environment, in: American Journal of Industrial Medicine, vol. 34, pp. 297-304.

8

CONTACTS

Klimis Ioannou, Mechanical Engineer, Beng, MEng email: [email protected] Alireza Veshagh, Associate Professor 205 IMC, University of Warwick email: [email protected]

A System for Resource Efficient Process Planning for Wire EDM 1

1

Sandeep Dhanik , Paul Xirouchakis , Roberto Perez 1

2

Institute of Production and Robotics, Mechanical Engineering Department, Swiss Federal Institute of Technology, Lausanne, Switzerland 2

R&D GF AgieCharmilles Technologies S.A., 1217 Meyrin 1, Geneva Switzerland

Abstract Efficient utilization of available resources for a particular machine tool technology is an important aspect of sustainable manufacturing. The objective of this paper is to present a method for efficient resource process planning for a Wire EDM Machine Tool System. For a given part information (required surface finish and workpiece height), the developed program automatically selects the feasible wires and generates the operation sequence and corresponding cutting conditions. The system then presents a multi objective framework consisting of both ecological criteria (waste generation, electricity consumption) and economic criteria (different costs and machining time) to suggest the wire which provides the best compromise solution for the considered criteria. Keywords: Wire EDM; Energy Consumption; Waste Generation

1

INTRODUCTION

Wire electro discharge machining (Wire EDM) is one of the important non-traditional machining processes, widely used in aerospace, nuclear and automotive industries [1]. It has been developed as an effective solution for a wide variety of materials including hard materials with intricate shapes. The Wire EDM process involves complex phenomena of generation of sparks and material erosion; these have been modeled by many researchers to solve the selection of optimum cutting conditions [2][3][4]. Further, considering the stochastic nature of the problem, a number of authors have tried to experimentally model the process for optimum process parameter selection using neural networks [5], genetic algorithms [6], and data mining techniques [7]. Although the minimization of process energy has been considered in some of these approaches, the consumption of the total electricity of the machine tool and other consumables like wire, filters and resins haven’t receive the same attention. Wire consumption is known to be one of the most important factors in Wire EDM machine tool utilization as it directly effects the waste generation and machine tool operation cost. Most of the efforts in past decades has been to increase machining speed without reducing the machining accuracy while considering various process related constraints like wire breakage. However, these approaches have not considered the impact of cutting conditions on the consumption of energy and wire, which are important for both economic as well as ecological points of view. Consideration of various consumables is especially important as the price of a wire EDM is small as compared to the cost of the consumed wire over the life of the machine tool. This paper presents a resource efficient manufacturing framework for Wire EDM which considers various economic and ecological factors to aid a process planner in selecting appropriate wire EDM consumables and cutting conditions. 2

LITERATURE REVIEW

Along with optimizing the Wire EDM process parameters, a number of researchers has identified and discussed the environmental

impacts of wire EDM machine tool utilization. Tonshoff et al. [8] reported on the environmental and safety aspects of EDM processes. Among the main potential environmental hazards they cited the hazardous gas, vapor and aerosols resulting from the high temperatures developed in the dielectric fluid. Also, heavy metals may be carried by the dielectric and the sludge. Since a great number of hazardous substances are generated during the EDM process it is very important to carefully treat and dispose this waste. Yeo et al. [9] proposed a method to assess the environmental impact of waste streams in die-sinking electric-discharge machining, transforming each of the three mass flows (electrode wear, part metal removal and dielectric waste streams) into a weighted mass flow by taking into account the rank value of the three considered hazard factors (toxicity, flammability and mass flow magnitude) of each mass flow and the relative importance (weights determined by pair-wise comparison of the importance between a pair of factors) of these hazard factors. The proposed method allows ranking from the environmental impact point of view alternative electrode-dielectric fluid combinations for die-sinking EDM machining. Yeo et al. [10] proposed a multi-objective method to select a dielectric fluid across several dimensions (machining time, consumed energy, part quality and electrode-part-dielectric fluid waste mass) in die-sinking electric-discharge machining. The best trade-off is obtained for the dielectric fluid with the highest utility calculated as a weighted linear combination of its utilities for each dimension; the weights are obtained from a pair-wise comparison of the relative importance of each pair of dimensions. Recently, the energy consuming wire-EDM system components and the energy consumption distribution was determined for the GF AgieCharmilles Eco EDM FI 440 cc machine tool [11]. It was found that a significant part of energy consumption was due to the water cooling, spark generator and water injection systems. Subsequently different operation modes were studied by variations in the part height, wire diameter, part material, wire material and cutting rates. The obtained results show that by changing the cutting conditions higher energy efficiency may be obtained. The machine, wire consumption and energy costs were further studied for a range of

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_38, © Springer-Verlag Berlin Heidelberg 2011

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process parameters. From these numerical examples it came out that the wire consumption costs are three to five times higher than the energy consumption costs.

machine tool builder GF AgieCharmilles SA, which can aid a process planner to achieve this goal. In summary, the objective of this paper is to summarize development in following areas:

It can be concluded that although various efforts are oriented towards the reduction of environmental impacts, there are the following shortcomings in the previously reported environmental impact assessment method (besides the fact that the method was developed for die-sinking EDM and not wire-EDM which is the focus of our study):

1. Energy consumption: To calculate the cost of machining based on consumable (EDM wire) consumption and electricity consumption by the following components:



The overall and component wise machine tool energy consumption of machine tool is not modeled.



The consumables waste streams are (electrodes, filters and de-ionizing resin) and



The influence of cutting conditions and part quality requirement is not taken into account.

not

considered

Since the inception of CNC machine tool technology, machine tool builders have created databases for cutting conditions which are developed for the practical operation of the machine tool. These databases are experimentally determined to achieve stable cutting conditions. Also, it is developed for the most common wires commercially available for the machine tool utilization phase. There exist at least 16 types of different for cutting steel according to GF AgieCharmilles Technology datatable[12]. Although machine tools are equipped with cutting condition tables for each wire, it is still a difficult task to decide which wires are feasible for a particular operation according to technical limitations and what is the best suitable wire among them. It is a daunting task to select the appropriate wire which adheres to the machining requirements as well as minimizes the machine tool energy and consumable utilization. Hence it is required to have a system, which can help the process planner to rank the different choices according to the predefined criteria or attributes. This paper presents a method and the developed computer tool in collaboration with a major EDM



Process related injection pump electricity consumption.



Process related spark generator input energy consumption.



Process independent (constant) energy consumption by the filling tank pump, auxiliary pump, and dielectric cooler.

2. Waste Stream Calculation: For a given application oriented user input (work piece material and thickness), the following direct waste streams are calculated: 

Wire consumption mass



Workpiece debris due to cutting process

3. Development of a multi objective optimization system for best wire selection among various feasible wires for given part requirement. 3 3.1

WIRE EDM PROCESS CONSIDERATIONS Process Diagram

As a first step, a model for electricity and waste assessment is conceptualized in Figure 1. In this model, the flows of the different materials, energy consumption relevant utilities and materials can be observed. During the machine tool utilization phase, electricity is consumed by the spark generator, flushing pump (also known as injection pump), filtration pump and waste treatment system. The waste consists of treated waste and disposed waste. During the EDM process, deionised water is constantly getting contaminated with metal particles produced during the EDM process and water

Figure 1: Process Flow and System Model for Wire EDM.

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filter/resins are used to treat this waste. Wire is constantly unrolling during the wire EDM process and cannot be used again due to quality issues, and hence it represents a significant source of waste in wire EDM. 3.2

Process Level Considerations

In Wire EDM, process level issues involve the consideration of various machining stages and corresponding cutting conditions according to the developed technology rules. These technological rules are defined in Charmilles technological tables [12]. The EDM wires consist of many types and diameters. There can be more than one wire suitable for a certain application. Hence, it is very important to take into account various wires and to find out which wire among a set of wires represents the best compromise among various criteria (cost, energy consumption, waste generation etc.)

  Figure 3: Power Consumption along the time horizon. The power consumption value of injection pump and spark generation unit depends upon the process (Workpiece material, wire type and diameter, cutting quality requirement). While, the other category of components (Filling pump, Filter Pump, Auxiliary pump, Cooler) are not affected by the process requirements. Hence, we need to take into account the Injection pump and Spark generation unit to calculate the total electricity consumption during the WEDM. Further, the spark energy output is formulated using the technology tables [12] and spark efficiency of the spark generator. Injection pump is found to be a direct function of a pressure index value (INJ) assigned by the machine tool controller and the relationship between the injection pump and INJ is established by experiments. Once spark generator efficiency is calculated, the input energy to the spark generator can be calculated with respect to the cutting conditions.

Figure 2: An example of a data sheet provided by GF Agie Charmilles for a workpiece made of steel and a brass wire [12]. Further, in order to achieve the specified workpiece surface finish by WEDM, a sequence of operations (one or multiple roughing, semi finishing, finishing passes) are required for a given wire. Each of these steps is an operation setting which contains a unique set of cutting conditions (various spark generation parameters, cutting speed and injection pump pressure) and the group of operation settings enabling the required surface finish is called operation sequence. There can be more than one operation sequence for a given set of surface finish, workpiece material, workpiece thickness, wire material and wire diameter. Therefore, it is needed to develop a system which selects the operation sequence according to the total machining time. For given part requirements, these details regarding operation settings and the cutting conditions can be useful for both energy and waste calculation as discussed in the following sections. 3.3

3.4

Waste Generation

For the disposable waste described in Figure 1, only the wire consumption can be accurately calculated. The filter systems are usually a quite simple installation, either paper-cartridge-filters or mineral filters. As there are no data available yet in terms of consumption for the recycling or burning of the filter, no definite conclusions can be drawn. However, the filter life is known to be affected by the eroded mass of workpiece due to the sparks. Wasted Workpiece material Calculation: During wire EDM, the material is removed from the workpiece by either thermal or mechanical action of sparks. The waste generation depends upon the wire diameter and the machining steps (see Figure 4). The type of wire and cutting conditions both affect this waste stream. For example, the bigger diameter wire can generate more waste than the smaller diameter wire for per mm of cut.

Electricity Consumption

The component wise power distribution during the various phases of a machining process on a WEDM machine tool system is shown in Figure 3. It can be seen that there are two types of components in the power distribution diagram: 



Process related power consumption components 

Injection pump power consumption



Spark generation unit

Process independent components 

Filling Pump



Filter pump



Auxiliary pump



Cooler

(constant)

power

consumption

Figure 4: Workpiece Material Removal Calculation based on Operation settings. Waste Wire Mass Calculation: In wire EDM, the rolling of wire can be used to calculate the wasted mass as the wire is used only once due to quality issues. The wire is chopped using a chopping device

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and this waste mass is put in a waste bin. Hence, wire is a significant waste in the WEDM process. 3.5

Cost Calculation

The cost of different wires is shown in Table 1, although the wire cost depends also on the spool size, this cost data is taken for the purpose of roughly comparing different wire materials. The electricity cost is taken as 0.12 CHF per kWh. Serial no.

Wire Material

Wire cost (CHF per Kg)

1

Hard Brass

12

2

Zinc Coated Brass

15

3

Zinc Coated Copper XS

20

Table 1: Cost of different wires. 4

DEVELOPED METHOD

The details discussed in the previous sections are implemented for the assessment of different EDM wires for the user defined requirements. In WEDM, the user has to define the part requirements such as workpiece material, surface finish and workpiece thickness as shown in Figure 5.

Figure 5: User Input. Based on the workpiece material, the developed program automatically selects all the wires suitable for cutting that material. For example, for the case of steel, the 6 types of Hard Brass wire, 4 types of Zinc coated wire and 2 types of Zinc coated Copper XS wires are initially selected.

Figure 6: Summary of the Method developed for assessment of Energy and Waste. However, not all the wires are suitable for a particular application. For example, thin wires are not suitable for very high workpiece height (more than 80mm) while thick wire may not be suitable for low surface finish requirement. Once a wire is found feasible, the operation sequences are determined. There can be more than one

operation sequence for a given surface roughness. For example in Figure 2, there can be more than two operation sequences which may satisfy a medium surface finish requirement. Also, each operation sequence is a combination of roughing, semi finishing and finishing stages. There can be multiple semi finishing stages

Sustainability in Manufacturing between roughing and finishing stages. For each of these stages, the wire is travelling across the same cutting profile length, but with different cutting conditions. Hence, there is a need to evaluate the overall effect of all the operation settings in an operation sequence. Using the data tables, the cutting conditions, spark generator setting and injection pump pressure index are extracted and the machining time for per unit length, component level energy consumption and waste are calculated as discussed in the previous sections. Subsequently, the various attributes of all the possible operation sequences for a wire are evaluated, an operation sequences is selected which corresponds to the minimum time or minimum energy per unit cutting length. It was found that minimum time also corresponds to minimum total energy of a machine tool; hence either minimum time or minimum energy is suitable for selecting the operation sequence. This procedure is repeated for all the wires in the feasible wire dataset. The following entities are eventually evaluated for each feasible wire:

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Figure 8: Spark Energy Consumption vs Workpiece height for different EDM wires. Further, the Injection pressure pump was measured and compared with the modeled power, this result is shown in Figure 9.

1. Total and component wise energy consumption 2. Waste Generation due to wire mass 3. Waste generation due to workpiece mass 4. Wire and electricity cost The flow diagram of the developed method is shown in Figure 6. Once the various entities for each wire are determined, it is required to find the wire which performs best among the different categories. Thus, it paves a way for multi objective optimization for best wire selection. In this paper, a weighted average method is suggested for the same. In order to implement this, weights and the baseline value for each of the attribute is required. The user has to define the weight of the objectives according to experience or requirements. The base line values are calculated as the average value of each attribute for all the feasible wires. This approach is shown in Figure 8.

Figure 9: Injection pump power vs INJ. 6

RESULTS

It can be seen from Figure 8 that the zinc coated copper XS wire is far more energy efficient for cutting large height of workpiece due to superior cutting speeds, while for small workpiece height the energy consumption is nearly the same for all the wires. However, if wires are compared with respect to various attributes, as shown in Figure 10, zinc coated copper XS wire has still the lowest energy consumption per mm length of cut, but the total cost is much higher due to the cost of wire consumption. The wasted mass of Zinc coated copper XS wire is also high as compared to the other wire.

Figure 7: Implementation of optimization framework. 5

EXPERIMENTS

A set of experiments are carried out on steel as workpiece material in order to identify the spark generation efficiency and verification of the adopted model for injection pump power. Spark generation efficiency is important as the output energy (process energy) is not the same as the input energy. Experiments are carried out on various WEDM wires and various parameters are monitored during the experiments. Spark energy obtained from the experiments is shown in Figure 8.

Figure 10: Spider chart of comparison of three wires in WEDM on steel (values are represented in percentage). In Figure 11, another machining scenario is presented with the same workpiece height, but different surface roughness. It can be seen clearly for this cutting scenario that Zinc Coated Copper XS wire can be regarded as a best solution in all the attributes. Thus,

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with the change in part requirement, the choice of the wire can change while considering different attributes.

choice of the best suitable wire, energy consumption and waste generation. There is no single wire which is best for all the attributes and hence there is a need of multi-objective framework to select the best compromise solution. 8

ACKNOWLEDGMENTS

This work is financially supported under the Swiss Innovation Promotion Agency CTI Project (CTIP-No.9933.2) “ReManufacturing: Concepts & Methods for Resource Effective Part Manufacturing”. The authors also thank the project team lead by Mr. Lukas Weiss of Inspire ETHZ for cooperation in energy measurement experiments. 9

Figure 11: Another example of steel machining using three wires with different required surface finish. The developed software presents such results for several wires. A sample example is shown in Figure 12. The wire index in Figure 12 corresponds to the list of wires as shown in Figure 5.In Figure 12, the missing index corresponds to the wires which are not suitable for the user defined application. It also shows that the contribution of cost of wire is much more significant than the electricity consumption. Further, the wire waste is much more significant than the waste of the workpiece mass.

Snoyes, R.; (1986): Current trends in non-conventional material removal processes, in: Annals of CIRP, vol. 35, No.2, pp. 467–480.

[2]

DiBonoto, D.D; (1989): Theoretical models of electrical discharge machining process—I. A simple cathode erosion model,in: Journal of Applied Physics Vol. 66, No. 9, pp. 4095– 4103.

[3]

Dhanik, S; Joshi, S.S.; (2005): Modeling of a single resistance capacitance pulse discharge in micro-electro discharge machining, in: Journal of Manufacturing Science and Engineering, Vol.127, pp.759–756

[4]

Das S., and Joshi, S.S.; (2010): Modeling of spark erosion rate in micro wire-EDM, in: International Journal of Advanced Manufacturing Technology (2010), Vol.48, pp. 581–596.

[5]

Kuriakose, S.; Mohan, K.; Shunmugam, M.S.; (2003) Data mining applied to wire-EDM process, in: Journal of Materials Processing Technology, Vol. 142, No.1, pp. 182-189.

[6]

Chen, H.C.; Lin, J.-C.; Yang Y.-Y.; Tsai, C.-H.; (2010): Optimization of wire electrical discharge machining for pure tungsten using a neural network integrated simulated annealing approach, in: Expert Systems with Applications: An International Journal, Vol. 37, No.10, pp. 7147-7153.

[7]

Kuriakose, S.; Shunmugam, M.S.; (2005): Multi-objective optimization of wire-electro discharge machining process by Non-Dominated Sorting Genetic Algorithm, in: Journal of Materials Processing Technology, Vol. 170 No. 1-2, pp. 133141.

[8]

Tonshoff, H.K.; Egger, R.; Klocke, F.;(1996): Environmental and safety aspects of electrophysical and electrochemical processes, in: CIRP Annals - Manufacturing Technology, Vol. 45, No.2, pp. 553-568.

[9]

Yeo, S.H.; H.C. Tan; and A.K. New; (1998): Assessment of waste streams in electric-discharge machining for environmental impact analysis, in: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 212, No.5, pp. 393-400.

[10]

Yeo, S.H.; and New, A.K.; (1999): Method for green process planning in electric discharge machining, in: International Journal of Advanced Manufacturing Technology, Vol. 15, No.4, pp. 287-291.

[11]

Deiss, C; (2009): Eco machine Study on Energy Consumption of wire and wire Erosion Machine (published in german), Master Thesis, RWTH Aachen University.

[12]

Charmilles; (2005): Technologies Manual Robofil 240 CC 440CC, GF Agie Charmilles SA.

Figure 12: A sample result window of software for 60 mm Steel cutting with 0.8 µm surface roughness. 7

CONCLUSION

The influence of wire diameter and material and part requirementsworkpiece height and surface finish, is investigated for machine tool use phase with different criteria: energy consumption, total machining cost, wire and workpiece waste generation. A computer program is developed to integrate existing technological database of a wire EDM machine, which calculates the abovementioned attributes. It can be concluded that the part requirements (workpiece height and surface finish) have significant effect on the

REFERENCES

[1]

Increased Trustability of Reliability Prognoses for Machine Tools 1

1

1

1

Gisela Lanza , Patrick Werner , Dominic Appel , Benjamin Behmann 1

Karlsruhe Institute of Technology (KIT), wbk Institute of Production Science, Karlsruhe, Germany

Abstract The estimation of trustable reliability figures for machine tools is a considerable challenge. The main reasons are the sparse availability of relevant components’ lifetime data as well as the load-dependence of reliability. The proposed paper presents a method to estimate increasingly trustable load-dependent reliability figures for machine tools using design information to estimate the reliability if no field data is given, service knowledge of an existing service department which monitors field maintenance of the products and documented field data of spare parts sales, service and maintenance activities. Keywords: Load-Depended Reliability Model; Trustability of Reliability Figures; Confidence Bounds

1

MOTIVATION AND OBJECTIVES

In recent times an increasing number of customers of the machine and plant industry ask for different kinds of special warranties [1], for example warranties for the maintenance costs over a long period of time, like 10 years [2], or warranted reliability figures for their production plants. Especially reliability improvement warranties with fixed reliability figures like a Mean Time Between Failure (MTBF) are often demanded. Currently, many companies in the machine and plant industry estimated these values purely on expert knowledge, mostly from the development department. But since the risks arising from these warranties could have a considerable impact on the company’s success, a trustable knowledge of the failure behavior of the machine components and the whole technical plants in the field is necessary. In most cases, this knowledge is best gained by statistically analyzing field data. This field data is achievable from service data of maintenance activities done by the operator’s maintenance or the manufacturer’s service department and to a lesser extent, from spare part sales. The main challenge of generating trustworthy predictions via statistical analysis in the machine and plant industry is the low data availability due to low production numbers and a comparatively low number of failures [3]. In this context the machine and plant industry differs considerably from industries with mass products where statistically analyzed reliability tests are common. Machine and plants are often individual products which are adapted to the buyers’ requirements. Moreover, reliability does not only depend on the technical characteristics of the considered components, it is also varying loads that have an essential impact on the failure behavior [3, 4]. Therefore, the success of the statistical analysis and the quality of the prediction strongly correlate with the inclusion of the load relations and the data quality. In order to address these challenges the paper in hand presents an approach to how systematically use different data sources in order to estimate trustworthy reliability figures using the developed methodology. Thus, the machine and plants industry is able to face the upcoming risk of extended warranties or reliability improvement warranties and the risk arising from the statistical variance of the

service life. Regarding high penalty payments up to 30 % of the machine price [5] the quantification of these risks is very important for the machine and plants manufacturer’s economical success. 2

RELIABILITY MODEL

Machines and plants in general are complex systems consisting of defined assemblies which can be, for their part, broken up in different components. Additionally, the varying applications of the components have a considerable influence on the machine service life. The installation position and the function of the components can thereby take in major constraints. Thus, it is essential to create a reasonable clustering of the machine components in order to systematically describe the machine structure and the components usage. To focus on relevant components for a further reliability consideration, clustering also has to include an analysis of the criticality of each component. Hence, a reduction of the machine structure complexity is realizable. The fault-tree analysis [6] constitutes an established tool to support this process. Depending on the data at hand, the statistical analysis is done at a different level of the tree. The more appropriate data available, the more detailed the level for the analysis can be chosen. For a trustworthy analysis, the level of detail should be as low as possible, ideally on the level of failure modes. However, in most cases, this is not possible since there are not enough failures per failure mode. In practice, it should be at least as detailed as the level of detail of the operator’s perception. For the analysis of the field data, mean values only, assuming an exponential distribution, are often used. Moreover, many companies start to use the two or three parametric Weibull distribution. But since reliability of machine tool components often highly depends on the operating conditions and the loads which result from these conditions, the Weibull distribution can be the wrong model. Therefore, the General Log-Linear model together with the Cumulative Damage model is used in this approach to describe this impact mathematically. [7] The advantage of this model is that it not only takes time-varying loads into account, but also different

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_39, © Springer-Verlag Berlin Heidelberg 2011

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applying loads at the same time. In the Weibull Cumulative Damage model the Weibull distribution is viewed in relation to a cumulative damage caused to the component by different loads rather than in relation to the component lifetime. The general form of the distribution function of the model is described in formula 1.

F (t; L)  1  e  (W ( t ; L ))

W (t; L )   e

a0 

 a j X (t ') j j

(1)

dt '

(2)

0

a0 and aj are function parameters and t is the variable for time. Xj is a transformation of the stress levels Lj. The kind of transformation depends on the kind of load. For mechanical loads this is according to the Power-Law - the natural logarithm. For thermal loads this is - according to the Arrhenius law - the reciprocal value. [7] The model allows the calculation of the remaining service life at any time for any probability using the conditional probability based on the previous loads over time and a predicted future load profile. Formula 3 describes a remaining service life T, given a cumulated damage of W, a prognosis load collective of W f and a probability P for survival. [8]  1

T  (  W   ln( P )  W )  W 3

4 4.1



Form parameter β is considered to be load-independent and, therefore, constant as a characteristic parameter for a specific type of failure. W(t;L) represents the cumulated damage which is a function of time t and a load vector L. It replaces the term t/η in the Weibull distribution because η is considered to be load-dependent. In the General Log-Linear form it is written as in formula 2 [7]. t

distribution [e.g. 13] for certain machine components, but in most cases only a wide range is given.

f

(3)

At first, values for service lifes are often very conservative estimates. In an analysis of ball screws at the wbk Institute of Production Science, the actual service life of the least reliable of 25 ball screws was twice the service life which the respective standard predicted. [12] This is not advantageous for not-safety relevant parts since a too low reliability given for a component might result in lost sales in the bidding process. Secondly, most standards do not provide the probability of failure or a deviation of the service life. There are some sources for characteristic values of the shape parameter of the Weibull

Use of knowledge of the service department

If the service activities of an existing service department have not been sufficiently documented in the past, the knowledge of the service department staff can be used to estimate the parameters of the Weibull distribution. Jäger and Bertsche show in [14] an approach for a three parametric Weibull distribution. For a loaddependent view, this approach has to be modified. If the life-stress relationship is known, the service staff is only used to estimate the scale parameter of the service life distribution. The staff is prompted for the first (tmin) and the last failure (tmax) of a known number of components n. The service life around which most failures happen is also prompted for. Using the Benard Median Rank [15] one can get the following two formulas:

F tmin   1  e

 t    min    L  

F tmax   1  e



t    max    L  

!

 

!



1  0,3 n  0,4

(4)

n  0,3 n  0,4

(5)

where η(L) is the load-dependent scale parameter of the Weibull distribution. By solving those two formulas, the value for the shape parameter β and the load level L (if not already known) can be estimated. Alternatively, the time at which most failures happen (e.g. the supremum of the distribution tsup) can be used together with the formulas 4 or 5.

df tsup  dt

USE OF DESIGN INFORMATION

The estimation of parameters for the General log-linear model requires sufficient data about lifetimes of components and the respective loads they have been subjected to over time. This data is often not available in the machine tool industry and especially not in the case of a new component without any field data. However, there are sources for first estimates of the parameters. Important sources are S-N curves or Wöhler curves which are widely used in mechanical engineering. These Wöhler curves are often available for some parts of the components or can be artificially created by following the FKM guidelines [9, 10]. Furthermore, standards for the calculation of the expected service life of mechanical parts include life-stress relationships. One example is the standard regarding the service life of bearings. This standard also assumes an exponential relationship between mechanical load and lifetime with an exponent of 3 or 3.3 depending on the type of bearing [11]. Most of these data sources have two shortcomings.

USE OF SPARE PARTS AND SERVICE DATA

tsup

 0   L  

  1     

1

(6)



Since the first failure might be an early failure the use of formula 5 together with formula 6 might give the best results. The practical application of this approach has shown that its results can only be seen as a rough estimation. Especially the missing consideration of suspensions is a considerable source of error [3]. In this case, suspensions are lifetimes of components which did not fail up till the time of the analysis. 4.2

Use of spare parts sales

Spare parts sales are often seen as a usable data source in order to estimate reliability figures. But from the sales data alone the time and place of the actual assembly cannot be derivated and therefore the lifetime of a component is not calculable. It may be possible that the operator of the equipment informs the manufacturer about the use of spare parts. But even if not, it should be possible to calculate a simple MTBF value for a component by dividing the number of components in the field with the number of sold spare parts for a particular time period (e.g. year). In the machine and plants industry, most components are purchased by specialized suppliers and many customers buy their spare parts directly from them. Thus, the manufacturer might not know about all spare parts assemblies, if he is not informed. This could be addressed if the operator agrees to buy his spare parts only from the manufacturer e.g. as part of a larger service contract.

Sustainability in Manufacturing 4.3

Use of service data

The best source of failure data for many machine and plant manufacturers is the documentation of maintenance activities of their own service department. In order to use this information, the service actions performed have to be sufficiently documented. At least, the service life of the failed component has to be calculable. This is true if either the component can be uniquely tracked or the place of assembly (machine, position in the components tree) is fully known. The service life could be measured from assembly date to failure date, or even better in operating hours. Additional information could be the exact failure mode, the reason for the failure, the operating conditions, including all loads and repair expenses. As outlined before, the goal is to collect data about the service life of components together with the exact failure modes and the respective load collective. Predefined select lists for the documentation considerably simplify the statistical analysis compared to free text field. A major problem of the use of service data is that maintenance actions are often done by the operator’s maintenance department or a third party and the manufacturer is not informed. This could lead to wrong suspensions where it is assumed that a component is still in service while instead it has already failed. 5

USE OF OPERATOR DATA

Data from the maintenance department of the operator is seldom available for the machine or plant manufacturer. However, when the operator requires a reliability improvement warranty (RIW), he often shares parts of his maintenance data with the manufacturer in order to control the reliability figures. One example for these RIWs is the Maintenance – Total Cost of Ownership (M-TCO) model of the Daimler AG [16]. The analysis of the data can give a holistic view on the behavior of the machines and plants for this respective operator as long as the data meets the same requirements as the service data described earlier. Unlike the service data, the operator data should not include the problem of unreported failures. On the other side, it is often more difficult for the manufacturer to observe the operating conditions completely. 6

227 confidence bounds. If an operator or a data point has a high impact on the parameter or the confidence bounds, it is likely that the data is not as trustworthy as the rest of the data.

The usage of confidence bounds is combined with a jackknife method [17] to estimate the impact of certain data or the impact of the operating conditions on the estimated parameters and their

Key figures

Weibull distribution

Data with suspension

MTBF

100%

Upper confidence bound

213%

Lower confidence bound

59%

Difference

153%

MTBF

100%

Upper confidence bound

139%

Lower confidence bound

71%

Difference

69%

Data without suspension

Table 1: Comparison of the confidence bounds. Furthermore, there is the challenge of fixing the wrong distribution to the data. This could be addressed by fitting the Generalized Gamma distribution [18] which is a combination of the log-normal and the Weibull distribution. As seen in table 2 this method incorporates the uncertainty of the unknown distribution through a higher deviation of the distribution parameters and the resulting MTBF. Using a Monte Carlo simulation described in [19], the uncertainty in the parameters can be incorporated in the further calculations like e.g. in the prognosis of the warranty costs.

APPROACH FOR THE MEASUREMENT OF TRUSTABILITY

As outlined before, many factors reduce the trustability of failure data in the machine and plant industry. There are possibilities to reduce these factors organizationally, but considerable uncertainties remain, mainly due to the low number of products in field and hence the low number of failures. For a risk assessment in the bidding process of a new machine, these uncertainties have to be estimated as well as possible in order to calculate the risk of the whole bidding. In this approach, the confidence bounds are used to estimate the uncertainty of the field data. Table 1 shows the 90 % both-sided confidence bounds of the MTBF of an analysis of a field data set of a machine tool component. In the last column the MTBF is set as the reference value, the confidence bounds are expressed in relation to the MTBF. The difference quantifies the width of the confidence interval. The larger one includes the suspension which was documented in the system, the smaller one does not. While normally the inclusion of suspensions is necessary for realistic analyses of reliability data, in this case the inclusion increases the uncertainty regarding the parameters. It is suspected that the documented suspensions do not correspond with real components’ service lifes but were wrongly assumed because the failures of the components were not reported.

Data description

Key figures

Weibull distribution

Generalized Gamma distribution

MTBF

100%

100%

Upper confidence bound

139%

271%

Lower confidence bound

71%

37%

Difference

69%

234%

Table 2: Comparison of confidence bounds for different distributions. 7

SUMMARY AND CONCLUSIONS

There is a high demand for trustable reliability figures in the machine and plant industry in order to face demanded reliability warranties and, at the same time, to estimate the risk of upcoming costs in case of non-compliance. But the special circumstances in this industry, determined by small companies, low production numbers, short lifecycles and long warranty periods result in considerable challenges for the estimation of these reliability figures, like distribution parameters or MTBF values. The paper showed an approach to gain more trustable reliability figures and to assess their trustability. Therefore an application-oriented method is proposed to systematically use different data sources concerning reliability figures. As a result, the uncertainty of the estimated reliability distributions can be quantified using confidence bounds. In practice, the abstract concept of statistical uncertainties has to be

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made usable for the bidding process of small to mid-sized machine and plant manufacturers. Therefore, the assessment approach and a signaling system are currently in development at the wbk Institute of Production Science, which rank the reliability figures in three steps: Green (figures usable without consultation of a specialist), yellow (consultation mandatory for important projects), red (consultation of a specialist mandatory). The specialist would mainly be a development engineer or a service engineer who are currently in most cases the source of estimations for the reliability parameters of the machine and plant components. 8

ACKNOWLEDGMENTS

We extend our sincere thanks to the German Research Foundation (Deutsche Forschungsgemeinschaft) for the promotion of the research project LA 2351/7-1 “Development of a methodology for a failure oriented spare parts provision considering operation and load impacts” (“Entwicklung einer Methodik zur ausfallgerechten Ersatzteilbereitstellung unter Berücksichtigung von Betriebs- und Belastungseinflüssen”). 9 [1]

REFERENCES Fleischer, J., Niggeschmidt, S., Wawerla, M. (2007): Machine Life Cyle Cost Estimation via Monte-Carlo Simulation, in: Advances in Life Cycle Engineering for Sustainable Manufacturing Businesses, Proceeding of the 14th CIRP Conference on Life Cycle Engineering, pp. 449-454, Wesada University, Tokyo, Japan, June 11th-13th.

[2]

Verein Deutscher Ingenieure (1986): VDI-Richtlinie 4004, Blatt 4, Zuverlässigkeitskenngrößen – Verfügbarkeitskenngrößen, Beuth, Berlin.

[3]

Niggeschmidt, S. (2010): Ausfallgerechte Ersatzteilbereitstellung im Maschinen- und Anlagenbau mittels lastabhängiger Lebensdauerprognosen, Fortschrittsberichte Band 155, wbk Institut für Produktionstechnik, Karlsruhe.

[4]

Fleischer, J., Niggeschmidt, S., Wawerla, M. (2007): Optimizing the Life-Cycle-Performance of Machine Tools by Reliability and Availability Prognosis, in: Advances in Life Cycle Engineering for Sustainable Manufacturing Businesses, Proceeding of the 14th CIRP Conference on Life Cycle Engineering, pp. 329-334, Waseda University, Tokyo, Japan, June 11th-13th.

[5]

Fleischer, J.; Weismann, U.; Nesges, D.; Wawerla, M. (2004): Life-Cycle-Performance in der Produktionstechnik, in: VDI-Z 146 10, pp. 87-90.

[6]

Birolini, A. (2004): Reliability Engineering – Theory and Practice, 4th ed., Springer Verlag, Berlin.

[7]

Nelson, W.B. (2003): Applied Life Data Analysis, WileyInterscience, New York.

[8]

Lanza, G., Werner, P., Niggeschmidt, S. (2009): Behavior of Dynamic Preventive Maintenance Optimization for Machine Tools, in: Proceeding of the Annual Reliability and Maintainability Symposium 2009, pp. 315 – 320, Fort Worth, Texas, USA.

[9]

Forschungskuratorium Maschinenbau (2003): Rechnerischer Festigkeitsnachweis für Maschinenbauteile aus Stahl, Eisenguss und Aluminiumwerkstoffen, 5. Aufl., VDMA Verlag GmbH, Frankfurt am Main.

[10]

Fleischer, J., Niggeschmidt, S., Werner, P. (2008): Application Oriented Approach for the Integration of Load Impacts in Reliability Analysis and Lifetime Prediction, in: International

Applied Reliability Symposium 2008, Frankfurt, Germany, March 26th-28th. [11]

DIN Deutsches Institut für Normung e.V. (2007): DIN ISO 281 Rolling bearings – Dynamic load ratings and rating life (ISO 281:2007), Beuth Verlag GmbH, Berlin.

[12]

Munzinger, C., Schopp, M., Hennrich, H. (2010): Increasing maintenance efficiency - A strategy regarding condition and load-based approaches for diagnosis and prognosis, in: Conference Proceedings of the 2nd CIRP Process Machine Interactions 2010, Vancouver, Canada, June 6th-10th.

[13]

Bertsche, B., Lechner, G. (2004): Zuverlässigkeit im Fahrzeug- und Maschinenbau: Ermittlung von Bauteil- und System-Zuverlässigkeiten, Springer Verlag, Berlin.

[14]

Jäger, P., Bertsche, B. (2004): A new approach to gathering failure behavior information about mechanical components based on expert knowledge. in: Annual Reliability and Maintainability Symposium 2004, pp. 90-95.

[15]

Abernethy, R. B. (2006): The New Weibull Handbook. 5. Auflage, Robert B. Abernethy Publishing, North Palm Beach, Florida.

[16]

Nau, D. (2004): Total Cost of Ownership (TCO) bei DaimlerChrysler, in Conference Proceedings of the Conference Life-Cycle-Performance in der Produktionstechnik 2004, Karlsruhe.

[17]

Quenouille, M. H. (1949): Approximate tests of correlation in time series, in: J. R. Statist. Soc. B11 (1949), pp. 18–84.

[18]

Kao, J.H.K. (1958): A New Life Quality Measure for Electron Tubes. IRE Transaction on Reliability and Quality Control, PGRQC 13, pp. 15-22.

[19]

Lanza, G., Werner, P., Behmann, B. (2010): Prognosis of machine tool warranty costs considering arising risks through weak data sets and unknown load profiles, in: Conference Proceedings of the European Safety and Reliability Conference (ESREL 2010), pp. 1014-1018, Rhodes, Greece.

Hidden Aspects of Industrial Packaging The Driving Forces behind Packaging Selection Processes at Industrial Packaging Suppliers Sandra Silgård Casell 1

1

Division of Packaging Logistics, Department of Design Sciences, Lund University, Lund, Sweden

Abstract The choice of industrial packaging has an impact on activities throughout the supply chain in terms of costs, handling efficiency, transport efficiency and environmental considerations. The aim of this study is twofold: to gain insight into the processes employed by industrial packaging suppliers in packaging selection; and to understand the effect interactions between customer and supplier have on selection. In addition, bottlenecks in the packaging selection process are highlighted. The research findings emphasize the process mapping and logistics cost analyses performed. Three companies, all packaging suppliers to global manufacturing customers active in various fields have participated in the case study. Keywords: Industrial Packaging; Packaging Suppliers; Process Mapping

1

INTRODUCTION

“Packaging contributes to the success of product supply chains, enabling efficient distribution of products, and reduced environmental impact of products spoilage and waste.” [1] A literature review of the research in industrial packaging indicates a lack of focus on industrial packaging. In support of this, [2] claimed more than ten years ago that the literature in the area of packaging was dominated by consumer packaging from a marketing oriented perspective. This still holds true. [3] investigated packaging from a retail supply chain stance, where marketing aspects play a predominant role. [3] claimed that without examining the marketing aspects no considerations of the logistics aspects of packaging were possible. This research points towards a research focus on sales packaging. [4] includes sales packaging and industrial packaging in the basic theoretical aspects of packaging logistics. Research on packaging has also focused on the producing company’s (i.e., the packaging customer’s) processes of managing packaging matters. [5] put packaging in the light of sustainability research, claiming that “Packaging has a key role to play in sustainable development.” [6] showed that the interplay between the packaging, the logistics, and the product development functions can have a positive impact on logistics performance and cut costs. [7] elaborated this reasoning further, indicating that integrated packaging and product development that embrace logistics considerations enable a competitive and coordinated supply chain. [8] discussed the potentials of enhancing resource utilization by integrating the development of product and packaging to run in parallel. Industrial packaging is often addressed from an operational view of the producing companies, such as deficient handling aspects [4]. However, none of this research focused on the work of the industrial packaging suppliers, nor on the central interactions between the customer and packaging supplier in developing a packaging solution to serve customer satisfaction. [9] addressed the packaging development process at sales packaging suppliers, but did not emphasize the supply chain context and cost aspects. [10] investigated the packaging selection processes and the influences

on packaging decisions at two producing companies. Nevertheless, insight into the processes at industrial packaging suppliers is not reported on. To reduce this gap this research was carried out. The purpose of this paper is twofold; to gain insight into the processes employed by industrial packaging suppliers in packaging selection and to understand their interactions with manufacturing companies, in the context of the supply chain in order to find a packaging solution that satisfies the demands of these customer. The research questions used to fulfill this purpose are: What processes and rationales are used when packaging suppliers suggest an industrial packaging solution? ii. What is the nature of the ongoing dialogue and the state of involvement between the industrial packaging suppliers and the manufacturing companies to arrive at a satisfactory packaging solution? This paper presents a frame of reference followed by the research methodology and descriptions of the cases. The results are then presented, followed by the discussion and conclusions. i.

2 2.1

FRAME OF REFERENCE Industrial packaging and PPS set-up

The packaging type in focus is intended to fulfill the functions of protection, enable handling of the product, and be the vehicle used between factories, distribution centers etc., and not primarily for individual consumers (i.e., as sales packaging). In the packaging hierarchy [11], this type of packaging would correspond to secondary and in some cases tertiary packaging. Different terms are used in the literature for this type of packaging; business-tobusiness packaging, transport packaging, distribution packaging, and industrial packaging. The packaging term used for these functions in this study is industrial packaging. [1] denote the packaging which remains in an industrial supply chain industrial packaging. This view also applies to the study reported on here. As [9] pointed out, the terms packaging and package are considered synonyms. In this research, the abbreviation for product and packaging system is PPS, referring either to an existing PPS or to

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_40, © Springer-Verlag Berlin Heidelberg 2011

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a potential PPS. The term PPS set-up should be interpreted as the supply chain context in which the product and packaging system is handled and its encounters with the logistical layout. In turn, the logistical layout should be interpreted as the arrangement of the logistics activities on operational and executional levels. 2.2

Process mapping

The use of process mapping is important as a tool for process improvement by gaining an understanding of the activities performed by an organization [12,13]. This tool is powerful in discovering interactions and relationships between activities in different functions [13,14], in defining the current state of operations, and in identifying problem areas where improvements can be made [12]. Enhancement in process performance and thus customer satisfaction can be achieved by identifying activities that increase productivity and reduce inefficiencies, duplications, process cycle times and costs [13]. [14] describe a process as “a repetitively used network of activities linked in an orderly manner. The activities employ identified information and resources for transforming ‘input objects’ to ‘output objects’, extending from the point of identification to that of customer satisfaction.” The work of describing processes is commonly denoted process mapping, where previously invisible processes are brought forward [14]. 2.3

Packaging purchase

The packaging design can influence the productivity and cost efficiency of materials handling [4]. More than 10 years ago, [4] showed that the dialogue with the packaging supplier on new packaging solutions and decisions were taken care of by a purchaser or a designer. [4] noted a need for developing the organization around the transport packaging. The study also demonstrated that most companies view packaging as a cost driver, instead of realizing the cost savings it can give rise to along the supply chain. [4] also found that there is often a lack of knowledge on how packaging affects the logistics system and vice versa. 2.4

Theory on the packaging development/selection process

[9] identified a number of theories of the packaging development process and found that they were not generic, were inconsistent in the distinguishable phases of processes, were composed of fragmentary interrelations between activities in the process, differed in decision gates, and were too old to be compatible with today’s technology. Based on the review of existing literature on packaging development processes, [9] provided an interesting approach to them for packaging manufacturers (i.e., packaging suppliers). Her aim was to present an integrated packaging and product development process [15]. She proposed a generic packaging development that deals strictly with applying the traditional aspects of product development on the packaging development process [9]. Considerations of underlying aspects such as cost and lead-time aspects for each stage are absent. Neither supply chain and logistics considerations nor their associated costs are included in her reasoning to obtain a packaging solution. [8] claimed that the integrated processes had potential to enhance the utilization of resources, however, with regards to what resources and from what aspects are not elaborated on. In addition, [15] argued that an ultimate product and packaging system meets the demands on transport, handling and storage, however, the perspective of the demands are not clear. According to [4], few packaging are selected based on where and how the packaging is handled. Results from the [10] study discussed practitioners’ views of the processes used for packaging selection and indicated that the employment of an integrated product and packaging development process at manufacturing companies reduced costs. The empirical findings that packaging suppliers are involved after the manufacturing companies have decided on a PPS, are discussed

by [9]. This time of involvement is not in line with the theoretical rationales and benefits of a concurrent packaging and product development process discussed by [6,9]. [16] addressed the aspect of sub-optimization of functional areas: “If logistics were involved earlier, it would be much easier to make cost trade-off decisions between the logistics implication of a particular design.” The system-wide assessment of the trade-offs brought about by logistical and packaging activities are emphasized by [1]. A packaging that is incompatible with its product and encountered environment in terms of poor adjustment and insufficient protection causes consequenses such as poor filling rates and product damages, all of which have economical and environmental impacts on individual activities as well as on the overall supply chain. [16] provide illustrative examples of incompability. For the selection of industrial packaging [1] addressed consideration to efficient use of materials, low environmental impact, and product protection. However, compatibility with the encountered environment was not stressed in relation to the selection. 3 3.1

METHODOLOGY Research methodology

Case studies were used to gain insight into the industrial packaging suppliers’ processes and driving forces. This approach was selected given the scarcity of theory elucidating these processes in the literature. This gap in insight gave rise to research questions of an explorative nature and the decision to apply a case study approach with multiple cases. It was felt that such an approach would best answer the two research questions, since the case study approach is advocated when the present theory is insufficient or when a research field is new [17]. Case studies are highly suitable when the research focuses on contemporary phenomena in its real-life contexts, and when the boundary between the context and the phenomena is uncertain as [18] maintains. These circumstances are true for the processes investigated in this study. In order to answer the RQs empirical data was collected from three major packaging suppliers that offer industrial packaging on a global scale. It was carried out by the use of semi-structured interviews, secondary data (internal documents), and observations (field trips), which enabled validation through triangulation. There was a total of nine interviewees: four from Company A, two from Company B, and three from Company C. After completing the data collection, the interviews were transcribed and data analysis was carried out. Analysis was performed in line with [19] open coding and relational analysis. An inductive influenced research approach was used to investigate the processes and rationales behind the industrial packaging selection process. The case sampling was based on the desire to include packaging suppliers offering one-way packaging solutions, returnable packaging solutions, and both kinds of packaging solutions. This particular sample selection was selected to give insights into the reasoning behind diverse packaging selection processes. To ensure and evaluate the quality, relevance, and rigor as well as the reporting of the study per se, the author has striven to consider the framework developed by [20]. 3.2

Case descriptions

This section presents the characteristics and activities of the three participating case companies. Case Context Company A Case Company A provides traded products (i.e. packaging commoditites) and company designed products (i.e. tailored packaging). The company has grown from a local packaging

Sustainability in Manufacturing supplier to its current position as a global supplier to manufacturing companies. Company A has an abundant number of material suppliers spread around the world and its customers represent manufacturing companies active in most market segments such as automotive, electronics, apparel, and third-party logistics firms. Its design center is located in Scandinavia. Company A’s major strength is in its competence to develop highly specific customer tailored packaging solution. The offering of generic packaging solutions is limited. The packaging solutions offered are one-way and returnable B2B packaging solutions. Its packaging solutions are employed in the customers’ inbound flow of small items and outbound flow of larger processed items. Case Context Company B Case Company B provides returnable business-to-business packaging solutions to a number of different markets such as automobile, food and beverage producers, apparel industry, and delivery firms. It has its own design center located in Europe. Company B advocates that its deep knowledge of packagingrelated issues in numerous markets enables cross-fertilization and thus gives it a competitive advantage. Its packaging solutions are used for inbound transports, for example deliveries between the customers’ component supplier (tier 1 supplier) to its customer’s production plant. The packaging solutions provided by Company B are also frequently used for outbound transports, for example from distribution center to retailer. Case Context Company C Case Company C is a global market leader in its segment of packing solutions. The company provides business-to-business and sales packaging. Company C sells almost exclusively one-way packaging. Its customers and their products operate on a variety of markets, including food producers (B2C), appliances (B2C), and heavy industry (B2B). Often the industrial packaging has dual functions and is also used as sales packaging. The trend is towards sales packaging since the transport packaging is assigned a dual function in terms of fulfilling marketing and protective purposes. 4

RESULTS

The following section provides answers to the first research question: What processes and rationales are used when packaging suppliers suggest an industrial packaging solution? The answers to the second research question, What is the nature of the ongoing dialogue and the state of involvement between the industrial packaging suppliers and the manufacturing companies to arrive at a satisfactory packaging solution? are dealt with in 4.2. 4.1

Process mapping of the logistics flow

The particular activities observed in the process mapping for each of the industrial packaging supplier are presented in Table 1. The processes for finding an industrial packaging for a new product introduction or an existing product are not separated in this study. Company A Upon a request to find a packaging solution for a customer’s product, the approach is to identify the perceived needs or problems. This is followed by collection of facts by means of process mapping and assessment of the existing characteristics of the product to be packed and the PPS’s encounters and setups that are affected by the industrial packaging set-up. Aspects that include the PPS encounters and set-up are conditions during transport and handling (i.e., supply chain data collection). The more specific information the customer provides, the better the packaging solution. Following the mapping of customer information and an understanding at Company A for the current PPS set-up

231 (see Table 1 for investigated aspects) Company A contrasts the processes activities and associated costs with potential PPS setups that would mitigate the identified cost drivers. Company A experiences that its customers are often not in control of the costs of transport that arise due to packaging. Thus, the reduction of transport volumes, a concrete measure that implies reduction of the costs, is especially addressed by Company A. By means of the financial assessment cost drivers and potential cost reductions are identified, a final PSS set-up proposal is presented and further refinements of the solution are discussed with the packaging technician at Company A. The information provided by the producing company and the professional experience of the sales person directs him or her in the direction of one-way or returnable packaging. In those cases where the choice between a returnable and one-way PPS set-up is uncertain, the results of the logistics cost analysis displays the break-even point for the two set-ups and enables a factually based selection. In addition to the logistics cost analysis, Company A wishes to depict environmental savings in the processes of developing an industrial packaging explicitly for its customers. This is to be done by the use of an environmental tool that enables calculations of the amount of carbon dioxide emissions in relation to the different packaging solutions and their associated activities. The implementation of this system is meant to give the customer facts in order to make a conscious decision. The decision on a generic versus tailored industrial packaging is largely determined by the cost of constructing and manufacturing. From a Company A point of view the potential industrial packaging ought to be cost effective from the standpoints of the manufacturing per se, transport and handling. Employment of the logistics cost analysis includes these activities with associated costs. A number of 500 packing items is considered a large order and hence warrants a tailored packaging solution. Company B Company B’s efforts are initiated by identifying the problem or a changed/new flow and the associated causes and effects that the customer experiences. The company typically found that the customer’s description of the problem is most often not as comprehensive as needed for full insight and/or includes less relevant aspects. Hence, the information is extracted that is considered important. If needed, additional information is collected by Company B in order to understand the parts of the customer’s supply chain through which the PPS will pass. The information collected by Company B is classified in two categories; characteristics of the product to be packaged and flow analysis of the prevailing PSS encounters and operational activities. Company B often assesses and evaluates the existing activities in the supply chain by on-site observations. In the logistics cost analysis two or more PPS set-ups are scrutinized and compared to demonstrate the most profitable PPS. From a profitability point of view in terms of the operational activities mapped, either returnable set-ups with different features are compared with each other or a returnable and a one-way set-up is compared. Company B stresses that the customer is often not aware of the pay-off time and initial investment of the prevailing PPS. Going further into details, the process mapping of the flow analysis identifies the activities occurring at each supply chain actor. Subsequently, by means of a logistics cost analysis, the costs each activity incurs are identified and appraised. The costs for the same types of activities are aggregated and placed in the specific cost pools of operational cost, cost of handling, fixed costs, technical cost, and economical cost. The process mapping and the data on the product make up the basis for constructing and suggesting a first packaging solution to the customers. Further dialogue between the packaging supplier and the customer that

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result in the final PSS decision is described in 4.2. Company B stresses that customers often keep track of the costs of material and transport but lack knowledge on the costs of handling. The production tool needed for a new packaging solution consumes considerable resources in terms of initial investments and a long lead time. If the product to be packaged and its supply chain require extensive transport protection, the machinery for a new tool is invested in. On the other hand, if the product to be packed allows, Company B directs its customers to already existing packaging solutions enabling financial leverage. Additionally, evaluations of the needed annual amount of industrial packaging guide in the direction of generic or tailored industrial packaging. Company C Company C provides industrial packaging which often is synonymous with sales packaging, that is, the same packaging is used for transport as well as for display at the retailer. This combined field of use puts additional conditions on the packaging in terms of marketing features (graphics, information, etc.) and product protection. To succeed in developing a satisfying packaging solution, the customer has to reveal the goal for which it is striving for. Company C collects characteristics of the product to be packaged, maps information about its market place, and information on its supply chain from the origin to point of delivery with an emphasis on the functional areas at the customer company that are affected by the PPS set-up. Table 1 presents data collected about the product and information about the activities concerning the mapping of the supply chain set-up. The development of a packaging solution is partly dependent on the activities that emanate from the different functional areas in the customer company, (i.e., production, construction, logistics, marketing, and sourcing). Trade-offs of the activities serve as the basis for a proposed packaging solution (see more on this in 4.2). Hence, the packaging selection is based on function versus cost. Company C argues that the process of investigating and evaluating the prevailing packaging solution is an iterative process, and thus is after some time reinitiated. For Company C to meet its customers’ expectations, needs, and requirements and yet be cost effective, a tailored industrial packaging solution is considered the appropriate route. For a generic packaging solution the service dimension and tailored competence is somewhat lost. The annual amount and demand for industrial packaging determines whether a generic or tailored industrial packaging is ordered. An edition of 500 industrial packaging items per annum is considered a low number and the tailored packaging solution design may be too costly.

Product information Type of product Weight Dimensions Sensitive features Scratches Bumps Static electricity Mapping of supply chain Market Characteristics Type of market Market analysis Competitor analysis General Process Characteristics Overall mapping of SC activities Product encounters along SC

A X X X

COMPANY B X X X

X X X

X X X

C X X X X

X X

No. of items per packaging No. of packaging annually Project duration Savings post project Returnable packaging Initial investment Cycle time Cleaning Pay-off time Technical life expectancy Dim. of packaging solution Collapsible property Non-collapsible property Volume of return transport Moist milieu Transportation Mode of transport Filling rate Transport distance Transportation duration Cost due to packaging weight Dim. of transport vehicle Cost of transport Packaging pattern Third party logistics provider Handling Unfolding Filling/Packing Human Automatic Transporter Transhipment Distribution center Unpacking Human Automatic

X

X X

X X X X X X X X X X X X X X X

X X X X X

X X

X X

X X

X X X X X

X

X X X X

X X X X X X X

X X X X X X X X

X X

X X

X

X X X

X

X X X

X X

X X

X X X X X X X X

End of life Sales packaging Visual exposure Information Differentiated features

X X X

Table 1: A summary of the product characteristics and mapping of supply chain activities and parameters. 4.2

X X X

X

Unique characteristics Origin & Destination Packaging solution Mending Dim.of existing packaging Thickness of walls Volume Length/height/depth

The supplier involvement

–

customer

dialogue

and

phase

of

All case suppliers stress the need for a close and continuous dialogue with the customers for a successful PPS set-up. Additionally, all three suppliers emphasis the benefits of letting their competences work out a packaging solution in parallel with the construction of the product to be packaged, or at least before the intended date of launching the product. Often the customer companies provide specification of requirements of the product to be packaged and if there is a need of complementary data, the

Sustainability in Manufacturing packaging suppliers gather this. The more restrictions they are given, the less creative they can be. Company A Given the diversity of Company A’s customers and each product’s individual demands on its packaging solutions, an individual set of information is needed to serve these demands. The main orders at Company A are for tailored packaging solutions. To be able to construct a tailored solution the information provided by the customer needs to be comprehensive. Company A stresses that in cases where the customer does not provide the necessary information, the packaging supplier possesses skills and experience to estimate plausible parameters. However, lack of correct data extends the lead time. Often, the different functional areas at Company A discuss with the corresponding functions at the customer company. This approach reduces misunderstandings since there are no intermediaries. In this way, the response is immediate and the lead time decreases. Company A would like to be involved in collaboration with the customer company’s construction department at an early stage. Improvident orders may impose higher costs than necessary, particularly when there is a need for an advanced packaging solution and the material used is traded. Company B During the ongoing dialogue between the customer and Company B, the supply chain mapping falls into place piece by piece. In discussion between the two parties about concrete packaging solutions and their feasibility with the supply chain, light is shed on additional aspects that have not been taken into account earlier. This case often appears since the professionals working with them consider the PPS set-up to be general and well known and thus taken for granted. Further discussion and refinement of the packaging solutions enables a better degree of accuracy and finally the optimal packaging solution is identified. In case of insufficient information from the customer, Company B feels that the experience from diverse business areas many times enables them to make reasonable and often surprisingly accurate assessments and estimates of costs of supply chain activities. Additionally, Company B often experiences that the contact person at the customer company is not the correct one. The person shares the basic information about the product, but often lacks the logistics aspects. Company B is aware that the customer company’s sourcing function often terminates the business opportunity based on price arguments, even though the collaboration has proved to be fruitful. Company B is often involved late in the customers’ production phases, though more and more companies have realized the benefits of involving the packaging supplier early on in the chain to enable optimization of transports, production etc. Company C To open up for contemplation and to direct focus away from the cost of investment of the packaging in the customer company’s sourcing function, Company C has a tradition of actively involving the different functional areas of production, design, logistics, marketing, and sourcing in the customer company. In doing so, the needs and requirements of each of the functions are emphasized. By making the costs that are incurred along the supply chain activities visible during the conditions of different packaging systems, people in the sourcing function become aware that escalated costs for some activities result in reduced costs elsewhere in the supply chain, and that the total sum ends up lower than for the current packaging. According to Company C, this approach achieves the most optimal packaging solution based on the trade-offs of the different functions’ requirements and needs.

233 Company C perceives that the interest in largely involving the packaging supplier in the process has grown. Yet, the most common case is that the customer companies come to realize a need for packaging after the product has been developed. 5 5.1

DISCUSSION Process mapping at the packaging suppliers

In accordance with [9], the findings of this study identified that the packaging suppliers do not acknowledge the use of theoretical packaging development and selection processes. Instead, their experience provides good guidance on how to progress in the process of developing packaging solutions for customer satisfaction. Judging from the findings from the three packaging suppliers, there are differences in the way of mapping the supply chain activities. The companies provided different levels of details on the mapping of the supply chain (Table 1). In line with [13,14], all three packaging suppliers use the process mapping technique to comprehend interactions and relationships between the activities of different functional areas. All three packaging suppliers focus on the aspects of costs in the mapping, though from different angles. The desired output result is common for all three companies; to cut the customers’ direct and associated packaging costs as regards the supply chain activities. The need for the logistics cost analyses seem to originate from the lack of knowledge at the customer companies on what drives costs. This finding is in accordance with what [4] addressed. Company B categorizes different activities and associated costs. These costs are interpreted as being linked to different functional areas for the use of a particular PPS set-up. Company C employs a somewhat different approach in that the compromises agreed on between the different functional areas are the foundation for the packaging selection. Comparison of the current PPS set-up to a potential one suggested by the packaging supplier is the main focus in the three industrial packaging suppliers’ mapping processes. The rationale to involve supply chain actors, that are affected by the packaging in the packaging decision is in line with [1]. As found in the study, when there is an uncertainty whether to select one-way or returnable packaging, the output of the logistics cost analyses at Company A and B display the break-even point for the two alternatives. Except for the analysis of the cost driven activities the selection of one-way or returnable industrial packaging may be influenced by other driving forces, such as what set-up is most cost effective and profitable from a packaging supplier’s production point of view. None of the industrial packaging suppliers claim to be purely a provider of commodities, but of tailored packaging solutions. All suppliers stress that their added value comes with a tailored packaging solution and not with a commodity. The cost of construction, manufacture, and the requirements of the product to be packed partly determine whether a tailored or generic industrial packaging is to be used. It is constantly a matter of function versus cost. The three packaging suppliers can be split in two groups that represent differences in the opinion on what quantities of packaging items justify scale of economy. Interestingly, the sales packaging perspective at Company C clearly distinguishes itself from the industrial perspective at Company A. Company B indicates the same stance as Company A. Hence, it can be assumed that the cost level for developing an industrial packaging is higher per item than for developing a sales packaging. 5.2

Intercompany dialogue and involvement

Regarding the engagement of different functional areas in the development of an industrial packaging, Company B seems to have a reactive approach, Company C a proactive approach and

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Company A somewhere in between. The findings of [9] that the manufacturing company decides on the PSS and then involves the packaging supplier do not correspond to the findings of this study. Rather, depending on the degree of advancement of the packaging function at the customer, there is a continuum of information given by the customer. An advanced packaging function might provide a well-specified order and the need for the suppliers’ investigative competence is outplayed. At the other end of the spectrum, customers are found that possess little knowledge in packaging matters and rely on the packaging supplier to provide all input. The intercompany priorities and commitment to packaging, and the priority of its function often reflects the knowledge of packaging professionals dealing with the packaging suppliers and the level of existence of a logistics organization advanced in packaging matters. Companies A and B explicitly argue that not too seldom the contact person at the customer company lacks adequate and necessary insight to provide the answers needed. Often purchasers are asked to arrange for an industrial packaging solution; this experience is supported by [4]. The purchaser focuses on what suppliers qualify, but do not have skills in trade-offs that come with the different PPSs offered by different suppliers. The price of the packaging solution is often why the business opportunity fails; companies do not look for trade-offs in different areas. All case companies claim that their involvement early on in the development of the product is cost beneficial especially as regards the utilization of resources. This is in coherence with the findings of [8] that argued that an integrated product and packaging development process would increase resource utilization Company B expresses that one way to ensure early involvement is by building relations and trust. The manufacturing customer’s insight into the positive supply chain effects that come with the collaboration of the packaging and product development functions is supported by [6]. 6

CONCLUSIONS AND FURTHER RESEARCH

The lack of a PPS set-up perspective at the customer companies, in addition to the mindset of the function of the packaging and the importance of its impact, seem to play a role in the priorities of the packaging skills at the manufacturing company. How important is it to have a fully compatible PPS? The industrial packaging suppliers must ask the right questions to find out all the relevant conditions, to be able to design a packaging that satisfies all the needs for the intended encounters and activities in the flow. The data collection would speed up and be facilitated if the customer companies prioritize having people and functions with the right competence engaged in the work. Management needs to ensure that competent staff is dealing with packaging requirements and the dialogue with the packaging supplier. Otherwise, lead time and costs increase. Manufacturing companies that view packaging and the packaging selection as prerequisites to manage to get their products to the right place, in the right time, in the right condition, and at the right price, open the door to potential cost savings. For further research it would be interesting to investigate which function influences the industrial packaging selection the most. According to [21], the sales packaging decision is mostly influenced by the marketing function. Regarding the industrial packaging decisions, however, this study indicates that the opinion of the sourcing function seems to carry the main weight. If this is the case, is that the adequate way? 7

ACKNOWLEDGEMENTS

The author wishes to genuinely thank the participating case companies, the supervisors, and Vinnova, the Swedish Governmental Agency for Innovation Systems for funding.

8

REFERENCES

[1]

Verghese, K. and Lewis, H. (2007): Environmental innovation in industrial packaging: a supply chain approach, Int’l. Journal of Production Research, 45:18, 4381-4401.

[2]

Stahre, F. (1996): Små returlastbärare i logistikkedjorinförande och effekter, Licentiate Thesis, Linkoping University, Sweden.

[3]

Saghir, M. (2004): A platform for packaging logistics, Doctoral Thesis, Lund University, Sweden.

[4]

Johnsson, M. (1998): Packaging Logistics – a value added approach, Doctoral Thesis, Lund University, Sweden.

[5]

Sonneveld, K. et al. (2005): Sustainable Packaging: How do we Define and Measure It?, 22nd IAPRI Symposium, pp. 1-9, São Paulo, Brazil.

[6]

Klevås, J. (2005): On opportunities of integrated packaging, logistics and product development – Experiences from a case study at IKEA, Licentiate Thesis, Lund University, Sweden.

[7]

Bjöörn, U. (2008): Integrating Packaging and Logistics in Industrial Development, Licentiate Thesis, Lund University, Sweden.

[8]

Bramklev, C. (2003): Concurrent Development of Product and Packaging - towards an integrated development procedure, Licentiate Thesis, Lund University, Sweden.

[9]

Bramklev, C. (2009): On a Proposal for a Generic Package Development Process, Packaging Technology and Science, 22, pp. 171-186.

[10]

Silgård Casell, S. (2010): The Packaging Selection Practicea case study, NOFOMA proceedings 2010, pp.761-776, Kolding, Denmark.

[11]

Jönson, G. (2006): Packaging Technology for the Logistician, 3rd ed., Lund University, Sweden.

[12]

Argent, D. (2007): Mapping the process, Paper, Film & Foil Converter, Vol. 81, No. 6.

[13]

Pojasek, R. B. (2005): Understanding processes with hierarchical process mapping, Environmental Quality Management, Vol. 15, No. 2, pp. 79-86.

[14]

Ljungberg, A. and Larsson, E. (2001): Processbaserad verksamhetsutveckling, Studentlitteratur, Lund, Sweden.

[15]

Bramklev, C. (2007): Towards Integrated Product and Package Development, Doctoral Thesis, Lund University, Sweden.

[16]

Zacharia, Z.G. and Mentzer, J.T. (2007): The role of logistics in new product development, Journal of Business Logistics, 28, (1), 83-VI.

[17]

Eisenhardt, K. (1989): Building Theories from Case Study Research, Academy of Mgmt Review, 14, (4), pp. 532-550

[18]

Yin, R. K (2003): Case study research: design and methods, 3rd ed., Sage Publications, Thousand Oaks, CA.

[19]

Corbin, J. and Strauss, A. (2008): Basics of Qualitative Research, 3rd ed., Sage Publications, Thousand Oaks, CA.

[20]

Olander-Roese, M., Lindh, H., and Silgård Casell, S. (2009): Towards Improved Reporting of Case Study Research-An evaluation of articles in top tier logistics and management journals, NOFOMA proceedings 2009, pp. 615-633, Jonkoping, Sweden.

[21]

Prendergast, G. and Pitt, L. (1996): Packaging, marketing, logistics and the environment: are there trade-offs?, Int. J. of Phys. Distr. & Log. Mgmt., Vol. 26, No. 6, pp. 60-72.

Applying Functionally Graded Materials by Laser Cladding: a cost-effective way to improve the Lifetime of Die-Casting Dies 1

1

1

2

2

Sebastian Müller , Helge Pries , Klaus Dilger , Sörn Ocylok , Andreas Weisheit , Ingomar Kelbassa 1

3

Institute of Joining and Welding, Technische Universität Braunschweig, Braunschweig, Germany 2 3

Fraunhofer Institute for Laser Technology ILT, Aachen, Germany

RWTH Aachen University, Chair for Laser Technology, Aachen, Germany

Abstract The lifetime and economic methods of improving the lifetime of a die-casting die are key factors for the die-casting industry since the global competition and the competition with other production techniques have increased significantly. The article depicts the approach, technical realization, latest results and process limitations of the INNOGRAD research project. Here, powder-based laser-cladding is applied to combine two materials as a functionally graded material. By applying gradient structures it is possible to fit the material to the predominant type of exposure, resulting in an increase in the lifetime of die-casting dies. Keywords: Graded Material; Laser Cladding; Die-Casting

1

INTRODUCTION

Pressure die-casting is a cost-efficient technology for the massproduction of aluminum components and has experienced growing application over the last two decades. At present, the manufacturing process plays an important role for the development of weightreduced parts for the automotive industry. Parts, produced by high pressure die-casting are mostly characterized by a wide area of application and high integration functionality. At present, the die-casting industry is subjected to strong cost pressure, due to a highly competitive environment. To ensure the role as a widely-used manufacturing process in the upcoming decades, the high-pressure die-casting industry must further meet the challenges of an increasing competition with other manufacturing techniques. In this context, the lifetime of the diecasting die has an important influence on the competitiveness of the die-casting industry, since this is directly related to the manufacturing costs. Up to 50 % of these costs are spent on production, maintenance and repair of the die-casting die. This has led to an increasing interest in optimizing the lifetime of a diecasting die. Numerous efforts were made in order to enhance the lifetime of these tools. Special grades, tailored to the predominant failure mode of die-casting dies have been developed. However, these materials are cost-intensive because of the higher amount of alloy elements and/or advanced refining technologies (e. g. electro slag remelting). Another approach is the improvement of welding technology in order to achieve a high quality repair welding. Due to process limitations of conventional welding processes (e. g. TIG welding) welded areas often exhibit poor material quality. Applying functionally graded materials by laser cladding enables the combination of materials designed for a specific wear pattern with a smooth transition between base material and coating. In respect of this technology, materials can be applied which exhibit a distinguished high-temperature strength at layers close to the surface and fracture toughness at layers beneath the surface.

2

BASICS

2.1

Laser cladding process

The laser cladding process is a powder-based application to build up 3D parts layer by layer. The powder can be fed either off-axially or coaxially. Figure 1 (b) shows a discontinuous coaxial powder feed nozzle used for the experiments. Three individual powder gas streams are fed into a powder gas stream focus on the surface of the substrate [1].

Figure 1: Principle of laser cladding process (a); discontinuous coaxial-powder feeding (b). The powder is fed to the interaction zone by a carrier gas stream (helium or argon). The laser beam melts the powder material particles and a thin layer of the base material. After solidification, a layer with a metallurgical bonding to the substrate is produced. By adaption of the process parameters such as velocity, powder feed rate and laser power, the thickness of the built layer can be varied typically from 0.1 up to 3 mm in a single pass. With multi-layer cladding, thicker layers can be produced. This method is used for the production of graded layers. The main advantages of the laser cladding process are high precision, a minimized heat affected zone (HAZ), low distortion of the base material and the variety of materials [2]. Nearly every metallic material can be cladded. Low melting alloys based on aluminum can be used as well as cobalt-, nickel- or titanium-based alloys, intermetallics (e. g. titanium aluminide) and high melting point metals, such as tungsten.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_41, © Springer-Verlag Berlin Heidelberg 2011

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236 2.2

Sustainability in Manufacturing Predominant failure modes of a die-casting die

In order to improve the lifetime of a die-casting die and to carry out repair welding works qualitatively, it is essential to know the predominant failure modes and their effect on the tool surface. Tools used for die-casting dies are subjected to high cyclic temperatures and mechanical loads. The high thermal loading of the die surface leads to a degradation of hardness and strength of the material [3]. Heating and cooling cycles cause thermal expansion and contraction of the material, generating strain fields which lead to a significant plastic deformation. The exceeding or accumulation of plastic deformation leads to failures at the surface of the die-casting die. The resulting failure modes are called heat checking and gross cracking [4]. Gross cracking is the result of a groove in the material. The groove can result from the geometrical shape of the tool surface or from the metallurgy of the material (e. g. segregation) [5]. The predominant case in die-casting applications is gross cracking, resulting from small radii, as shown in Figure 2 (a). Local stress exceeds the strength of the material; a total failure of the material is the result in these areas. Due to stress relief, only single cracks occur in critical regions. However, these cracks are relatively long and have a high crack propagation velocity.

The research project started with a review of boundary conditions for functionally graded materials. As a main outcome of phase one, a list of adequate materials is generated. The materials shall possess at least one mechanical property which exceeds the performance of conventional tool steels (e. g. the yield strength at elevated temperatures, fracture toughness, hot wear resistance). Phase 2 started with basic simulations and the production of onedimensional functionally graded materials. Subsequently, investigations took place in order to characterize the microstructure and the mechanical properties of the functionally graded material. Phase 3 contains thermal fatigues tests with selected material combinations. With the results of these experiments, it can be focused on promising material combinations and the risk of total failure in real die-casting dies is further minimized. In the final phase 4, long-term tests on die-casting dies are conducted.

Heat checking can be found in areas with a high thermal load. Here, the resulting strain fields at the surface lead to a fatigue of the material instead of exceeding the strength. Since the load is applied to a larger area, the amount of cracks is higher. Cracks, resulting from heat checking have a shorter crack length. Figure 2 (b) shows the surface degradation resulting from heat checking after 8500 cycles. The material, displayed in both figures is a 1.2343 (AISI H11) in a heat-treated condition.

Figure 2: Cross section of gross cracking (a) and heat checking (b) failure mechanism at the die-casting tool surface. Another failure mode is the degradation of tool surface due to abrasive wear mechanism. Here, fractions of particles in the melt mainly silicon - cause a wear of the tool surface. This failure mode occurs especially in ingate areas of the die-casting die, since there is the highest velocity and pressure of the melt. If a repair welding is requested, the described failure modes mean different challenges in the selection of materials and welding preparation. Gross cracking sections require a material with high ductility and fracture toughness for stress relief and low crack propagation rates. Areas, exposed to heat checking require a material with a high strength at elevated temperatures in combination with an adequate ductility and fracture toughness. 3 3.1

THE INNOGRAD RESEARCH PROJECT Aim and approach of the research project

The main goal of the INNOGRAD research project is improving the lifetime of die-casting dies by applying functionally graded materials to die-casting dies. The research project began in January 2008 and will take three years. Figure 3 depicts the four phases of the research project and the participating industrial companies.

Figure 3: Procedure of the INNOGRAD research project.

3.2

Potential of laser cladding with respect to time saving and cost reduction

Figure 4 depicts the procedures for a conventional tool manufacturing process and for an alternative manufacturing process, employing laser cladding. Considering the differences between both manufacturing processes, it becomes obvious that the alternative manufacturing process lacks four cost- and timeintensive steps: the production of raw steel blocks, rough machining, stress relieving and semifinish machining. The alternative manufacturing process, however, adds two additional steps: the machining of degenerated surfaces and the application of functionally graded materials by laser cladding. A tempering is appropriate in order to relieve weld residual stresses [6]. Unlike the heat treatment of the conventional production process, only one tempering is necessary.

Sustainability in Manufacturing

237 3.4

Build-up process of graded material by laser cladding

For building up graded layers, two different powders are fed simultaneously into the interaction zone, where both are melted by the laser radiation. The alloy composition of the solidified layer is a mixture of both materials. By changing the powder feed rates stepby-step, a smooth transition from one component to the other can be achieved. Here, Figure 5 serves to visualize the build-up process of functionally graded materials [1].

Figure 5: Schematic drawing of the build-up of graded layers. 4 4.1

RESULTS Metallographic results

During all steps of the experiments, the quality of the processed graded materials is investigated by various methods. The first step is the characterization of the microstructure by optical microscopy to ensure that the cladded layers are assembled without any cracks and only low porosity. Figure 4: Comparison of manufacturing processes. 3.3

Functionally graded materials for die-casting applications

Materials, designed for die-casting applications should exhibit the following properties: a high toughness and ductility in all regions, a high strength at elevated temperatures and a high resistance against tempering [3]. However, materials designed for a high strength often lack an adequate toughness and ductility. Conversely, materials with a high toughness and ductility are not able to achieve a high strength at elevated temperatures.

Figure 6 shows the combination of Marlok and Dievar in a onedimensional gradient. The gradient structure, mentioned in Figure 5, becomes visible in this cross section. The gradient structure exhibits a very low porosity and no cracks.

Thus, when designing a functionally graded material for die-casting applications, the idea is to combine materials with a high resistance against heat checking with materials, exhibiting a high toughness and ductility. Considering these boundary conditions, the use of a martensitic chromium hot work tool steel (Uddeholm designation DIEVAR) and a nickel maraging steel (Metso designation MARLOK) turns out to be a promising combination for die-casting applications. The DIEVAR material is designed and has been proven to exceed the properties of standard martensitic hot work tool steels as regards heat checking and gross cracking resistance [7]. Hence, it is predestined to serve as the outer layer of a functionally graded material. The MARLOK material is characterized by excellent fracture toughness, good strength at elevated temperatures and a good weldability [8]. In respect of its high fracture toughness, this material serves as the buffer layer between the top layers of DIEVAR and the base material (AISI H11). The following Table 1 provides the alloy composition of the two special grades and the alloy composition of the base material. material

Cr

C

Mo

Si

Ni

Co

Fe

Ti

V

Mn

1.2343

5,0

0,4

1,3

1,0

-

-

base

-

0,4

0,4

Dievar

5,0

0,4

2,3

0,2

-

-

base

-

0,6

0,5

Marlok

0,3 0,01 4,5

-

0,1

0,1 14,0 10,5 base 0,2

Table 1: Alloy composition of selected materials.

Figure 6: Cross section of one-dimensional gradient. After having assured the quality of the microstructure, the next step is the characterization of hardness. In order to get a twodimensional information of the hardness distribution, the ultrasonic contact impedance (UCI) hardness testing method is used. Figure 7 shows the two-dimensional hardness distribution before the heat treatment. The hardness of the base material is about 450 - 500 HV 1, which is a typical value for die-casting dies. At the transition between the base material and the buffer layer, the heataffected zone (HAZ) becomes visible. For a length of about 400 µm, the hardness rises up to 600 - 650 HV 1. This hardness increase is not critical since the area is located far from stressed regions at the tool surface. The following three buffer layers consisting of Marlok have a hardness of about 400 - 450 HV 1. The material is in a stage

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between a soft annealed condition (hardness would be in a range of 300 - 350 HV 1) and a precipitation-annealed condition. The three buffer layers are followed by four transition layers with a composition, mentioned in Figure 5. A slight gradient in hardness becomes visible here, resulting in a final hardness of about 600 650 HV 1 at the tool surface. The areas of a higher hardness at the surface result from boundary effects and can be neglected.

Figure 9: Stress-strain curves for distinguished die materials. Figure 7: Two-dimensional hardness distribution of a functionally graded material without heat treatment. Figure 8 depicts the hardness distribution of the same gradient structure after a heat treatment for two hours at a temperature of 580 °C. The heat treatment did not affect the hardness of the base material, which is essential in order to maintain its mechanical properties. The buffer layer is in a precipitation-annealed stage, resulting in a hardness of about 500 - 550 HV 1. The hardness of the three top layers is not affected.

5

SUMMARY

It has been shown that it is technically feasible to apply functionally graded materials by laser cladding. Graded layers were built up with a smooth transition of composition, only low porosity and without any cracks. The mechanical properties of the gradient materials are superior in comparison to the conventional base material. A wide amount of different materials can be processed, since the metal powder is manufactured by gas-atomizing conventional materials. Hence, this production technology is also sensible for other fields of application like cutting tools, forging tools or tools for continuing casting processes. However, due to the limited application rate of the laser cladding process, this application is predestinated for rather small volumes. Applying functionally graded materials by laser cladding bears the potential of contributing significantly to cost savings in terms of tool manufacturing. This derives from two aspects: the higher lifetime of die-casting tools and savings, resulting from a shortened manufacturing process.

Figure 8: Two-dimensional hardness distribution of a functionally graded material after heat treatment. 4.2

Mechanical properties

Test specimens have been prepared in order to characterize the mechanical properties of the material. These experiments have been conducted with different materials and temperatures. The geometry of the test specimens is according to DIN 10002 and the test specimens have undergone the same heat treatment for two hours at 580 °C prior to testing. First, tensile tests of the basic materials have been conducted in order to gain knowledge about the mechanical properties of the top layer and buffer layer structures. Moreover, in an advanced phase of the research project, temperature-dependent tensile tests of gradient structures have been conducted in order to reveal the mechanical properties of gradient materials. Figure 9 depicts the stress-strain curve of the base material 1.2343 (heat-treated condition) and two gradient materials, detailed previously. It becomes visible that the DIEVAR material considerably exceeds the yield strength, the ultimate strength and fracture elongation of the base material. The precipitation-hardened MARLOK material slightly exceeds the yield strength and the ultimate strength of the base material. However, it significantly exceeds the fracture elongation of both materials and thus proves its qualification as a buffer layer material.

Future activities of this research project will be concerned with the advanced application of graded layers on real die casting tools and its evaluation under operating conditions. 6

ACKNOWLEDGMENTS

The authors would like to thank the Federal Ministry for Economics and Technology (project no. 16IN0598) for funding this research project. 7

REFERENCES

[1]

Ocylok, S.; Weisheit, A.; Kelbassa, I. (2010): Functionally graded multi-layers by laser cladding for increased wear and corrosion protection, in: Physics Procedia 5, pp. 359-367.

[2]

Vedani, M. (2004): Microstructural evolution of tool steels after Nd-YAG laser repair welding, in: Journal of Materials Science, Vol. 39, pp. 241-249.

[3]

Klobcar, D.; Tusek, J.; Taljat, B. (2008): Thermal fatigue of materials for die-casting tooling, in: Materials Science and Engineering A, Vol. 472, pp. 198-207.

[4]

Sjöström, J.; Bergström, J. (2004): Thermal fatigue testing of chromium martensitic hot-work tool steel after different austenitizing treatments, in: Journals of Materials Processing Technology, Vol. 153-154, pp. 1089-1096.

Sustainability in Manufacturing [5]

Müller, S.; Pries, H.; Dilger, K. (2010): Standzeiterhöhung von Druckgießformen durch Gradientenwerkstoffe, in: Assistentenseminar Fügetechnik und Schweißtechnik, Vol. 268, pp. 49-53.

[6]

Grum, J.; Žnidaršič, M. (2006): Residual stess analysis after laser surface alloying with various powdered materials, in: International Journal of Microstructure and Materials Properties, Vol. 1, No. 2, pp. 219-230.

[7]

Liluashvili, Z.; Pries, H.; Dilger, K. (2008): Untersuchungen zur Standzeitoptimierung von Aluminium-Druckgießformen, in: Schlussbericht AiF 14389 N, p. 139.

[8]

Klobcar, D.; Tusek, J.; Taljat, B.; Kosec, L.; Pleterski, M. (2008): Aging of maraging steel welds during aluminium alloy die casting, in: Computational Materials Science, Vol. 44, pp. 515-522.

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A Total Life-Cycle Approach towards Developing Product Metrics for Sustainable Manufacturing 1

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2

Ankur Gupta , Anshu Dhar Jayal , Michela Chimienti , I. S. Jawahir 1

1

Institute for Sustainable Manufacturing, and Department of Mechanical Engineering, University of Kentucky, Lexington, KY, USA 2

Department of Mechanical and Management Engineering, Polytechnic of Bari, Bari, Italy

Abstract This paper presents a total life-cycle approach towards developing comprehensive product metrics for sustainable manufacturing including the triple bottom line: environment, economy and society. The developed generic metrics are grouped under different metrics clusters, and are categorized across the four life-cycle stages (pre-manufacturing, manufacturing, use and post-use) of a product. This gives an opportunity to develop a leveling system for the metrics based on the presence of different metrics across multiple life-cycle stages. The development and deployment of relevant product metrics ontology is shown as a prerequisite for the ultimate evaluation and improvement in product design for sustainable manufacturing. Keywords: Product Life-Cycle; Sustainable Manufacturing; Product Metrics Ontology

1

INTRODUCTION

Sustainable products are generally defined as those products that provide environmental, societal and economic benefits while protecting public health, welfare and environment over their full commercial cycle, from the extraction of raw-materials to final disposition [1]. According to the National Council for Advanced Manufacturing (NACFAM) in the U.S., sustainable manufacturing includes the manufacturing of sustainable products, and the sustainable manufacturing of all products [2]. This signifies the importance of developing product-level metrics towards fulfilling the goal of sustainable manufacturing. Further, the U.S. Department of Commerce defines sustainable manufacturing as “the creation of manufactured products that use processes that minimize negative environmental impacts, conserve energy and natural resources, are safe for employees, communities, and consumers and are economically sound” [3]. This statement indicates the close interconnection between product-based and process-based metrics for sustainable manufacturing. The National Institute for Standards and Technology (NIST) has a well-established sustainable manufacturing group actively involved in the development of metrics for sustainable manufacturing [4]. Development of product-based sustainability metrics has been going on for a considerable period of time, and researchers in the past have suggested different ways to assess the sustainability content of a product. A large number of indicators for product sustainability are available in the literature. The triple bottom line aspect of sustainability (considering the environmental, societal as well as economic factors) is well known and accepted in the academia as well as industry. The quantitative evaluation of tradeoffs among metrics across the triple bottom line is a difficult task, and this is one area where the ongoing research at the University of Kentucky is focused. It is a challenge to define and contain the system boundaries while trying to define the interrelationships among metrics across the triple bottom-line. A total life-cycle based approach helps to meet this challenge by developing metrics within the boundaries defined by the four life-cycle stages of a product.

2

TOTAL LIFE-CYCLE APPROACH TOWARDS PRODUCT METRICS DEVELOPMENT

A total life-cycle based approach towards developing indicators as well as metrics for product sustainability is the key element of the work presented in this paper. The categorization of metrics in this way provides an opportunity to develop a comprehensive list. The four life-cycle stages of a manufactured product in a closed-loop system considered here are: pre-manufacturing, manufacturing, use, and post-use [5]. Each life-cycle stage is defined in brief to understand its range of influence. This is critical because all the indicators/metrics are placed under different life-cycle stages based on these definitions. Pre-manufacturing: The foremost stage in the life-cycle of any product is the extraction of raw material from the natural reserves. Pre-manufacturing includes mining metal ores and smelting them into metal alloys, extraction of crude oil and processing it into hydrocarbons, cutting trees and transforming them into usable wood or paper, etc. Manufacturing: It is the phase where raw materials are transformed into finished products. A wide range of processing techniques is involved in this phase based on the desirable performance characteristics that are needed for the final product. Assembly (manual or automated), product packaging, etc., are also considered to be a part of the manufacturing phase. Use: The use phase pertains primarily to the amount of time the consumer owns and operates the product. During its use stage, the product needs to be energy-efficient, safe, reliable, easy to operate, maintain and repair, etc. Post-use: The post-use stage involves the final processing of a product for disposal, incineration, recycling, remanufacturing, or other end-of-life processing. Different end-of-life options can be considered during this stage to prolong the product life-cycle and also to ensure perpetual material flow in continuous development of next generation products from successive life-cycles.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_42, © Springer-Verlag Berlin Heidelberg 2011

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241

PREVIOUS WORK ON INDICATORS/METRICS PRODUCT SUSTAINABILITY

FOR

Fiksel et al. [6] were among the earliest to develop product sustainability indicators and categorize these under environmental, societal and economic aspects. This work has a good aggregation of indicators, but with no total life-cycle consideration. Kaebernick et al. [7] and Ritzen and Beskow [8] developed procedures that consider environmental effects at the design stage of product development. Schmidt and Butt [9] developed a product sustainability index (PSI), which is implemented as a sustainability management tool in the Ford product development system. A significant part of the work in the product sustainability area is based on ISO 14000 standard series, which is pre-dominantly environmental, making it more of an environmental impact assessment. Further, no categorization across product life-cycle stages is performed. Consideration of four life-cycle stages across the triple bottom line has been an area of considerable emphasis from the early work done at the University of Kentucky [10]. 4

PRODUCT SUSTAINABILITY INDICATORS

EVALUATION

USING

The six major elements of product sustainability along with numerous sub-elements identified in our early work are shown in Figure 1. These sub-elements form the basis for developing generic product sustainability indicators. Based on the requirements of different products and industrial sectors, these indicators can be selected. However, there is a need to combine these indicators and estimate aggregate scores/indices that can help to evaluate or compare different products in terms of their overall sustainability content. Jawahir et al. [11] evaluated the sustainability content of a product using a generic product sustainability index (PSI), incorporating the three aspects of sustainability and categorizing the indicators (influencing factors) across the four life-cycle stages of a product. The weights assigned to the influencing factors are approximate numbers based on their relative importance and company priorities.

Figure 1: Product sustainability wheel [10]. Gupta et al. [12] used the analytic hierarchy process (AHP) to determine the relative importance of different influencing factors and compare the sustainability content of two similar products.

AHP is a widely used mathematical technique that can prioritize a mixed group of elements with both qualitative and quantitative nature, minimizing the subjectivity involved [13]. Again, the life-cycle based categorization of the indicators is a key towards developing an AHP-based product sustainability hierarchy, as shown in Figure 2 for two different designs of a consumer electronic product (MP3 player). The life-cycle stages of a product form the Level L2 of the hierarchical structure in Figure 2. The corresponding influencing factors under different life-cycle stages are placed at Level L3 and this helps in designing a more comprehensive and accurate questionnaire, leading to a better evaluation of product sustainability content. After performing the AHP based matrix calculations, it was established that Product I is more sustainable compared to Product II. The overall priority values for all the influencing factors at Level L3 are also determined that helps in establishing the indicators that need prioritized attention. Considerable interdependence is observed while developing the influencing factors or metrics for product sustainability. The interdependence refers to the influence of an indicator in one aspect over another indicator under a different aspect of sustainability (triple bottom line). Similarly, an indicator categorized under a certain product life-cycle stage can also have influence in other life-cycle stages. AHP methodology does not take this interdependence into account. The analytic network process (ANP), which is a generalization of AHP, can be used to study this interdependence and interaction of higher-level elements in a hierarchy on lower-level elements. The feedback structure used in this methodology helps in the decision making to attain a desired future [14]. The problem is structured as a network in ANP, rather than as a hierarchy. However, analytical calculations with ANP become very lengthy and complicated for a comprehensive set of influencing factors. 5 5.1

LIFE-CYCLE BASED LEVELING SYSTEM FOR PRODUCT METRICS Life-cycle based leveling system

An interesting observation while categorizing metrics across lifecycle stages is that some of these metrics have presence across multiple life-cycle stages. This provides an opportunity to organize metrics at different levels; for example, top level (Level 1) metrics can be the ones that are present across all four life-cycle stages. Level 2 metrics are the ones that are present across any three lifecycle stages. Similarly, Level 3 metrics are present across any two life-cycle stages and Level 4 metrics are only present in one lifecycle stage. Figure 3 shows a pyramid structure representation of these different levels of metrics. Further, Figure 4 shows the organization of metrics in the form of a Venn diagram. The four circles comprising the Venn diagram represent the four life-cycle stages of a product: pre-manufacturing, manufacturing, use, and post-use. Some example metrics (environmental, societal and economic) and the interdependence among these metrics are represented (through single and double headed arrows) in the Venn diagram. It can be easily noticed that the metrics presented as Level 1 need prioritized attention because of their influence across all life-cycle stages of a product. However, no weightings are assigned to any metric at this point which makes it difficult to ascertain if a Level 4 metric needs more attention than a Level 1 metric to enhance the overall sustainability content of a product. The metrics at four different levels set up the taxonomy of metrics, which can help in the future development of product metrics ontology. Ontology, which is an explicit specification of a conceptualization [15], and its challenging application in developing the metrics for product sustainability will be briefly presented in the last section.

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Figure 2: Product sustainability hierarchy [12]. Considerable subjectivity is involved in assigning the weightings to the metrics even in their current form as shown in Table 2. Further, any weighting system will be very product-specific. The application of AHP and ANP is a good approach that can be considered for assigning weightings to the metrics. A recent ANSI workshop also emphasized the need to have decision-making processes, such as AHP, that can be applied with flexibility based on varying needs for product sustainability standards [16]. The results obtained through AHP and ANP can be integrated with the data available for the metrics to derive more science-based weightings for a specific product. The recently undertaken case studies at the University of Kentucky involve automotive and aerospace products, and these case studies are expected to provide real-world examples for evaluating the actual product sustainability content. 5.2

different measurement method under corresponding life-cycle stages. For example, if an automobile is under consideration, the ‘energy use’ during the manufacturing stage can be based on different processes and machines used. For the use stage, the same ‘energy use’ metric can be based on the miles per gallon etc. It should also be noticed that the product metrics under premanufacturing and manufacturing stages are mostly related to the processes involved with these products. The measurement method under these two life-cycle stages can be correlated to the methods defined for the process metrics. The process metrics development is not a part of this work. However, it is worth mentioning here because the close interactions between process metrics and product (pre-manufacturing and manufacturing stage) metrics can help in eliminating the redundancy involved.

Metrics clusters and product metrics

Based on the six major sustainability elements and corresponding sub-elements of product sustainability as mentioned before, a product metrics system is developed for generic products. The metrics are grouped under different metrics clusters to make them more structured. These metrics clusters have an important significance because these will help in a systematic aggregation of data while considering the complete life-cycle of a product. The proposed metrics clusters are defined for the environmental, economic as well as societal aspects, as shown in Table 1. There are 13 metrics clusters in total, with ‘end-of-life management’ being a common metric cluster across all elements of the triple bottom line. Several metrics are identified and defined under different clusters. Some example metrics are shown (along with the clusters in which these metrics occur) in Table 2. All metrics are categorized across the life-cycle stages of a product to have a detailed understanding of the influence of a particular metric. Further, a generic measurement method is defined for each metric. This measurement method needs to be customized based on the product that is being evaluated. D/L stands for ‘dimensionless metric’ under the unit column in Table 2. The life-cycle based categorization of the metrics indicates the challenge involved in performing a complete sustainability evaluation for a product. The metrics that are present across multiple life-cycle stages will have a

Figure 3: Leveling system for product metrics.

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METRICS CLUSTERS

Figure 4: Examples of interdependence among indicators/metrics across life-cycle stages. ENVIRONMENT

ECONOMY

SOCIETY

Residues

Investment

Education

Energy Use and Efficiency End-of-Life Management Material Use and Efficiency

Innovation End-of-Life Management Quality

Customer Satisfaction End-of-Life Management Safety and Societal Wellbeing

Water Use and Efficiency Table 1: Product metrics clusters. 6

TOWARDS AN ONTOLOGY-BASED PRODUCT SUSTAINABILITY

APPROACH

FOR

The analysis of developed metrics and their categorization shows that considerable interdependence exists among them across lifecycle stages and with respect to triple bottom line. It is important to account for these interrelationships when evaluating the sustainability of a product. There is an increasing trend in developing software tools for product design and development. Most common among these are product life-cycle management (PLM) tools being developed by many companies. A significant amount of data for the pre-manufacturing and manufacturing life-cycle stages of a product overlaps with the manufacturing process-level data and a good integration between product master data and manufacturing master data would be needed. PLM tools provide a good environment to start and their use could be enhanced by including the various metrics clusters and developed metrics presented here. Furthermore, an ontologybased approach is proposed and considered as a solution towards improved product life-cycle management and thus improved overall product sustainability.

Fundamentally designed and used to improve communication between either humans or computers, ontologies are a good means to enable knowledge sharing and reuse. The main aim of ontology is to make explicit the knowledge contained within software applications, as well as that within an organization and the business procedures in a particular domain [17]. Considering that the metrics presented in the previous sections need to be defined and those definitions have to be adopted and understood by enterprise applications across the manufacturing system, the development of a product ontology which also takes these metrics into account is a sound solution for assuring and proceeding towards product sustainability. The ontology is often captured in some form of semantic network with nodes representing concepts or individual objects and arcs representing relationships or associations among the concepts [18]. The metrics clusters presented in Table 1 are good examples that can act as seed points for recognizing the ontology concepts. Also, the interdependence among metrics, as explained with the help of some examples in Figure 4, will help in representing the associations among the concepts of the ontology. This ontological approach will help in the development and deployment of relevant product metrics that will appropriately determine the overall product sustainability for sustainable manufacturing. 7

CONCLUDING REMARKS

This paper presents a generic product metrics system to assess the sustainability content of a product that can help in moving towards the goal of achieving more sustainable manufacturing. The metrics clusters and the corresponding metrics are developed so as to meet the needs across a broad range of industrial segments. An emphasis has been given to the life-cycle-based approach wherein the metrics are categorized across the four life-cycle stages of a product. Some analytical tools, such as AHP and ANP, are proposed along with data gathering that can help in assigning some weighting to different metrics.

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Residues

INDIVIDUAL METRICS Emissions Rate (carbon-dioxide, sulphur-oxides, nitrous-oxides etc.) Solid Waste Stream Liquid Waste Stream

End-of-Life Management (Environmental)

Research and Development expenditure to enhance environmental sustainability/ Total research and development budget

$/$ (D/L)

Reused Product Ratio

Number of reused product units sold/ Total number of product units sold

D/L

Recycled Material Usage Rate

Recycled Water Usage Rate

Quality

Number of remanufactured product units sold/ Total number of product units Restricted material usage (Referenced from RoHS, REACH)/ Total number of product units made Amount of recycled material used (manufacturing phase)/ Total number of product units made Mass of recycled packaging material used/ Total number of product units made Net water consumption/ Total number of product units made Amount of reused or recycled water consumption/ Total number of product units made Cost of energy consumption/ Total number of product units made

PM

M

U

PU

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

mass/unit

Design-forEnvironment Expenditure

Energy Cost

Innovation

mass/unit

KWh/unit $/unit

Water Use Efficiency

End-of-Life Management (Economic)

Mass disposed into landfill/ Total number of product units made Liquid residues (cleaning agents, coolants etc.) generated/ Total number of product units made

Average maintenance (repair) energy per product unit over the use phase/ Total number of product units made

Packaging Material Usage Rate

Cost

mass/unit

Maintenance/ Repair Energy

Restricted Material Usage Rate

Water Use and Efficiency

Total Emissions (summing up different types of emissions and assign any weighting if possible)/ Total number of product units made

KWh/unit $/unit

Remanufactured Product Ratio

Material Use and Efficiency

UNIT

Net energy consumption/ Total number of product units made

Energy Efficiency Energy Use and Efficiency

MEASUREMENT METHOD

D/L mass/unit mass/unit mass/unit gallons/unit $/unit gallons/unit $/unit $/unit

Product Operational Cost

Costs involved during the product operation over its life-span per product unit

$/unit

Product Maintenance Cost

Maintenance/repair costs involved during the product use over its life-span per product unit

$/unit

Legal Cost

Costs incurred on legal disputes (involving employees and customers)/ Total number of product units made

$/unit   

  

  

  

Average Disassembly Cost

Total disassembly cost/ Number of product units disassembled

$/unit parts/unit

  

  

  

  

Reused Product Profit

Average profit per reused product unit sold

$/unit

  

  

  

  

Remanufactured Product Profit

Average profit per remanufactured product unit sold

$/unit

  

  

  

  

Design Life

Average designed life-time of the product (compared with similar competing products)

Hours

  

  

  

  

Research and Development Cost

Research and Development costs on product sustainability related initiatives/ Total number of product units made

$/unit   

  

  

  

Life-cycle Span

(Actual average life span of the product unit)(Designed average life span of the product unit)

Hours   

  

  

  

Sustainability in Manufacturing

Education

Customer Satisfaction

End-of-Life Management (Societal) Safety and Societal Well-being

245

Employee Training and Development

Average employee hours spent on training (related to product design, manufacturing, safety, quality etc.)/ Total number of product units made

Hours/unit $/unit

Repeat Customer Ratio

Number of repeat orders for the product/ Total number of product units sold

(D/L)

Product Return Rate

Average products units returned/ Total number of product units sold

(D/L)

Ease of Sustainable Product Disposal

Average cost involved in sustainable product disposal per unit of product disposed

$/unit

Ease of Product Takeback

Average cost involved per unit of product takeback after first-life of the product

$/unit

Product Processing Injury Rate

Average number of injuries during product processing/ Total number of product units sold

incidents/unit $/unit

Product Use Injury Rate

Average number of injuries during product use/ Total number of product units sold

incidents/unit $/unit

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

Table 2: Product metrics under different metrics clusters categorized across the life-cycle stages of a product. Case studies on major automotive and aerospace products are underway to apply the metrics system. Further, an ontology-based approach is suggested as a pre-requisite for continuous improvement in evaluating the sustainability content of manufactured products. 8

Schmidt, W.P.; Butt, F. (2006): Life-cycle tools within Ford of Europe's Product Sustainability Index, Int. J. Life-cycle Assessment, Vol. 11, No. 5, pp. 315-322.

[10]

Jawahir, I.S.; Dillon, O.W.; Rouch, K.E.; Joshi, K.J.; Venkatachalam, A.; Jaafar, I.H. (2006): Total life-cycle considerations in product design for sustainability: A framework for comprehensive evaluation, Proc. 10th Int. Research/Expert Conf. (TMT 2006), Barcelona, Spain, pp. 110.

[11]

Silva, N.D.; Jawahir, I.S.; Dillon, O.W.; Russell, M. (2009): A new comprehensive methodology for the evaluation of product sustainability at the design and development stage of consumer electronic products, International Journal of Sustainable Manufacturing, Vol. 1, No. 3, pp. 251-264.

[12]

Gupta, A.; Vangari, R.; Jayal, A. D.; Jawahir, I. S. (2010): Priority evaluation of product metrics for sustainable manufacturing, Proceedings of the 20th CIRP Design Conference, Nantes, France, April 19-21.

[13]

Saaty, T.L. (2008): Decision making with the Analytic Hierarchy Process, Int. J. Services Sciences, Vol. 1, pp. 8398.

ACKNOWLEDGMENTS

The authors acknowledge the project sponsorship by the National Institute of Standards and Technology (NIST). They also would like to extend their sincere thanks to other project team members, Dan Seevers, Tao Lu, Mohannad Shuaib and Chris Stovall for their contributions. Project guidance and continuous advice of Professors F. Badurdeen, O.W. Dillon, Jr., K.E. Rouch and M. Dassisti (Bari Polytechnic, Bari, Italy) are also gratefully acknowledged. 9

[9]

REFERENCES

[1]

www.sustainableproducts.com/susproddef.html [accessed Jan 6, 2011].

[2]

www.nacfam.org/PolicyInitiatives/SustainableManufacturi ng/tabid/64/Default.aspx [accessed Jan 6, 2011].

[3]

www.trade.gov/competitiveness/sustainablemanufacturin g/how_doc_defines_SM.asp [accessed Jan 6, 2011].

[14]

Saaty, T.L. (2008): The Analytic network process, Iranian J. Oper. Res., Vol. 1, No. 1, pp. 1-27.

[4]

Manufacturing Engineering Laboratory, National Institute of Standards and Technology (NIST), (2009): NIST Workshop on Sustainable Manufacturing: Metrics, Standards and Infrastructure, Gaithersburg, MD, USA, Oct 13-15.

[15]

Gruber, T. (1993): Towards principles for the design of ontologies used for knowledge sharing, Technical Report KSL93-04, Knowledge Systems Laboratory, Stanford University.

[5]

Jawahir, I.S.; Dillon, O.W. (2007): Sustainable manufacturing processes: New challenges for developing predictive models and optimization techniques, First Int. Conf. on Sust. Manuf. Montreal, Canada.

[16]

American National Standards Institute (ANSI) (2009): ANSI workshop toward product standards for sustainability, Workshop Report.

[6]

Fiksel, J.; McDaniel, J.; Spitzley, D. (1998): Measuring product sustainability, J. Sust. Prod. Des., Vol. 6: pp. 7-19.

[17]

Denkena, B.; Shpitalni, M.; Kowalski, P.; Molcho, G.; Zipori, Y. (2007): Knowledge management in process planning, Annals of the CIRP, Vol. 56, No. 1, pp. 175-180.

[7]

Kaebernick, H.; Kara, S.; Sun, M. (2003): Sustainable product development and manufacturing by considering environmental requirements, Robotics and Computer Integrated Manufacturing, Vol. 19, pp. 461-468.

[18]

Huhns, M.N.; Singh, M.P. (1997): Ontologies for agents, IEEE-Internet Computing, Vol. 1, No. 6, pp. 81-83.

[8]

Ritzen, S.; Beskow, C. (2001): Actions for integrating environmental aspects into product development, J. Sust. Prod. Des., Vol. 1, pp. 91-102.

Carbon Footprint Analysis for Energy Improvement in Flour Milling Production 1

1

1

Chee Wai Patrick Shi , Fatida Rugrungruang , Zhiquan Yeo , Bin Song 1

1

Singapore Institute Technology of Manufacturing,71 Nanyang Drive, Singapore 638075

Abstract From the “cradle-to-gate” assessment of one ton of plain flour, wheat production is found to contribute most to the carbon footprint of plain flour with a percentage over 60%. In particular, the flour mill production, an energy-intensive lifecycle stage, accounted for approximately 30% of the final carbon footprint results — with the milling process resulting in 40% of the production emissions. Direct GHG emissions reduction strategies proposed include the purchased wheat from suppliers who demonstrate cleaner production and are of proximity. Alternatively, carbon footprint can be lowered indirectly through making the operations more energy efficient by improving the processes and equipment used. Keywords: Carbon Footprint Assessment; Energy Efficiency; Flour Mill Production

1

INTRODUCTION

The increasing concern of climate change globally has created a wave of carbon footprint programmes developed by different countries and organizational bodies to assess the environmental performance of products and services [1]. Carbon footprint, a subset of data from Life Cycle Assessment (LCA), is utilized to quantify the impact of Greenhouse Gas (GHG). In simple terms, this methodology focuses on the analysis of GHG emissions that is deemed to cause climate changes which is one of the key elements in LCA [2]. In the carbon footprint assessment, all major anthropogenic greenhouse gases engendered within the product or service system are converted to CO2 equivalent and summed up to determine the final global warming potential which can be adopted as the baseline for improvement. Having the knowledge of this baseline is vital for operational improvement, better management of resources and improvement of efficiency. As it is the aim for Singapore government to develop the country into a low carbon society, carbon footprint assessment can be a useful tool to facilitate such a move. The paper presents the carbon footprint analysis for plain flour manufactured in Singapore. Flour generally is one of the most essential ingredients found in our daily diet. Commonly found in bread, cakes, noodles and the list runs on, it is a food source vital to many around the world. Therefore, it is critical to ensure that the manufacturing of flour is carried out in sustainable manner. Although the wheat is imported, the study encompasses the production of wheat to provide the flour mill company a holistic view of the total product system. Flour can be a Business-to-Customer product (B2C) but for this study, Business-to-Business (B2B) would be the main concern. The results generated from the study created a baseline for their manufacturing operation improvement. Using the carbon footprint analysis, the company is able to understand their operation emissions, identifying the hot spots, and adopting the suggested recommendation from the study for further reduction in their carbon footprint. The used of carbon footprint analysis as an indicator to elevate the energy efficiency for producing a product is also is also explored and investigated.

A large amount of carbon emitted is generated within the flour milling production and is attributed indirectly by the use of equipment that consume electricity. This is similar to the majority of the manufacturing industries in Singapore. Therefore the reduction electrical consumption would translate to lower carbon footprint. 2 2.1

METHODS Guidelines

The study is conducted following the guidance of the International Standards Organisation (ISO) 14040 and 14044 which are well established framework for LCA [3]. The Publicly Available Specification 2050 (PAS 2050) [4] developed by the British Standards Institution (BSI) in partnership of Carbon Trust and Department of Environment Food and Rural Affairs (Defra) is also adopted for this study. Presently, there are no standards enforced globally for carbon footprint assessment but many carbon footprint initiatives use these standards mentioned as a point of reference [1] [5]. 2.2

Goal and Scope of Study

The purpose of this study is to provide a Life Cycle Inventory (LCI) that quantifies the GHG (carbon footprint) associated with the raw material extraction, production and transportation linked to flour mill production. These stages define the scope of the study which is cradle-to-gate. The results from the study should answer the following questions: 

What is the carbon footprint to one ton of plain flour?



Where are the major contributors of the carbon footprint?



What are the corresponding recommendations to reduce the emission generated?

The work conducted is to aid the flour mill company to better understand how to improve their product system in terms of carbon footprint.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_43, © Springer-Verlag Berlin Heidelberg 2011

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Shipment to Singapore

Electricity, Fuel, Fertiliser, Chemical

Wheat Production

Transportation

Preparation Unloading f rom vehicle

Storage in Silos

Cleaning Processes

Production Wheat Milling

Wheat weigher

Finishing

Delivery

Bran

Greenhouse Gas Emission

Raw Material Production

247

Pollard

Entoletor

Flour Sampling

Flour Bin

Bulk Flour

Delivery

Packing Additives

Mixing Premix

Legend Included in the assessment Excluded in the assessment

Figure 1: System boundary of plain flour production. 2.3

The Functional Unit

The functional unit of the product system is defined as one ton of plain flour delivered to a customer in bulk container. All inputs and outputs to the product system are normalised to the production of one ton of flour. 2.4

System Boundaries

Figure 1 shows a simplified life cycle process flow for the production of plain flour. The dashed lines represent the boundaries of the product system to the environment. The processes included in the system boundaries start with wheat cultivation. The cultivated wheat is harvested and transported from two main suppliers in Australia and USA. Once the wheat reaches the flour mill plant in Singapore, it undergoes several preparation processes before milling commences. These processes include unloading the wheat from the vehicle, storing and cleaning. The clean wheat then goes through the flour milling processes where the output – plain flour – is produced. Bran and pollard are the two co-products generated during the milling processes. Subsequently, the flour goes through a mixing process and is filled in a bulk tank ready to be delivered to the miller’s customers. There are two production lines working on hard and soft wheat. Both production lines were analysed and presented in this paper. 3

LIFE CYCLE INVENTORY

The life cycle inventory analysis of one ton of plain flour involves collating resource consumption and emissions data on wheat cultivation, transportation and flour mill production in the defined

system. The two types of inventory data are required in a carbon footprint assessment, mainly activity data (resource consumptions) and emission factors (conversion per unit of resource consumption) [4]. This assessment is carried out based on the inventory data collected from various sources including specific data provided by the company as well as peer-reviewed sources, publicly available models and reports, and databases. These data sources can be categorised as primary data source and secondary data source [4]. Primary data source is gathered directly from flour milling company which is mainly actual input-output data. For example, the data from the company includes energy consumption (electricity and diesel), production volume, bill-of-material, wastage produced and location of customers. Secondary sources are those from which generic input-output data were gathered and are representative of actual data. Examples include upstream production of wheat, electricity generation from the grid and transport of the wheat crop. Details of data collection and modelling are described in the following sections according to the sequence of the product lifecycle stages. 3.1

Raw Material Production

Wheat is purchased from Australia and USA. This study has relied on peer-reviewed sources for the secondary resource profile and emissions data of the upstream wheat production. The Global Warning Potential (GWP), on a 100 year time line, of wheat production studied in Australia [6] and USA [7] are 303.66 kg-CO2 eq/ton and 283 kg-CO2 eq/ton respectively. For the wheat production in Australia, the stage of raw material production covers the pre-farm activities, on-farm activities (seeding, spraying, harvesting) and post-farm activities (transport to

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silo, silo to port). Background data on production of fertilisers and pesticides, and electricity generation are also included. However, the carbon uptake during crop growing was omitted from the study. As argued by Biswas et al [6], CO2 uptake from crop growth is not considered as much of the plant material was retained on site following harvest. It is assumed that sequestered CO2 would be rereleased with time. Similarly, soil carbon (C) sequestration is considered insignificant, and soil CH4 emission uptake was not included because of the absence of data and is expected to be low from fertilized agricultural soils. Furthermore, the regional-specific value for the proportion of Nitrogen fertiliser emitted as Nitrous oxide (N2O) is used instead of the international default values such as from Intergovernmental Panel on Climate Change (IPCC) [8] and United States Environmental Protection Agency (US EPA) GHG inventory [9]. On the other hand, the research work on wheat production in USA [7] covers production of grain farming inputs and their transport, fuel use during grain farming, machinery production, and transport of milled wheat to the processing centre and point-of-sale. However, the research further emphasizes the transport infrastructure such that the impacts from fuel production, transport vehicle manufacturing and end-of-life were also included. The data employed into our study therefore omits the transportation section and only focuses on wheat production without wheat product transportation. Furthermore, the study was interpreted on the basis of IPCC conversion factors. It also considered the transferring of carbon from the atmosphere to soil matter which can be a CO2 sink. However, an impact of soil carbon storage was discussed as having a considerably large in the uncertainty ranges. The dataset was therefore employed in this study without modification. Transportation

The wheat is transported to Singapore from Australia and USA either by bulk vessel or container ship. The average distance from Perth, Australia is 4,588 km and Portland, USA is 13,178 km. The distances are obtained by an Internet calculation interface [10]. For this study, the bulk carrier would be the transportation mode used and the assumed load carried would be 105,000 tons. The -6 emissions therefore would be 2.41 x 10 kg-CO2e per kg-km [11]. 3.3

Delivery to Customer

The finished product, plain flour, is delivered to a customer in a 15 ton bulk tank truck. In this study, the flour mill’s customer on the west side of Singapore is selected as the destination of the plain flour. The assumption is also made that the return journey for the bulk tank is empty. 3.5

Energy Data

Electricity and diesel are two energy types involved in this carbon footprint study. They are common resource inputs to all process steps along the product lifecycle particularly in production and transportation stages. The use of electricity from the power grid in turn contributes to the global warming potential (carbon footprint). This is due to the burning of fossil fuels in the extraction and generation of electricity, and must be taken into account. Power grid emissions factor of Singapore was collected from [13]. Similarly, the emissions factor of diesel was obtained from [11]. 3.6

Allocation bran and pollards as co-products

During the milling of the wheat, co-products, bran and pollard, are generated. These co-products are used as inputs to another product system. When situation of such occurs, all associated emissions should be apportioned accordingly. As per stated in ISO 14040 and 14041 [3], an allocation of input and emissions of the sub-system shall be expanded to incorporate the burden from processing the co-products. In this case, the co-products are reprocessed into bio-packaging materials. 4

RESULTS AND DISCUSSION

4.1

Carbon Footprint Assessment Results

The carbon footprint of one ton of plain flour is calculated as a sum of the inventory data related to the acquisition of wheat production, transportation, flour mill production and delivery to customer. The overall carbon footprint for plain flour are quantified as 495.07 kgCO2eq/ton from hard wheat and 467.71 kg-CO2eq/ton from soft wheat. Figure 2 illustrates the carbon footprint in kg-CO2eq/ton of each stage. 350

Flour Milling Production

The flour milling production can be categorised into three sections namely preparation, production and finishing. All activity data associated with electricity and material usage related to these sections are collected directly from the company. In the preparation section, the wheat is firstly unloaded from the bulk vessel or containers and sent for cleaning. The wheat unloaded is transported to storage silos by various unloading mechanisms before undergoing through a series of cleaning processes. An insignificant amount of waste is produced during the cleaning processes which mounted up to approximately less than 0.5% of the throughput. Similar amount of waste generated is observed for two of the production lines. Milling and mixing of the cleaned wheat are carried out in the production section. The wheat is passed through a series of machines to break open the wheat kernels and reducing of the endosperm by grinding to obtain the final product – plain flour [12]. The two production lines that handle soft and hard wheat generate a total of approximately 26% and 25% of co-products (bran and pollard) respectively. Lastly, additives of less than 1wt% are added to the flour by a mixing process. In the finishing section, the mixed flour is sent to the storage silos and is filled in bulk tank truck for delivery upon request from customers.

300

289.39 288.91

Hard Soft

250

kg-CO 2 eq/ton

3.2

3.4

200

183.62 156.77

150 100 50

21.67

21.67 0.42 0.42

0 Wheat production Transport to f lour Production of f lour mill

Delivery

Figure 2: Overall carbon footprint of hard and soft plain flour. The carbon footprint distributions for each stage to produce plain flour from hard and soft wheat are further illustrated in Figure 3 and 4. The results show that wheat production makes the largest contribution to the overall product carbon footprint which is in the region of 60%, while the flour mill production gives an important contribution of approximately 30%. The emissions due to transportation are considerably small which is about 5% for wheat transport and almost negligible for delivery to customer. Due to the land constraint in Singapore, agriculture is not the major contributor to the economy. Therefore there is a great reliance on

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imported agriculture products from overseas and wheat is one of them. The results have shown that production of wheat is the highest. Studies carried out on wheat production are greatly debatable. The two examples [6] and [7] cited in this study for wheat production show difference in emissions although their approaches in their studies are similar in many ways. The dominant emissions N2O reported in the two studies are 9% [6] and 50% [7], which is generated from agricultural soils. Other reported emissions generated during wheat production do not have such large uncertainty. There have been many studies investigating the nature and extent of N2O emissions and approaches for improvements. However, the technical details and improvement potentials pertaining to the wheat production will not be discussed under the scope of this analysis. It will require revisiting as new research in this area develops. Delivery 0.08%

Production of flour 37.09%

Wheat production 58.45%

Transport to flour mill 4.38%

Delivery 0.09% Wheat production 61.76%

Transport to flour mill 4.63%

Figure 4: Distributions of product (plain flour) carbon footprint from soft wheat. Bulk flour filler 4.71%

Unloading 2.61%

Cleaning 7.58%

Flour bin 5.70%

Figure 5: Distribution of carbon footprint for flour milling of hard wheat. On the other hand, the focus has been directed at the flour mill production stage which is of particular interest to the flour mill company. The flour mill production process is a promising area where the company has full control over when it comes to implementing carbon footprint reduction strategies.

Cleaning 8.86%

Milling 42.96%

Figure 5 and 6 show the distribution of the carbon footprint of the flour mill production of the hard and soft wheat. Approximately 40% of the emissions is contributed by the flour milling process for the two production lines. 23% to 25% of which is contributed by the flour weigher and entoletor (high speed spinning disinfection machine used to destroy possible infestation found in the flour). These two processes amount up to approximately 65% of the total carbon footprint for the flour mill production. RECOMMENDATION FOR AREAS OF IMPROVEMENT Raw Material

The largest contributor to the overall emissions of the plain flour product comes from the wheat production. Biswas et al. [6] suggests that by reducing the emissions from fertilizer could significantly impact the overall emission for wheat production. It had also been suggested that approximately 80% emissions could be mitigated from the on-farm stage by substituting chemical fertiliser for organic fertilizer, but subject to variability and further research required. Reducing the use or selecting the right choice of transportation fuel can greatly reduce the emission. Advice in the use of cleaner production strategies is given and by considering plant capacity utilisation, technology used and maintenance of the plant. Similar recommendations have been made by Meisterling et al. [7]. The authors also highlighted food miles as an important parameter, but not necessarily the most important compared to the farming practices. This statement can also be supported by the findings obtained from this study where the wheat production emissions was over ten times greater than that of transportation. Nevertheless, the upstream (and downstream) production is not within control of flour mill company. The improvement can only be achieved through purchasing decisions and policies with low carbon footprint objectives. 5.2

Milling 40.40%

Unloading 3.05%

Figure 6: Distribution of carbon footprint for flour milling of soft wheat.

5.1

Production of flour 33.51%

Flour weigher and Entoletor 23.75%

Flour weigher and Entoletor 25.43%

5

Figure 3: Distributions of product carbon footprint (plain flour) from hard wheat.

Mixing 15.25%

Bulk flour Mixing filler 7.50% 5.52% Flour bin 6.68%

Hot spot identification

From the carbon footprint assessment in the milling process, weigher and entoletor have been areas identified as the key contributors to high carbon footprint. For this study, focus has been placed on identifying possible areas where improvement can be conducted to reduce the carbon footprint. For the flour milling production, the source of carbon footprint is generated solely by electricity. The way to reduce carbon footprint is to improve the energy efficiency of the processes or the equipment used. Figure 7 shows the overall distribution of electrical usage in the flour mill plant in the year 2009. The highest percentage of usages is accredited to the milling processes, weigher and entoletor of the hard and soft wheat, 32.79% and 26.42% respectively. Majority of the power generated comes for motors of various sizes employed in flour processing. Upon detailed investigation, the highest motor consumption is rated at 90kW used to power a large fan. The fan is

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Sustainability in Manufacturing

DB-N 0.15%

DB-Q 1.07%

DB-M 0.16% DB-J 0.37%

DB-R 0.97% DB-S 2.24%

DB-T 2.89% DB-U 0.09%

DB-K 1.87%

DB-X 3.63% DB-A 2.35%

DB-B 5.44%

Milling - hard wheat 32.79%

DB-H 0.25% DB-G 5.34% DB-F 3.13% DB-E 4.75%

DB-C 6.07%

Figure 7: Distribution of electrical consumption for the flour milling plant.

Overall Product Carbon Footprint (kg-CO2eq/ton)

495.07 491.41

490

493.20

Hard 488.04

489.69

482.13

479.56

486.46

480 470

Soft

484.95

483.51

480.82

467.71 463.57 459.77

465.6

460

461.63

456.28

457.98

450

453.09

454.65

450.19

451.61

440 0

2

4

6

8

10

12

14

16

18

20

Percentage (%) of motor improvement

Figure 8: Possible overall product carbon footprint reduction upon implementation of motor improvement. That is approximately 1.74% and 2.08% of improvement compared to before any improvement carried out on the motors. The carbon footprint for processing hard and soft wheat on the flour mill production will be 175.01 and 147.05 kg-CO2eq/ton, respectively, which are approximately 4.96% and 6.20% improvement from before.

183.62

180

Hard

179.96 176.59

181.75

178.24

160

Soft

173.50

175.01

170

170.68

172.06

168.11

169.37

156.77 152.64

150

154.66

148.83

145.34

150.69 147.05

140

142.15

143.71

139.26

140.67

130 0

2

4

6

8

10

12

14

16

18

20

Precentage (%) of motor improvement

Figure 9: Possible overall flour mill production carbon footprint reduction upon implementation of motor improvement. It can be clearly seen that the improvements are more significant on the flour mill production compared to the total product system. From the study, evidences clearly show that carbon footprint can be reduced by a significant amount by simply improving the energy efficiency in operating the equipments within the production plant. 5.3

Using of co-products

It has been demonstrated in this study that the product carbon footprint can be reduced due to the allocation of co-products. The findings from this study show that when bran and pollard are utilised in other products such as packaging (becomes co-products), it absorbs about 4% of the product carbon footprint. The conversion of by-product into a useful and valuable co-product is an encouraging approach which not only results in environmental improvement, but is also prominent in the aspects of resource efficiency and economic benefits. This increases the utilisation of natural resources, reduces the disposal of waste and can be used as substitute material to non-renewable resources such as plastics and fossil fuels. 6

Milling - soft wheat 26.42%

500

190

Flour Mill Production Carbon Footprint (kg-CO2eq/ton)

required to run continuously during the whole production cycle and there are several numbers of these large fans and the purpose of these fans is to transport wheat and flour from point to point during the flour production. Recommendations were suggested to the flour mill company in methods to run the motor more efficiently thus reducing the overall production and product carbon footprint. Reduction methods encompass improvement in wheat and flour transportation through the piping hence reducing the speed of the fan, installation of variable speed drives and controllers to improve and to monitor the product flow, and wheat and flour transportation sequencing. Affinity Law states that the power of the motor is proportional to the speed of the fan cube therefore by reducing the fan speed the power of the motor will reduce in a greater magnitude. If the motor speed of the fan is reduced by just 10%, the reduction of the power of the motor will be approximately 30%. Therefore the 90kW motor will be now running at 65kW. Figures 8 and 9, illustrate reduction in carbon footprint for the overall product (1 ton of flour) and flour mill production versus the percentage of possible motor improvement implemented to the 90kW motors. Under the scenario, the flour mill company is able to reduce successfully 10% of the power consumption of the motors, the overall product carbon footprint from processing hard and soft wheat will be 468.46 and 459.98 kg-CO2eq/ton, respectively.

CONCLUSIONS

Carbon footprint assessment (life cycle approach) has been found to be a useful tool for quantifying GHG emissions from the “cradleto-gate” of one ton of plain flour, and for identifying which production stages are responsible for these emissions. The overall carbon footprint is quantified as 495.07 kg-CO2eq/ton for plain flour produced from heat wheat and 467.71 kg-CO2eq/ton for plain flour produced from soft wheat. Wheat production was found to be the most predominant stage in the carbon footprint of the plain flour product which accounts for over 60%. A foremost opportunity to improve the carbon footprint caused by upstream production is through the purchasing-decision of wheat where suppliers with cleaner production and closer location (minimised transport need) are chosen and sourced. The flour mill production was identified as an energy-intensive lifecycle stage which gives an important contribution of approximately 30% to the final carbon footprint results. It was recommended that efforts must be focused on improving the efficiency of energy use in the flour mill production. In particular, the milling process that causes approximately 40% of the production emissions. The emissions can be reduced by 1% to 11% if the wheat and flour transportation system’s efficiency is improved. Much of the emissions from the flour mill plant is contributed by the used of electricity. Therefore, proper energy management system should be enforced to ensure that the process and equipment used are energy efficient. Lastly, the use of co-products, bran and pollard, helps to maximise the utilisation of natural resources, minimise the disposal of waste and added value to the excess. By converting the co-products into bio-packaging materials can shared out the environmental impact by 23%.

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251

ACKNOWLEDGMENTS

The authors also would like to thank all relevant parties who contributed in one form or another to the project. 8

REFERENCES

[1]

Finkbeiner, M., (2009): Carbon footprinting – opportunities and threats, in International Journal of Life Cycle Assessment, Vol 14, pp. 91-94.

[2]

European Platform on Life Cycle Assessment European Commission – Joint Research Centre Institute for Environment and Sustainability (2007): Carbon Footprint – what is it and how to measure, pp. 1-2 http://lca.jrc.ec.europa.eu/Carbon_footprint.pdf. Last assessed 10 November 2010.

[3]

ISO, International Organization of Standardization – ISO 14040/44 (2006): Environmental management – Life cycle assessment – Principles and framework/Requirements and guidelines.

[4]

British Standard, (2008): Publicly Available Specification (PAS 2050) – Specification for the assessment of the life cycle greenhouse gas emissions of goods and services.

[5]

Pandey, D., Agrawal, M., Pandey, J. S., (2010): Carbon Footprint: current methods of estimation, in Environmental Monitoring and Assessment, DOI:10.1007/s10661-0101678-y.

[6]

Biswas, W.K., Barton, L., Carter, D., (2008): Global warming potential of wheat production Western Australia: a life cycle assessment, in Water and Environment Journal, Vol. 22, pp. 206-216.

[7]

Meisterling, K., Samaras, C., Schweizer, V., (2009): Decisions to reduce greenhouse gases from agriculture and product transport, in Journal of Cleaner Production, Vol. 17, pp. 222230.

[8]

Houghton, J.T., Ding, Y., Griggs,D.J., Noguer,M., Van der Linden,P.J., Dai, X., Maskell,K., Johnson, C.A., (2001): Climate Change 2001: the scientific basis. Contribution of working Group I to the third assessment report of the Intergovernmental Panel of Climate Change, Cambridge, UK; New York, USA: Cambridge University Press.

[9]

United State Environmental Protection Agency (US EPA) (2010): Inventory of U.S. Greenhouse Gas Emission and Sinks 1990-2008 EPA 430-R-10-006.

[10]

Sea distance calculator, in http://www.searates.com/ reference/portdistance. Last assessed 10 November 2010.

[11]

PE International, GaBi Echterdingen, Germany

[12]

Campbell, G. M.,(2007): Handbook of Powder TechnologyRoller Milling of Wheat, Vol 12, Chap. 7, pp. 383-419.

[13]

National Environmental Agency (NEA), Information on emission factors (for CDM projects in Singapore), in http://www.nccc.gov.sg/informationOnEmissionFactors. pdf. Last assessed 10 November 2010.

4.3,

LCA-software,

Leinfelden-

Modelling Machine Tools for Self-Optimisation of Energy Consumption 1

2

2

Robert Schmitt , José Luiz Bittencourt , Ralf Bonefeld 1 2

Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen, Aachen, Germany

Bosch Rexroth AG, Centres of Technology Competence and Innovation Strategy, Lohr am Main, Germany

Abstract This paper presents a novel approach for modelling machine tools and so preparing the basis for self-optimisation. Based on previous experiments and publications, the main energy consumers in typical machine constructions are identified and machine components are structured in a way that facilitates the definition of the optimisation problem. Also energy saving possibilities are illustrated together with the suggested structure. In addition, further planed research works for the implementation of self-optimised machine behaviour are presented. Keywords: Energy Efficiency; Machine Tools; Modelling

1

INTRODUCTION

The life cycle duration of manufactured products has been continually reduced in the last decades. As a consequence, the demand for more flexible production machines has increased. In the specific case of machine tools, this flexibility is often reached by oversizing machine components in the requirement and design phases. The side effect of this practice is a notable reduction of the machine’s energy efficiency and hence an increased TCO (total cost of ownership) [1]. In order to compensate this efficiency drawback, methods for machine tools’ self-optimisation in view of energy consumption have been developed. A self-optimising machine tool is an intelligent system that has the capability to react autonomously and flexibly to its surrounding environmental conditions, to the interference of external users/systems, or also to their own dynamic behaviour, modifying their local objectives and adapting their parameters/structure in response to these dynamic factors [2][3]. Regarding the specific problem of energy efficiency, such a machine tool is able to adapt itself to the current production requirements, plan the power balance of energy consumers and reduce energy losses [4]. In this paper, the main energy consumers in typical machine constructions are identified based on previous experiments and publications. Machine components are structured in a way that facilitates the definition of the optimisation problem. In addition, a novel approach for modelling machine tools in view of selfoptimisation is presented and further planed research works are described. 2

ENERGY CONSUMERS IN MACHINE TOOLS

There are many different classifications for energy consumers in cutting machine tools. According to [5], the most important consumers are spindles and feed axes together with their electronics. Other relevant consumers are periphery components for medium supply (e.g. hydraulic, cooling and coolant components). Following this concept, basically two groups of consumers can be defined: drives and periphery. A simple

monitoring application that divides consumers in this way is presented in [6]. Drives are considered to be the biggest energy consumers during production time. They are responsible for process logistics and shaping. Another classification divides them into three categories [7]: main drives, secondary drives and auxiliary drives. Within the group of auxiliary drives, pumps for several mediums can be found. However, this is an unusual classification, because pumps are often considered to belong to the periphery, due to their functional objectives. The periphery is mostly composed by the so called ancillary units and other machine components that assist machine operation, process logistics and process mastering. Some examples of ancillary units are the cooling unit, the hydraulic unit and the coolant unit. Measurements of power consumption distributions related to these machine components can be found in [8], [9] and [10]. In [11], main and auxiliary drives are classified separated (e.g. spindle and feed axes, respectively) and other consumers are also grouped as periphery. The load responsible for the energy consumption is divided into basic and operating loads. The energy demand can be primary or secondary – where the secondary demand is not involved in the modification of the work piece. The authors of [12] focused on the structure of the energy consumption combining operation states with machine components. A given example shows the consumed energy not only distributed between machine components (i.e. electric cabinet, hydraulics, drive control, main spindle and coolant), but also together with stand-by losses and the process. Although the presented classifications can be very functional and easy to understand, it is not clear, which consumers depend on each other. The cause-effect relationships of the energy consumption development are hidden. For instance, when a motorpump continues consuming energy to circulate cooling fluid, even though there is nothing to be cooled, it is evident that some relationships are not considered. In [13], consumers are not presented in parallel, but in three different scopes that determine

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_44, © Springer-Verlag Berlin Heidelberg 2011

253

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Sustainability in Manufacturing - Energy Efficiency in Machine Tools

the energy demand in cascade: the process, the main axes and the auxiliary components, which are responsible for coolant, cooling, pneumatics, exhaustion and hydraulics. In this case, cause-effect relationships can be easier identified and some measures to save energy are cited based on this structure. In terms of implementation of self-optimisation capabilities, the only drawback of this procedure is the complexity involved in the definition of the process for the machine controller.

maintenance and availability, and present therefore a great potential to save energy. Nevertheless, machine tools manufactures prefer to adopt this paradigm because of reduced investment costs and compact construction of components. Table 1 lists some pros and cons concerning the use of common suppliers at machine level:

A simple approach to classify machine components in view of energy consumption, to clarify relationships and to highlight energy saving potentials is shown in Figure 1. The superior part of the pyramid (i.e. operator, NC program and control system) triggers commands and operations for the machine components, which are supposed to execute some job. This is a simplification of the process description at machine controller level. The machine components need energy to do the job and receive it from the common supply systems. These systems provide the required energy to the machine components through a specific medium. The hydraulic components, for instance, use the hydraulic fluid provided by a hydraulic pump or accumulator (common supplier) to perform work. The necessary energy is obtained from the available hydraulic power.

commands, operations

energy demand

Operator, NC program, Control system

Machine components Main components

Auxiliary components

Common supply systems (cooling, hydraulics, pneumatics, electrical power supply, etc) Figure 1: Machine structure and development of energy demand. In the next subsections, the most important consumers following the proposed classification will be discussed. 2.1

Machine components

Figure 1 shows the division of machine components into main and auxiliary components. This is a functional classification that helps to identify the consumers in a macro point of view. While typical main machine components are spindles and feed axes, auxiliary components can be tool magazines, chip transporters, pallet changers and others. As explained in section 2, machine components need support from supply systems in order to perform their jobs. This functional relationship generates energy consumptions both from machine components (consumers) and suppliers. 2.2

Common supply systems at machine level

There are many types of common supply systems used in machine tools. Good examples are hydraulic systems, cooling systems, and electrical power supply systems. Pneumatic suppliers can also be considered a common supply system, but they are usually available in the factory plant and are not offered at machine level. Normally, common supply systems have a constant physical dimension as interface for all consumers (e.g. hydraulic pressure, voltage, etc.) and a variable physical dimension to dose power (e.g. hydraulic flow, electric current, etc.). They often consume more energy than necessary, because of oversizing, interface

Pros

Cons

Investment costs;

Operation costs;

Control simplicity of consumers;

Supply excess;

Energy exchange between consumers;

Oversizing;

Compact construction of consumers

More transport losses

Table 1: Pros and cons for the use of common suppliers. 3

ENERGY LOSSES AND SAVING POTENTIALS

The identification of losses and the systematic analysis of their causes are the basis for the development of energy efficient technologies. Measures to improve efficiency like the use of energy recovery, the adoption of efficient components with energetic convenient dimensioning as well as the shortening of processing time and the reduction of medium are cited in [13]. Dornfeld lists in [14] different strategies for energy reduction depending on the relation between processing power consumption and the so called “tare” power consumption (power consumption that is independent from the process). Operations are classified as “tare heavy” or “process heavy” in order to select measures like process optimisation (tooling, path, etc.) or cycle time reduction. In [11], energy losses of machine tool components are grouped in four categories: electric losses, damping losses, friction losses and flow losses. The authors distinguish component and system optimisation by mentioning respectively their direct and indirect effects for increasing energy efficiency. Another way to identify losses and uncover saving potentials is to analyse the direct handling with energy in view of energy transformation, distribution and storage. In the case of machine tools it is difficult to use this approach, once machine components can handle energy in several ways. Considering the structure proposed in section 2, energy losses in machine tools can be divided into three categories: consumer losses, supplier losses and supply excess. The following subsections will describe these losses. 3.1

Consumer losses

Consumer losses are related to the efficiency of the machine components (main and auxiliary components) and their elements (e.g. motors, frequency converters, gears, cylinders, valves, etc.). Possible measures to reduce these losses are: 

optimisation of acceleration profiles;



optimisation of cutting fluid usage;



energy recovery and reutilisation;



optimisation of machine’s thermodynamics;



improvement of energy efficiency of components;

These measures can be implemented in different life cycle phases. While some of them can only be considered in the design phase, others are continuous processes that must be executed during the whole machine usage period.

Sustainability in Manufacturing - Energy Efficiency in Machine Tools 3.2

Supplier losses

4

Supplier losses are analogue to the consumer losses. They occur according to the energy efficiency of the supplier components and their distribution circuits under different working points. Some measures to improve efficiency are: 

elimination of leaks in fluid distribution circuits;



reduction of the distribution circuits;



improvement of energy efficiency of supplier components;

The machine design defines predominantly, which of these measures are taken into account. 3.3

Supply excess

Common supply systems often consume more energy than necessary because of their design paradigm. Beside the frequently oversized system components, common suppliers are thought to maintain an interface to consumers, which can be very convenient (e.g. constant hydraulic pressure provided by a pump), but can consume much energy. In addition, common suppliers must be always available, because of a lack of information about when, which consumer will demand support. This generates a supply excess, which is related to the excess of supplied medium or unnecessary availability. The behaviour of a typical common supplier is presented in Figure 2. In this example, the operations A, B, C and D represent support requests from different machine components (consumers). These operations differ from each other in respect of time of arrival, duration and load, which is qualitatively plotted in the middle graph. In this case, the power consumption of the supplier (presented in the upper graph) does not directly correspond to the load progress. The reason is that this supply system contains an accumulator before the interface with its consumers. The power source of the supplier remains decoupled from the accumulator and is only coupled for a short period — when the accumulator reaches a predefined low level. This behaviour can be observed on the two peaks of the upper graph of the Figure 2. Between the peaks, a supply excess caused by unnecessary availability with duration Δt

Supply excess (stand-by)

SELF-OPTIMISING COMMON SUPPLIERS

Considering the discussed structures and categories of energy consumers, their energy losses and saving potentials, common supply systems can be modelled in order to facilitate a posterior system optimisation. The focus of this approach is to reduce the described supply excess by implementing supply controllers. Such controllers are able to switch suppliers into different modes/states pursuing a reduction of their total energy consumption. A similar modelling approach was presented by Dietmair and Verl in [15]. The authors focused on the assessment of machine energy consumption using operative state machines together with usage profiles. Each state represents a predefined power balance between the machine components (energy consumers) and can be achieved or not, depending on the usage profile. Although this concept facilitates the assessment of the machine energy consumption, the support for optimisation is not appropriate for the implementation of self-optimising systems. This occurs because the operational states contain sets of parameters, which must be optimised independently from the usage profile, ignoring usage variations. Another disadvantage of this approach is that idle and operational power consumptions are not handled separately, covering energy saving potentials like the reduction of supply excess. 4.1

Functional state machine for common suppliers

In order to tackle the problem of supply excess discussed in section 3.3 and prepare the basis for the implementation of self-optimising systems, a functional state machine for common suppliers is proposed. This state machine differs from that presented in [15] in some ways: 

Transitions cost not only time, but also energy.



States do not represent what is currently done, but which operations are currently supported.



Each common supplier has its own functional state machine.



Operations are defined and also demand time and energy.

The idea is to model common suppliers more optimisation-oriented and help the decision making for the so-called sleep mode or shutoff strategies. According to this approach, the optimisation problem at supplier level can be defined by: “Find the best state/trajectory considering the required operations and time constraints in order to reduce idle power and total energy consumption”. To formulate the problem mathematically, an operation oi, belongs to a state si can be defined as:

t

Load at supplier

P input Supplier

is pointed. This occurs because the supplier keeps consuming energy (power source is decoupled but not shut off) even if there is no operation to support.

Operations

255

t

A B C D

oi, j  (Tlead , Pdemand ),

where Tlead is the time taken to complete the operation and Pdemand the power demand caused by the operation at supplier level. An operation can be supported in one or more states and a state si is defined as:



Δt

Figure 2: Typical supplier with load progress and supply excess. To reduce losses related to supply excess, the following measures can be considered: 

implementation of supply controllers;



elimination of bypasses;



shut-off strategies for suppliers;

that

(1)



s i  Pidle , Oi , Oi  o i, j | j  1,2,... , t

j

(2)

where Pidle is the basic constant power consumption presented by the supplier without load and Oi is a set of supported operations in the state si. Transitions between states can be given as a vector:

t i  So , Sd , Ttrans , E trans ,

(3)

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Sustainability in Manufacturing - Energy Efficiency in Machine Tools

ΔE01, ∆t01

∆E31, ∆t31

Mode 0 Pidle,0

Pidle,1

∆E12, ∆t12

Mode 1

Mode 3 ∆E23, ∆t23

Mode 2

∆E10, ∆t10

A, C

Pidle,3

A, B

∆E21, ∆t21

Pidle,2

∆E32, ∆t32 A, B, C, D

Figure 3: Example of a functional state machine. where So and Sd respectively represent the origin and the destination states, Ttrans is the duration of the transition and Etrans is the amount of energy consumed during the transition. The optimisation problem to reduce losses related to supply excess can be solved by finding the best state trajectory for each set of previewed operations. This can be done by adding the energy costs for idle, transition and operation periods. Once the different possibilities for a specific usage profile (operations progress) are calculated, the minimal cost trajectory that satisfies both time and functional constraints can be selected and performed. Figure 3 shows an example of a functional state machine for a specific common supplier. The numbered states are named “Mode” and the supported operations are called A, B, C and D. In the state “Mode 0” no operation is supported. This could be a low power state used to save energy when machine components are idle and do not demand energy from supplier. For instance, an optimisation scenario could be described as followed: 

Current state is “Mode 2”.



Operation “A” is foreseen beginning in Δtbegin seconds.



5

Further work will also focus on the reduction of consumer losses, as introduced in section 3.1. The main objects of study will be the optimisation of acceleration profiles as well as energy recovery and reutilisation. 6

Both transitions times Δt21 and Δt23 are shorter than Δtbegin.

Considering these constraints, the calculation of energy costs for the possible states is presented in Table 2. The total costs include also the transition costs, in the case of switching to “Mode 1” or “Mode 3”. The lowest total consumption corresponds to the best trajectory for the present scenario. State

Idle

Transition

Operation

Total

Mode 2

Pidle,2 . (∆tA+∆tbegin)

0

PA . ∆tA

2

Mode 1

Pidle,1 . (∆tA+∆tbegin ∆t21)

∆E21

PA . ∆tA

1

Mode 3

Pidle,3 . (∆tA+∆tbegin ∆t23)

∆E23

PA . ∆tA

3

Table 2: Example of energy cost calculation. The modelling and optimisation approach could be enhanced by expanding the definition of operations. It is possible to assign other characteristics like maximum and minimum expected power drains in order to define the best state also in view of transient behaviour.

FURTHER RESEARCH

In order to validate the usability and the completeness of the presented modelling method, simulations are being developed and experiments in typical real machines are planned. Moreover, efforts have been done to define machine operations that have some parameters, like duration or power demand, with a higher degree of uncertainty. For this case, machine learning algorithms are expected to be used, so that the system can learn with its experience, which is perceived by means of the already available data in the machine controller. Following the concept of selfoptimisation, the machine tool will be able to adapt itself to the current production requirements, plan the power balance of energy consumers and reduce energy losses.

SUMMARY

In this paper, energy consumers of typical cutting machine tool constructions were discussed and machine components were structured in order to facilitate the definition of the optimisation problem. After the identification and the classification of energy losses and saving potentials, a novel approach for modelling machine tools in view of self-optimisation of energy consumption was presented. In the proposed method, transitions between states/modes include time and energy consumptions, providing essential information for the optimisation. Instead of defining several operational states, functional states are used to represent the availability of subsystems, and therefore the current supported operations. State selection is done by a supply controller, which optimises the energy consumption depending on the usage profile of the machine tool. 7

ACKNOWLEDGMENTS

The authors thank the German Research Foundation DFG for the support of this research within the “Aachen House of Integrative Production” research initiative. The self-optimisation of machine tools’ energy consumption is being worked within the scope of the Cluster of Excellence "Integrative Production Technology for HighWage Countries" at the RWTH Aachen and at Bosch Rexroth AG.

Sustainability in Manufacturing - Energy Efficiency in Machine Tools 8

REFERENCES

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[1]

Kühnle, J. (2008): Überdimensionierung Industrieanzeiger, Issue 15, pp. 102.

vermeiden,

[2]

Gausemeier, J.; Frank, U.; Giese, H.; Klein, F.; Oberschelp, O.; Schmidt, A.; Schulz, B.; Vöcking, H.; Witting, K. (2004): Selbstoptimierende Systeme des Maschinenbaus: Definition und Konzepte, HNI-Verlagsschriftenreihe.

[3]

Gausemeier, J.; Frank, U.; Schmidt, A.; Steffen, D.; Giese, H.; Klein, F.; Tichy, M. (2005): A Design Methodology for SelfOptimizing Systems, AAET 2005 - Automation, Assistance and Embedded Real Time Platforms for Transportation, Technical University of Braunschweig.

[4]

Gausemeier, J.; Kahl, S.; Radkowski, R. (2010): Selbstoptimierende Produkte – neue Perspektiven zur Steigerung der Energieeffizienz, in: Proceedings of the 1st International Colloquium of the Cluster of Excellence eniPROD, pp. 641-656, Chemnitz, Germany.

[5]

Brecher, C.; Boos, W.; Klein, W.; Kuhlmann, K.; Triebs, J. (2009): Ressourceneffizienzbewertung einer Werkzeugmaschine zur Steigerung ihrer Wirtschaftlichkeit, Werkzeugmaschinen ZWF, Issue 9, pp. 711-715.

[6]

Bittencourt, J.; Landgraf, G.; Bonefeld, R.; Schmitt, R.; Pavim, A. (2010): Model-based monitoring of machine tools energy consumption, in: Proceedings of the International Chemnitz Manufacturing Colloquium 2010, pp. 673-680, Chemnitz, Germany.

[7]

Götze, U.; Koriath, H.-J.; Kolesnikov, A.; Lindner, R.; Paetzold, J. (2010): Energetische Bilanzierung und Bewertung von Werkzeugmaschinen, in: Proceedings of the 1st International Colloquium of the Cluster of Excellence eniPROD, pp. 157-184, Chemnitz, Germany.

[8]

Abele, E.; Kuhrke, B.; Rothenbücher, S. (2010): Maximierung der Energieeffizienz von Werkzeugmaschinen, MM MaschinenMarkt, Issue 9, pp. 26-29.

[9]

Gutowski, T.; Dahmus, J.; Thiriez, A. (2006): Electrical Energy Requirements for Manufacturing Processes, in: Proceedings of the 13th CIRP International Conference on Life Cycle Engineering, Leuven.

[10]

Brecher, C.; Herfs, W.; Heyers, C.; Klein, W.; Triebs, J.; Beck, E.; Dorn, T. (2010): Ressourceneffizienz von Werkzeugmaschinen im Fokus der Forschung, wt Werkstattstechnik online, Issue 7/8, pp. 559-564.

[11]

Neugebauer, R.; Wabner, M.; Rentzsch, H.; Kocourek, P.; Ihlenfeldt, S. (2010): Structure Principles of Energy Efficient Machine Tools, in: Proceedings of the 1st International Colloquium of the Cluster of Excellence eniPROD, pp. 207229, Chemnitz, Germany.

[12]

Dietmair, A.; Verl, A. (2010): Energieeffizienter Betrieb von Produktionsanlagen, in: Proceedings of the 1st International Colloquium of the Cluster of Excellence eniPROD, pp. 185206, Chemnitz, Germany.

[13]

Abele, E.; Kuhrke, B.; Rothenbücher, S. (2010): Entwicklungstrends zur Erhöhung und Bewertung der Energieeffizienz spanender Werkzeugmaschinen, in: Proceedings of the 1st International Colloquium of the Cluster of Excellence eniPROD, pp. 99-120, Chemnitz, Germany.

[14]

Dornfeld, D. A (2010): Sustainable Manufacturing – Greening Processes, Systems and Products, in: Proceedings of the International Chemnitz Manufacturing Colloquium 2010, pp. 99-113, Chemnitz, Germany.

Dietmair, A.; Verl, A. (2009): A generic energy consumption model for decision making and energy efficiency optimisation in manufacturing, International Journal of Sustainable Engineering, Vol. 2, No. 2, pp. 123-133.

Energy-Efficient Machine Tools through Simulation in the Design Process 1

1

Christian Eisele , Sebastian Schrems , Eberhard Abele 1

1

Institute of Production Management, Technology and Machine Tools, Technische Universität Darmstadt, Darmstadt, Germany

Abstract Machine tool manufacturers are increasingly challenged by their customers to quantify the energy consumption of their product during the design process. Therefore the availability of instruments to consider the energy demand already in the early phases of the machine tool conception is essential. This article describes an approach to simulate the energy consumption of machine tools by modeling the energetic interactions of the machine tools’ components. Machine Tool manufacturers can thereby identify the optimization potentials already early in the design process. Exemplarily, components of a machine tool’s coolant system will be modeled and the systems energy consumption will be evaluated. Keywords: Machine Tools; Design Process; Simulation

1

INTRODUCTION

Rising energy and raw material costs are only one of the challenges for manufacturing companies in order to be able to offer competitive products in a global and dynamic market environment. The demand for lower production costs moves also the energy consumption of manufacturing equipment into focus. Especially users in the automotive industry demand more often an indication for new acquisitions of how much energy a machine tool will expectedly consume during operation [1]. The factor “energy efficiency” is therefore another important evaluation criterion for new investment in machinery and equipment in addition to the classical parameters accuracy, performance, cost and reliability. Improving the energy efficiency of their products also leads to a competitive advantage for machinery and component manufacturers. Approaches to increase energy efficiency exist, for example the use of variable speed drives, but are generally associated with higher investment costs and depend significantly on the particular usage profile of the machine tool. Since reliable statements regarding the expected usage profile and the resulting energy demand are difficult to meet during the development process, efficiency potentials are often not fully exploited. Usually this results in the use of lower priced but also more energy-intensive components in machine tools. 2

SIMULATION TO CONSUMPTION

DETERMINE

THE

ENERGY

So far, no methods or tools are available to component respectively machine manufacturers in order to consider the energy consumption of a machine tools on component level already in the early stages of the machine development. Only with the knowledge of the energy consumption, it can be assured that the machine configuration and components with the highest benefit for the entire machines’ lifecycle are selected in the development process. Due to the complete modeling of the system, it can be adequately designed and optimization actions can be fitted specifically to the requirements.

Thus the often existing over dimensioning of components can be avoided. Since over dimensioned components operate below their nominal operating point their efficiency decreases which translates into significantly increased energy consumption. Simulation technologies are already widely accepted in other areas of the machine development and are used for a variety of tasks. Among other benefits, accuracy, speed and reliability were increased with decreasing development costs and time due to the application of simulation tools [2]. Therefore the use of simulation techniques seems to be an appropriate approach to estimate the energy consumption already in the early stages of the product development. In the following sections, the exemplary methods for modeling and simulation of a coolant system of a machine tool (Model VL7, manufacturer EMAG) are presented. The preparation of the simulation first requires an analysis of the system to be simulated, in order to identify those components that affect the energy consumption significantly. The subsequent modeling of the components aims to mathematically represent their energetic characteristics. Physical effects or components which only have a small impact on the energy consumption will be neglected to simplify the modeling process. The coolant system which is to be simulated is schematically displayed in Figure 1. The coolant medium is delivered through the pump and piping to the outlets, for example the tools. The 2/2-wayvalves allow to connect or disconnect individual functions of the coolant system. A direct connected three-phase AC induction motor drives the pump. 3

MODELLING SYSTEM

AND

SIMULATION

OF

THE

COOLANT

Primarily, the simulation models of the components must guarantee a proper handling and a sufficiently accurate quantification of the energy consumption. To reproduce the real behavior of the components exactly is not object of the simulation, only major factors that influence the energy consumption will be included. In addition, due to the practical usability of the simulation tool during

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_45, © Springer-Verlag Berlin Heidelberg 2011

258

Sustainability in Manufacturing - Energy Efficiency in Machine Tools the development process, all parameters for the simulation have to

259 The flux equations for rotor and stator were given by [3], [4]:

 s  Ls  Lh   i s  L h  i r

Energetic relevant system components

 s  Ls  L h   i s  Lh  i r

Turret

(2)

r  Lr  Lh   i r  Lh  i s

Spray Nozzles

Lathe chuck

r  Lr  Lh   i r  Lh  i s

Ls , Lr : Stator and rotor leackage inductances Lh : Magnetizing inductance

Main casting flushing

Working chamber flushing

With the calculated currents of rotor and stator combined with the following equation

Turret flushing

M el 



3  p  s  is  s  is 2



(3)

M el : electrical moment p : number of pole pairs

Pipes Rohrleitungen

Induction Motor N = 3.0 kW n = 2840 1/min U = 400V / 50Hz

the electrical torque can be calculated [3], [4]. Using the equilibrium of moments, the load torque and the rotation speed dependent losses, e.g. friction, can be accounted for.

Centrifugal Pump 8bar 80l/min



Figure 1: Schematic figure of coolant system with energetic relevant components. be on hand. If appropriate and available, characteristic curves or mathematical equations were used for the modeling of the coolant system components’. Modeling

AC Induction Motor For modeling of the AC induction motor, the three stator voltages shall be used as input variables. The voltages are transformed in a rotor fixed coordinate system by Clarke transformation in order to have easier to handle equations for modeling. The voltage equations for stator and rotor were calculated by using the following formulas [3], [4]:

d  s dt d U s  R s  i s    s dt d 0  R r  i r   r      r  dt d 0  R r  i r    r     r dt U s  R s  i s  

U s , i s :  axis stator voltage and current U s ,i s :  axis stator voltage and current R s , R r : Stator and rotor resistance s , s : Stator  and  axis fluxes r , r : Rotor  and  axis fluxes  : Angular velocity

(4)

M L : load torque

Coolant

3.1

d  Me  ML   D dt

(1)

D : factor of speed dependent losses

 : inertia The values for the motor parameters must be either requested by the motor manufacturer or can be calculated with type plate data which is not as exact as having the original values [5]. Centrifugal Pump The centrifugal pump is modeled by a characteristic diagram model, as the energetic and characteristic behavior is completely characterized by it. Characteristic diagrams for centrifugal pumps of pressure-dependent delivery heights and the corresponding required shaft power is provided in the data sheet of the pump published by the pump manufacturer. The implementation of the characteristic diagram is done by approximating the curve with interpolation methods. Therefore four equidistant nodes have to be extracted from each diagram. With the method of polynomial curve fitting, the coefficients of a third degree polynomial curve are determined. Beyond the range of the node data, linear extrapolation was used which is subject to a greater degree of uncertainty [6]. Since the provided characteristic curves in the data sheet were recorded at a certain reference density of the fluid and a certain reference angular velocity, it is necessary to use affinity laws in order to simulate systems with other velocities or fluid density. The delivery rate can be calculated with [7]:

q  q ref 

  ref

q : pump delivery q ref : pump reference delivery

 : angular velocity  ref : reference angular velocitiy

(5)

260

Sustainability in Manufacturing - Energy Efficiency in Machine Tools

The pressure of the pump with different density and angular velocity was modeled according to the following equation [7]:

whereas the equation to model the friction factor for turbulent flow is

H  H ref 

  ref

     ref 

   

2

(6)

based on the Haaland equation [9][10].

fT 

H : pump delivery height H ref : pump delivery height reference

P  Pref 

 ref

   

Spray Valves

3

(7)

The spray valves at the end of the pipes can be modeled as a local flow resistance with abrupt cross section geometry. The pressure losses can be modeled according to the orifice formula [10]. 2

Pref : referencepump brake power

p 

Pipes The pressure loss in the pipes due to friction was modeled according to the Darcy-Weisbach-equation [8].

l    q2 d 2  A2

(8)

f L : friction factor laminar flow Re : Reynolds Number

Δp : pressure loss

 : flow coefficien t A : orifice Area

 : fluid density

2/2-Way-Valves

The losses are a function of the flow rate and a friction factor which is dependent on laminar or turbulent flow. Also the pipe geometry and the fluid density is considered in the equation. The friction factor for laminar flow was modeled according to the following equation [8]:

k : geometric form factor (k  64 for circular pipes)

(11)

The value of the flow coefficient depends on the geometrical properties of the orifice and is usually provided in textbooks.

q : fluid flow rate

k Re

1    2   q 2   A

q : fluid flow rate

Δp : pressure loss f : friction factor l : length of pipe d : pipe diamter A : pipe cross Area  : fluid density

fL 

(10)

d : pipe diameter Re : Reynolds Number

P : pump brake power

p  f 

2

r : pipe surface roughness height

With the following formula, the brake power can be determined [7]:

     ref 

1.11       1.8 log  6.9   r     10     Re  3.7 d    

f T : friction factor turbulent flow

 : fluid density  ref : reference fluid density



1

(9)

The valves in the system are used to regulate the flow to the spray valves. As the spray valve, they represent a flow resistance in the hydraulic system. For calculation of the flow rate through the orifice, the orifice formula (see 11) is used. The passage Area is dependent on the position of the valve. When the valve is closed, a small leakage area is assumed to exist which represents the clearance of the physical slide valve.

A A O  AL

for valve open for valve closed

(12)

AO : Valve opening Area AL : Valve leackage Area The value of the flow coefficient is usually provided in manufacturer datasheets.

Sustainability in Manufacturing - Energy Efficiency in Machine Tools

261

Measurements

Simulation 3000 3

Electr. Power [kW]

Electr. Power [kW]

3000 3 2000 2

2000 2

1000 1

1000 1

0 0

50

100

150

200

250

300

80 60 40 20 0 0

50

100

150

200

250

150

200

250

300

50

100

150

200

250

300

50

100

150

200

250

300

60 40 20

10

Pressure [bar]

Pressure [bar]

100

80

0 0

300

10 8 6 4 2 0 0

50

100

Flow rate [l/min]

Flow rate [l/min]

100

00 0

50

100

150

200

250

8 6 4 2 0 0

300

Time [s]

Time [s]

Figure 2: Power measurements (left) and simulation results (right) for the machining cycle of a test workpiece. 3.2

Simulation

Subsequently, the components were computed with Simscape language, which is based on Matlab. The use of Simscape offers the advantage that simulation models of mechatronic systems can be built on the basis of their existing physical network. Thus an easy handling of the simulation model is assured for the designer when configuring the simulation model. In addition, Simscape components can be easily integrated into a library structure which ensures a good reusability of the simulation models. In order to determine the system’s energy consumption, a machining cycle of a test workpiece was simulated. As extensive performance measurements of various function modules during the machining cycle were part of the first project phase [11], this data can now be used for the verification of the simulation model. On the left side of Figure 2, the measurement results of the time profile of the measured flow rate and pressure of the centrifugal pump as well as the electrical power consumption of the induction motor are presented. For comparison reasons, the simulation results are displayed on the right side of Figure 2. As can be seen, a good conformity of the measured data and the simulation results can be recognized. When comparing the simulated electrical power consumption of the induction motor with the measured, the deviation is below 5%, which can be regarded as sufficiently accurate.

4

EVALUATION OF ENERGY-EFFICIENCY MEASURES

With the simulation model of the coolant system, it is now possible to select various component configurations and to use the simulation results of different variants in order to evaluate their potential savings in terms of energy efficiency. By the use of a centrifugal pump of another manufacturer and the application of an induction motor with the higher efficiency class Eff1, the potential savings of these actions will be exemplarily conducted. The requirement for selecting the components was, that the same performance measures, in terms of flow and pressure for the pump as well as speed and torque for the induction motor, as before can be met. Figure 3 shows the electrical power consumptions of both variants for the already known machining cycle of the test workpiece. For reason of comparisons, the power consumption of the system that was not optimized is also diagrammed in gray. In both cases the energy consumption of the system was reduced. If the average power consumption of 1.91 kW of the original system is used as basis, the demand of energy was reduced by 3.7% to 1.84kW during the machining cycle. By application of the optimized pump an improvement of 18.3% and an average power consumption of 1.56kW were achieved.

Sustainability in Manufacturing - Energy Efficiency in Machine Tools

Optimized Pump

3

2

1

0 0

Optimized System Initial System

50

100

150

200

250

Electr. Power [kW]

Electr. Power [kW]

262

2

1

0 0

300

Time [s]

Eff1-Motor

3

Optimized System Initial System

50

100

150

200

Time [s]

250

300

Figure 3: Simulation results of different component configurations. 5

SUMMARY AND CONCLUSIONS

The ability to determine the energy consumption of machine components already in the early stages of the development process is an important step on the way to the energy efficient machine tool. With this knowledge, it is possible to analyze and compare different machine configurations in their energetic performance and to optimize the machine tool accordingly. Based on the illustrated example of a machine tool coolant system, it was shown that the energy consumption of this system can be calculated with simulation models without the need of expensive and time intensive power measurements. Also different optimization measures can be evaluated in terms of cost and energy saving potentials. By modeling other components of the machine tools function modules’ as well, it will be possible to calculate the energy consumption of the entire machine tool in the future. Based on these results, further optimization potentials can be identified, such as the intelligent control of auxiliary units or a process customized component and equipment sizing. 6

Törnig, W.; Spellucci, P. (1990): Numerische Mathematik für Ingenieure und Physiker II - Eigenwertprobleme und numerische Methoden der Analysis, Springer Verlag, Berlin, München.

[7]

Gülich, J. F. (2010): Kreiselpumpen - Handbuch für Entwicklung, Anlagenplanung und Betrieb, Springer Verlag, Berlin, München.

[8]

Watter, H. (2008): Hydraulik und Pneumatik – Anwendungen und Simulation, Vieweg + Teubner, Wiesbaden.

[9]

Haaland, S. (1983): Simple and Explicit Formulas for the Friction Factor in Turbulent Flow, Journal of Fluids Engineering (ASME), Vol. 103, No. 5, pp. 89–90.

[10]

Jelali, M.; Kroll, A. (2004): Hydraulic Servo Systems – Modeling, Identification and Control, Springer Verlag, London.

[11]

Rudolph, M.; Abele, E.; Eisele, C.; Rummel, W. (2010): Analyse von Leistungsmessungen als Beitrag zur Untersuchung der Energieeffizienz von Werkzeugmaschinen, Zeitschrift für Wirtschaftlichen Fabrikbetrieb: ZWF, Carl Hanser Verlag, München, Vol. 110, pp. 876-882.

ACKNOWLEDGMENTS

The authors gratefully acknowledge the financial support of the Federal Ministry of Education and Research (BMBF) and the project supervision of the Project Management Agency Forschungszentrum Karlsruhe, Divison Production and Manufacturing Technologies (PTKA-PFT) for the project e-SimPro – Energieeffizienz von Produktionsmaschinen durch Simulation in der Produktentwicklung (Energy efficient production machines through simulation in the product development process. 7

[6]

REFERENCES

[1]

Kuhrke, B.; Erdle, F. (2010): Energieeffizienz als Investitionskriterium, in: Werkstatt + Betrieb : WB, Carl Hanser Verlag, München, Vol. 143, No.1-2, pp. 30-32.

[2]

Zirn, O.; Weickert, S. (2009): Modellbildung und Simulation hochdynamischer Fertigungssysteme, Springer Verlag, Berlin, München.

[3]

Schröder, D. (2009): Elektrische Antriebe – Grundlagen, Springer Verlag, Berlin, München.

[4]

Fuest, K.; Döring, P. (2007): Elektrische Maschinen und Antriebe, Vieweg Verlag, Wiesbaden.

[5]

Quang, N. P., Dittrich, J. A. (1999). Praxis der feldorientierten Drehstromantriebsregelungen, Expert-Verlag, Ehningen bei Böblingen.

8

CONTACT

Christian Eisele Institute of Production Management, Technology and Machine Tools (PTW), Technical University of Darmstadt, Germany. [email protected]

Energy Consumption Characterization and Reduction Strategies for Milling Machine Tool Use 1

1

1

Nancy Diaz , Elena Redelsheimer , David Dornfeld 1

Laboratory for Manufacturing and Sustainability, University of California at Berkeley, USA

Abstract Since machine tools are used extensively throughout their functional life and consequently consuming valuable natural resources and emitting harmful pollutants during this time, this study reviews strategies for characterizing and reducing the energy consumption of milling machine tools during their use. The power demanded by a micromachining center while cutting low carbon steel under varied material removal rates was measured to model the specific energy of the machine tool. Thereafter the power demanded was studied for cutting aluminum and polycarbonate work pieces for the purpose of comparing the difference in cutting power demand relative to that of steel. Keywords: Green Machine Tools; Energy Consumption Reduction; Specific Energy Characterization

1

INTRODUCTION

A product undergoes three life-cycle stages: manufacturing, use and end-of-life. Consumer products whose environmental impact is dominated by the use phase include light fixtures, computers, refrigerators, and vehicles, in general products that are used extensively during their functional life. All the while these products consume resources, in particular energy in the form of electricity or fuel. The machine tool is one such product. The use phase of milling machine tools has been found to comprise between 60 and 90% of CO2-equivalent emissions during its life cycle [1]. This study presents a method for predicting the electrical energy consumed in manufacturing a product for the purpose of reducing its environmental impact. In conducting a life cycle assessment, product designers may choose to opt for a process, economic input-output (EIO), or hybrid approach. The drawback of the process LCA, though, is that because this method entails acquiring process-specific data it is time consuming and therefore resource intensive. An alternative to measuring the machine tool’s electrical energy consumption directly, for example, is to use aggregate data as is done with EIOLCA [2]. An EIO-LCA, therefore, is not specific to the design of a particular product. The strategies presented herein provide a method for more quickly generating manufacturing energy consumption estimates for a particular product. 1.1

Cutting load profile

As described by Diaz et al. in [3] the power demand of a machine tool is comprised of cutting, variable, and constant power components. The cutting power is the additional power drawn for the removal of material. The machine tool used in this analysis, the Mori Seiki NV1500 DCG, is a micromachining center with a relatively low standby power demand when compared to large machining centers. Therefore, the cutting power can comprise a large portion of the machine tool’s total power demand. Energy consumption for high tare machine tools was found to be primarily dependent on the processing time of the part, which is dictated by the part geometry, toolpath, and material removal rate.

One such method for optimizing the tool path for minimum cycle time was presented in [4]. This paper is concerned with the effect of the material removal rate on energy consumption. The material removal rate for a 3-axis machining center can be varied by changing the feed rate, width of cut, or depth of cut. Since increasing the feed rate was found to have dire consequences on the cutting tool life [5], the experiments conducted herein varied material removal rate through width of cut and depth of cut experiments for the purpose of analyzing the material removal rate’s effect on cutting power and more importantly, energy consumption. Although increases in the material removal rate translate to faster machining times, the loads on the spindle motor and axis drives increase as well, resulting in higher power demand. Since our main interest is energy consumed in product manufacture, the trade-off between power demand and machining time was analyzed to confirm that the increased loads due to faster material removal was not increasing the total energy consumed. 2

POWER DEMAND FOR VARIED M.R.R.’S

Since machine tool programmers and operators have an array of options when defining the process plan for part production, this analysis strives to reduce energy consumption by process parameter selection of a machine tool. Specifically, the parameters concerning material removal rate (M.R.R.) were varied on a Mori Seiki NV1500 DCG while selecting appropriate tooling. The power demand was measured with a Wattnode MODBUS wattmeter. In previous work, experiments were conducted in which spindle speed, feed rate, feed per tooth, and cutter type were varied to analyze the change in energy consumption while milling a low carbon steel, AISI 1018 steel [5]. Also, [6] conducted experiments on face milling, end milling, and drilling operations in which the energy consumption, machining cost, and tool wear were compared for increased cutting speeds. Tool wear and, consequently, cutting tool cost increased significantly when the process parameters veered away from the recommended cutting conditions. So in the

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_46, © Springer-Verlag Berlin Heidelberg 2011

263

264

Sustainability in Manufacturing - Energy Efficiency in Machine Tools

following experiments the cutting tool type was changed to maintain the recommended process parameters, but reduce energy consumption while machining, nonetheless.

Figure 2 shows the average power demand of the NV1500 DCG for cutters (1) – (3). The relationship between power and M.R.R. shifts from parabolic to linear in moving from the conditions imposed on cutter (1) to cutter (3). The increase in power demand is the greatest for cutter (3), but the load on the spindle motor and axis drives is also much greater than that of the 2 flute cutting tools since the feed rate is twice as large or greater.

2.1

Width of Cut Experiments

Given the energy savings from changing the cutter type this project focused on varying material removal rate. First the width of cut was increased while machining with a: 1. 2 flute uncoated carbide end mill, 2. 2 flute TiN coated carbide end mill, and 3. 4 flute TiN coated carbide end mill. Peripheral cuts were made along the y-axis at a depth of cut of 2 mm with an 8 mm diameter end mill over a length of 101 mm in a 1018 steel work piece. The width of cut was varied by 1 mm increments between 1 mm and 7 mm, in addition to a 7.5 mm width of cut. Table 1 summarizes the cutting conditions used. The chip load was maintained at approximately 0.03 mm/tooth to avoid excessive tool wear and breakage. Spindle Speed Cutter [

rev ] min ute

Feed Rate

[

Chip Load

mm ] min ute

[

mm ] tooth

M.R.R.

[

mm 3 ] sec ond

(1)

5426

330

0.033

11 - 83

(2)

7060

430

0.030

14 - 108

(3)

7060

860

0.030

29 - 215

Table 1: Process parameters for width of cut experiments. Once the power was measured for each width of cut experiment, the power demand was measured for the machine tool while air cutting, that is, while running the toolpath without material removal. This way the power associated with the material removal process could be extracted, known hereafter as the cutting power demand. The average air cutting power demand was found to be 1510 W for the cutter (2) process parameters, so it was subtracted from the average total power demand. Figure 1 shows the cutting power demand as a function of the M.R.R. for cutter (2). This plot has a slightly parabolic trend with a point of inflection at approximately 75 3 mm /s. The cutting power demand for the 7.5 mm width of cut was almost nine times greater than the 1 mm width of cut. Since the total air cutting power demand was only 1510 W, though, the resulting increase in total power demand of the machine tool was only 28%. Thus in terms of energy consumption, the operator still experiences energy savings with the increase in M.R.R.

Cutting Power [W]

450

430 W

400

367 W

350 300

281 W

250 200

206 W

150

149 W

100 0

Depth of Cut Experiments

Depth of cut experiments were also conducted on a 1018 steel work piece 101 mm in length. Cuts were made along the y-axis using 8 mm diameter, 2 flute uncoated and TiN coated carbide end mills under near slotting conditions (a width of cut of 7.5 mm). The power demand was measured at depths of cut of 1, 2, 4, and 8 mm. The chip load was maintained constant across the various cutters at 0.051 mm/tooth. The spindle speed and feed rate were varied, though, to account for higher loads on the machine tool during the depth of cut experiments (see Table 2 for a summary of the processing conditions). Spindle Speed Cutter [

rev ] min ute

Feed Rate [

mm ] min ute

Chip Load [

mm ] tooth

M.R.R. [

mm 3 ] sec ond

(1)

2500 - 3200

254 - 325

0.051

40 - 250

(2)

3250 - 4160

330 - 425

0.051

50 - 330

Table 2: Process parameter ranges for depth of cut experiments.

500

50

Figure 2: Average total power demand as a function of M.R.R. 2.2

106 W 34 W 0

58 W 50

100

MRR [mm^3/s] 2 flute TiN Coated Carbide

Average

Figure 1: Cutting power demand using cutter (2) while cutting 1018 steel.

Figure 3 summarizes the power demanded by the NV1500 DCG for the 2 flute TiN coated end mill (cutter (2)) and the energy consumed as a function of material removal rate. Although the power demand increases with load the energy consumption still drops drastically with the increase in material removal rate. The machine tool experiences a power demand increase of approximately two-thirds, whereas the energy consumption reduces to less than one-third of its original value. This shows that the decrease in processing time effectively dominates over the increase in power demand due to increased loads. Since the power demand was shown to increase with load, and experimentally this increase in load was not enough to increase the overall energy consumption, the trade-off between power demand and processing time will be analyzed.

Sustainability in Manufacturing - Energy Efficiency in Machine Tools 200

3,000

180

Energy [kJ]

140

2,000

120 100

1,500

80

1,000

60 40

500

20 0

Power Demand [W]

2,500

160

0 0

100

200

300

400

MRR [mm^3/sec] Energy

Power

Figure 3: Energy and power demand as a function of M.R.R. for depth of cut experiments with cutter (2). 2.3

Trade-off Between Power Demand and Processing Time

The machine tool’s electrical energy consumption is dependent on the power demand, pavg, and processing time, ∆t, as seen in Equation 1. Since the power demand shows some variability due to the internal cooling unit of the machine tool, the average power demand, pavg, will be used. As was mentioned previously, the average power demand is composed of a cutting, pcut, and air cutting, pair, component; consequently the energy consumption can be expanded as follows:

e  pavg * t  ( pcut  pair ) * t

(1)

Two scenarios will be compared. Scenario (1) is the base scenario, while scenario (2) will be the scenario in which the material removal rate is increased for the purpose of reducing processing time. The constants, α and β, were created to represent the increase in pcut and decrease in ∆t, respectively (see Equations 2 and 3). Note that both constants are less than unity.

pcut 1





(2)

pcut 2

t 2 t 1

(3)

Equation 4 shows the relationship between pavg1 and pavg2, which assumes that the air cutting power demand, pair, remains relatively constant for both scenarios.

pavg 1   * pavg 2  pair * (1   )

265 with large work volumes which have a high standby power demand. Further work can be conducted in which the assumption that the air cutting power demand does not stay constant to expand the applicability of the power and processing time trade-off analysis. 3

CHARACTERIZING THE SPECIFIC ENERGY

The specific energy of various manufacturing processes was previously summarized by Gutowski et al. [7], but for any given manufacturing process the data was limited to only a sample of process rates. This study, though, will focus on milling machine tools and the operable range of the machining center when characterizing the specific energy. In characterizing the energy consumption of a machine tool, as the M.R.R. approaches infinity the specific energy is expected to reach a steady state of zero. But, given the work volume, spindle speed, and table feed constraints of a machine tool as well as the maximum loads that can be applied without deforming the main body frame or breaking the spindle motor, the operator will never reach a M.R.R. anywhere near infinity. So under the constraints of the M.R.R. a curve of the following form:

ecut  k *

1 b M .R.R.

was fit to the data from the width of cut and depth of cut experiments. Note that the constant, k, essentially has units of power and b represents the steady-state specific energy. The total specific energy, which accounts for cutting and air cutting power demand, was indeed found to have an inverse relationship with the M.R.R. (see Figure 4). The air cutting power demand dominated the specific energy. The impact of the cutting power demand on the specific energy was minimal since at high loads (i.e. at high M.R.R.’s) the machining time decreased significantly. The specific energy decreases rapidly until a M.R.R. of 3 approximately 75 mm /s is reached. For M.R.R.’s lower than 75 3 mm /s, a slight increase in the material removal rate causes a sharp drop in the specific energy because machining time improves 3 dramatically. At M.R.R.’s greater than 100 cm /s, the gain from increasing the process rate is minimal since the specific energy begins approaching a steady-state value. This gain could be significant for work pieces requiring a substantial amount of material removal, but since the machine tool used in this study is a 3 micromachining center a M.R.R. greater than 100 mm /s would show only a minor decrease in energy consumption given standard work piece sizes.

(4)

If the relative size of the air cutting power demand is denoted by:

i 

pair i pavg

(5) i

where i is 1 or 2 for scenarios 1 and 2, respectively, then the inequality presented in Equation 6 shows the condition that must be met in order for the energy consumption of scenario (2) to be smaller than that of scenario (1). 2 

 1 

(6)

So if β is less than α, then e2 will always be less than e1. Also, as η2 increases (i.e. if the air cutting power demand comprises a large portion of the total power demand) then the probability of e2 being less than e1 increases. This would be the case for machine tools

(7)

Figure 4: Specific energy as a function of M.R.R.

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Sustainability in Manufacturing - Energy Efficiency in Machine Tools

The best fit model was found to be:

results. The process parameters used in the experiment are outlined in Table 3.

e cut  1481 *

1  3.678 M.R.R.

(8)

where the first constant, a, is similar to the average air cutting power demand values. As was expected, the specific energies at low M.R.R.’s had such large variations (due to the internal cooling unit) that they surpassed the bounds of the model, but at high M.R.R.’s the specific energies were well within the bounds. Upper and lower bounds with a 95% confidence level are provided below: 1 e cut  1478 *  3.541 M.R.R.

(9)

1 e cut  1488 *  3.853 M.R.R.

The machine tool analyzed in this paper is a micromachining center. Larger machine tools can process material at higher rates, therefore shifting the specific energy curve to the right. But these machine tools will also have higher standby power demand due to the peripheral equipment [8] causing an upward shift in the specific energy curve (see Figure 5).

Specific Energy

 

Macro

Material Removal Rate

The aforementioned experiments were conducted with a low carbon steel work piece. The type of material being machined is also a factor in the cutting power demand of the machine tool, though. A plastic work piece, for example, is expected to generate a smaller load on the spindle motor than a metal work piece and therefore result in a lower cutting power demand. Since the cutting load is expected to vary with the work piece material, the following experiments were conducted to measure the power demand of the Mori Seiki NV1500 DCG while machining peripheral cuts on 1018 steel, 6061 aluminum, and polycarbonate. A depth of cut and width of cut of 2 mm and 4 mm, respectively, was used. The chip load of 0.0254 mm/tooth was maintained constant across the experiments, to allow for the comparison of the

Polycarbonate

[

mm ] tooth

0.0254

0.0254

0.0254

[

mm ] min ute

248

621

310

Spindle Speed

[

rev ] min ute

4889

12223

6112

M.R.R.

[

mm 3 ] sec ond

44

82.8

41.3

Table 3: Process parameters for power demand experiments with multiple work piece materials. The recommended cutting speed varied with the work piece material. Aluminum was cut at the highest speed, followed by polycarbonate, then steel. The use of coolant while machining aluminum was recommended by the cutting tool manufacturer due to the material’s ductility and its tendency to build-up on the cutting tool. Coolant was also recommended for polycarbonate to prevent it from melting because of the high temperature at the cutting tool and work piece interface. Steel can be cut without coolant (which would greatly reduce the total power demand of the machine tool), but since cutting fluid aids with chip exit and this study is primarily concerned with the cutting power demand, coolant was used when cutting all material types. The power demand of the NV1500 DCG is shown in Figure 6, and is broken down into cutting and air cutting power demand. The air cutting power demand is approximately the same across the three processing conditions. The difference is due primarily to the change in spindle speed, the highest of which was used while cutting aluminum. The difference in the power demanded by the axis drives was found to be negligible even though the feed rate for aluminum is more than two times that of steel. The cutting power demand shows greater variability for the three work piece materials. The cutting power was the greatest while machining the steel work piece. In fact, it was approximately 7% of the total power demand. This may be due to the fact that it has the highest tensile strength, followed by aluminum, then polycarbonate. The cutting power while machining the polycarbonate work piece was the smallest and almost negligible, only 1% of the total power demand. 1800

Power Demand [W]

EFFECT OF WORK PIECE MATERIAL ON POWER DEMAND

6061 Aluminum

Feed Rate

Figure 5: Shift in specific energy plot for larger machine tools. 4

1018 Steel

Units

Chip Load

(10)

This specific energy model can be used to estimate the total energy consumed while cutting. The part features and tolerances would dictate the size and type of machine tool required for part manufacture. The optimal M.R.R. can be determined using standard process parameters based on the work piece material and the appropriate cutting tool for the feature creation. Therefore, the total energy consumption while cutting can be calculated by multiplying the specific energy estimate by the volume of material removed.

Nano Micro

Parameter

1600 1400

117

87

14

1450

1500

1470

1200 1000 800 600 400 200 0 Steel Cutting Power

Aluminum

Polycarbonate

Air Cutting Power

Figure 6: Power demand of NV1500 DCG for steel, aluminum, and polycarbonate work pieces.

Sustainability in Manufacturing - Energy Efficiency in Machine Tools

267

A particular work piece material can be machined at a range of process parameters while maintaining minimal tool wear and good surface finish. So future experiments should be conducted in which the material removal rates overlap as much as possible across the work piece materials under study when calculating the cutting power demand for the purpose of comparison. Also, the power demand of the spindle motor and the axis feed drives should be measured directly since presently the cutting power demand is obtained by subtracting the air cutting power demand from the total power demand of the machine tool.

Machine Tool Technologies Research Foundation (MTTRF2009) 2009 Annual Meeting, pp. 47-50, Shanghai, China.

5

The specific energy model allows a product designer to estimate the manufacturing energy consumption of their part’s production without needing to measure power demand directly at the machine tool during their part’s production. Since the specific energy as a function of M.R.R. for the micromachining center presented herein varied by as much as an order of magnitude, it is important to use process parameters and machine tool-specific data to determine accurate electrical energy consumption. This model could therefore be used in place of aggregate embodied energy values for manufacturing processes as provided by [9] or to replace process estimates with great uncertainty when conducting hybrid life cycle assessments. ACKNOWLEDGMENTS

This work was supported in part by Mori Seiki, the Digital Technology Laboratory (DTL), the Machine Tool Technologies Research Foundation (MTTRF), Kennametal, and other industrial partners of the Laboratory for Manufacturing and Sustainability (LMAS). The authors would like to thank the UC Berkeley Mechanical Engineering Department’s Student Machine Shop for providing valuable insight and advice. For more information, please visit lmas.berkeley.edu. 7

Inamasu, Y.; Fujishima, M.; Hideta, M.; Noguchi, K. (2010): The Effects of Cutting Condition on Power Consumption of Machine Tools, in: Proceedings of the 4th CIRP International Conference on High Performance Cutting (HPC2010), Vol. 1, pp. 267-270, Gifu, Japan.

[7]

Gutowski, T.G.; Liow, J.Y.H.; Sekulic, D.P. (2010): Minimum Exergy Requirements for the Manufacturing of Carbon Nanotubes, IEEE International Symposium on Sustainable Systems and Technology (ISSST2010), Washington, D.C.

[8]

Behrendt, T. (2010): Development of a Simulation-Based Application to Derive and Estimate Potentials of Efficiency Measures for Diverse Machine Tool Processes, Diploma Thesis, Braunschweig University of Technology.

[9]

Ashby, M.F. (2009): Materials and the Environment: Ecoinformed Material Choice, Butterworth-Heinemann, Burlington, MA, USA.

CONCLUSIONS

This study has shown that the machining time dominates energy demand for high tare machine tools. Additionally, it has provided a method for characterizing the specific energy of a machine tool as a function of process rate, which can be extended to other types of manufacturing processes.

6

[6]

REFERENCES

[1]

Diaz, N.; Helu, M.; Jayanathan, S.; Chen, Y.; Horvath, A.; Dornfeld, D. (2010): Environmental Analysis of Milling Machine Tool Use in Various Manufacturing Environments, IEEE International Symposium on Sustainable Systems and Technology (ISSST2010), Washington, D.C.

[2]

Carnegie Mellon University Green Design Institute. (2010): Economic Input-Output Life Cycle Assessment (EIO-LCA), Available from: http://www.eiolca.net/

[3]

Diaz, N.; Choi, S.; Helu, M.; Chen, Y.; Jayanathan, S.; Yasui, Y.; Kong, D.; Pavanaskar, S.; Dornfeld, D. (2010): Machine Tool Design and Operation Strategies for Green Manufacturing, in: Proceedings of the 4th CIRP International Conference on High Performance Cutting (HPC2010), Vol. 1, pp. 271-276, Gifu, Japan.

[4]

Rangarajan, A.; Dornfeld, D. (2004): Efficient Tool Paths and Part Orientation for Face Milling, in: Annals of the CIRP, Vol. 53, No. 1, pp. 73-76.

[5]

Diaz, N.; Helu, M.; Jarvis, A.; Tönissen, S.; Dornfeld, D.; Schlosser, R. (2009): Strategies for Minimum Energy Operation for Precision Machining, in: Proceedings of the

An Investigation into Fixed Energy Consumption of Machine Tools 1,2

1,3

1,2

Wen Li , André Zein , Sami Kara , Christoph Herrmann

1,3

1

Joint German-Australian Research Group in Sustainable Manufacturing and Life Cycle Management

2

School of Mechanical and Manufacturing Engineering, Life Cycle Engineering and Management Research Group, The University of New South Wales, Sydney, Australia

3

Institute of Machine Tools and Production Technology (IWF), Product- and Life-Cycle-Management Research Group, Technische Universität Braunschweig, Germany

Abstract Improving energy efficiency of manufacturing processes requires knowledge about the energy consumption as a function of the machine tool and cutting process itself. Both theoretical and empirical models of unit process energy consumption have emphasized the relevance of fixed energy consumption which ensures the machine readiness. However, the machine tool behavior during the stand-by mode is lack of thorough study. This paper presented the investigation of fixed energy consumption from definition and description to improvement strategies. Six machine tools covering different manufacturing processes are selected for this investigation in order to evaluate the future savings. Keywords: Machine Tools; Fixed Power; Energy Consumption

INTRODUCTION

The reduction of electrical energy demands in the use phase of machine tools is an essential key to improve the environmental performance over the entire life cycle. Preliminary environmental studies for machine tools used in discrete part manufacturing (e.g. turning and milling) indicate that more than 99% of the environmental impacts are due to the consumption of electrical energy [1]. Although the use of electrical energy is crucial from the environmental and also the economic point of view, studies are primarily based on rough estimates considering averaged demands. In order to increase the reliability, case-specific energy demands of machine tool processes are presently measured and transformed into models supporting the quantification of energy demands [2]. Traditional estimation of cutting energy for turning and milling processes is based on process parameters, which has been a starting point for the optimization of machining processes under energetic aspects as well as the derivation of capacity requirements for the machine tool [3]. As this method is restricted to the cutting process and solely capturing the energy for material removal, the unavoidable energy demand ensuring an operational readiness of the machine tool is yet disregarded. Recent theoretical exergy framework and empirical models of unit process energy consumption have emphasized the relevance of fixed energy consumption which ensures the machine readiness [45]. More importantly, the fixed power demands continuously accumulate the total energy consumption throughout the work shift. However, the machine tool behaviour during the stand-by period is lack of thorough studies. This paper investigates the energy consumption of the machine tool for reaching and remaining operational readiness. The initial point therefore is the definition of a fixed power demand of a machine tool. Starting from this definition, the fixed power demands of six machine tools covering three different manufacturing processes are physically measured and analysed. The fixed power demands are described on a component basis by considering the machine configuration and given power demands of components. Within the detailed information, the energy requirements of machine

availability are discussed as an enabler to promote energy efficiency of machine tools. 2

FIXED ENERGY DEMAND OF MACHINE TOOLS

2.1

Definition of Fixed Energy Demand of Machine Tools

The energy consumption of a machine tool results from the temporal power demand which is not static but rather dynamic throughout a machining process. It is influenced by the design of the process and the selected machine tool. Power meters enable to capture the specific power demand of a machining process which consequently provides a basis to recognize actions (e.g. acceleration of spindles). Reviewing the power profile of an exemplary turning process in Figure 1, the start-up of the machine, spindle and material removal as well as the resulting power states can be determined [4]. With consideration of these states the power demand can generally be differentiated into a variable and a constant portion [5]. 8000

7000

6000

Effective Power (W)

1

Spindle Accelerate

5000

4000

Spindle Start

3000

Material Removal start

Unproductive Power Tool Tip Power

Ready for Operation

2000

Operational Power Fixed Power

Machine Start

1000

Machine Switch Off

0 1

101

201

301

401

501

Time 601

701 (0.1S)

Figure 1: Power profile of a turning process [4].

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_47, © Springer-Verlag Berlin Heidelberg 2011

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Sustainability in Manufacturing - Energy Efficiency in Machine Tools

269

The variable power considers the process-related demand to conduct the machining operation. This includes not only the power required for removing material but also the process-depended operation of components (e.g. spindle rotation and movement of axis). Apart from that, the constant power demand resumes the fixed, machine-related power ensuring a functional mode of operation (ready for operation) [3]. While the variable power aggregates the power demand of motors and spindles enabling the material removal, the fixed power demand also includes the power demand of operating components as motors and spindles [6]. These devices are energized to maintain in position. With regard to components and supporting a better understanding of the power demands (see Figure 1), an extension to the given power classification is proposed considering the following four power segments [4]:



Time for operational readiness: duration from machine start-up until all the indispensable components are activated to ensure operational readiness.



Energy consumption for start-up: the total energy consumption during the start-up period.



Fixed power: as defined before, it can be used to estimate energy consumption of remaining machine availability.



Time for machine power-off: duration from machine switch-off until every component is inactivated.



Energy consumption for power-off: consumption during the power-off period.

3

DESCRIPTION OF FIXED POWER DEMAND



Fixed power: power demand of all activated machine components ensuring the operational readiness of the machine tool;



Operational power: power demand to distinctively operate components (e.g. move axis or rotate spindle) enabling the cutting as performed in air-cuts;

In order to derive the energy index of machine readiness and availability, energy metering and monitoring is essential to obtain authentic information of each individual machine. It requires a high resolution to capture the instantaneous power peak and the rapid changes of machine states. Therefore, the sample rate should be less than 0.5s.



Tool tip power: power demand at tool tip to remove work piece material;



Unproductive power: power converted to heat mainly due to frictions during the material removal.

2.2

Technologies of Reducing Fixed Energy Consumption

As mentioned before, the fixed energy consumption is highly relevant for reducing energy consumptions of manufacturing processes throughout different machine states. Different energy efficiency measures aim at reducing the fixed energy demands through improved machine tool design as well as optimized process design. From the machine tool builder’s perspective, the improvement of machine tool design includes for instance from substitution of inefficient electrical motors to use of break for non moving axes [1]. As a result, the instantaneous fixed power could be minimized. For the existing manufacturing plant, process control measures enable the optimal utilization of the process by eliminating nonvalue adding tasks. However, standby state of each machine tool is unavoidable in most scenarios. The smart energy saving technologies has thus been introduced by control suppliers such as DMG Energy Save, which automatically power off or switch machine tool into hibernate mode once the standby period exceed a customer defined limit [7]. In order to achieve an optimal result, the configuration of the smart control system requires detailed information about machine readiness and availability. Therefore, the energy requirements of ensuring operational readiness are focused in this paper. 2.3

The Energy Index for Machine Readiness and Availability

As shown in Figure 1, machine tool passes different state to achieve operational readiness. During this period, machine tool not only consumes electrical energy but also requires a certain amount of time to achieve operational readiness. The same situation is applied to machine power-off stage. Therefore, the following energy related indicators are selected for evaluating machine readiness and availability. 

Peak Power: maximum instantaneous power requirement during the start-up period, which is relevant to the additional energy cost due to power peaks.

the

total

energy

A component-based description of fixed power consumption is also important to offer insights of machine behaviour. The starting point is to identify all the electrical components as well as their characteristics. Then, the constitution of the fixed power should be described. Preliminarily, Others like Dietmair et al used finite approach to assign the energy consumption to each component according to different operation sequences [2]. However, only the hydraulics can be quantified based on observed energy curve. Owing to the physical constraints of power measurement at a component level, alternative information resources were utilized, such as wiring scheme. It should be noted that the rated power given in machine documentations is an estimated value under either nominal or extreme conditions, which initially indicates the capacity of the electrical motor. Therefore, the calculated fixed power breakdown is compared with real data to provide approximate information of each component. The analysis comprehends six machine tools covering three different manufacturing processes (Table 1). Machine tool

Type

Studer S40

Universal grinding machine (3 spindles)

Studer S120

Internal grinding machine (1 spindle)

Colchester A50

CNC lathe (1 spindle)

MS NL 2000MC/500

CNC lathe with milling functionality (2 spindles)

MS Dura Vertical 5100

Vertical milling machining centre (1 spindle)

DMU 60 P

5-axis milling machining centre (1 spindle)

Table 1: Machine selection for conducting the study. 3.1

Experimental Consumption

Measurements

of

Fixed

Energy

For each of the above listed machine tools, the power demand was measured at the main switch with a National Instrument (NI) system, which is developed on a LabVIEW interface in conjunction with a NI data acquisition device. The voltage and current signals are captured and recorded every 0.1 second via NI module 9225

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Sustainability in Manufacturing - Energy Efficiency in Machine Tools

and 9229 respectively. Three Fluke current clamps were applied to convert current signals into voltage signals. The captured signals are processed simultaneously to the LabVIEW interface via NI compact chassis Cdaq-9172. The power measurement started from turning on the main power switch until each machine tool was ready for operation. The above measured period varies in terms of duration due to different start up procedures. Although the power consumption during standby-mode fluctuates within a small derivation, the fixed power is relatively static comparing to machine start-up and operation periods. In order to indicate the power behaviour, the start-up to operation for each device is illustrated in Table 2.

periphery system, cooling and lubrication system, control system and auxiliary system [3].

Pfixed =3.69

3 0

Drives

6

Studer S40

Spindle

Effective Power (kW)

9

Based on the operation of components, the power profile of a machining process represents the accumulation of the individual power demands for each component (see Figure 2). The research scope is limited to a machine tool with its integrated components; disregarding additional peripheral devices as coolant filter systems. Other components, such as coolant pump motor, chip conveyer motor, and tool library systems are only activated when they are commanded during processing stage. In this case, they are thus excluded for fixed power description.

Pfixed =1.69

Studer S120

2 0

Effective Power (kW)

Pfixed = 1.16

Colchester Tornado A50

2

Besides rotary motion, holds as well as centres work piece

Rotary Tool Spindle Motor

Rotary motion for cutting tool

i-Axis Motor

Hydraulic Unit Motor

Rotary motion for pump to supply clamping pressure

Lubricant Pump Motor

Rotary motion for pump to supply lubricant

Oil Cooler Pump Motor

Rotary motion for pump to supply oil cooler circuit

Turret Motor

Effective Power (kW)

4

Mori Seiki NL2000MC/500

Pfixed = 1.58

2

2

Mori Seiki DuraVertical 5100

Pfixed = 1.02

1

Auxiliary System

0

Effective Power (kW)

9 6 3 0

Spindle Amplifier/ Frequency Converter Servo Amplifier /Frequency Converter Computer and Display

DMU 60P Pfixed = 5.45

Table 2: Measuring fixed power for each machine tool. Deduction of Fixed Power Demand

Machine tools can be characterized as assemblies of components ensuring a specific function [6]. Each component performs a particular act enabling the entire machine to perform more complex, useful functions. Table 3 summarizes briefly the individual functions of electrical components in machine tools which can generally be classified into spindle drives, servo drives, hydraulic system

Periphery System

Effective Power (kW)

3

Control System

0

3.2

Cooling Lubrication System

0 6

Linear motion for cutting tool towards i-axis Besides rotary motion, holds as well as centres work piece at tailstock Rotary motion for cutting tool change

Tailstock Spindle

6 4

Main Spindle Motor

Servo Drives

4

Function

Hydraulic System

Effective Power (kW)

6

Component

Lightning Fan Coolant Pump Motor Chip Conveyer Motor Tool Change Arm Motor

Transfer numerical control signal for spindle rotation speed into adjusted electrical signal Transfer numerical control signal for servo feed into adjusted electrical signal Processing and visualization of program Lightning the working area Air flow generation for cooling electrical components Rotary motion for pump to supply coolant circuit with pressure Rotary motion for chip conveyer Rotary motion for tool change

Table 3: Electrical components in machine tools. Considering the power characteristics of components two types can generally be identified. The first type considers components that are either fully activated or not. The auxiliary components are generally under this category. Although the power demand of hydraulic pump depends on the desired pressure, the oil pressure remains constant

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271

throughout the stand-by and processing stages. The change of hydraulic pressure only occurs when unclamping the chuck. Hence, the hydraulic system can be classified as a static component. The same reason can be applied to cooling and lubrication system due to the continuous operation with a constant load. The second type covers components that are operated with a dynamically adjusting load. Generally, the spindle and servo motors rotate at variant speed. The dynamic torque and load on the drive system requires frequent adjustments [8]. The power demands for the control system (e.g. frequency converter) thus vary accordingly. Therefore, the spindle drives, servo drives and associated control system are grouped as adjusted components, as illustrated in Figure 2.

Instead of relying on real time measurement, the wiring scheme, circuit diagram and machine specifications were utilized for the fixed power estimation of each component. According to EN 60204 wiring schemes document integrated components as well as their power demand in detail in order to facilitate awareness about safety, function and maintenance of electrical equipment used in machines [9]. Thus, the power demand of components at nominal operational conditions can easily be derived for these documents. With other documents (e.g. circuit diagram, machine manuals), the rated power or nameplate power can be obtained for the major electrical components. This given value is the power output of a device under specific or nominal operating conditions, which indicates the capacity of each motors and drives with a continuously load [8]. Table 4 is an exemplary list of component rated power for Colchester A50.

0

1 activated (t)

0

0

Cooling & Lubricant

1 activated (t)

0

Power demand due to component activation and operation

Auxiliary System

1 activated (t)

Pconstant

Pconstant

Pconstant

PFC(load)

PS(load)

PM(load)

Control System

Spindle Drives

100% load (t)

0

100% load (t)

Servo Drives 0

100% load (t)

Power (W)

Hydraulic System

t

Time (s)

Figure 2: Power agglomeration of components to the power demand of the machine tool.

3.3

Component-based description of Fixed Power demand

Physical measurements at a component level require access to each sub-system. Conventional energy metering system can only capture the voltage and current data with constant frequency, which is not suitable for the devices with variant frequency such as amplifier, frequency converter and servo drives. The metering point at the main switch also limits the transparency of machine behaviour, since only significant power changes can be detected from the observed curve. Category

Component

Rated Power (kW) [10]

Auxiliary System M1 Cross Slide Fan

0.040 0.020

Lightning

0.036

[10]

Computer and Display

-

Hydraulic System Hydraulic pump motor

0.550

Cooling and Lubrication

Cooling Pump

[10-11]

-

Lubricant Pump

Sub-total Control System

0.646

Spindle Amplifier Module

0.120

[12]

Servo Amplifier Module

0.093

[12]

[10-11]

X-Axis Servo Motor

0.500

Z-Axis Servo Motor

0.500

Turret Servo Motor

0.300

Spindle Drive

Spindle Motor

5.500

Periphery

Coolant Pump

Servo Drives

[10]

Spindle Motor Fan

[10-11] [10-11] [10-11] [10]

0.370

Table 4: Rated power list of each component in Colchester A50.

For most of the tested machines, all the static systems are activated, such as hydraulic system, auxiliary system, cooling and lubricant system. The hydraulic, cooling and lubrication system have been identified as the main electrical consumers for machine readiness. For those major components, the rated power values highly agree with real measurements. For instance, the hydraulic pump of Colchester A50 is rated as 0.55 kW. The power curve of machine start-up indicates a significant power increase due to hydraulic activation from 0.45kW to 1.05 kW. Another example is for the complex 5-axis machine centre DMU 60P. The cooling unit normally remains idle until the temperature exceed a certain degree, while the power demand increases from 5.45 kW to 6.8kW. The rated power values of all the cooling components which includes compressor, pump and fans sum up to 1.25 kW. However, the aggregation of available rated power of static components (e.g. 0.646 kW) does not fit the real measurements (e.g. 1.16 kW). The differences are mainly due to following reasons: 1. Lack of information about several components; 2. Difference between input power and output power; 3. Disregards the adjusted power demand for the servo drives and the control system. For some reviewed machines, the rated power is not provided for each electrical component. Generally, the machine specifications only include the nameplate power for the main drive motors. As shown in table 4, the energy related information for computer, cooling and lubricant system is yet absent. Certainly, the input power is not equal to output power as the energy transmission efficiency is constantly less than 1. In addition, the rated power is estimated under nominal operating conditions which may not be the same situation as machine standby. Nevertheless, the difference is relatively small as the static components operate under constantly low load. Apart from the components with constant power demand, the servo motors and the associated control system are also activated [13]. For the turning and milling machine tools, the servo motor holds the cutting tool at the home position against the gravity of the cutting tool, which requires the servo motor constantly adjusting the tool position with relatively low loads. The servo amplifier or associated frequency converters are hence activated accordingly. However, the specific loads on the servo motors are unlikely to be quantified, especially during the stand-by stage. The self-consumed electrical energy of frequency converters or amplifiers is even more difficult to derive. The further investigation of the Fanuc amplifier (used for Colchester A50) showed that the heat dissipation of the servo amplifier is 93W under normal operational loads [12]. Since the servo motor is only positioning, all the rated power demands of servo motors and associated control units are scaled down accordingly.

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Sustainability in Manufacturing - Energy Efficiency in Machine Tools

By comparing the experimental power demand at different machine states with the rated component specific power features, a component-based description of fixed power demand is therefore obtained, as summarized in Figure 3 [10-12, 14-19].

DMU 60P

Servo Drives 17% Control System 6%

Σ 5.45

MS Dura Vertical 5100

Σ 1.02

Auxiliary System Cooling & Lubrication System

MS NL2000MC/500

Σ 1.58

Hydraulic System

Σ 1.16

Studer S120

Servo Drives

Σ 1.69

Figure 4: Average fixed energy breakdown of reviewed machine tools.

Σ 3.69

Studer S40

0

1

2

3

4

5

6

Figure 3: Component-based description of fixed power consumption. 4

STRATEGIES FOR FIXED ENERGY REDUCTION

Energy consumption reduction generally includes two strategic approaches. One is by reducing the instantaneous power demands, which requires an energy oriented design of machine tool at a component-base; the other one is by shortening the period of fixed power integration, which can be achieved by both increasing machine utilization as well as switching-off the machine to reduce the standby time. To practice above energy saving strategies, it is essential to acknowledge the energy performance of the machine tool during start-up, standby and power-off stages. However, the existing machine documentations do not provide sufficient information for energy consumption estimation. Moreover, energy metering and monitoring of each individual machine is time consuming and costly. Generally, it requires 1.5 hours for applying the metering system, measuring the process and analyzing the data with hourly costs of US$50. The initial installation cost is even more expensive since specialized and certified technician is required for connecting the high voltage. For a large plant, there are normally hundreds machine tools differentiating from age to capacity. It is nearly impossible to derive energy profile for each individual machine tool. In order to avoid further physical measurements at machine level, it is important to include power demand of the electrical consumer at different stages in the machine manuals. 4.1

Cooling Lubrication System 31%

Hydraulic System 27%

Contol System Colchester A50

Auxiliary System 19%

Componented-based demands

improvements

of

fixed

power

A reduction of fixed energy consumption can directly be achieved by technical measures that reduce the fixed power demand of components through applying energy efficient devices. Figure 4 illustrates average fixed energy breakdown of the reviewed machine tools. It suggests that the improvements of hydraulic system, cooling and lubrication system can save up to 58% of fixed energy consumption.

The self-regulatory initiative lead by Cecimo has listed potential measures for energy improvements of machine tools. For instance, the hydraulic unit and cooling lubricant unit are suggested to be coupled with control system, and be activated only on operating stage. For the auxiliary units, the line connected motors can be replaced by inverter motors. The feed axes during non moving axes should be also switched off and clamped by a brake [1]. In order to precisely estimate the leverage of the energy efficiency measures, the component-based description of fixed power consumption needs to be improved in terms of its authenticity and level of detail. 4.2

Process optimization consumption

for

reducing

fixed

energy

As mentioned earlier in this paper, the fixed power adds the total energy throughout different machine states. Different strategies should be applied according to the status of the machine tool. During the operation stage, the fixed power sets the power base for functional performance. According to the studies about specific energy consumption (SEC), the share due to fixed power consumption (specific fixed energy) can be reduced by increasing the process rate [4]. In other words, a higher production speed results less fixed energy consumption per product. For the non-continuous manufacturing processes, such as turning and milling, the standby time is unavoidable but feasible to be minimized. The main strategy here is to switch-off the machine if standby time is long enough. It is critical to notice the functionality of the fixed power, which ensures the machine readiness for operation. Once the machine is completely switched off, a specific time is needed to regain operational readiness. Therefore, the energy saving measures should not sacrifice the availability of the machine tool. As defined in section 2.3, the energy related index is compared among selected machine tools (see in Table 5). The study cycle starts from machine power-off until the machine readiness is retrieved. A 30 min idle period is assumed for the comparison between temporarily switching off the machine and keeping machine standby.

Sustainability in Manufacturing - Energy Efficiency in Machine Tools

273

4

9

2.4

9

Time to power-off (s)

15

10

10

15

10

15

Energy to power-off (kWh)

0.012 0.004 0.001 0.005 0.002 0.025

Fixed Power (kW)

3.69 1.69 1.16 1.58 1.02 5.45

Time to standby (s)

250

Energy to standby (kWh)

0.256 0.036 0.004 0.038 0.021 0.096

Studer S40

110

30

150

110

100

Cecimo (2009): Concept Description for CECIMO’s SelfRegulatory Initiative (SRI) for the Sector Specific Implementation of the Directive 2005/32/EC, available online: http://www.ecodesign-info.eu/documents/Machine_tools _VA_20Oct09.pdf, last revised 8/2/2010.

[2]

Dietmair, A., Verl, A. (2009): A generic energy consumption model for decision making and energy efficiency optimisation in manufacturing, in: International Journal of Sustainable Engineering, 2: 2, 123-133.

[3]

Kalpakjian, S; Schmid, S. R. (2006): Manufacturing Engineering and Technology, Ed. 5, Prentice Hall, S. 220.

[4]

Li, W., Kara, S. (2010): An Empirical Model for Predicting Energy Consumption of Manufacturing Processes: A Case of Turning Process, in: Proceedings of the Institution of Mechanical Engineers, Part B, Journal of Engineering Manufacture. In Print.

[5]

Gutowski, T., Dahmus, J., Thiriez, A. (2006): Electrical Energy Requirements for Manufacturing Processes; in: 13th CIRP International Conference on Life Cycle Engineering, Leuven, Belgium.

[6]

Weck, M., Brecher, C. (2006): Werkzeugmaschinen Konstruktion und Berechnung, 8. Ed., Springer.

[7]

DMG. Energy Save. Online: http://za.dmg.com/ino/mailing_ energysave_10/en/energysave.htm.

[8]

Crowder, R. M. (1995): Electric Drives and their Controls, Oxford Science Publications.

[9]

International Electrotechnical Commission (2009): IEC 602041, Safety of machinery - Electrical equipment of machines.

[10]

Colchester Co. (2000): Circuit Diagram of Colchester Tornado A50.

[11]

Colchester Co. (2000): Manual of Colchester Tornado A50, T5F-E02-11/98.

[12]

Fanuc Co. Fanuc AC Servo Amplifier Alpha Series Descriptions. B65162E/03. Online: http:// www.docstoc.com docs/28703564/Fanuc-AC-Servo-Amplifier-Alpha-SeriesDescriptions.

[13]

Nailen, R. L. (2002): When is a motor idle?, in: Electrical Apparatus, January 2002, Barks Publications.

[14]

Fritz Studer AG (2007a): Technical Manual for Studer S40.

[15]

Fritz Studer AG (2007b): Technical Manual for Studer S120.

Total Energy Cost for Temporary Switch Off (kWh) 0.268 0.040 0.005 0.043 0.023 0.121 Energy Saving if machine idle for 30min (kWh)

1.577 0.805 0.575 0.747 0.487 2.604

Table 5: Comparison of energy index of machine readiness. Firstly, the peak power has been detected during the machine startup period. Although the peak value is less than the spindle acceleration or other rapid changes of motor states, this instant drawing current may cause additional energy cost due to grid quality. The time from machine power-off to standby differentiates among the reviewed machine tools. While grinding machine Studer S40 requires 3.5 mins for pre-lubrication, the Colchester A50 can regain operational readiness in half minute. When applying an automatic energy saving system, the default switch-off time should be selected according to the cycle-time from machine switch-off to standby. Based on the assumed scenario, the machine tool with high fixed power demand, such as DMU 60P, Studer S40, can result significant savings by temporally switch-off the machine. It should be noted that the machine is completely powered off in this estimation. Recent technologies may allow machine to be easily restarted through the receipt of the familiar emergency shut-off operating mode [7]. Both power-off and hibernate mode requires customized analysis of fixed power consumption. Since the energy saving device cost more than ￡1,099 pre device, the cost efficient estimation should be also included in practice. 5

SUMMARY

This paper presented the investigation of fixed energy consumption from definition and description to improvement strategies. The awareness of fixed power demands have been raised due to the considerable share of the total energy consumption. While physical measurements derive the authentic power behaviour during different machine states, the machine documentation should also provide sufficient information of energy consumption to improve the transparency of the machine tool. The strategies for fixed energy reduction are discussed and evaluated considering both machine design measures and operational process optimizations. 6

ACKNOWLEDGEMENTS

The lead author kindly acknowledges the funding provided by the Advance Manufacturing Cooperative Research Centre for this research. This paper was compiled by the Joint German-Australian Research Group “Sustainable Manufacturing and Life Cycle Management” funded by the BMBF under reference AUS 09/AP1 and managed by the International Bureau of the BMBF at DLR.

REFERENCES

[1] DMU 60P

MS Dura Vertical 5100

6

Peak power (kW)

Colchester A50

9

Studer S120

MS NL2000MC/500

7

[16]

Mori Seiki Co. (2004): Technical Manual of NL Series.

[17]

Mori Seiki Co. (2004): Service Information Folder – Electrical Circuit Diagram NL Series, 148037B05.

[18] Mori Seiki Co. (2008): Service Information Folder – Electrical Circuit Diagram Dura Vertical, 148440A22. [19]

Deckel MAHO Co. (2001): Circuit Diagram of DMU_60P.

Energy Efficiency Measures for the Design and Operation of Machine Tools: An Axiomatic Approach 1,2

1,3

1,2

André Zein , Wen Li , Christoph Herrmann , Sami Kara

1,3

1

Joint German-Australian Research Group in Sustainable Manufacturing and Life Cycle Management

2

Institute of Machine Tools and Production Technology (IWF), Product- and Life-Cycle-Management Research Group, Technische Universität Braunschweig, Germany 3

School of Mechanical and Manufacturing Engineering, Life Cycle Engineering and Management Research Group, The University of New South Wales, Sydney, Australia

Abstract Due to environmental legislation and increasing customer demand, the development and deployment of energy-related improvement measures for machine tools has intensified. These measures centre different aspects of machining as integrating energy efficient components or applying start-stop strategies. Although the measures aim for a reduction of energy demand, guidance on the selection and prioritization of efficiency measures is necessary in order to identify adequate methods and create awareness about the effects and interdependencies. Using axiomatic design a matrix is developed that relates functional requirements of improving energy efficiency of machine tools to design parameters. Keywords: Machine Tools; Energy Efficiency; Axiomatic Design

1

INTRODUCTION

The reduction of electrical energy demands in the use phase of machine tools is an essential key to improve the environmental performance over the entire life cycle. Preliminary environmental studies for machine tools used in discrete part manufacturing (e.g. turning and milling) indicate that a proportion of more than 99% of the environmental impacts is due to the consumption of electrical energy [1]. As a consequence, the improvement of the environmental performance of machine tools is enforced by European environmental legislation through the preparatory initiation of an ecodesigndirective and moreover approached by self-regulatory initiatives of the machine tool industry [2, 3]. Measures to improve energy consumption of machine tools provide substantial leverage to reduce the associated environmental impacts in the use phase. The development of those measures comprises organizational as well as technical aspects. While organizational measures focus on the mode of operation of a machine tool, technical measures for instance address specifically the substitution of components through energy efficient alternatives. Although all measures are determined to improve the energy consumption, a systematic concept that provides structured guidance for the implementation of energy efficiency measures and associated impacts is yet absent. Based on the initial functional requirement to reduce the energy consumption for a machining cycle and in accordance with the axiomatic design theory, a decomposition matrix is developed which decomposes functional requirements and design measures for improving energy efficiency of machine tools. The proposed concept intends to successfully guide the implementation of energy efficiency measures for machine tools. 2

IMPLICATIONS OF THE ECODESIGN DIRECTIVE ON MACHINE TOOLS

The ecodesign directive provides an EU wide framework that defines ecodesign requirements for products which either directly (energy-using) or indirectly (energy-related) impact the environment through the consumption of electrical energy in the use phase of the

life cycle [4]. The directive is applicable for products which can be characterized by the following three criteria. Products should have significant sales and trade relevance with more than 200.000 units sold in the EU per year, considerable environmental impacts due to the use of energy (anticipated as 1000 PJ of primary energy) and a notable potential for improvement in terms of its environmental impact without entailing excessive costs [2]. As a result of the initiation of an ecodesign directive, rules and criteria are determined that limit the energy demand of products made available to markets in the European Union. Moreover, rating schemes can be defined that classify products according to the energy efficiency. An example therefore is the energy efficiency rating for electrical motors which evaluates the energy efficiency through relating mechanical output power to electrical input power in defined performance test procedures [5]. Preliminary studies which elaborated the extension of the ecodesign directive to new product groups estimated the associated environmental impacts of machine tool usage and pointed out the existence of eminent improvement potential. Within the analyzed product groups, machine tools ranked third place with a primary energy demand of 17.475 PJ per year [6]. In addition, promising saving potentials have been identified as improving the power factor, reducing the power demand in idle mode as well as integrating variable speed drives [6]. As a consequence of these preliminary studies, the implementation procedure described by the ecodesign directive was opened in 2008 aiming at the improvement of the environmental performance of machine tools and commenced with the initiation of a machine tool related product group study in 2010. Triggered by these efforts and industry self-regulatory initiatives, the development and deployment of energy-related improvement measures have further intensified starting, for instance, from the development of energy efficient components to the integration of energy-management principles into machine tool controls [1]. Prior to the analysis of improvement measures, the associated energy demand of machine tool operation is described in order to derive the objectives and scope for the axiomatic decomposition.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_48, © Springer-Verlag Berlin Heidelberg 2011

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Sustainability in Manufacturing - Energy Efficiency in Machine Tools 3

ENERGY EFFICIENCY OF MACHINE TOOLS

3.1

piece (so called air-cut) and the material removing capacity [13].

Power Demands of Machine Tools

Machine tools represent stationary assemblies that are fitted with (or intedend to be fitted with) a drive system other than directly applied human effort. They consist of joined parts and moving components enabling the entire machine tool to perform a complex, useful function which is the geometric shaping of workpieces made of arbitrary materials using appropriate tools and technologies [7, 8]. In machine tools electrical energy is transformed into mechanical or other desired forms of energy. The energy consumption of a machine tool results from the temporal accumulation of the individual power demands for each component (see Figure 1) [9]. Thus, the power demand is not static but rather dynamic throughout the machine tool operation. It is influenced by the design of the process and the selected machine tool configuration. Machine tool Sensor systems

In this case, the power measurement for the grinding machine shows that more than 3.5 kW are required as fixed demand and that the power demand increases up to 5.2 kW throughout processing including the variable power demand. These power demands do not consider the power demand of the mandatory filter unit which is providing coolant to the machine and continuously operating. However, the power profile enables to evaluate machining processes with regard to their energy demand [14]. The two displayed grinding processes differ only in the value of the MRR and are given in Table 1. The processing times and energy demands are derived from the data of the power measurement; initially considering the activation of the spindle to the final stop of the spindle for each process. The st results show that the 1 process with higher MRR prevails in terms of energy consumed per removed material. If the energy demand is allocated to the removed material volume and processing time, the resulting specific energy demand for the processes decreases with reduced MRR.

Power demand due to operation of components

st

Control

P1(t)

P2(t)

P3(t)

P4(t)

P5(t)

P6(t)

Frequency converters

Spindles

Power (W)

Signal elements

275

Servo motors

2 Processing

Processing time (s)

121

246

Total energy (Wh)

321

482

110

253

211

229

3600

3600

0.089

0.134

0.00074

0.00054

- Fixed energy (Wh) Time (s)

- Variable energy (Wh)

t

3

Material removed (mm ) Total energy per removed -3 material (Wh mm )

Figure 1: Agglomeration of power demands - according to [9, 10]. Power meters enable to capture the dynamic power demand of a machining process which consequently provides a basis to recognize actions and associated power demands. Reviewing the power profile of an exemplary internal cylindrical grinding process in Figure 2, the start-up of the machine tool and spindle as well as two machining processes with varying material removal rates (MRR) can be determined. Based on the resulting power demand, a variable and fixed portion can generally be differentiated [11, 12]. While the fixed power covers the constant demand, which is necessary to ensure a functional mode of operation (ready for

nd

1 Processing

-3

-1

Specific energy (Wh mm s )

Table 1: Comparing machining processes according to the energy demands. With regard to the total energy demand for a machining process, optimization measures should aim at maximizing the MRR in order to reduce the impact of the fixed power. However, while increasing the MRR it is also absolutely essential not to neglect the resulting process conditions and work piece quality.

operation), the variable demand power considers the power for carrying out the machining operation without touching the work

Power

Power factor

1,0

6

0,8

5 4

0,6

Variable demand

3

0,4

2

Fixed demand

0,2

1 0 0 Machine start up

100

200

Initial spindle lubrication

300 Spindle start

400 1st Processing

500 Idle

600

700

2nd Processing (with 50% MRR)

Figure 2: Power demand of a grinding machine (two processing cycles).

800

0,0 Time900 (s)

Machine turned off

Power Factor

Effective Power (kW)

7

276

Sustainability in Manufacturing - Energy Efficiency in Machine Tools

In addition to the power demand, Figure 2 also displays the power factor which indicates how efficiently the machine tool is using the power supplied to it [15]. While the power factor generally remains at 0.8 in the example of the grinding machine, the start-up and shutdown of the machine tools leads to power factors less than 0.5. Thus, only 50% of the power supplied is used as effective power.

Reusing invested energy

With regard to the power demand and power factor resulting from the operation of the grinding machine tool, the indicated saving potentials given in the EU directive can easily be identified. This includes the improvement of the low power factor and most importantly the reduction of power demands in non-processing times (e.g. reduce fixed power during spindle lubrication and in idle mode). Although saving potentials can be determined to improve the energy consumption, a systematic concept that provides structured guidance for the selection and implementation of energy efficiency measures and the associated impacts is yet absent.

Recovering energy

Classification Scheme to Improve Energy Efficiency of Machine Tools

In general, energy efficiency is defined as relation of output to energy input. Energy efficiency can furthermore be specified using a variety of indicators based on physical, economic or thermodynamic reference parameters [16]. Due to the complexity of defining a functional reference for machine tools, an overall indicator for the valuation of energy efficiency of machine tools is yet obsolete [1]. Thus, as a basis for deriving improvement measures the energy efficiency of machine tools is in this paper described as the amount of electrical energy invested to perform a complete machining operation consisting of the procedures start-up, set up, processing of a distinct amount of material and shut down (as displayed in Figure 2). Consequently, improving energy efficiency for the above mentioned scope requires either maximizing the output for a given input or minimizing the energy required to provide a given output. In the case of machine tools, the minimization of energy is encompassed by improvement measures that initially reduce energy demands and subsequently reuse invested energy or finally recover energy losses of transformation processes [according to 17]. Reducing energy consumption With regard to the power demand in Figure 3, a reduction of energy consumption can directly be achieved by technical measures that reduce the power demand of components through applying energy efficient devices. In addition, the enhancement of energy efficiency can indirectly be realized through organizational measures [18]. While technical measures include for instance the replacement of hydraulics and motors with energy-efficient ones, organizational measures focus on the optimization of process times based on energy-oriented process planning (compare Table 1). Reduce energy demand by technical measures

Apart from the consideration of energy consumption, another important aspect is the conversion of electric energy within the machine tool and the resulting energy liberation. Recovering energy losses through heat recuperation techniques may be beneficial once a heat potential is present. Energy recovery potentials are generally approached by thermal management (e.g. apply heat exchanger to control cabinets) [1, 21]. In addition to the effect of an improvement measure, the point of action can be classified according to the process, specific components or the entire machine tool design. Hence, this classification takes into account the implementation ability of the measure. While a process optimization can be applied instantaneously, changes in the design of the machine tool are more beneficial for the subsequent machine tool generation. Based on this classification scheme, every improvement measure can be clustered and prioritized according to the effect and the implementation ability. Thus, this builds the basis for the subsequent decomposition of saving potentials and interlinking with adequate measures. 3.3

Improvement Measures

Triggered by the necessity to improve the environmental performance of machine tool usage, measures to minimize the energy demand of machine tools in the use phase have been developed and deployed. Initially, a catalogue of measures has thus been established based on the available measures developed and collected within the research project Prolima, the initiative Blue Competence as well as the self-regulatory initiative lead by Cecimo [1, 22, 23]. All in all, a set of more than 190 improvement measures has been listed and classified according the developed classification scheme. It has to be pointed out that not all measures are categorized excluding those which do not provide an energy-related effect. Hence, in Figure 4 the selection of measures which could clearly be assigned to the given set of categories is displayed. 120 102

Amount of improvement measures

3.2

Apart from the reduction of energy consumption, improvement measures can furthermore aim at reusing energy. Especially motors enable to reuse energy once the motor acts as a generator in braking mode. Examples include for instance the energy balancing of multi-motor drives or kinetic buffering of energy [20].

100 80 60 40

Power

20

Reduce energy demand by organisational measures

14

8

0 Reduce

Reuse

Recover

Effect of improvement measures

Time

Figure 3: Strategies to reduce the energy demand of machine tool usage [according to 19].

Improve machine design

Improve components

Improve processing

Figure 4: Classification of energy-related improvement measures. Based on the classification, the relevance of measures to reduce the energy consumption was determined. Although more than 40% of these measures aim at reducing the energy demand through

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277

improved machine tool design, 22% of the measures are pursuing the same effect by improved process design.

decomposition are displayed in Table 2. Based on the initial FR 1, the subsequent level resolves the three FRs to reduce, reuse and recover energy with the DP to analyze specific saving potentials to fulfill the requirements.

As a result of the classification, more than 100 energy-reducing measures have been identified. However, due to couplings and interrelations between the measures and the resulting effects on the energy consumption, a systematic concept is required that provides structured guidance for the selection and implementation of energy efficiency measures. Thus, a design guide is developed with regard to axiomatic design theory which decomposes improvement measures as design parameters to fulfill the functional requirements (representing saving potentials). 4 4.1

DECOMPOSITION OF ENERGY EFFICIENCY MEASURES TO IMPROVE MACHINE TOOLS Axiomatic Design

Axiomatic design is a systematic tool that structures and clusters measures within a design process through mapping of functional requirements and design parameters. A functional requirement (FR) can be defined as a set of functional needs of a system (e.g. product or process). A related design parameter (DP) represents a response which fulfills the FR, hence leading to a structured design process [24, 25]. The relationship between FR and DP is defined in a vector which displays the decomposition of the FR with unique and preferably uncoupled DP. The decomposition has for that reason to consider two axioms in order to obtain an optimal design process [24]: 1. Independence Axiom: Maintain the independence of the functional requirement. 2. Information Axiom: Minimize the information content. In accordance with the axiomatic design theory, the decomposition demands to define an initial FR which states the objective and scope for the design process. At the main decomposition level, the related DP is rather extensive and will lead with ongoing decomposition to more specific and detailed solutions that fulfill the requirements [26]. Hence, the axiomatic design methodology enables to link energy saving potentials for machine tool usage with optimal improvement measures. Moreover, by ordering the results in a systematic topdown structure and integrating path dependency (reading from left to right) the decomposition vector provides guidance for the implementation of measures to minimize the energy demand of a machining cycle (according to [27]). 4.2

Objective and Scope

With regard to the definition of energy efficiency, the objective of the decomposition focuses solely on the minimization of the electrical energy demand to perform a machining cycle. Moreover, the scope is limited to a machine tool with its integrated components; disregarding additional peripheral devices as coolant filter systems. In contrast to the use of indicators like the specific energy consumption or energy per manufactured part, the scope is set to cover the power demand of a full machining cycle without additional references. This enables to consider the characteristic energy consumption of a machine tool with value-adding and also non-value-adding activities (e.g. idle mode). Moreover, this rather extensive focus avoids considering the product material and processing technology specifications. 4.3

Mapping of Parameters

Functional

Requirements

to

Design

The energy efficient machine tool decomposition focuses solely on energy-related objectives and thus the contribution of FRs on minimizing the energy demand. The resulting FR and DP of the initial

To extend the decomposition, the branch of the FR 11 (minimize energy) is decomposed into FRs aiming at the reduction of machining time (FR 111) prior to reducing the power demand of components (FR 112). While the machining time involves organizational measures based on energy-aware process planning, the FR 112 can be fulfilled by technical means to avoid or reduce the power demand of energy using components. FR 1: Minimize energy demand of a machining cycle DP 1: Energy efficient machine tool decomposition FR 11: Reduce energy input DP 11: Identify and explore potentials for energy reduction FR 111: Minimize operation time of machining process DP 111: Energy-oriented process planning FR 1111: Minimize processing time DP 1111: Perform process at maximum material removal rate ensuring target quality FR 1112: Minimize time of non-value adding tasks DP 1112: Reduce time non-value adding tasks FR 11121: Avoid non-value adding tasks DP 11121: Eliminate non-value adding tasks FR 11122: Reduce time of non-value adding tasks DP 11122: Plan process with minimal non-value adding tasks FR 112: Minimize power demand of a machining cycle DP 112: Improve power demand of the machine tool FR 1121: Operate components efficiently DP 1121: Use components only when required FR 1122: Minimize power demands of components DP 1122: Substitute inefficient components with efficient ones FR 1123: Minimize power demand to operate machine DP 1123: Reduction of moved masses FR 12: Reuse energy DP 12: Identify and explore potentials for energy reuse FR 121: Ensure energy feed back DP 121: Integrate energy feed back system FR 1211: Reuse kinetic energy to power the machine tool DP 1211: Feed back the braking energy to power the machine tool FR 1212: Conserve kinetic energy DP 1212: Integrate kinetic energy buffering systems FR 1213: Maximize energy potential DP 1213: Transform energy into other useful forms FR 13: Recover energy losses DP 13: Identify and explore potential energy losses FR 131: Ensure efficiency of energy transformation DP 131: Eliminate non-efficient transformations FR 132: Minimize energy losses of transformation DP 132: System to prevent and minimize losses FR 133: Maximize energy recovery DP 133: Integrate energy recovery system FR 1331: System to directly recover electrical energy DP 1331: Apply thermal management to recover electrical energy FR 1332: System to indirectly recovery energy DP 1332: Apply thermal management to conserve energy losses Table 2: Derived FR and DP of the energy efficient machine tool decomposition. The decomposition of the branch FR 12 shows just one direct link to reuse energy of accelerated or differently powered components which could be satisfied by applying feed back or buffering measures.

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Sustainability in Manufacturing - Energy Efficiency in Machine Tools

In contrast, the third branch of FR 13 entails three major FRs. Based on the second law of thermodynamics, the recovery of energy has to ensure that transformation of electrical energy is done efficiently, hence avoiding the losses in first place (FR-DP 131). Based on this, the inevitable losses should be minimized (FR-DP 132) before the application of recovery measures is considered (FR-DP 133).

5

In alignment with the classification of improvement measures in Figure 4, the decomposition of FR and PD displayed in Figure 5 confirms the increased availability of improvement measures to reduce the energy consumption of machine tool usage in contrast to reusing or recovering energy. With regard to improving the energy demand of a machine tool, this initial decomposition enables to identify and structure potentials and improvement measures guiding the successive deriviation of implementation sequences.

SUMMARY

Against the background of the increasing availability of energyrelated improvement measures for machine tools, this paper presented axiomatic design as a systematic tool to structure improvement potentials and provide guidance for the optimal implementation sequencing of measures. Based on the initial functional requirement to minimize the energy demand of a machining cycle, design measures are derived aiming at the reduction, reuse or recovery of energy. Based on the first decomposition, the decomposition vector will be detailed in future work and extended in detail to describe the couplings and interrelation between the FR and DP.

FR-1

Minimize energy demand of a machining process DP-1

Energy efficient machine tool decomposition

FR-11

Minimize energy input

DP-11

Identify and explore potentials for energy reduction

FR-111

Minimize operation time of a machining process

DP-111

FR-112

Minimize power demand of a machining process

DP-112

FR-1111

FR-1112

FR-1121

FR-1122

Minimize processing time

Minimize time for non-value adding tasks

Ensure effective usage of component

Minimize power demands of components

DP-1111

DP-1112

DP-1121

DP-1122

Perform process with maximum MRR

Reduce time for non-value adding tasks

FR-11121

Avoid nonvalue adding tasks

DP-11121

Eliminate nonvalue adding tasks

Use components only when necessary

FR-13

Reuse energy

Recover energy losses

DP-12

DP-13

FR-121

FR-131

Identify and explore potentials for energy recovery

Identify and explore potentials for energy reuse

Improve power demand to perform the machining process

Energyoriented process planning

FR-12

Substitute inefficient components

Ensure energy feed back

Ensure efficiency of energy transformation

DP-121

DP-131

Eliminate nonefficient transformations

Integrate energy feed back system

FR-1123

Minimize power demand to operate the machining process DP-1123

Reduce moved masses through machine design

FR-1211

Reuse kinetic energy to power machine tool

DP-1211

Feed back braking energy to power machine tool

FR-1212

FR-1213

Conserve kinetic energy

Maximize energy usage potential

DP-1212

DP-1213

Integrate kinetic energy buffering system

Transform energy into other useful energy forms

FR-11122

Reduce time to perform nonvalue adding tasks

DP-11122

Operate process with minimal nonvalue adding tasks

Figure 5: The first 4 levels of the energy efficient machine tool decomposition.

FR-132

Minimize energy losses of transformation

DP-132

System to prevent and minimize losses

FR-1331

Directly recover energy

DP-1331

Apply thermal management to recover energy

FR-133

Maximize energy recovery

DP-133

Integrate energy recovery system

FR-1332

Indirectly recover energy

DP-1332

Apply thermal management to conserve energy losses

Sustainability in Manufacturing - Energy Efficiency in Machine Tools 6

ACKNOWLEDGEMENTS

This paper was compiled by the Joint German-Australian Research Group “Sustainable Manufacturing and Life Cycle Management” funded by the BMBF under reference AUS 09/AP1 and managed by the International Bureau of the BMBF at DLR. 7 [1]

REFERENCES Cecimo (2009): Concept Description for CECIMO’s SelfRegulatory Initiative (SRI) for the Sector Specific Implementation of the Directive 2005/32/EC, available online: http://www.ecodesign-info.eu/documents/Machine_tools _VA_20Oct09.pdf, last revised 8/2/2010.

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[3]

European Commission (2007): Study for preparing the first Working Plan of the EcoDesign Directive, available online: http://ec.europa.eu/enterprise/policies/sustainablebusiness/files/workingplan_finalreport_en.pdf, last revised 11/11/2010.

[4]

European Commission (2010): Eco-design of Energy-Using Products, http://ec.europa.eu/energy/efficiency/ecodesign /eco_design_en.htm, last revised: 8/18/2010.

[5]

de Almeida, A. T., Ferreira, F. J. T. E., Fong, J., Fonseca, P. (2008): EUP Lot 11 Motors Final Report, online available: http://www.ecomotors.org/files/Lot11_Motors_1-8_280408 _final.pdf, last revised 11/11/2010.

[6]

European Commission (2008): Establishment of the working plan for 2009-2011 under the Ecodesign Directive, available online: http://eur-lex.europa.eu/LexUriServ/ LexUriServ.do? uri= COM: 2008:0660:FIN:EN:PDF, last revised 11/11/2010.

[7]

Schischke, K. Hohwieler, E.; Feitscher, R., König, J., Duchstein, B., Nissen, N. F.: Energy-Using Product Group Analysis Executive Summary, available online: http://www.ecomachine tools.eu/typo/reports.html?file=tl_files /pdf/EuP_Lot5_Task1_draft_V01.pdf, last revised 11/11/2010.

[8]

Weck, M., Brecher, C. (2006): Werkzeugmaschinen Konstruktion und Berechnung, 8. Ed., Springer, Berlin.

[9]

Devoldere, T., Dewulf, W., Deprez, W., Willems, B., Duflou, J. (2007): Improvement Potential for Energy Consumption in Discrete Part Production Machines; in: Advances in Life Cycle Engineering for Sustainable Manufacturing Businesses, Springer.

[10] Dietmair, A., Verl, A. (2009): A generic energy consumption model for decision making and energy efficiency optimisation in manufacturing, in: International Journal of Sustainable Engineering, 2: 2, pp. 123-133. [11] Gutowski, T., Dahmus, J., Thiriez, A. (2006): Electrical Energy Requirements for Manufacturing Processes, in: 13th CIRP International Conference on Life Cycle Engineering, Leuven, Belgium. [12] Herrmann, C., Zein, A., Winter, M., Thiede, S. (2010): Procedures and Tools for Energy Metering of Machine Tools, in: Manufacturing 2010 - 3rd International Scientific Conference, Poznan.

279 [13] Eckebrecht, J. (2000): Umweltverträgliche Gestaltung von spanenden Fertigungsprozessen, Shaker, Aachen. [14] Anderberg, S. E., Kara, S., Beno, T. (2010): Impact of energy efficiency on computer numerically controlled machining, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Volume 224, Issue 4, 2010, pp. 531-541. [15] Saidur, R. (2010): A review on electrical motors energy use and energy savings, Renewable and Sustainable Energy Reviews, Volume 14, Issue 3, pp. 877-898. [16] Patterson, M. G. (1996): What is energy efficiency? - Concepts, indicators and methodological issues, in: Energy Policy, Volume 24, Issue 5, May 1996, pp. 377-390. [17] Kaebernick, H. (2008:, Reuse, Recycling and remanufacturing impediments for industrial implementation, 15th CIRP International Conference on life cycle engineering, 2008, Australia [18] Herrmann, C., Thiede, S., Zein, A., Ihlenfeldt, S., Blau, P. (2009): Energy Efficiency of Machine Tools: Extending the Perspective, in: 42nd CIRP Conference on Manufacturing Systems, Grenoble. [19] G.E. Fanuc (2008): The Environmental and Economic Advantages of Energy-Efficient Motors, available online: http://leadwise.mediadroit.com/files/2928energy%20savin g_wp_gft688.pdf, last revised 11/11/2010. [20] Siemens (2010): Blue Competence, available online: http://www.automation.siemens.com/mcms/mct/de/motio n-control-events/metav-2010/blue-competence/Seiten/ Ausstellung%20%E2%80%9EBlue%20Competence%E2%80%9C. aspx, last revised 11/11/2010. [21] Diaz, N., Helu, M., Jarvis, A., Tönissen, S., Dornfeld, D., Schlosser, R. (2009): Strategies for Minimum Energy Operation for Precision Machining, Proceedings of MTTRF 2009 Annual Meeting, available online: http://sustainablemanufacturing.biz/media//DIR_17101/95 43103a2878 dfb8ffff83b7ffffd524.pdf, last revised 11/11/2010. [22] Prolima (2010): Environmental Product Life Cycle Management – Best Practice Manual, available online: http://www.prolima.eu, last revised 11/11/2010. [23] VDW (2010): Blue Compentence, available online: http:// http://www.vraagenaanbod.nl/download/VDW%20Blue%2 0Competence%20Concept%20EMO%20Milaan.pdf, last revised 11/11/2010. [24] Suh, N. (1990): The Principles of Design, Oxford University Press, New York. [25] Reynal, V. A., Cochran, D. S. (1996): Understanding Lean Manufacturing According to Axiomatic Design Principles, Lean Aircraft Initiative, Report Series #RP96-07-28. [26] Babic, B. (1999): Axiomatic design of flexible manufacturing systems, in: International Journal of Production Research, Vol. 37, No. 5, pp. 1159-1173. [27] Cochran D. S., Arinez, J. F., Duda, J.W., Linck, J. (2001): A Decomposition Approach for Manufacturing System Design. In: CIRP - Journal of Manufacturing Systems, 20(6), pp. 371389.

Analyzing Energy Consumption of Machine Tool Spindle Units and Identification of Potential for Improvements of Efficiency 1

1

1

1

E. Abele , T. Sielaff , A. Schiffler , S. Rothenbücher 1

Institute of Production Management, Technology and Machine Tools, Technische Universität Darmstadt, Darmstadt, Germany

Abstract This paper describes the results of the analyses of a representative machine tool spindle unit and the thereof identified potentials for increasing the energy efficiency. This is done within the project “EnergieMSP”, whose aim it is to develop an energy optimized spindle unit with an adapted electric drive train. The holistic analysis of the system is done in a machine tool to determine the consumption of pressurized air, the energy demand for the tool change and hydraulic stand-by losses. The frictional losses in the bearings and rotary union and the electrical drive train where separately investigated at test benches. Keywords: Machine Tools; Spindle Units; Efficiency

1

INTRODUCTION

Public environmental awareness and the sociopolitical debate regarding the climate change lead to tightened political regulations with the aim to reduce the emission of greenhouse gases. Thus the producer’s responsibility toward environmental impact of their products will increase. This regards also machine tools as they are part of the work program within the framework directive for energy using products of the Council of the European Union [1]. In the course of that the energy cost will increase as well and affect the manufacturing costs of producing industry. Considering cutting processes the energy consumption of machine tools have the biggest part of the total energy needed for the process as a study at the Heidelberger Druck conducted by the PTW [2] has shown. Figure 1 shows the complete allocation of the electrical energy consumption for machining a turning work piece.

for acquisition and the annual accruing costs for a period under consideration of ten years. The allocation of the annual operating costs of this machine tool is given at the right column of figure 2.

10 9 8 7 6 5 4 3 2 1

490,000 € Operating Costs of a Machine Tool p.a. (without labor costs, tool costs and overhead) lubrication for cutting 39,000 €

pressurized air energy costs occupancy costs repair

Invest: 100,000 €

maintanance capital commitment

Figure 2: Operating cost of a machine tool.

Figure 1: Breakdown of Energy consumption for machining a turning work piece. This big amount of the energy consumption causes up to 20% of the operating costs of machine tools per year [3]. Figure 2 shows the operation costs for an exemplary machine tool according to COSTRA study conducted by the PTW. The left column of figure 2 illustrates the total cost of ownership, including the investment costs

To reduce energy costs the requirement of low energy consumption becomes more and more the main focus of research and development activities in manufacturing engineering as well as for the machine tool manufacturers. The authors of [4] also observe that besides the need of an improved efficiency the potential of savings has to be determined during development and design phases, so that they could be reflected with the mostly higher invest costs. The return on investments of energy saving measures strongly depends on the rate of capacity utilization. Because of that it becomes necessary that users of machine tools define the user profile of the machine for the manufacturer, so they can review potential measures for improved efficiency [5]. Therefore the need to identify and analyze the main energy users is given. The fact that in an average machining center the main spindle mostly unit has the biggest connection power shows that this core component with its peripheral systems takes one of the main parts of the energy consumption of the machine tool during the primary processing time. But also during the secondary processing time the spindle units and added systems like the supply for pressurized air for

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_49, © Springer-Verlag Berlin Heidelberg 2011

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Sustainability in Manufacturing - Energy Efficiency in Machine Tools

281

sealing air and oil-air-lubrication as well as hydraulics for tool clamping need a considerably amount of energy [6,7]. In order to achieve the aim of a spindle unit for machining parts with minimized energy demand a holistic improvement of the mechatronic system is necessary. For investigation of the spindle unit three topics were defined, which are energy efficient electrical drive train, improvement of efficiency through lightweight design and loss minimized spindle components.

specific thermal capacity of the coolant medium. The cooling system needs electrical power (PRec) for the recirculation of the cooling fluid. With the EER of the chiller between electrical input power and delivered cooling power (PWater) the total power consumption for cooling is:

2

SYSTEM BOUNDARIES

To analyze the system and determine the power consumption and the energy efficiency ratio (EER) of the system and its components one has to define reasonable system boundaries. Therefore all components which are in general necessary for operating the machine tool spindle unit were considered and the interaction with the machine tool analyzed. The border of the electrical drive system is chosen at the intermediate direct current link. This was caused by the fact that a network of drives often has only one central direct current link for the power distribution to several consumer loads in the network. Therefor the inverter and the smoothing inductances are part of the tool spindle system. On the tool side of the spindle unit the mechanical power (Pme) output as product of rotating speed (n in rpm) and torque (T in Nm) is defined:

Pme  n

 30

T

(1)

PCooling 

PWater  PRec EER

(2)

The tool clamping mechanism is mostly hydraulic actuated. The needed power is determined by flow and pressure measurements on the fluid side and a power measurement on the electrical side. Typical energy efficiency ratios for hydraulic pumps are in the range of 30% to 40%. As the hydraulic power can be provided local as well as central for other consumers, the definition of a system border is more difficult. In addition to that there are some alternative concepts which use pressurized air, coolant lubrication or electromechanical actuators for tool clamping. To achieve comparability to each other, especially electromechanical, systems it will be calculated on how much electrical energy is needed to generate the demand of hydraulic energy. For the given system one needs 1 kWh of electric energy to generate 0.35 kWh of hydraulic energy. With those definitions and the specified system borders the significant energy consumptions of the spindle system where systematically analyzed to find out starting points for improvements of efficiency. Figure 3 shows the machine tool spindle unit with the named peripheral components and the described system border.

The EER of the converter can be determined by the ratio of the effective power of the motor and the power of the direct current link, which can be measured. The EER of the motor follows as ration of mechanical power to effective power of the motor. The compressed air conditioning is outside the defined border, as this is often centrally realized for many consumers of pressurized air in the plant. The consumption of pressurized air itself is regarded and set together by the following parts: 

Bearing lubrication (optional): Oil air lubrication of the bearings 6 is an option, as with a speed parameter of 1.5•10 mm/min the bearings are lubricated with grease and therefore need no additional energy during operation. For higher values oil air lubrication is used which needs pressurized air and electrical energy.



Sealing air: To protect the spindle unit against chips, particles, fluids and condensate formation.



Exhaustion (optional): Surplus oil in the machine tool spindle housing is exhausted by the venturi-effect



Taper cleaning air: During the tool change the taper is cleaned by pressurized air to ensure that no particles are at the contact surfaces between tool holder and interface.

The consumption of pressurized air is measured in the supply line by calorimetric transducer in standard cubic meters per hour (Nm³/h). The costs for one Nm³ are one euro cent for modern air supply units. As the costs for compressed air conditioning are dominated by electrical and the costs for one kWh can be assumed to 10 euro cent, one need approximately 0.1 kWh of electrical energy for one Nm³ of pressurized air [8]. For cooling the machine tool spindle unit cooling channels are in the section of the drive and the bearings. Therein a cooling fluid circulates, so that heat and with that an energy exchange from the spindle unit to the heat exchanger is realized. With that the temperatures of the spindle components are limited and thermal deflections in axial direction are mostly avoided. The needed cooling power (PWater) can be calculated as the product of mass flow, temperature difference between forward and back flow and the

Figure 3: Definition of System Boundaries. 3

ENERGY TRANSPORT MECHANISMS MACHINE TOOL SPINDLE UNIT

INSIDE

THE

Besides the EER of the machine tool spindle unit the energy transport inside the spindle is important for the precision and the energy compensation. All losses of the spindle system appear as heat in the system and cause a rise in temperature of the system. This leads to unwanted extensions of components e.g. the spindle shaft. Therefore, besides the economic aspects it is of interest to minimize the losses with respect to the machining accuracy. Irrespective which kind of motor is used the electric drive of the spindle unit is a heat source. Figure 4 shows the location of the heat sources and cooling exemplary for a spindle unit with synchronous motor, where additionally a shaft cooling is shown, which is only used for particular applications. All copper, eddy current and hysteresis losses of rotor and stator are converted to heat and have to be conducted out of the spindle. Therefore the system has cooling channels in the stator housing at which the heat is transferred to the cooling fluid by forced convection. Those cooling channels are often around the bearings too (see Figure 4), so that the heat which is generated by the

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Sustainability in Manufacturing - Energy Efficiency in Machine Tools

friction in the bearings is directly transferred to the cooling fluid. The heat of the rotating part has to be transferred by heat conduction through the bearings and convection in the air gap to the stator part and therefore also to the cooling fluid. Another small part is transferred by heat radiation to the ambient air, but this could by neglected due to the small temperature difference between spindle housing and ambience.

4.2

Pressurized air

The consumption of pressurized air was measured on the existent machine tool. Sealing air holds the largest proportion with 9.27 3 Nm /h, followed by the bearing lubrication with 7.89 Nm³/h and exhaustion with 1.49 Nm³/h. The consumption of lubricating air decreased at a maximum speed by 3% as opposed to idleness. This dependence was however disregarded in the process and a value adopted at mean speed. The consumption of pressurized air, as defined in the paragraph System boundaries, was recalculated into an equivalent electrical power input and amounts to 1874 W. A 3 metered flow of 23.3 Nm /h was determined for the cone cleaning 3 air at a tool change. A consumption of 0.01 Nm of air equals to an equivalent electrical energy of approximately 1 Wh per tool change. 4.3

Hydraulics

In [8] empiric models are determined and validated with the help of extensive test benches, which allow an estimation of the breakdown of the energy transport. With that one gets the following distribution for the heat of the rotor for the used reference spindle unit:

The energy demand for a tool change in the reference system was determined by gauging pressure and flow in the supply pipe of the hydraulic cylinder of the tool releasing device. The hydraulic peak output accounts to 1.6 kW and the hydraulic energy for a complete cycle of releasing/clamping can be specified with 0.2 Wh. An electrical energy of 0.59 Wh per tool change results with consideration of efficiency (see paragraph 2 System Boundaries). Hydraulic systems will always hold losses in the leakage, in order to maintain the system pressure. This Standby-consumption was determined by the reference machine, whose hydraulic system runs in a storage charging circuit, as amounting to 36 W (electrical).



4.4

Figure 4: Location of heat sources and sinks within spindle units [9].

70% are transmitted by convection via air gap to the stator within the area of the drive.



16% are transmitted by convection via air gaps outside the area of the drive to the stator or housing



10% are delivered to ambient air



4% are removed from the rotor via convection and conduction through the bearings.

This estimation was done for a permanent exited synchronous machine in field weakening operation at 20,000 rpm and a load of 5.4 Nm. This estimation is not valid in general and has to be considered for each different system and operating point separately. However, due to the relation of a small air gap to a large surface in the area of the drive in all machine tool spindle units, the biggest amount of heat is transferred via convection in the air gap of the drive. This is supported by the high rotational speed, because this leads to a turbulent air stream, which is advantageous for energy transport. Generally the heat transfer coefficient increases for small air gaps and high circumferential speed. Therefore, the reduction of the air gap is of benefit for the achievable drive power as well as for good heat transfer in the spindle unit. 4 4.1

DETERMINING THE ENERGY EFFICIENCY RATIO OF THE REFERENC SYSTEM Reference System

In order to determine the energy efficiency a reference system was chosen, which will be optimized along the progress of the project by the identified potentials. The reference system can be identified by the following benchmark data: maximum number of revolutions -1 6 28,000 min ; speed parameter of 2.4•10 mm/min (oil-air lubrication); tool interface HSK 63; maximum torque 38 Nm (S1); maximum continuous output 40kW (S1) and weight 52 kg. The machine tool spindle unit is currently available in varying bearing configurations, thus creating the possibility to compare different systems. The spindle is available for inspection in a machine tool DMG V75 and as a single spindle in the test stand.

Friction in rotating Components

In an attempt to measure friction and the resulting losses in the spindle bearing, a separate test bench was constructed. This complex approach is needed in order to exactly calculate the frictional torque produced by the bearing. Especially repercussions of the electrical drive and of the rotary union have to be excluded from the friction moment. Therefore a bearing for the spindle shaft in a spring-loaded O-array was designed in the test bench. This shaft is driven by a separate spindle. Figure 5 shows that the spindle is mounted on an air bearing and has a degree of freedom along its rotation axis, which is mounted free of friction; thus providing the precise measurement of the actual torque on the bearings with a constant number of revolutions. In order to provide the opportunity for further inquiries on the bearing, the possibility of measuring the temperature on the inner and outer ring during operation was created. A change in temperature can be made possible by adjusting the coolant flow rate and the heating of the shaft. Furthermore, the axial preload force can also be varied, in order to determine the effect of the temperature, the axial preload force and the number of revolutions on the friction moment. In cooperation with the bearing manufacturer of the project consortium any further effects of different osculation and cage geometries will be examined. For a first analysis of the distribution of energy consumption to be created with qualitative results, measurements were taken on different operating points on common spindle bearings with diameters of 70 mm. The results in Figure 5 show that with 24,000 rpm, an output of 1 kW is needed to keep two bearings revolving with constant rotational speeds. These first results initially provide the dimension in which the frictional losses of the bearing fall. These dimensions have also been determined by previous studies in [11]. The rotary union, which also has bearings and rotates with same speed as the spindle, is necessary for the transfer of high pressure lubricating coolant onto the revolving shaft. An exemplary rotary union, was examined in the test bench in the interest of the friction moment. In order to determine the dependence on pressure and rotational speed, these values were varied, ranging from 0 to 80 bar and 0 to 30,000 rpm. The most unfavorable case was at 80 bar and

Sustainability in Manufacturing - Energy Efficiency in Machine Tools

283

q

30,000 rpm, resulting in a friction output of 140 W. Without pressurization a friction output of 20 W at 3000 rpm was measured. 1000 Power [W] / Torque [Nmm]

900 800

LIq

Torque sensor

500

Conection of cooling Coupling Air bearing 300

UP

Uq  PM

Ud PM

400

200

5000

Electrical Drivetrain

To analyze the electrical drivetrain with its components motor, converter and motor choke the reference spindle was mounted on a test bench and loaded with a swing frame machine. There it is possible to set different operating points and to measure rotational speed and torque. For the determination of the EER one has to measure the power of intermediate direct current link, the effective power at the motor terminals and the mechanical power at synchronized times. At high rotational speeds the spindle units with permanent magnet synchronous machines operate in field weakening mode. That means one needs very high field current (Id) to compensate the field of the permanent magnets on the rotor, which causes the linked air gap flux (ΨP). Otherwise the speed (Ω) proportional counter electromotive force (EMF) will rise to the voltage limit (ULim) of the inverter and therefore a further increasing of speed would not be possible. One has to consider that the speed in this context is the speed of the rotary field, which is mechanical speed multiplied with the number of pole pairs. This can be seen in the equation of the voltage per phase (UP) of the permanent magnet synchronous machine in steady state operation according to [12]:

 U d  jU q  R I

 j

(R) P

d

Id

Ud

d

b) field weakening

Figure 6: Vector diagrams for different operating points.

Torque Power

(R) P P

Iq

IP

a) base speed

10000 15000 20000 25000 rotational Speed [min-1] Figure 5: Test Bench for investigation of friction losses in bearings end exemplary results.

U

Uq

U Lim

IP  Iq

0

(R) P

PM

UP

600

100

4.5

q

LId

U Lim

Spindle bearing Telemetric temperature measurement

700

LIq

As can be seen in Figure 6 in field weakening operation, one gets especially at low loads (small torque current Iq) a high phase angle between voltage and current and therefor a power factor (cos(φ)) near to zero. Power measurements at those operating points are very difficult and one needs very precise measurement equipment [13]. Figure 7 shows exemplary the results for the analysis of the system at a load of 5 Nm. Therein are the losses and EER for a speed range from 6000 rpm to 28,000 rpm. The motor of the reference system starts, depending on the load, approximately at 11,000 rpm to operate with field weakening. One can see in the diagram of Figure 7 that above that speed the EER becomes lower.

 

(3)

This is the voltage equation in rotor reference frame, which is indicated by the superscript (R). Wherein Ud is the voltage in the direction of the main flux of the permanent magnets and perpendicular to that one has the voltage Uq. The inductance (L) is the sum of motor inductance and of the motor choke. Dividing equation 3 in real and imaginary part one gets the equations for Ud and Uq.

U d  R P I d   LI q

(4)

U q  RP I q  LId  PM

(5)

With those equations one can draw the vector diagram for different operating points, which is shown in Figure 6, where the operation in base speed range and in field weakening is compared. The resistance (RP) is neglected due to its less impact.

Figure 7: Results of loss power and EER measurements of the reference spindle unit. 4.6

Other Components with Energy Consumption

As described in section 2 and shown in Figure 3 there are a lot of components needed to operate the machine tool spindle units. For a holistic consideration all of them have to be taken into account. Without a detailed description they are given additionally to the named operating point dependable ones in Figure 8.

284 5

Sustainability in Manufacturing - Energy Efficiency in Machine Tools POTENTIAL FOR IMPROVEMENTS AND DEPENDENCY OF OPERATING POINT

5.1

Comparison of operation Points

With the results of the previous section two different operation points were summarized and compared to each other. Figure 8 shows the sankey diagram for operating points in base speed range compared to one in field weakening range. For both operating points the load was 5.4 Nm. One can see on the left side in Figure 8 that for lower speed the pressurized air, which is independent of the operating point, dominates the losses. Although the losses of the electrical system rise significantly at high speeds (see Figure 7) the EER of the whole system is with 56% higher than at lower speeds where only an EER of 50% could be reached. The reason for that is a big part of the energy consumption is determined by the peripheral components, which is constant for all operating points. The worst case therefore is the system when it’s ready for use and controls to zero speed at no load. To keep this state a total power of 2485 W is needed, whereof 75% are used for pressurized air.

Figure 8: Allocation of losses for two different operating points. 5.2

Potential for Improvement of Energy Efficiency

Figure 9 shows the determined system energy efficiency ratio for a constant load over the complete speed range, including all necessary components to operate the machine tool spindle unit. The system has its maximum EER of 60% at a speed of 16,000 rpm. In the graph of figure 9 three additionally scenarios for improvements are inscribed. The first of them is to reduce the load independent consumption of peripherals like pressurized air and hydraulic leakage by 30%. This reduction has especially at lower speeds, where the electric drive system has high EERs, a remarkable potential to improve the efficiency.

The second scenario provides a reduction of the losses of the electrical drive (converter, inductance and motor) about 15%. This measure has the biggest impact at high speeds. The shape of the curves in figure 9 shows how the scenarios effect on the EER depending on the operation point. One can see that the curves of the two scenarios cross nearly at the maximum of the measured EER. Hence, it is absolutely necessary to consider the whole system to achieve an improvement for all operation areas. Thus, the third case shows the combination of the first two ones. The reduction of pressurized air consumption offers very high potential for increasing the energy efficiency of the system. Therefore concept for lubrication and bearings have to be developed, which allow operation at characteristic speed values of 6 2.5x10 mm/min and higher without pressurized air. An approach could be seen in grease reservoir lubrication for high speed spindle bearings. Also for the sealing air one can think about alternatives through complex designed labyrinth-sealing, so that the consumption of sealing air could be reduced or completely avoided. However this could result in higher costs and has to be compared with the life cycle costs but could be a benefit after a short amortization time. For further possible savings the user profile of the machine tool and spindle unit has to be regarded. For machining with many tools and short primary process times the secondary process times caused by tool changes consume a considerable part of the machining time. The reduction of the chip-to-chip time, e.g. at the machining of crankcases for engines, could rise productivity and efficiency. The chip-to-chip time [14] includes the movement of the axes, the tool change itself and the run-up and breaking of the spindle unit. Depending on the required speed the acceleration and deceleration of the spindle holds the biggest part of the tool changing time. Because of that in many machining centers the drive capacity of the spindle unit is oversized. That means the maximum torque is chosen two to three times higher than it would have been necessary for the cutting process to reduce run-up times. Figure 10 shows the power consumption of the electric drive during such a machining cycle.

Figure 10: Duty cycle for a machine tool spindle unit. The objective in the project “EnergieMSP” is to reduce the inertia of the spindle shaft by lightweight design with carbon fiber composites so that the same accelerations could be achieved with much lower torque. One aim is to have a direct connection to the bearings so that the utilization of the advantageous material density of the composite would be compensated through added steel sleeves. Preliminary studies with prototypes are actually done.

Figure 9: Measured system energy efficiency ratio and scenarios for improvements.

As an alternative to the conventional tool clamping with springs and hydraulic disengagement an electro-mechanic system was tested on a prototype. This show clearly advantages in the energy consumption, which is only regarded for clamping and releasing the tool. The electro-mechanic solution needed 0.11 Wh per tool

Sustainability in Manufacturing - Energy Efficiency in Machine Tools

285

change whereas the hydraulic system needs 0.59 Wh. However there is a disadvantage during the clamped time, because the electro-mechanic system requires 287 W of auxiliary energy compared to 36 W of the hydraulic system. Hence, this is only useful in cases with a high number of tool changes per hour.

Anwendung von Lebeszykluskostenanalysen von Werkzeugmaschinen, Gabler, pp. 51-80.

Furthermore the concept for the electric drive train is to use additional components for energy storage (capacitors) to buffer power peaks, which occur at frequent tool changes. Measures like this provide also the possibility for the recovery of the kinetic energy at a deceleration of the spindle unit for e.g. tool changes [15]. Thus, power supply could be reduced in design size, which results in lower cost for connection power. Regarding the improvement of the drive itself it is also important for which using profile the spindle unit is designed. For a universal usage or the described application above permanent magnet synchronous machines with field weakening ratios of 3:1 to 4:1 are preferred. The reason is the high EER up to nominal speed and the high specific power. A possibility for improvement is an better adjustment between motor and converter. For given voltage and current output limits one has to minimize field weakening so that only the minimum reserve for compensation of load steps without big breaks in speed remains. Those measures were supported with improvements of the motor through other winding schemes (double layer windings, single coil winding, higher filling factors) and alternative materials for the magnetic circuit of the machine. If the spindle unit is mainly used for long terms at high speeds asynchronous machines could be the better alternative. Moreover for machining at highest speeds or at highest speed parameters for bearings the minimization of the friction within the bearings could deliver a significant proportion to increase the system EER. Therefore spindle bearings with modified geometries of bearing races and cages were developed from the project consortium of “EnergieMSP”. 6

Kuhrke, B.; Erdle, F. (2010); Energieeffizienz als Investitionskriterium in Werkstatt und Betrieb 1, 2/2010.

[5]

Abele, E.; Kuhrke, B.; Rothenbücher,S. (2010): Entwicklungstrends zur Erhöhung der Energieeffizienz spanender Werkzeugmaschinen, in:1st International Colloquium of the Cluster of Excellence eniPROD, pp. 99-120.

[6]

Gutowski, T., Dahmus, J., Thiriez, A. (2006) "ElectricalEnergy Requirements for Manufacturing Processes",Proceedings of the13th CIRP International Conference on Life Cycle Engineering, May 31st-June2nd, 2006, Leuven, pp. 623-628.

[7]

Dahmus, J., Gutowski, T. (2004) An environmental analysis of machining, Proceedings of IMECE2004, 2004 ASME International Mechanical Engineering Congress and RD&D Expo, November 13-19, Anaheim,California USA.

[8]

VDMA 24378 (2009): Prognose des Energieverbrauchs von Lackieranlagen (Entwurf), 03, 2009.

[9]

Abele, E.; Brecher, C.; Altintas, Y. (2010): Machine tool Spindle Units, in: CIRP Annals - Manufacturing Technology, Volume 59, Issue 2, pp. 781-802.

[10]

Gebert, K. (1997): Ein Beitrag zur thermischen Modellierung von schnelldrehenden Motorspindeln. Dissertation TUDarmstadt.

[11]

Steinert, T. (1995): Das Reibmoment von Kugellagern mit bordgeführtem Käfig, Dissertation RWTH Aachen.

[12]

Schroeder, D. (2009): Elektrische Antriebe – Regelung von Antriebssystemen, Springer-Verlag, Berlin-Heidelberg.

[13]

Huber, W. (2010): Elektrische Verluste und Wirkungsgrade, in Elektronik Praxis, No.8 2010.

[14]

VDI 2852: Kenngrößen numerisch gesteuerter Fertigungseinrichtungen; Span-zu-Span-Zeit bei Automatischen Werkzeugwechsel.

[15]

Diaz, N.; Helu, M.; Jarvis, A.; Tonissen, S.; Dornfeld, D.; Schlosser, R. (2009): Strategies for Minimum Energy Operation for Precision Machining. Proceedings of MTTRF 2009 Annual Meeting, Shanghai.

SUMMARY

This article referred about the results of the analysis of a representative machine tool spindle unit and the identified possibilities for improvement of energy efficiency. The identified potentials were used as a base for the design and realization of an energy efficient spindle unit. The results show that it basically makes sense to reduce the consumptions of the peripherals like pressurized air, hydraulics and stand-by consumption of power electronics, which are independent from the operating points. Those measures also provide enormous potential for the improvement of the complete machine tool. Regarding the electric drive train, bearings and tool change system the possible improvements strongly depend on the using profile of the spindle unit and have to be reflected with the additional costs, which those measures cause. 7

[4]

REFERENCES

[1]

Council of the European Union, Directive 2005/32/EC of the European Parliament and the Council of 6 July 2005 establishing a framework for the setting of ecodesign requirements for energy-using products and amending Council Directive 92/42/EEC and Directives 96/57/EC and 2000/55/EC of the European Parliament and the Council, Official Journal of the European Union, Brussels 22.07.2005.

[2]

Schiefer, E. (1999): Analyses of the energy consumption of a Traub TNS 65/80D within the machining production of the Heidelberger Druck AG, PTW.

[3]

Abele, E; Dervisopoulus, M.; Kuhrke, B. (2008): Schweiger, S. (Editor) Lebenszykluskosten optimieren Bedeutung und

Energy Consumption as One Possible Exclusion Criterion for the Reuse of Old Equipment in New Production Lines 1

1

1

1

Lars Weyand , Helmut Bley , Martin Swat , Kirsten Trapp , Dirk Bähre 1

1

Institute of Production Engineering, Saarland University, Saarbruecken, Germany

Abstract The reuse of production equipment represents a promising approach to saving investment costs. Therefore, more and more companies are taking the topic of reuse into consideration. However, there are also risks and disadvantages concerning the reuse of old production equipment. In some cases, reusing old equipment can eventually be more expensive than buying new resources. Therefore, an adequate reuse assessment is necessary. Not only technical factors and investment costs have to be considered, life cycle aspects such as energy consumption play a crucial role as well. In this paper, an approach to a risk-reduced reuse of old equipment is presented. Keywords: Production Equipment; Reuse; Energy Consumption

1

INTRODUCTION

If manufacturers decide to reuse resources from previous production lines, they are theoretically able to take important competition advantages [1], [2]. Investment costs regarding the purchase of new equipment can be reduced and moreover, problems during the ramp-up phase can often be avoided due to the knowledge regarding old resources within their own company. Therefore, more and more companies are taking the topic of reuse into consideration. However, there can also be disadvantages concerning the reuse of old production equipment. Uncertainties regarding the suitability of the resources and regarding the spare parts supply present a risk and warranty claims regarding old equipment usually do not exist. There is partly no sufficient experience with the issue of dealing with the topic of reuse and business processes in this area are often not fully developed [3]. In some cases, reusing old equipment can eventually be more expensive than buying new resources due to life cycle aspects. Table 1 summarizes the discussed pros and cons regarding the reuse of old production equipment.

Reuse of assembly equipment

In order to adequately deal with the topic of reuse, a detailed reuse assessment is necessary. This reuse assessment has to take lots of different aspects into account. Not only technical factors and investment costs have to be considered, life cycle aspects and the resulting life cycle costs play a crucial role as well. One important life cycle aspect is the topic of energy consumption [4], [5]. Energy is a requested, limited and increasingly expensive commodity that exerts economic and ecological pressure on production companies [6], [7], [8]. This aspect has to be considered in connection with modern production planning [9] – especially if equipment from old production lines is to be reused. This paper deals with the topic of reuse and energy efficiency in the area of production planning. A special approach which allows performing a selective reuse planning is presented. This approach also considers the topic of energy consumption in an explicit way. It is explained how energy aspects can be taken into account at the early stages of production planning and a method allowing product variant-oriented energy calculations is introduced. 2

EXISTING APPROACH EQUIPMENT

TO

REUSING

PRODUCTION

- Reduction of the necessary investments in new resources

A planning workflow for a selective reuse planning has already been presented in [10], [11]. The approach mentioned is a 3-step approach which considers reuse aspects already in the planning process so that reusable equipment is automatically identified. Consequently, there is no need to start the planning process by considering reuse restrictions, whereas this is possible too.

- Feasible from a technical point - In some cases, more efficient of view, problems during the resources could be available ramp-up phase do not have to on the market be expected

In a first step, a so-called early resource calculation has to be executed. The early resource calculation determines the equipment which would be bought today considering the latest technical achievements and innovations available on the market. It is a planning activity in which new equipment which fulfils the requirements of the planning task in the best way is identified. Due to the fact that the final need of resources – the number of necessary resources – can be determined after the line balancing only, this obviously is only a first, rough calculation.

Advantages

Disadvantages

- Uncertainties concerning the suitability of the old resources and concerning the spare - Knowledge concerning the use parts supply of the resources within the company - No warranty claims

Table 1: Advantages and disadvantages of reusing resources.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_50, © Springer-Verlag Berlin Heidelberg 2011

287

288

Sustainability in Manufacturing - Energy Efficiency in Process Chains

In a second step, a so-called reuse calculation has to be taken into account. It has to be checked whether old equipment, which fulfils the general requirements too, is available. As to the decision whether to favor old or new equipment, not only technical aspects and cost calculations regarding initial investment costs have to be taken into consideration. Life cycle aspects and life cycle costs have to be considered as well and both aspects are included in the developed approach. As to the calculation of the remaining life time, some publications have already dealt with this topic – for instance in the publications [12], [13], [14], [15]. Regarding big companies, it is rated as reasonable to put experts from the maintenance and repair department in charge of calculating the remaining life time of the resources. Weibull analyses are necessary and talks with the resource suppliers make sense too. The third step is called final resource planning. As explained in [11], this activity is necessary due to the fact that the line balancing finally determines the number of resources needed. Figure 1 shows the elaborated reuse planning approach including the three steps described above dealing with resource planning activities. As to the reuse calculation, lots of data regarding the old equipment has to be available (performance data, installation data, data regarding performed modifications, data in respect of completed hours of operation, data of former activities concerning resource availability and malfunctions, in the best case a CAD model, additionally recent photos etc.).

Planning data

Early resource calculation2

Process planning1

not okay

Preliminary resource list

Processes

Iterative improvements

okay

not okay

Line balancing

Reuse calculation

No. of stations, assembly sequence, …

Preliminary Preliminary reusable new equipment equipment

okay Final resource planning

not okay

Final resources (old + new equipment) okay Digital validation checks

not okay

Checked PPR models

Further planning activities 1,2 Based

on digital graphs PPR = Product-Process-Resource Figure 1: Developed planning workflow according to [11], [16].

In general, the old resources have to be assessed from many different perspectives. It is proposed to involve experts from different departments in the assessment activity. These experts have to have special knowledge and experience concerning the relevant areas. It is expected that at least one expert from the quality department, one from the maintenance and repair department, one from the occupational safety and the environment protection department, one from the control engineering department and one expert from the cost department will be needed. Every expert has to give a detailed, written statement about the suitability of the equipment initially rated as reusable and has to guarantee by his or her signature that all statements are made to the best of his or her knowledge. In general, every expert needs his or her own digital assessment form which contains particular fields to be filled in. These digital forms can consist of several pages. Finally, it could be reasonable to integrate all of the digital forms into one final form containing only the most important data. This final digital form presents the basis for making the final decision. From our point of view, the whole assessment process has to be supported by software. A suitable digital working environment including a reuse library and possibilities for cross-functional communication has to be available [16]. The general suitability of the approach has already been checked based on a separate example taken out of the automotive industry. A scenario of a side door assembly has been discussed in detail [10], [17]. By means of the discussed side door example, it was shown that the developed concept is feasible, whereas the created software prototype still has to be improved in order to be able to guarantee fast and comfortable reuse assessments. The obtained results are promising, whereas it is clear that further examples have to be investigated. There are still some points which have to be discussed in more detail. One aspect is the topic of how to deal with energy aspects more explicitly. Section 3 shows how energy aspects can be considered in a local way in connection with the reuse calculation in which old and new resources have to be compared. In contrast to that, Section 4 explains how the energy consumption of the whole production line, which is still being developed, can be calculated. Moreover, a method for calculating variant-specific energy consumptions is introduced. 3

DETAILED CONSIDERATION OF WITHIN THE REUSE APPROACH

ENERGY

ASPECTS

Within the developed approach, it is differentiated between the two following values of energy consumption: “energy consumption of the resource Rj per hour in the case of use (||Euse, Rj||)“ and “energy consumption of the resource Rj per hour in the case of stand-by ((||Eidle, Rj||)“. As to the approach presented in Section 2, the energy consumption of new and old resources can be immediately compared by production planners during the reuse planning. It is a paired comparison analysis of energy values regarding ||Euse, Rj|| and ||Eidle, Rj||. The results of this comparison have to be checked regarding their acceptability. Strong deviations can lead to an exclusion of old resources even if all other requirements – the requirements regarding quality, safety etc. – are fulfilled. Interesting examples of significant improvements regarding the energy consumption of resources can be found in recent publications. In respect of laser welding, the improvements regarding laser sources – the change from rod to disk lasers – are impressive. More than half of the costs for cooling and electricity can be saved with modern disk lasers. In [18], a quantitative comparison of a modern 4 kW disk laser and a modern 4 kW rod laser is presented. The comparison is based on the following boundary conditions: the laser sources are in use during 8 years, 3shifts per working day and the average duty rating is 75%. The disc

Sustainability in Manufacturing - Energy Efficiency in Process Chains laser finally causes lower operating costs than the rod laser. As to the disc laser, the operating costs per hour are approximately 18 €, whereas the rod laser causes expenses of over 20 € per hour in the same situation. From the point of view of investment costs, this result is surprising due to the fact that the disc laser is more expensive than the rod laser. The final reason for the better result of the disc laser is its lower energy consumption. The electricity costs per operating hour for instance are approximately 1.4 € in comparison to 7.5 €. The energy savings of the disc laser are so important that it surpasses the higher investments costs in the total calculation. In this case, a reasonable final decision would be to purchase the disc laser instead of the rod laser. A similar progress regarding energy savings as mentioned in connection with the laser sources has been reached in the area of industrial furnaces [19]. Moreover, cleaning processes have become more efficient too [20]. The above-mentioned comparison of laser sources considers new resources. In case of comparing old and new equipment, it can be assumed that the differences regarding the energy aspects can be even more extreme – e.g. in case of an old rod laser which has to be compared with a new disc laser. From our point of view, there is no doubt that energy consumptions can play an important role within reuse discussions. If there are old, energy-consuming resources which would have to be uninstalled, transported, reinstalled, adapted and commissioned with much effort in order to fulfill new tasks in reuse scenarios, the purchase of new, energyefficient resources could be the better solution. As to production planning – including reuse planning –, it is proposed to use planning software. The general aim is to support

289 production planners as much and as good as possible so that suboptimal solutions can be avoided. In the case of using planning software, the comparison of the energy values could be performed by software and the identified deviations could be classified automatically. The impact of the deviations could be visualized by means of different colors – for instance green for small deviations, yellow for medium deviations and red for strong deviations. The limits of the colored areas naturally have to be defined in advance. In our model – a classic product-process-resource model –, the energy values are eventually transferred from the resources to the processes in connection with the process-resource allocation. The equipment-specific values regarding the energy consumption are then becoming attributes of the processes, whereas it does not matter whether an old or new resource is allocated to a process. In order to simplify the issues discussed in this paper, it is defined that only one resource can be allocated to one process. Moreover, it is assumed that a process needs a resource full time (100% of the process time) in the case of a process-resource allocation. In the simplest case, each process Pi consequently contains five energyrelevant attributes: a process time (ti), a frequency of use (fi), an energy consumption per hour in the case of use (||Euse, Pi||), an energy consumption per hour in the case of stand-by (||Eidle, Pi||) as well as a rate (ri) defining the energy costs in Euro per consumed kilo joule, which depends on the operating method of the resource. Furthermore, the process contains information about the product variants that need to make use of this special process. Figure 2 shows what happens in the case of a process-resource allocation and it summarizes all the points discussed above.

Process without resource allocation

P1

Process with resource allocation

Process attributes t1 f1 r1 ||Euse, P1|| = 0 ||Eidle, P1|| = 0 …

Process attributes t1, f1, r1 ||Euse, P1|| = ||Euse, R3|| ≠ 0 ||Eidle, P1|| = ||Eidle, R3|| ≠ 0 …

Resource attributes ||Euse, R3|| ≠ 0 ||Eidle, R3|| ≠ 0 …

R3 P1

Processes in a process graph Process step 1 f1 = 100% t1, r1 ||Euse, P1||, ||Eidle, P1|| …

Process step 2

Process step 3

R2 P2

R1

R3

f2 = 70% t2, r2 ||Euse, P2||, ||Eidle, P2|| …

1,2

P1 f4 = 30% t4, r4 ||Euse, P4||, ||Eidle, P4|| … V

V

R4

1,2,3

V

P3 1,2,3

P4 3

1,2,3 Product variants

f3 = 100% t3, r3 ||Euse, P3||, ||Eidle, P3|| …

Variant elements which include alternative processes (here: P2 and P4 are alternative processes; either P2 or P4 is executed during the production; it is impossible that both processes are executed during the same time) Regarding a process step which contains two variant elements V , the rule is: n fi, if the variant elements V contain the process Pi ∑ fi, alternative = 100% fi, alternative = 0, in all other cases i=1

Figure 2: Transfer of resource attributes to process attributes within the model.

290

Sustainability in Manufacturing - Energy Efficiency in Process Chains

In general, it is not enough to look at the energy consumption in a local way only. In fact, a paired comparison analysis of energy values within the step of reuse planning is a first necessary check in respect of acceptable energy consumptions but further analyses regarding the energy efficiency of the whole production line and regarding the products and product variants which are produced in this line have to be performed – at least at this point of time at which a complete draft of the production line is available. This is an important point especially due to the fact that production lines are often divided into sections and planned section by section by different production planners so that a complete overview of the production line and its energy consumption is often missing at early planning stages. Therefore, it is proposed to perform further global analyses if a complete draft of the production line is available. Such global energy analyses are necessary particularly if the management has defined limits regarding the allowed energy consumption. One reasonable target of the management could define that new lines would have to be less energy-consuming than former similar production lines. Section 4 deals with the topic of calculating the energy consumption of production lines in a more detailed way. 4

CALCULATING THE PRODUCTION LINES

ENERGY

CONSUMPTION

optimization step could also lead to the result that fewer resources could finally be reused due to their suboptimal energy consumption. In general, it is proposed to automatically calculate the average energy consumption of the production line as well as the variantspecific energy consumption by software. A manual calculation of values that is time-consuming and error-prone should be avoided. Moreover, the use of software offers further advantages. Results could be pictured in a clear way by means of digital diagrams and an intelligent digital environment could automatically generate proposals regarding improvements. An unbalanced situation regarding the energy consumption of product variants can be dangerous even if the average energy consumption of the production line per piece is lower than the defined target. One reason for that might be that the sales forecasts regarding product variants are uncertain. Customers could eventually order more product variants that need lots of energy in the production process and in this case, the average calculations performed in the step of production planning would be wrong. Therefore, it is not enough to perform average calculations only – variant-specific analyses are necessary as well. It should always be tried to reach a balanced situation.

OF

Symbols

Regarding a first assessment of the production line, it is reasonable to consider the average energy consumption of the production line per piece. The aforementioned average energy consumption of the production line per piece can be calculated – considering the assumptions of Section 3 – based on equation (1).

 n  E    ti  || Euse, Pi ||  f i     i 1

(1)

  G    ti  || Eidle, Pi || 1  f i    i kJ   i 1  i1 py  n

Description

Unit

E

Average energy consumption of the production line per piece

[kJ]

E(x)

Variant-specific consumption of energy regarding one product variant x

[kJ]

n

Number of processes within the process graph

/

m

Number of additional energy consumptions which are considered

/

ti

Process time of the process Pi

[h]

Process time of the process Pi in case this process is part of the analysed product variant x

[h]

m

However, it can be dangerous to work with average calculations only. An explicit examination of energy aspects regarding single product variants has to be performed too. The goal of each company should be to produce each of their product variants in an energy-saving way and to make a progress regarding the energy consumption from one product generation to the next. The variantspecific consumption of energy regarding one product variant x can be calculated based on equation (2). All symbols of equation (1) and (2) are described in Table 2.

  E ( x )    vi ( x) || Euse , Pi ||     i 1 n

     ti  || Eidle, Pi ||      i1 n

    vi ( x) || Eidle, Pi ||     i1  n

(2)

Gi   kJ   i 1 py   m

Equation (2) delivers the variant-specific energy consumption, whereas the results can be used for comparisons and conclusions. In case a target regarding the energy consumption is not met, possibilities for reducing the variant-specific consumption have to be taken into account, whereas it has to be considered that the average energy consumption of the production line will be affected as well. Moreover, production planners have to be careful in respect of optimizations due to the fact that more aspects than only the energy aspects mentioned have to be considered. However, an

vi(x)

vi (x) = ti, if Pi necessary for x vi (x) = 0, if Pi not necessary for x ||Euse, Pi||

Energy consumption of the process Pi per hour in the case of use

[kJ/h]

||Eidle, Pi||

Energy consumption of the process Pi per hour in the case of standby

[kJ/h]

fi

Frequency of use of the process Pi

x

Product variant analysed

Gi

Energy consumptions that are not considered within the equations (In accordance with [21], energy per year used for lighting, heating etc.)

py

Predicted number of pieces which will be produced within the production period of one year Table 2: Description of symbols.

[%] /

[kJ]

/

Sustainability in Manufacturing - Energy Efficiency in Process Chains

291

In order to show that average calculations often have to be treated with caution, one simple example dealing with drilling processes and their energy consumption is discussed. The example is not connected to a reuse scenario, but it is sufficient to show that focusing on average values exclusively can lead to risks. The analyses have been performed at the Saarland University in connection with a student research project [22]. Different parameters have been varied in the analyses and their impact on energy consumption has been investigated. However, only the impact of the diameter will be discussed in this section in a bit more detail.

Energy costs can be calculated by means of equation (3) and equation (4). Cø represents the average energy costs of the production line per piece, whereas C(x) represents the variantspecific energy costs of one specific product variant x.

In our case, there are two different product variants which get different drill holes. Product variant 1 gets a drill hole with a diameter of 7.5 mm, whereas the diameter is 15 mm regarding the second product variant. As shown in Figure 3, the realization of the different holes causes different energy consumptions concerning the drilling machine. In order to realize a hole with a diameter of 7.5 mm, an electrical energy of 15.456 kJ is needed. As to the hole with a diameter of 15 mm, 30.831 kJ are necessary. The sales forecast states as follows: It is assumed that 70% of the yearly total production will deal with product variant 1, whereas the remaining 30% will be needed for product variant 2. Based on this forecast, the average energy consumption can be calculated. In this example, 20.063 kJ per piece are needed on average. At this point, the question occurs whether this result is reliable.

 n  C ( x)    vi ( x) || Euse , Pi || ri   i  1   

By concentrating on the variant-specific results and comparing the obtained values, it is obvious that there is an unbalanced situation: product variant 2 consumes nearly twice the energy needed for product variant 1. Consequently, it is clear that the average result is not reliable. If the demand situation is different from the one defined in the forecast, the manufacturer will probably be confronted with higher energy consumption and higher costs. If 70% of the yearly total production will deal with product variant 2 for instance in reality, an average energy consumption of 26.206 kJ per piece will result out of the drilling process. This means that the consumption would be approximately 31% higher than calculated within the planning phase. Of course, this is a simple example, but it shows that focusing on average values is not reliable in unbalanced situations. Therefore, it is proposed to use not only equation (1) in order to assess the energy consumption of production lines – from our point of view, further variant-specific analyses are necessary. The variant-specific analyses especially become interesting if mixed-model production lines which consist of a high number of variant-specific processes and resources are considered at the planning stage.

Energy consumption [kJ]

E (1) 1 Sales forecast:

70%

E (2)

2 30%

  n  m G   ti  || Eidle , Pi || ri  1  f i    i  rgi € py  i1  i1 

 n     ti  || Eidle, Pi || ri      i 1

(3)

(4)

  n  m G   vi ( x) || Eidle , Pi || ri    i  rgi €  py  i1   i1  Within equations (3) and (4), information about the rates ri defining the energy costs of the processes Pi per consumed kilo joule as well as information about the rates rgi defining further general energy costs of the production line per consumed kilo joule, which are not considered in other terms of the equations, is necessary. The unit of the rates ri and rgi is Euro per kilo joule. The calculation results can finally be visualized again in diagrams which contain a high transparency. The resulting diagrams are basically similar to the diagram shown in Figure 3, whereas in this case the axis of the ordinate considers energy costs, not energy consumption. Based on the favored diagrams, product variants with high energy consumption and/or high energy costs can be easily identified. The clear presentation of the existing conditions regarding energy consumption and energy costs has some advantages. Misinterpretations and information losses in case of information transfer can be avoided or at least reduced. Moreover, comparisons with other production lines become much easier through the use and superposition of the diagrams. Regarding intelligent digital environments, it can be said that such systems would offer the possibility of automatically identifying the most energy-intensive processes. In the case that process graphs, as described in [16], are used, a feedback regarding suboptimal processes could be executed again in a visual way. Inadequate processes regarding the energy consumption can be highlighted in terms of color in process graphs. All in all, it is rated as necessary to support the whole production planning process by software. In the future, production planners will need simple and transparent software tools which can be easily used and which offer the possibility for performing general as well as variant-specific assessments [16]. This type of software tool is also required as far as energy analyses of production lines are concerned.

30.813 E  =20.063 15.456

 n  C    ti  || Euse , Pi || ri  f i     i1

Product variants

Product variant 1: D = 7.5 mm, Product variant 2: D = 15 mm Material: 16MnCr5, Drilling depth: 10 mm E = (15.456 * 0.70) kJ + (30.813 * 0.30) kJ = 20.063 kJ Figure 3: Drilling process and its energy consumption depending on varying diameters in accordance with [22].

5

SUMMARY AND OUTLOOK

Energy efficiency becomes a more and more important topic in the manufacturing industry. In this paper, it has been discussed how energy aspects can be considered in connection with a reuse planning approach which aims at reusing old production equipment in new production lines in order to save costs. In this context, it has been clarified that an unacceptable energy consumption of the old equipment can finally lead to the decision to purchase new equipment. However, it has also been mentioned that it is not

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sufficient to look at energy aspects from a local perspective only. A paired comparison analysis of energy values of old and new resources within the stage of reuse planning is only the first step that is necessary. Further analyses regarding the energy efficiency of the whole production line and the products and product variants which are produced in this line certainly are necessary.

[8]

Takata, S.; Kimura, F.; van Houten, F.J.A.M.; Westkämper, E.; Shpitalni, M.; Ceglarek, D.; Lee, J. (2004): Maintenance: Changing Role in Life Cycle Management, CIRP Annals Manufacturing Technology, Volume 53, Issue 2, pp. 643-655.

[9]

Jawahir, I.S.; Holloway, L.; Rouch, K.E.; Hall, A.; Dillon, JR., O.W.; Knuf, J. (2005): Design for Sustainability (DFS): New Challenges in Developing and Implementing a Curriculum for Next Generation Design and Manufacturing Engineers, 3rd SME International Conference on Manufacturing Education.

[10]

Weyand, L.; Bley, H. (2010): Automotive Final Assembly Planning and Equipment Reuse, International Conference on Competitive Manufacturing (COMA), pp. 343-348.

[11]

Weyand, L.; Bley, H.; Merl, D. (2010): Boundary Conditions for a Selective Reuse Planning in the Automotive Industry, 7th CIRP International Conference on Intelligent Computation in Manufacturing Engineering (ICME).

[12]

Kara, S.; Mazhar, M.; Kaebernick, H.; Ahmed, A. (2005): Determining the Reuse Potential of Components Based on Life Cycle Data, CIRP Annals - Manufacturing Technology, Volume 54, Issue 1, pp. 1-4.

[13]

Anityasari, M.; Kaebernick, H. (2008): A concept of reliability evaluation for reuse and remanufacturing, International Journal of Sustainable Manufacturing, Volume 1, Number 1-2, pp. 3-17.

[14]

Weule, H.; Buchholz, C. (2001): Method for assessment of reuse suitability within modular assembly systems, Assembly Automation, Volume 21, Number 3, pp. 241-246.

This research activity was partly supported by the research project “Flexible Assembly Processes for the Car of the Third Millennium (MyCar)” funded by the Commission of the European Union and by the research project “Ganzheitliche Gestaltung energieeffizienter technologischer Prozessketten (enPROchain)” funded by the program „Zentrales Innovationsprogramm Mittelstand (ZIM)“ of the German Ministry of Economics (BMWi).

[15]

Fitzgibbon, K.; Barker, R.; Clayton, T.; Wilson, N. (2002): A failure-forecast method based on Weibull and statisticalpattern analysis, Annual Reliability and Maintainability Symposium, pp. 516-521.

[16]

Weyand, L. (2010): Risikoreduzierte Endmontageplanung am Beispiel der Automobilindustrie – Risk-reduced Final Assembly Planning in the Automotive Industry, Dissertation, Universität des Saarlandes.

7

[17]

Weyand, L.; Bley, H. (2010): Planning of Final Assembly Lines which are Flexible in Respect of the Output, 3rd CIRP Conference on Assembly Technologies & Systems (CATS), pp. 7-12.

[18]

Hammer, T.; Brockmann, R. (2006): Scannerschweißen mit dem Scheibenlaser – Remote Laser Welding by Disc Laser, Laser Technik Journal, Volume 3, Issue 3, pp. 36-38.

Methods of calculating the energy consumption of a production line have been presented. In this context, it has been mentioned that the results of average calculations partly have to be handled with caution. Average calculations that are based on uncertain sales forecasts usually deliver hints regarding the annual energy consumption of the line, but they are not reliable in unbalanced situations and they do not give any information about the energy efficiency of single products and product variants. Therefore, additional variant-specific analyses are necessary. All in all, first promising results have been obtained, whereas there is no doubt that further examples have to be discussed in the future and that the presented equations still have to be enhanced where necessary – at this point, the underlying assumptions included in the equations should not be forgotten. Moreover, it has to be discussed in the future how available software prototypes can be modified so that energy aspects can be addressed as explicitly as mentioned in this paper. Production planners need transparent software tools which are easy to use and which offer the possibility for performing general as well as variant-specific assessments – also regarding the topic of energy efficiency. 6

ACKNOWLEDGMENTS

REFERENCES

[1]

Ko, J.; Hu, S.J.; Huang, T. (2005): Reusability Assessment for Manufacturing Systems, CIRP Annals - Manufacturing Technology, Volume 54, Issue 1, pp. 113-116.

[2]

Weule, H.; Buchholz, C. (2001): Re-use of Assembly Systems: A great ecological and economic potential for facility suppliers, Proceedings of SPIE, the International Society for Optical Engineering, Volume 4193, pp. 44-55.

[3]

Fleschutz, T.; Harms, R.; Seliger, G. (2009): Valuation of Assembly Equipment Reuse with Real Options, 20th Annual Conference of the Production and Operations Management Society.

[4]

Dewulf, W.; Duflou, J. (2003): Simplifying LCA Using Indicator Approaches - A Framework, CIRP Seminar on Life Cycle Engineering.

[5]

Grote, K.-H.; Antonsson, E.K. (2009): Springer Handbook of Mechanical Engineering.

[6]

Herrmann, C.; Zein, A.; Thiede, S.; Bergmann, L.; Bock, R. (2008): Bringing sustainable manufacturing into practice – the machine tool case, Sustainable Manufacturing VI: Global Conference on Sustainable Product Development and Life Cycle Engineering.

[7]

Jeswiet, J.; Duflou, J.; Dewulf, W.; Luttrop, C.; Hauschild, M. (2005): A Curriculum for Life Cycle Engineering Design for the Environment, 1st Annual CDIO Conference.

[19] Irretier, O. (2010): Energieeffizienz in Industrieofenbau und Wärmebehandlung – Maßnahmen und Potentiale, Energy efficiency in industrial furnace engineering and heat treatment – provisions and potentials, in: elektrowärme international, pp. 37-44. [20]

Krebs, M.; Deuse, J. (2009): Parts cleaning in the value stream, 3rd International Conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV), pp. 800-809.

[21]

Rahimifard, S.; Seowa Y.; Childs, T. (2010): Minimising Embodied Product Energy to support energy efficient manufacturing, CIRP Annals - Manufacturing Technology, Volume 59, Issue 1, pp. 25-28.

[22]

Latz, C.; Jost, S. (2010): Energieverbrauch in der spanenden Fertigung am Beispiel Bohren – Energy consumption in metal-cutting manufacturing based on the example of drilling, Institute of Production Engineering, Student research project, Saarland University.

Optimizing Energy Costs by Intelligent Production Scheduling 1

Agnes Pechmann , Ilka Schöler 1

1

Department of Mechanical Engineering, University of Applied Sciences Emden/Leer, Emden, Germany

Abstract Small and medium sized enterprises tackle the problem of high energy consumption and costs. Reducing both by fixing leaks, improving the thermal insulation of buildings and switching of unnecessary heating/cooling are first steps. More advanced steps are reengineering machinery and processes. Within this paper results of a research project are presented. Unused potential for increasing energy efficiency can be found by optimizing the production schedule. A full scale PPC software was developed which is able to schedule production without energy peaks and furthermore is able to create a 24h energy forecast to hand over to the energy supplier. Keywords: Production Planning and Controlling; Energy Peaks; Load Management

1

INTRODUCTION

With Technical solutions the full potential to increase energy efficiency is not exploited, organizational aspects need to be discovered as well. An optimized production schedule is a further step towards increasing energy efficiency. First steps in reducing the energy demand for production sites are to collect information regarding the current status of the energy consumption and to analyze the potential to avoid or reduce it [1]. Technically easy but very effective steps to avoid energy consumption are e.g. fixing leaks (pressured air), improving the thermal insulation of buildings, and switching off unnecessary lighting and heating/cooling. Technically more advanced steps to decrease the energy consumption are elevating the energy efficiency of machinery and processes, integrating renewable energy and helping to stabilize the energy grid by avoiding energy peaks. Research has been done concerning the question on how to reduce the energy consumption within a production site covering thermal insulation of facilities, reduction of conversion losses, optimization of the production processes (e.g. reducing the production temperature or pressure) [2, 3]. Little has been researched on savings (energy, CO2, costs) due to organizational optimization on the shop floor itself. [4, 5]. Is there still potential to reduce energy consumption and energy peaks when considering regular restriction set by the market and or the customer like short delivery times? How does this change when considering non-omissible interferences caused by machinery, material or humans? How is it possible to handle the necessary plan and control data? Industrial planning and controlling generally focus only on the direct economic and technical aspects, neglecting so far the role of energy consumption and its possibilities of cost savings. In order to preserve the environment and develop a sustainable industry (in terms of economic and natural resources), the scarce and efficient use of energy must be included among the target values for industrial intelligent production scheduling and controlling.

The latest German energy concept of September 2010 underlines the need for environmentally friendly electrical power supply. In times of climate change due to high greenhouse gas concentration, raising need of energy and consequently, a higher need of energy import, it is necessary to provide a dependable and affordable electrical power supply in Germany [6]. The supply is one side; the demand is the other side to look at when talking about reducing CO2 emission and the dependability on foreign energy sources. We will focus on reducing and optimizing the demand. The main focus within the BMBF sponsored research project called Energy (E-)PPS (support code 01LY0813A) is to develop a production planning and controlling software which is able to handle regular PPC tasks and to reduce energy consumption by intelligent scheduling and organization of production processes. The software is targeted toward small and medium sized production facilities with a wide range of standard products with small to mid size series. Controlling energy consumption of production processes and optimizing its use in respect to timing by key energy indicators creates the necessary visibility of the energy demand and its related costs. Then as the second and main step of optimization the avoidance of cost intensive energy peaks through intelligent production scheduling is targeted. The very practical oriented approach within the project leads towards a better understanding of the energy demand and its related costs as stated above. The E-PPS software is a full scale PPC-software and is developed for small and medium production sites with a high variety of products. Beyond that the scheduled production runs without high energy peaks. Furthermore the E-PPS creates a 24 hour energy forecast to hand over to the energy supplier. Any short notice change in production such as “emergency” orders or machinery break down is implemented into the production schedule corresponding the 24 h forecast. After this first introductory part, some basic, relevant facts of the energy power market will be presented in chapter two, followed by aspects regarding energy consumption of manufacturing processes (Chapter 3). In chapter four we will list established approaches on how to decrease energy consumption as such, and we will point out

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_51, © Springer-Verlag Berlin Heidelberg 2011

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possibilities of a more holistic approach on energy cost savings. In order to control the changes required for a successful cost saving program energy key performance indicators (KPIs) are of value. The identification of these KPIs is the focus of chapter five. The purpose and use of the E-PPS software and the requirements for such production planning and scheduling software is stated in chapter six, followed by the necessary requirements of production processes for its use (Chapter 7). The paper concludes with an outlook on the future of E-PPS and next steps and a short summary. 2

IMPORTANT ENERGY (-MARKET) FACTS

The energy market as such is a highly developed and dense market not only in Germany. One of the main points to know as an energy consumer with interest in optimizing energy costs is how the electricity costs sum up, based on the following charges: 

Customer service charge (covers e.g. billing related costs and standby costs of the power system).



Energy charge (depends on the actually used kWh per billing period).



Power charge (depends on the peak demand in kW used within the billing measuring cycle time, usually a 15 min interval) [7].



Power factor charge (depending on how effectively the provided power is used by the consumer, also called regulating power charge).

With the knowledge of the different parts of the electricity bill and its related costs, a decision can be made where to start cost cutting projects. The different charges offer different potential for cost cutting. The customer service charge is a candidate for lowering costs by renegotiating the present contract conditions with the electricity supplier; sometimes with surprisingly positive outcomes. To reduce the energy charge, direct energy consumption has to be cut down; one way is replacing older, not as efficient equipment with newer and more efficient one. The result will be less energy consuming production processes which lowers the energy charge. Whether this is a feasible solution has to be decided by the company based on return on investment decisions and financial resources available for these kinds of investments. The power charge (charge for the peak demand) is the total sum of energy demand of all energy users within the company, e.g. all production equipment / machinery, computers, light, and air conditioning. The main share usually comes from the shop floor in the case of a manufacturing company. High energy consuming industries such as paper or metal have tools, the so called load management in place to limit energy consumption. If the peak power per 15 min interval gets too high, machinery is shut down according to a pre-defined plan. Usually either the user with the highest peak demand is shut down or the ones which are the least critical to the production process. Though this is a very effective way to cut down on short-term power demand and therefore lowering the peak, the main purpose lays not in energy cost savings but in not crossing the technical available power limit which would result in stress on the whole power grid. A further effect of “just” shutting down machinery is the lowered productivity of the production. Standard conditions for electronic power contracts are getting less and less common for production companies. While every production company has to negotiate its own detailed contract conditions with the power supplier, the negotiations can be positively influenced for the consumer if its own future demands are known. With the capability to present energy load forecasts, displaying the power

demand for the upcoming 24 hours on a quarterly hour basis, the power supplier is enabled to optimize its overall power and regulation power production. In addition to that the power supplier is able to optimize its purchase demand since it knows more exactly how much power it needs to provide to its customers. The more exact it can build its own aggregated power supply profile, the lower is the safety span it needs to have available in case of unaccounted demand. Having correct forecasts for the peak demand is especially important since it is the main concern of the grid operators. The knowledge about the exact time of the peak demand as well as the avoidance of high peak demand (meaning to have lower peak levels) helps to stabilize the energy grid and to avoid the just in case portion of the regulation power reserve. In short: known and/or lower high peak demand leads to less regulating power and, thus, to less energy costs for the supplier and the consumer. And, in addition, the less regulating power is used, the more CO2 emission is avoided. 3

SOME ASPECTS CONSUMPTION

ON

ENERGY

EFFICIENCY

AND

First, though speaking about energy, we focus in this paper on electricity. Secondly, the definition of energy efficiency needs to be specified since it is not consistent in literature and is used in an unusual way. A common definition is: energy efficiency is the ratio between benefit and cost. The benefit will be the output and the cost in this specific case will be the amount of energy used for this specific output. The output can be a single piece or a certain number of pieces. The energy used for this certain amount of product is called specific energy [8]. Energy efficiency within this paper is used in respect to balanced power profiles; ideally having minor or even non peak demands. However, the amount of energy per unit produced is very important, too, but not the main focus in the project. Electricity consumption as such can be classified from different perspectives; here we look at it from a manufacturing consumer perspective as shown in Figure 1. In order to optimize the power load, here: balancing the power demand to a minimum possible around the average demand, the dependencies of the power consumers have to be identified. Action to cut down energy demand can and has to be considered for the two general split ups, the base load and production dependable energy. The first part, the base load consumption, consists of energy used for facility and the serviceability. Overall consumption

Base load

Facility

Serviceability

Production dependable Product dependent

Product independent

Figure 1: Electricity consumption. The facility includes mainly buildings and heating systems/air condition for offices. To cut down the energy consumption within the building, it is recommended to call in a specialist on energetic factory building refurbishment. Serviceability includes the air conditioning systems, e.g. in cleanrooms, and coolingsystems (for

Sustainability in Manufacturing - Energy Efficiency in Process Chains

295

lubrication) for machine tools, e.g. for a hydraulic press. To cut down on energy consumption in these areas a closer look has to be taken into the off-side machinery within the shop floor. Special care has to be taken not to endanger the required ambient conditions for production by ad-hoc actions.

profile which each individual production process step for each individual product shows. The overall energy profile of the company is the sum of each individual process step at each given time.

The second main electricity consumption part is the energy used directly in the production processes, therefore directly related to operational steps, here referred to as production dependable energy consumption. The production dependable energy consumption has two fractions, the product dependable and the product undependable fraction. Intelligent production scheduling such like E-PPS is focusing on the product dependable energy consumption since the software is scheduling and organizing the production on defined products. By looking at the product dependable energy the main interesting and often forgotten aspect is the power profiles. Each single machine has a distinguished power profile for each defined production step for each product/material. The energy profile of a single production process is likely to change if the material is changing, e.g. a milling machine processing steel vs. copper. The product undependable energy consumption is more or less a constant consumer such as vacuum pumps.



Machinery used.



Product being produced.



Process step measured.

Most of the times companies do not know the base load and the production dependable energy consumption of the factory; for most of the small and medium sized companies the topic energy consumption is, more than less, a black box. Now some forwardlooking companies are investing in electricity measurement equipment for production while investing in new machinery. But gathering of data is only of help if analysis and evaluation are made and the appropriate actions are taken. 4

OPTIMISATION APPROACHES

In industry, especially in the heavy energy consuming branches like metal, paper or plastics, a few approaches to limit energy consumption can be found. The most common approaches will be named, followed by a new holistic approach. 4.1

Implemented common approaches to cut down energy consumption and costs

Three different approaches can be found within the industries to reduce energy consumption and energy costs.

The measured energy profiles are defined through the following information:

Figure 2: Energy profiles with a standard PPC software. Figure 2 shows exemplary energy profiles. Two processes (process A and process B) are running at the same time on the shop floor. In total the energy profile shows an energy peak demand at 5:05 since both processes have a peak demand at that time. This peak demand will cause a tremendous peak in the energy grid as well. And, unfortunately, if the peak demand is higher than the allowed value in the energy contract the peak will result in additional cost, too. If it is possible to postpone one of the processes, then the peak demand can be lowered; costs for the extreme peak are avoided! To transfer this idea – product and process dependable energy profiles used in a PPC software – the project E-PPS was set up to have the following four major steps within the workflow: 

1. Optimization of single machinery (investing in new and less energy needing machinery).

Developing a method to identify main energy efficiency indicators.



2. Energy cut offs to reduce energy peak demands (as described in chapter 2).

Defining specific requirements for a software system for energy efficiency planning and controlling.



Developing the software system E-PPS.

3. Energy load forecasts on an aggregated level to cut down cost due to a better position in the contract negotiation. None of the above solves the problem of the high energy consumption in the industry nor is it achieving the overall best result for the companies. The price of each single product might increase and the productivity of the plant will go down due to shut downs of single machinery. Also the forecast of the energy consumption at an aggregated level does not give the possibility to react appropriately if a peak demand is occurring. 4.2

The holistic optimization

Acknowledging that the common approaches do not tap the full potential to cut down energy cost, the idea was born for a more holistic approach with the ability to manage energy consumption of the production through an intelligent production planning and controlling system. The potential to increase the energy efficiency due to a better production planning and controlling is possible through the energy

The testing of measurements and calculations of the energy consumption and efficiency indicators were made in a pilot plant. The project focuses on small and medium sized companies preferable with a very high variety on non standard products. The pilot plant is a company within the semiconductor field. The product spectrum was sufficient enough to test the E-PPS software. 5

KPIS TO MEASURE CONSUMPTION

AND

CONTROL

THE

ENERGY

Key Performance Indicators (KPIs) are a set of measures which can be used to look back and see how well the company in various fields (purchasing, sails, production etc.) at a certain time performed but also to see, if the direction one is heading to is still right and even further, what has to be done to improve even more [9]. In general, a set of KPIs is a control tool which can be adapted for each company and for each question. In this particularly case they

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should help the energy manager to see what has to be done to reduce the energy consumption dramatically. Similar to the continuous improvement process such as the PDCA Cycle (Plan, Do, Check, Act) an eight step procedure was developed during the runtime of the E-PPS project. To have the possibility to get suitable KPIs matching the needs of the shop floor, this eight-step procedure was developed [10] and is shown in Figure 3:

1. Facility and Equipment Inventory

6. Quantifcation of Indicators

7. Monitoring and Controlling

2. Process Analysis

5. Identification of Causes and Factors

8. Review and Evaluation

3. Initial Energy Measurements

4. 20/80 Identification

6

E-PPS SOLUTION FOR ENERGY AND COST SAVING

The main question for being able to organize and schedule the production considering all planning criteria (e.g. delivery time, capacity) including energy efficiency is to define the input data of the software. The requirements differ depending on the industry and its specific needs. Independent of the differences the following information is necessary in every case for the E-PPS software: 

Detailed information about the existing energy contract.



Detailed information about each individual production process.



Detailed information about the energy consumption profile of each production machine (production dependable part).



Detailed information about further energy consumer (base load part).

The energy contract information includes the energy and power charge, power factor charge and the customer service charge. The production process information includes the single production resources (first, second and n-choice, products and product variation on each production resource), production times (set-up, processing time), and cost centers.

Figure 3: Finding procedure of KPIs. The eight steps are: 1. Facility and equipment inventory. 2. Processes analysis (including identification and characterization of the processes and identification of the equipment and machinery). 3. Initial energy measurements (including gathering the energy bills and profiles from the supplier and measuring the main equipment and machinery involved) 4. 20/80 identification (including individual and global analyses). 5. Identification of causes and factors (for the significant high energy consumption). 6. Quantification of the developed indicators. 7. Monitoring and controlling (including deciding which data, from which source at which frequency). 8. Review and evaluation (to prove that the chosen indicators are still valid and useful). This set of customized energy KPIs allows not only the energy manager to get an overall look at the performance of the production and, therefore of the energy consumption, but also this set of KPIs works as an alarm system in the case something does not operate correctly. Since the KPIs are numbers determined by the main energy consumer they will react accordingly to the performance of the consumer. Furthermore, while developing these KPIs, the gain of knowledge about the production processes, the consumption of energy per unit and the composition of the resulting energy costs are of tremendous use. To sum up the implementation of the customized energy efficiency indicators within a production company leads to the following: 

Customized set of energy efficiency indicators.



Specific and detailed knowledge about all energy consumers.



Detailed knowledge about each specific product, process step and its own energy profile.



Detailed knowledge about the product specific cost profile as a function of the energy consumption for each product.

Figure 4: Process stages. The energy consumption profile of each production machine includes the load profile with detailed information about the stage of the process [11] and the product which is produced. An example of a load profile is shown in Figure 4. The load profile is subdivided into five different parts. Each part has its specific profile. Especially the standby and idle profiles can be used within the planning routine to calculate the difference between e.g. different starting times of the production. The amount of time needed to gather all energy profiles depends on different factors: a) number of measurement equipment sets available b) pre-installed or integrated measurement equipment on the machinery c) number of single production/operation processes and d) duration of the production/operation processes. 7

REQUIREMENTS FOR THE USE OF E-PPS SOFTWARE

The main question after implementing the power profiles into the software is under which conditions is the use of the E-PPS software feasible? Certain requirements are needed within the production processes in order to work according to the production plan of EPPS. The main question is: how flexible is the production process? Does the production have the flexibility 

to halt a running process?



to delay a process step?



to pull forward a process step?

Sustainability in Manufacturing - Energy Efficiency in Process Chains The potential to halt, delay or pull-forward a process differs from industry to industry, from product to product and from process to process. A very flexible production site will be able to use all three methods to move a processing step to avoid peak demands. The result will be a desired production output with a well-balanced energy profile. An example of a well-balanced energy profile can be seen in Figure 5.

297 industry or is the cost saving potential high enough for an implementation in other industries with less energy consumption? Feedback on recent exhibitions shows that a considerable interest exists concerning energy consumption and reducing energy costs. Yet the energy price today seems still too low for putting further efforts on reducing energy consumption which goes beyond the common solutions as stated in section 4.1. In the future, with higher costs on energy power consumption but even more for stabilizing energy grids, it can be expected that companies are willing to invest in a more holistic approach like the E-PPS software. Next to cost aspects, aspects regarding awareness and capabilities of dealing with energy questions have to be considered, and – the simple, first steps in optimizing energy consumption (e.g. insulation of buildings, avoiding leaks) have to be carried out. Then, the future is open to invest in more advanced energy optimizing tools like E-PPS. 9

Figure 5: Energy profiles with E-PPS software. The comparison between the energy profiles of a standard PPC software (Figure 2) with the application of the E-PPS software (Figure 5) reveals the peak demand at 5:05. This energy peak can be reduced to a lower level when using the E-PPS software. Though with E-PPS we can bring the power peaks to a lower level, it has to be noted that the overall direct energy consumption stays the same. Nevertheless, the declined peak demands reduce the power peak charge. Furthermore the effect on cost saving due to the energy forecast is a question of negotiation with high cost saving potential. As mentioned before, the main question whether the E-PPS software is valuable or not is, from this point of view, a question of flexibility on the production and processes involved. The process steps have to be flexible enough to be planned according to needs of the market/production dependencies and according to energy efficiency criteria. To achieve a reduction of energy costs through the E-PPS software, it is necessary to be able to halt, delay or predraw a process. If that is not possible for whatever reasons, the EPPS is not the right tool to reduce the cost for the power charge displayed on the energy bill. On the other hand, the E-PPS software is a great tool to generate the 24 hour energy load profile forecast for negotiation purposes. 8

FUTURE WORK WITHIN THIS THEME

Further questions have to be discussed to define requirements to be fulfilled by the production company to achieve the attained value out of the use of the E-PPS software. The following main points have to be considered and further analyzed: 

Order type requirements.



Manufacturing type requirements.



Shop floor scheduling requirements.

The question of which production companies are ideal users of the E-PPS system has to be answered. Right now the system is implemented and tested in a medium sized enterprise which operates in the semiconductor field. Is the cost cutting potential of the E-PPS software only interesting for high energy consuming

SUMMARY

The simple and application oriented idea of the E-PPS project to reduce energy costs by reducing energy peak demands resulted in the question of how much energy is actually used at each given time during the production of a single piece. The usage of the eight step procedure to define customized KPIs leads to a lot of needed information and to an order of importance of the different machinery concerning energy use. The results of the E-PPS project show that it is possible to reduce energy costs by intelligent planning, organizing and scheduling of production if the specific load profile of each production step is considered while creating a production schedule. Reducing peak demands and creating a 24 hour energy load profile forecast helps reducing the energy costs for small and medium production sites. On an aggregated level, CO2-reduction is possible through the reduction of regulation power on the power provider’s side. 10 REFERENCES [1]

Lackner, P. et al (2007): Handbuch Schritt für Schritt Anleitung für die Implementierung von Energiemanagement; Wien, Österreichische Energieagentur – Austrian Energy Agency.

[2]

Kühnert, C. et al (2009): Optimierung der Prozessfrührung komplexer verfahrenstechnischer Prozesse mit Support Vector Machines; Frauenhofer-Institut für Informations- und Datenverarbeitung, Karlsruhe.

[3]

Steinko, W. (2008): Optimierung von Spritzgießprozessen; Carl Hanser Verlag, München.

[4]

Schiefendecker B. (2006): Energiemanagement-Tools – Anwendung im Industrieunternehmen, Springer-Verlag, Berlin Heidelberg.

[5]

Junge, Mark (2007): Simulationsgestützte Entwicklung und Optimierung einer energieeffizienten Produktionssteuerung, Dissertation; kassel university press GmbH, Kassel.

[6]

Deutsche Bundesregierung (2010): Energiekonzept für eine umweltschonende, zuverlässige und bezahlbare Energieversorgung, Berlin.

[7]

Müller, E. et al. (2009): Energieeffiziente Fabriken planen und betreiben; Springer Berlin Heidelberg.

[8]

Irrek, W, Thomas S. (2008): Definition Energieeffizienz, Wuppertaler Institut für Klima, Umwelt, Energie GmbH, Wuppertal.

298 [9]

Sustainability in Manufacturing - Energy Efficiency in Process Chains Parmenter, D. (2007): Key performance indicators. Developing, implementing, and using winning KPIs, John Wiley & Sons, Inc., Hoboken, NJ.

[10] Aragon Sandoval, M. J. (2009): Selecting and Defining Indicators for Energy Consumption Monitoring in a Production Facility, Master Thesis, University of applied science, Emden/Leer, Emden. [11] Weinert, Nils (2010): Vorgehensweise für Planung und Betrieb energieeffizienter Produktionssysteme, Dissertation, Frauenhofer Verlag Stuttgart.

Methodology for an Energy and Resource Efficient Process Chain Design 1

1

Sebastian Schrems , Christian Eisele , Eberhard Abele 1

1

Institute of Production Management, Technology and Machine Tools, Technische Universität Darmstadt, Darmstadt, Germany

Abstract In consequence of rising costs for raw materials and energy, as well as the customers’ increasing awareness of environmental protection the question of a sustainable production is becoming more and more important. A considerable part of the energy and resource demand in manufacturing is determined during the production planning process. Thus the chosen production technique and the consequential process design have a big influence on the consumption values. This paper presents a methodology to assess different manufacturing technologies, analyzing and estimating their energy and resource consumption and finally choosing the process chain that fits the best to the company’s requirements. Keywords: Technology Assessment; Process Chain Design; Resource Efficiency

1

INTRODUCTION

During the past years a consequent increase of costs for raw materials and energy intensifies the question how to minimize energy and raw material consumption in the production process. With 47% of the overall electrical energy consumption in Germany, the industry has a promising potential to reduce the energy demand and therewith the energy costs [1]. A recent study specifies the total reduction potential for energy costs in Germany with 53 billion Euro with a 10 billion Euro share in the industry [2]. Another aspect which intensifies the industry’s ambitions to shift towards a more energy and resource efficient production is the customer’s increasing awareness of sustainability and sustainable products. An important contribution for this development is caused by the debate about global warming and the negotiated environmental agreement of the Kyoto protocol [3]. Based on this agreement to reduce the emissions of greenhouse gases within the next decades, many industrial companies have declared to reduce their emissions significantly in the upcoming years as well. An essential point to achieve these ambitious objectives is the reduction of energy and resource consumption which concerns especially electrical energy of production machines. For this reason the potential of optimizing the energy consumption along the process chain in the production process is assessed and a methodology leading to an energy efficient production system is developed. 2 2.1

OBJECTIVE Energy and resource consumption in process chains

In order to optimize energy and resource consumption in production systems, two different approaches are commonly used. It is either possible to optimize an existing production system by replacing systematically inefficient machines or components against more efficient ones or to identify the energetic optimal way of production already in early phases when the production process is planned. Figure 1 shows the relation between the upcoming resource costs

(including energy) and the scope of influence on these costs during different phases starting with the production planning and ending in the phase of manufacturing according to [4] [5]. Hence the greatest influence and saving potential is located in the early phases of the planning process.

possibility of influencing resource* costs

cumulative resource* costs

high

*Ressources: - energy - comp. air - raw materials - supplies

low product development

process chain design

manufacturing

time

Figure 1 : Resource costs and influencing possibilities during the production planning [4] [5]. A lot of research dealt already with the optimization of energy and resource consumption in existing production systems. With the high energy consumption in production and the political and industrial objectives to reduce CO2 emissions in mind, these approaches show a very important step to minimize energy and resource consumption. But as the influence on energy and resource consumption is much higher in early phases of the product development process, a new approach supporting the production engineer is necessary. Energy and resource consumption was no decision criterion for alternative process chains in production planning so far [6] [7] [8]. This is for example attributable to the former low energy and resource costs and thus the non-existing economical pressure, the uncertain data in the conceptual phase of the process planning and the associated difficulties in predicting future consumption values. As the demand for an energy and resource efficient production

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_52, © Springer-Verlag Berlin Heidelberg 2011

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Sustainability in Manufacturing - Energy Efficiency in Process Chains

today is rising, energy and resource consumption of production processes is becoming a more and more important factor which is already taken into account when purchasing a machine [9]. Life cycle inventory databases (LCI) which are commonly used for life cycle assessments or energy and resource consumption estimations contain only little information about the consumption of different production processes which can strongly vary by different production machines or scenarios [9]. Thus it is necessary to develop a methodology which enables a reliable estimation of the energy and resource consumption not depending on LCI Data. 2.2

Preceding research activities

The inclusion of ecological information during the product development process has already been treated in different research projects. The collaborative research centre (CRC) 144 at the RWTH Aachen dealt with the assessment of energy and resource consumption of materials and technologies. The methodology included a comparison of alternative processes focusing on the embodied energy. Still, a general modeling procedure of manufacturing processes, a capturing of the required data as well as a strategy to predict the energy consumption of processes in the planning stage is not covered [10]. Main topic of the CRC 392 and the following transfer area 55 was to develop methodologies for prospective estimations of the ecological influence of products along their whole life cycle. Based on lifecycle inventory data, an estimation of the influence of a product was conducted in the product development process. A methodology to predict the influence of alternative manufacturing processes is not included in this method [11] [12]. As lifecycle inventory databases are too generic and neglect many driving parameters such as the influence of the machine configuration or the periphery, they are generally not suitable for a prediction of manufacturing processes yet. Former approaches dealing with the assessment and selection of alternative process chains were mainly oriented to technological or economical selection criteria [13] [14] [15]. In a few cases ecological criteria have been taken into account [7] [8], but the emphasis were mainly on the processing of the ecological data and did not include the acquisition or the anticipation of expected data. Current studies concentrate particularly on the energy consumption of production processes. Taken into account that the energy consumption of production machines has been brought into focus recently, only a few methodologies have been developed. Kuhrke and Dietmair have both developed different methodologies to forecast the energy consumption of machine tools. Kuhrke’s model bases on the cooperation of the machine tool manufacturer and the customer who define together use cases of the future operating conditions. He develops a model enabling the precalculation of the machine components’ energy consumption basing on these use cases and targets an optimal, demand actuated, machine design [9]. Dietmair describes use-case specific models basing on previous energy measurements of the regarded machine. He defines different machine states which can be combined for an arbitrary machining cycle and finally predict the energy consumption [16]. A methodology focused on the production process is introduced by Schultz. He develops a methodology to assess different manufacturing processes by an input / output process model. The methodology concentrates on the merging of the ecological assessment by a LCA and the economical assessment by a costbenefit analysis. He does not describe the way how to determine

the necessary data or how to predict the energy of processes which do not exist yet [17]. Weinert introduces a model which can calculate the energy consumption of different processes using so called energy-blocks. On the basis of previous measurements he defines different machine states and interpolates a function which approximates the energy consumption curve shape. Like in Dietmair’s model, previous measurements are necessary to be able to calculate the energy consumption of a process. To predict the energy consumption of machines he assumes that the energy consumption of similar machines is comparable but a model to predict or transfer energy calculations is missing [18]. The described methodology in this paper concentrates on the early phase of the production planning and aims to allow the production engineer to choose the most efficient way to produce a certain product. An assessment of alternative process chains towards their energy and resource efficiency builds the fundament for the selection of the process chain which fulfills most suitable the requirements regarding the different ambitions (e.g. technological and economic) including the predicted need of energy and resources. Models are developed to predict the consumption values of different production processes and to handle the uncertainty of data in production planning. The models are designed in a way that they work with the available data and a low parameterization effort to deliver calculation results as exact as possible. Subsequently the calculation results of these models have to be utilized in a decision model which combines the ecological decision parameters with other existing parameters respecting user specific decision demands. 3

PROCESS MODELS

In order to be able to determine the energy and resource consumption of a manufacturing process, models are needed which describe the process and the necessary parameters as exact as possible and help prognosticate the expected consumption values. The constraints for these process models are the consideration of the manufacturing machine, the manageability of the models and the necessity of a prognosis of the energy and resource consumption of the regarded process as reliable as possible. The modeling of the processes is oriented on a three-stage reference model which classifies the process from a conceptual process chain to a concrete process layer (see Figure 2).

Observation layer

Transfer

Production Process chain structure analysis …

Manufacturing technology Turning Drehen

•primary forming •forming •cutting…

Specific Proces Varnishing Lackieren

Analysis of single processes

Assessment of alternative process chains Process models of exemplarily chosen main processes

A A B B C C

… varnishing Lackieren Spanende machining Bearbeitung Pa a r m e te r

Z e ti

L e i st u ng

E in h ie t

F o rm

s

x *y + z

W k

x *y + z

e l

Da t e n t y p

F uz z y

F uz z y

Ka r ft

N

x *y + z

Z ah l

…

…

…

…

Software environment for an integrated process chain assessment

Figure 2 : Detailed structure of the models.

Proz es s

Prozes skette

Ferti gun gs verfahren +… #…

Prozes s datenb an k

Ma Msa chi sch n ie ne

Ressourc en

Sustainability in Manufacturing - Energy Efficiency in Process Chains

301

Turning process Parameter Material part diameter secondary time factor cutting depth main time … neccessary process energy

Unit steel 4,000 3,500 4,000 6,351 … 0,565

4,000 3,500 4,000 6,351 … 0,565

4,000 3,500 4,000 6,351 … 0,565

4,000 mm 3,500 4,000 mm 6,351 min … … 0,565 kWh

Cathegory double double double double … double

process specific parameters

Machine tool

… machining varnishing Parameter Time Power Force …

Unit s kW N …

Formu la Data x*y+ z Fuzzy x*y+ z Fuzzy x*y+ z Double … …

Parameter chip-to-chip-time idle time set-up time … energy consumption machine tool cutting tool waste

Unit 3,000 3,000 3,000 3,000 s 0,100 0,100 0,100 0,100 s 120,000 120,000 120,000 120,000 min … … … … … 5,717 8,482 14,010 16,508 kWh 0,005 0,005 0,006 0,007 kg

Cathegory double double double … fuzzy fuzzy

cooling lubricant supply Parameter Value Unit … W energy consumption cool. lub. supp. 0,0000 0,0000 0,0000 0,0000 kWh water consumption 16,0096 22,5908 35,7532 42,3344 kg

Cathegory fuzzy fuzzy fuzzy

Parameter

… Value

Unit

machine specific parameters

peripheral components

Cathegory

Figure 3 : Section of a process model to calculate the consumption values of a machining process. In a first step of the approach generic process models of five different production processes have been developed. Based on measurements and literature research the determining factors and fundamental energy calculating equations have been evaluated for each manufacturing technique. In this step the focus is primarily set on the process itself and less on the production machine. Aside from raw materials and supplies, the energy consumption of the processes represents the most important key figure. Figure 3 shows a section of an exemplary process model for the machining process.

consumed less energy per piece than the new one, these two parameters do not permit a reliable estimation of the energy needed. It is rather more important to consider the respective machine configuration with the installed components for the consumption prediction. Therefore the machine specific parameters play an important role in the calculation in the process models. The accuracy of the calculation depends on the estimation of unknown process and machine data in the process planning. Thus the models have to be adapted in the way that they can easily be modified and parameterized, using predefined databases.

The structure of the process models is divided into two parts. Influencing factors affiliated to the process on the one side and influencing factors affiliated to the production machine on the other side.

In other research projects of PTW, Maxiem [9], Esimpro [22] and the research group Ecomation [23], assessment methods of energy efficient machine tool components and simulation models for the use-specific energy consumption of defined machine tools and its components are developed. These models are designed to deliver an exact simulation of the energy consumption of a specific machine tool on which the detailed machine and work piece parameters are already common. As these models are especially developed for the calculation of the energy consumption of machine tools, their transfer to other manufacturing processes is not provided.

The strategy to develop the models is depending on the regarded process and its energetic conditions. For a varnishing process for example, the process depending energy cannot be determined by specific equations as for a machining process. No energy is introduced to the work piece at the operating point. Nevertheless the process parameters (like the varnish thickness) influence the resource consumption and have also to be considered. For this reason empirical determined data is used to calculate the consumption values for such processes. For the example of a machining process, the energy consumption has been calculated using the equation of Viktor and Kienzle [19] to approximate the necessary chip removal energy. Measurements have shown that the energy consumption of a process is strongly influenced by the operation of the production machine itself and less by the specific process parameters [20] [21]. An analysis of two machine tools in the project has shown that the same machining process on two comparable equipped machines of different age and connected load by the same manufacturer can cause a difference in energy consumption up to almost 40% per piece. As the older machine with a higher connected load

As much information about the processes and the machines is still uncertain in the production planning phase, the simulation of specific machines is not possible. The above described process models will be advanced to use dynamic simulation models to be able to calculate the energy and resource consumption of different production processes. The models base on general machine models which are able to deliver the needed accuracy to be able to serve as decision making basis. These general models cover different production machines and their components. Each model is predefined in different standard power classes which enable a primarily calculation without the necessity of detailed information about the process and the machine.

302

Sustainability in Manufacturing - Energy Efficiency in Process Chains

Lösung A

EerFer Drehen

Härten

Schleifen

100

100

100

80

80

80

60

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40

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Plan

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Para1 Para2 Para3 1 1 0 2 1 0 1 2 1 4 4 1 Σ P.weight 0.4 0.4 0.2 Para1 Para2 Para3

point value 0 1 2 3 4

characteristic impossible still possible sifficient good ideal

Alt. 1

Alt. 2

Alt. 3

Preselection of feasible process chains

Preselection of alternative manufacturing technologies

Prior elimination of technological and economical unsuitable solutions in the production planning

Calculation of the predicted energy and resource demand

Calculation of the energy and resource consumption of alternative process chains using the predefined process models

Weighting factors for energy, resources and other decision parameters

Determination of a scala of assessment values

Determination by experts opinion and a paired difference test of all decision factors

Subdivision of the characteristic of each attribute along a ten-stage scale

Calculation of comparable values of different process chains

Calculation of the overall value of a process chain including all decision parameters and the corresponding wheight

Figure 4 : Main steps of the decision model. The modular design enables an easy calculation of the influence of alternative components or whole machines. The models are stored in a database. The use of that database permits the production planner to check alternative production processes easily. Combined with the specific use case and the corresponding machine and component states, a calculation of the needed energy and resources can be optimized. 4

DECISION MODEL

As used in the product life cycle assessment (LCA) following [24], a decision model to identify the preferred alternative has been developed. In contrast to a LCA, the decision methodology needed for the choice between several production alternatives has not only to include the ecological decision parameters but also technological or economical determining factors. Therefore the described decision problem is assigned to multi criteria decision models which are characterized by: 

Multiple criteria to be assessed



Multiple decision parameters



A comparison of alternatives [25]

Similar to the LCA, energy and resource consumption but also e.g. the technological and economical attributes serve as a decisionmaking basis. Beside the decision parameters, the methodology has also to consider the fact that every user may impose different standards on the assessment methodology and attaches different importance to the decision parameters. Another fact to be considered is that alternative process chains may consume different kinds of resources or different forms of energy (electrical energy or gas e.g.). The comparability of these alternatives has nevertheless to be preserved and the methodology to be designed in order to allow a reliable decision. In a first step the determination of technological decision parameters is not included and the parameters are assumed as given data.

Figure 4 describes the general steps of the decision methodology. The decision methodology is oriented on [26] and begins with the prior elimination of technical and ecological not considerable solutions. Thus it can be assumed that only suitable solutions have to be assessed. The second step builds the foundation for the final selection of the process chain, the calculation of the expected energy and resource demand. Using the predefined process models the energy and resource consumption of the process chain will be calculated and serves as data base for the further assessment. Once these values are determined, they can be combined with other decision parameters like technical or economical ones. The actual assessment starts in step three. Generally, different companies may assign a different importance to the decision parameters. Thus a point rating system has been introduced based on different weighting factors for each parameter, following, a paired difference test is used to calculate these factors. For all parameters, a cross checking matrix A is developed, that describes the weighting of all parameters among themselves (see Figure 5).

compared to

p1 p2 p3 … pn

parameter 1 parameter 2 parameter 3 …

1 2 2

parameter n

2

0 1 1

0 1 1

0 0 0 …

2

2

=A

ann

Figure 5 : Cross checking matrix for the parameter evaluation.

Sustainability in Manufacturing - Energy Efficiency in Process Chains

The weighting factors Fj are subsequently calculated by the normalized point weight of each parameter:

    Fj      

    i 1 n  n    aij     j 1  i 1  n



aij

(1)



In order to be able to compare substitutable process steps, a value scale for each single process step has to be defined. Some of the parameters appear in multiple alternative processes (the energy consumption in almost every process for example) and some of the parameters may appear in only one of the alternatives (like special operating supplies). For the comparison of resources which are consumed by multiple decision alternatives, the 5-point scale can be spread equally over the range between the smallest and highest resource demand following equation (2) where Opt stands for the optimal and Pes for the most unfavorable value.

(2)

For other decision parameters, the distribution of the value scale has to be determined by an expert’s opinion. After the calculation of the corresponding point-values of every process step, the normalized total value of the process step PPi is calculated by the multiplication of each parameter’s point value PRj and the corresponding weighting factor Fj divided by the number of decision parameters n.

PPi 

1 n

n

 P

Rj

 Fj



(3)

CONCLUSION AND OUTLOOK

In this paper, a methodology is introduced to assess alternative manufacturing process chains towards their energy and resource efficiency. It can be noticed that the main levers for an energy and resource efficient production are in the phase of the production planning. Especially in this early phase the main challenge is the uncertainty of the needed data and the associated prospective calculation of the consumption values. LCI data which have been used in the past for the energy consumption estimation of production processes only contain very generic information about the processes and are not transferable to a particular production process. The presented methodology builds a suitable basis for a transfer into practical use. In this first step the process models and the methodology set a starting point for further work which includes a transfer into practical use in industrial environment. The quality of

ACKNOWLEDGMENTS

The authors gratefully acknowledge the financial support of the German Research Foundation (DFG) for the project AB 133/40-1: EerFer “Entscheidungsunterstützung zur energieund ressourceneffizienten Fertigung” (Decision support for an energy and resource efficient process chain design). 7

REFERENCES

[1]

Kiesel, Herkner (2009): BDEW Bundesverband der Energieund Wasserwirtschaft e.V., Energiemarkt Deutschland, Berlin, Germany.

[2]

Mc Kinsey & Company (2009): Wettbewerbsfaktor Energie als Chance für die deutsche Wirtschaft.

[3]

United Nations, (1998): Kyoto Protocol to the United Nations Framework Convention on Climate Change, Kyoto, Japan.

[4]

Ehrlenspiel K., Kiewert A., Lindemann U. (2007): CostEfficient Design, Springer, Berlin, Heidelberg.

[5]

Müller, E.; Engelmann J.; Strauch, J. (2008): Energieeffizienz als Zielgröße in der Fabrikplanung. Energieeffizienzorientierte Planung von Produktionsanlagen am Beispiel der Automobilindustrie, in: Werkstattstechnik online, SpringerVDI-Verlag, Vol. 7/8, pp. 634-639.

[6]

Eversheim, W. (2002): Organisation in der Produktionstechnik, Band 3. Arbeitsvorbereitung. Springer Verlag Berlin, Heidelberg.

[7]

Heitsch, J. (2000): Multidimensionale Bewertung alternativer Produktionstechniken. Dissertation, RWTH Aachen, Germany.

[8]

Trommer, G. (2001): Methodik zur konstruktionsbegleitenden Generierung und Bewertung alternativer Fertigungsfolgen. Dissertation, RWTH Aachen, Germany.

[9]

Kuhrke, B.; Schrems, S.; Eisele, C.; Abele, E. (2010): Methodology to assess the energy consumption of cutting machine tools, in: Proceedings of the 17th CIRP International Conference on Life Cycle Engineering (LCE2010), pp. 76-82, Hefei, China.

1

Finally the point value of the whole process chain can be calculated by the addition of the point value of each process step. The overall point value builds finally the decision base for the process planner to be able to compare and select the process chain which fulfills the defined requirements at best. 5

the predicted consumption values, the manageability as well as the algorithms are to be optimized in cooperation with industrial partners for the transfer into practice. Further development on the decision methodology will not only include the influence of each decision parameter, but also the influences between the parameters themselves. 6

In the next step, the characteristic of all decision parameters, for example the results of the prior energy and resource consumption calculation are transferred into a general scale of values going from 0 (unsatisfactory) to 4 (very good).

  4   x  Pes  PRj   Opt  Pes  

303

[10] SFB 144 RWTH Aachen (ed.) (1996): Energie- und Rohstoffeinsparung – Methoden für ausgewählte Fertigungsprozesse, Düsseldorf: VDI-Verlag (VDI-Z Integrierte Produktion, Sonderpublikation). [11] Abele E.; Anderl R.; Birkhofer H. (2005): Environmentallyfriendly Product Development Methods and Tools, SpringerVerlag Berlin Heidelberg. [12] Abele, E.; Anderl, R.; Birkhofer, H.; Rüttinger, B. (2008): EcoDesign – Von der Theorie in die Praxis. Springer-Verlag Berlin Heidelberg. [13] Ullmann, C. (1995): Methodik zur Verfahrensplanung von innovativen Fertigungstechnologien. Dissertation, RWTH Aachen, Germany. [14] Fallböhmer, M. (2000): Generieren alternativer Technologieketten in frühen Phasen der Produktentwicklung. Dissertation, RWTH Aachen, Germany.

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[15] Knoche, K. (2004): Generisches Modell zur Beschreibung von Fertigungstechnologien. Dissertation, RWTH Aachen, Germany. [16] Dietmair, A.; Verl. A. (2010): Energy Consumption Assessment and Optimisation in the Design and Use Phase of Machine Tools, in: Proceedings of the 17th CIRP International Conference on Life Cycle Engineering (LCE2010), pp. 76-82, Hefei, China. [17] Schultz, A (2002): Methode zur integrierten ökologischen und ökonomischen Bewertung von Produktionsprozessen und – technologien. Dissertation Universität Magdeburg, Germany. [18] Weinert, N. (2010): Vorgehensweise für Planung und Betrieb energieeffizienter Produktionssysteme, Dissertation, TU Berlin, Germany. [19] Victor, H.; Kienzle, O. (1952): Die Bestimmung von Kräften und Leistungen an spanenden Werkzeugmaschinen, in: VDIZ, Vol. 94, pp. 200-305, Germany. [20] Abele, E.; Schrems, S. (2010): Ressourcenorientierte Bewertung alternativer Prozessketten - Herausforderungen und Möglichkeiten zur Prozesskettenbewertung im Produktionsplanungs-prozess, in: ZWF, Vol. 105, p. 542-546, Carl Hanser Verlag München, Germany. [21] Abele, E., Dervisopoulos, M., Kuhrke, B. (2008): Bedeutung und Herausforderungen der Lebenszyklusanalyse am Beispiel Werkzeugmaschine, in: Schweiger, S. (ed.): Lebenszykluskosten optimieren. Gabler Verlag Wiesbaden, pp.51-79, Germany. [22] Rudolph, M; Abele, E., Eisele, C., Rummel, W. (2010) : Analyse von Leistungsmessungen – Ein Beitrag zur Untersuchung der Energieeffizienz von Werkzeugmaschinen, in: ZWF, Vol. 105, pp. 876-882, Carl Hanser Verlag München, Germany. [23] Abele E.; Schrems, S. (2010): Determination of energy consumption control factors of machine tools by component oriented simulation, in: Conference Proceedings International Chemnitz Manufacturing Colloquium (ICMC 2010), pp. 711 718, Chemnitz, Germany. [24] DIN EN ISO 14040: Umweltmanagement – Ökobilanz – Grundsätze und Rahmenbedingungen. Berlin, Beuth, Germany, 2009. [25] Hwang, C.-L., Masud, A. S. M. (1979): Multiple Objective Decision Making – Methods and Applications. Lecture Notes in Economic and Mathematical Systems, No. 164. Springer Verlag, Berlin Heidelberg, Germany. [26] VDI-Richtlinie 2225 (1997): Technisch-wirtschaftliches Konstruieren. Beuth Berlin, Germany.

Sustainability in Manufacturing - Energy Efficiency in Process Chains

A New Shop Scheduling Approach in Support of Sustainable Manufacturing 1

1

2

Kan Fang , Nelson Uhan , Fu Zhao , John W. Sutherland 1

2

2

School of Industrial Engineering, Division of Environmental and Ecological Engineering and School of Mechanical Engineering, Purdue University, West Lafayette, USA

Abstract Shop scheduling is a classic manufacturing decision-making problem. A new approach to scheduling that considers peak power load and energy consumption (and associated carbon footprint) in addition to cycle time is presented. A general multi-objective mixed-integer programming formulation is provided and examined using a simplified case study that considers the scheduling of a variety of components on two machines. The challenges of finding a solution to this scheduling problem are discussed, which motivates the need for specialized algorithms for these new scheduling problems. Computationally efficient algorithms that compute near-optimal solutions and optimal solutions under specific assumptions are examined. Keywords: Scheduling; Peak Load; Carbon Footprint

1

INTRODUCTION

Over the last 60 years, the consumption of energy by the industrial sector has almost doubled. The industrial sector is the largest energy consumer and currently accounts for about one-half of the world’s total energy consumption. In addition, industrial energy consumption, which was at 175 quadrillion Btu in 2006, is projected to increase 40% by 2030. In the United States, approximately 34% of all the end-use energy consumption was associated with the industrial sector, and the associated energy cost in 2006 was about $100 billion. Since the U.S. energy supply is dominated by fossil fuels (more than 85% of the energy comes from such sources such as coal and natural gas), the industrial sector contributes 27% of the U.S. greenhouse gas (GHG) emissions. This makes the industrial sector second to the transportation sector in terms of GHG emissions. Manufacturing enterprises in the U.S. are facing ever-increasing pressure to reduce their reliance on fossil fuels and reduce their carbon footprint. This pressure is driven by concerns related to climate change, energy costs, and energy security. Energy issues will assume an even more important role in the future, owing to ever-increasing demand for energy from developing countries, and the likely implementation of a carbon tax or carbon cap-and-trade policy. These economic and environmental drivers motivate the need for initiatives directed at substantially reducing energy consumption and GHG emissions from manufacturing enterprises. Most previous research on manufacturing energy consumption has focused on developing more energy efficient machines/processes [1]. However, the energy requirements for the active removal of material can be quite small compared to the background functions needed for manufacturing equipment operation [2]. Drake et al. [3] showed that there are significant amounts of energy associated with machine start-up and machine idling. As a result, in a mass production environment, more than 85% of the energy is utilized for functions that are not directly related to the production of parts [4]. This suggests that energy saving efforts focusing solely on updating individual machines or processes may be missing a significant, and perhaps a bigger, opportunity, i.e., system-level changes. Unfortu-

nately, such approaches have not yet received much attention. Current shop floor scheduling strategies employed by manufacturing enterprises focus mainly on productivity and throughput time, with energy and environmental factors often ignored. Although energy/environment related criteria have not been usually considered as major factors in manufacturing systems, minimizing energy consumption has been an area of interest in computer and embedded electronics systems for several years [5,6]. Given the scale of industrial activities – 175 quadrillion Btu energy consumed, $100 billion in costs, and 1.5 billion tons CO2 equivalent produced – relative to computer/electronics system activities, this suggests that a tremendous opportunity exists with respect to industrial activities. Clearly, similar research is needed for manufacturing enterprises. In addition, since manufacturing plants are often charged based on the peak power demand (referred to as “power consumption” to distinguish it from energy consumption) from the energy provider instead of actual electricity consumption, optimized operation schedules could further reduce energy costs. Compared to machine or process redesign, implementation of optimized shop floor scheduling and plant operation strategies only requires a modest capital investment. Given this backdrop, this paper presents a general formulation of the shop floor scheduling problem that considers productivity, carbon footprint, and peak load simultaneously. A simple job shop with two machines is used to demonstrate potential trade-offs among these criteria and the complexity inherent to this new scheduling challenge. 2

BACKGROUND

Existing research on production operation methods to reduce environmental impacts is sparse. At the equipment level, a literature search only resulted in a handful of papers. One of the most relevant studies is one by Mouzon et al. [7], who investigated the problem of scheduling a single machine to minimize total energy consumption. In particular, they looked at the scheduling of a CNC machine in a machine shop for a supplier of small aircraft parts. They pointed out that if instead of leaving the non-bottleneck ma-

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_53, © Springer-Verlag Berlin Heidelberg 2011

305

306 chines idle, they could be turned off until needed; such a change would result in an 80% savings on total energy consumed. They showed that the ability to predict the next arrival of a job (e.g., the inter-arrival times between jobs) greatly affects the effectiveness of various dispatching rules (for example, batching vs. non-batching). Mouzon and Yildirim [8] examined the scheduling environment and proposed a metaheuristic framework to compute schedules that minimize the total energy consumption and the total tardiness on a single machine. Considering the hierarchical structure of a manufacturing plant and associated planning functions, shop floor schedules have an impact on schedules at the equipment level. As a result, shop floor schedules could significantly affect energy consumption as well as other environmental impacts of an individual machine. Unfortunately, although a variety of performance measures have been considered for shop scheduling, these efforts have largely focused on economic, time, or operational considerations. For example, one typical objective in such scheduling problems is to minimize the incurred setup cost or setup time, which arises from the reconfiguration that often needs to take place between jobs. For just-in-time manufacturing systems, a common objective is to schedule jobs so that the usage rate of all parts is as constant as possible, or so that the load of each workstation is as constant as possible. In contrast, research on scheduling with environmentally-oriented objectives is relatively scarce. However, research on energy-aware scheduling is growing. For instance, Subai et al. [9] incorporated energy and waste considerations into the hoist scheduling problems that arise from surface treatment processes. Wang et al. [10] proposed an optimal scheduling procedure for vehicle sequencing in order to reduce energy consumption in an automotive paint shop. By selecting appropriate batch and sequence policies, they also found that the paint quality can be improved and the number of repaints can be reduced. Nevertheless, these efforts on scheduling research, especially those for flexible manufacturing systems (FMS) in use by many market-leading enterprises, provide a starting point for introducing environmental considerations into schedule optimization, particularly from a model and algorithm development perspective. An FMS can be viewed as a production system that is capable of producing a variety of part types. The system consists of a number of machines or workstations, each of which can perform different operations with the appropriate tooling setups. Motivated by customer demands to produce greater part variety, large OEMs are moving to FMS technology since an FMS is better suited to producing large component variety than dedicated equipment such as transfer lines. Since an operation may be performed at any one of a number of machines, the routing of a job through the system is flexible, and needs to be considered when determining a schedule. In addition, the use of material handling systems and limited buffers imposes additional constraints on the starting times of jobs. Flexible assembly systems are similar, except the routing of a job is more or less fixed. Most of the research on scheduling for flexible manufacturing and assembly systems has focused on specific problems that arise in industry, and as a result, the existing literature is vast [11]. Various optimization-based approaches have been considered for scheduling in flexible manufacturing and assembly systems, including agent-based approaches [12], metaheuristics [13], constraint programming [14], and mathematical programming [15]. None of these studies addressed energy related objectives in modeling the scheduling problem. The next section presents an optimization model with productivity and environmental objectives.

Sustainability in Manufacturing - Energy Efficiency in Process Chains 3

MATHEMATICAL PROGRAMMING FORMULATION FOR MULTI-OBJECTIVE SHOP SCHEDULE OPTIMIZATION

Consider a set of machines 1,2, … , , which are ordered so that a job cannot start on machine until it is completed on machine 1 , for 2, … , . In addition, consider a set of jobs 1,2, … , that need to be processed on each machine in . These constraints can be relaxed or modified to reflect other types of process/job interdependencies (e.g., a job shop). For many processes, the time required to perform a job may be reduced by increasing the machine speed, with the consequence generally being increased peak power demand. To consider power consumption/peak load as part of our formulation, a finite and discrete set of machine speeds 1,2, … , is considered; on each machine, every job runs at a speed to be determined. The processing time of job ∈ on machine ∈ at speed ∈ is 0. In addition, the power consumption (peak power demand) of job ∈ on machine ∈ at speed ∈ is 0. The following ten sets of decision variables are associated with the problem: 

max

is the makespan of the schedule:



max

is the peak total power consumption;



max

is the GHG emissions (carbon footprint);

  

denotes the completion time of job on machine ; is equal to 1 if job is processed on machine with speed , and 0 otherwise; is equal to 1 if job precedes job , and 0 otherwise;



on machine is , is equal to 1 if the start time of job before the completion time of job on machine , and 0 otherwise;



on machine , is equal to 1 if the completion time of job is after the completion time of job on machine , and 0 otherwise;



, is equal to 1 if the completion time of job on machine occurs during the processing of job on machine , and 0 otherwise;



is equal to 1 if

,

1 and

1, and 0 otherwise.

,

The following multi-objective mixed integer linear program seeks to minimize: (i) the makespan, (ii) the peak total power consumption, and (iii) the total carbon footprint, and is inspired by the work of Manne [16]. Below, represents a very large constant and is the carbon footprint of electricity consumed by the shop which can be found using EPA’s eGRID2007 Version 1.1 by specifying a facility’s 5-digit zip code. For example, electricity consumed by a manufacturing facility located in West Lafayette, IN (zip code 47907) has a carbon footprint of 0.616 kg/kWhr (1.538 lb/kWhr). minimize

max

minimize

max

minimize

max

subject to , ∈ ,

max

∑

,, ∈ ,

∈

∑

,

∑

∑

∈

∖ 1 ;  ∈ ,

, ∈

∈

,

,  ,

,

1

,

, ,

∈ ∈

;  ,

,  , ;  , ;  ,

(3)

∈ :

, ∈

1

∈

1 ,

(2)

,    ∈

∈

∑

,

(1)

∈ ∈ , ∈ ,

;  , ;  ,

1, ∈ : ∈ ,

(4) 1, (5) (6) (7) (8)

Sustainability in Manufacturing - Energy Efficiency in Process Chains 1

,

∑

,

1, ∈

∈

1, ,

, ,

∈

∑

∈

∈

(9)

; ∈ ,

(10) ,

∈ :

(11) ,

2, , , ∈ : ∑

∈ ;  ∈ ,

;  ,

∈ :

∑

∈

∑

∈

(12) ,

max ,

; ∈                                                                                           (13)

∑∈ ∑

∈

∑

max ,

∈

     

∈ 0,1 ,

      ,

∈ ; ∈ ,

∈ 0,1 , ∈ 0,1 ,

∈ 0,1 , , ∈

;

∈ 0,1 ,

,

∈ 0,1

(14)

Constraint (1) ensures that the makespan of the schedule is greater than the completion time of any job. Constraints (2)-(3) ensure that a job cannot start on machine until it is completed on machine 1. For each pair of jobs: , ∈ , either job is processed before job , or vice versa. Constraints (4)-(5) ensure that the ordering of the jobs is consistent across machines. Constraints (6)-(9) ensure that the binary decision variables , , and take on only the intended values. Constraint (10) ensures that each job is processed with exactly one speed on each machine. Constraints (11)-(12) ensure that the decision variables correspond to a permutation on . Finally, constraint (13) ensures that the total power consumption across machines at any time instant is at most max , while constraint (14) ensures that the total carbon footprint for completing all the jobs is at most max . For the multi-objective schedule optimization model formulated above, one can search for Pareto efficient schedules, i.e., feasible schedules that are not dominated by any single performance measure. It should be noted that the traditional scheduling problem – that is, finding a schedule that minimizes the makespan for a flexible manufacturing system – is already computationally difficult. Thus, it is expected that introducing additional decision variables, objectives, and constraints related to power/energy consumption and carbon footprint will make the scheduling problem even more computationally challenging. To gain a better understanding of the problem, a case study for a simple hypothetical flow shop is shown below. 4

CASE STUDY: A TWO MACHINE JOB SHOP

A shop is assumed to make cast iron plates with slots. Starting with cast iron plates, two operations are required (with each operation performed on a separate machine): face milling and profile milling. The plates (Figure 1) can have different lengths, different face milling depths of cut, different slot depths, and different numbers of slots. In total, the case study considered 36 different parts to be produced, which correspond to the combinations of three different plate lengths, two different face milling depths of cut, three different numbers of slots, and two different slot depths. Cutting speeds for both face milling and profile milling are independent variables that are within the range recommended by the Machinery's Handbook [17]. Table 1 shows the geometry of the parts and cutting conditions. The shop is organized so that each plate must be face milled before it undergoes profile milling. For a job processed on one of the machines, the load and energy consumption can be calculated based on the equations provided below. Figure 2 provides additional insight into the meaning of several of the variables. ∙ ∙ ∙

∙

(15)

∙ ∙ ∙

(for face milling) ∙

307

(16)

∙  

 

 

(for profile milling)

∙ ∙ ∙

 

 

(17) (18)

 

∙

∙

(19)

∙

In the relations above, the subscript “basic” corresponds to the lowest power level of machine tool operation. For the basic level, machine tool energy is consumed by lighting, the NC controller, chiller system, oil pump, and way lube system. Activities performed while the machine tool is at the basic power level include workpiece loading/unloading, positioning, and fixturing. The subscript “idle” subscript corresponds to a power level higher than the basic level. For the idle power level, the main spindle is turned on and power is also provided to the automatic tool changer and cutting fluid pump. Activities performed while the machine tool is at the idle power level include the tool approaching the workpiece, the tool retracting from the workpiece, tool motion between features, adjustments in the machine settings, and tool change operations. Finally, the subscript “cutting” corresponds to a power level and the period of time when material is actually being cut. In the equations represents electricity consumption (in MJ or kWhr), represents power consumption (in kW), w, d, and V represent the cutting width, feed per tooth (or flute), and cutting speed, respectively. represents the specific cutting energy, represents the length of the workpiece, represents the cutter diameter, ( ) represents the number of teeth (flutes) per cutter, represents the spindle speed, and represents the number of slots. If the cutting energy is the product of the specific energy and the amount of material removed, then it may be noted that for a given operation on a part, the energy consumption will be constant regardless of the cutting speed, assuming the specific cutting energy is independent of feed rate and cutting speed. Part Geometry Width (cm)

20

Length (cm)

35/45/55

Thickness (cm)

10

Depth of milling on surface (mm)

2/4

# of slots

4/6/8

Slot depth (cm)

0.5/1.0

Slot width (cm)

3.0

Cutting conditions Face milling Cutter diameter (cm)

30

# of teeth

15

Feed per tooth (mm)

0.2

Cutting speed (m/min)

18/24/30/36/45

Profile milling # of flutes

4

Feed per flute (mm)

0.1

Cutting speed (m/min)

18/24/30/36/45

Table 1: Part Geometry Settings and Cutting Conditions.

308

Sustainability in Manufacturing - Energy Efficiency in Process Chains flexible manufacturing and assembly systems is already notoriously difficult to solve.

Figure 1: A Cast Iron Plate with Slots.

Figure 2: Power Profile for a Representative Machining Operation (e.g., Face Milling).

Figure 3: Pareto Frontier Showing Tradeoff Between Peak Load and Makespan. With the mathematical programming model for the scheduling problem and cutting process relations established, and a set of jobs to schedule, an optimal schedule can be determined. Attempts were first made to use the commercial optimization software packages IBM CPLEX, in conjunction with goal programming techniques to identify points on the Pareto frontier. Unfortunately, for this twomachine 36-job problem, a provable optimal solution could not be found within 24 hours with a computer of two 2.5 GHz Quad-Core AMD 2380 processors and 32 GB of RAM. This is not surprising since it is known that job scheduling with only a single objective for

With hard-to-solve mathematical programming models, it is often advantageous to study related, but easier-to-solve models. A relaxation of a mathematical programming model is an auxiliary mathematical programming model that is formed by weakening the constraints or the objective function of the model. Researchers have successfully created near-optimal schedules for various real-world scheduling problems represented by hard-to-solve mathematical programming formulations, using information from computationally tractable relaxations of these hard-to-solve models [18]. For the two-machine flow shop problem, algorithmic and structural results for some fundamental special cases of the problem are shown below. Suppose the flow shop does not have intermediate storage between the two machines. That is, Machine 1 (face milling in this case) cannot start processing the next part if the part it has just completed cannot start being processed on Machine 2 (profile milling). This is sometimes known as “blocking” in the scheduling literature. In this case, it can be shown that this scheduling problem is equivalent to an asymmetric traveling salesman problem. This transformation was used to solve the particular instance described above. Using the Concorde TSP solver, the Pareto efficient frontier was computed for this relaxed case with peak load and complete time (makespan) as the two objectives considered. The Pareto frontier was generated by specifying 21 different upper bounds on the peak total power consumption and then searching for the minimum makespan. Each schedule corresponding to the minimum makespan was computed in 4-5 seconds. Figure 3 shows the Pareto efficient frontier for this case. It can be seen that there exists a trade-off between makespan and peak load. If the makespan is the dominant consideration, a complete time as short as approximately 10,000 seconds (~2.75 hours) can be achieved at a corresponding relatively high peak load of 15 kW. On the other hand, if we can tolerate a longer complete time, the peak load can be reduced to less than 6 kW, with a corresponding makespan of approximately 75,000 seconds (~20.8 hours). Figure 3 also shows the carbon footprints corresponding to the 21 minimum makespans identified. It can be seen that carbon footprint decreases as the upper bound of power consumption increases. In other words, the carbon footprint and makespan have a similar behavior; this suggests that the carbon footprint can be reduced by minimizing the makespan. Suppose the constraints on available cutting speeds are relaxed and it is assumed that the cutting speed can take on any value within the recommended range. In particular, job ∈ on machine units of work, and a job that requires units of ∈ requires work and is processed at speed has a processing time of / . We also assume that the power consumption at speed is for some constant 0. When 0 1, the optimal schedule is simply to process all the jobs without overlap at the fastest possible speed. When 1, the following results hold: 1. Suppose the flow shop does not have intermediate storage between the two machines. In this case: 

Suppose the work required is consistent across machines—that is, for any two jobs: , ∈ , implies . To be specific, this means that if a part has a relatively small processing time on Machine 1 (face milling in this case), then it also has a relatively small processing time on Machine 2 (profile milling). For this case, an optimal schedule can be computed in polynomial time. This is accomplished by transforming the scheduling problem into an equivalent asymmetric traveling salesman problem that satisfies the so-called Demidenko [19] conditions (the Demidenko conditions are a set of triangleinequality-type relations).

Sustainability in Manufacturing - Energy Efficiency in Process Chains 

If in addition to the conditions above, the work required for each job is the same on each machine – that is, for any job ∈ , – then, an optimal schedule can be computed by a simple priority-list algorithm. In particular, if ⋯ then scheduling the jobs according to the permutation 1,3,5, … , n, … ,6,4,2 yields an optimal schedule.

2. If the flow shop does have intermediate storage between the two machines, that is, Machine 1 (face milling in this case) can start processing the next part immediately after completing the current part, no matter whether or not Machine 2 is ready to accept the part being processed, then the following holds. For simplicity, we assume the power consumption at speed is . 

Assuming the total power consumption on the two machines is max at any time in the schedule, and given a fixed permutation of the jobs, an optimal schedule (i.e., job completion times and job/machine speeds) can be found in polynomial time. In addition, the sequence of jobs can be decomposed into subsequences of jobs that are processed at the same speed. To illustrate, suppose we have 4 jobs 1,2,3,4 , and it is decided in advance that the jobs are to be processed according to the order 4,2,1,3 . Then we can determine the optimal speeds and completion times for each of the jobs in polynomial time. This kind of result on the mathematical structure of the scheduling problem is useful in the design of neighborhood search algorithms to find near-optimal solutions.

5

SUMMARY, CONCLUSIONS, AND FUTURE WORK

A general multi-objective mixed integer linear programming formulation has been presented for optimizing the shop schedule that considers both productivity (e.g., makespan) and energy (e.g., peak load and carbon footprint) related criteria. Different from the current schedule optimization approaches where productivity is the only objective (and thus the highest possible operation speed is preferable), this new formulation considers the operation speed as an independent variable, which can be varied to affect the peak load and energy consumption. The constraints associated with the formulation can be relaxed or modified to reflect other types of process/job interdependency (e.g., a job shop). A simplified case study – a two-machine flow shop producing cast iron plates with slots is used to demonstrate the complexity of the problem. It was found that even for this simplified case, the computational time could be so significant that it is almost time prohibitive to compute Pareto frontiers. Several special cases that were more theoretically and practically tractable were examined. The findings from this examination include: 

If there is no intermediate storage between the two machines the problem can be transformed into an equivalent traveling salesman problem. The resulting Pareto frontier suggests that there exists significant trade-offs between makespan and peak load.



If cutting speed can be treated as a continuous variable, under the conditions that there is no intermediate storage and the work required is consistent across machines, the problem can be transformed into an equivalent asymmetric traveling salesman problem, the solutions to which can be computed in polynomial time.



If cutting speed can be treated as a continuous variable and there is intermediate storage, an optimal schedule can be found in polynomial time for any given permutation of the jobs.

Although the two-machine flow shop problem has some interesting structural and algorithmic properties, these may not hold as the scale of the shop increases to industrial conditions where perhaps

309 hundreds of machines are involved. Moreover, the computation time will be prohibitive for such industrial-sized problems. This suggests that in order to find practical schedules that balance economic and environmental performance, the following activities are needed: (i) construct simplified, adequate shop floor models for which optimal schedules can be found, and (ii) design specialized algorithms (e.g., relaxations of the general scheduling problem or neighborhood searches) for which acceptable schedules can be found with reasonable computational effort. It should be noted that in addition to cycle time or makespan other factors such as tardiness, cost, and quality, are generally considered in shop floor scheduling. From an environmental performance perspective, although only energy related criteria, e.g., peak load, energy consumption, and carbon footprint, have been introduced as new objectives here for shop floor schedule optimization, in the future other objectives could be considered. For example, the scheduling formulation could address such other environmental and occupational health impacts as water consumption, air emissions, and noise. Considering all of these objectives simultaneously is expected to introduce nonlinear correlations among some decision variables and constraints thus making the scheduling problem even more difficult. It should also be noted that the scheduling optimization discussed here is “static”. In reality, due to unforeseen disturbances on the shop floor during the execution of a schedule, an originally optimal schedule may become sub-optimal or even unacceptable; thus, a new schedule will often have to be found in a relatively short time frame [11]. Integrating environmental considerations into this kind of dynamic scheduling or real-time scheduling problem clearly represents a significantly larger challenge. Since environmentally responsible shop floor scheduling has the potential to significantly reduce the energy and environmental footprint of manufacturing facilities without incurring large capital investment, numerous opportunities exist in this new area which are expected to have a broad and significant impact on manufacturing enterprises. We hope that the work presented herein related to environmentally conscious scheduling will serve as a starting point for others to make contributions to this emerging area. 6

REFERENCES

[1]

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[2]

Dahmus, J.B., Gutowski, T.C. (2004): An Environmental Analysis of Machining, in: ASME International Mechanical Engineering Congress and RD&D Expo, November 13- 19, 2004, Anaheim, California.

[3]

Drake, R., Yildirim, M.B., Twomey J., Whitman, L., Ahmad, J., and Lodhia, P., (2006): Data Collection Framework on Energy Consumption in Manufacturing, in: IIE Annual Conference and Expo, May 20–24, 2006, Orlando, FL.

[4]

Gutowski, T.C., Murphy, C., Allen, D., Bauer, D., Bras, B., Piwonka, T., Sheng, P., Sutherland, J., Thurston, D. and Wolff, E., (2005): Environmentally Benign Manufacturing: Observations from Japan, Europe and the United States. In: Journal of Cleaner Production, Vol.13, No.1, pp.1–17.

[5]

Swaminathan, V., and Chakrabarty, K., (2003): EnergyConscious, Deterministic I/O Device Scheduling in Hard RealTime Systems, in: IEEE Trans. Comput. Aided Des. Integr. Circ. Syst., Vol.22, Vol.9, pp.847–858.

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Mouzon, G., Yildirim, M.B., (2008): A Framework to Minimise Total Energy Consumption and Total Tardiness on a Single Machine, in: International Journal of Sustainable Engineering Vol.1, No.1, pp.105-116.

[9]

Subai, C., Baptiste, N. E., (2006): Scheduling Issues for Environmentally Responsible Manufacturing: The Case of Hoist Scheduling in An Electroplating Line, in: Int. J. production Engineering, Vol.99, No.1, pp.74-87.

[10]

Wang, J., Li, J., Huang, N., (2009): Optimal Scheduling to Achieve Energy Reduction in Automotive Paint Shops, in: Proceedings of 2009 ASME Manufacturing Science and Engineering Conferences, October 4-7, 2009, West Lafayette, IN, USA.

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Comparison of the Resource Efficiency of Alternative Process Chains for Surface Hardening 1

1

1

1

Gunther Reinhart , Saskia Reinhardt , Tobias Föckerer , Michael F. Zäh 1

Institute for Machine Tools and Industrial Management (iwb), Technische Universität München, Munich, Germany

Abstract As negative implications of resource exploitation and further undesirable ecological developments, e.g. climate change, increase, companies are confronted with novel challenges. Especially during the production stage of a product’s lifecycle companies have the possibility to influence the resource consumption by choosing the most efficient process chain for a certain manufacturing task. To compare accumulated resource flows of different process chains, a new valuation method using a resource efficiency index was developed. Exemplarily, this paper will analyze the resource consumption of two alternative process chains for surface hardening of a workpiece resembling a guide rail. Keywords: Production Planning; Sustainable Manufacturing; Machining

1

INTRODUCTION

Resources, e.g. raw materials, are getting scarce as a result of the rapidly rising demand. In order to prevent the negative implications of resource exploitation and further undesirable environmental developments, e.g. climate change, legislation is starting to restrict and influence both companies and consumers in their behavior. In addition, the image and consequently the competitiveness of a producing company are strongly influenced by its efforts regarding the establishment of resource efficient and sustainable products and processes [1]. These developments have led to the consideration of environmental effects of the usage and disposal phase of the product lifecycle during product design. But in most cases not only using and disposing of a product cause resource depletion and waste, but also the manufacturing phase can be held responsible for a large share of the environmental burden [2]. Therefore, it is important to consider the manufacturing process chain specific resource consumption during the production planning phase, as 80% of the environmental impact of a manufacturing system is fixed at that time [3]. In particular, if several alternative manufacturing process chains are able to fabricate the product a decision will have to be made. Apart from the decision criterion cost, the criterion resource efficiency should be taken into consideration for the reasons mentioned above. In spite of these findings, the resource flows of manufacturing processes are not as well known as they should be. Furthermore, research studies state that available methods supporting the evaluation of resource efficiency are still insufficient [4]. Main approaches that aim to quantify resource flows and to evaluate the resource efficiency of manufacturing process chains will be discussed shortly in the following. Current approaches that aim to quantify resource flows of a manufacturing process either use a material and energy flow based analysis or attempt to derive resource consumption in a predominantly analytical way. Especially machining processes have been analyzed concerning the production of waste material, the consumption of cutting fluid and the use of energy [5, 6]. However, the quantification of resources used in the process is based solely on theoretical calculations, rendering the approach inept for the

prediction of overall resource flows that include the manufacturing equipment as well. A variety of valuation methods utilizing an expost material and energy flow based analysis, also known as inventory analysis, exists. Most of these methods also include the assessment of the environmental impact of the regarded object [7, 8, 9]. The approaches mentioned above focus on an ex-post analysis, which does not show the predictive character needed in the production planning phase. Recently, a few approaches sought to develop a general method for resource efficiency evaluation [10, 11]. The goal of this paper is to further develop and apply a general method for evaluating resource efficiency of manufacturing process chains based on the approach introduced by [11]. Therefore two alternative process chains, one using only traditional manufacturing processes and one including a new hybrid manufacturing process, will be compared and their resource efficiency will be evaluated. The remainder of this paper is set out as follows. The next section presents the modeling of the material and energy flows and the evaluation of the resource efficiency. The modeling procedure is then applied to two alternative process chains for surface hardening in the third section. Finally, the resource flows are calculated and the material and energy efficiency are determined for each process chain. Using the resulting resource efficiency index a quantitative comparison of the alternative process chains is possible. 2 2.1

METHODOLOGY Modeling of Resource Flows

A manufacturing process chain consists of different manufacturing processes that are needed to change a product from one defined state to another. In this paper a manufacturing process is modeled as a composition of the manufacturing technology used, the manufacturing system the technology runs on and the additional peripheral systems. The manufacturing system and more complex peripheral systems can be subdivided into their components, which is indicated by the circles surrounding the manufacturing system in Figure 1.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_54, © Springer-Verlag Berlin Heidelberg 2011

311

312

Sustainability in Manufacturing - Energy Efficiency in Process Chains

peripheral systems manufacturing system manufacturing technology

1

manufacturing system

5

2 system 4

Figure 1: Manufacturing process model. Generally every resource ri can constitute an input ri IN and an output. Whereas output is divided into output going into the product ri PROD and output that is wasted ri OUT. Input resources used in a cutting process are for example energy, material, water, auxiliary material, coolant etc. The quantity of every ri IN, ri PROD and ri OUT required by the examined manufacturing process for one manufactured product can be described by corresponding resource vectors rIN, rPROD and rOUT (see Figure 2).

rPROD rIN process

rOUT Figure 2: Resource flows of a manufacturing process. In general resources used in manufacturing process chains can be divided into two main categories: material and energy. This subdivision of resources facilitates both the quantification of resource flows and the evaluation of resource efficiency. For the quantification of indirect resource flows (e.g. the proportion a manufacturing process has regarding the power consumption of a central compressed air system) the produced quantity per time unit is needed as supplemental information. The following subsections describe the quantification of rIN, rPROD and rOUT using the manufacturing process model. Input Resource Flow Quantification The input energy flow consists of the manufacturing system and the peripheral systems. The energy consumption of the technology is part of the manufacturing system. The required power can be calculated theoretically for many standard technologies. As the technology is executed on the manufacturing system, the theoretical value has to be multiplied with a correction factor due to interaction between technology and manufacturing system. Generally, the input energy flow of manufacturing systems and peripheral systems can be calculated using the power consumption of defined system states and the time during which the system is in one of the defined states based on the work schedule of the product. Accordingly, the input energy flow is set together as follows:

rEnergy IN  rEnergy IN manufacturing system  rEnergy IN peripheralsystemk

(1)

k

The power consumption of system states usually varies due to the composition of active and inactive components of the manufacturing

3

pow er consumption

system or peripheral system. Figure 3 shows the calculation of the power needed in the system states A to D depending on the system’s active components.

44 3,5 [kW] 33 2,5 2.5 22 1,5 1.5 11 0,5 0.5 00 A

B C systemstates

D

Figure 3: Power consumption of different system states. For each defined state of a system the required power has to be assessed. The best way to determine the values is by conducting power measurements of the system. As the method should be applicable in the planning phase the power data has to be a requirement when soliciting a quotation. If there is no data available the required power values have to be estimated using measurement data of similar systems if possible. If only a fraction of the peripheral system’s input energy flow can be assigned to the manufacturing process, the energy flow can usually be allocated to the manufacturing process based on the manufactured product quantity and relative energy intensity of the product. The input material flow consists of all material going into the process. Generally there are there different categories of material used in manufacturing processes: workpiece materials, auxiliary materials and tool materials. The workpiece materials and some auxiliary materials can be directly allocated to the product. Other centrally provided auxiliary materials and tool materials can be allocated to the manufacturing process based on the manufactured product quantity and relative material intensity of the product. Product and Output Resource Flow Quantification The product energy flow is either the ideal energy used to perform a certain manufacturing process or the minimal energy of all the technologies in the alternative process chains that can be used to perform the process step. The product material flows equal all workpiece material flows and the auxiliary material flows that go into the product. Typically, the required workpiece material can be calculated using product design data. The output energy and material flows are established by subtracting the product resource flows from the input resource flows. In the case of the workpiece, the output material flow is determined by subtracting the product geometry from the unmachined part geometry. 2.2

Resource Efficiency Evaluation

Resources are usually understood as natural resources subdivided into raw materials such as minerals, environmental media such as air, water or earth and flowing resources such as wind or solar energy [12, 13]. These categories already include most of the resources that are potentially used in a manufacturing process. In order to make the term even more practical for industrial application, resources such as electrical energy have to be integrated. The term ‘efficiency’ is defined in various ways depending on the particular context. In general, efficiency can be understood as the ratio of benefit and effort. Relating this definition to resources either implies that, given a certain amount of resources used, the amount of produced units has to increase in order to obtain a more resource efficient situation. Or, on the other hand, the provided the amount of

Sustainability in Manufacturing - Energy Efficiency in Process Chains produced units is fixed and the amount of resources used has to be decreased. Whereas the use of resources includes contamination, damage and waste represented by ri OUT. In order to allow a resource efficiency calculation, all resources have to be standardized to one consistent unit. In this paper, the above-mentioned resource categories may be used. The unit for the category material is kilogram [kg], requiring the unification of solids, gases and liquids being substances in different states of aggregation. For the category energy the standard units are Joule [J] or kilowatt hours [kWh]. Having assessed the meaning of efficiency for manufacturing processes and eliminated the unit calculation problem, the material efficiency of a manufacturing process ωMaterial is defined as follows [11]:

i 1 ri PROD  Material  n n i 1 ri IN   i 1 ri OUT

313

process chain ‘induction hardening’ 1. milling (d = 3 mm) 2. induction hardening 3. grinding (d = 0.1 mm)

hardened surface layer (hardening depth = 0.4 mm)

process chain ‘grind-hardening’

n

(2)

d = depth of cut Figure 4: Alternative machining of workpiece.

The benefit of a manufacturing process is the product resource flows and the effort put in which consists of the input resource flows and all output resource flows that do not go into the product. This definition implies that the more input flows directly into the product the higher the resource efficiency. Efficiency of 100% is only attained, if all resource input goes into the product itself, leaving no additional output. Also, the more auxiliary resources are needed for the process, the more the efficiency decreases. Consequently, resources that do not go into the product are accounted for twice in the denominator, representing an input resource on the one hand and waste or contamination on the other hand.

The two alternative process chains, one using only traditional manufacturing processes and one including a new hybrid manufacturing process, is compared and their resource efficiency is evaluated. As shown in Figure 4 and Figure 5, the traditional process chain includes a milling process, an induction hardening process [14] and a grinding process. As customary, grinding is used as a finishing process after several steps of soft machining and a subsequent heat treatment at the end of the process chain.

process chain ‘induction hardening’ induction milling..... hardening

As the output energy flow has no know detrimental effect on the environment it does not have to be accounted for as effort. Accordingly, the energy efficiency of a manufacturing process ωEnergy can be reduced to:

i1 ri PROD n i1 ri IN

3 3.1

Material  Energy 2

heat treatment

milling..

grind-hardening

finishing grinding

(3) change of manufacturing system

The resource efficiency is based on both material and energy efficiency. The ratio of material efficiency to energy efficiency may vary according to the company’s focus. In this paper it is assumed that material and energy efficiency are equally important and the resource efficiency index is calculated as follows:

 Resource 

soft machining

grinding

process chain ‘grind-hardening’

n

 Energy 

1. milling (d = 2.5 mm) 2. grind-hardening (d = 0.5 mm) 3. grinding (d = 0.1 mm)

(4)

APPLICATION Alternative Process Chains

As application this paper analyzes the resource consumption of two alternative process chains for surface hardening of a workpiece resembling a guide rail. Both process chains start from the same semi-finished part, a bar with a square cross section (150 mm length, 28 mm width, 18 mm height) consisting of soft-annealed 100Cr6. The two alternative process chains both modify the workpiece by machining a 10 millimeter wide slot with a depth of 3.1 millimeter and realizing a hardened surface layer with a hardening depth of 0.4 millimeter as shown in Figure 4.

Figure 5: Comparison of the two alternative process chains and classification of the process steps concerning production phases. The alternative process chain employs the “grind-hardening” process, which is an innovative approach to cut down the process and auxiliary time by substituting conventional hardening processes [15]. Therefore, grind-hardening is a hybrid manufacturing process, which can be classified as a soft machining and heat treatment process at the same time. Grind-hardening enables a process integrated heat treatment by grinding with subsequent finishing in one clamping. The large amount of heat in the contact zone between the grinding wheel and the workpiece, which is generated by deformation, shearing, friction and separation while grinding, is used for surface layer hardening by means of a short time austenization of the machined part. The martensitic hardening is mainly achieved by self quenching [16] supported by the convective heat transport of the used coolant [17]. 3.2

Modeling of Resource Flows of the milling process

In the following, the different resource flows will be modeled exemplarily with the milling process (see Figure 6) of the grindhardening process chain.

314

Sustainability in Manufacturing - Energy Efficiency in Process Chains

d w vf vc

vf vc

= = = =

depth of cut = 2.5 mm width of cut = 10 mm feed rate = 7.97 mm/s cutting speed = 1.67 m/s

w d Firstly, the product energy flow is assessed. The power necessary for the process Pc can be determined by multiplying cutting force Fc and cutting speed vc:

Pc  Fc  vc

(5)

König et al. [18] describe how the cutting force can be calculated theoretically, so that no previous measurements are required. In this case the cutting power is 894 Watt. The product energy flow results from multiplying power and cutting time tc:

rEnergyPROD  Pc  tc  894 W 18.9 s  16,896.6 J

1 1.0

f (d)  0.9423 d 0.165

0,8 0.8 0,6 0.6 0,4 0.4 0,2 0.2 00 0

1

2

axes movement incl. main spindle on

Pc, real  f (d )  Pc  0.810  894 W  724.14 W

5

2 milling

1

4

3

0 0

10

20

30

40

50

60 time

70

80

power approximated Wirkleistung angenähert Figure 7: Measured power consumption of the milling process. In order to variably model the milling process, the power consumption of the main components is assessed. As the machine’s axes movement only occurs when the spindle is turned on, the power consumption of the axes movement has to by derived by subtracting the power consumption of the spindle from the measured value. With these component power values the resulting power consumption of the system states can be calculated independently, making further power measurements unnecessary. Only the power needed to execute the technology itself has to be assessed separately. When determining the technology power consumption it is again possible to calculate the power consumption independent of measurements by using the theoretical process

(7)

3 [kW] 2 1 0 A

[s] 110 90 100

power measured Wirkleistung gemessen

6

On the basis of the now given information about the power consumption of the components, the different system states can be calculated as depicted in Figure 9. In this case, component 1 is not one physical consumer but subsumes all small components that consume power when the milling machine is turned on, including e.g. transformers or lighting.

standby

2

[mm] 5

Figure 8: Correction factor of technology power consumption.

1

3

3 4 depth of cut d

The grind-hardening process chain has a depth of cut of 2.5 millimeter and a correction factor of 0.810. Accordingly, the power consumption of the technology as one component of the manufacturing system is calculated as follows:

power consumption

power consumption

4

in process (milling)

f(d) based on measurements trendline

1,2 [-]

(6)

The input energy flow of the considered manufacturing system, the milling machine, can be derived from the different system states of the process as described in Section 2.1. Figure 7 shows the measured power of the milling process over time and visualizes the four states of the milling machine. The power graph displays the actual power measured on the one hand and the approximated power consumption on the other hand. The approximated power represents the ideal run of the power curve neglecting singular power peaks. 6

main spindle on

correction factor f(d)

1.4 1,4 Figure 6: Face-milling process.

[kW] 5

power described in Equation 5 and multiplying the value with a correction factor, that has to be derived from empirical studies. These empirical studies include a variation of parameters and simultaneous measurement of the electrical power consumed. For the milling process considered in this paper a non-linear correlation of depth of cut and power consumption was ascertained concerning the correction factor. The discovered correlation is visualized in Figure 8.

components: 1: basic consumption 2: machine control 3: feed drives 4: main spindel 5: technology

B C D system states

system states: A: standby B: axes movement C: main spindle idle D: in process

Figure 9: Power consumption of the states for the milling machine. The input energy flow can be determined by multiplying the system states of the milling machine and the time during which the machine is in one of the defined states based on the work schedule for the milling process. The assumed waiting time is a result of the difference between process time and the cycle time of the production line. The energy for each process step and state is listed in Table 1 and the final input energy flow of the manufacturing system results in 138,816 Joule.

Sustainability in Manufacturing - Energy Efficiency in Process Chains step

system state

time [s]

energy [J]

clamping

state A

60

42,000

state B

7

5,250

state C

3

4,500

state D

18.9

42,036

state C

3

4,500

state B

7

5,250

unclamping

state A

20

14,000

cleaning

state A

10

7,000

waiting

state A

20.4

14,280

149.3

138,816

machining

sum

Table 1: Work schedule of the milling machine. The only peripheral system used during the milling process is the compressed air system. In this case, instead of modeling the entire system only the energy needed to produce the estimated amount of compressed air is calculated. Based on the machine that was examined and its work schedule the input energy flow of the peripheral system is determined for a compressed air consumption rate of 1.5 liters per second at 6 bar for 10 seconds (step ‘cleaning’ in Table 1). The resulting energy flow is 13,072 Joule. The entire input energy flow according to Equation 1 is:

rEnergy IN  rEnergyIN milling machine rEnergy IN compressedair system  138,816 J  13,072 J  151,888 J The input material flow of the workpiece corresponds to the semifinished part of 0.5935 kilogram of soft-annealed 100Cr6. The product material flow is made up of 0.557 kilogram of 100Cr6 forming the machined workpiece. The output material flow is established by subtracting the product material flow from the input material flow resulting in 0.0365 kilogram. The milling tool material flow is an input and output flow but does not go into the product. Also the fraction of the milling tool, which is allocated to one workpiece results from distributing the entire tool material equally over the expected tool life. The resource flows of the other processes can be modeled and assessed in a similar way. Especially, for the grinding processes the energy flows of the coolant system, as a complex peripheral system, are modeled using a state based approach as introduced above for entire manufacturing system. In addition, the coolant consumption per workpiece is calculated by dividing the entire coolant residing in the coolant system by the quantity of products that are machined during a coolant-renewal interval. 3.3

Resource Efficiency Evaluation

Having assessed all resource flows based on a weekly production quantity of 800 pieces, the resource efficiency of the alternative process chains can be determined. Table 2 shows the material flows of the induction hardening process chain. The material flows of the grind-hardening process chain are displayed in Table 3. Due to the fact that the semi-finished part and the final workpiece geometry are the same, the material flows are identical. The tool waste of the induction hardening process chain is less than the tool waste of the grind-hardening process chain, because the tool wear of grind-hardening is added. The coolant flow is independent of the utilization ratio of the grinding machine and therefore identical for both process chains. In this case a coolant system with a capacity of 800 liters of water based coolant solution and a coolant-renewal interval of 26 weeks are assumed.

315 rMaterial IN [kg]

rMaterial OUT [kg]

rMaterial PROD [kg]

tool waste

0.0043

0.0043

0

workpiece

0.5935

0.0365

0.557

0.05

0.05

0

coolant

0.0435

0.0435

0

sum

0.6913

0.1343

0.557

cooling water

Table 2: Material flows of process chain ‘induction hardening’. rMaterial IN [kg]

rMaterial OUT [kg]

rMaterial PROD [kg]

tool waste

0.0143

0.0143

0

workpiece

0.5935

0.0365

0.557

coolant

0.0435

0.0435

0

sum

0.6513

0.0943

0.557

Table 3: Material flows of process chain ‘grind-hardening’. In order to compare the energy efficiency of the two process chains a benchmark for each production phase has to be found. Table 4 displays the ideal energy flows concerning the three phases introduced in Figure 5, which will be used as the basis of comparison in the following evaluation. For the heat treatment phase the energy needed for the austenitization is applied, assuming a low heating rate [19]. Further, the minimal energy of the analyzed technologies is used for the soft machining and finishing phase. production phases

energy [J]

soft machining

20,280

heat treatment

2,491

finishing

6,807

sum

29,578

Table 4: Ideal energy flow concerning the production phases. In order to determine the input energy, Table 5 and Table 6 show the different process steps. Each step relates to the energy consumed by the corresponding manufacturing system and peripheral systems. The energy of all process steps added up finally forms the energy of the entire process chain. Before each change of manufacturing system and at the end of each process chain the workpiece is cleaned for ten seconds using the compressed air system. The additional cooling system in the induction hardening process step is needed for quenching the workpiece to realize surface hardening. step milling

induction hardening

grinding sum

system

energy [J]

milling machine

126,790

compressed air

13,072

induction hardening machine

160,700

cooling system

87,450

compressed air

13,072

grinding machine

336,127

coolant system

157,120

compressed air

13,072 907,403

Table 5: Input energy flow of process chain ‘induction hardening’.

316

Sustainability in Manufacturing - Energy Efficiency in Process Chains

The values concerning the milling process step in Table 6 are derived from the resource flows modeled in Section 3.2. step

system

energy [J]

milling machine

138,816

Erhöhung der Energieproduktivität, in: Zeitschrift für wirtschaftlichen Fabrikbetrieb (ZWF), Vol. 105, No. 10, pp. 870-875. [3]

Griese, H.; Müller, J.; Sietmann, R. (1997): Kreislaufwirtschaft in der Elektronikindustrie: Konzepte, Strategien, Umweltökonomie, VDE-Verlag, Berlin, Germany.

[4]

Neugebauer, R. (Ed.) (2008): Energieeffizienz in der Produktion: Untersuchung zum Handlungs- und Forschungsbedarf, Fraunhofer Gesellschaft.

[5]

Munoz, A. A.; Sheng, P. (1995): An analytical approach for determining the environmental impact of machining processes, in: Journal of Materials Processing Technology, Vol. 53, No.3-4, pp. 736-758.

[6]

Bley, H.; Nickels, T.; Schmidt, J. (1997): Mutual Effects in a Sequence of Cutting and Cleaning, in: Proceedings of the 29th CIRP International Seminar on Manufacturing Systems, pp. 125-132, Osaka, Japan.

[7]

Goedkoop, M.; Spriensma, R. (2001): The Eco-indicator 99: A damage oriented method for Life Cycle Impact Assessment, retrieved March 16, 2009, from http://www.pre.nl/download/ EI99_methodology_v3.pdf.

[8]

DIN EN ISO 14040 (2006), Beuth Verlag, Berlin, Germany.

[9]

Salonitis, K.; Tsoukantas, G.; Drakopoulos, S.; Stavropoulos, P.; Chryssolouris, G. (2006): Environmental Impact Assessment of Grind-Hardening Process, in: Proceedings of the 13th CIRP International Conference on Life Cycle Engineering (LCE 2006), Vol. 2, pp. 657-662, Leuven, Belgium.

[10]

Neugebauer, R. (Ed.) (2010): Energy-Efficient Product and Process Innovation in Production Engineering, Verlag Wissenschaftliche Scripten, Auerbach, Germany.

[11]

Reinhardt, S.; Reinhardt, G. (2009): Resource Efficiency Valuation of Manufacturing Processes, in: Quaderni della XIV Summer School 'Fancesco Turco', pp. IV.84-IV91, Monopoli, Italy.

This paper introduced an approach for evaluating the resource efficiency of manufacturing process chains. The procedure was applied to two alternative process chains for surface hardening. The material and energy flows of both chains were determined and evaluated – identifying the new hybrid manufacturing process ‘grind-hardening’ as a resource efficient alternative to the traditional hardening process using induction. Further analysis of possible transport and handling processes should be conducted to expand the scope of the process chain valuation. Furthermore a weighting scheme for resources has to be developed in order to reflect the special characteristics of different materials and energy types and their ecological effects.

[12]

Commission of the European Communities (2003): Towards a Thematic Strategy on the Sustainable Use of Natural Resources (No. COM(2003) 572), Brussels, Belgium.

[13]

Rogall, H. (2008): Ökologische Ökonomie, VS Verlag für Sozialwissenschaften, Wiesbaden, Germany.

[14]

Benkowsky, G. (1990): Induktionserwärmung: Härten, Glühen, Schmelzen, Löten, Schweißen, Verlag Technik, Berlin, Germany.

[15]

Zäh, M. F.; Brinksmeier, E.; Heinzel, C.; Huntemann, J.-W.; Föckerer, T. (2009): Experimental and numerical identification of process parameters of grind-hardening and resulting part distortions, in: Production Engineering – Research and Development, Vol. 3, No. 3, pp. 271-279.

5

milling grind-hardening

grinding

compressed air

13,072

grinding machine

348,450

coolant system

158,400

grinding machine

168,577

coolant system

98,400

compressed air

13,072

sum

938,787

Table 6: Input energy flow of process chain ‘grind-hardening’. Applying Equation 2 to the calculated material flows (Table 2 and Table 3) the material efficiency of the process chains can be determined. The energy efficiency of each process chain is calculated by dividing the accumulated ideal energy by the entire input energy of the respective process chain as implied in Equation 3. The specific efficiencies of the different process chains are listed in Table 7. The resource efficiency is calculated according to Equation 4, indicating the grind-hardening process chain as the most resource efficient alternative. process chain ‘induction hardening’

process chain ‘grindhardening’

material efficiency [%]

67.47

74.70

energy efficiency [%]

3.26

3.15

resource efficiency [%]

35.37

38.93

Table 7: Resource efficiency of both process chains. 4

SUMMARY AND OUTLOOK

ACKNOWLEDGMENTS

[16]

The authors would like to thank their colleagues at the Foundation Institute of Materials Science (IWT) for their support concerning the grinding machine data and the Deutsche Forschungsgemeinschaft (DFG) for funding the project ‘Grind-Hardening Process Simulation’.

Brockhoff, T., (1999): Schleifprozesse zur martensitischen Rand¬schicht¬härtung von Stählen, Shaker Verlag, Aachen.

[17]

Brinksmeier, E.; Minke, E.; Wilke, T., (2005): Investigations on Surface Layer Impact and Grinding Wheel Performance for Industrial Grind-Hardening Applications, in: Annals of the WGP, Vol. 12, No.1, pp. 35-40.

6

[18]

König, W.; Essel, K.; Witte, L. (1982): Specific Cutting Force Data for Metal-Cutting, Verlag Stahleisen, Düsseldorf, Germany.

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[1]

Shrivastava, P. (1995): Environmental technologies and competitive advantage, in: Strategic Management Journal, Vol. 16, No. S1, pp. 183-200.

[2]

Reinhart, G.; Karl, F.; Krebs, P.; Reinhardt, S. (2010): Energiewertstrom – Eine Methode zur ganzheitlichen

[19] Orlich, J.; Rose, A.; Wiest, P. (1973): Atlas zur Wärmebehandlung der Stähle, Verlag Stahleisen, Düsseldorf, Germany.

Synergies from Process and Energy Oriented Process Chain Simulation – A Case Study from the Aluminium Die Casting Industry 1

1

Christoph Herrmann , Tim Heinemann , Sebastian Thiede 1

1

Institute of Machine Tools and Production Technology, Technische Universität Braunschweig, Braunschweig, Germany

Abstract Due to the significant ecological relevance and constantly rising prices, energy consumption more and more gets into the focus of manufacturing companies which strive to consciously consider energy consumption when planning and managing production facilities. Thereby it is important to take into account the interdependencies on different hierarchical levels in a production system (between single processes and the whole process chain). Against this background this paper presents an approach for a combined application of an energy oriented process chain simulation and a detailed process simulation. This approach enables an integrated evaluation of the interactions of parameter variations on both levels. Keywords: Energy Efficiency; Simulation; Aluminium Die Casting

In order to increase the efficiency of production processes and process chains especially in energy intensive industries like the aluminium die casting industry, a systematic approach against the background of a comprehensive system understanding is necessary [4] [5]. It is not sufficient to focus on only single selected system elements of the production. To avoid focusing on minor relevant aspects and local optimisation as well as problem shifting the whole production system including all relevant input and output flows has to be taken into consideration. Against this background,

Figure 2 shows fields of action in the context of energy- and resource efficiency in production. One can differentiate between the machine- or process perspective and the view on process chains or production/factory system, yet both are directly connected as depicted in the figure. Based on either singular or permanent data collection, the understanding of interrelations through modelling as well as on suitable methods for the evaluation and prediction of operating behaviour, it is the ultimate objective to integrate energyand resource consumption as a further dimension into operational decisions (besides conventional objectives like for instance

a)

Aluminium Price (USD/Ib)

INTRODUCTION

In modern automotive design lightweight construction plays a major role for reducing fuel consumption and improving the driving characteristics of automobiles. An extensively applied way for reducing the weight of automobiles is the substitution of steel parts through aluminium parts. Many of these parts have a very complex structure and still they need to be produced in mass production. While being able to fulfil these strict requirements in terms of quality and quantity aluminium high pressure die casting is a well established production technology. This is also reflected in the quantity of produced aluminium die casting parts. In 2008 only in Germany over 413,000 tons of die casted aluminium parts were manufactured causing over one million tons CO2eq in the foundry. [1] [2] Having overcome the impacts of the recent global financial crisis the aluminium die casting branch recovers to well-known growth rates. By the year of 2005 the yearly growth rate in this industry branch in Germany was about 10%. Nevertheless the current growth rates in the aluminium die casting industry cannot hide the fact that this whole industry is under heavy pressure of reducing its overall costs in order to fulfil the requirements of its customers which are mainly automotive OEMs. As major cost drivers in this industry energy and aluminium prices need to be considered. Steadily increasing prices for raw materials (Figure 1, a) and energy (Figure 1, b) before the recent crisis and again a trend to increasing prices for aluminium and energy supplies after the financial crisis exert significant pressure to reduce energy and material consumption within the aluminium die casting process chain.

250

b)

electricity oil 200

gas gross domestic product (GDP)

price index (2000=100)

1

150

100

50

0 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

year

Figure 1: Development of a) Al (10 year progression 2000-2010, graph from infomine.com) and b) Energy Prices (compared to GDP) [3].

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_55, © Springer-Verlag Berlin Heidelberg 2011

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Sustainability in Manufacturing - Energy Efficiency in Process Chains maintaining a defined temperature within the metal before it is charged into the casting chamber. Usually natural gas is used for smelting the metal in the smeltery whereas electricity is used for maintaining the temperature in the dosing oven. An alternative solution for the supply of the casting cells with molten aluminium is the supply of liquid metal directly from the metal supplier to the casting plant and the casting cells. In this case there is no need for smelting furnaces in the casting plant and the energy for resmelting the aluminium after it has already been smolten during the alloying process can be saved. However in this case specific infrastructure needs to be implemented at the metal supplier and the casting plant. Furthermore the molten metal needs to be heated during the transportation between metal supplier and casting plant.

Integration

Scenario Simulation / Improvement

Analysis / Evaluation

Modeling

Data Acquisition / Measuring

Figure 2: Fields of action for energy- and resource efficiency in production [5]. utilization, cycle times, quality rates). Within this systematic approach it is increasingly important to develop scenarios for improving the focussed process or process chain and to evaluate the impact of these measures based on a simulation approach before their individual implementation. The simulation of improvement scenarios becomes necessary as the energy and resource consumption behaviour of production machines is usually highly dynamical and also complex on process chain level due to the manifold interactions of the single subprocesses and also because of the their interdependencies with connected peripheral equipment and technical building services. [5] The effect and synergy of a combined application of a process simulation (Magmasoft®) and a process chain simulation (energy oriented process chain simulation, developed by IWF, Technische Universität Braunschweig) will be discussed in this paper. As a basis the underlying aluminium die casting process chain will be introduced in the following. ALUMINIUM DIE CASTING PROCESS CHAIN Subprocesses and material/energy aluminium die casting process chain

flows

in

the

According to the focus of the BMBF-funded research project ProGRess (www.progress-aluminium.de) the aluminium high pressure die casting process chain can be described as depicted in Figure 3. The process chain consists of four major steps in order to produce parts in a defined quality: smelting of aluminium, the die casting process itself, heat treatment to set up certain metal properties and one or several machining processes to realize the final geometry and surface quality. The first step in the in-house process chain in aluminium die casting companies is a centralized smeltery in which different furnaces smelt large quantities of solid aluminium ingots to liquid aluminium that is transported in crucibles via fork-lift trucks to the diverse die casting cells in the casting plant. At the casting cells the molten aluminium gets filled into dosing ovens that are also used for

As it is illustrated in Figure 3 the described process steps are usually divided by quality gates where scrap material is assorted. This assorted material as well as swarf and in particular the gating system and sprue waste that are stamped off the work piece directly after the casting are transferred to the smeltery again and get resmelted and supplied to the casting cell afterwards as cycle material. Additionally, as mentioned, there are diverse auxiliary flows that are needed to ensure stable casting and machining processes like cooling water, release agents, lubricants, etc. that need to be taken into consideration when it comes to a holistic assessment of this process chain.

emissions, energy, auxiliary materials (e.g. cooling water, release agents) chips, (recyling) material (e.g. sproud spill) , waste

liquid metal

casting process form

spraying

machine

Machining

Heat Treatment

Die Casting quality gate

solid smelting furnace

dosing oven

Smelting

Self-hardening alloys furnace / process

Figure 3: Aluminium die casting process chain.

machining process machine

quality gate

2.1

quality gate

2

The die casting process itself takes place in casting cells that usually consist of the mentioned dosing oven, the die casting machine with its dies, tempering units, parts-removal robots, spraying devices for applying release agents and saws or stamping presses for removing e.g. gating systems and sprue waste from the work piece. Inside the casting cells the liquid aluminium is casted into solid semi finished parts. In this process electricity is consumed by the dosing oven, the die casting machine, the spraying device, the involved robots, the tempering units, the spraying robot and the saws/stamping presses. Additionally release agents, water and compressed air are used by the spraying device. As process output there are the semi finished parts and aluminium (gating systems, sprue) that is stamped off the semi finished parts. After a visual quality check the semi finished parts are processed by a mechanical treatment. As these operations can be manifold also the input and output flows can be very versatile. Besides diverse auxiliary flows (e.g. coolants or compressed air) at least the electrical energy consumption by the value adding processes and the peripheral equipment like e.g. exhaust air systems needs to be analyzed. In some cases the die casted work pieces also get a heat treatment in order to influence the material properties. Depending on the intended function of the product or by using self hardening alloys this process step is not necessary.

die casted parts in defined quality

Sustainability in Manufacturing - Energy Efficiency in Process Chains 2.2

319

Challenges in aluminium die casting in the context of energy and resource efficiency

assessing the impact of material efficiency in foundries in relation to their total energy consumption.

The aluminium die casting process chain is strongly depicted by significant losses of energy as well as material. A major part of the energy input is needed for heating of material/parts (e.g. very high relevance of waste heat) [6]. But especially the heat balance of the die casting process itself is characterised by high energy losses. A large part of the energy input is lost in the process in terms of heat or by cooling processes. On the whole, the extensive heat losses in the die casting process are extremely dissatisfying in terms of environmental performance respectively energy efficiency. Figure 4 shows the main thermal energy flows in the die casting process of aluminium. Besides the heat losses in the value adding process also the heat losses in non value adding peripheral equipment cannot be ignored.

Furthermore, material losses of 2-5% occur, which cannot be reintegrated into the process again and which are simply lost. Whereas from the company’s point of view those losses are mainly essential in terms of material costs, the energy-intensive and environmentally damaging exploitation of aluminium is especially critical from an ecological point of view (waste which potentially endangers the environment, large areas are necessary for the winning of bauxite, electrolysis for winning aluminium). Thus, from a global point of view, besides an extensive usage of recycled secondary aluminium an enhancement of material efficiency and therefore a reduction of aluminium consumption indirectly also leads to a considerable decrease of energy demand [8] [9].

2, 4 kWh

Restw esi dual h ea t R ärme

0,5 kWh up bis to 5 kWh 5 kWh EvapoVerd ration ampfung

1,9 kWh

1,6 kWh

CKool ü hling ung

CKool ü hling ung

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rme Wä He at lverle oss s

Trennstoff Release agent Casting Gussform mould

6,9 kWh

Gie ßkolben Plunger Melted Schmelze mass

C asting chamber Castin Gie ßkammer Gie gßrchan innenel

Ofen F urnace

Fin ishe d compo nen t

T emperature emperier control Geräunits te

Pheripherieger Peripheral devices äte

Against this background measures for increasing the energy and material efficiency can be devided in two categories: organizational and technology/design oriented measures. Organizational measures adress measures like cycle time reduction and the reduction of unproductive idle modes whereas technology or design oriented measures adress measures that focus on the improvement of the production process itself (e.g. by using energy effcient drives or reducing scrap material) or the improvement of the product or the corresponding machine tools (e.g. through volume reduction of the product and its gating systems).

4,8 kW Environment

6,2 kWh W Hea ärmet verl lo sses uste

Ger Deävice tevelorl sses uste

Figure 4: Thermal energy flows in the die casting process of aluminium [6]. Compared to the casting process itself even more heat is needed in the smeltery for the liquidation of aluminium. In this particular step of the aluminium die casting process chain the energy demand is directly linked to the amount of material that needs to be smelted and therefore can be reduced by reducing the amount of material that needs to be processed in the casting process [7]. However, it is exactly the bad exploitation of the raw material aluminium that is problematic in the process. Spillover and sprue (which can make up up to 50 % of the cast form and are determind by the product and tool design) as well as finished components, which do not meet the required quality demands, and parts from the start-up process are partly remelted into ingots as cycle material and have to run through the whole energy intensive process again. Depending on the production parameters or component this applies to 30-70% of the originally input material (Figure 5) [2]. The impact of the continuos resmelting of cycle material can be estimated regarding the fact that in an average aluminium smeltery 930 kWh of energy are needed for smelting one ton of aluminium. This value is based on the total energy consumption of a smeltery that uses shaft furnaces and can vary depending on the smelted alloy but still can be used for Umschmelzen resmelting in toMasseln ingots

Recycling-Material cycle material 30%30-70% 70%

scrap Ausschuss solid metal Blockmaterial

3

SIMULATION APPROACHES TOWARDS ENERGY AND RESOURCE EFFICIENCY IN ALUMINIUM DIE CASTING

8,9 kWh

3.1

Process simulation in aluminium die casting

Within the research project ProGRess the company Magma Gießereitechnologie GmbH simulates the effects of changing the geometry of e.g. gating systems and the effects of a variation of process parameters (e.g. cycle time and injection speed) on the quality of the casted products. By doing this optimized process parameters can be found through conducting manifold simulation runs. So e.g. the cycle time, quality rate or gating system volume can be reduced/increased in iterative simulation runs and the corresponding product quality (in terms of porosities, solidification behaviour, etc.) can be predicted in order to define the best process parameters according to the individual target function that still guarantee high quality products. To illustrate the potential of a process simulation for the aluminium die casting process Figure 6 compares the original design of an aluminium die casting product and its gating system with an improved version in which the volume of the gating system has been reduced significantly. Through a process simulation that has been conducted with the software Magmasoft® it can be ensured that the quality of the product in terms of entrapped gas, solidification behaviour, etc. is not negatively affected by this measure. By applying this measure 25% of the metal in the gating system can be saved which leads to a decrease in the total aluminium shot weight of approx. 12% [10]. As described above this also directly affects the energy efficiency in the smeltery as there is no smelting energy needed for the saved metal. original design

improved design

material 5% - 7% 5-7%

casting

Gießprozess process

Bauteil product

liquid metal Flüssigmetall

Materialverluste metal loss 2-5% 2% - 5%

Figure 5: Cycle material in aluminium die casting [2]. Figure 6: Design variation of gating system [10].

320

Sustainability in Manufacturing - Energy Efficiency in Process Chains

In this sample simulation run it has also been shown that besides the reduction of the gating system volume also the cycle time can be reduced by 8%. Although this is a respectable result it cannot be predicted whether this measure would lead to bottlenecks in the downstream process chain and therefore would flatten the effect on the production line.

focus on application areas that will lead to real improvements also on a process chain level. In this way a target-oriented improvement of production systems can be ensured.

3.2

The structure and characteristics of the interlinked processes of the underlying case study for the simulation and pre-evaluation of parametervariations is shown in Figure 7. In this case three casting cells with peripheral equipment serve two identical CNC milling machines for mechanical treatment before they are being transported automatically by a conveyor in a one piece flow into an abrasive blasting machine and finally to a palletizing device.

In contrast to detailed process simulation approaches process chain simulation focusses more on the interdependencies and interactions of multiple processes within a factory. Referring to previous publications (e.g. [11] [12] [13]), the architecture (input, logic, user and evaluation layer) of the simulation that is used for this paper shall not be explained in detail here. Basically it is a modular, flexible approach which allows a realistic representation of the production system with all the interdependencies and dynamics of involved technical equipment. As an extension of well-known material flow simulators all energy related input and output flows are explicitly considered. This means that based on real metered consumption data the machine behaviour can be depicted with state charts – each operating state has a definable duration (e.g. based on certain time or trigger events) and is connected with a certain consumption of a resource (described as value or equation, e.g. depending on process parameters). Thus, with this technique the dynamic consumption behaviour of e.g. all forms of energy, any (auxiliary) materials or even emissions can be modelled. Furthermore an energy oriented process chain simulation can predict the overall energy consumption of whole process chains that result from single process parameter variations [11]. Sample load profiles (for electricity as well as compressed air consumption) that can be generated this way are illustrated in Figure 8. The derivation of the electricity consumption that is caused by the generation of compressed air is simulated in an integrated module in which the behaviour of compressors can be modelled. [12] 3.3

Synergies from a combined application of process and process chain simulation

The impact of organizational or technological or design oriented improvement measures regarding economical criteria (lead times, product-related costs, etc.) as well as ecological criteria (energy and material consumption) underlies dynamical effects within the process (e.g. thermodynamical behaviour of material flows) as well as along the process chain (e.g. dynamic energy demand, bottle neck situations). As these effects often depend on partial reciprocal interrelations of the individual subsystems of a production process or on interactions of subprocesses within a process chain a simulation approach is needed for the evaluation of improvement scenarios that are proposed to be implemented in the process chain. Especially detailed process oriented simulation approaches face the challenge that they can only serve with a very limited perspective when it comes to a holistic evaluation of a process chain. Still their potential for delivering a detailed view into the order of events of the main processes within a process chain is often more promising than the exclusive use of a process chain simulation. As it is often practically not feasible to run a detailed process simulation for every subprocess and as it is also not feasible to simulate the effect of every single process parameter in every kind of peculiarity due to restrictions of computing capacities a combination of the advantages of process and process chain simulation approaches is needed. One approach for the preevaluation of the effect on a process chain that comes from parametervariations within one single process will be introduced in the following. This pre-evaluation will set the boundaries for a parametervariation in a detailed process simulation that is used for the improvement of die casting operations. With these restrictions as input for detailed process simulations those simulation runs can

CASE STUDY

Elements of the process chain that are not depicted in Figure 7 are beyond the system boundary of the case study. Thus effects on upstream processes like smelting ovens are calculated based on the simulation results afterwards. Casting cell

Saw, Robot

Casting cell

Saw, Robot

CNC-milling CNC-milling Casting cell

Abrasive blasting

Palletizing

Saw, Robot 90000 80000

Die casting machine

W

70000 60000

peripheries

Process chain simulation for aluminium die casting

4

50000

heating/ cooling

40000 30000

spraying robot

20000

handling robot

10000

Casting cell

t

0

Figure 7: Process chain for simulation case study. The simulation model that has been deduced from the process chain description is depicted in Figure 8. It is parameterized with real metered data like cycle times, (energy) load profiles depending on operation modes, process dependend material efficiency, etc. and focuses on the consumption of electrical energy in this case. Based on this model and the underlying parameterization for every subprocess of the process chain the effect of changing process parameters in the die casting process on the total energy consumption per part and the required throughput time per part can be estimated. The manipulated process parameters in this case are the cycle time and quality rate. Furthermore the effect of the quality rate in comparison to the material volume of the product and its gatingasystemainatermsaofamaterialaefficiencyacanabeaevaluatedain 800

1,000

contract power [kW]

compressed air [m³/h ]

400

500

system electricity consumption [kW]

0

0 0

2,000 4,000 Electrical power consumption (1s and 15min interval)

0

2,000 4,000 Compressed air consumption (1s interval)

Figure 8: Simulation model based on case study process chain and sample load profiles.

Sustainability in Manufacturing - Energy Efficiency in Process Chains order to evaluate levers for decreasing the embodied energy per part. As this is a process chain simulation only the effects on the process chain are considered. The effects of parametervariations on the intra-process behaviour (e.g. in terms of wear or differing load peaks through speed variations) need to be evaluated afterwards by a detailed process simulation. 4.1

Varied parameters on process and process chain level

The objective in this case is the production of 40 flawless parts.This output is set fixed. Through the variation of single process or design parameters manifold scenarios can be simulated. Table 1 depicts the single parameters (cycle time, material volume, quality issues, etc.) that also can be manipulated in detail in the process simulation Magmasoft®. In this case the shot weight is directly linked with the material efficiency. As the product design and the product weight are set fixed the aluminium shot weight can still be varied because of possible design variations of the gating system. As the gating system gets stamped off the product after the casting process it becomes cycle material and the volume of the gating system determines the material efficiency of the die casting process. Regarding the two simulation approaches the volume of the gating system has a direct impact on the mold filling and therefore on the product quality that can be simulated in the process simulation. On the process chain level the material efficiency as well as the quality rate that determines another part of the cycle material have an impact on the total energy consumption regarding the smelting energy in the shaft ovens. The cycle time can be manipulated by changing the clamping time of the die casting machine (DCM). On process level this is linked with the simulation of the solidification behaviour and the shortest required cycle time for continuous solidification. On the other hand the effects of manipulated cycle times can lead to new bottleneck situations or changes in the length of standby or operative modes of succeeding processes on process chain level. It is assumed that the characteristic of the underlying load profile of the DCM is not affected by changes in the cycle time in this case as the varied clamping times represent only changes in idling times and no changes in the dynamic power consumption behaviour of the machine. 4.2

Simulation scenarios based on parameter variations

The described parameters are varied in a realistical and technical feasible range in different scenarios (see Table 1) in order to preevaluate their effect on the process chain as an input for a succeeding detailed process simulation. They are individually compared to a base run of the process chain simulation. Scenario 1 (S1) to scenario 5 (S5) describe an increase in material efficiency through an improved design of the gating system which leads to a decrease in the aluminium shot weight. S6 to S13 describe a variation in the cycle time whereas a decrease is considerd as well as an increase. S14 and S15 deal with a variation in the quality rate, which also affects the overall energy consumption as energy is wasted through scrap material. S16 is a combination of S5 and S9 and therefore describes the effect of reduced cycle times in combination with reduced aluminium shot weight. This combination Scenario Base run Scenario

Shot weight 100%

Shot Material weight Efficiency

S1

98%

S2

96%

S3

94%

Material Efficiency 71,10%

Scenario Cycle Time

73%

S6

74%

S7

76%

S8

94%

Scenario

98%

S14

96%

S15

S4

92%

77%

S9

92%

S5

90%

79%

S10

102%

S11

104%

S12 S13

Quality Rate

Cycle Time 100%

Quality Rate 100%

Material Cycle Scenario Shot weight Efficiency Time

Quality Rate

95%

*1

S16

90%

79%

92%

100%

98%

S17*2

90%

79%

92%

100%

*3

90%

79%

92%

100%

*4

90%

79%

92%

100%

*5

90%

79%

92%

100%

S18 S19

S20 *1

: Combination of S5 and S9

*4

106%

*2

108%

*3

: Abrasive Blasting: Lot Size 1 : Only 2 DCMs and S16 : Abrasive Blasting: Lot Size 10 and S16

: Only 2 DCMs

*5

Table 1 : Scenarios and parametervariations for process chain simulation case study.

321 is noteworthy as usually a reduction of shot weight enables a reduction of cycle times as the solidification of the metal takes less time when less material is casted. S17 and S18 describe the effect of selected organizational measures for an improvement of the process chain. Lot sizes of a process with high energy consumption during standby modes (abrasive blasting, see Figure 7) are varied and the process is simulated to be shut down during idling times in order to avoid standby energy consumption. S18 combines S17 with S16. S19 describes the reduction of DCMs in the process chain from three to two as another orgainzational measure. S20 combines S19 with S16. 4.3

Process chain simulation results as boundary conditions for process simulation

Figure 9 shows the simulated energy consumption per flawless part in relation to the result of the base simulation run which is paramterized with real metered process data and parameters. The base run itseld shows that the die casting cells are the main electricity consumers with a share of about 73%. The abrasive blasting process as well as the compressors for the generation of compressed air have a share of 11% each whereas the saws, robots and CNC-milling-machines have a share of only 5% in total. 110,00% 105,00% 100,00% 95,00% 90,00% 85,00% 80,00% Base S1 Run

S2

S3

S4

S5

S6

S7

S8

S9

S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20

Figure 9: Total energy consumption per flawless part. It is obvious that the reduction of casted material leads to a decrease of the energy consumption per part as the saved metal does not need to be smelted. In comparison to that the variation of cycle times does not lead to a strong increase or decrease of the energy consumption on process chain level. On the contrary a decrease of the quality rate leads to a significant increase of energy consumption as it is also connected with additional scrap material that needs to be smelted. Regarding that a decrease in the volume of casted metal often allows a decrease in the cycle time of the process it is shown with the results of S16 that this combination of varied parameters leads to a decrease in the energy consumption per flawless part of about 10% compared to the base simulation run. S17 and S18 show that the change to a batch production at the abrasive balsting process has an additional effect of only about 2%. The reduction of DCMs (S19 and S20) show only a marginal effect as the production load has to be transferred to the remaining DCMs in order to produce 40 flawless parts – but it shows that the investment in the third machine would not necessarily have been needed. Regarding the time per part (Figure 10) the simulation results demonstrate that none of the described parameter variations lead to a significant effect on process chain level. The throughput time is only affected by organizational measures like the batchwise production in the abrasive blasting process and the reduction of DCMs. 110,00% 105,00% 100,00% 95,00% 90,00% 85,00% 80,00% Base S1 Run

S2

S3

S4

S5

S6

S7

S8

S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20

Figure 10: Production time per part. Figure 11 illustrates the lever that single parameters have on the total energy consumption per part and the production time per part on process chain level. As the same parameters can be simulated in a detailed process simulation like Magmasoft® for the optimization of the die casting process the results of the process

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Sustainability in Manufacturing - Energy Efficiency in Process Chains

chain simulation can span an area of parametervariations in which a detailed and time-consuming process simulation can lead to promising results. Therefore this pre-evaluation of parameters can decrease the effort that is needed for a holistic improvement of processes and process chains.

7

Sensitivity: Energy per flawless part

[2]

Institute of Joining and Welding, TU Braunschweig.

[3]

German Federal Ministry of Economics and Technology (2007): Energy Statistics, http://www.bmwi.de/ BMWi/Navigation/Energie/ enenergiestatistik.html.

[4]

Schultz, A. (2002): Methode zur integrierten ökologischen und ökonomischen Bewertung von Produktionsprozessen und technologien, Dissertation, Magdeburg, Germany.

[5]

Herrmann, C., Thiede, S., Heinemann, T. (2010): Ganzheitliche Ansätze zur Erhöhung der Energie- und Ressourceneffizienz in der Produktion, in: 10. Karlsruher Arbeitsgespräche Produktionsforschung 2010, Karlsruhe, Germany, 2010.

[6]

Optimierung der Energiebilanz beim AluminiumDruckgießprozess, final report, Deutsche Bundesstiftung Umwelt, support code AZ 22197, 2007.

[7]

Soldering, P., Petku, D., Mardan, N. (2009): Using simulation for more sustainable production systems - methodologies and case studies, in: International Journal of Sustainable Engineering, Volume 2, No. 2.

[8]

Bayrisches Landesamt für Umweltschutz (2005): Effiziente Energieverwendung in der Industrie – subproject „Metallschmelzbetriebe“, Augsburg.

[9]

Anders, U., Pries, H. Dilger, K. (2003): Ökologisch und ökonomisch optimierter Trennstoffeinsatz beim AluminiumDruckguss, BMBF, 01RW0055, Braunschweig, 2001-2003.

[10]

Magma Gießereitechnologie GmbH, presentation at 10. Karlsruher Arbeitsgespräche Produktionsforschung 2010, Karlsruhe, Germany, 2010.

[11]

Herrmann, C.; Thiede, S. (2009): Process chain simulation to foster energy efficiency in manufacturing, in: CIRP Journal of Manufacturing Science and Technology, Elsevier, ISSN 17555817.

[12]

Thiede, S., Herrmann, C. (2010): Simulation-based Energy Flow Evaluation for Sustainable Manufacturing Systems, in: Proceedings of the 17th CIRP International Conference on Life Cycle Engineering (LCE2010), pp. 99-104, Hefei, China.

[13]

Herrmann, C., Thiede, S. (2009): Towards Energy and Resource Efficient Process Chains, in: Proceedings of the 16th CIRP International Conference on Life Cycle Engineering (LCE2009), pp. 303-309, Cairo, Egypt.

110,00% Shot weight Cycle Time Quality Rate

105,00%

100,00%

[1]

95,00%

90,00% 90%

95%

100%

105%

110%

Sensitivity: Production time per part 110,00% Shot weight Cycle Time Quality Rate

105,00%

100,00%

95,00%

90,00% 90%

95%

100%

105%

110%

Figure 11: Sensitivity anlaysis of simulation results 5

SUMMARY / OUTLOOK

Against the background of the increasing relevance of considering energy and resource consumption in producing companies the paper introduces the aluminium die casting process chain as example for highly energy intensive process chains. Two simulation approaches are presented for the evaluation of parametervariations on process and on process chain level. Both simulation approaches are applied to case studies from the aluminium die casting industry. Within this case study the process chain simulation is used for a pre-evaluation of effects that occure on process chain level an are affected by variatons in the die casting process. Through this preevaluation the area of necessary parametervariations within the process simulation can be reduced in order to decrease the necessary computing capacity and to enable a more target oriented improvement of the process chain. As result of the process chain simulation a potential for decreasing the energy consumption per part by 10-15% seems to be possible. In upcoming research work the results of the process simulation have to be used as input on process chain level. By doing this the results of the detailed optimization on process level can be finally evaluated on process chain level for achieving a severe improvement in the observed production system. 6

REFERENCES VAR – Verband der Aluminiumrecycling-Industrie e.V., Key Figures – Production of Aluminium in Germany; http://www.aluminiumrecycling.com/en/recycling/eckdate n.php.

ACKNOWLEDGMENTS

The introduced analysis of the aluminium die casting process chain is based on the research project ProGRess (Design of Resource efficient Process Chains using the Example of Aluminium Die Casting; www.progress-aluminium.de) that is funded by the German Ministry of Education and Research (BMBF) and managed by the project management agency Karlsruhe (PTKA). All data has been anonymized and alienated and does not show the exact results that have been elaborated within the project consortium.

8

CONTACT

Christoph Herrmann

[email protected]

Tim Heinemann

[email protected]

Sebastian Thiede

[email protected]

Institute of Machine Tools and Production Technology (IWF), Product- and Life- Cycle-Management Research Group, Technische Universität Braunschweig, Germany

Context-Aware Analysis Approach to Enhance Industrial Smart Metering 1

2

1

1

2

2

2

C. Herrmann , S.-H. Suh , G. Bogdanski , A. Zein , J.-M. Cha , J. Um , S. Jeong , A. Guzman 1

1

Institute of Machine Tools and Production Technology (IWF), Product- and Life-Cycle-Management Research Group, Technische Universität Braunschweig, Germany 2

Center for Ubiquitous Manufacturing, POSTECH, Pohang, Gyeongbuk, South Korea

Abstract With consideration of the increasing relevance of energy consumption and rising energy costs, strategies to improve energy efficiency in manufacturing environments have to be developed. As the energy consumption results from the temporal accumulation of individual power demands of subordinate devices, energy metering enables to capture these demands and display the dynamic behaviour. A fundamental precondition for the identification and implementation of improvement measures is nevertheless transparency about energy demands as well as related couplings and interdependencies. In this paper, the context-aware analysis approach is proposed to provide additional information supporting the understanding of energy consumption in manufacturing environments. Keywords: Manufacturing System; Energy Efficiency; Context Awareness

1

INTRODUCTION

In manufacturing systems energy and resources are used in order to obtain operational readiness (e.g. through compressed air provision or heating) and conduct transformation processes for value creation. Hence, manufacturing is simultaneously value creating and resource-consuming. Due to increasing electricity and raw material costs, the usage of energy and resources is increasingly exerting pressure on the management of manufacturing companies. Industrial operations have consumed about 29 % of the final energy in Germany in 2007 [1]. Considering the electrical energy proportion, more than 556 PJ are used in industrial application areas. This corresponds to 23 % of the total industrial final energy consumption [2]. In the Republic of Korea the industrial sector is even responsible for 56 % of the final energy consumption in 2006. When calculating the share of the electrical energy consumption, the industrial sector accounts for more than 50 %, representing about 598 PJ [3]. Assuming 3500 kWh yearly electricity consumption per 4-member household, this equals to more than 92 million households. With regard to the increasing relevance of energy consumption in manufacturing systems and the related costs, strategies to improve energy efficiency have to be developed. In accordance with the principles of a sustainable development, these strategies have instantly to consider economic, ecological and social aspects from a life cycle perspective in order to avoid problem shifts from one life cycle phase to other life cycle phases [4]. ‘Organizations of all kinds are increasingly concerned to achieve and demonstrate sound environmental performance by controlling the impact of their activities, products or services on the environment […].’ (Introduction of DIN EN ISO 14001 [5]). In this statement the aspect of control, as an enabler to improve sustainability, is highlighted. In order to realize a sustainable development through control, management systems have to be enabled to define objectives and derive strategies to efficiently design, plan and operate all elements in manufacturing systems [6]. An important precondition for this is the availability of adequate and prompt information about the energy and resource demands and

resulting consumption patterns of all elements in manufacturing systems in order to facilitate optimal decision making of improvement measures [7][8]. 2 2.1

INDUSTRIAL SMART METERING Energy consumption of manufacturing processes

Manufacturing processes transform semi-finished inputs into valueadded outputs. Energy consumption becomes a physical necessity to perform that transformation. Theoretical calculations can be performed to estimate minimum energy expenditures of energy to perform processes (for example metal cutting or metal forming), but due to several losses in forms of mechanical friction, plastic and elastic deformation as well as the resulting heat losses a fairly higher amount of necessary energy expenditures is needed to perform the actual transformation process. Gutowski et al. have shown in early studies of manufacturing processes that the actual consumed energy for machining processes is overwhelmed by over five times as much energy needed for auxiliary processes like coolant pumps, lubrication supply and technical air ventilation [9]. To draw that conclusion Gutowski et al. had to meter the actual power demand of all subordinate devices in regard to the overall demand of the process related to the number of produced units. Another study concerning the energy efficiency of manufacturing processes was performed by Devoldere et al., showing that the regarded hydraulic press brake’s actual processing time, used for discrete work piece bending added up for a time share of less than 13 % of the total active time of the machine, resulting in a unproductive time share of over 87 %, consuming a high amount of unnecessary energy expenditures [10]. In this study Devoldere et al. have clearly indicated the need to approach an analysis of energy consumption behaviour by considering the aspect of time. Consumed energy is the integrated demand of electrical power over a certain period of time and is usually not considered as being static in its behaviour. In order to gain a better understanding of energy consumption of manufacturing processes a metering strategy has to be applied

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_56, © Springer-Verlag Berlin Heidelberg 2011

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taking the aspect of time-dynamic behaviour and of subordinate devices into consideration. 2.2

Metering of energy consumption

To gain an understanding of the energy and resource consumption behaviour of manufacturing processes a time-related measurement of the power demand of a selected system is to be applied initially. The electrical power actually demanded by a process is imposed indirectly from the metering values of voltage and current of all active electrical supply lines of the system. Figure 1 shows the power profile P(t) of an exemplary production machine.

Figure 3 shows exemplarily how the linkage of expert knowledge to the power profile from Figure 1 can be applied. The grey horizontal and vertical lines indicate a rough division of power demand ranges of different operation modes of the processes observed by the process engineer from the operation of the selected grinding machine. maximum process power P/W

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Figure 3: Power (P) demand of a grinding process over time (t).

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Figure 1: Power profile P(t) of a production process. The amount of informational degree that can be derived from the given metering data is highly dependent of the granularity of a measurement in time and in amplitude [11]. This granularity is a result from the metering system’s sampling rate, metering signal resolution and the capacity of the digital processing system in the measurement chain. Analysing Figure 1 under the aspects of a better energetic system understanding, one can define maximum power demands and draw a conclusion about the dynamic behaviour of the process by estimating the variance of the profile, but can hardly allocate any power demand level to any operation mode. Neither can one tell which amount of consumed energy was related to value adding and which to non-value adding operation modes. In order to gain a better understanding of the power profile the lack of information has to be compensated with expert knowledge of operators or engineers or further informational sources. The selection, dimensioning and operation of the metering system as well as the realisation of a metering data acquisition, data processing and the provision of the pre-processed metering data is what we have related to in this paper as Industrial Smart Metering. The emphasis on ‘smart’ is related to the coupling to an integrated data pre-processing and communication interface.

Energy

System

Resources

Products Emissions

Time

Figure 2: Generic metering model for better energy and resource aware system understanding (adapted from [7]). Industrial smart metering adopts the generic model of energy and resource metering of industrial manufacturing processes as depicted in Figure 2, in order to create a foundation for a better system understanding by taking all inputs and outputs as well as the time aspect into consideration. When applying also expert knowledge to the gained metered data, a certain degree of allocation of power demands and time shares is possible by either logging process observations or known events to the metered data.

The higher informational degree of Figure 3 in relation to Figure 1 is determined by the allocation of time-spans to events like start-up, machine setup and processing. Each time-span contains a specific field of individual power demand behaviour. But nevertheless, a true allocation of subordinate power demands is hardly possible on the given informational background not mentioning the time and effort to manually allocate visual observations to the time axis of the metered power profile. Today’s market provides smart meters known from the applications in private households, implemented with the focus to enable a certain level of transparency of the energy consumption of a household. By giving the user a visual feedback through various means of information ranging from power profiles over different time periods or accumulated energy counts or even calculated performance indicators. The provided information is generated in order to overcome the consumer’s habitual consumption behaviour by raising his awareness for the energetic impact of his behaviour [12]. The new awareness is ideally causing a motivation in the consumer to rethink his routine behaviour and finding a more optimal solution while taking energy as a new optimization criterion into consideration. The concept of Industrial Smart Metering is trying to adapt the same approach as smart metering in private households and is applying it to the requirements of a manufacturing environment [11]. Obviously, the requirements of a manufacturing environment are a lot more ambitious. The target group of the provided energy-related information does not only consist of one or two persons with quite the same interest, skill, and competence level as in a private household, but is rather divers, ranging from the shop floor operator and facility manager up to the process engineer and management staff. Each single target person has a different expert knowledge and a separate range of operational competency which leads ideally to a very case specific information provision for each receiver of the information. Against this background the use of context related information to enhance the analysis and evaluation of power demand profiles in terms of industrial smart metering by integrating additional already existing informational sources from the manufacturing environment is proposed. Such additional informational sources can be simply the human logging the operation modes or rather complex, the machine’s programmable logic controllers (PLC) as proposed by Vijayaraghavan and Dornfeld [13], external sensors, and historical metering data from databases. The following chapter introduces the

Sustainability in Manufacturing - Methods and Tools for Energy Efficiency context-aware approach and introduces a general model that can be applied to manufacturing environments. 3

CONTEXT AWARE APPROACH

3.1

Context-awareness

Currently, ubiquitous computing technologies are receiving an increasing attention as a means to realize a more sustainable manufacturing [14][15][16]. Especially, among the technologies, context-awareness can be used to increase the understanding of energy consumption in manufacturing environments. This section describes a basic introduction into the contents of contextawareness and explains the major elements of technology. In general, context-awareness is the ability to provide suitable services to a user by analyzing the context of the user. The context can be any information characterizing the situation of an entity. The entity can be person, place, or object relevant to the interaction between the user and a context-aware application [17]. The context is diverse from situation to situation. In case of the energy related situation, the energy profile, historic consumption data, operational data from PLC and ERP can be considered as some of the available context. A system can be understood as context-aware if it uses context to provide relevant information and/or services to the user, where relevancy depends on the user’s task. In order to realize a context-aware integration of the additional contextual informational sources, the following major elements of technology are required as shown in Figure 4. Application service Middleware Context reasoning Ontological Rule-based reasoning approach Context modelling

Context model

Distributed reasoning

Application interface

Additional reasoning

User Device

Data integration

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… Context sensing Receptor

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A/D convert Manual input

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325

maintain ensuring the integrity, consistency and validity of the context and to apply reasoning techniques. Many modelling approaches are available such as mark-up scheme models, graphical models and ontology based models [19]. The model is required when incorporating external databases from users, devices, environments, etc. Context reasoning Reasoning the context is to infer logical consequence from existing information and decision rules. The aim of context reasoning is to deduce new knowledge, based on the available context information. To do so, the reasoning engine checks the context model database for consistency, classifies new information and applies decision rules. Based on the collected information, and on the decision rules provided by the experts, the system can adapt itself to the changes which are detected. There are various techniques such as ontological reasoning, rule-based approach, distributed reasoning, and additional reasoning including probabilistic logic, fuzzy logic, and Bayesian networks [20][21][22]. Middleware The middleware intermediates between the low-level measuring devices and the high-level context-aware application. The middleware consists of sub-modules which support context sensing, modelling, and reasoning. It collects the sensed context, processes the context, and provides suitable services to the application via the application programming interface. 3.2

Holistic factory model adopting context-awareness

In the field of sustainable manufacturing, the context-awareness approach for fostering energy and resource efficiency has not been seen yet. It aims towards enabling operators to make a decision, based on a systemic system understanding derived from real-time sensed context of the factory, instead of a decision based on a fragmentary system view derived from single energy profiles and a limited expert knowledge. Figure 5 shows a context aware information handling model implemented into a holistic factory view including the technical building services (TBS), machines, the factory environment, the energy and resource distribution network and the factory shell as possible context sources. The rather holistic perspective of the manufacturing environment implies the informational complexity indicated by many metering points and various decentralised data storage devices. Application system

Figure 4: Generic architecture of context-awareness middleware. Context sensing Sensing the context is the start of context-awareness. The context could be collected via manual input of an operator, analogue or digital input of sensors (such as smart energy meters), RFID readers and sensor network nodes. Then the receptors process the information with additional treatments such as signal processing, feature extraction, and profile generation. The sensed context is stored according to a context model and is used for reasoning [18].

Context

HMI Mobile In-machine Workstation

Visualization Middleware Context reasoning Context modeling

Context model

Context sensing

technical building services

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Time

Barcode scanners

Metering database

Operator

...

Environment (Factory) Temperature Humidity profiles profiles Schedules Time Distribution net

ERP data

Humans

... factory environment machine Legend:

Context modelling The context model provides a basis on which the context-aware application is developed and executed. The model is used to express and store the dynamic and uncertain information sensed while the application is running. The model should be easy to

machine distribution network

source of context: smart metering decentralized data storage and processing

Figure 5: Concept of the context aware information handling.

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The presented context-aware approach is aiming to extend the users understanding of the energy and resource flows by providing a better transparency of the system behaviour of single consumers and their related processes as well as in relation to the whole manufacturing environment. The amount of informational degree provided to the user is targeted to extend his already existing expert knowledge.

metering is applied at an exemplary compressed air distribution network with the use of context sensing on one producer (PP) and three consumers (CP A, CP B and CP C). The sensed context is derived from electrical power metering on the four devices. The main metering point is deployed by means of installing an industrial volumetric flow sensor in the distribution network between the producer (with buffer) and the three consumers.

In order to derive a higher informational degree from industrial smart metering data the available context around the entity has to be sensed and aggregated in context models. This task is performed by the middleware as depicted in Figure 5. The proposed context used for extending the informational degree is divided into two categories consisting of context information from processes, including machines and TBS as well as context information from the environment, represented by the surrounding factory. The various informational sources inside these two categories range from visual observations from operators in forms of digital process protocols to real-time sensor data from subordinate processes or interlinked processes. The middleware fulfils the role of aggregating this context information as well as interpreting the individual informational sources in terms of indicating their relation to the metering data that is to be analysed (e.g. a graph like Figure 1). The interpreted data is handed on to the reasoning unit which is interlinking the informational sources and is providing the higher informational content to the user through visualisation elements. The relative context that is taken into consideration is case specific and can consists of informational sources directly related to the process, like energy meters or position sensors or speed sensors as well as indirectly related informational sources like, ERP-data, barcode scanners and RFID-readers. The superposition of smart metered data and context-aware information is aiming to provide the user a higher degree of information as he himself would be capable of deriving by using solely his expert knowledge as a single source of information.

Graph a) of Figure 6 shows the metered volumetric flow profile Q(t) of the compressed air flowing from the producer side to the consumer side. Without further information a proper analysis of the volumetric flow profile cannot be executed sufficiently. Peak demands can be identified, but the much more important key figures like leakage flows or identification of consumption behaviour of single consumers is impossible without having more volumetric flow metering points at each single consumer at hand.

a)

4.1

CASE STUDIES Technical building services

Compressed air is one of the most commonly used pre-processed secondary energy forms in industrial manufacturing processes. Around 10 % of the total electrical energy consumed by the industry sector can be allocated to compressed air usage [23]. In defiance to the low efficiency of compressed air production, the energy carrier compressed air is in high favour of the manufacturing industry because of its universal applicability. It is used in machine tools for clamping, air-lubricated bearings, in handling processes for grippers and sorting and in control applications even as an information carrier. To the human, compressed air is invisible, has no harming effect if being exposed to it, is only sensible through its impulse or by its acoustic noise when passing from high pressure to low pressure environments and is often taken for granted because no separate cost units exist. These facts lead to the matter why compressed air is mostly treated unaware of its actual impact to the overall energy consumption. In most manufacturing companies the actual compressed air consumption of single processes or whole distribution systems is unknown. The degree of transparency is therefore very low, which makes it an ideal application field for the presented approach. This case study shows how industrial smart

Q / m³/h

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Sensed context

The individual receiver of the context aware information is not restricted by the context-aware application in any way to use his expert knowledge and competence level to draw further conclusions and to tap the derivable efficiency potentials by changing his usage behaviour or by taking direct actions.

The approach of context-awareness allows us now to have a walkaround of installing new sensor elements by accessing already existing informational contexts. In this case study we present how already existing electrical energy meters installed in the three consuming processes used for industrial smart metering purposes can benefit the analysis of the Q(t) profile by applying the presented context-aware approach.

PP CP A CP B CP C t/s

Figure 6: Context-aware analysis of a compressed air profile. The sensed context information in graph c) consists simply of the duty cycles of the four devices derived from the change in state of the electrical energy consumption profiles (high state equals a power demand higher than zero, low state equals a power demand of the processes of zero watts), assuming that compressed air is consumed as soon as the machines are powered up. During context modelling, the change of the duty cycles from active to inactive and vice versa are synchronised in time axis with Q(t) and allocated to the enlarged section of the volumetric flow profile displayed in graph b) of Figure 6. From graph b) and the allocated context-aware information of graph c), the user is now able to derive much more transparency of the compressed air distribution network through the application of context reasoning. During the time where no producer and no consuming devices are running, a constant leakage flow can be successfully identified. In the same way, peak demands can be

Sustainability in Manufacturing - Methods and Tools for Energy Efficiency

With regard to the energy-related optimization of machine tools from process and component perspective, a comprehensive understanding of the underlying processes and operating states of components during the operation of the machine tool is essential. Due to the complexity of performed processes and the time overlay of starting and stopping procedures, guidance is required providing data about the exact operation of each integrated device [13].

Machine tool Signal elements Control (PLC)

P/ W

Process definition (HMI)

Sensor systems

Frequency converters Energy flow Information flow

Power demand due to operation of components

Spindle velocity, Position of axis, …

Spindles / Motors

Middleware

t/ s

t1

P(t)

(context sensing)

Figure 7: PLC as information source for energy-related analysis. Programmable logic controllers (PLC) are applied in machine tools to realize the automated operation of machining processes. Hence, PLCs are controllers that capture data about the conditions and operating parameters of components in order to test, evaluate and resolve parameters to operate the process [27]. Thus, the PLC represents an important source of information which can support the analysis of power profiles in a context-aware application (see Figure 7). Data from the PLC of a grinding machine tool was accessed using an OPC protocol and transferred for context sensing via middleware in a database system [28]. The considered test procedure includes the starting of the machine tool and the spindle as well as moving the axis. Due to the variety of available data, the spindle velocity and positions of the x- and z-axis were initially monitored. The resulting data from a power measurement as well as the PLC data is displayed in Figure 8 for the operation of the machine tool. In context modelling, the superposition of data from the two sources is done through time index synchronisation. This enables to relate the increase of power demand with the operation of the spindle. Consequently, an energy-related analysis can be initiated improving the power demand of the spindle as well as the operating time by context reasoning. With regard to the movement of the axis, the power measurement revealed no significant increase of power. However, the measured data enables to identify and avoid nonvalue adding movements of the axis and can thus support the reduction of processing times to a necessary minimum. The merging of PLC data with power demands supports the context-aware understanding of the process and performed motions of the integrated components and thus avoids manual monitoring

6 Power (kW)

Machine tools are primarily the centre of attention with regard to power measurements performed in manufacturing [10][24][25]. While it is simple to measure the temporal power demand of a manufacturing process, the analysis of the performed operations and the resulting behaviour demands additional information in order to derive optimal improvement measures and determine the saving potentials [26].

Effective Peff / kW

Integration of PLC data in power measurements of machine tools

4

2

0 Z-Axis Position Spindle Velocity (normalized) (normalized)

4.2

and observation of the machine tool behaviour for an energy-related analysis. Hence, this represents the starting point to resolve highly detailed data about the energy demands and operation of components as a basis for energy-related improvements (e.g. process improvement) [13]. Although software applications provide access to the PLC of a machine tool, the interpretation of the data is yet time demanding in order to create a context model with consistent linking of the data sources to sub-component operations and modes.

1

X-Axis Position (normalized)

allocated to single processes. The additional knowledge gained from the context-aware analysis can be transformed into immediate efficiency optimisation actions.

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Figure 8: Example of merging data from power measurement and PLC information.

5

SUMMARY AND OUTLOOK

This paper has introduced a context-aware analysis approach to enhance industrial smart metering applications. It was shown that the manufacturing industry is getting sensitised to treat energy and resource consumption in manufacturing environments not simply as necessary cost factors to enable value-creation, but as a strategic investment just like time and material. Energy and resource aware manufacturing requires a high level of system understanding. The basis for this understanding is industrial smart metering. It has been shown that understanding metering data requires system knowledge that is unevenly distributed on various knowledge carriers inside the manufacturing environment. The introduced context-aware analysis approach is adapting methodologies known from context-aware applications on consumer-product level to the industrial manufacturing environment. Two case studies show exemplarily the application of the approach. It could be demonstrated how the different informational sources ranging from smart energy meters to machine PLCs could be used to enhance the analytical degree of information of the presented volumetric flow and power profiles. While context-awareness is mostly applied to simple usage scenarios like houses, offices, etc. but rather seldom to complex usage scenarios like factory environments, the resulting challenges

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become quite obvious. The context in manufacturing environments is much more complex and has more dynamic contexts and events. Therefore, we see a wide field for more fundamental studies on context-awareness applications in manufacturing environments. The paper has shown the benefits that can be derived in the field of energy efficiency and is emphasizing the potentials in the field of a more sustainable manufacturing.

[12] Fischer, C. (2008): Feedback on household electricity consumption: a tool for saving energy?, in: Energy Efficiency, pp. 79-104. [13]

Future work will focus on the methodological aspects of the contextaware analysis approach to match specifically the manufacturing environment. Furthermore the studies on gaining energetic flow transparency of manufacturing processes will be broadened and intensified.

Vijayaraghavan, A.; Dornfeld, D. (2010): Automated energy monitoring of machine tools, in: CIRP Annals – Manufacturing Technology, Vol. 59, pp. 21-24.

[14]

Suh, S.-H.; Shin, S.-J; Yoon, J.-S.; Um J.-M. (2008): UbiDM: a new paradigm for product design and manufacturing via ubiquitous computing technology, in: International Journal of Computer Integrated Manufacturing, Vol. 21, Issue 5, pp. 540-549.

6

[15]

Shin, S.-J.; Yoon, J.-S.; Suh S.-H. (2010): u-Factory: A conceptual framework and its application, in: 7th CIRP Intelligent Computing in Manufacturing Engineering, Capri.

[16]

Um, J.-M.; Yoon, J.-S.; Suh S.-H. (2008): An architecture design with data model for product recovery management systems, in: Resources, Conservation and Recycling, Vol. 52, Issue 10, pp. 1175-1184.

[17]

Dey, A.K.; Abowd, G.D. (1999): Toward a better understanding of context and context-awareness, Technical Report, Georgia Institute of Technology, pp 9-22.

[18]

ISO (2007): ISO 13374-2:2007 Condition monitoring and diagnostics of machines – Data processing, communication and presentation – Part 2: Data processing.

[19]

Strang, T.; Linnhoff-Popien, C. (2004): A Context Modelling Survey, in: Proceedings of the 6th International Conference on Ubiquitous Computing, Nottingham, England.

[20]

Ranganathan, A.; Al-Muhtadi, J; Campbell, R.H. (2004): Reasoning about Uncertain Contexts in Pervasive Computing Environments, in: IEEE Pervasive Computing, Vol.3, No.2, pp. 62-70.

[21]

Korpipää, P.; Mäntyjärvi, J.; Kela, J.; Keränen, H.; Malm, E.-J. (2003): Managing Context Information in Mobile Devices, in: IEEE Pervasive Computing, Vol.2, No.3, pp. 42-51.

[22]

Bikakis, A; Patkos, T; Antoniou, G.; Plexousakis, D. (2008): A Survey of Semantics-Based Approaches for Context Reasoning in Ambient Intelligence, in: Communications in Computer and Information Sci., Vol. 11, Springer, pp. 14-23.

[23]

Radgen, P.; Blaustein, E. (2001): Compressed air systems in the European Union, LOG_X Verlag.

ACKNOWLEDGEMENTS

This work was made possible by the financial support of the German Academic Exchange Service (DAAD) and the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (MEST) of Korea within the project funding for the “German-Korean Partnership Program (GEnKO) - Sustainable Manufacturing through Ubiquitous System Engineering” (D/09/02082) as well as by the support of the Korea Ministry of Environment (MOE) within the “Project of a School of Ecodesign”. 7

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[2]

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[3]

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Devoldere, T.; Dewulf, W.; Deprez, W.; Willems, B.; Duflou J. (2007): Improvement Potential for Energy Consumption in Discrete Part Production Machines, in: Proceedings of 14th CIRP Conf. on LCE, pp. 311-316. Herrmann, C.; Bogdanski, G.; Zein, A. (2009): Industrial Smart Metering – Application of Information Technology

Exergy Efficiency Definitions for Manufacturing Processes 1,2

1

1,2

Renaldi , Karel Kellens , Wim Dewulf , Joost R. Duflou 1

1

Center for Industrial Management, Dept. of Mechanical Engineering, Katholieke Universiteit Leuven, Belgium 2

Group T – Leuven Engineering College, K.U. Leuven Association, Belgium

Abstract The original application of thermodynamic metrics for manufacturing processes has been under development throughout the last decade. The metrics are based on the second law of thermodynamics. Therefore, the exergy value of both input and output streams is used to quantify them. Different definitions of exergy efficiency metric have been employed in previous studies. This difference may hamper its application outside the academic setting. This paper presents comparisons between different definitions for a variety of manufacturing processes. The objectives are to determine the applicability of each definition for specific processes and to demonstrate why more robust definitions still require development. Keywords: Exergy Analysis; Resource Efficient Manufacturing; Discrete Manufacturing Processes

1

INTRODUCTION

Manufacturing activities require input resources, such as energy and raw materials, to produce products, waste and emissions as output. In terms of energy consumption, worldwide industrial sector consumed approximately 98 exajoules (EJ) of energy in 2008. This accounts for 28% of world energy consumption [1]. A representative situation prevails in Europe where 13.5 EJ out of the 48.5 EJ total energy consumption is used by industry. Gas and electricity are the two most common energy sources utilized, each of them accounts for 31% of the total European industrial energy consumption. On the output side, the European manufacturing industry is responsible for 364 million tonnes (Mt) of waste within the 2953 Mt total generated [2]. The industrial sector was also the second major contributor to global green house gasses emissions [3]. Both the input and output of manufacturing have impacts on the environment. Reducing the negative impacts of manufacturing processes has become one of the main concerns of manufacturing companies due to several driving forces, such as more stringent government regulations, increasing energy and resource costs, and increasing public awareness of sustainability issues. Therefore, both consuming resources as efficiently as possible and producing minimum waste and emissions are essential.

ings by means of reversible processes, involving interaction only with the abovementioned components of nature”. Unlike energy, exergy is not conserved; thus, exergy can be destructed in a system. In-depth discussion on the development and application of the exergy concept in general can be found in [4, 5, 6]. One of the early studies on the implementation of an exergy analysis in discrete manufacturing process was conducted by Creyts and Carey [7]. They utilized the exergy analysis to evaluate the environmental performance of machining processes. In a more recent study, Gutowski et al. [8] have developed a thermodynamic framework to analyze a generic manufacturing process. They also calculated the exergy efficiency of different manufacturing processes. On a manufacturing system level, Saiganesh and Sekulic [9] applied the exergy analysis for a production line of printed circuit boards. Comparison of resource consumption between two manufacturing methods by means of exergy analysis and Life Cycle Assessment was conducted by Medyna et al. [10].

In order to minimize environmental impact of a manufacturing process, first the process input and output should be quantified. Given all the variety of input and output, and also different kinds of sustainability objectives, the number of metrics required to fully quantify the process can be quite excessive. Among different available approaches, the original application of thermodynamic metrics for manufacturing processes has been under development throughout the last decade.

Similar to exergy analysis in power generation and process industry systems, the exergy analysis in a manufacturing system aims to detect and evaluate thermodynamic imperfection and indicate possibilities for improvement. The exergy efficiency is an important parameter in achieving these objectives. In the aforementioned studies, different definitions of exergy efficiency metrics were employed. Although the studies confirmed that exergy analysis can be used to determine resource efficiency in manufacturing processes, this difference in definitions may lead to confusion and hamper its application outside the academic research setting. In [8] and [9], the authors realized that there are different definitions of exergy efficiency, but no examples were given to illustrate the difference between definitions.

The thermodynamic metrics are based on the second law of thermodynamics. Therefore, instead of just using the energy metric, the exergy value of both input and output streams is used to quantify them. Exergy is defined by Szargut et al. [4] as “the amount of work obtainable when some matter is brought to a state of thermodynamic equilibrium with the common components of the natural surround-

This paper presents comparisons between different exergy efficiency definitions for a variety of manufacturing processes. The objectives are to determine the applicability of each definition for specific processes and to show why more robust definitions still require development. In a broader scope, this study is part of the research effort in assessing energy and resource efficiency of manufacturing systems.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_57, © Springer-Verlag Berlin Heidelberg 2011

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330 2

Sustainability in Manufacturing - Methods and Tools for Energy Efficiency DEFINITIONS OF EXERGY EFFICIENCY

The different components of exergy in a system are shown in Figure 1. In its simplest form, the exergy balance of a system can be written as follows:

Bloss ,int  Bin  Bout

(1)

Here, Bin represents the sum of the exergy of all input streams, while Bout defines the output streams exergy. The internal exergy loss Bloss,int is exergy loss due to internal irreversibilities in the system. The exergy efficiency definition proposed by Grassman [12] is the ratio between the total exergy output and the total exergy input (2). This definition of efficiency was applied to a manufacturing system setting in [9].

 

Bout Bin

(2)

However, as shown by Sorin et al. [11], not all exergy output can be considered as useful output since there are external exergy losses included in the output. The external exergy losses Bloss,ext include heat losses, material waste and emissions. Thus, it is more appropriate to describe the efficiency as the ratio between the useful exergy output and the exergy input. This ratio is also known as the degree of perfection ηp [4].

p 

Bu Bin

virtually unmodified during the process. This can lead to an inflated value of degree of perfection. Sorin et al. [11] proposed a solution by differentiating between transiting exergy Btr and utilizable exergy Bpu, and defined the utilizable exergy coefficient ηu as the ratio between produced utilizable exergy and consumed exergy.

(3)

u 

B pu Bc



Bu  Btr ,u Bin  Btr ,in

(4)

It should be noted that the transiting exergy could exit the system in the useful output stream and/or in the losses stream. If there is no transiting exergy in the losses stream, then Btr,in = Btr,u. A similar problem occurs in the calculation of the degree of perfection for subtractive manufacturing processes. This is because the objective of a subtractive process is the removal of some material from the work piece. Therefore, part of the material input remains unmodified during the process. Branham and Gutowski [13] defined the efficiency of removal ηr to solve this problem (5). Here, the input exergy Bin* is defined as the exergy content of the material that is to be removed from the workpiece and any other necessary exergy input such as electricity and consumables.

r 

Bremoved Bin*

(5)

The application of all previously mentioned definitions of exergy efficiency to the analysis of different manufacturing processes is illustrated in the next section. The results of applying different efficiency definitions are compared and the applicability of each definition for process and manufacturing systems is discussed.

For certain processes, care should be taken in calculating the degree of perfection since it is possible for an input stream to be

Figure 1: Graphical representation of different types of exergy streams (adapted from [11]).

Sustainability in Manufacturing - Methods and Tools for Energy Efficiency 3

EXERGY ANALYSIS FOR DIFFERENT MANUFACTURING PROCESSES

Manufacturing processes can be broadly classified into three categories: subtractive processes (e.g. milling, turning, grinding), additive processes (e.g. joining, coating, sintering) and mass-conserving processes (e.g. forging, bending, rolling). In this work, exergy analysis is performed on three manufacturing processes, each representing one of these three categories: laser cutting, selective laser sintering and bending. The specific chemical exergy values utilized for the exergy analysis are taken from [4], unless stated otherwise. In this study, the analysis is focused on the process in a standalone machine. Auxiliary activities which are not part of the actual process are excluded from the analysis. An example of such activities is the direct recycling process of waste material or consumables. 3.1

Subtractive process: laser cutting

The investigated laser cutting process is performed on a high power (5kW) conventional CO2 laser cutting machine tool for sheet metal cutting operations [14]. In this example, the laser cutting is employed to cut a 1 mm thick S235JR steel sheet with 1.6 m cutting length. The exergy analysis of the laser cutting process is summarized in Table 1. On the input side, the laser cutting process requires steel sheet as the work piece material, nitrogen as the processing gas and electricity as the energy source. The output streams constitute the product, removed material, waste material and a relatively small amount of air emissions. input

mass (kg)

specific chemical exergy (kJ/kg)

Steel sheet

0,247

6750

1667,25

Nitrogen

0,073

25,7

1,87

Electricity

exergy (kJ)

total exergy input (kJ) 2453,93

mass (kg)

exergy (kJ)

total exergy output (kJ)

Product

0,185

6750

1248,75

1667,25

Cut steel

0,00624

6750

42,12

Waste steel

0,05576

6750

376,38

NO

3,22e-08

2963,33

0,000095

NO2

4,06e-08

1208,7

0,000049

Table 1: Exergy analysis of the laser cutting process. Figure 2 shows the values of different exergy efficiency definitions for the laser cutting process. It can be seen that different efficiencies have a significant discrepancy between them. The inclusion of external exergy losses, in this case the waste steel and air emissions, in the output exergy Bout causes a relatively higher value of ηε. The external exergy losses are omitted from the nominator Bu in the calculation of ηp, resulting in a lower ηp value compared to ηε. An even lower value is reached by ηr because only the exergy of the removed material, instead of the exergy of the whole work piece material, is considered in this efficiency. 3.2

total production time is 901 minutes. This case study is based on the work of Kellens et al. [15]. The summary of exergy analysis of the SLS process is given in Table 2. The specific chemical exergy value of PA2200 is based on Nylon 6 [16]. In SLS, the input stream consists of the working material, electricity and compressed air. The compressed air is fed into nitrogen generators inside the machine to produce nitrogen gas. The nitrogen is utilized to create an inert atmosphere inside the process chamber. The products and waste material are the output of the SLS process. The efficiencies of the SLS process are shown in Figure 2. The value of ηε differs significantly from ηp because of the relatively high amount of waste material, i.e. 86% of the input material, which is not being taken into account as a useful output in calculating ηp. By regarding the exergy of the un-sintered material as transiting exergy, ηu shows a higher value than ηp. In SLS, the transiting exergy exits the system in the losses stream since in this analysis, the unsintered material is considered as waste material. This makes the denominator in ηp larger than the one in ηu, while the nominator is identical in both variables; hence a higher value of ηu. input PA 2200 Compressed air Electricity output Product Waste material

mass (kg)

specific chemical exergy (kJ/kg)

exergy (kJ)

total exergy input (kJ)

23,87

33000

787710

1280910

408

150

61200 432000

mass (kg)

specific chemical exergy (kJ/kg)

exergy (kJ)

total exergy output (kJ)

3,33

33000

109890

787710

20,54

33000

677820

Table 2: Exergy analysis of the SLS process.

784,8 specific chemical exergy (kJ/kg)

output

331

Additive process: selective laser sintering

The selective laser sintering (SLS) case study is performed by producing a sample batch of products. Fine Polyamide PA2200 is used as the working material with a layer thickness of 12 µm. The

3.3

Mass-conserving process: bending

In a bending process, a flat metal sheet is bent up to a certain bend angle. A hydraulic press brake is used in this example. Table 3 shows the results of the exergy analysis of the bending process. The product has the same exergy value as the material input since its thermodynamic properties remain unmodified and only its shape is changing during the process. input Steel sheet

mass (kg)

specific chemical exergy (kJ/kg)

exergy (kJ)

total exergy input (kJ)

0,185

6750

1248,75

1633,95

Electricity output Product

385,2 mass (kg)

specific chemical exergy (kJ/kg)

exergy (kJ)

total exergy output (kJ)

0,185

6750

1248,75

1248,75

Table 3: Exergy analysis of the bending process. The efficiencies of the bending process are illustrated in Figure 2. Both ηε and ηp have the same value because there is only one output from the bending process. One might argue that there are other outputs such as heat emissions, but the significance of these emissions is negligible in comparison to the material output. As an illustration, the theoretical heat emission of the bending process is five orders of magnitude lower than the product exergy. In calculat-

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Sustainability in Manufacturing - Methods and Tools for Energy Efficiency

ing ηu, the whole work piece can arguably be considered as transiting exergy because the exergy of the work piece does not change during the process, i.e. no mass subtraction or addition. Therefore, ηu of this process is zero.

100

ηε

90

ηp

80

ηr

70

ηu

Another option in defining the thermodynamic efficiency of a manufacturing process, which is not shown in the previous section, is the isentropic efficiency. It is defined as the ratio between the minimum theoretical energy and the real required energy needed to perform a process. The problem with this definition is that there are several ways to define the minimum theoretical energy, as demonstrated in [17]. Moreover, the theoretical nature of isentropic efficiency renders it less useful in determining inefficiency and improvement potential in practical situations.

50 40 30 20 10

4.2

0 Laser Cutting

SLS

Bending

Figure 2: Exergy efficiencies of different manufacturing processes. 4

DISCUSSION

Different definitions of exergy efficiency have been applied to three representative manufacturing processes. For a given process, the differences in value between definitions can be quite significant. This difference in efficiency definitions could lead to difficulty in using exergy analysis in a manufacturing system setting. As an example, if ηε or ηp is used to compare the performance of the given laser cutting and SLS process, it can be concluded from Figure 2 that laser cutting is more resource efficient. However, if ηr and ηu are utilized, then SLS is the more efficient one. In deciding on which definition to use, the characteristics of each definition have to be considered thoroughly. 4.1

As the first example, the effect of nesting efficiency on exergy efficiency of laser cutting process is presented. The nesting efficiency itself can be considered as part of process planning. From resource utilization point of view, a higher nesting efficiency is desirable for the laser cutting process. Figure 3 depicts the exergy efficiency of the laser cutting process with three nesting efficiency values. The laser cutting process described in the previous section has 75% nesting efficiency.

100

Both ηr and ηu are necessary improvements over ηp in subtractive and additive processes, respectively. These definitions are able to overcome the transiting exergy issue which persists in the definition of ηp. Care should be taken when calculating ηr for subtractive process since the term “removed material” could become a source of confusion. For example, in a laser cutting process, the removed material is represented by the material in the cutting kerf, not the remainder of the sheet metal. In this case, the excess sheet metal is considered as the transiting exergy in the loss stream. On the contrary, for another subtractive process, such as sheet metal shearing, there is practically no cutting kerf. From this example, it is clear that the robustness of the current definition of ηr needs to be improved.

75%

90

85%

80

Process level consideration

The fact that not all output is useful makes the usage of ηε to determine resource efficiency inappropriate. Quantifying all the output is another problem in using ηε since not all output can be easily measured. For example, heat emission is clearly present during the laser cutting and selective laser sintering process, but its quantification is not as straightforward as the other output. Nonetheless, ηε could be useful in illustrating the internal irreversibility of a process. This can be the case if it is desirable to compare internal exergy losses of two machines performing exactly the same process.

System level consideration

Inclusion of system level variables is necessary if exergy analysis is utilized to determine the resource efficiency of a manufacturing system. Exergy analyses in the previous section are focused solely on the process itself. Here, brief examples are given to illustrate the applicability of exergy efficiency definitions if system level variables are taken into account.

95%

70 60

%

%

60

All definitions have difficulty in properly determining the performance of the mass-conserving process. Since both ηε and ηp include the effect of transiting exergy in their calculation, their value can be falsely inflated in a mass conserving process. For example, the value of ηε and ηp for exactly the same bending process would be higher for larger workpiece although it has the same bend length, thickness and material as the smaller workpiece. As for ηu, the nature of the mass-conserving process makes it difficult to determine the produced useful exergy output of the process since the macroscopic thermodynamic properties of the workpiece is virtually unchanged. This peculiarity also holds for most massconserving processes.

50 40 30 20 10 0 ηε ηε

ηp ηp

ηr ηr

Figure 3: Exergy efficiency of laser cutting process with three different nesting efficiencies. One of the interesting points is the decrease of ηε with nesting efficiency. This is because both the total exergy input and output are lower for a higher nesting efficiency. On the other hand, ηp is

Sustainability in Manufacturing - Methods and Tools for Energy Efficiency increasing with the nesting efficiency since the total exergy input is decreasing, while the produced useful exergy output is constant. The value of ηr does not change with the nesting efficiency because in this study, the amount of removed material is unchanged for different nesting efficiency, i.e. higher nesting efficiency is manifested in reduced material input. The constant value of ηr for different nesting efficiency shows that this definition is less suitable for describing resource efficiency in system level environment since higher nesting efficiency means higher resource efficiency. For the second example, the exergy analysis for SLS is performed while taking into account the direct material recycling activity. According to [15], approximately 50% of the non-processed material in the SLS output can be recycled; thus, reducing the amount of new material input. Despite of this, the values of all efficiency definitions are constant because the recycling only reduces the transiting exergy in the losses stream Btr,loss, while other exergy streams remain unchanged. This demonstrates that, similar with the relation of ηr and nesting efficiency in laser cutting process, all efficiency definitions have limited capability to describe the increased resource efficiency effect of direct material recycling in the SLS process. From these examples, it is clear that both ηr and ηu are less qualified for assessing resource efficiency if system-level variables are taken into account. This stems from the fact that both definitions are conceived with transiting exergy independence in mind. Therefore, both are specifically process oriented metrics, while at system level, parameters such as materials allocation and process planning also play a significant role in determining resource efficiency. In contrast, the first example suggests that ηp has a better capability in describing system-level resource efficiency, although its application at process level is problematic. Thus, it is very likely that process level exergy efficiency definitions could not be directly translated to a system level. Even though further investigation is needed to substantiate this preliminary indication, it is in accord with the notion of dependency between the appropriate way of applying exergy analysis and the size of the application [18]. 5

SUMMARY

efficiency metrics with manufacturing systems resource efficiency in perspective. 6

At system level analysis, it is shown that process level exergy efficiency definitions could not capture the increase in resource efficiency resulting from system level measures. This indicates that system level efficiency definitions are not supposed to be a direct translation from the process level ones. The authors agree that there is no single rigid definition of exergy efficiency for all manufacturing processes; as the huge variety of discrete manufacturing processes makes it very difficult, if not impossible, to derive such a definition. Nevertheless, clear and robust definitions of exergy efficiency are still required to achieve the objective of exergy analysis in manufacturing systems; otherwise a misleading conclusion might be drawn due to incomparable magnitude of efficiencies between sub-systems. With the results of this study in mind, future work includes the development of exergy

ACKNOWLEDGEMENTS

The authors acknowledge the support of the European Fund for Regional Development (EFRO - Europees Fonds voor Regionale Ontwikkeling) and the Agentschap Ondernemen (Flemish government) through the D2 project 476 and of the Institute for the Promotion of Innovation through Science and Technology in Flanders (IWT-Vlaanderen) through its PhD grant N°091232. 7

REFERENCES

[1]

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[2]

Eurostat (2009): Energy transport and environment Indicators, 2009 edition, European Union.

[3]

Intergovernmental Panel on Climate Change (2007): Climate Change 2007: Synthesis Report.

[4]

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[5]

Bejan, A. (1997): Advanced Engineering Thermodynamics, Second Edition, John Wiley & Sons, New York.

[6]

Dincer, I., Rosen, M.A. (2007): Exergy: Energy, Environment and Sustainable Development, Elsevier, Burlington, MA.

[7]

Creyts, J., Carey, V. (1999): Use of extended exergy analysis to evaluate the environmental performance of machining processes, in: Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, Vol. 213, pp. 247-264.

[8]

Gutowski, T.G., Branham, M.S., Dahmus, J.B., Jones, A.J., Thiriez, A., Sekulic, D.P. (2009): Thermodynamic Analysis of Resources Used in Manufacturing Processes, in: Environmental Science & Technology, Vol. 43, No. 5, pp. 1584-1590.

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Saiganesh, S., Sekulic, D.P. (2010): Balancing Material and Exergy Flows for a PCB Soldering Process: Method and a Case Study, in: Proceedings of the 2010 IEEE International Symposium on Sustainable Systems and Technology, pp. 16, Arlington, VA, USA.

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Medyna, G., Nordlund, H., Coatanea, E. (2009): Study of an exergy method for environmental evaluation assessment in the early design phase using comparative LCA and exergy approach, in: International Journal of Design Engineering, Vol. 2, No. 3, pp. 320-345.

[11]

Sorin, M., Lambert, J., Paris, J. (1998): Exergy Flows Analysis in Chemical Reactors, in: Trans IChemE, Vol. 76, Part A, pp. 389-395.

[12]

Grassmann, P. (1950): Zur allgemeinen definition des wirkungsgrades, in: Chem Ing Technik, Vol. 4, pp. 77-80.

[13]

Branham, M.S., Gutowski, T.G. (2010): Deconstructing Energy Use in Microelectronics Manufacturing: An Experimental Case Study of a MEMS Fabrication Facility, in: Environmental Science & Technology, Vol. 44, No. 11, pp. 4295-4301.

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Duflou, J.R., Kellens, K., Devoldere, T., Deprez, W., Dewulf, W. (2010): Energy related environmental impact reduction opportunities in machine design: case study of a laser cutting machine, in: International Journal of Sustainable Manufacturing, Vol. 2, No. 1, pp. 80-98.

This work describes the differences in exergy efficiency definitions for a variety of discrete manufacturing processes. Unlike in typical energy conversion devices, the definition of exergy efficiency for a manufacturing process is not always straightforward. The exergy efficiencies ηr and ηu are able to appropriately present the resource efficiency of subtractive and additive processes, respectively. However, the definition of ηr is still unclear for specific cases. In the mass-conserving process category, another definition of exergy efficiency needs to be developed since the current definitions have limited significance in depicting the resource efficiency of the corresponding process.

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[15]

Kellens, K., Dewulf, W., Deprez, W., Yasa, E., Duflou, J.R. (2010): Environmental analysis of SLM and SLS manufacturing processes, in: Proceedings of the 17th CIRP International Conference on Life Cycle Engineering (LCE2010), pp. 423428, Hefei, China.

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Dewulf, J., Van der Vorst, G., Kang, W., Van Langenhove, H. (2010): The efficiency of the manufacturing of chemical products through the overall industrial metabolism, in: Proceedings of the 23rd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ecos2010), Lausanne, Switzerland.

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Branham, M., Gutowski, T.G., Jones, A., Sekulic, D.P. (2008): A Thermodynamic Framework for Analyzing and Improving Manufacturing Processes, in: Proceedings of 2008 IEEE International Symposium on Electronics and the Environment, San Francisco, USA.

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Rosen, M.A. (2008): Size considerations in applications of exergy analysis, in: International Journal of Exergy, Vol. 5, No. 3, pp. 249-274.

State of Research and an innovative Approach for simulating Energy Flows of Manufacturing Systems 1,3

1,3

Sebastian Thiede , Christoph Herrmann , Sami Kara 1

2,3

Institute of Machine Tools and Production Technology, Technische Universität Braunschweig, Germany

2

Life Cycle Engineering and Management Research Group, The University of New South Wales, Sydney, Australia. 3

Joint German-Australian Research Group Sustainable Manufacturing and Life Cycle Management

Abstract The paper addresses the issue of energy efficiency as an important topic in sustainability in manufacturing. Against the background of a necessary holistic system understanding and derived research demand, an innovative energy flow oriented manufacturing system simulation approach is presented. Besides the description of the conceptual approach, the applicability and the potentials of usage are shown in two different case studies. Keywords: Energy Efficiency; Sustainable Manufacturing; Production Management

1

INTRODUCTION

Due to its growing economic relevance and the related environmental impact, energy consumption is a major issue in both politics and companies nowadays. In very general, “energy is the capacity to do work” (e.g. [1]) so it is necessary to execute any kind of designated tasks. With mechanical, thermal, chemical, electric, electromagnetic and nuclear energy different forms of energy can be distinguished (e.g. [2]). Conversion is basically possible and also necessary to enable the usability of naturally available primary energy carriers like coal, oil or gas in industrial practice. However, practically this is always connected with certain losses. As an example of primary energy consumption and conversion processes Figure 1 shows an energy flow diagram for the case of Scotland which is basically quite similar for most industrialized countries.

Figure 1: Energy flow Sankey diagram for Scotland (in TWh) [3]. On a national scale, industry is one of the major consumers of natural gas as primary energy carrier, e.g. in Germany the share is 36% compared to Scotland with approx. 28% (of direct used gas) [3] [4]. Additionally, industry consumes major share of electricity which is a secondary energy carrier and is produced using primary sources including significant losses. In Germany, industry is

responsible for the consumption of 47% of the national electricity [4]. Within companies further conversions take place in order to generate the actual usable form of energy to fulfil the working task. Altogether the most typical energy conversions are from gas to process heat (e.g. generation of steam) and from electricity to mechanical energy (e.g. electric drives or generation of compressed air) [5]. As mentioned, energy consumption has a very strong relevance from both economic as well as environmental perspective. Thereby the pure energetic view as shown in Figure 1 is certainly just one perspective; whereas striving towards sustainability in manufacturing demands a more detailed analysis of connected economic as well as environmental impacts (here depicted with related CO2 emissions). Therefore (based on the data from [5]) Figure 2 shows the estimated energy costs and CO2 emissions for the German manufacturing industry for the main energy sources. The calculation is based on the average energy prices for the considered years and the emitted CO2 for generating electricity (energy source mix for Germany) or directly burning oil, gas or coal. The calculations underline the major importance of considering electricity in comparison to primary energy sources (due to upstream chain). Only through its electricity consumption, industry is responsible for approx. 18% of CO2 emissions (plus approx. 20% through direct industrial emissions) in Germany [4]. Additionally energy supply in general is naturally connected with the depletion of diverse non-renewable resources (e.g. oil, gas, coal). As a result, based on currently known securely mineable deposits and demand, the statically estimated supply range is approx. 40-60 years for oil and gas respectively [4]. Besides, the calculation also stresses the very strong economic relevance of industrial energy consumption. Energy prices for electricity, gas and oil are steadily increasing for the last couple of years [4]. As shown in Figure 2, energy costs for producing companies has been more than doubled from the year 2000 to 2008. Against the background of these urging environmental as well as economic challenges, increasing the efficiency in using energy has become a major strategy. Different studies reveal the significant

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_58, © Springer-Verlag Berlin Heidelberg 2011

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Sustainability in Manufacturing - Methods and Tools for Energy Efficiency

improvement potential within industry. The study of “Energy Efficiency in Manufacturing” prepared by Fraunhofer Gesellschaft underlines the relevance of production processes in single companies as well as on a global base and highlights the major potential of increased production process efficiency to optimize the environmental as well as economic performance [6]. The study “Energy Efficiency in Manufacturing: The Role of ICT” highlights the s saving potentials of 10-40% in manufacturing and stresses the importance of ICT (Information and Communication Technologies) as enabler for energy efficiency [7]. A comprehensive study for the case of Germany reveals similar significant potentials in the manufacturing industry regarding e.g. the efficient usage of energy [5]. Altogether, depending on the field of action a saving potential of 10-30% of energy consumption was identified based on the technology which was available in 2002. From today´s perspective the potential is likely to be even higher.

electricity gas oil coal total

energy consumption [in PJ] 819,1 973,7 231,2 407,8 2431,8

energy costs (2000) [in €] 10.012.650.793 € 4.577.253.331 € 10.558.553 € 586.200.977 € 15.186.663.655 €

energy costs (2008) [in €] 20.073.221.336 € 9.094.440.438 € 22.046.590 € 1.566.545.164 € 30.756.253.528 €

related CO2 emissions [in t] 130.933.135 38.745.623 10.395.556 37.185.949 217.260.264

machines which execute or support the actual value creating processes directly need energy (typically electricity) to fulfil their designated processes. However they also need diverse other energy forms/media like compressed air, steam or cooling water which are provided by technical building services (TBS). Another task of technical building services is to ensure the needed production conditions in terms of temperature, moisture and purity through cooling/heating and conditioning of the air. The essential influencing variables are the local climate at the production site (e.g. seasonal influences) and also the exhaust air and waste heat that is primarily emitted by production machines or personnel. Altogether, besides direct energy consumption through production equipment, TBS need further energy to fulfil their tasks and enable factory operation. Referring to a study of the European Union, this consumption counts for a major part of the industry energy consumption [9]. Additionally high potentials for energy related improvement in that field were identified [5]. local climate

coal 17%

80%

oil

gas 5%

e.g. gas, oil, electricity

electricity 17%

raw materials

technical building services (TBS)

40%

production environment

exhaust air, waste heat

energy/media e.g. comp. air, steam, electricity

Process/ Machine 1

30% 18%

60%

cooling heating

energy

120% 100%

e.g. temperature, humidity, radiation

FACTORY BUILDING

Process/ Machine n

products scrap, waste

auxiliaries

by-products

e.g. coolants

40% 65% 20%

60%

34%

raw materials energy/media

0%

MACHINE

products

process 12

kW

consumption in PJ

cost perspective (2008)

CO2 emissions

Figure 2: Estimation of costs and CO2 emission related to energy (based on consumption data from 2002 from [5], in Petajoule). Against this background an approach to foster energy efficiency in manufacturing companies is required. Hereby energy efficiency is the ratio of the production output (e.g. in terms of quantities with defined quality) to the total energy input (e.g. electricity, gas, oil) for the operation of the whole factory system. Considering the mentioned opportunities and the relevance of different energy input flows it becomes clear that there is a need for appropriate methods and tools incorporating a holistic perspective on all energy sources and forms to identify and tab the most worthwhile potentials for the individual company case. However energy is just one of several inputs for a production process and minimizing energy consumption is just one of the target objectives of a company (besides e.g. material and personnel costs, production time, quality). While different measures may also cause conflicts of goals an appropriate approach shall be able to consider these different perspectives. 2 2.1

THEORETICAL BACKGROUND System definition

The consideration of all relevant energy flows necessarily requires a holistic factory definition with three partial systems: the production system itself (with machines and controlled through production management), the technical building services (TBS) and the building shell (Figure 3) [8]. These partial systems interact as a complex control system with dynamic interdependencies between different internal and external influencing variables. Production

auxiliaries

by-products S120 Innenrundschleifen Werkzeug: CBN Werkstück: 100Cr6 (62HRC)

10

Q'w = 1,5 mm³mm -1s-1 V'w = 200 mm³mm-1 vc = 60 ms-1

8

scrap/waste

6

personnel

4

heat

2 0

information

0

50

100

150

200

250

300

e.g. power demand of grinding process

information

Figure 3: Holistic system definition on energy consumption of manufacturing systems [8]. A typical example for internal energy flows involving TBS is the generation of compressed air. Because of its advantages compressed air is broadly used in manufacturing companies for different purposes. It is basically a conversion of electrical energy to mechanical energy. Altogether about 10% of total industrial electricity consumption is caused by generation of compressed air (which means 80 TWh or 55 million tons CO2) [10]. As one big disadvantage compressed air usage is often connected with very high system losses. Studies show that less than10% of the input energy ends up as an actual usable mechanical energy. As a result compressed air is actually one of the most expensive forms of energy in industry [11]. Studies reveal that saving opportunities are not used yet; potentials are estimated with 5-50% (average approx. 33%) for the next 15 years [10]. 2.2

General requirements and solution approach

Against the background of the previous explanations some general requirements can be derived which have to be addressed when considering energy and resource efficiency in manufacturing (e.g. [12] [13]): Extended process and holistic factory system definition: In order to avoid focusing on minor relevant issues (while neglecting major challenges) and local optimization with problem shifting, all

Sustainability in Manufacturing - Methods and Tools for Energy Efficiency relevant input- and output flows of production processes must be explicitly considered. This includes all energy (e.g. compressed air, electrical power, waste heat) and material (e.g. auxiliary materials as cooling lubricants) flows, which lead either directly or indirectly to additional energy and/or resource consumption Consequently applying these concepts to a whole factory leads to the holistic factory definition as shown above – including the consideration of manifold interdependencies between the constituting elements Dynamics of consumption-/emission behaviour and reciprocal effects: All relevant input- and output flows are typically not static values but highly dynamic depending on the operating conditions of the processes and the machines. As measurements clearly underline, the usage of nominal values is not sufficient while they do not reflect the magnitude and the dynamics of actual consumption. Consumption and emission profile of single machines add up to cumulative load profiles on the factory level. In the end these dynamic cumulative load profiles (e.g. process heat demand, compressed air demand, heat flow into the factory building, electrical power demand) are decisive for design and control of the technical equipments (e.g. dimensioning of compressed air system) as well as for billing (e.g. energy supplier).

not support those considerations yet. The following section will analyze the state of research work in order to identify necessary research demand. For the matter of this analysis a deep review of relevant books and research papers, not only in the field of (e.g. manufacturing) engineering but also adjacent disciplines (e.g. operations research, computer science), was conducted. The analysis focuses on discrete-event multi-machine production system simulation with application to environmental aspects. In total twelve relevant research approaches were identified and considered. Authors included in the investigation are: Heilala et al., Rahimifard et al., Solding et al., Weinert et al., Junge, Hesselbach et al., Hornberger et al., Löfgren, Johannsson et al., Dietmair/Verl, Wohlgemuth et al., and Siemens AG (e.g. [13]-[23]). The following criteria were identified based on the system definition and requirements as stated above, as well as practical issues related to the application:  

Thinking in process chains: final products are usually not the result of a single production processes, but are rather manufactured in several steps on different production lines in the sense of production process chains. Against the background of energy- and resource efficiency, the process chain has to be regarded and evaluated as a whole, as it may involve further potentials (e.g. combination of processes). Moreover, problem shifting might occur while improving measures in one process can possibly lead to worse performance of others.



Life-cycle-oriented perspective: Analogous to the thinking in process chains, all life cycle phases of products (this includes also all the technical equipment within the factory itself) have to be considered when it comes to deriving measures concerning the energy and resource efficiency. Thus, the decisive factor for increasing the energy efficiency of a machine tool, for instance, is not the improvement of single parameters of a specific process, rather the development of the machine itself. Moreover, the choice of a specific process (e.g. joining techniques) has direct effects on the use- and disposal phase which could lead to increased efforts in those phases.



Integrated evaluation: In order to deduce advantageous solutions, several relevant target dimensions must to be considered simultaneously. Besides an ecological evaluation (with a correct balance of the different input- and output parameters, e.g. environmental effects of electricity- and gas consumption), this includes a realistic economic (on the basis of a suitable cost model which integrates real contract conditions) and technical evaluation (e.g. effects on product quality). Possible conflicts of goals must be disclosed and decision support to their solution must be offered. Analysing these requirements reveals that simulation is a promising approach. Discrete event simulation is an established method to analyse and improve manufacturing systems. With an extension towards energy consumption a realistic consideration of time based energy consumption behaviour and energy efficiency measures on system level would be possible. 3



 

  



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completeness of energy and resource flows (ideal: all internal and external energy flows of manufacturing companies) realistic representation of consumption dynamics on machine and factory system level (ideal: cumulative load profiles for all energy flows) interdependencies with technical building services (ideal: interactions of all TBS subsystems considered) focused fields of action for improvement: technological measures/organisational measures (ideal: full range of levers for improvement in one solution) possibility of actual optimization studies (ideal: optimization can be used which was already proved in case studies) scale and scope of technical/ economic/ ecological evaluation (ideal: realistic full cost calculation scheme, automated LCA, wide range of technical performance criteria considered) provision of actual decision support (ideal: appropriate methods for integrated evaluation are provided) consideration of uncertainty (ideal: appropriate methods are provided and their applicability proved) transferability to different cases and industries (ideal: wide range of production situations can be depicted) modelling and simulation effort in terms of time, costs and necessary expertise (ideal: simulation study can be conducted with low additional effort from non-simulation experts) appropriate visualisation of material/energy flows and results (ideal: all key figures and relevant diagrams shall be provided automatically and continuously during runtime) embedment within application cycle (ideal: comprehensive application cycle is provided ensuring goal-oriented modelling and systematic derivation of improvement measures)

Each single research approach was evaluated with respect the different criteria using a specific four-step scheme (fulfilment of 25%, 50%, 75% and 100% with certain thresholds for each step). Based on these investigations, Figure 4 shows the average value (over all 12 considered approaches) for each criterion as well as over all criteria (dashed vertical line). Additionally the range is depicted as average of the six highest and lowest values in each category. Based on this analysis several findings can be observed: 

Having in mind that 1.0 (100%) is the maximum and ideal value of each criterion it becomes clear that there is a significant room for improvement in all areas towards the vision of a comprehensive integration of energy and resource flows into simulation based planning procedures.



Some approaches fulfil certain criteria quite well – however they involve significant drawbacks in other areas. There is no approach with balanced and high fulfilment of all criteria.



Criteria completeness (of energy and resource flows) and dynamics are fulfilled higher than the average (still at relatively

STATE OF RESEARCH AND RESEARCH DEMAND

Whereas discrete event manufacturing system simulation augmented with relevant energy flows was identified as promising approach the question arises whether certain solutions are already available. A review of commercially available manufacturing simulation tools (e.g. Plant Simulation, Delmia) reveals that they do

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Sustainability in Manufacturing - Methods and Tools for Energy Efficiency low level though). Typically technical variables are considered for evaluation, often in combination with other economic and/or ecological variables. Also the criterion visualisation is fulfilled above average.

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Figure 4: Evaluation results for state of research. 4

SIMULATION CONCEPT

After the evaluation of the previous work [24], a new concept of the proposed energy flow oriented simulation approach has been developed and depicted in Figure 5. As illustrated, it is not a specific simulation model - based on the simulation tool AnyLogic it is rather a modular simulation environment which allows the flexible modelling of any manufacturing process chain or factory as a whole. II

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Figure 5: Conceptual structure of energy flow oriented manufacturing system simulation. Four main modules can be distinguished which dynamically interact through defined interfaces. These modules are: Process Module(s): Process modules are core elements for modelling of the actual production machines and processes. A process module is quite generic and can be parameterized in detail in order to achieve a sufficiently realistic model of a specific machine. Machine behaviour is depicted with state charts – each operating state has a definable duration (e.g. based on certain time

or trigger events) and is connected with a certain consumption of a resource (described as value or equation, e.g. depending on process parameters). Thus, with this technique the dynamic consumption behaviour of (e.g. all forms of energy), any (auxiliary) materials or even emissions can be modelled. TBS Module(s): TBS-related energy demand of the actual production equipment (e.g. compressed air) serves as input for appropriate partial TBS-models (e.g. for generation of compressed air). Herewith additional energy consumption (e.g. electricity needed to generate compressed air) of TBS is calculated based on detailed equation-based sub models. Additionally TBS models simulate the possible supply with energy or media – interacting with the production system, a lack of e.g. compressed air (air pressure to low) leads to failures of production machines. Evaluation and Visualization Module: the total energy demand of the production site as a sum of consumption of production itself and TBS (standard resolution of 1 second) is passed to the evaluation and visualisation module. Based on specific contract models (e.g. including peak costs and different fees in the case of electricity) and environmental background data the actual economic and environmental impact of energy and resource consumption are calculated. Production performance variables are also being considered, e.g. in order to calculate key figure like the energy efficiency (as ratio of output and energy input) of the system. Additionally an interface to E!Sankey® (developed by IFU Hamburg GmbH, www.e-sankey.com) was established which allows a dynamic visualisation of energy flows in the factory with Sankey diagrams in order to provide decision support. Production Planning and Control (PPC) Module: Production planning and control capabilities are also embedded which allow detailed configuration of capacity planning/machine allocation or lot sizes for several individual products/orders process chains . They can also run through the production simultaneously. Through combination and parameterization of different modules any process chain or whole factory can be modelled. Thereby it is also important to mention that this is also true for flexible production systems without rigid coupling of machines (which typically requires significant effort in common simulation tools). The modelling of the production system structure and the specific parameterization can be done relatively fast and without extensive knowledge of manufacturing system simulation. Furthermore, through interfaces to common tools like MS Excel, those activities can be done totally separated from the actual simulation environment. In this case just starting the simulation run is necessary in the actual simulation tool. The proposed energy flow oriented manufacturing system simulation approach consequently focuses on the requirements given by the holistic factory system definition as shown above as well as resulting criteria. Compared to the current state of the research many advances can be pointed out: All relevant internal and external energy flows can be considered with their time based behaviour and interdependencies. Diverse field of actions can be addressed in order to derive and evaluate measures for increasing the energy and resource efficiency (e.g. evaluation of single machines or TBS measures on factory level, strategies for improved planning and control of process chains). Different dimensions of evaluation are being considered in detail simultaneously, actual decision support is given (e.g. illustration of consumption drivers) and also the issue of uncertainty can be addressed. Finally, the modular structure allows broad applicability. The possibility to depict flexible production structures of diverse scale and scope as well as the easy usability also addresses specific needs of SME (small and medium sized enterprises).

Sustainability in Manufacturing - Methods and Tools for Energy Efficiency 5

CASE STUDIES

Finally two quite different case studies (in terms of production structure and management) shall give an impression about the broad applicability and potentials of the developed approach. 5.1

Weaving mill

The first case study (in parts already introduced in [25]) considers a company running a large scale weaving mill to produce technical textiles which are being used for industrial purposes (e.g. supporting material for abrasive papers, printing industry). The factory of the weaving mill basically consists of a total of 41 weaving machines based on four different basic machines types operating independently (no linkage, every machine with own production program) and almost continuously in a three shift system. In context of energy, each machine needs electricity but also a significant amount of compressed air for operation. In reality the electricity needed for compressed air generation for the weaving mill is even higher than the direct electricity consumption of the machines itself. Actual time based values with respect to different speeds were measured for all machine types and could be transferred to equation based consumption models (Figure 6).

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an interaction of TBS with production system itself, this also includes the failure of weaving machines if the pressure is too low for operation. One can see that those considerations allow a convergence towards optimal compressor system setup while ensuring full production performance to improve total energy efficiency. Finally, Figure 6 also shows visualization in E!Sankey® on a factory layer. This Sankey diagram is automatically generated and provides a clear picture on energy inputs and outputs of the factory. 5.2

Printed circuit board assembly (SME company)

The second case study considers a SME company which assembles printed circuit boards in a very flexible production environment (no coupling of machines, free flow of orders). As previous analyses showed the total energy consumption of the company is mainly determined by few large processes (e.g. reflow oven, solder waves, compressor) partly with distinctive heating periods before operation. Those consumers and further machines (with smaller energy consumption) which are relevant to depict the logic of the process chains were modeled with the energy flow manufacturing simulation approach and measured consumption patterns were integrated. A typical production program with different products/orders differing in process chain structure (involved machines, sequences, lot sizes) was also applied. Figure 7 shows the simulated total electrical power demand (direct consumption and compressed air induced, here as 15min interval) for a whole production day. 70 60

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Figure 6: Procedure and fields of action for simulation based improvement of energy efficiency in weaving mill. The weaving mill with all machines as well as the very sophisticated compressor park (actual dimensions and control of each compressor) was modeled with the proposed energy flow simulation environment and the consumption models for compressed air and electricity were embedded. The validation showed that significant accuracy could be achieved. Although the production program planning has obviously just minor impact in continuous production, two fields of action were identified. As first option, Figure 6 shows the influence of changing operation speed on total energy consumption (direct plus compressed air induced), energy costs and production output. The diagram sensitizes that operation at lower speed might save a significant amount on electricity (spread of >30%) which means a couple of thousand Euro per month on related costs in three shift production. While certainly being no strategy in times of economic upturn (due to less output) this could be a useful strategy for low utilization phases. The second field of action is the dimensioning and control of the compressor park itself. As an example, Figure 5 (step 2) shows the influence of typical parameters like nominal air pressure and system volume (e.g. buffer tank size) on the energy efficiency of the whole system. As

S1 (Base Run)

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max. electrical power [kW]

electricity consumption [kWh]

electricity costs [€/month]

time per piece [sec]

Figure 7: Simulation results for second case study - daily load profile for electrical power for different scenarios (15min interval). S1 as base run depicts a typical case where all machines were just turned on at shift start (6am) for pre-heating and run the whole day (either in standby or operation mode) in order to guarantee ideal availability over the day. The load profile reveals the significant start-up peak and the quite constant consumption over the day on relatively high level (until shift end at 4pm). S2 shows the effect of a more energy conscious operation of the company while firstly turning machines on at the time when an order actually occurs. The results show that a significant decrease of maximum power and total electricity consumption can be achieved through this measure with just minor effect on production performance (through higher waiting times due to start-up/heating processes). S3 goes even further and reveals the effect of an (automatic or operator induced) shut-down after certain time of machine idleness (but just for machines where it is technically feasible). This results in even more savings on electricity consumption and related costs. Certainly,

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Sustainability in Manufacturing - Methods and Tools for Energy Efficiency

since this is just a sample day, the effect of these measures needs to be verified for different production scenarios and in industrial practice. However, the general potential looks like promising and the achievable order of magnitude encourages to actual application in the company. Since just selected scenarios were considered, through a more systematic design of measures even more saving potential seem to be possible for certain cases. 6

SUMMARY AND OUTLOOK

Based on the necessary holistic factory system definition towards energy and resource efficiency and against the background of the urging research demand in that field, the paper presents an innovative energy flow oriented manufacturing simulation approach. The concept was described and the advances in comparison with the state of research were pointed out. To underline the broad applicability and potentials of the developed approach two very different case studies were presented and different measures to improve energy and resource efficiency on diverse fields of action could be identified. Besides practical application further research will focus on the development of more detailed TBS modules, the conduction of actual optimization studies and the coupling with detailed machine/process simulation. 7

ACKNOWLEDGMENTS

The introduced cases are based on the research project EnHiPro (Energy and auxiliary material efficiency in production) that is funded by the German Ministry of Education and Research (BMBF) and managed by the project management agency Karlsruhe (PTKA). All data has been anonymized and alienated and does not show the exact results that have been elaborated at the project consortium. 8

REFERENCES

[1]

McKinney, M., Shoch, R., Yonavjak, L. (2007): Environmental Science – Systems and Solutions, 4th edition, Jones and Bartlett, Sudbury, MA.

[2]

U.S. Energy Information Administration (2009): Glossary, http://www.eia.doe.gov/glossary.

[3]

Scottish Energy Study (2006): http://www.scotland.gov.uk.

[4]

German Federal Ministry of Economics and Technology (2009): Energy Statistics.

[5]

Seefeldt, F.; Wünsch, M. (2007): Potenziale für Energieeinsparung und Energieeffizienz im Lichte aktueller Preisentwicklungen, Prognos AG.

[6]

Fraunhofer Gesellschaft (2008): Energieeffizienz in der Produktion (funded by BMBF).

[7]

ICT and Energy Efficiency - Consultation Group on Smart Manufacturing (2008): Energy Efficiency in Manufacturing The Role of ICT.

[8]

[9]

Herrmann, C.; Kara, S.; Thiede, S.; Luger, T. (2010): Energy Efficiency in Manufacturing – Perspectives from Australia and Europe, In: 17th CIRP International Conference on Life Cycle Engineering (LCE2010), Hefei, China. Rebhan, E. (2002): Energiehandbuch - Gewinnung, Wandlung und Nutzung von Energie, Springer, Berlin.

[10] Radgen, P.; Blaustein, E. (2001): Compressed Air Systems in the European Union - Energy, Emissions, Saving Potentials and Policy Actions. [11] Gauchel, W. (2006): Energy-saving pneumatic systems, O+P Ölhydraulik und Pneumatik, Vol. 50, Nr 1.

[12] Herrmann, C., Thiede, S., Heinemann, T. (2010): Ganzheitliche Ansätze zur Erhöhung der Energie- und Ressourceneffizienz in der Produktion, 10. Karlsruher Arbeitsgespräche Produktionsforschung 2010, Karlsruhe, Germany. [13] Hesselbach, J., Herrmann, C., Detzer, R., Martin, L., Thiede, S., Lüdemann, B. (2008): Energy Efficiency through optimized coordination of production and technical building services; Proceeding of the 15th Conference on Life Cycle Engineering, Sydney. [14] Dietmair, A.; Verl, A. (2009) : A generic energy consumption model for decision making and energy efficiency optimisation in manufacturing. International Journal of Sustainable Engineering, Bd. 2, Nr. 2, pp. 123. [15] Heilala, Juhani; Vatanen, Saija; Tonteri, Hannele; Montonen, Jari; Lind, Salla; Johansson, Björn; Stahre, Johan (2008): Simulation-based sustainable manufacturing system design. In: Mason, Scott J. (Hg.): 2008 Winter Simuation Conference. [16] Hornberger, Markus (2009): Total Energy Efficiency Management. Vom Energiemanagementsystem zur Simulation der Energieverbrauchswerte auf Prozessebene. Elektronik ecodesign congress. München. [17] Johansson, B.; Mani, M.; Skoogh, A.; Leong, S. (2009): Discrete Event Simulation to generate Requirements Specification for Sustainable Manufacturing Systems Design. [18] Junge, M. (2007): Simulationsgestützte Entwicklung und Optimierung einer energieeffizienten Produktionssteuerung. Dissertation, Univ. Kassel. [19] Löfgren, B. (2009): Capturing the life cycle environmental performance of a company’s manufacturing system. Göteborg. Chalmers University of Technology. [20] Rahimifard, S.; Seow, Y.; Childs, T. (2010): Minimising Embodied Product Energy to support energy efficient manufacturing. In: CIRP Annals - Manufacturing Technology, Jg. 59, pp. 25–28. [21] Solding, P., Petku, D.; Mardan, N. (2009): Using simulation for more sustainable production systems – methodologies and case studies. In: International Journal of Sustainable Engineering, Jg. 2, H. 2, pp. 111–122. [22] Weinert, N., Chiotellis, S., Seliger, G. (2009): Concept for Energy-Aware Production Planning based on Energy Blocks. In: GCSM2009 (Hg.): Proceedings of the 7th Global Conference on Sustainable Manufacturing, pp. 75–80. [23] Wohlgemuth, V.; Page, B.; Kreutzer, W. (2006): Combining discrete event simulation and material flow analysis in a component-based approach to industrial environmental protection. In: Environmental Modelling & Software, Jg. 21, H. 11, pp. 1607–1617. [24] Herrmann, C.; Thiede, S. (2009): Process chain simulation to foster energy efficiency in manufacturing, In: CIRP Journal of Manufacturing Science and Technology, Elsevier. [25] Thiede, S., Herrmann, C. (2010): Simulation-based Energy Flow Evaluation for Sustainable Manufacturing Systems, 17th CIRP International Conference on LCE, Hefei, China. 9

CONTACT

Sebastian Thiede Institute of Machine Tools and Production Technology (IWF), Product- and Life- Cycle-Management Research Group, Technische Universität Braunschweig, Germany, [email protected]

Modular Modeling of Energy Consumption for Monitoring and Control 1

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3

Alexander Verl , Eberhard Abele , Uwe Heisel , 1 1 1 2 3 Anton Dietmair , Philipp Eberspächer , Raphael Rahäuser , Sebastian Schrems , Steffen Braun 1

Institute for Control Engineering of Machine Tools and Manufacturing Units, Universität Stuttgart, Stuttgart, Germany 2

Institute for Production Management, Technology and Machine Tools, TU Darmstadt, Darmstadt, Germany 3

Institute for Machine Tools, Universität Stuttgart, Stuttgart, Germany

Abstract A prerequisite to achieve energy efficiency in production through optimization is the possibility to use simulation models to predict the consequences settings, decisions and actions have on the energy consumption and thus on the lifecycle cost of production machines. But today’s production systems are dominated by agile structures and rapid changes of general conditions so that predictive energy consumption models need to be adaptable. Therefore in the ECOMATION project the modular modeling approach for energy consumption prediction presented here is being developed, which facilitates re-use of energy consumption models and thus minimizes the cost of finding the optimal operational profiles. Keywords: Energy Efficiency; Machine Tools; ECOMATION

1

INTRODUCTION

An important step to achieve energy efficiency in production is to inform the involved persons and automatic control systems about the consequences decisions and actions have on the energy consumption and thus on a substantial share of the lifecycle cost of production machines. In addition to measurements which quantify the energy consumption for individual cases, models that describe the energy consumption and its driving factors in a generic form are key enablers to energy consumption optimization for complex production systems. Simulation models allow us to estimate the effects different decision options and parameter settings have on the energy turnover over the entire lifecycle of complex production systems. In the literature models of sustainability aspects are available [1], but the level of detail of general models is not sufficient for multilevel optimization and control. Those publications that focus on energy aspects typically present either coarse models of overall machine tool energy consumption which do not include controllable parameters [2] or models of detail aspects like the dependency of machine tool energy consumption on particular process parameters [3]. What is missing today is a modeling approach that includes submodels with parameters that can be influenced by optimization and control of different levels in a way that keeps complex system models manageable. Modular modeling and model abstraction [4] are required for systematic energy consumption modeling. Production systems in global, turbulent environments are not only complex, but are dynamically changing, agile structures that face rapid shifts of demands, requirements and general conditions. On the one hand this means that optimization cannot be done once at the beginning of the lifecycle of a production system but has to be implemented as an ongoing process which constantly pushes the production system towards its energy optimal operating point despite frequent changes throughout the entire use phase. Permanent measures have to be complemented by energy optimizing control. A complexity minimizing approach for that is presented in [5]. As a consequence of the dynamic nature of today’s production systems and their environment, individual predictive energy consumption models can only be used for a limited time and scope

before changes of the production system render them inaccurate and useless. A multitude of factors influence the degree of energy efficiency a particular manufacturing strategy can attain. Creating new models repeatedly would cause the cost for the energy optimization to surpass the cost savings that could be realized through the resulting energy savings. For widespread applications of energy efficiency optimization, the associated cost has to be minimized by making energy consumption model information easily, quickly and cheaply available. In the ECOMATION project a modeling approach for energy consumption prediction is therefore being developed which is modular to facilitate re-use and adaptation to new scenarios. The available knowledge about the energetic structure of a production system may vary from no knowledge at all to detailed information about the dynamic behavior of individual components. Therefore, a generic way of composing model blocks is being used in combination with exchangeable structural model blocks of typical resources and components of different levels of detail. The structural model blocks can then be adapted through a small number of parameters to match the energy consumption behavior of real components. This paper starts with the introduction of the theoretical requirements, structure and interfaces of a modular energy consumption model of a production system in Section 2. The remaining chapters cover different aspects of the submodel creation and validation process for the example of a horizontal lathe. Section 3 treats the influence of the machining process on the energy consumption. In this context it is shown how an overall machine energy consumption model can be used for optimization during process planning. How the influence of individual machine components on the energy consumption can be broken down in submodels based on component states, general and process conditions is shown in Section 4. The modeling of the local coolant lubricant system of the lathe is given as an illustrative example. As in many productions systems the coolant lubricant is supplied by centralized units, an approach for calculating the energy consumption of such centralized systems is presented in Section 5. This represents large system modular composition to create planning models.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_59, © Springer-Verlag Berlin Heidelberg 2011

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Sustainability in Manufacturing - Methods and Tools for Energy Efficiency ASPECTS OF MODELING EFFICIENCY

2.1

Modeling requirements

It is commonly agreed that models should match the requirements of the situation in which they are used in to ensure efficiency. Requirements that have to be taken into account include the model’s descriptive capability, its computational complexity, its scalability and the required modeling effort. The main objective of modeling here is to calculate quasistationary key indicators for optimization of the operation of machines and production systems for minimum energy consumption within the boundaries set by a manufacturing task. It is not an objective to model machines based on their detailed physics, and models should be focused on aspects of the modeled system that have a direct influence on energy consumption. At the same time, it is important that implications of these aspects on other properties are included in the model if these properties are either part of the general conditions set by a manufacturing task or conflicting objectives to energy minimization. For example, that a certain amount of material is removed from a work piece is mandatory and thus defines a boundary for the optimization, while for example wear rates may be conflicting objective functions that have to be balanced with energy consumption and therefore should be included in the model used for optimization. Relevant information that is calculated from the model therefore includes active power, reactive power, heat generation and flows, temperature and thermal deformation accuracy, dynamic excitation and transmission characteristics including dynamic losses deformation accuracy and work piece roughness, wear and breakage limits. Other requirements on the modeling approach are imposed by the context in which the models are used. As shown in [5], energy consumption optimization cannot be performed efficiently and robustly by a single centralized unit for realistic manufacturing scenarios of large and dynamic production systems. Consequentially, calculations based on the energy consumption models will have to be performed on all kinds of different control computers which may have only very limited computational resources. This, on the one hand, leads to the requirement that the energy consumption models will have to be easy to evaluate and portable between different controls. Whenever possible, feed forward calculation of energy consumption based on a parameter set is desirable, so that optimization algorithms can use the models efficiently with iterative modification of input settings. On the other hand, it means that energy consumption models should allow any sub-section relevant for the local context to be evaluated independently. Sectioning should thereby be supported horizontally, e.g. calculations for a single station of a production line should be possible, as well as vertically, i.e. detail which is not relevant on one level of control should be eliminated through abstraction. 2.2

Scalable modular modeling and model information re-use

Based on the requirements listed above it becomes clear that only a modular modeling approach can satisfy all criteria. Submodels with the abstract interface shown in Figure 1 are proposed to build the overall system energy models (e.g. Figure 4 and 11) from them. This structure is derived in previous publications about modeling of individual machine tools and the required types of structures [6].

Event

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Figure 1: Metamodel of energy consumption submodels.

Figure 1 thereby constitutes the abstract metamodel and interface which allows representing all submodel aspects relevant to energy consumption [6]. Events may lead to a component to change its operational state, or the component may be forced into a particular state. The changes may be induced externally, through internal stochastic behavior or when the component continuous states meet certain conditions. Each operational state is characterized by a different capability of the component to fulfill the demands imposed on it and how the component’s resulting demands are calculated (e.g. supply flow). Non-scalar relationships between a machine component and its environment that link its function to its energy consumption are its dynamic stiffness and its thermal behavior. An example of submodel interfacing will be given in Figure 4. Subcomponent modularization for bidirectionally interlinked models, e.g. a motor/pump/orifice combination, is presented in Section 4. Besides the energy consumption behavior itself, it is also important to be able to describe the production system operation. This can be done through trajectories of constraints over time. These trajectories of constraints are similar to the trajectory of discrete and continuous states a machine follows over time, but they define the set of state values the machine is allowed to be in at each point of time. The remaining degrees of freedom are used for optimization. To be able to treat systems of different levels of detail with the same common knowledge but in each case with minimal complexity, transformations from a higher level of abstraction to a lower level, representing e.g. a machine control, and transformations from a lower level of abstraction to a higher level are required (Figure 2). S(t) t S(t)

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Figure 2: Modeling of usage profiles and control. Figure 3 illustrates that the models used for particular tasks, like incorporating analytical model knowledge, learning parameters from measured data, controlling components and machines in real-time and planning production systems each emphasize different aspects of the same system. The fact that information may be entered in one context and used different other context makes it attractive to establish bidirectional mappings between different representations. Routing these mappings through a generic representation (gray) thereby limits the number of required interfaces and mappings. Analytic Model (very high detail, narrow scope)

Planning Model (very low detail, very large scope)

Learning Model (fixed structure, narrow scope)

Control Model (high/low detail, narrow scope)

Figure 3: Transformations between model forms. As it is not realistic and economic to try to get to accurate energy consumption models purely based on analytical modeling and catalog data, a library of generic model building blocks together with actual power intake information [5] and algorithms for model parameter adaptation based on measured data should be used [6]. In the following paragraphs, a number of important modeling steps will be treated in detail for the example of the coolant lubricant system and use of a lathe. The treatment is not exhaustive in terms of different objective criteria and different levels of detail, but is meant to illustrate how a modular energy consumption model can be composed from different building blocks of different detail.

Sustainability in Manufacturing - Methods and Tools for Energy Efficiency 3

MODELING THE INFLUENCE OF MACHINING PROCESSES

It is obvious that minimizing the amount of energy required for a given machining operation has to take place without compromising process performance, stability, robustness, surface quality and chip formation. The submodel for the manufacturing process therefore is the heart of the overall model and links energy to other aspects. The overall simulation environment (Figure 4) uses a virtual CNC Module to generate from G-Code tool path data which is passed to the machine tool kinematic model to determine the position of the tool. The cutting model computes the intersection between the tool and work piece geometries and outputs the resulting cutting forces based on a cutting law. The forces are the input to kinematics and drive model modules which calculate the required electric power. Machine Tool Model NCProgram

Virtual CNCModule  Output:

Basic model of mechanics and kinematics  Output: Tool movement M

Interpolated trajectory NC

Basic drive and controller model  Output: Electric Power E

situation most experimental results are derived from. Other cutting models use a linear cutting law as for example [8]. A new approach in cutting force prediction is relying on a cutting energy based method [9], which is not dependent on the knowledge of specific cutting forces but on the precise knowledge of material data. All approaches to cutting force prediction have one thing in common: they need a description of the uncut volume in order to determine the actual chip geometry. Modern shop floor programming systems often have the ability to easily set up data for the uncut work piece geometry. Most CAM-Systems certainly are able to represent both uncut as well as already cut geometry. With knowledge of the expected cutting forces during a cutting operation, this data is passed to the machine model as loads for the axes’ drives and spindle and thus the electrical power required for the operation can be estimated. The difference between this value and a purely analytical cutting power Pc computed by

Pc  Fc  vc

Workpiece geometry Material Tool geometry Temperature Cooling lubricant condition Cooling lubricant flow rate and pressure

P Cutting model

Figure 4: Structure of the simulation environment. 3.1

Sub-Model of Process Related Energy Conversion

To investigate the effects of variable process parameters and different machining strategies on the energy consumption of machine tools, simple models of the process are required that cover the power consumption influence of the process itself. Such models have been created for turning and milling. In the following, investigations and experimental results for the turning process are presented. The process model for the turning operation is based on a full cutting law formulation according to Kienzle-Victor [7]. The resultant cutting force {F} can be split up into the three main components Fc in circumferential direction, Ff in feed direction and Fp in radial direction, expressed by the empirical law

 Fc  k c1.1  b  h1 m c  F    F f  k f 1.1  b  h1 m f  1 m  F p  k p1.1  b  h p

     

(1)

It is a function of the specific cutting force coefficients ki1.1 and the depth of cut b and uncut chip thickness h, which are depending on the tool rake angle  according to (2).

b

Validated Example for a Turning Process

To validate the created models, a large number of measurements have been performed. In this paper we present validation examples for the lathe Gildemeister CTX 420 linear, which is widely used in production. It is equipped with a 28.3 kW main spindle unit, active tools, ball screw driven z- and y-axis and an x-axis with linear direct drive (LDD). Auxiliary systems include hydraulic chuck clamping and revolver locking, the coolant lubricant pump, cooling devices for the LDD, main spindle and hydraulics, chip conveyor and oil mist extraction. Turning experiments on 42CrMo4V work pieces (diameter 72 mm; length 210 mm) have been carried out to investigate the accuracy of the model and to evaluate the possible influence of coolant lubricant flow on the cutting forces. The cutting speed was varied in three steps (vc = 80; 110 and 140 m/min), cutting depth in five steps (ap = 1.0; 2.0; 2.5; 3.0 and 3.5 mm) while four distinct feed rates (fz = 0.1; 0.25; 0.4 and 0.55 mm/rev) were applied. The whole sequence has been repeated 3 times with different coolant lubricant flows of 0.25, 4.8 and 11.6 l/min. All three components of the predicted cutting force correspond very well with the experimental data. A minor influence of the cutting speed vc was observed, i.e. the cutting force slightly rises with rising cutting speed. The influence of coolant lubricant flow can almost be neglected since no significant changes in the measured forces could be observed. The predicted power consumption during cutting (Figure 5) shows satisfying agreement with experimental data. The measured and simulated power consumption for one set of parameters with four distinct feed rates are shown in Figure 6. Except for the deviations during spindle run-up and run-down the predicted power agrees well with the measured values.

ap

sin  h  f z  sin 

(2)

Additional correction terms known from literature are neglected for simplicity purpose. With the cutting parameters ap and feed rate fz the basic chip geometry can be derived from (2) and the cutting force estimated from (1). The specific cutting force coefficients ki1.1 and exponents m need to be taken from literature or derived by experimental identification beforehand. This is a major drawback of this method, especially as the values become more and more uncertain as the actual cutting condition differs from the standard

(3)

indicates the efficiency of the machine tool’s driveline. 3.2

Basic process model Chip geometry, MRR  Output: Cutting forces, Spindle torque

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Figure 5: Spindle Power P in dependence of ap and fz, cyan circles: measurement, black squares: predicted values.

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Figure 6: Measured and predicted total power consumption P during experiment sequence with vc = 110 m/min and ap = 2.5 mm. Figure 7 shows the isosurface of constant material removal rate (MRR) of 6 cm³/min in the scalar field of cutting power over the vc ap - fz –space. Additionally depicted is an isoslice at a constant cutting speed of vc = 110 m/min. If a constant MRR is desired, the right part of the isosurface of constant MRR yields the minimum power requirements for the operation. In other words: high cutting depth at low feed rates should be aimed for. However, the choice of too low a feed rate leads to the formation of helical, snarled or even worse – long ribbon chips, which is not acceptable.

For the determination of the energy control factors, detailed component models have been developed. These models permit a dynamic simulation of the component’s energetic behavior. The energy consumption influencing factors are determined by the simulation of different machine components. Without the necessity of detailed and expensive measurements, the influence of the variation of their controllable parameters can easily be identified by the parameterization of the simulation models. For the implementation on the machine control, the models are adapted to deliver a quick and on the machine control executable calculation. These adapted models are designed as user defined SFunction Blocks which allow including calculations in the C programming language. This enables an export to a real machine control and increases the quickness of the simulation. Compared to a dynamic simulation, a steady state simulation does not take in account the transients in the start-up phase of the components which has no major influence on the overall energy consumption in any way. Therewith the models can be calculated much faster and only a few algebraic loops are necessary. The general structure of both model types and the equations on which the calculation is based stays the same. An important factor of the component modeling is that all components can be connected among themselves and can easily be exchanged with an alternative component. The models are built up in a way that each component can be regarded independently or be easily connected to other models by the use of defined in- and output signals. Thus, the behavior of single components as well as the interaction between the components which influence each other is simulated. An example for a control cabinet cooling device and possible interactions with other components can be found in [10]. 4.2

Figure 7: Isosurface of constant MRR, color coded by cutting power Pc in Watts. At a preferred cutting speed the optimum would be a feed rate, where still satisfying chip forms develop. In our experiments this can be achieved at feed rates above 0.25 mm/rev. 3.3

Representing the Process in Modular Modeling

From the previous paragraphs as well as the literature on simulation of production machines it becomes obvious that process models define the loads on machines and their components. Different types of the latter will be able to fulfill the demands with different energy consumption, so that separating machine and process modules along the lines of Figures 1 and 4 is strongly motivated. 4

Structure and Validation Example for a Coolant Pump

The interaction of components within a functional module will be explained by the example of a cooling lubricant system. The electric motor, the cooling lubricant pump and the downstream components like the valves and the tool characterize the system to be modeled. In the model, each component is regarded independently with input and output variables which build the linkage to other components. Considering the demanded volume flow rate at the tool the resulting system pressure is led back in the lubricant pump, which calculates the corresponding torque which has to be delivered by the electric motor. Figure 8 shows the structure of the submodel with a second layer of modularization. An analysis has shown that the most influencing components of the cooling lubricant system are the pump and the tool or the orifice at the outlet of the system. The pipework of the system and other installed components can be neglected. In this case the system has been reduced to the pump and the orifice, which already give a sufficient approximation.

COMPONENT MODELS

The dependence of a machine’s energy efficiency and effectiveness on the way different construction solutions of machine components fulfill demands and loads lead to the demand for component models which are customizable to the actual machine configuration and modular to enable an easy evaluation of alternative components. 4.1

Modular Modeling Aspects for Components

The models have to fulfill two main functions: the determination of energy consumption influencing factors of the components on one side and the implementation of the models on the machine control for the development of a machine close energy loop on the other side. Therefore two different kinds of models have been developed.

Figure 8: Secondary interface structure of a modular simulation submodel of a cooling lubricant system with bidirectional coupling.

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Figure 9: Measured and simulated mean power consumptions for different volume flow rates (left) and measured and simulated power consumption curve for a volume flow rate of 14 l/min of the cooling lubricant system (right). The models are built up in a way that all necessary system parameters can be taken from component data sheets. This allows an easy adjustment of the models for a special machine type and simplifies the comparison between alternative components and the analysis of their influence on the energy consumption. A measurement of a real machine has been conducted to validate the precision of the simulation results and their manageability. As the pump set is usually operated with a constant flow rate, the system has been modified in a way that the volume flow rate could be varied by the use of a gate valve. The energy consumption has been measured for different volume flows and compared to the output of the simulation models. The parameters for the simulation models have been taken from the data sheets of the motor and the characteristic curves of the pump. Figure 9 shows the direct comparison between the measured and simulated power of the pump set for different volume flow rates. It can be seen that the models permit a reliable calculation of the energy consumption, as the measured and simulated power consumption differs by max. 4% in this case. The quality of the parameter data is crucial for the precision of the model. In order to be able to analyze the interaction between all relevant machine components, models of the whole machine periphery are being developed. Especially for speed controlled motors like main spindle, feed drives or future speed controlled cooling lubricant systems, the definition of different component states is important to allow for model based energy optimal machine control. 4.3

Component Sub-Model Abstraction

As has been explained in section 2, different model detail levels have to be supported in order to allow for vertical integration, i.e.

the application of the same model knowledge on different levels of abstraction. In its most basic form, such a transformation can consist of calculating a mean power based on a component model and a typical operation profile. This has been performed based on measurements for the example machine treated here (Figure 10). 5

For energy consumption assessment of a manufacturing system it is important to include the electrical power intake for the supply demand, e.g. pressured air, hydraulic oil or coolant lubricant. In metal-cutting manufacturing systems generally 60% of the total electrical power intake is needed for coolant lubricant conditioning and supply [11]. In many production systems the coolant lubricant is supplied by centralized units. Therefore an approach of a modular model for energy consumption calculation of a centralized cooling lubricant supply system is introduced in the following two sections. 5.1

Structure of a centralized supply system

The equipment of a coolant lubricant supply system depends on various aspects like production size, cutting method and material. In general the structure of the circulation system can be divided in: supply path, return path, cleaning unit, chip processing and cooling. In the supply path the coolant lubricant is delivered from a reservoir by a pump station to the production hall and is fed to a large number of machines through a network. After the use in the machine tool the contaminated cooling lubricant is transported back to the cleaning unit with devices like flutes or pump-back stations. Chip breakers and separators are used depending on the chip volume and form. In the cleaning unit the chips are separated in general by sedimentation and by filtration to reach the required fluid cleanness rating. To minimise contamination the coolant lubricant is typically cleaned in a separate cleaning loop which carries more fluid than the volume circulating through the supply and return path [12]. After separation, oily chips and grinding sludges are deoiled in the chip processing unit with centrifuges and presses. For temperature stabilization a cooling unit may be necessary. The heat input into the coolant lubricant is approximately about 20% to 50% of the machine tool power consumption and 80% of the pump performance. Additional heat exchange takes place between the environment and the fluid [13]. 5.2

Figure 10: State-based energy consumption by components.

LARGE SYSTEMS MODELLING ON THE EXAMPLE OF A CENTRALIZED COOLING LUBRICANT SUPPLY SYSTEM

Modeling of centralized supply systems

Figure 11 shows the modular model approach of a centralized cooling lubricant supply unit. Due to the structure of the supply system the model consists of four submodels. The submodels generally consist of further submodels.

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Sustainability in Manufacturing - Methods and Tools for Energy Efficiency

legend: p= pressure Q= flow rate ch= amount of chips heat= heat input in coolant lubricant

return path

example: subsystems of supply path pumpstation network

heat Q

Q

supply path p, Q

heat

p,Q p, Q

p, Q

heat

p

p Q

Q

cleaning unit + chip processing

production system machine 1 machine 2 …

p, Q

p, Q

Q

ch

ch

cooling heat heat

heat

Figure 11: Model approach for energy consumption assessment of a centralized coolant lubricant supply system. The inputs are the demand of flow rate, pressure and chip quantity and the heat input into the fluid. In the return path additional flow rate can be needed for flushing by the pump station in the supply path. The increase of pressure due to losses in fittings and pipes as well as height differentials is calculated in the network submodel with the given system characteristics. The operating point and the power consumption are calculated in the pump station submodel by the pressure and flow rate, the pump characteristics and the control mode. The flow rate in the cleaning unit and chip processing model is calculated by the flow rate input for the supply path. The pressure demand and the use of filter pumps depend on the selected filtration type. With the input of the chip quantity an average differential pressure due to contamination of the filter is calculated. Devices for extraction or chip processing are modeled with constant power consumption with an on-and-off control or permanent active. The electrical power for cooling is calculated by the total heat input into the fluid multiplied by a coefficient of performance for cooling. The sum of the power consumption of all submodels leads to the total electrical power intake. Due to the modular approach the influences of different equipments on the total power consumption can be analyzed by changing or substituting the submodels.

[2]

Dahmus, J.B.; Gutowski, T. (2004): An Environmental Analysis of Machining. Proc. 2004 ASME International Mechanical Engineering Congress, Anaheim, California.

[3]

Draganescu, F.; Gheorghe, M.; Doicin, C.V. (2003): Models of machine tool efficiency and specific consumed energy. J. of Materials Processing Technology, No. 141, pp.9-15.

[4]

Ferretti, G.; Magnani, G.A.; Rocco, P. (2004): Virtual Prototyping of mechatronic systems. Annual Reviews in Control, Vol. 28, No. 2, pp.193-206.

[5]

Verl, A.; Westkämper, E.; Abele, E.; Dietmair, A.; Schlechtendahl, J.; Friedrich, J.; Haag, H.; Schrems, S. (2011): Architecture for Multilevel Monitoring and Control of Energy Consumption, Proc. 18th CIRP International Conference on Life Cycle Engineering LCE 2011, Braunschweig, Germany (accepted for publication).

[6]

Dietmair, A.; Eberspaecher, P.; Verl, A. (2010): Predictive Simulation for Model Based Energy Consumption Optimisation in Manufacturing System and Machine Control. Int. J. Manufacturing Research (accepted for publication).

[7]

Kienzle, O.; Victor, H. (1957): Spezifische Schnittkräfte bei der Metallbearbeitung. Werkstofftechnik und Maschinenbau, Vol. 47, No. 5, pp. 224-225.

To achieve a higher level of energy efficiency, the overall power consumption of production systems has to be optimized throughout their entire lifecycle. Today even calculating the power consumption of existing systems is a challenge. In this paper, model information re-use and identification have been identified as key enablers to make energy efficiency optimization economically viable. Consequentially a modular modeling approach to simulate the power consumption of production systems is proposed which has been detailed for process, component and system aspects and validated with experimental results. Parts of the models were created as detailed modular submodels. Based on this overview publication we are planning to further develop and integrate the modeling process in the control of machine tools. In this way, each machine control can work as a monitoring device for its power consumption and can reach actually energy optimal states through optimization [5].

[8]

Altintas, Y. (2003): Cutting Process Simulation and Optimisation, Proc. FTK2003, Stuttgart, pp. 219-246.

[9]

Zekhanov, J.A., Storchak M. (2007): Analysis of Contact Width Changing Regularity on Basis of Variational Orthogonal Cutting Model, in: Theory and Practice of Engineering Equipment, Voronezh, Vol. 15, pp. 65-71.

[10]

Abele, E.; Schrems, S. (2010): Determination of energy consumption control factors of machine tools by component oriented simulation. Proc. Int. Chemnitz Manufacturing Colloquium (ICMC 2010) , Chemnitz, Germany, pp. 711-718.

[11]

N., N. (2010): Spanende Bearbeitung, Wirtschaftsministerium Baden-Württemberg, online, available from http://www.umweltschutz-bw.de/index.php?lvl=353.

[12]

N.N. (2005): VDI Richtlinie 3397 Part 2 - Maintenance of metalworking fluids, Beuth Verlag, Berlin.

7

[13] Tornau, D. (1999): Kühlschmierstoffe und Anlagen – Theorie und Praxis, Expert Verlag, Renningen Malmsheim.

6

SUMMARY

ACKNOWLEDGMENTS

The authors are grateful to the German Research Foundation for funding the presented work in project FOR1088 “ECOMATION”.

9 8 [1]

REFERENCES Shao, g.; Kibira, D.; Lyons, K. (2010): A Virtual Machining Model for Sustainability Analysis. Proc. ASME 2010 CIE 2010, 15-18 August 2010, Montreal, Canada.

CONTACT

Philipp Eberspächer Institute for Control Engineering of Machine Manufacturing Units (ISW), University of Stuttgart [email protected]

Tools

and

Architecture for Multilevel Monitoring and Control of Energy Consumption 1

2

3

Alexander Verl , Engelbert Westkämper , Eberhard Abele , 1 1 1 2 3 Anton Dietmair , Jan Schlechtendahl , Jens Friedrich , Holger Haag , Sebastian Schrems 1

Institute for Control Engineering of Machine Tools and Manufacturing Units, University of Stuttgart, Stuttgart, Germany 2

3

Institute of Industrial Manufacturing and Management, University of Stuttgart, Stuttgart, Germany

Department of Production Management, Technology and Machine Tools, Technical University of Darmstadt, Darmstadt, Germany

Abstract Guaranteeing energy efficient operation of production systems through a-priori optimization is an extremely complex task. We therefore propose an alternative approach where controls can decide locally if an energy reduction is possible and set components to energy-optimal states. In this paper we present results from the research group ECOMATION describing the information flow that generates energy control loops on different levels based on model information and an appropriate communication and control infrastructure. The communication mechanisms and control structures in production systems and machines are presented which allow using models automatically and coherently on all required levels of detail and abstraction. Keywords: Energy Efficiency; Energy Monitoring; Energy Control

1

INTRODUCTION

Studies have shown that consumed energy and compressed air often contribute over 20% to the total lifecycle costs of production machines [1]. To reduce the energy consumption in plant and machinery, four different strategies can be chosen: 1. optimization of the process chain; 2. optimization of the technology of individual process steps; 3. permanent structural measures including component selection; 4. energy-optimal operation and control; Strategies 1-3 can yield only an optimization “on average” and thus do not allow exploiting energy saving potential that is specific to a subset of the operational profiles of the machines and components. For example, replacing a pump with a higher efficiency model leads to substantially lower energy consumption only if the operation of the pump in an energy-optimal state is ensured for all different work pieces manufactured on the machine in substantial quantities. In Section 2 we will motivate an architecture based on decentralized energy control loops that form the basis for such an energy efficient operation of entire production systems spanning all the individual machines and resources built into them. In Section 3 we will then go on to show how information about the actual energy consumption in relation to the operation of components, machines and production systems can be gained during the use phase. Section 4 covers how energy consumption information can be communicated between the component, machine, production line, factory and system levels. Section 5 addresses decentralized optimizing control strategies.

tionships between the operation profile of a machine, the machine’s performance with respect to the use case and the energy consumption of the machine are known. Such model knowledge is expensive and often also inaccurate if it is created based on detailed physical models and laboratory measurements, especially for machines which are built in exactly the same configuration in only very small numbers and which may change their behavior over their operational life cycle. In addition to that, it is often not possible to model the behavior of machines in terms of state profiles accurately without significant cost and effort. This holds especially true for machines that are operated in turbulent glocalized production environments and thus constantly experience major variations of their operation. In the context of this paper a “glocalized production system” is interpreted as a dynamic network of producer-consumer relationships spanning different locations with variable individual properties and markets. As the entire production system is considered, the energy balance per work piece is influenced by all stakeholders in different production chains and the potentially complex interactions between factories and logistics, making the operation even more volatile. 2.1

Decentralized architecture for energy optimization

Based on these considerations we argue that the most cost efficient and effective way to ensure operation of machines and entire production systems at their energy optimal operating point is to equip the components, machines and factories with the capability to learn models of their energy consumption behavior during their normal operation. These models can then be used as a basis for ongoing self-optimization. This is illustrated in Figure 1. Use Case Conditions Actual Energy Consumption Behavior Model

2

ENERGY CONTROL LOOPS

For operating a machine in an energy-optimal way, information about both the energy consumption characteristics of the machine and its components as well as the use case is required. Within the constraints defined by the use case, the machines and components can be controlled to follow a state trajectory that minimizes the total energy consumption. Such an optimization requires that the rela-

Variation within Boundaries For Energy Optimization Actual Operational State

Energy and Secondary Effect Causal Model Identification Actual Power

Performance

Figure 1: Local energy control loop closed within a control level.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_60, © Springer-Verlag Berlin Heidelberg 2011

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Sustainability in Manufacturing - Methods and Tools for Energy Efficiency

The control of one level of a production system, forming the middle row in Figure 1, receives information about conditions that have to be met to fulfill a production scenario from a superior planning or control authority. Based on a model that relates energy consumption and other performance criteria to operational parameters, the control selects the most energy efficient trajectory of states and parameters which lies within the boundaries. In this way, energy control loops are closed that push production systems towards their optimal operating point even if a-priori knowledge is imperfect and behavior changes over time. At the beginning of the operation of a machine or other production resource, a coarse model is used which is created based on the knowledge available a-priori e.g. from catalog data, generic models and previous experience. During operation of the machine, the actual operational states and parameters, power consumption and performance are recorded and related to each other. The deviation of the actual values and relations from the predicted values and relations are continuously used to adapt the parameters of the energy consumption behavior model. As the model which is being used as the basis for optimization is getting increasingly accurate, the local optimization of the operation is continuously improved. An energy consumption model which can be used is described in [2]. In addition to being used as the basis for local optimization, the model is also communicated to adjacent system levels. The next higher planning level receives information about both the energy consumption in each state and for different parameter settings (energy consumption model) as well as typical characteristics of the locally selected energy optimal trajectories and the characteristics of not directly controllable parameters and states depending on the use case boundary settings (behavior model). That can then be combined with other locally generated models of resources and be used to optimize the settings of boundary conditions of all resources governed by that higher control level. Such an approach that is analogous to the concept shown in Figure 1 is illustrated in Figure 2.

System Use Case Conditions System Energy and Behavior Model

Variation within Boundaries For Energy Optimization

Resource Conditions

Model Aggregation and Causal Effect Identification

Resource Energy and Behavior Model

Figure 2: Energy control loops in higher control levels. 2.2

Complexity of the decentralized energy control

The optimum use case conditions calculated by one controller for a controller of a lower level typically only define some but not all aspects of the behavior of the lower level resource. Based on this, optimization in the control of the resource is performed to determine the optimum settings for the aspects left open by the higher level controller. This is reiterated for all levels. The principle of optimizing energy efficiency determining aspects locally in the context, level and detail where they are normally treated in the production environment thereby leads to a robust overall system where each optimization, planning and control task is of minimum complexity. Direct communication of energy consumption model information takes place only between controls of a resource and its subresources, and each control has only to be aware of the interdependencies with and within its direct neighbors. Systematic local aggregation and abstraction of model knowledge ensure that the communicational and computational loads remain limited even for large overall systems. Figure 3 gives a schematic overview of the various energy control loops that can be created by following such a decentralized approach.

Glocalized System Option forGlocalized a Glocalized PS Production Production System Plans and Constraints Factory

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Figure 3: Energy control loops in higher control levels. 2.3

Stability of the energy control loops

A key aspect of successful operation of such a system which includes feedback will be whether it stabilizes the system at its operating point with minimum energy consumption or whether it can lead to instabilities. We therefore briefly review general conditions that have to be met for robust stability of the energy control loops. One such condition is that commanded changes may not include higher dynamics than the bandwidth with which the consequences of these changes become visible in the energy consumption and behavior model. Similar to this local condition, a global condition for stability is that the dynamics of the nested controllers have to monotonously decrease from the innermost control loop to the outermost control loop. As bifurcation, i.e. discontinuous changes in the actual behavior or discontinuities in the model used by the controller as a basis for optimization, can lead to oscillating, unstable and even chaotic behavior of the controlled system, the identification-optimization loop should avoid discontinuities. For maximum safety we propose to design the inner loops and identification to be so much faster than the optimization and higher level loops that they appear quasistationary to the latter. For the case of manufacturing, we can assume that this condition can be met by the proposed hierarchic control structure. Changes of the energy consumption behavior on a lower level will typically become visible on a faster time scale than any systematic changes in the way e.g. a machine is scheduled by the production line control. Nevertheless, optimization and model identification algorithms have to be designed with the stability criteria in mind. This can be ensured by updating the model used for optimization and communication only at certain points of time based on the identified model instead of using a single continuously adapted model. 3

ALLOCATION OF ENERGY CONSUMPTION TO CAUSES

This section of the paper will be devoted to identifying energy consumption with components and causes. This is a systematic prerequisite for using actual energy consumption data from the use phase for optimization of production system and machine control. The overall energy consumption of a machine tool as an example for a production system resource consists of the sum of the individual energy intake streams of all its components. The consumption of the components depends on their individual operational state, which is dependent on the overall machine state to some degree, but may show some degree of independent variation as well.

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Figure 4: Connection of the Components of the Index V100. While a few types of components provide explicit information about their current power consumption through mechanisms described later in this paper, for most of the components the power consumption is not explicitly known. In these cases, the share of power consumption of the component has to be estimated based on the mains power consumption and the states of the components using a power consumption model. To be able to separate individual contributions to the total power at the mains connection of a machine and thus to be able to identify levers that allow to optimize the machine operation with respect to energy consumption, it is necessary that the states of components are known to the control. 3.1

Classification of consumers

Different machine tools consist of different components and even in machine tools of the same type, some components can differ. In Figure 4 the components of an Index V100 turning machine and their connections to power supply and control can be seen [3]. The consumers have been associated to four color coded classes with respect to how changes in their states take place: 1. always on; 2. switched on/off commanded by machine control; 3. continuous state commanded by machine control; 4. switched on/off or continuously controlled independently; Components that are always active are for example the electronics in the control cabinet, the HMI, the PLC, the NCU and some fans or cooling devices. The consumption of these components constitutes the basic power load of the machine tool.

Some components are switched on and off by the machine control based on the current program e.g. the chip conveyer, the hydraulic pump or coolant lubricant pump. Other components commanded by the machine control are the feed drives and the main spindle. These have a continuous state, depending on the requirements of the process on the machine tool. But the current process can also influence the power consumption of switching components, e.g. the coolant lubricant system. The states of the switching components without connections to the machine control are unknown to the machine control. For these, the state has to be estimated by a mean value or a behavior model for the component is necessary in addition to the energy consumption model. This is possible for components like cooling devices, which are switching based on temperature, but impossible for components like machine lamps, which are switched on and off by the user. 3.2

Model based energy consumption prediction

One goal of the ECOMATION research group is the implementation of simulation models in the machine control in order to be able to operate the machine in an energy optimal way by the use of energy control loops. To reach this goal, machine component models which calculate the energy consumption are developed and different operational states to which components can be set are defined [4]. Figure 5 shows the information flow between the machine control, the components and the models. The sum of the energy consumption of each component for the momentary actual machine state thereby results in the overall energy consumption of a machine.

Figure 5: Information flow between the machine control, the simulation models and components.

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Sustainability in Manufacturing - Methods and Tools for Energy Efficiency

As there is no simple direct relationship between energy consumption and performance of a machine on the one hand and process and machine parameters on the other hand, model based optimization is studied in the ECOMATION project as a means to achieve minimum energy consumption operation of resources. Modular simulation models are developed to be able to identify and assess the influence of different controllable parameters of each machine component and to allow calculating the effects variations of the controllable parameters of the component have. To make sure that model based optimization can be applied despite limited computational capabilities of component and machine controls, the energy consumption models are designed as input output models which receive the control quantity from the machine control and output the resulting energy consumption of the component. In this case the term “component” denotes the whole regarded functional unit which includes the combination of different single components as shown in Figure 6.

component model control commands e.g.: flow rate

energy consumption electric motor

cooling valves tool lubr. pump functional unit

Figure 6: Component model structure coolant system example. Although often one component of this functional unit describes the “controllable” single component – a speed controlled electric motor in most cases – the interaction between all sub-components in the functional unit is responsible for the resulting energy consumption. In addition to that, aggregate models are composed from individual functional units. In the example case of a speed controllable cooling lubricant system, the component simulation models from one work package of the ECOMATION research group are combined with a model from another work package which focuses on the cutting process. Both models together are then used to determine the optimal operating point of the pump by combination of the necessary and optimal pressure and flow rate for the particular machining process within the energy control loop. A major challenge at the beginning of operation of a new resource or at the beginning of a new or modified kind of operation is that the influence of the controllable parameters on the process and the energy consumption is often unknown or known only with a large margin of error and that a detailed energy consumption profile study based on dedicated test cycles, test machining operations and laboratory measurements is mostly not possible or too elaborate. Therefore, the ECOMATION research group aims to combine verified structural models of the energy consumption behavior of components, the processes and interdependencies with a validation of the models based on measured data. Systematic studies of the influencing factors and components are essential, but model parameters are identified automatically during the use phase, thereby creating information feedback in energy control loops. 3.3

Digital field busses in energy consumption identification

A basic way to identify energy consumption models online in machine controls consists of measuring the total power intake at the mains connection and correlating it with the vector of machine states at each point of time. This approach is suitable for deriving model knowledge for simple cases of the consumers introduced in Section 3.1. However, this approach is limited to coarse models that map simple, more or less static relationships and cannot easily be detailed any further.

An alternative approach for components with a more complex behavior is based on digital field bus communication mechanisms. A digital field bus provides an interface for components to communicate aggregate information about actual energy consumption values in different energetic states. In this way, the complex problem of separating all different influences on the overall energy consumption of a machine or production line is broken down into the much less complex problems of identifying component models locally and combining them into aggregate models. If the behavior of the complex components of a machine is identified by the component controls, it can then be subtracted from the mains power intake, and the remaining power consumption can be broken down more easily in identification. For many components, it has become clear that a suitable approach to model its energy consumption behavior is based on a number of discrete states together with a few continuous state variables. An energetic state of a component needs to be described by the corresponding average energy consumption, how much time is necessary to change to the energetic states, how much energy is necessary for changing to and from the energetic states and the minimal and maximal time of stay [5][6]. Depending on the component the values provided by the energetic states can be either static or dynamic. For example a pump which can only switched ON and OFF would provide two static energetic states assuming the energy consumption and the changing time between states is always constant. The energetic states of a controlled cooling module on the other hand would be dynamic as the time to reach a thermally stable operating condition depends on the temperature and thus on the time and intensity of activity. Following this approach, the control acquires the model of all energetic states of a component and the energy consumption in these states during the initialization of the machine. If the energetic state is static the information can be used during the whole production period. If the energetic state is dynamic all information has to be updated repeatedly in the way described in Section 2. Based on the information provided by the energetic states a control can decide if an energy reduction based on the present state of the machine is possible. If this is the case functionality is required to force the component into the energy optimal state. Similarly, local energy saving algorithms can be run on component controls in combination with supervisory control running on the machine control PC. These aspects are detailed in Section 5. 4

COMMON FRAMEWORK FOR ENERGY OPTIMIZATION

Based on the information provided by direct measurements, smart components and simulation models described above, it is theoretically possible to pre-calculate the overall energy consumption of machines and other resources for different settings. A problem that remains to be solved is how the different component models, measurements and information provided via field bus functionality can be integrated into an energy optimizing control. One possibility would be to hard-code energy calculations into the PLC or NC, while another possibility would to exchange data between the PLC/NC and a dedicated optimization application or to exchange data with an external PC. Each manufacturer provides different possibilities of integrating own functionalities into the machine control. Siemens control allows to integrate user functionalities written in C++ using compile cycles [7]. The Beckhoff TwinCAT ADS provides the possibility to exchange data between control and components and a user application through shared memory. Using the IndraMotion MTX from Bosch Rexroth it is possible to integrate user C-code using job lists to access control internal data and integrate new functionalities.

Sustainability in Manufacturing - Methods and Tools for Energy Efficiency

351

It becomes obvious that the option of hard-coding energy monitoring and optimization functionality into an existing numerical or logic control would severely limit the impact of that solution to a small share of machines and components. If entire glocalized manufacturing systems were to be controlled based on this approach, a very high effort would have to be invested into creating similar and interoperable monitoring and control capabilities for a large number of brands on the market. From previous standardization exercises it has become clear that widespread collaboration among control manufacturers to create interoperable solutions is unlikely.

Another approach is shifting the place of the decision one layer down to the component control itself. The machine control thereby informs the component about boundary conditions, e.g. a pause time, and the component control decides locally by itself what state or switching trajectory within the given boundaries is most efficient. In such an approach the control may retain the capability to access information in the component and command an early wake up in case the pause time is changed by a superior control level. This approach can only be realized with smart components that are connected through a digital field bus and provide the necessary communication mechanisms for detailed model information.

Based on these considerations the ECOMATION research group proposes to create a generic energy monitoring and control solution and to combine it with a simple framework that makes the different access mechanisms of different components and controls available through a unified framework. A mechanism supported by most machine controls of many manufactures is OPC (OLE for process control). OPC provides a communication mechanism to exchange data between the different controls and user applications [8]. Although it is supported by different manufactures, the data available via OPC differs for each machine control. OPC allows separating the power consumption monitoring system physically from the machine control because the data exchange is based on DCOM using a TCP/IP network. Therefore, a common power consumption monitoring for different machine tools could be realized based on OPC with limited platform specific development.

5.2

5

ENERGY CONSUMPTION CONTROL

Once a common platform is established for accessing energy consumption data and controllable states and parameters that allow to influence the energy balance of production machines and other resources in a unified manner, the energy control loops introduced in Section 2 can be realized by implementing energy minimizing optimization solutions on all levels of control. The optimization of the energy efficiency of production systems includes the improvement of process and production planning and the reaction to shortterm variations in operation conditions. Short-term variations can only be detected and controlled in the machine control. To ensure a demand-oriented, energy-optimal operation, energy control loops are created to be able to set components in the energy-optimal state depending on the actual production program. The objective of these loops is not only the definition of an energyoptimal machining process by calculations of the expected energy consumption in advance, but also a continuous process to optimize the machine’s energy consumption during machining, regarding the interaction among the components and the process itself. 5.1

Component level energy control

Depending on the component type, different energetic states can be adopted. Several components may only be set in two states: on and off. In these cases, optimization results in a schedule at what time the components’ function is needed and when can it be switched off. For components which are always in an optimal operating point when they are active, this kind of control may already be sufficient. In other cases the component load varies along the machining cycle. Then controllability of the component in different states or with continuous parameters is much more suitable. Setting single components to energy optimal states can be done in different ways. The most common approach for most components in the near future will be direct enforcing of an energy state. The machine control gathers all required information and then orders each component to switch to a particular state which is considered to be energy-optimal based on the energy model and objectives.

Energy control functions on the individual machine level

To be able to optimize the machine operation for energy efficiency, a module in the machine control is required that interprets NC code, production line commands, e.g. about idle periods, PLC information, and the information provided by the components. By combining all of this information, the energy-optimal state of the machine can be identified and set. NC code can be monitored by an observer which will analyze the code in advance. PLC information needs to be analyzed by the module to receive information about components that are not addressed by the NC code. Cyclic processes like work piece transportation and NC code execution start and stop orders can be interpreted. The module will receive idle times from the production planning level and provides information to it. Based on this information the machine and its components are set to energyoptimal states directly after finishing the last command. If a component is not used for a period of time the module will check if another energetic state is more optimal, send the component to the state and wake it up in time. In case of an unexpected machine failure which will last over a critical threshold the production planning tool needs to be informed [4][5][6]. The machine control is also the level where real time machining process control functions are situated. These functions detect variations in the machining conditions and react by selecting energy optimal parameters in real time. 5.3

Production system level energy control

A single manufacturing resource is not able to detect disturbances in the flow of material, in a peripheral system, or at an upstream station. Thus, the manufacturing resource cannot initiate measures, and a central management system is needed. On this level, the energetic optimization of the entire process chain including possible peripheral systems can be realized. In view of overall planning, it is important to distinguish between the tasks “detailed scheduling and process control” and “long-term planning” (Figure 7). Detailed scheduling and process control is usually a functionality of the Manufacturing Execution System (MES) and consists of the anticipatory consideration and the reaction to unexpected occurrences. Supervisory control could e.g. switch downstream stations into a standby mode based on upstream machine states and a model of the temporal and causal relationships between the stations. Here the real-time capability is a central feature [9]. Long-term planning considers a longer period of time and is a prerequisite for detailed scheduling and process control. Based on the required product characteristics, processes and resources are selected. In a further step, capacity and layout planning will be executed. We have presented an approach for a model-based energy efficiency optimization for production planning in based on linking the material flow simulation of the process chain with statebased energy models of manufacturing resources [10]. This allows optimizing various organizational aspects of production in relation to low energy consumption. It turned out that an enormous energy saving potential lies in the organizational optimization. Currently, in the research group ECOMATION these models are extended to particular shift patterns, peripheral systems and other factors.

352

Sustainability in Manufacturing - Methods and Tools for Energy Efficiency system control. Energy control loops which push the manufacturing system towards energy optimal operation within the boundaries set by the process and production task are created by extracting model information about the actual energy consumption behavior from the data that becomes available and using this model knowledge for optimization. Communication and generic framework solutions are identified to be crucial components of such a decentralized system. Energy savings that can be realized with the proposed multilevel monitoring and control system depend on the production scenario and on the capabilities of previously installed equipment for autonomous demand driven self-regulation. We expect that savings may lie in the order of magnitude of above 50% for cases of typical nonadaptive high performance machines are operated with large production system load variations to below 10% for machines with selfregulating components operated in stable mass production.

Figure 7: detailed scheduling and long term planning. 5.4

Further research of ECOMATION will be conducted to realize the elements of the presented theoretical solution and evaluate the system’s performance, stability and robustness.

Level spanning communication for energy optimization

The exchange of energy model data among factory-, line- and machine-controllers for detailed scheduling and process control based on actual energy consumption requires a common interface which fulfills the requirements of scheduling and process control:

7

ACKNOWLEDGMENTS

The work presented was funded by the German Research Foundation (DFG) in project FOR1088 “ECOMATION”.

1. The time-discrete, quasi-continuous capturing of readings

8

2. The event-discrete data collection and communication

[1]

Zulaika J.; Campa F.J.; Altamira J.A.; López de Lacalle L.N.; Urbikain G. (2009): Using Stability Lobe Diagrams for the Redesign of a Machine-Tool based on Productivity and Ecoefficiency criteria”, Proc. 12th CIRP Conf. of Modelling of Machining Operations, Spain.

[2]

Verl A.; Abele E.; Heisel U.; Dietmair A.; Eberspächer P.; Rahäuser R.; Schrems S.; Braun S. (2011): Modular Modeling of Energy Consumption for Monitoring and Control, Proc. 18th CIRP Int. Conference on Life Cycle Engineering LCE 2011, Braunschweig, Germany (submitted for publication).

Thereby, 1 defines a monitoring and 2 a messaging system. On the one hand, the monitoring system is needed to perform the continuous energy data collection and include it with time stamps in the production management system (e.g. MES). On the other hand it provides the functionality of a messaging system, being the core functionality of the communication architecture. It enables bi-directional communication between machine controls and the management system on the production system, factory and production line level. In bottom-up messages all communication of a hierarchically lower level to a higher level are summarized. This corresponds to communication from machines to the higher-level management system. Top-down messages are defined as communication which is directed from a hierarchically higher level to a lower level, i.e. from the management system to the machine. To keep the data volume low, transparent communication is an important prerequisite. A first prototype of such a system-wide communication architecture is being developed in ECOMATION. OPC is currently being evaluated for multi-level Monitoring and Control of Energy Consumption of a process chain including the peripheral systems (Section 4). It covers the exchange of the following information: 

Timestamp (date on which the message was issued);



Station (code of the sending respectively the receiving facility);



Status (current status of the machine in bottom-up messages);



Message code and, if applicable, data body;

OPC communication follows a mailing principle which allows a cross-level communication where OPC items are stored on a server and each participant can access its own inbox and output. 6

[3]

INDEX GmbH (2007): V100, Stromlaufplan, Esslingen.

[4]

Dietmair A., Verl A., (2010): Energy Consumption Assessment and Optimisation in the Design and Use Phase of Machine Tools. 17th CIRP International Conference on Life Cycle Engineering (LCE2010), p. 76-82, Hefei, China.

[5]

Schlechtendahl, J. (2010): Whitepaper SERCOS Energy, SERCOS International e.V., pp. 6-7, Süssen, Germany.

[6]

PROFIBUS Nutzerorganisation e.V. (2010): PI White Paper: The PROFIenergy Profile, pp.10-11, Karlsruhe, Germany.

[7]

Siemens AG (2007): SINUMERIK 840D Integrated Monitoring and Diagnostics (IMD), User’s manual. Erlangen.

[8]

Iwanitz F.; Lange J. (2001): OLE for process control: Grundlagen, Implementierung und Anwendung. Hüthig Verlag, Heidelberg.

[9]

VDI 5600 Blatt 1 Fertigungsmanagementsysteme – Manufacturing Execution Systems (MES), VDI Richtlinien 2007.

[10]

Dietmair, A.; Haag, H.; Böck, J.; Rahäuser, R. (2010): Model based energy efficiency optimization for planning and Control, Third International Conference on Eco-Efficiency, Egmond aan Zee, Netherlands.

SUMMARY

This paper gives an overview of the results of the first year of work in ECOMATION research group of developing a generic architecture for multilevel energy consumption monitoring and control. The presented solution is based on the concept of decentralized, hierarchic optimization and relies on mechanisms in component, machine, production line, factory and factory spanning production

REFERENCES

9

CONTACT

Jan Schlechtendahl ([email protected]) Institute for Control Engineering of Machine Manufacturing Units (ISW), University of Stuttgart

Tools

and

Green Performance Map – An Industrial Tool for Enhancing Environmental Improvements within a Production System 1

1

1,2

2

Karin Romvall , Martin Kurdve , Monica Bellgran , Joacim Wictorsson 1

School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna, Sweden 2

Haldex AB, Sweden

Abstract Empirical findings indicate a need of support for environmental management within the manufacturing industry for improving the environmental performance of their production systems. This paper elaborates on a generic, three step visualization tool, here called Green Performance Map (GPM). The GPM adds to the framework of ISO 14001, providing the user with a systematic procedure to visualize environmental performance in order to facilitate the identification, prioritization and communication of relevant environmental aspects. The results are based on theoretical studies and an extensive case study at a Swedish automotive company. Pilot tests indicate a vast potential for the GPM tool. Keywords: Environmental Management System (EMS); Lean and Green Production; Decision and Communication Support

1

INTRODUCTION

Environmental concern has risen as an important topic in management research as well as within the manufacturing industry implying that manufacturing companies now need to operate a business that is competitive as well as sustainable from a social, environmental as well as economical perspective. The realization that environmental sustainability should not only be viewed from a regulatory or cost perspective has implied a dramatic change of focus when creating competitive strategies. Stakeholders such as regulators, customers, shareholders, and employees are now pressing manufacturing companies to find new ways of improving the environmental performance of their production systems [1]. To achieve this, there is an increased interest in corporate activities * aimed at reducing or eliminating the waste created during the production, use and disposal of products [2]. Today, merely being ISO 14001 certified is not enough [3] in order to reach the required environmental performance level. Even though ISO 14001 supplies a good framework for environmental work, management needs support in order to engage employees throughout the organization and thereby improve the companies´ overall environmental performance. Gaps that have been identified include support for; identification of environmental aspects within the production system, prioritization of these in order to settle on relevant focus areas for improvement as well as communication of environmental information to increase employee commitment. Adding value to operations by a lean and green initiative is one step in the right direction. Even so, an earlier study [4] indicate that the situation at many Swedish manufacturing companies today is characterized by environmental responsibility exclusively being held by environmental experts and thereby not integrated in day-to-day operations (which is advocated by the lean philosophy). Further, the fact that environmental information is often compiled in not-socomprehendible format implies a perceived complexity which limits a general understanding and thus increased commitment. For this reason, making environmental information easy to understand, and thereby accessible to all, as well as focusing the organization *

towards environmental improvements will be crucial in order to take a step forward. To overcome some of these challenges facing industry in their strive to improve, this paper presents a support tool, here called Green Performance Map, developed with the purpose to visualize environmental performance in order to facilitate the required identification and prioritization of environmental aspects as well as succeed with efficient communication of relevant environmental information. 2

RESEARCH DESIGN

The purpose of the research presented in this paper has been to provide support for environmental management in industry. A study designed as an extensive single, participating case study was performed during 2010. The case study allows for an increased understanding of the topic since it investigates a contemporary phenomenon in depth and within a real-life context [5]. A Swedish automotive firm was chosen as the object of study. The studied company, Haldex AB, is a provider of product solutions to the global automotive industry, with a focus on products in vehicles that enhance safety, environment and vehicle dynamics. The company consists of three divisions with R&D, manufacturing and sales worldwide. Haldex has identified green manufacturing as a possible order winner in the future, which is why the company is eager to find new ways of improving their environmental performance from a production system point of view. The company has also implemented a lean production program, called the Haldex Way, enabling reduction of waste in the production system. The study was performed at the company´s two Swedish manufacturing sites whose manufacturing activities primarily include metalworking, assembly and testing operations. Both sites are ISO 14001 certified. To increase the reliability and validity of the research findings a variety of sources was used for data collection. To collect theoretical evidence, a review of related research within the area of environmental management and green manufacturing has been

In this study, waste is viewed as a wide concept including both lean and green aspects.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_61, © Springer-Verlag Berlin Heidelberg 2011

353

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Sustainability in Manufacturing - Selected Applications

performed. The result of the literature review is summarized in section 3. The methods of empirical data collection have primarily been focus group interviews, workshops and document reviews. Initially, semi-structured focus group interviews were conducted with various company representatives in order to clarify the limitations with the current way of working. In addition, relevant existing models and tools were reviewed and analyzed for strengths and weaknesses. For example, a benchmarking study in search of best practices was performed at the Volvo Group, which is considered to be among the environmental leaders of Swedish manufacturing industry. To organize the work, six workshops were held for which a project group was created, consisting of in total seven primary members (including environmental and operational management representatives as well as researchers). The workshops were designed as both forums of discussion and work meetings to develop the proposed tool. Table 1 below gives additional information about the workshops. Workshop number

Number of participants

Length (time)

1

5

4h

Initial discussion and problem statement

2

5

6h

Review of existing models and tools + initial GPM tool development

Focus

3

5

5h

GPM tool development

4

20

2h

GPM tool discussion

5

7

2h

GPM tool refinement

6

7

2h

GPM tool evaluation

Table 1: Workshop characteristics.

improvements. The overall purpose of implementing an EMS is to improve the organization´s environmental performance. One important part of the planning phase is the identification of significant environmental aspects, i.e. elements of an organization’s activities or products or services that can interact with the environment. However, it is up to each company to decide how to identify aspects and prioritize these to decide which are significant. Further, companies need to establish, implement and maintain procedures for internal and external communication. How to communicate environmental work also has to be determined by each company. Hence, support is needed in both these areas. According to ISO 14001, environmental performance is the measurable results of an organization’s management of their environmental aspects. The performance measuring is further dealt with in ISO 14 031 and upcoming ISO 14 051 but no explicit performance goals are provided by these standards. ISO 14 031 has incorporated the standard for Environmental Management Accounting (EMA), which focuses on the physical flow of water, energy and material into products, emissions and waste as well as the associated cost driven by this physical flow [9]. ISO 14 031 defines internal environmental performance indicators of two types [10, 11]: 

Management performance indicators (efforts)



Operational performance indicators (physical performance)

For example, efforts include costs, whereas physical performance contains resource use. ISO 14 051 is the upcoming standard for Material Flow Cost Accounting (MFCA). MFCA specifies the input in terms of water, energy, raw material and auxiliary material and their respective costs. The output is divided into Product Output and Non Product Output (including material waste, waste water and emissions). Capital material such as buildings and equipment are not used in the material balance but can be accounted for in other ways within MFCA [12]. 3.2

3

FRAME OF REFERENCE

A production system typically determines several environmental impacts such as unrestricted exploitation of non-renewable natural resources, over-exploitation of renewable resources, contamination of soil, water and air, generation of and emission of greenhouse gases [6]. The now well known concept of green manufacturing focuses on long-term thinking and according to van Berkel et al. [7], it advocates reduction or even prevention of pollution to air, water and land and waste at source, as well as to minimize risks to humans and other species by continuously working with the integration of environmental improvements in processes and products. They further state that underlying principles to reach the environmental goals on a process level are e.g. the reduction of energy use, reduction of material waste and emissions and use of recyclable material. 3.1

ISO 14 001 as a framework for environmental improvements

ISO 14 000 is composed of a series of international environmental standard with the goal to enhance environmental consciousness within organizations by helping them manage and evaluate environmental aspects of operations. The standards provide a construct for demonstrating commitment to environmental protection, sustainable development and continual environmental improvements. The ISO 14 001 standard [8] is an Environmental Management System (EMS), comprising the phases Environmental policy, Planning, Implementation and operation, Checking and Management review and should result in continual environmental

Achieving synergies through Lean and Green

Lean production has its origin in the Toyota Production System (TPS), described by e.g. Womack and Jones [13], and the concept is widely spread in industry. Lean production is a management philosophy with a long term perspective focusing on e.g. value creation through waste reduction. Several studies investigating the relationship between lean production and green manufacturing have been performed, e.g. [14-16]. Even though the positive synergies identified are numerous, some argue that lean production alone is not able to address all environmental issues [17]. Practicing lean production supports the elimination of certain kinds of waste, but there are still blind spots related to environmental issues [18]. Without a clear focus on environmental improvements, potential advances can easily be overlooked. Further, separation of responsibility [19] may be an area that impedes the possible synergetic effects from “lean and green” efforts. It is important to generate initiative among everyone in the organization to constantly adapt, improve, and keep the organization moving forward [20]. This refers to the lean principle of employee involvement and enables the company to increase commitment to environmental work. For example, Hanna et al. [19] suggest that work teams should be freed to pursue projects with environmental goals because such projects frequently also improve operational performance. 3.3

Enhanced environmental management through visualization

Visual representations intend to make information easier to grasp, emphasize crucial points and involve the observers, simplifying dayto-day interactions [21]. Visualization is an aspect of great

Sustainability in Manufacturing - Selected Applications importance to lean practitioners. The aim is to make information easy to see and understand, e.g. by reducing the amount of reports and trying to summarize information to one piece of paper [22]. The lean toolbox includes many useful methods and tools for continuous improvements. Value Stream Mapping (VSM) is a comprehensive visualization tool commonly used to illustrate the main processes (and their operations or sub processes) together with lead times, buffers and information flows [23]. According to Braglia et al. [24] it is one of the best tools to map a process and to identify its main criticalities. To further enhance the tool, the US Environmental Protection Agency (EPA) recommends incorporating environmental considerations into VSM. This provides a modified VSM, presenting environmental impact in addition to traditional lean aspects. [25] A common way of visualizing resource flows is input/output (I/O) models (see Figure 1). Hence, these can e.g. be used to represent a production system. According to Hubka and Eder [26] a system has the function to transform certain inputs to desired outputs and can both consist of sub-systems and itself be part of a supersystem in a hierarchical structure.

Figure 1: A simple input/output model. One of the most referenced I/O models is the IDEF0, which is a structured approach for graphical representation of complex relationships. However, Ang et al. [27] state that the process of IDEF0 modeling can be time-consuming and inconsistent. Another I/O model for visualizing the material flow is the Sankey diagram. Schmidt [28] acknowledges that this is an important aid in pointing out inefficiencies and potential for savings in connection with resource use. He states that for the purpose of management, economic value of the energy, material flows and information from cost accounting may be included. Hence, the use of flow charts showing added value or the costs of energy and material flows is particularly important for production systems.

4

EMPIRICAL FINDINGS

One challenge that has been identified during the case study is how to increase the maturity in the organization regarding environmental work. Findings indicate a common view of the phases of environmental maturity, illustrated by the steps in Figure 2 below.

355 communicating appropriate focus areas on different levels. Many organizations refer to ISO 14001 certification for their environmental work, but confusions may exist around its general purpose and content. Findings indicate that, even though ISO 14001 constitutes a good framework for environmental improvements, certification alone does not guarantee that an environmentally sustainable system is created. Common challenges connected to ISO 14001 are identification of environmental aspects, determining what aspects that have a significant impact on the environment and communicating environmental information. Including cost in environmental work provides a basis for decision making. However, accounting by the means of MFCA or EMA may be difficult to grasp for non-experts and the result has to be explained and communicated to decision makers and employees in order for it to be a useful decision support. Further, environmental reports are often hard to understand implying a perceived complexity which limits a broader understanding. Findings indicate that one way of making environmental information easy to see, understand and communicate is visualization. Lean and green is considered a promising concept for employee involvement and improved communication. Nevertheless, even though VSM is often a favored visualization tool, empirical findings indicate that it may be hard to include more than two or three environmental aspects with a Green-VSM, making it difficult to indicate what aspects to focus on. The tool can also be hard to grasp for someone who has never used the methodology before, and it often includes too much detail on aspects that are not relevant from an environmental perspective. Regarding I/O models, graphical IDEF0 is still perceived as a specialist tool. It is beneficial when used to divide complex flows to few, simpler units, but unsuitable for situations characterized by simple flow patterns with high material complexity and diversity, which is the case for environmental aspects. The visualization support is also considered as inadequate. Sankey diagrams are common if there is homogeneity of materials going into the process, for energy mapping or where there are several different sub processes. However, the tool is of limited use when several different materials are included in one process. It is also time consuming to draw why it is not commonly used in environmental reporting or internal visualization. Based on the findings, the project group determined that an improved support tool for environmental management, overcoming current challenges identified, should be developed. 5

Figure 2: Environmental maturity – common steps identified. However, the situation at many Swedish manufacturing companies today is that environmental responsibility is often solely held by environmental experts. Further, the fact that environmental information is often compiled in a not-so-comprehendible format implies a perceived complexity which limits a general understanding. Since the area of green manufacturing is wide, this complexity implies a challenge related to identifying and

DEVELOPING THE GREEN PERFORMANCE MAP (GPM)

The purpose of developing a tool for environmental management was to enhance environmental improvement by providing improved support for communication of environmental information as well as for decision making. With an existing visualization graphics as a baseline, the project group began outlining a specification for how to support the improvement environmental awareness and general understanding based on the use of visualization as a means of communication. Important tool characteristics included “simple to understand”, “easy to use”, comprehensive as well as “resourceefficient”. A draft for an environmental management support tool was developed and later pilot tested at the two case company sites as well as at one of the benchmarking company sites. After this, a generic tool, here called Green Performance Map (GPM), could be finalized. The GPM is visual, adds to the framework of ISO 14001, is based on the principles of lean production and uses the system structure of an input/output model. The eight categories included (illustrated in Figure 3) are derived from environmental aspects in green

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Sustainability in Manufacturing - Selected Applications

manufacturing, lean VSM features, as well as categories of MFCA and performance indicators included in EMA. Risks and impact on human health are not always considered as environmental aspects, but these issues are in most cases connected to general environmental aspects. Hence, if data is available for different human health aspects, these could, optionally, be included in the GPM as further discussed in section 6. All aspects to the left are inputs to the chosen process and all aspects to the right represent outputs, as illustrated by the arrows.



A map of the current state is created by inserting applicable environmental aspects under each of the eight categories. Each box represents one environmental aspect and an example for the aspect “electricity” is highlighted in Figure 4. The aim is to cover all environmental aspects of the chosen process and include these in the GPM.



For each aspect, the amount and related cost should be specified wherever possible. At many companies, an environmental report can be a support in this step.

Step 2: Data analysis and prioritization ELEKTRICITET 8 819 MWh

DIESEL 5 m3

TRYCKLUFT

FJÄRRVÄRME 3 107 MWh

BENSIN 7,2 m3

TRANSPORTER

HFC 13,7 kg

STOFT PULVERMÅLN < 10 kg

LÖSNINGS MEDEL 0,2 ton

CO2 BÅTFRAKT 275 ton

RME 7,2 m3

EMBALLAGE WELLPAPP Xx ton

SMÖRJFETT 18,4 ton

MÄSSING 0,5 ton

ABA 1 516 ton

Value adding material

ALFDEX 272 ton

Productive output

LWS 8 ton

LOCTITE 0,3 m3

BLANDAT 190 ton

SMÖRJ & HYDRAULOLJA 4,9 m3 ALKALISKT TVÄTTMEDEL 2,8 m3

ADB 1 664 ton

EMBALLAGE PAPPER Xx ton

PACKNINGAR 1 ton

ROSTSKYDDSOLJA H20 0,4 m3

BULLER (Villkor)

RESERVDELAR 14 ton

Risk for human health

HÄRDSALT 14,2 ton

TRÄ 36 ton

PULVERFÄRG 2,6 ton BLÄSTERSAND 2 ton

TORKPAPPER XX ton FINPAPPER XX ton

AVFETTNINGS MEDEL L-BAS 0,4 m3

HFC 31,9 kg

SKÄRVÄTSKE KONCENTRAT 13 m3

GJUTJÄRN 476 ton

NATRIUMHYPOKLORIT 1 ton

OLJE ABSORBENTER

PAPPER 10,6 ton VERKTYGSSTÅL 0,1 ton

KOPPAR 0,1 ton

GLAS 0,5 ton

SKÄRVÄTSKA 44 ton

ALKALISKT VATTEN 78 ton

SPILLOLJA 2,4 ton

AVFETTNINGS AVFALL 2,9 ton

SLAM OLJEAVSKILJARE 12,5 ton

OLJEHALTIGT KOMPOST 9 ton

DIVERSE FARLIGT AVFALL 4,1 ton

BATTERIER 0 ton

FAST CN-HALT AVFALL 6,8 ton

SMÖRJFETT 0 ton

HYDRAULOLJA 3,25 ton

SKÄROLJA 3,8 m3

SANITÄRT VATTEN 7 750 m3

VATTEN 11 153 m3

BLANDSKROT 90 ton

PLAST 3,8 ton ELAVFALL 4,2 ton

INDUSTRIAL DEGREASER 0,1 m3 LÄCKSÖKN SPRAY 0,1 m3

OLEG STÅL 33 ton

R-FRITT 0,1 ton MÄSSING 0,3 ton

Emissions (water/soil)

Water

SMIDE 213 ton

ALUMINIUM 1,3 ton PULVERFÄRG 0,9 ton

Non productive output

WELL 32 ton

Non value adding material

CYANIDHALT. VATTEN 172 ton DAGVATTEN

BRÄNNBART AVFALL 27,4 ton

EMBALLAGE

Återvinning 901 ton

GUMMI 7 ton

CO2 FJÄRRVÄRME 74 ton

Emissions (air/noice)

Energy

EMBALLAGE PLAST Xx ton

PLAST 92 ton

CO2 TRUCKTRP 5 ton

CO2 ELPRODUKTION 82 ton

OLJEDIMMA < 200 kg

EMBALLAGE TRÄ Xx ton

ALUMINIUM 83 ton

CO2 TJ/PROVBILAR 33 ton

CO2 FLYGFRAKT 34 ton

Farligt avfall 163 ton

SINTERMETALL 70 ton

CO2 LASTBILSFRAKT 463 ton

CO2 TJ.RESOR FLYG 163 ton

STOFT METALL < 10 kg

STÅL 1 013 ton

27,4 ton 172 ton

GJUTJÄRN 2 706 ton

Figure 5: GPM – Step 2 (example). 

The environmental aspects in the GPM are reviewed and the significance of each aspect is illustrated by color (see Figure 5). The result of this step also functions as decision support for which aspects to focus on.



Green indicates no or positive environmental impact, yellow means intermediate impact, whereas red indicates a significant impact.



The environmental aspects can be prioritized according to criteria such as, comprehensiveness, cost, resources available, to what degree they can be affected etc. The format of the GPM supports this task by being visualized, comprehensive and structured and thereby easy for all to follow.

Figure 3: GPM structure with eight primary aspect categories. The aim of the GPM is to provide environmental communication and decision support for environmental and operational management. By reducing the perceived complexity regarding environmental work through visualization, the GPM tool both encourages commitment among all staff and supports decision making by making it easier to identify and prioritize environmental aspects. By implementing focused improvement activities for these aspects, the company can improve their environmental performance from a production system perspective, thereby adding value to environmental work. 5.1

Step 3: Action plan

The GPM tool

Activity

The tool consists of three steps, which are described in more detail below. For each step, a figure illustrates a visual example from a pilot test at the case company. Hence, the text in the GPM in Figure 4 and 5 is not supposed to be readable in detail.

Now

Incl packaging in BOM

<3mths

<1y

<3ys

<5ys

◘

Environmental training (all)

Step 1: Process mapping through flow visualization

<6mths

◘

Replace machine Z

◘ Figure 6: GPM - Step 3 (example).



An action plan is developed with activities for how each prioritized environmental aspect should be improved. The activities should be developed both on short and longer term perspective as the example in Figure 6 illustrates.



Responsibility for each activity is distributed in order to assure implementation.

5.2

How to use the GPM tool

The GPM can be performed as current state and future state (goals) in line with the lean tool VSM. Since the GPM is developed to be generic, the tool can be used at different levels in the production system, from site level to a specific process or operation. Figure 4: GPM – Step 1 (example). 

The visual GPM structure is used as a template and support for identifying environmental aspects of the chosen process.

Sustainability in Manufacturing - Selected Applications

357 Even though this paper suggests a division of environmental aspects in eight categories, it might be suitable for companies with a lower degree of environmental maturity to begin with a lower number of aspect categories. One example found at the benchmarking company was a simpler model, using only four categories; energy, waste, emissions and water.

Figure 7: The GPM tool at different levels.

During workshop discussions and benchmarking activities regarding the eight categories, an optional ninth category: “human health” was suggested. In this category, in its simplest format absenteeism (in lost hours) and the corresponding cost should be included. If there is data available this should be broken down into different health impacts, e.g. absence due to: accidents, injuries ergonomics, chemical exposure etc. as illustrated in Figure 8.

As illustrated in Figure 7, the GPM tool can be used bottom-up (adding the impacts from each operation in the process) as well as a top-down (breaking down the overall impacts from an entire plant into the different processes). 6

ANALYSIS AND DISCUSSION

One challenge identified at the case companies is a perceived complexity regarding environmental work, which limits a general understanding. Here, the GPM tool is able to fill a gap. The visual format of the GPM enables better communication by making environmental information easier to understand. Hence, using the GPM tool will promote an improved general awareness, enabling employees to understand how they can contribute to a reduced environmental impact and, in turn, initiate environmental improvement actions. Further, the visual aid when identifying and prioritizing environmental aspects also supplies an improved support for decision making since it facilitates the choice of focus areas for different parts of the organization. Subsequently, appropriate improvement activities can be decided upon for each process, according to the significance of the impact at different levels. In many cases, red impacts probably require more urgent or comprehensive actions while yellow might involve monitoring or continuous improvement actions. The result of the GPM can fit on one page (in line with Toyota´s project management philosophy) and thereby it constitutes a good foundation for efficient improvement meetings. The holistic perspective supports strategic, long term planning of environmental improvement work as well as short term action. Even though an impact is marked as red (significant), there may be limitations in e.g. available technology impeding environmental improvements. Therefore, it is crucial to develop an action plan with different time perspectives, e.g. immediate actions, within 1 year, within 3 years, within 5 years or for the next time an investment in new equipment or technology is made. According to the findings, cost is important to consider for decision making. Resource use is crucial to measure in order to set targets that can be followed up in order to assure that improvements have occurred. If e.g. a full scale MFCA or EMA is available, including cost in the mapping of environmental aspects makes the GPM a more powerful tool for decision making, implying where the largest environmental costs are present. Thereby, it can give an indication to where cost saving potential can be found. For external costs this is usually simple. However, internal costs are often hidden in overhead and harder to attain [29], implying that total costs are often underestimated. Of course, the GPM can be used to visualize environmental aspects as such without MFCA or EMA, since information can be added as the company learns more about their environmental impacts.

Figure 8: The Human health category (example). Although a top-down approach is most common in industry today, using the GPM with a bottom-up approach enables the company to get a more realistic picture of the current state as well as choose relevant focus areas for each process and set targets for these. In Table 2 below, the primary advantages and limitations of the GPM tool are summarized. Advantages (+)

Limitations (-)

Fits in the ISO 14001 framework, including EMA and MFCA

How to prioritize aspects not included

Supports systematic inclusion of all environmental aspects

Environmental risks primarily not included

Facilitates strategic, tactic and operational improvements.

Much background data required

Generic structure

Internal costs may be hard to attain

Simple/easy to understand

Further testing needed

Supports communication of environmental information

Table 2: Advantages and limitations of the GPM tool. 7

CONCLUSIONS

In the research described in this paper, current challenges regarding environmental work at the studied companies were mapped. The findings indicate a growing need for environmental management support adding to the ISO 14001 framework. Environmental work has been perceived as complex and hard to understand, leading to reduced commitment, limiting environmental improvements. To develop simple to use and easy to understand support, visualization was regarded as crucial to be able to engage personnel and succeed in continuous improvements. During a number of workshops a support tool for visualizing environmental aspects, here called Green Performance Map (GPM), was developed and pilot tested at two manufacturing sites. The GPM is an input/output model that adds to the general framework of ISO 14001, builds on the principles of lean and green production, and provides the user with a hands-on tool comprising three steps. The tool supports strategic as well as operational management and can (since it is generic) be used at site, process as well as operational level. The purpose of the visual tool is to reduce the perceived complexity of environmental work in general when identifying environmental aspects, prioritizing these and

358

Sustainability in Manufacturing - Selected Applications

communicating the result. Hence, he GPM is considered to fill an important gap within environmental improvement work, enhancing environmental improvements within industrial production systems.

Production p. 339-352. Schaltegger, S., et al., Editors. Springer Science + Business Media B.V. [11]

United Nations Division for Sustainable Development (2001) "Environmental Management Accounting Procedures and Principles".

[12]

Jasch, C. (2009). Environmental and Material Flow Cost Accounting - Principles and Procedures, Springer Science + Business Media B.V., Vienna.

[13]

Womack, J. P.; Jones, D. T. (1996). Lean Thinking, Simon and Schuster, New York.

[14]

Bergmiller, G. G. (2006), Lean Manufacturers´ Transcendence to Green Manufacturing: Correlating the Diffusion of Lean and Green Manufacturing Systems, PhD Dissertation, University of South Florida.

Future work

[15]

To improve the performance and features of the GPM tool, further development of the model is needed. One important issue is how to prioritize environmental aspects and activities. Also additional testing will be necessary for validation.

Herrmann, C.; Bergmann, L.; Thiede, S. (2009), Methodology for the Design of Sustainable Production Systems, Int J Sustainable Manuf, 1(4):376-395.

[16]

8

Herrmann, C.; Thiede, S.; Stehr, J.; Bergmann, L. (2008), An environmental perspective on Lean Production, Proceedings of the 41st CIRP Conference on Manufacturing Systems, pp. 83-88, Tokyo, May 26-28.

[17]

Rothenberg, S.; Pil, F. K.; Maxwell, J. (2001), Lean, Green and the quest for superior environmental performance, Prod Oper Manag, 10(3):228-243.

[18]

United States Environmental Protection Agency (EPA) (2003) "Lean manufacturing and the Environment: Research on advanced manufacturing systems and the environment and recommendations for leveraging better environmental performance".

[19]

Hanna, M. D.; Newman, R. W.; Johnson, P. (2000), Linking operational and environmental improvement through employee involvement, Int J Oper Prod Manag, 20(2):148165.

[20]

Rother, M. (2010). Toyota Kata: Managing People for Improvements, Adaptiveness and Superior Results, McGraw Hill.

[21]

Seifert, J. W. (2002). Visualization, Presentation, Moderation: A practical guide to sucessful presentation and the facilitation of business processes., Wiley, Weinheim.

The contribution of this research is of importance to both industry and academia. An industrial need has been identified and the GPM tool is able to fill the gap by supporting environmental management. The tool has been developed within the manufacturing industry, but the generic format developed by the authors makes it useful in different settings and also possible to adapt. Scientifically, the findings presented in this paper primarily add to the area of lean and green production. The GPM concept adds to the recent development of MFCA with support for visualization that can make MFCA available to others than environmental management system experts and thus be useful in operations management.

ACKNOWLEDGMENTS

The authors would like to express their gratitude for the time and cooperation of the participating representatives from Haldex and Volvo. Further, the financial support to the research project Green Production Systems supplied by the Swedish Governmental Agency for Innovation Systems, VINNOVA/FFI, and the initiative for Excellence in Production Research, XPRES, is gratefully acknowledged. 9 [1]

REFERENCES Arena, M.; Duque Ciceri, N.; Terzi, S.; Bengo, I.; Azzone, G.; Garetti, M. (2009), A state-of-the-art of industrial sustainability: definitions, tools and metrics, Int J of Product Life Cycle Mgnt, 4:207-251.

[2]

Melnyk, S. A.; Sroufe, R. P.; Calantone, R. (2003), Assessing the impact of environmental management systems on corporate and environmental performance, J Oper Manage, 21:329-351.

[3]

Sarkis, J. (2001), Manufacturing's role in corporate environmental sustainability, Int J Oper Prod Manag, 21(5/6):666-686.

[4]

Romvall, K.; Wiktorsson, M.; Bellgran, M. (2009), Competitiveness by integrating the green perspective in production – A review presenting challenges for research and industry, Proceedings of the Flexible Automation and Intelligent Manufacturing, FAIM, pp. 340-347, California, USA.

[5]

Yin, R. K. (2009). Case Study Research: Design and Methods, SAGE Publications, California.

[6]

Gutberlet, J. (2000), Sustainability: a new paradigm for industrial production, Int J Sustainability in Higher Education, 1(3):225-236.

[7]

[8]

[22]

Liker, J. (2004). The Toyota Way, McGraw-Hill, New York.

[23]

Rother, M.; Shook, J. (2003). Learing to see: value stream mapping to create value and eliminate muda, Lean Enterprise Institute Inc., Cambridge.

[24]

Braglia; Carmignani; Zammori (2006), A new value stream mapping approach for complex production systems, Int J Prod Res, 44(18):3929-3952.

[25]

United States Environmental Protection Agency (EPA) (2007) "The Lean and Environment Toolkit".

[26]

Hubka, V.; Eder, W. E. (1988). Theory of Technical Systems, Springer-Verlag, Berlin.

[27]

van Berkel, R.; Willems, E.; Lafleur, M. (1997), The Relationship between Cleaner Production and Industrial Ecology, J Ind Ecol, 1(1):51-66.

Ang, C. L.; Luo, M.; Gay, R. K. L. (1995), Knowledge-based approach to the generation of IDEFO models, Comput Integr Manuf Syst, 8(4):279-290.

[28]

International Organization for Standardization, "ISO 14001:2004 Environmental management systems Requirements with guidance for use", 2004.

Schmidt, M. (2008), The Sankey Diagram in Energy and Material Flow Management. Part II: Methodology and Current Applications, J Ind Ecol, 12(2):173-185.

[29]

Kurdve, M. (2009). Chemical Management Services: Safeguarding Environmental Outcome, in Environmental Management Accounting (EMA) as a Support for Cleaner Production p. 209-229. Schaltegger, S., et al., Editors. Springer Science + Business Media B.V.

[9]

Jasch, C. (2000), Environmental performance evaluation and indicators, J Cleaner Prod, 8:79–88.

[10]

Langford, R. (2009). Environmental Performance Indicators Key Features of Some Recent Proposals in Environmental Management Accounting (EMA) as a Support for Cleaner

Analysis and Quantification of Improvement in Green Manufacturing Process of Silicon Nitride Products 1

1

Nozomu Mishima , Shinsuke Kondoh , Hideki Hyuga², You Zhou², Kiyoshi Hirao² 1

Advanced manufacturing Research Institute, AIST, Tsukuba, Ibaraki, Japan ²Advanced manufacturing Research Institute, AIST, Nagoya, Aichi, Japan

Abstract Although green manufacturing is an important issue, not only energy consumption but also manufacturing quality is important for practical industries. In this report, the enhancement in product quality, are taken into account to quantify the process improvement. In quantifying the improvement, quality characteristics are categorized to 3 types to express real material requirements. As a result, it is said that the newly developed high-speed-reactive-sintering method to fabricate silicon nitride parts is far more energy efficient than the conventional method, because the process can improve material characteristics, shorten the processing time and reduce energy consumption throughput the total process Keywords: Environmental Impact; Total Performance Analysis; Silicon Nitride

1

INTRODUCTION

AIST proposed a concept of ‘Minimal Manufacturing’ and has been trying to widespread the idea to industries. Minimal manufacturing is a similar concept to sustainable manufacturing, but strongly focuses on developing and implementing material and manufacturing technologies. The core concept is to satisfy high quality, low cost and low environmental impact simultaneously. In order to know the individual technologies in minimal manufacturing are ‘minimal’, the balance of manufacturing quality, cost and environmental impact should be evaluated. The authors have proposed [1] a method called ‘total performance analysis’ to quantify the balance of value, cost and environmental impact through the lifecycle of products, and have been trying to apply the method to find a target of improvement in manufacturing processes [2]. Former paper [3] proposed a method to quantify process improvement effect by sum of improvement in quality characteristics (material properties). However, it was pointed by material scientists that simple sum of every property does not explain the reality of material development. In this paper, the authors again choose the manufacturing processes to fabricate silicon nitride parts. Utilization of reactive sintering is effective in decreasing the cost of raw materials and improving the material characteristics [4,5]. These advantages contribute greatly in enhancing the quality characteristics of the product. Since the value of a product is expressed by weighed sum of quality characteristics, in our definition, enhancement of material characteristics is a good solution to enhance the eco-efficiency of the product. Instead of taking the simple sum of improvements of quality characteristics, the paper tries to categorize the characteristics to 3 different types. Then, different equation is applied to each type in calculating the effect of improvement. In addition, further improvement is tried in the sintering process. The improved process called high speed reactive sintering seems very helpful in reducing the energy usage in the sintering. Through the analysis, the paper tries to quantify the enhancement of total efficiency and to prove that the improved manufacturing process of silicon nitride is effective in increasing the ‘greenness’ of the target product.

2 2.1

TOTAL PEFORMANCE ANALYSIS (TPA) Basics of TPA

In the former researches, we proposed an index to evaluate real eco-efficiency of products, by considering product’s utility value, cost and environmental impact. New eco-efficiency index was defined by (1) and was named total performance indicator (TPI). Since in existing evaluation indexes the value is usually a fixed value, it cannot consider change of the value throughout the product lifecycle. The proposed index was the simplest combination of environmental and economical efficiencies. In our proposal, because the utility value of the product can be expressed by integration of occasional values throughout the lifecycle, it can simulate value decrease due to obsolescence and physical factor as shown in Figure 1.

TPI 

UV

(1)

LCC LCE

TPI: total performance indicator UV: utility value of the product LCC: life-cycle cost of the product LCE: life-cycle environmental impact of the product VI Value decrease due to obsolescene Overall value decrease curve Value decrease due to physical factor

Figure 1: Value decrease through product lifecycle.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_62, © Springer-Verlag Berlin Heidelberg 2011

359

360 Process TPI

Usually manufacturing processes are combinations of many segment processes, such as material processing, forging, finish machining, etc. In addition, there are many ways to combine processes and boundary conditions. Therefore, it is very important to evaluate which manufacturing process is really eco-efficient comparing to alternative options. We define the total performance of the manufacturing process by (2). The equation expresses the balance of the product value created by the process, versus the cost and environmental impact necessary to fabricate a product. In the manufacturing stage, it is usually difficult to know the lifecycle facts of the product such as the obsolescence rate, etc. Thus, in order to simplify the expression, we propose to replace utility value by the occasional value of the product. The simple value can be measured by the market price, when the product is commercially available. Then, (3) shows the simplified TPI of each segment process. The numerator ‘Vi’ of the equation may vary due to process quality. For example, a manufacturing process with higher profile accuracy may have a higher value than a similar manufacturing process with lower quality. Manufacturing quality also has a strong relationship between cost and environmental impact of the process. For example, it is known that cost and environmental impact of machining vary due to the cutting conditions and usually they are larger when the manufacturing quality is higher. In addition, for these reasons, in evaluating manufacturing processes, it is necessary to consider value of the segment process versus cost and environmental impact concurrently. We can quantify how the target manufacturing process is efficient, by calculating (3).



(2)

MCE i  MCC i

i 1

MCCi: Cost of ith segment process, MCEi: Environmental impact of ith segment process

MCE i  MCC i

(3)

TPIsegment: Total performance indicator of the segment process Vi: Value of the product added by ith segment process Since the TPI calculated by (3) is an efficiency index, larger TPI is better. After analyzing the manufacturing process and calculating the TPI of each segment process, it is possible to draw a TPI view graph. Segment processes with shallow inclinations are suggested to be the primary targets of improvement.

3 3.1

(4)

FRVk: value of kth functional requirement V: value of the product Uk: importance of kth FR Ti: sum of importance of all functional requirements

n: Number of segment processes

Vi

Value of functional requirements

Applying QFD [6, 7], it is possible to clarify importance of each functional requirements of a heat radiation plate. We set 5 functional requirements (FR). Table 1 shows how each functional requirement is important for customers. It also indicates the virtual price of each functional requirement. Total price of the product (assumed to be 4.2kJPY/kg) was allocated to functional requirements corresponding to importance of FRs. Value of each functional requirement can be calculated based on (4).

FRVk  V  ( u k / T )

TPIprocess: Total performance indicator

TPI segment 

3.2

PROCEDURE OF TPA OF MANUFACTURING PROCESS

FR0

Heat radiation capability

10

0.29

1.2

FR1

Hard-to-failure

5

0.14

0.6

FR2

Electric isolation capability

10

0.29

1.2

FR3

Smooth and parallel surface

5

0.14

0.6

FR4

Resistance capability against atmosphere

5

0.14

0.6

Case study; silicon nitride plate

To show an actual procedure of process TPA and improvement of a process, a practical example has been examined. As the target product we choose a ceramic heat radiation plate for power ICs whose overview is shown in Figure 2. Ceramic radiation plates are used frequently because of its high thermal endurance, high specific strength and resistance ability to wear. Some of the authors have been engaging in process improvement of manufacturing

Value of FR(kJPY)

V i n

Figure 2: Ceramic heat radiation plate.

Importance (ratio)

TPI process 

process of ceramics. One of the purposes of this paper is to apply TPA to the specific process and quantify the effect of the abovementioned process improvement. Roughly speaking, the main function of a radiation plate is to radiate heat efficiently. But, the functional requirements can be separated into more detailed 5 functional requirements (FR) such as ‘heat radiation,’ ‘electric insulation capability,’ and so on. In addition, 5 FRs are related to 9 quality characteristics that are equivalent to material characteristics. Defined FRs and quality characteristics are shown in Table 1 in the next page.

Importance for customers

2.2

Sustainability in Manufacturing - Selected Applications

Table 1: Importance and value of functional requirements.

Sustainability in Manufacturing - Selected Applications Relational matrix of functional requirements and quality characteristics

The second step of the analysis is to determine the contribution of each segment process to the value. By identifying the relationship between segment processes of the total process and the quality characteristics, it is possible to calculate the value of the segment processes. We dismantled the total manufacturing process into 6 processes. The value of each segment process is expressed by (5). Table 2 shows the results of the calculation of the segment process value.

11

QV

k

 ( x j ,k / S k )

PVj: Value of jth segment process QVk: Value of kth quality characteristic xj,k: importance of kth quality characteristic have on jth segment process Sk: sum of importance of related segment processes.

Segment process

5

Vi  (w i ,k / Ti )

3

Mechanical strength

0.33

3

3

1

3

9

Fracture toughness

0.33

3

3

1

3

9

Thermal expansion

0.13

9

3

Electric resistance

0.64

9

3

3

3

Dielectric breakdown strength

0.64

9

3

3

3

Surface flatness

0.27

1

3

Surface roughness

0.27

1

3

Corrosion resistance

0.39

9

1

1

Value of the segment process (kJPY)

0.16

1.2

Mechanical strength

9

1

1

0.33

Fracture toughness

9

1

1

0.33

Thermal expansion

3

1

0.13

Electric resistance

9

1

0.64

Dielectric breakdown strength

9

1

0.64

Surface flatness

9

0.27

Surface roughness

9

0.27

Corrosion resistance Sum

9 9

21

18

20

0.39

14

Table 2: Relation of FRs and quality characteristics. Relational matrix of quality characteristics and segment processes

The third step of the analysis is to know the contribution of each segment process on the value. By identifying the relation between each segment process composing the total manufacturing process and quality characteristics, it is possible to calculate value of segment processes. We dismantled the total manufacturing process of a DPF to 5 segment processes. Table 3 shows the result of the calculation of process value based on (6).

1

9

1

9

1

3

3 0.34

9

4.2

0.89

0.6

3

0.34

0.6

Quality characteristics

Resistance capability against atmosphere

1.2

Value of quality characteristics (kJPY)

Smooth and parallel surface

0.6

Sintering

9

Binder removal

Mixture

1.2

0.67

Quality characteristics of DPF

Heat conductivity

1.2

Electric isolation capability

(kJPY)

Hard-to-failure

Value of FR

Heat radiation capability

Functional requirements

Sheet forming

Material supply

Heat conductivity

QVk: Value of kth quality characteristic Vi: Value of ith FR wi,k: sum of importance of kth quality characteristic on ith FR Ti: sum of importance of all the related quality characteristics

Grinding

(5)

i 1

3.4

(6)

k 1

Value of quality characteristics

QVk 

PV j 

1.80

3.3

361

9

Table 3: Relation of quality characteristics and processes. 4 4.1

QUATIFICATION OF PROCESS IMPROVEMENT T Evaluation of the base process

Table 4 shows the rough estimation of cost and environmental impact of the segment processes, based on the information from manufacturing engineers. These cost and environmental impact include those of machines. Figure 3 is the TPI graph of the original manufacturing process

362

Sustainability in Manufacturing - Selected Applications Exp.

Segment process

Linear

0.34

4.2

0.5

13.8

Total

0.89 5

Grinding

Sintering

0.34 3

Binder removal

Sheet forming 0.16 0.1

Mixture 0.67 0.2

Mechanical

Electric resistance,

strength,

Dielectric

Fracture

breakdown strength,

toughness,

Surface roughness,

Thermal

Surface flatness,

expansion

Corrosion

3.9

0.8

0.6

0.2

0.8

resistance 1.1

Cost (kJPY)

0.4

Environmental impact (kgCO2/kg)

5

Value of the process (kJPY)

1.80

Material supply

Heat conductivity

Must

Table 5: Categorization of quality characteristics Table 4: environmental impact and cost of the segment manufacturing processes

4.3

Value increase

5

Value (K yen)

grinding 4

Sheet forming

3

mixture

sintering

2

binder removal

Material supply

1

0 0

1

2

3

4

5

6

7

(MCE*MCC)0.5

Figure 3: TPI of the original manufacturing process. Each segment line indicates the value after the corresponding segment processes. An inclination of a segment line shows TPI of the corresponding segment process. An inclination of a virtual line connecting between the starting-point and the end-point of the lines indicates TPI of the total process. 4.2

Categorization of quality characteristics

As it is briefly mentioned in the beginning, quality characteristics have different meanings in material development. Material scientists says there are 3 different categories. We named 3 categories as ‘exponentially important characteristics,’ ‘linearly important characteristics,’ and ‘must-have characteristics.’ Table 5 shows the categorization. These categories correspond to target characteristics that are strongly focused on, characteristics that are helpful in increasing design flexibility, and characteristics that should be satisfied automatically.

Improvement in quality characteristics

Improvement of silicon nitride manufacturing process is an ongoing research topic. Some methods to enhance the performance of the process or reduce the process time have been studied [8]. The purpose of using this process as an example is to ensure the design approach is to simulate the process improvement effect well. Therefore, it is necessary to compare with actual improvement and quantify the effect. In AIST, improvement of material characteristics of silicon nitride by using new manufacturing technology has been discussed. The new material is called sintered reaction-bonded silicon nitride (SRBSN). In the new manufacturing process, more inexpensive silicon powder than silicon nitride powder is used, because the silicon nitride structure is directly made during the sintering process with chemical reactive process. It results that the cost and the environmental impact of ‘material supply’ is reduced compared to the original process. Contrarily, those of the new ‘sintering’ process increase. Costs and environmental impacts of other processes remain the same. In addition, by using this process and inputting suitable additives, material characteristics can be greatly improved. It has been reported [9, 4] that heat conductivity, insulation resistance and dielectric breakdown strength of the product are greatly improved compared to conventional sintered silicon nitride (SSN). Especially, improvement in heat conductivity has very important meaning. Since this characteristic is the target characteristic of this device, it is evaluated by (7). On the other hand, mechanical strength decreases. Value of ‘linearly important‘ characteristics including mechanical strength is evaluated by (8) and ‘must-have’ characteristics are calculated based on (9). Table 6 shows the reported improvements in the quality characteristics, by normalizing original value to 1.

Vi  V0  Pn / P0 

3

Vi  V0  Pn / P0 

Vi  V0 ( Pn  P0 ) Vi  0( Pn  P0 )

(7) (8) (9)

Total 5.19 11.8

0.34

5.4

0.5

0.5

7

1.03

Grinding

Sintering

Binder removal 0.34

1.6

Environmental impact (HS-SRBSN)

Surface flatness

Surface roughness

Corrosion resistance

.13

.64

.64

.27

.27

.39

New Process (SRBSN)

Imprvd.

2.1

.30

.33

.23

.64

.64

.27

.27

.39

New Process (HS-SRBSN)

4.0

Dielectric breakdown strength

.33

4.2

Insulation resistance

.33

0.8

Thermal expansion

1.2

0.8

Fracture toughness

Original

1.8

Mechanical strength

Cost (SRBSN) (kJPY/kg)

1.6

(kg-CO2/kg) Cost (SRBSN) (kJPY/kg)

Heat conductivity

In quantifying the value enhancement due to the improvements in quality characteristics, we assumed that the value of each quality characteristic is linear to corresponding specification. For example, the value of ‘new’ heat conductivity is calculated to be 1.4kJPY, since it will be 1.2 times of the original value 1.2kJPY. Table 7 shows the value of the improved quality characteristics in kJPY.

Value of the new process (kJPY) Environmental impact (SRBSN) ((kg-CO2/kg)

3

Table 6: Improvements in quality characteristics.

3

1.1

0.2

1

0.2

1

Sheet forming

2.0

0.16

2.0

0.1

1.8

0.1

1

0.8

0.9

0.8

1.2

Mixture

SRBSN

0.91

1

0.2

1

0.2

1

0.4

Corrosion resistance

1

0.4

Surface roughness

1

Material supply

Surface flatness

1

2.41

Dielectric breakdown strength

1

1

Insulation resistance

1

1

Thermal expansion

1

0.2

Fracture toughness

Original

Segment process

0.2

Mechanical strength

363

Heat conductivity

Sustainability in Manufacturing - Selected Applications

Table 8: Value, environmental impact and cost of the improved segment manufacturing processes. Old process

6

The values of quality characteristics have to be allocated to values of segment processes again. In addition, a new sintering technique named high speed sintered reaction-bonded silicon nitride (HSSRBSN) has been developed by some of the authors. By using this technique, it is possible to reduce the electric consumption drastically, while maintaining the good sintering quality to achieve improved quality characteristics. On the other hand, process cost of sintering slightly increases because high quality furnace is necessary. Finally, Table 8 shows the value, cost and environmental impact of the two improved processes. Figure 4 is the TPI graph of the improved processes reflecting Table 8.

Value (K yen)

Table 7: Improvements in quality characteristics.

grinding

Sheet forming

5

sintering

4

mixture

3

binder removal

Material supply

2 1 0 0

1

2

3

4

5

6

7

(MCE*MCC)0.5

Figure 4: TPI of the improved process. The above comparison of TPI of the old process, SRBSN and HSSRBSN suggested that the material composition is the most important consideration. The ‘sintering’ of the SRBSN seems worse than that of the old process. However, it is inseparable with the new ’material supply.’ The figure indicates that the efficiency of the total process was improved. It also suggests that the further improvement should be optimization of sintering conditions in order to make the new sintering process more efficient. To answer this requirement, far more efficient sintering process named HS-SRBSN was implemented. HS-SRBSN seems very effective in avoiding the shortage of SRSBN. Finally, overall efficiency of the process indicated by TPI has been improved approximately 2.3 times.

364 5

Sustainability in Manufacturing - Selected Applications CONCLUSIONS

In the paper, a new method to evaluate manufacturing processes by applying TPA was proposed. In the former example, effect of manufacturing process improvement in enhancing product quality was not quantified well. Because the quantification method didn’t correspond to the real requirement on the quality characteristics. In this paper, the evaluation method was applied to a new example which is a manufacturing process of a heat radiation plate made by silicon nitride. In the example, by implementing the new manufacturing technology, material characteristics are greatly improved. The new material is called sintered reaction-bonded silicon nitride (SRBSN). By categorizing the quality characteristics to 3 types, total value increase was calculated. Using these data, manufacturing efficiency of the improved process was compared with that of the old process. Plus, more efficient sintering method called high speed reactive sintering was also analyzed. Quality characteristics of the material obtained by the improved process were the same as SRBSN. However, because of the much lower electric consumption of the high speed process, total efficiency indicated by process TPI was drastically improved. As future work, it is necessary to examine whether the allocations of FRs to quality characteristics and quality characteristics to segment processes are reasonable enough. In addition, it should also be questioned whether the categorization approach of quality characteristic is generally applicable. 6

REFERENCES

[1]

Kondoh, S.; Masui, K.; Hattori, M.; Mishima, N.; Matsumoto, M. (2008): Total Performance Analysis of Product Life-cycle Considering the Deterioration and Obsolescence of Product Value, International Journal of Product Development, Vol.6, Nos.3/4, pp334-352.

[2]

Kondoh, S.; Mishima, N.; Hotta, Y.; Watari K.; Masui, K. (2009): Total Performance Analysis of Manufacturing Processes, International Journal of Automation Technology, Vol.3 No.1, pp.56-62.

[3]

Kondoh, S.; Hyuga, H.; Zhou, Y.; Mishima, N.; Hirao, K. (2010): Analysis of Eco-efficiency of Ceramics Manufacturing Processes for Silicon Nitride, Proceedings of 17th CIRP/LCE.

[4]

Zhou, Y.; Zhu. X.; Lences, Z.; Hirao, K. (2008): SinteredReaction Bonded Silicon Nitride with High Thermal Conductivity and High Strength, Int. J. of Appl. Ceram. Tech., 5 [2] 119-126.

[5]

Hyuga, H.; Yoshida, K.; Kondo, N.; Kita, H.; Sugai, J.;Okano, H., Tsuchida, J. (2008): Nitridation enhancing effect of ZrO2 on silicon powder, Material Letters, 62, 3475-3477.

[6]

Akao, K. (1990): Quality Function Deployment, Productivity Process, Cambrige, M.A.

[7]

Kondoh, S.; Umeda, Y.; Togawa, H. (2007): Development of redesign method of production system based on QFD, Journal of Advanced Mechanical Design, Systems, and Manufacturing, Vol. 1, No. 1, pp.181-192.

[8]

Zhu, X,; Hayashi, H.; Zhou, Y.; Hirao, K. (2004): Influence of Additive Composition on Thermal and Mechanical Properties of b-Si3N4 Ceramics, J. Mater. Res., 19 [11] 3270-3278.

[9]

Zhu, X.; Zhou, Y.; Hirao, K. (2006): Effect of Sintering Additive Composition on the Processing and Thermal Conductivity of Sintered Reaction-Bonded Silicon Nitride, J. Am. Ceram., 89[11] 3331-3339.

Evaluation of the Environmental Impact of different Lubrorefrigeration Conditions in Milling of γ-TiAl Alloy Giovanna Rotella, Paolo Claudio Priarone, Stefania Rizzuti, Luca Settineri Department of Production Systems and Business Economics, Politecnico di Torino, Turin, Italy

Abstract Conventional manufacturing techniques have not been subject to much scrutiny by industrial ecologist to date. The implementation of environment-friendly methodologies in metal cutting is, consequently, of considerable direct economic, social and technological importance. This paper aims to analyze the milling operation of a non conventional material such as -TiAl alloy from an environmental point of view, taking into account the impact of such material removal process in its various aspects. In particular, three kind of cooling conditions, namely wet, Minimal Quantity of Lubrication (MQL) and dry have been analyzed. Furthermore, for each coolant condition, different process parameters (i.e. cutting speed and feed rate) have been considered during milling operation in order to evaluate their environmental impact. Keywords: Milling Process; Lubricants; Sustainable Production.

1

INTRODUCTION

The manufacturing processes were systematically developed and analyzed in order to achieve, through innovation, a maximum efficiency in association with economic manufacturing conditions. Nowadays the economical mass production is not enough to succeed but it is also important to adopt sustainable manufacturing practices like improving energy consumption, waste management, environmental impact, operational safety and personal health. The faster way to assure sustainability in manufacturing is the analysis of the existing processes and their subsequently modification in order to achieve environmental benefits. Among manufacturing processes, machining can be wasteful in its use of both materials and energy. In this paper, a preliminary analysis of the environmental impact during a milling process was carried out. In particular, the process has been evaluated through the measurement of the quality of the machined products, the tool life and the energy related to the different lubricant conditions. The measurements have been done at varying of lubrication methods (dry, wet and MQL), on a -TiAl sample. This “hard to machine” material was chosen since it is an attractive candidate for structural aerospace applications due to its high-strength, low density and specific weight, and good oxidation resistance[1]. Furthermore, it is well-known that manufacturing process parameters have a significant impact on the performance/life of the final product [2 - 4]. Hence, the effects of process-level changes have been analyzed in order to truly achieve reduced environmental impact over the integrated product life cycle when -TiAl alloy is machined. 2

THE ROLE OF COOLING/LUBRICATION IN MACHINING PROCESS

An individual manufacturing process can be analyzed from the environmental point of view detecting the major factors of influence and the possible alternative design of the process. In machining the most prominent environmental issue is the profligate use of cutting fluids (CFs) or metalworking fluids (MWFs) that have different im-

pacts on the machining process [3 - 14]. One of these concerns the electrical consumption: the absorbed power will increase due to the lubricant supply (pumping system and so on). Therefore, the total energy consumption of the process will increase. Moreover, lubricants are also considered economic burden since they must be disposed and treated wastes at the end of their life cycle [2]. Furthermore, their use is also characterized by problems in the immediate working environment and hazards for the worker’s health in contact with them [2 - 6]. As far as the first problem is concerned, it is known that the cutting fluid is assumed to diverge into four paths during the machining process: vapor waste stream generated through cutting-fluid diffusion into the surrounding environment; liquid waste stream created through fluid coating on the chips generated during the machining process; liquid waste stream resulting from cutting-fluid coating of the workpiece; lubricant flow collected and recirculated through the system. Theoretically speaking, and considering not leakages, the recirculating portion of the cutting-fluid stream is recovered and reused. A significant portion of the chip-coated fluid may also be recovered through centrifugal or steam-injection methods (energy costly methods) but in this analysis the chip-coated fluid is assumed to be unrecoverable. Concerning the hazards for human health, some parameters like the relative toxicity and flammability of lubricants have been taken into account as proposed by Munoz and Sheng [4] and resumed in Table 1. The level of toxicity LC50 is the Lethal Concentration Value used as one possible indicator of the degree of toxicity of a substance. The ranges of toxicity are indicated by the ranking value WT. The value WT = 5 indicates an extreme toxicity level of the substance considered, when WT = 4 the level of toxicity is high and so on. The best level of WT is equal to 1 indicating a low level of toxicity so a low level of hazard for human health. Another important indicator, for lubricant environmental evaluation, is the flammability indicated by the melting point Tm or the flash point Tf. A non combustible material presents a value of Tm > 500 °F so a ranking value

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_63, © Springer-Verlag Berlin Heidelberg 2011

365

366

Sustainability in Manufacturing - Selected Applications

of WF equal to 1. A combustible lubricant presents a Tf > 100 so a WF equal to 2 whereas WF= 3 corresponds to a Tf < 100 so a flammable lubricant.

(roughness indexes and hardness). The complete experimental plan is reported in Table 4.

These trends pushed a number of research to find alternative techniques such as dry machining (cutting without the aid of CFs) as well as minimal quantity of lubrication (MQL) machining. Nevertheless, reach the aim of sustainability is not as simple as just to turn off the cooling/lubricating fluid supply but it is necessary to understand the machining process with cooling/lubricating mechanisms dealt within. In fact, sometimes the dry process can be detrimental for the characteristics of the final product and can significantly reduce the useful life of the tool. The reason lies in several important functions of cutting fluids, like the reduction of temperature in cutting zone and of friction, the cleaning of tools and workpiece, the transport/evacuation of chips, etc. An alternative is the MQL lubrication methods that lies on atomizing and delivering of a minute quantities of lubricants to the cutting zone in a compressed air jet. The media employed, typically oils, are used to reduce friction and adhesion between the chip-tool and tool-workpiece interfaces. Consequently, the heat generated is lower than in completely dry machining case. Toxicity

Rank value (WT)

LC50 > 450

1

350 < LC50 < 450

2

250 < LC50 < 350

3

150 < LC50 < 250

4

LC50 < 150

5

Flash point (F°)

Rank value (WF)

Tm > 500

1

Tf > 100

2

Tf < 100

3

Table 1: Rank value for toxicity and flammability for metalworking fluids. 3

EXPERIMENTAL PLAN

Figure 1: Experimental set-up of the milling tests. More in detail, the first set of experimental tests was aimed to analyze the effect of the lubricant conditions fixing the process parameters in order to identify the worst case in terms of tool wear. At this stage, the cutting speed was equal to 50 m/min, the feed per tooth equal to 0.08 mm/tooth, and the axial and radial depth of cut were set to 0.3mm. Then, the analysis was extended with the aim to evaluate the influence of the cutting parameters on tool life, surface quality and power consumption. In particular, the feed was set to 0.1 mm/tooth and three levels of cutting speed were selected. Only dry and MQL conditions were taken into account. For all the tests reported in Table 4, the electrical power consumption, the roughness of the finished surface, the cutting forces and the tool wear were evaluated. Elements

[%weight]

Aluminium

32.0-33.5

Niobium

4.5-5.1

The experimental tests were performed using a three axis CORTINI M500/F1 vertical CNC milling machine, with a maximum power of 3.7 kW and a maximum torque of 24 Nm.

Chromium

2.2-2.6

Oxygen

Max 0.08

The milling operations were carried out on a -TiAl specimen with rectangular shape. It was obtained by electron beam melting process and thermal treated in order to improve the machinability. The chemical composition and the mechanical properties of the material are reported respectively in Table 2 and Table 3. Furthermore, the -TiAl specimen presented an average initial hardness of 273 HV30, acquired by a hardness tester EMCOTEST M4U 025.

Nitrogen

Max 0.02

Carbon

Max 0.015

Iron

Max 0.04

Hydrogen

Max 0.001

The experimental set-up is shown in Figure 1. Tools used in the experiments were 10 mm diameter VERGNANO F405 carbide ISO K30/K40 end mills, with 4 uncoated mills. The cutting tool angle was 12° and the helix angle was equal to 30°. The milling tests were executed in dry, MQL and wet conditions in order to verify the power absorption, the cutting forces acting during the process, the environmental impact and the quality of the machined samples

All Others Elements Titanium

Max 0.05 Balance (60% Max)

Table 2: Chemical composition of -TiAl alloy. The electrical power consumption was measured using a YOKOGAWA WT130 power meter which was clamped onto electricity supply wires to the machine. The evaluation was done by measuring the current in different steps, first of all, after switching the machine on, without activate the spindle or the motors.

Sustainability in Manufacturing - Selected Applications

367

Test 1

Test 2

Test 3

Test 4

Test 5

Test 6

Test 7

Test 8

Test 9

Spindle speed [rpm]

1592

1592

1592

1114

1114

1592

1592

2260

2260

Feed rate [mm/min]

509

509

509

446

446

637

637

904

904

Process Parameters

Cutting speed [m/min]

50

50

50

35

35

50

50

71

71

Feed per tooth [mm/tooth]

0.08

0.08

0.08

0.1

0.1

0.1

0.1

0.1

0.1

Lubricant condition

DRY

WET

MQL

DRY

MQL

DRY

MQL

DRY

MQL

Table 4: Experimental campaign After that, the motors were loaded and then the spindle speed turned on. The further step was to measure the current while the spindle was running and when the tool was positioning to the initial point of engagement without any other operation. Subsequently the total current was recorded during machining. Tools were periodically examined, by means of a stereo microscope LEICA MS5 (with 40X magnification), at each cutting passes, until the fixed acceptable wear was reached. The roughness of every milled surfaces were measured by a roughness tester HOMMEL TESTER T1000. Finally, the cutting forces acting during the process were measured by means of a four-component KISTLER dynamometer. For the WET process, the flow rate was equal to 10 l/min while for the MQL process was 0.0003 l/min. Figure 3: Power distribution in WET milling. Property (at Room Temperature) Tensile Strength

344.7 MPa

Yield Strength (0.2% offset)

275.8 MPa

Elongation, percent in 4D

0.50

Table 3: Mechanical properties of -TiAl alloy. 4 4.1

RESULTS AND DISCUSSION Power distribution

Figures 2-4 show the percentage of the power consumption for the three above-mentioned lubricant conditions, with a cutting speed of 50 m/min and a feed equal to 0.08 mm/tooth.

Figure 4: Power distribution in MQL milling. The total power acquired for each test is the sum of diverse contributions: the idle power, the motors, the spindle, the axis jog and the coolant pump, when it is present. Lubricant condition

Total absorbed power

DRY

1.35 kW

WET

1.51 kW

MQL

3.90 kW

Table 5: Total absorbed power for the three lubricant conditions. Although the machining power depends on material removal rate and workpiece material, the pie chart highlights that the non-cutting operations dominate power consumption in the machining process. Figure 2: Power distribution in DRY milling.

Furthermore, the analysis carried out at the varying of the cutting parameters didn’t highlight substantial differences in terms of power consumption. It is also confirmed by the obtained small chip thickness and measured cutting forces. It is worth to pointing out that this trend is also due to the values and variations of the selected cutting parameters. This precautionary choice was mainly due to the innovative material used in this research and, therefore, due to its unknown behavior under machining. In addition, the most power

368

Sustainability in Manufacturing - Selected Applications

4.2

Tool wear and tool life measurement

Tool life estimation was conducted using the above mentioned cutting conditions. The tool wear, which takes into account both the flank and the corner wear (Figure 5), was recorded at regular intervals during machining and for each lubricant condition. The wear limit “TW*” was fixed to 100 μm.

140 120

Tool wear [m]

consuming process is the MQL one, due to the current consumption of the cooling equipment. Thus, the data presented in this study confirms that machine modules are by far more significantly power consuming than the milling process itself [6].

100 80 60 40 20 0 0

20

40

60

80

100

120

140

160

Cutting time [min]

Corner wear

New tool outline

V=35 m/min; f=0.1 mm/tooth; DRY

V=35 m/min; f=0.1 mm/tooth; MQL

V=50 m/min; f=0.1 mm/tooth; DRY

V=50 m/min; f=0.1 mm/tooth; MQL

V=71 m/min; f=0.1 mm/tooth; DRY

V=71 m/min; f=0.1 mm/tooth; MQL

Figure 7: Tool wear measurement.

Flank wear

160

145.1 133.3

Tool life [min]

140 120 100 80 60

Figure 5: Tool wear measurement.

40

The results reported in Figure 6, at fixed cutting feed and speed, highlight that the longer tool life was obtained using MQL cooling condition. In particular, tool life of 5.8 minutes was measured in wet condition, while 24.2 minutes and 145.1 minutes were respectively observed for dry and MQL cooling conditions. In addition, as shown in Figure 7, the tool wear is also influenced by the cutting speed: at the increasing of the cutting speed the tool wear decreases.

20

49.0 24.2

19.3 7.2

5.8

0

0.95

7.1

1

V=50 m/min; f=0.08 mm/tooth; DRY

V=50 m/min; f=0.08 mm/tooth; WET

V=50 m/min; f=0.08 mm/tooth; MQL

V=35 m/min; f=0.1 mm/tooth; DRY

V=35 m/min; f=0.1 mm/tooth; MQL

V=50 m/min; f=0.1 mm/tooth; DRY

V=50 m/min; f=0.1 mm/tooth; MQL

V=71 m/min; f=0.1 mm/tooth; DRy

V=71 m/min; f=0.1 mm/tooth; MQL

Figure 8: Tool life.

250

Tool wear [m]

4.3 200

150

100

50

0 0

20

40

60

80

100

120

140

160

Cutting time [min]

DRY

WET

MQL

TW*

Figure 6: Tool wear for different lubricant conditions. Finally, as depicted in Figure 8, the tool life of the MQL process is bigger than the others in all the investigated cases and, as a general trend, it increases by decreasing the cutting speed. Furthermore, the tool wear increases by increasing the feed per tooth.

Roughness estimation

The roughness of the machined sample was measured for each lubricant condition in order to evaluate the characteristic of the machined surface. In particular, mean average, Ra, the average maximum height of the profile, Rt, the skewness, Rsk, and the curtosis roughness, Rku, were measured. It is important to note that Rsk and Rku are important roughness indexes when the machined surface lift needs to be investigated, especially for aerospace applications. The results, as shown in Table 6, demonstrate that each process presents acceptable profiles as far as the surface quality is concerned. In particular, the maximum height of the profile ranged between 1.66 and 3.03 m while the Ra value varied from 0.22 to 0.32m. The skewness resulted to be less than 0 in all the considered tests while Rku more than 3 except in Test 8. 4.4

Manufacturing sustainability

Figure 9 reports the results of the different conditions utilized in this research as far as sustainability concepts are regarded. In particular, observing Figures 9-10, it can be noted as MQL process is the best compromise in terms of tool life and surface quality although, as above mentioned, the three cooling processes permit to obtain similar roughness quality indexes and therefore, machined surface quality.

Sustainability in Manufacturing - Selected Applications

369

Test 1

Test 2

Test 3

Test 4

Test 5

Test 6

Test 7

Test 8

Test 9

Rt [m]

1.81

2.38

2.52

2.62

2.46

2.03

2.46

1.66

3.03

Ra [m]

0.22

0.26

0.28

0.31

0.28

0.24

0.27

0.22

0.32

Rku

3.31

3.44

3.45

3.28

3.35

3.25

3.38

2.98

3.53

Rsk

-0.12

-0.36

-0.28

-0.05

-0.20

-0.09

-0.19

-0.05

-0.26

Table 6: Roughness results for the experimental campaign. 4.5

Manufacturing sustainability

Figure 9 reports the results of the different conditions utilized in this research as far as sustainability concepts are regarded. In particular, observing Figures 9-10, it can be noted as MQL process is the best compromise in terms of tool life and surface quality although, as above mentioned, the three cooling processes permit to obtain similar roughness quality indexes and therefore, machined surface quality. Roughness Rt Index [μm] 1.5 0.2 Roughness Ra Index [μm]

Hardness HV30 320

3.5 290 0.4 55 -0.1 4 0.9 3

Cutting Force [N] 35

-0.4 Roughness Rsk Index

3.5 Roughness Rku Index

min Power [KW] 1

148

Tool life [min] WET

DRY

MQL

Figure 9 Comparison measured parameters for each lubricant conditions.

Roughness Rt Index [μm] 1.5

not affect very much the current consumption while the machine modules and equipments are the major responsible of the electrical consumption. In fact, MQL condition shows the higher energy consumption due to the use of the coolant pump. Concerning the level of hazard for workers in contact with the lubricants, both the data sheet of the liquids used in MQL and WET didn’t show the LC50 level. However, the MQL lubricant is completely a vegetable oil, consequently it’s level of hazard is lower than that used for WET process (synthetic oil). In addition, the flammability level is also the lowest in the case of MQL (WF=1) lubrication system. Finally, it is also important to highlight as the quantity of lubricant used during MQL process is significantly low, therefore less pollutant for the environment are produced. 5

In this paper milling experimental operations on -TiAl were carried out. The process was repeated for three different lubricant conditions in order to evaluate the environmental impact and the surface characteristics of each process. The overall results highlight that the MQL process has some benefits in terms of surface quality and especially for the tool life but it also results to be the most expensive process in terms of power consumption. For the considered process parameters, the MQL does not affects very much the roughness of the surface but it allows to save the tool for more than 6 time compared to the dry one and 25 times to the wet lubrication system. Finally, it should be pointed out that further investigations and experimental tests at varying of more severe cutting conditions will be necessary to improve the accuracy of proposed sustainability concept on this new classes of Ti-alloys for aeronautic aerospace industries.

0.2 Roughness Ra Index [μm]

Hardness HV30 320

6

Cutting Force [N] 35

MRR [mm3/min] 85

CONCLUSIONS

3.5 290 0.4 0.9 55 35 4

Mantle, A.-L., Aspinwall, D.-K.(2001): Surface integrity of a high speed milled gamma titanium aluminide, in: Journal of Materials Processing Technology, Vol. 118, pp.143-150.

[2]

Jayal, A.-D., Balaji, A.-K. (2007): On a process modelling framework for sustainable manufacturing: a machining perspective, in: Proceedings of IMECE2007 ASME International Mechanical Engineering Congress and Exposition - Seattle, Washington, USA.

[3]

Marksberry, P.-W., Jawahir, I.-S. (2008): A comprehensive tool-wear/tool-life performance model in the evaluation of NDM (near dry machining) for sustainable manufacturing in: International Journal of Machine Tools & Manufacture, Vol. 48, pp. 878–886.

[4]

Munoz, A., Sheng, P. (1995): Analytical Approach for Determining the Environmental Impact of Machining Processes, in: Journal of Materials Processing Technology, Vol. 53, No 3, pp. 736-758.

148 Tool life [min]

1 min Power [KW]

DRY; v = 35 m/min

MQL; v = 35 m/min

DRY; v = 50 m/min

MQL; v = 50 m/min

DRY; v = 71 m/min

MQL; v = 71 m/min

Figure 10: Comparison of measured parameters for each process parameters in dry and MQL conditions. On the contrary, as far as the power consumption is regarded, it can be highlighted as the MQL cooling process is the most power consuming process compared to the others. On the other hand, it allows to reach longer tool life permitting to limit tool cost and tool replacement. Furthermore, as general trends, each process does

REFERENCES

[1]

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[5]

Kopac, J., (2009).: Achievements of sustainable manufacturing by machining, in: Journal of Achievement in Materials and Manufacturing Engineering, Vol. 34, No 2, pp.180-187.

[6]

Rajemi, M.-F., Mativenga, P.-T., Aramcharoen, A. (2010): Sustainable machining: selection of optimum turning conditions based on minimum energy considerations, in: Journal of Cleaner Production. Article in press.

[7]

Devoldere, T., Dewulf, W., Deprez, W., Douflou, J.-R. (2008): Energy Related Life Cycle Impact and Cost Reduction Opportunities in Machine Design: The Laser Cutting Case, in: Proceedings of CIRP International Conference on Life Cycle Engineering –, Sydney, N.S.W.

[8]

Klocke, F., Eisenblatter, G. (1997): Dry Cutting, in: Annals of the CIRP, Vol. 46, No 2, pp. 519-526.

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Jayal, A.-D., Balaji, A.-K. (2009): Effects of cutting fluid application on tool wear in machining: Interactions with toolcoatings and tool surface features, in: Wear, Vol. 267, pp. 1723-1730.

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Jayal, A.-D., Balaji, A.-K. (2005): Tribological and thermal effects of cutting fluid application in machining with coated and grooved tools, in: ASME MED, Vol.16, No 1, pp. 513-520.

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Weinert, K., Inasaki, I., Sutherland, J.-W., Wakabayashi, T. (2004): Dry Machining and Minimum Quantity Lubrication in: Annals of the CIRP, Vol. 53, No 2, pp. 511-537.

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Pusevec, F., Kopac, J. (2009): Achieving and Implementation of Sustainability Principles in Mahining Processes, in: Advances in Production Engineering & Management, Vol.4, No 3, pp. 151-160.

[13]

Dahmus, J.-B., Gutowski, T.-G. (2004): An Environmental Analysis Of Machining in: Proceedings of IMECE2004 ASME International Mechanical Engineering Congress and RD&D Expo - Anaheim, California USA.

[14]

Gutowski, T.-G., Dahmus, J., Thiriez, A. (2006): Electrical energy requirements for manufacturing processes in: Proceedings of 13th CIRP International Conference on Life Cycle Engineering - Leuven, Belgium.

Quantitative and Qualitative Benefits of Green Manufacturing: an Empirical Study of Indian Small and Medium Enterprises Kuldip Singh Sangwan Department of Mechanical Engineering, Birla Institute of Technology & Science, Pilani INDIA

Abstract Green Manufacturing (GM) has attracted the attention of organizations all over the world. However, managers, who are considering the introduction of GM in their organizations not only have to identify the application and plan its implementation but also have to ensure that the use of GM will be a viable alternative. Most critical issue with the industry, particularly with SMEs before implementing GM is what benefits will be achieved with its implementation. This paper identifies the quantitative and qualitative benefits of GM through a literature survey. A survey of 198 Indian SMEs in India, using a questionnaire specially developed for this study, has been done to validate the benefits by using SPSS statistical tool. Keywords: Green Manufacturing; Sustainable Manufacturing; Statistical Analysis

1

INTRODUCTION

With growing awareness of environmental issues – from global warming to local waste disposal and pollution problems – business and government have come under increasing pressure to reduce the environmental impacts involved in the production and consumption of goods and services. Until quite recently the usual response to environmental problems involved measures to reduce pollution and waste after they had been produced; for example, by installing flue gas desulphurization equipment in a power station or waste water treatment plant in a factory. However, lately, some organizations began to shift their attention from these ‘end of pipe’ approaches towards developing ‘clean or green’ manufacturing, which generates less pollution and waste in the first place and make efficient use of energy and materials. Approaches to environmental issues can be broadly classified into three categories – concept approaches, wherein the organizations employ environmental protection measures and think of biodegradable products, compliance approaches, wherein organizations comply with the environmental regulations and also think ahead of continual improvement, and finally a system approach to environmental issues by implementing green manufacturing as a system. Melnyk and Smith [1] defined green manufacturing as “a system that integrates product and process design issues with issues of manufacturing planning and control in such a manner as to identify, quantify, assess, and manage the flow of environmental waste with the goal of reducing and ultimately minimizing environmental impact while also trying to maximize resource efficiency”. Green Manufacturing (GM) is the intersection of product development and manufacturing practices with environmental issues and concerns. The greater the overlap between these areas, the greater the extent to which manufacturing practices recognize and embody environmental issues, concerns, and practices as shown in Figure 1. Environmental factors have to be considered along with supplier concerns and market considerations, as well as production, distribution, service, use and disposal issues during the design of the product.

Today, green manufacturing involves continuous improvement of environmental attributes of products, processes and operations. The most far-reaching implication of green manufacturing is the need to take an environmental life cycle approach to production. This approach requires that environmental impacts are understood and summed up across the life-time of the product, process, material, technology, or service being evaluated. The goal is to reduce the overall environmental impact of a product or process to a minimum, and not simply address one aspect of the impact, as minimizing the impacts of subsystems does not ensure that the impacts of the entire system are minimized, or even reduced. Green Manufacturing is also known by a plethora of different names – clean manufacturing, environmentally conscious manufacturing, environmentally responsible manufacturing, and sustainable manufacturing. Irrespective of the name, the goal remains the same – designing and delivering products that minimize negative effects on the environment through their production, use, and disposal.

Manufacturing and Design Practices

Green Manufacturing

Environmental Issues, Concerns, and Practices

Figure 1: Green manufacturing - the critical intersection [1].

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_64, © Springer-Verlag Berlin Heidelberg 2011

371

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Sustainability in Manufacturing - Selected Applications

In recent years green manufacturing has been widely considered for implementation to maintain competitive advantage. However, the implementation of such systems is expensive and relative investments tend to be irreversible, thus necessarily requiring careful consideration before a decision can be made. Managers, who are considering the introduction of GM in their organizations not only have to identify the application and plan its implementation, but also have to ensure that the use of GM will be a viable alternative. At present, managers have difficulties in assessing the impact of green manufacturing because of the lack of quantification of green manufacturing benefits, thereby making it difficult to justify green manufacturing as an alternative option. As a result judgments about green manufacturing become costs in ethical or moral terms. A set of quantitative and qualitative benefits of green manufacturing identifies throughout the life cycle of the products. These issues are imperatives in reference to emerging economies like India where organizations are trying hard to catch up with the European, Japanese and American manufacturing organizations. Indian industry should clearly understand the benefits of green manufacturing in Indian context vis-à-vis world context. Researchers have pointed out the lack of quantifiable performance measures as an obstacle to the implementation of green manufacturing [2] [3]. A review of 102 research papers on green manufacturing by Sangwan [4] shows that there is hardly any research paper that studies Indian industry in terms of green manufacturing. This paper identifies the qualitative and quantitative benefits of green manufacturing through a literature survey. The identified benefits were validated by using SPSS statistical analysis tool on the data collected through a survey of 198 Indian SMEs. 2

METHODOLOGY

Initially a literature review is done to identify the benefits of green manufacturing. Next, a survey instrument is developed based on the literature survey and the interviews with practitioners from 5 Indian organizations. This survey instrument is sent to more than 1200 different SMEs and out of which 198 responses were received. A questionnaire was designed as a research instrument with the intention to make a sincere effort to tap the collective wisdom of the professionals within the various SMEs as shown in the appendix. To ensure understandability of the questionnaire, the questions were critically reviewed for their clarity and content many times and some modifications were incorporated in the questionnaire before finalizing it for printing. A five point Likert scale was used to allow respondents to respond to the survey items where 1 means very low, 2 means low, 3 means medium, 4 means high and 5 means very high. Once the questionnaire is ready, the next step is to select the sample of respondents, as samples should be those for whom the instrument is intended. So, the persons working on the level of managers and above are selected having at least 5 years of experience and responsible for various manufacturing activities of the industry. Pre-testing of the questionnaire is done to ensure the accuracy by providing it to 2 academicians and 2 industrial professionals having knowledge of the subject. The questionnaire is sent to various SMEs having business in textile, chemical, rubber/plastic, cement, fabrication, machinery, electrical/electronics, automotive, pharmaceutical, steel/iron and food sectors. The chosen companies were having a number of employees ranging from less than 50 to more than 150.

3

BENEFITS OF GREEN MANUFACTURING

Gutowski et al [5] reviewed the American, European and Japanese industries and saw that the major motivations for environmentally benign manufacturing are: cost reduction, risk mitigation, market advantage, regulatory flexibility and corporate image. Lefevre et al [6] found from the empirical study of Canadian SMEs that the implementation of green strategies improved organizational innovativeness (product, process and managerial innovation) and organizational competitiveness (cost containment, revenue generation, liability management and corporate image, and exports performance). Sarkis and Rasheed [7] have listed the various expected benefits of ECM as: safer and cleaner facilities, lower future costs for disposal and worker protection, reduced environmental and health risks, and improved product quality at lower cost and higher productivity. Poksinska [8] also argues that showing care for the environment and establishing a strong environmental image may help organisations to attract environmentally conscious customers and suppliers. A lot of successful cases also indicate that well-formulated environmental strategies could lead to a number of business advantages such as better quality, reduced costs, improved company’s environmental image and relations with stakeholders, and the opening of new markets [9]. Further the authors found that the stimulation of staff morale, enhancement of the company’s image and customer loyalty are the most significant benefits of EMS. The most advanced environmental technologies will make no contribution to the pursuit of sustainability unless they can wrestle market share away from conventional products and change the market’s agenda for product development and marketing [10]. Senthil et al. [11] developed a life cycle environmental cost analysis incorporating costing into LCA (life cycle accounting) practice. This model prescribes a life cycle environmental cost model to estimate and correlate the effects of these costs in all the life cycle stages of the product. The newly developed categories of eco-costs are: cost of effluent treatment/control/disposal, EMS, eco-taxes, rehabilitation, energy saving and savings from recycle and reuse strategies. Kobayashi [12] presented a methodology and software tool to establish an eco-design concept of a product and its life cycle by assigning appropriate life cycle options to the components of the product. Product life cycle simulation techniques have been proposed to evaluate the environmental burden and revenue of an organization caused by a single or multiple product life cycle from a medium-term or long-term viewpoint [13][14]. Proponents of ECM claim that organizations can reduce their costs in the form of reduced waste management/disposal costs, reduced penalties, reduced future liabilities and lower regulatory driven costs and can improve product demand [15]. A properly designed green manufacturing system can trigger procedural or technological changes, and as a result can reduce the operational costs and improve the value of a product. It allows a company to use raw materials, energy, or labor in a more effective way, and thereby reduces the business/operation costs. Experiences from Austria, Netherlands, Sweden, and the UK show that manufacturing environmentally-friendly products or services will not necessarily increase business/operation costs; on the contrary, because of the better use of resources, a company’s manufacturing costs can be reduced. Sustainability in the development and manufacture of new products is a strategy that is widely accepted in principle, although not yet widely practiced. The integration of environmental requirements throughout the entire lifetime of a product needs a new way of thinking and new decision tools to be applied [16].

Sustainability in Manufacturing - Selected Applications

373

A total of 12 quantitative benefits and 9 qualitative benefits are identified through the literature survey as given in tables 1 and 2. 4

RESULTS OF SURVEY INSTRUMENT

The numerical scores from the questionnaire provided a measure of strength of opinion of the effect of each item on the success of the project. These are subsequently transformed into relative importance index using the following formula (adopted from [17]):  5  ai xi  Index of item/ vari able x (Ix)   i  1 5   5 xi  i 1 



Importance



       

Table 2 shows the importance index analysis results for various GM quantitative benefits. It shows that all the identified quantitative benefits are important. Benefits related to waste management are perceived more important than the benefits related to the life cycle of the product.

(1)

Where: ai = Constant expressing weight given to i xi = Variable expressing frequency of response for i i = 1, 2, 3, 4, 5. The importance indices range from zero to 1. The value of ‘i’ varies from 1 to 5 and the corresponding values of ‘ai’ will be a1, a2, a3, a4,and a5 respectively where a1=1, a2=2, a3=3, a4=4,and a5=5.These indices reflect the relative importance of the factors listed in the questionnaire. The importance indices have been classified into five categories to reflect the respondents’ ratings as follows:     

Very important: 0.8  Ix  1.0 Important: 0.6  Ix  0.8 Preferred: 0.4 Ix  0.6 Less important: 0.2  Ix  0.4 Not important: 0  Ix  0. 2

Improved working conditions

4.343

0.907

Better organization image in public

4.239

0.941

0.816

Improved staff morale Enhanced customer loyalty/ satisfaction Establishing or improving brand value

4.213

0.932

0.812

4.119

1.074

0.797

4.000

0.949

0.772

Lowered regulatory concerns

3.849

0.972

0.732

Increased market opportunities

3.890

0.962

0.752

Improved product performance

3.807

1.077

0.730

Decreased liabilities

3.693

1.040

0.712

Standard Deviation

Mean

‡

SD

I ‡ Index

Reduced waste handling cost Lowered waste categorization cost Reduced waste treatment cost

3.672

0.983

0.710

3.656

0.935

0.707

3.709

0.925

0.719

Reduced waste disposal cost

3.741

0.973

0.724

Reduced waste storage cost

3.703

0.971

0.712

Lowered transportation cost

3.481

1.014

0.662

Decreased packaging cost Reduced overall cost of the product Lowered cost of production Reduced user operation/use cost Lowered maintenance/service cost Reduced overall cost to the organization

3.465

1.034

0.667

3.592

2.347

0.695

3.407

1.075

0.657

3.359

1.014

0.650

3.434

1.012

0.665

3.492

11.128

0.676

Standard Deviation

‡

†

Importance Index

Table 2: Mean, standard deviation and importance index for GM quantitative benefits.

I ‡ Index 0.839

†

Mean

†

The importance index analysis for qualitative benefits given in table 1 shows that all the identified benefits are either very important or important. The three most important qualitative benefits of green manufacturing implementation as perceived by the Indian industry are – improved working conditions, better organization image in public and improved staff morale. The three least important benefits of green manufacturing implementation as perceived by Indian industry are – decreased liabilities, improved product performance and improved brand value. This shows that the Indian industry does not perceive green manufacturing as a tool to improve product performance or brand value, rather it perceives GM as a tool to improve image of organization in public and among employees. Interestingly, even after big industrial mishaps in the recent past, the Indian industry does not perceive green manufacturing will reduce liabilities. Qualitative Benefit

Quantitative Benefits

†

SD

Importance Index

Table 1: Mean, standard deviation and importance index for GM qualitative benefits.

5

DATA ANALYSIS

This section discusses the reliability and validity analyses of the data as it is essential for several reasons. First, it provides confidence that the empirical findings accurately reflect the proposed measures. Second, empirically validated measures can be used directly in other studies in the field for different populations. They also yield valid tools to practitioners for assessment, benchmarking and longitudinal evaluation of their programs. Reliability and validity analyses have been carried out on the data acquired for the benefits of green manufacturing. This provides the academic and industry users with confidence that the scales measure important factors which are related to independent measures of the same constructs, and that each scale measures a single construct. 5.1

Reliability Analysis

Reliability refers to the degree of dependability and stability of data. Reliable measures will produce the same results each time it is administered to the same person in the same setting. There are four methods to assess the reliability of empirical measurements the retest method, the alternative form method, the split-halves method and the internal consistency method. The first three methods have major limitations (particularly for field studies) such as requiring two independent administrations of the instrument on the same group of people or requiring two alternate forms of the measuring instrument. In contrast, the internal consistency method works quite well in field studies because it requires only one administration. Also, it is the most general form of reliability estimation [18]. The internal consistency of a set of measurement items refers to the degree to which items in the set are homogeneous. Internal consistency can be estimated using reliability coefficient, such as Cronbach’s alpha. Prior to further analysis, using the SPSS,

374

Sustainability in Manufacturing - Selected Applications

reliability coefficient (Cronbach’s alpha) was calculated for each benefit. An alpha value of 0.70 is often considered as the criteria for internally consistent established performance measures/ constructs/scale. Flynn et al. [19] suggested three methods to improve the reliability coefficient. First, the constructs should be accepted without any changes if it has a strong alpha value (at least 0.70), with consistent item intercorrelation values. Second, constructs with acceptable (at least 0.60), but not high alpha values should be further analyzed to determine whether alpha could be improved by removal of some items. The item intercorrelation matrix served as a guide in determining which items contributed least and, thus, the best candidates for deletion. If their removal did not significantly alter the content of the construct, these items should be eliminated. But, at least three items should be retained in each construct in order to provide good resolution of the dimensionality of the construct. Third, a similar elimination analysis should be performed on the constructs, which failed to achieve the minimum criteria alpha value. If the construct still failed to achieve the criterion after elimination of items with lower item intercorrelations, the entire construct should be discarded. Table 3 provides a summary of the internal consistency analysis by using SPSS before and after the deletion of unreliable or invalidated benefits. The three qualitative benefits – improved working conditions, better organization image in public and enhanced customer loyalty/satisfaction – were deleted to make the factor unifactorial during validity analysis. The Cronbach’s alpha (α) value for the quantitative and qualitative factors is above 0.9, which reflects excellent reliability of the data. The high value of correlation coefficients for the data also shows that the identified benefits have high correlation among them. Benefit

Total no. of benefits

α

Mean correlation coefficient

Before deletion Qualitative

9

0.9356

0.5477

Quantitative

12

0.9407

0.5695

6

0.9351

0.6154

5

0.9236

0.7075

7

0.9160

0.6090

After deletion Qualitative Quantitative (waste related) Quantitative (life cycle related)

Table 3: Summary of internal consistency analysis. 5.2

Validity Analysis

Validity refers to the degree to which items truly measure the factors which they intend to measure. Factor analysis has been used on the data collected through survey to validate the benefits of green manufacturing. Factor analysis addresses the problem of analyzing the interrelationships among a large number of variables and then explaining these variables in terms of their common underlying dimensions (factors). There are two forms of factor analysis, namely, Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).The EFA is designed for a situation where links between the observed and latent variables are unknown or uncertain. The analysis thus proceeds in an exploratory mode to determine how and to what extent the observed variables are linked to their underlying factors. Factor loading is used to present these relations. The EFA helps to

identify whether selected items cluster on one or more than one factor. The uni-dimensionality of factors is thus assessed. Usually, three or more items are selected for a latent variable or construct. However, the aim of CFA is to test or confirm a pre-specified relationship between factors and latent variables. EFA was carried out for validation of the underlying factors. In general, there are two steps in a factor analysis: (1) the extraction of factors; and (2) the rotation of factors. The former finds the number of factors and the latter obtains a clear picture of what these factors represent. Next, the appropriateness of the factor model is determined by examining the strength of the relationship among the items/variables. Correlation matrix, Barlett’s test of sphericity and Kaiser-Meyer-Oklin (KMO) measure of sampling adequacy are the three measures recommended in the literature for this purpose. Correlation matrix Visual inspection of the correlation values during analysis reveals that all the correlations are greater than 0.3. This implies that the respective items under each factor are likely to have common factors. Barlett’s test of sphericity Barlett’s test assesses the overall significance of the correlation matrix. If the value of the statistic test for sphericity is large and the associated significance level is small, then it can be concluded that the variables are correlated. Barlett’s test of sphericity demonstrated sufficiently high values for all the factors (at p <= 0.0001). KMO measure of sampling adequacy The KMO test results show the qualitative benefit factor having a KMO value of 0.909 and the quantitative benefit factor having a value of 0.872 which is above the suggested minimum standard of 0.5 required for running factor analysis. Factor analysis was conducted on benefits, based upon principal components analysis with Varimax rotation. The number of factors to be extracted in each analysis was determined by the eigen value of factors. Factors will be extracted in accordance to the number of eigen value over 1. When an item in a measure loaded more than one factor, the rotated (varimax) solution was examined, to determine whether the factors beyond the first were substantively meaningful or merely unwanted ‘nuisance’ factors. Those items which created nuisance factors or in other words the items which represented more than a single domain were deleted. Cronbach alpha was then recalculated to verify the remaining item’s reliability. Finally the remaining items are refactored in order to verify that the items are loaded on a single factor. All items under quantitative benefits were examined and grouped under two measures of quantitative benefits – quantitative benefits related to waste and quantitative benefits related to life cycle. Now, these two newly created factors were analyzed again starting from the reliability analysis. Three qualitative benefits – improved customer loyalty/satisfaction, improved organization image in public and organization working conditions – were deleted during the factor analysis to make the factor uni-directional even if these benefits were given high weightage by the industry experts.

Sustainability in Manufacturing - Selected Applications Qualitative Benefit Improved staff morale

375

Factor loading 0.84

Establishing or improving brand value

0.82

Lowered regulatory concerns

0.79

Increased market opportunities

0.79

Improved product performance

0.78

Decreased liabilities Quantitative Benefits (Waste related) Reduced waste handling cost

0.77 Factor loading 0.78

Lowered waste categorization cost

0.73

Reduced waste treatment cost

0.68

Reduced waste disposal cost

0.67

Reduced waste storage cost

0.66

Quantitative Benefits (life cycle related) Lowered transportation cost

0.66

Decreased packaging cost

0.65

Reduced overall cost of the product

0.61

Lowered cost of production

0.60

Reduced user operation/use cost

0.59

Lowered maintenance/service cost

0.59

Reduced overall cost to the organization

0.59

[3]

Azzone, G. and Noci, G. (1998): Identifying effective PMSs for the deployment of “green” manufacturing strategies, in International Journal of Operations and Production Management, Vol.18, No. 4, pp. 308-335.

[4]

Sangwan K. S. (2008): Green Manufacturing – Stakeholders, Benefits and Performance Measures, In Proc. of national conference on new vistas in manufacturing: vision 2020, IE(I) Jaipur.

[5]

Gutowski T, Murphy C, Allen D, Bauer D, Bras B, Piwonka T, Sheng P, Sutherland J, Thurston D, Wolff E.,(2005): Environmentally benign manufacturing: observations from Japan, Europe and the United States, in Journal of Cleaner Production; Vol. 13, No. 1, pp.1-17.

[6]

Lefebvre É, Lefebvre L A, Talbot S.(2000): Environmental initiatives, innovativeness and competitiveness: some empirical evidence. In: Proceedings of the IEEE EMS International Engineering Management Conference, pp. 674679.

[7]

Sarkis, J. and Rasheed, A (1995), Greening the manufacturing function, in Business Horizons, Vol. 38, No. 5, pp. 17-27.

[8]

Poksinska, B. (2003), Behind the ISO 9000 and ISO 14000 certificates Licentiate and PhD Theses: IEI: Linköping University.

[9]

Pun, K.F., Hui, I.K., Lau, H.C.W., Law, H.W. and Lewis, W.G. (2002), Development of an EMS planning framework for environmental management practice, in International Journal of Quality & Reliability Management, Vol. 19, No.6, pp. 688709.

[10]

Pujari D, Peattie K, Wright G.(2005): Organizational antecedents of environmental responsiveness in industrial new product development, in Industrial Marketing Management; Vol. 33, No. 5, pp.381-391 .

[11]

Senthil, K.D., Ong, S.K., Nee, A.Y.C. and Tan, R.B.H. (2003), A proposed tool to integrate environmental and economical assessments of products, in Environmental Impact Assessment Review, Vol. 23, No. 1, pp. 51–72.

[12]

Kobayashi, H. (2005), Strategic evolution of eco-products: a product life cycle planning Methodology, in Research in Engineering Design,, Vol.16, No. 1–2, pp.1–16.

[13]

Hoshino, T., Yura, K. and Hitomi, K. (1995), Optimisation analysis for recycle-oriented manufacturing system, in International Journal of Production Research, Vol. 33, pp. 2069–2078.

[14]

Umeda, Y., Nonomura, A. and Tomiyama, T. (2000), Study on life-cycle design for the post mass production paradigm, in Artif. Intel. Eng. Des. Anal. Manuf., Vol.14, No. 2, pp. 149– 161.

Table 4: Reliable and valid qualitative and quantitative benefits of GM for Indian SMEs with factor loading. 6

SUMMARY

This paper identifies the quantitative and qualitative benefits of green manufacturing through a literature survey. The data collected through a survey of 198 Indian SMEs is used to refine and validate the benefits. The final quantitative benefits of green manufacturing in order of their decreased ranking are improved morale, improved brand value, lowered regulatory concerns, increased market opportunities, improved product performance and decreased liabilities. The quantitative benefits of green manufacturing are related to either waste (reduced waste handling cost, lowered waste categorization cost, reduced waste treatment cost, reduced waste disposal cost and reduced waste storage cost) or life cycle of the product (lowered transportation cost, decreased packaging cost, reduced overall cost of the product, lowered cost of production, reduced user operation/use cost, lowered maintenance/service cost and reduced overall cost to the organization). The results of reliability and validity analyses, by using SPSS statistical tool, provide sure evidence that the identified benefits are highly reliable and valid for the Indian SMEs. The high values of factor loadings verify that the benefits are uni-directional and independent. However, the instrument used in the study assigns equal weightage to each benefit. It may be a good idea to investigate further whether assigning different weightage to different benefits would improve assessment. 7

REFERENCES

[1]

Melnyk S. A. and Smith R. T.(1996): Green Manufacturing, in SME Publication.

[2]

Sangwan K. S. (2006): Performance Value Analysis for Justification of Green Manufacturing Systems, in Journal of Advanced Manufacturing Systems, Vol. 5, No. 1, pp. 59-73.

[15] Porter, M. E. and Van der Linde, C. (1995), Green and competitive: ending the stalemate, in Harvard Business Review, Vol. 73, No. 5, pp. 120–134. [16]

Kaebernick H, Kara S, Sun M. (2003): Sustainable product development and manufacturing by considering environmental requirements, in Robotics and Computer Integrated Manufacturing; Vol. 19, pp.461-468.

[17]

Digalwar, A.K. and Sangwan, K. S. (2007): Development and validation of performance measures for world class manufacturing practices in India, in Journal of Advanced Manufacturing Systems, Vol. 6, No. 1, pp.21–38.

[18]

Nunnally, J. (1967), Psychometric Theory, McGraw-Hill, New York.

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[19]

Flynn, B.B., Schroeder, R.G. and Sakakibara, S. (1994), A framework for quality management research and an associated measurement instrument, in Journal of Operations Management, Vol. 11, No.4, pp.339-366.

[20]

Hair, J., Anderson, R., Tatham, R. and Black, W. (1995), Multivariate Data Analysis, 4th ed., Prentice-Hall, Englewood Cliffs, NJ. APPENDIX Questionnaire

Please rate degree or extent of practice for each variable on 1 to 5 scale where: 1 – Completely Disagree, 2 – Rarely Agree, 3 – Partly agree, 4 – Rather Agree, 5 – Completely Agree Qualitative Benefits i) ii) iii) iv) v) vi) vii) viii) ix)

Consideration of environmental issues improves working conditions Consideration of environmental issues improves organization image in public Consideration of environmental issues improves staff morale Consideration of environmental issues enhances customer loyalty/satisfaction Consideration of environmental issues helps in establishing/improving brand value Consideration of environmental issues lowers regulatory concerns Consideration of environmental issues increases market opportunities Consideration of environmental issues improves product performance Consideration of environmental issues decreases liabilities

Quantitative benefits i) ii) iii) iv) v) vi) vii) viii) ix) x) xi) xii)

Consideration of environmental issues reduces waste handling cost Consideration of environmental issues lowers waste categorization cost Consideration of environmental issues reduces waste treatment cost Consideration of environmental issues reduces waste disposal cost Consideration of environmental issues reduces waste storage cost Consideration of environmental issues lowers transportation cost Consideration of environmental issues decreases packaging cost Consideration of environmental issues reduces overall cost of the product Consideration of environmental issues lowers cost of production Consideration of environmental issues reduces user operation/use cost Consideration of environmental issues lowers maintenance/service cost Consideration of environmental issues reduces overall cost of the organization

Preliminary Environmental Assessment of Electrical Discharge Machining 1

2

1,2

Karel Kellens , Renaldi , Wim Dewulf , Joost R. Duflou 1 2

1

Department of Mechanical Engineering, K.U.Leuven, Leuven, Belgium

Group T – Leuven Engineering College, K.U.Leuven Association, Leuven, Belgium

Abstract Manufacturing processes, as used for discrete part manufacturing, are responsible for a substantial part of the environmental impact of products, but are still poorly documented in terms of environmental footprint. This paper presents the first results of a data collection effort, allowing to assess the overall environmental impact of three types of Electrical Discharge Machining (EDM) processes: die sinking EDM, wire EDM and micro EDM. After the inventorisation of all process flows using the CO2PE!-methodology, a subsequent impact assessment analysis allows indentifying the most important contributors to the environmental impact of EDM. Finally some improvement potential is sketched. Keywords: Electrical Discharge Machining (EDM); Energy and Resource Efficiency; CO2PE!-Initiative

1

INTRODUCTION

Until recently, functional performance and the initial purchase price of machine tools were the main selection criteria for the purchase of new machine tools. Recently, a movement towards environmentally benign manufacturing can be observed as a result of three driving factors. Besides more stringent regulatory frameworks, also competitive economic advantages and proactive green behavior are motivating factors to switch to environmentally benign manufacturing [1]. Although manufacturing processes, as used for discrete part manufacturing, are responsible for a substantial part of the environmental impact of products, they are still poorly documented in terms of their environmental footprint. The lack of thorough analysis of manufacturing processes has as consequence that optimization opportunities are often not recognized and that improved machine tool design in terms of ecological footprint has only been targeted for a few common processes. This paper presents the first results of a data collection effort, allowing to assess the overall environmental impact of three types of Electrical Discharge Machining (EDM) processes: die sinking EDM (EDM), wire EDM (WEDM) and micro EDM (µEDM). Using the CO2PE!-methodology [2], first the different modes of the processes are investigated, including both productive and non-productive modes. In particular consumption of electric power is recorded for the different modes. Subsequently, time studies allow determining the importance of productive and non-productive modes of EDM machine tools. Previous studies have indeed indicated that the influence of stand-by losses of machine tools is often substantial for various manufacturing processes. Besides the conducted time and power measurements, consumables as well as manufacturing emission data based on industrial experiences and literature complete the LCI data collection effort. A subsequent impact assessment allows indentifying the most important contributors to the environmental impact of the different types of EDM. Next to the electricity consumption (mainly of the pumps), the consumption of dielectrics proves to cause important environmental aspects. Finally, the paper sketches some improvement potential for EDM machine tools based on the presented LCA.

2

PRINCIPLE OF ELECTRICAL DISCHARGE MACHINING

Electrical discharge machining (EDM) is a widely used unconventional manufacturing process developed around 1943 by Lazarenko [4]. EDM is typically used to produce dies and molds as well as for finishing of aerospace, automotive and medical parts. Figure 1 shows the concept of EDM. Pulsed arc discharges occur in the “gap”, filled with an insulating medium such as a dielectric liquid like hydrocarbon oil (EDM) or de-ionized water (WEDM), between the tool electrode and workpiece. The tool electrode is moved towards the workpiece until the gap is sufficiently small to ionize the dielectric. The erosive effect of the electrical discharges between tool and workpiece removes the material. Current research trends of EDM are described by Kunieda et al. [5] and Abbas et al. [6]

Figure 1: Concept of EDM [5].

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_65, © Springer-Verlag Berlin Heidelberg 2011

377

378 2.1

Sustainability in Manufacturing - Selected Applications Die sinking EDM (EDM)

Figure 2 shows the typical machine tool architecture of die sinking EDM. The main subunits of the system are: generator, positioning system, dielectric circuit (e.g. tank, filters, pumps…), exhaust system and the machine tool control.

filling the work tank. This machine also requires cooling water and compressed air. The wire guides are consumables as they need to be replaced regularly. The lubrication is done manually. 2.3

3 Figure 2: Sinking EDM machine tool [5]. The EDM machine tool analyzed in this study is a Roboform 350γ [7]. This machine has three linear and one rotational axis driven by servomotors. The dielectric system is driven by one pump and has a dielectric tank of 410 l. The dielectric (hydrocarbon oil) is filtered by four paper filters. Fumes and toxic gases are removed by an exhaust system using an external fan. The machine tool and the dielectric are cooled by an external closed cooling water circuit and the lubrication is obtained by distributing the lubrication oil from a centralized reservoir. 2.2

Wire EDM (WEDM)

The principle of wire EDM is sketched in Figure 3. In addition to the subunits listed for die sinking EDM, wire EDM requires a wire guiding system to position and guide the wire electrode.

Micro EDM (µEDM)

The investigated µEDM machine tool is a Sarix SX-100 [8]. The machine tool has two separate units: the controller unit including the generator and three servo driven axes and the dielectric system unit containing the compressed air driven pumps, filter and dielectric reservoir. As the dielectric is sprayed directly into the working gap, this differs from EDM and WEDM. During our study, an oil based dielectric was used. In case deionised water is used, an additional deionising filter is required. The electrode is a fixed rod, shaped by a wire electrode. The shaping of the electrode can be compared to machining with WEDM. This machine also requires cooling water (in our case tap water), compressed air and lubrication oil. LCI DATA COLLECTION

This section describes the Life Cycle Inventory data collected using the CO2PE!-methodology [2] [3]. The system boundaries of the analysis are set to include only the operating phase of the involved EDM machine tools. First results of the performed time and power measurements are presented. Furthermore, consumption of consumables and manufacturing emission data are listed based on industrial experience and literature in order to sketch an initial idea of the proportion of the energy related impact to the total generated environmental process impact (Section 4). 3.1

Time studies

Industrial time studies were performed for both EDM and WEDM. Important note here is that the industrial partners use some special clamping molds, which may influence the clamping time slightly. Nevertheless, this study gives an indication of the time distribution over the different modes. For µEDM a time study took place at the laboratory of the K.U.Leuven. Since the machine tools were never switched off, the start up phase is not included. Die sinking EDM For EDM, a time study was performed for ten different product designs on four different machine tools during six days. Three use modes have been identified: standby mode (e.g. process waiting for operator), supporting tasks mode (e.g. workpiece clamping, tool change, calibration…) and the operational mode (e.g. material removal). Figure 4 shows the share of the different modes. Supporting Mode 25%

Operational Mode 66%

Standby Mode 9% Figure 3: Wire EDM [5]. For WEDM, a first case study was performed on a Robofil 240cc machine tool [7]. These machines typically have five axes. The two heads which guide the wire can move in both X and Y directions. The upper head can additionally move up- and downwards. The wire itself is driven by a separate motor. The generator used in the machine studied has been designed for machining of ceramics. Besides four paper filters and a de-ionising filter, the dielectric system consists of four pumps: a filling pump (to fill the work tank with dielectric), a filter pump (to force the dielectric through the filters), a high pressure pump (to generate the pressure of the high pressure injection) and an assisting pump. The latter pump aids to deliver the wanted flow rate at high pressure and also assists in

Figure 4: Time share of the different production modes EDM. Wire EDM The time study for WEDM was performed on seven machine tools covering in total over 230 hours. Similarly to EDM, three production modes were identified: standby (e.g. process waiting for operator), supporting tasks (e.g. wire changing, workpiece clamping, tank filling…) and the operational mode. The share of the different modes is presented in Figure 5. Micro EDM For µEDM a time study took place at the laboratory of the K.U.Leuven After 7143 working hours, the investigated machine

Sustainability in Manufacturing - Selected Applications tool was in operational mode for about 6300 hours or 88.2% of the total time. Since the machine tool is switched off between two tests, the standby time is negligible, so the supporting takes approximately 11.8% Supporting Mode 9,5%

Operational Mode 83,5%

Standby Mode 7,0% Figure 5: Time share of the different production modes WEDM. 3.2

Power studies

During the power study, the electrical power consumption of the machine tools as well as their different subunits are investigated for all indentified production modes. Die sinking EDM The power consumption is measured for die sinking using a copper tool electrode (ø 14 mm) in combination with a hard metal (Sverker 21) workpiece. The applied discharge current is 16 A during the

379 roughing phase and 6 A during the finishing phase. Figure 6 shows the average electrical consumption during the different modes. For all modes, the pump is the main consumer ranging from 50 up to 72% of the total electrical power consumption. The generator itself has an average consumption of around 300 and 400 Watt during finishing and roughing respectively, a rather small contribution of about 10%. Wire EDM Figure 7 shows the results of the power study performed for WEDM. A ceramic (HfC) workpiece of 5mm was machined with a brass tool electrode. Compared to the EDM machine, the power consumption is higher, but similar to EDM also here the main power consumers are the pumps which use on average 65% of the total electrical power. The generator represents about 7% of the total power. Depending on the discharge frequency, the consumption rate of the generator will change. During similar measurements for an aluminium workpiece of 10 mm, the consumption during operational modes was around 1 kW higher than for the ceramic work piece of 5 mm. Besides the consumption of the generator was doubled to around 700 W, the increase is mainly driven by a higher consumption of the high pressure pump.

4 3,5 Power [kW]

3 2,5 2 1,5 1

Other Fans & Lightning Drives Generator Pump

0,5 0

Power (kW)

Figure 6: Electrical power consumption of EDM (copper electrode, hard metal workpiece).

5

Other

4

Fans

3 2 1 0

Drives Generator Filling pump Filtration pump Supporting pump High pressure pump

Figure 7: Electrical power consumption of WEDM (brass electrode, 5 mm ceramic workpiece).

380

Sustainability in Manufacturing - Selected Applications

Micro EDM For the µEDM machine tool, only the consumption of the two units as a whole are measured. Again the pump unit is consuming most of the power: on average 70%. The total power of the machine drops from 1 kW in the roughing/pre roughing phase to 130 W in the energy save mode. During the roughing/pre roughing mode, the pump uses 730 W, the controller uses then about 268W, in the finishing phase this is 676 W and 260 W respectively. There are two separate standby modes, one with high pressure (production ready) and one without. During both standby modes the controller uses 200 W. The pump unit consumes 505 W in the high pressure standby mode and 480 W in the other standby mode. During the energy save mode the pump unit is switched off. 3.3

Consumable studies

Besides energy, production processes also consume resources. Based on industrial experiences as well as literature, most relevant consumables for EDM, WEDM as well as µEDM processes are listed in Table 1. Consumables direct related to the number of production hours (e.g. dielectric, filters, lubrication oil…) are based on a working scheme of 2000 hours/year (250 days with one shift of eight hours). Furthermore also the removed workpiece material as well as the tool electrode wear should be taken into account. For products where the removed workpiece material cannot be easily obtained based on the product design, the former can be calculated by equations 1, 2 and 3, while equations 4 and 5 can be used for the latter [9] [10]. Important note here is that at some moment also the remaining part of the tool electrode should be remanufactured or even discarded resulting in an additional waste flow (and related environmental impact). R MRR m

6.64 10 R

I

R  

 I 

R

1.78 10

m

R  

,

 M

  I 

(1) (2)

= MRR 

 ρ  M

(3)

 ρ

.

(4) (5)

 ρ

With: I M M MRR

discharge current [A] melting point of the electrode [°C] melting point of the workpiece [°C] material removal rate [m³/s]

R R

average metal removal rate from electrode [m³/A s] average metal removal rate from workpiece [m³/A s]

m

mass flow of the tool material [kg/s]

m

mass flow of the workpiece material [kg/s]

ρ

mass density of the tool material [kg/m³]

ρ

mass density of the workpiece material [kg/m³]

For WEDM, the used tool electrode volume can be easily obtained by multiplying the wire speed with the wire diameter. 3.4

High temperature and pressure in the discharge channel of the EDM process can lead to the generation of reaction products in the hydrocarbon oil dielectric. Consequently, operators as well as the broader environment are exposed to these often toxic aerosols and gaseous emissions emitted from the dielectric surface. Evertz et al. [11] [12] and Jose et al. [13] performed exposure assessments to analyse the risk involved in this process. Electrode tools and work pieces used have a strong influence on aliphatic compounds and metals but not on volatile organic compounds such as benzene, toluene, ethylene-benzene and xylene (BTEX) and polycyclic aromatic hydrocarbons (PAHs) in air emissions [12]. Besides the material removal rate (MRR), used dielectric and both tool and workpiece material, the amount of generated and emitted emissions is dependent on several process parameters such as peak current, dielectric level, pulse duration and flushing pressure. While an increase in the former three parameters results in an increase of the concentration of aerosols, a reduction of aerosols can be observed for an increase of the flushing pressure [13]. Figure 8 [12] shows the total emissions for four different levels of discharge currents using an X36CrMo17 workpiece, R8340 tool electrode and a dielectric (hydrocarbon BP 200T) level of 35 mm. Emission data for different dielectric levels and combinations of workpiece (X3NiCoMoTi, 56NiCrMoV7, X36CrMo17) and electrode (R8340, R8500) materials as well as empirical equations for other current levels are given by Evertz [11]. For each variation, 3 up to 6 sample-parallels have been taken. For EDM systems without exhauster system, the concentration of aerosols at the breathing zone of the operator often exceeds the permissible exposure limit for respirable particles (5 mg/m³) once higher current values are applied. The concentration of aliphatic compounds and chromium are the most important here. Furthermore, contact with dielectric (air-bone or direct) may lead to allergic reactions (mostly skin) [12] [13].

EDM Compressed Air Dielectric

WEDM

µEDM

1 l/min (6 bar)

1 l/min (6 bar)

4,8 l/min (6 bar)

Hydrocarbon Oil

De-ionized water

Hydrocarbon Oil

10 l / week

10 l / week

0,45 l / week

Replacement each year

Replacement each year

Replacement each year Dielectric filters

Replacement every 200 hours

De-ionization Resin

/

Cooling water

6 l/min (10-15°C)

Air filters Others

Emission studies

Replacement each year

/

6 l/min (10-15°C)

2 l/min (10-15°C, >2 bar))

Replacement every three months Lubrication Oil

Grease: 250 g/Year

0.5 – 1 l / Year

Wire Guides

Table 1: Consumables for EDM, WEDM and µEDM.

Grease: 100 g/Year Wire electrode for shaping

Sustainability in Manufacturing - Selected Applications

381

Figure 8: Total emissions [mg/min] for different discharge currents [12]. Processes using de-ionized water (e.g. WEDM) or water-based dielectrics have less environmental risks. The expected emissions here are carbon monoxide, nitrogen oxide, ozone and some other aerosols [14]. The nature of these emissions could explain both the limited available data on generated process emissions and the lack of exhauster systems by for example WEDM processes. 4

LIFE CYCLE ANALYSIS (LCA)

In order to obtain an initial idea about the most important contributors to the environmental impact of die sinking processes, this section describes a preliminary LCA for one hour of EDM roughing. Figure 9 summarizes the distribution of a range of different impact creating factors for one hour of EDM roughing including energy and resource (dielectric, tool electrode, removed workpiece material, compressed air…) consumption as well as the generated process emissions based on a working scheme of 2000

Compresed Air 0,1% Energy  Consumption  Exhaust  System 3,9%

Energy  Consumption  EDM Process 47,3%

Lubrication 0,1%

hours a year. Production and end of life treatment of filters are not taken into account. Emitted aerosols and gasses are modeled as air emissions instead of immissions. The impacts are calculated based on the ReCiPe Endpoint (H) V1.04 / Europe ReCiPe H/A method [15] using the ecoinvent v2.0 database [16] and expressed in millipoints (mPts). Despite the potential risks for EDM operators (e.g. exceeding of the permitted concentration of aerosols and gaseous emissions), the environmental impact is mainly caused by the consumed electrical energy (47,3%) and the dielectric (23,1%). Due to the limited available data about consumables and generated process emissions, the data representativeness and accuracy for some input parameters should be improved before more generic conclusions can be formulated.

Energy  Consumption  Process  Cooling 19,4%

Process  Emissions 0,0% Dielectric  (Production +  EOL) 23,1%

Workpiece  Material 1,0%

Electrode  Material 5,1%

Figure 9: Distribution of the environmental impact during 1 hour of EDM roughing (copper electrode, hard metal workpiece) based on the ReCiPe Endpoint (H) V1.04 / Europe ReCiPe H/A method [15] using the ecoinvent v2.0 database [16] and expressed in millipoints (mPts).

382 5

Sustainability in Manufacturing - Selected Applications IMPROVEMENT POTENTIAL

As indicated in Section 4, the environmental impact is mainly caused by the consumed electrical energy and in case of hydrocarbon oil using processes the production as well as the end of life treatment of the dielectric. Reduction measures for both impact creating factors are investigated and some improvement potential is described below. First, the total energy consumption can be minimized by selectively switching on and off non required subsystems over the different modes. As the pumps consume on average around 60% of the total energy, switching off the different pumps during supporting (e.g. workpiece clamping, tool change, calibration…) and standby modes could provide significant electrical energy savings. Some machine tools are already equipped with a “green” standby mode in which similar measures result in energy reductions up to 66%. Intelligent self decision technologies could assist here to optimize the use of this mode. Since the machining speed increases disproportionally with higher discharge currents and in consequence higher energy consumption rates, another energy reduction measure can be found in higher material removal rates. Often, the MRR could be further increased by the use of ultrasonic vibrations of the workpiece [6]. Of course also other process parameters such as the required surface conditions and accuracy should be taken into account here. Next to the electrical energy consumption, also the use of hydrocarbon oil dielectrics has an important contribution to the environmental impact. Therefore the replacement of hydrocarbon oil dielectrics by water-based (plain water, water mixed with organic compounds, de-ionized water...) or gaseous (Dry-EDM) dielectrics could help to reduce the environmental impact and related human health risks. [6] [17] An approach to reduce the consumption of dielectrics could be the use of jets to provide the required dielectric in the gap between electrode tool and dielectric instead of the use of immersing both the workpiece and electrode in the dielectric tank. [17] Finally also different factors to reduce the electrode tool wear ratio such as the polarity and thermal properties of the electrode materials are important parameters which can be influenced to reduce the created impacts. One of the greatest advantages of the use of gaseous dielectrics is the very low level of electrode wear. [5] 6

SUMMARY

Using the CO2PE!-Methodology [2] [3], Life Cycle Inventory (LCI) data is collected and the environmental performance regarding energy and resource consumption as well as generated emissions of three case studies performed on an EDM, WEDM as well as µEDM machine tool are investigated in this paper. Impact reducing measures are presented for the most important contributors to the environmental impacts. Future work comprises the completion of the LCI data regarding consumables and process emissions as well as a wider coverage of the different variants/capacities of machine tools within these processes. Furthermore, the influence on the environmental footprint of both, the selected process parameters (e.g. discharge current…) and material for tool electrode as well as workpiece material will be analysed more in detail. 7

ACKNOWLEDGMENTS

The authors acknowledge the support of the Institute for the Promotion of Innovation through Science and Technology in Flanders (IWT-Vlaanderen) through its PhD grant N°091232, and of the European Fund for Regional Development (EFRO - Europees Fonds voor Regionale Ontwikkeling) and the Agentschap Ondernemen (Flemish government) through the D2 project 476.

8

REFERENCES

[1]

Gutowski, T., C. Murphy, D. Allen, D. Bauer, B. Bras, T. Piwonka, P. Sheng, J. Sutherland, D. Thurston, and E. Wolff, (2005), Environmentally benign manufacturing: Observations from Japan, Europe and the United States, in: Journal of Cleaner Production, Vol.13, pp 1-17.

[2]

CO2PE! (Cooperative Effort on Process Emissions in Manufacturing) – Website and data exchange platform, http://www.mech.kuleuven.be/co2pe!

[3]

Kellens, K., Dewulf, W., Overcash, M., Hauschild, M., Duflou, J.R., (2010), Methodology for systematic analysis and improvement of manufacturing unit process life cycle inventory (UPLCI), Part 1: Methodology Description., Submitted for publication in Int. J LCA. Lazarenko, B.R., (1943), To invert the effect of wear on electric power contacts, Dissertation of the All-Union Institute for Electro Technique in Moscow/CCCP (in Russian).

[4]

[5]

Kunieda, M., Lauwers, B., Rajurkar, K.P., Schumacher, B.M., (2005), Advancing EDM through Fundamental Insight into the Process, CIRP Annals – Manufacturing Technology, Vol. 52, pp. 64-87.

[6]

Abbas, N.M., Solomon, D.G., Bahari, F., (2007), A review on current researchtrends in electrical discharge machining, Int. Journal of Machine Tools & Manufacture, Vol. 47, pp. 12141228.

[7]

Website of Agie Charmilles: http://www.gfac.com/gfac.html, last visited 28th October 2010.

[8]

Website of Sarix: http://www.sarix.com/ , last visited 28th October 2010.

[9]

Yeo, S.H., Tan, H.C., New, A.K., (1998), Assessment of waste streams in electric discharge machining for environmental impact analysis, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 212/5, pp. 393-401.

[10]

Weller, E.J., (1984), Non-Traditional Machining Processes 2nd edition, Society of Manufacturing Engineers Michigan. .

[11]

Evertz, S., (2003), Electrical Discharge Machining: exposure assessment using emission and immission based monitoring, PhD thesis, faculty of mathematics, informatics and natural science, RWTH Aachen.

[12]

Evertz, S;, Dott, W., Eisentraeger, A., (2006), Electrical discharge machining: Occupational hygienic characterization using emission based monitoring, Int. Journal of Hygiene and environmental health, Vol. 209, pp. 423-434.

[13]

Jose, M., Sivapirakasam, S.P., Surianarayanan, M., (2010), Analysis of Aerosol Emission and Hazard evaluation of Electrical Discharge Machining (EDM) Process, Int. Journal of Industrial Health, Vol. 48, pp. 478-486.

[14]

Bommeli, B., (1983), Study of the harmful emanations resulting from the machining by electro-erosion, Ateliers de Charmilles S.A. .

[15]

ReCiPe, (2008), http://www.lcia-recipe.net, last visited 17th November 2010.

[16] Ecoinvent v2.0 dbase, (2007), http://www.ecoinvent.org, last visited 28th October 2010. [17]

Leão, F., Pashby, I., (2004), A review on the use of is environmentally-friendly dielectric fluids in electrical d charge machining, J. of Materials and Processing Technology, Vol. 149, pp. 341-346.

Development of an Interpretive Structural Model of Obstacles to Environmentally Conscious Technology adoption in Indian Industry 1

Varinder Kumar Mittal , Kuldip Singh Sangwan 1

1

Mechanical Engineering Department, Birla Institute of Technology & Science, Pilani, Rajasthan INDIA

Abstract Rapid economic and industrial growth of emerging economies like India is posing environmental and social problems not only to their own countries but also to the world. The adoption of environmentally conscious technologies (ECT) in emerging countries faces many obstacles. This paper identifies eleven obstacles to ECT adoption from review of literature. Further an interpretive structural modelling technique has been used to develop a structural model to obtain a proper hierarchy and interrelationship among the obstacles. This model will help the decision makers in industry and government to prioritize the focus on the obstacles for adoption of ECT. Keywords: Environmentally Conscious Technology; Interpretive Structural Modelling; Obstacles

1

INTRODUCTION

Environmentally conscious technology has become a buzzword these days in academic institutions and industries round the globe. Because of increased concerns of the world about the pollution problem and depletion of natural resources, a growing number of firms in developed countries have begun working towards adoption of environmentally conscious technologies (ECT) but the firms in emerging countries like India show reluctance for the adoption of these technologies because of some obstacles. Emerging economies like India and China are growing at a rate of more than 8% (in 2008), which is greater than the growth rate of many developed countries like the US, Japan, Canada and the UK. Statistics of 2008 show that the GDP of India is 4th highest in the world and India is at 5th position in CO2 emissions in the world which reflects the level of industrialization of the country [1]. Researchers have shown that current levels of consumption are far beyond the level the planet can sustain. If everyone lived as the West does, we would need 3 to 5 times what the planet is estimated to provide [2]. Therefore, there is a growing need to adopt environmentally conscious technologies in emerging economies like India. There are indications that some Indian industries are willing to adopt these technologies [3]. However, initiation for adoption of ECT is not an easy task for India because of social, political and economical reasons on one side and on the other side the lack of trained manpower and alternative technologies coupled with the pressure for lower prices makes it difficult for the industry to adopt. Successful adoption of ECT needs not only cooperation among the employees at all levels of the hierarchy, but also financial and policy support and incentives from the government. Proper identification of obstacles hindering the adoption of ECT is a prerequisite to the formulation of appropriate policies by the government and the industry to mitigate these obstacles. There are few research articles which have identified the obstacles to the adoption of newer or alternative technologies for European, Japanese, Chinese and American industries but none for the Indian industry. However, to the best of author’s knowledge, there exists

no framework of these obstacles which can provide, the decision makers, insight into relationship among various obstacles. In this paper, an attempt has been made to identify the obstacles to environmentally conscious technologies through a study of 19 research articles during 1994 – 2009 and discussions with practitioners. A hierarchy has been established among the obstacles and a model showing the interrelationship has been developed using an interpretive structural modeling (ISM) method. 2

OVERVIEW OF OBSTACLES TO ECT ADOPTION

Eleven obstacles have been identified from a literature review of 19 peer-reviewed research journal articles [4-22], which are further scrutinized by discussions with academician working in this area and some top level executives from industries having knowledge about the subject as shown in Table 1. An overview of these obstacles is presented below: 2.1

Lack of Information

There is a general difficulty in accessing and appreciating cleaner production related information and acting on it. Also managers and staff are unaware of cleaner production’s economic and environmental benefits [4]. Lack of awareness, education and training on cleaner production technologies hinder the adoption of cleaner production technologies. The difficulty of collecting appropriate data and measurement problems may also be barriers to cleaner production [5] [6]. It has been pointed out by a group of environmental managers that the companies generally have very limited knowledge about the environmental aspect of their products [7]. Data often exist only for selected aspects of a production site (e.g. energy use, water consumption, emissions) but even this data cannot be broken down to the specific products. Therefore, environmental managers often do not provide detailed information about areas for improvements for future products [7]. 2.2

High Cost

The implementation cost is an important barrier in ECT adoption. Ries et al [7] explained after discussions with 20 environmental

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_66, © Springer-Verlag Berlin Heidelberg 2011

383

Zhang (2000) [11]

Zhang et al (2009) [18]

Luken and Rompaey (2008) [12]

Hilmi Yuksel (2008) [8]

Post and Altman (1994) [6]

Ries et al (1999) [7]

Karakosta and Psarras (2009) [19]

Pitt et al ( 2009) [20]

Ang and Wilkinson (2008) [15]

Mont and Leire (2009) [13]

Roberts and Sims (2008) [14]

Dixon et al (2008) [21]

Veshagh and Li (2006) [22]

8

9

10

11

12

13

14

15

16

17

18

19

√ 

 

√ 

 

√ 

√ 

√ 

√ 

 

√ 

 

√ 

 

√ 

 

√ 

√

 

√ 

√ 

√ 

√ 

√ 

√ 

√ 

 

 

√ 

√ 

 

 

 

 

 

√ 

 

 

 

 

 

 

√ 

√ 

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Thiruchelvam et al (2003) [5]

7

Wang (1999)[16]

6

Shi et al (2008) [4]

5

Sardianou (2008) [9]

Walker et al (2008) [10]

Sustainability in Manufacturing - Selected Applications

Cooray (1999) [17]

384

Obstacles

1

2

3

4

Lack of Information

√ 

√ 

√ 

√ 

High Cost

√ 

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Fear of Success

 

√ 

 

 

Lack of Alternative Technology

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Lack of Human Resources

√ 

 

 

No/weak Legal Structure

 

√ 

Lack of Public Demand

 

√ 

Lack of Government Support

 

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Pressure for Lower Prices

 

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Slow Rate of Return

√ 

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Lack of Performance Measures

 

 

 

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√ 

AUTHOR(S) AND YEAR

Table 1: Literature Review of Obstacles of ECT adoption. managers that cost-orientation is a bigger obstacle than strategic orientation. The marketing department often shares the opinion that it is mainly seen as an increasing cost for the design but barely adding value to the product. There are few market analyses studying the customer demand in this respect. Since marketing is a driving force in the early phases of product planning, the lack of expertise is even more significant in this area. A high capital cost is required to implement cleaner technologies and any new technology. Arrangement of funds for major and minor environmental improvements, expected internal rate of return on capital projects is hence acting as a barrier to the ECT adoption [6]. Shi et al [4] also support that higher initial capital costs of clean technology as compared to conventional technologies prevent organizations from implementing cleaner production. 2.3

Fear of Success

The fear of success plays a vital role amongst managers to implement new technologies. In a study of Chinese SME’s it was found that a manager’s worry about the risks in changing the current production processes and technologies is a major barrier during the implementation of cleaner production [4]. 2.4

Lack of Alternative Technology

Industries face major hurdles in environmentally conscious technology adoption as there is a lack of alternate green technologies. Organizations are incompetent at accessing external technical support while the internal support is insufficient [4]. 2.5

Lack of Human Resources

A lack of skilled personnel to implement and operate ECT acts as a hindrance in the adoption. The technical and information barrier is an internal barrier which depends on the characteristics of the company itself. Shi et al [4] further argued that limited in-plant technical staffs are fully occupied on daily production, let alone

identifying and implementing new cleaner production. In SMEs, training programs for the employees to operate and maintain cleaner production at shop floor level are insufficient. 2.6

No/weak Legal Structure

The absence of a sufficient legal structure poses as a barrier as legislation is treated as help in setting goals. Existing standards on EMS focus on both legal compliance and continual improvement. The former sets a kind of minimum requirement. Environmental legislation often prescribes a certain kind of environmental goal. In many west European countries environmental legislation emphasizes limit values for emissions. It is highly site-oriented and only a few regulations focus on a broader concept of product orientation [7]. Companies have therefore little incentive to set product-oriented goals. In a study on Chinese firms, it is pointed out that a weak enforcement of environmental regulations does not make the adoption of cleaner production an urgent task [4]. Constraints like regulations, standards and operating permits act as barriers to environmental change and ECT adoption [6]. 2.7

Lack of Public Demand

There is dire lack of pressure by customers, media, community and NGO’s for ECT adoption as the environmental concerns are either very low or no concerns. The environmental concern of the customers and legislators had a significant impact on the environmental engagement of businesses. However, environmental issues have not yet become subject customers explicitly ask for [7]. In some developing countries, it is suggested that customers do not demand or prefer products produced in a more environmentally sound manner [3]. In some studies, lack of community concerns like perception of risks associated with the business is also considered as a barrier to ECT adoption [6].

Sustainability in Manufacturing - Selected Applications 2.8

Lack of Government Support

Lack of government support in technology transfer from developed countries to developing countries, help to provide land for project expansion, to spread awareness among masses for the need of ECT etc., for companies to move towards green initiatives is found to be an important obstacle. In developing countries like India, lack of financial support or incentives like tax exemptions and grants for the installation of newer technologies is probably one of the important barriers to cleaner production initiatives. 2.9

Pressure for Lower Prices

Companies are always under immense pressure to sell products at lower prices owing to international competition. Under these circumstances the adoption of cleaner production often incurs additional costs. It also undermines competitiveness of enterprise in the market place [4]. Having a leading edge in the market is a must for companies to survive in the market and the adoption of newer technologies may increase their cost. Indian market being highly sensitive to price changes deters the adoption of new technologies, which may require an increase in initial product cost. 2.10 Slow Rate of Return Slow rate of return on the investments made in adopting cleaner production processes and techniques and longer gestation periods make companies especially SME’s reluctant to invest in ECT [4]. The investment in time and money for the environmental programmes has to be justified by the managers through a cost benefit analysis. Managers often encounter major difficulties in measuring ecological improvements and expressing environmental improvements as economical benefits. The investment in ECT tends to be a long term investments which does not show immediate tangible benefits. Also the outcome is highly uncertain and difficult to predict [7].

385 ISM methodology helps to impose order and direction on the complexity of relationships among elements of a system for complex problems like the one under consideration. However, the direct and indirect relationships between the obstacles describe the situation far more accurately than the individual factor taken into isolation. Therefore, ISM develops insights into collective understandings of these relationships. The ISM is interpretive as the judgment of the group decides whether and how the variables are related. It is structural as on the basis of relationship an overall structure is extracted from the complex set of variables. Developing inter-relationships among variables through the expert opinion has been used and recommended by many researchers [23-26]. It is a modeling technique as the specific relationships and overall structure are portrayed in a graphical model. It is primarily intended as a group learning process but can also be used individually. The various steps involved in the ISM methodology are: 

Identifying the elements, which are relevant to the problem or issue, this could be done by a literature survey or any group problem solving technique.



Establishing a contextual relationship between elements with respect to which pairs of elements will be examined.



Developing a structural self-interaction matrix (SSIM) of elements indicating pair-wise relationship among elements of the system.



Developing a reachability matrix from the SSIM, and checking the matrix for transitivity. Transitivity of the contextual relation is a basic assumption in ISM which states that if element A is related to B and B is related to C, then A is necessarily related to C.



Partitioning of reachability matrix into different levels and drawing ISM model.



Review of the ISM model to check for conceptual inconsistency and make the necessary modifications.

2.11 Lack of Performance Measures The need of performance indicators to show the improvements in the existing system is highly required to convince owners to invest in ECT. The lack of performance measures results in reluctance to ECT adoption. This also leads to difficulty in demonstrating and quantifying the impact of ECT on a company [5]. 3

DEVELOPMENT OF ISM MODEL

ISM is an interactive learning process whereby a set of different directly and indirectly related elements are structured into a comprehensive systemic model. The model so formed portrays the structure of a complex issue in a carefully designed pattern employing graphics as well as words.

S. No. 1 2 3 4 5 6 7 8 9 10 11

Obstacles Lack of Information High Cost Lack of Human Resources No/Weak Legal Structure Lack of Govt. Support Lack of Public Demand Slow Rate of Return Lack of Performance Measures Pressure for Lower Prices Lack of Alternate Technology Fear of Success

The following shows the development of an interpretive structural model of 11 obstacles to ECT adoption in Indian industry: 3.1

Structural self-interaction Matrix (SSIM)

Experts from the Indian industry and academia were consulted in identifying the nature of contextual relationships (see Table 2) among the obstacles though ISM methodology suggests the use of expert opinions alone based on management techniques such as brain storming, nominal group technique, etc. For analyzing the obstacles in developing SSIM, the following four symbols have

2 V

3 V X

4 V X X

5 V O V V

Obstacles 6 7 V V V V O V X V A O V

Table 2: Structural Self-interaction matrix (SSIM).

8 V V V V V V V

9 V V V V O V O A

10 V V V V V V V V V

11 V V V V V V V V V A

386

Sustainability in Manufacturing - Selected Applications

been used to denote the direction of relationship between obstacles i and j:



If the (i, j) entry in the SSIM is V, the (i, j) entry in the reachability matrix becomes 1 and the (j, i) entry becomes 0.

V = Obstacle i will help achieve obstacle j;



If the (i, j) entry in the SSIM is A, the (i, j) entry in the reachability matrix becomes 0 and the (j, i) entry becomes 1.



If the (i, j) entry in the SSIM is X, the (i, j) entry in the reachability matrix becomes 1 and the (j, i) entry also becomes 1.



If the (i, j) entry in the SSIM is 0, the (i, j) entry in the reachability matrix becomes 0 and the (j, i) entry also becomes 0.

A = Obstacle j will be achieved by obstacle i; X = Obstacle i and j will help achieve each other O = Obstacle i and j are unrelated. 3.2

Initial Reachability Matrix

The SSIM has been converted into a binary matrix called the initial reachability matrix by substituting V, A, X and O by 1 and 0 as per the following rules:

Obstacles S.No.

Obstacles

1

2

3

4

5

6

7

8

9

10

11

1 2 3 4 5 6 7 8 9 10 11

Lack of Information High Cost Lack of Human Resources No/Weak Legal Structure Lack of Govt. Support Lack of Public Demand Slow Rate of Return Lack of Performance Measures Pressure for Lower Prices Lack of Alternate Technology Fear of Success

1 0 0 0 0 0 0 0 0 0 0

1 1 1 1 0 0 0 0 0 0 0

1 1 1 1 0 0 0 0 0 0 0

1 1 1 1 0 1 0 0 0 0 0

1 0 1 1 1 1 0 0 0 0 0

1 1 0 1 0 1 0 0 0 0 0

1 1 1 1 0 1 1 0 0 0 0

1 1 1 1 1 1 1 1 1 0 0

1 1 1 1 0 1 0 0 1 0 0

1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 0 1

Table 3: Initial Reachability Matrix.

S. No.

Obstacles

1 1 0 0 0 0 0 0 0 0 0 0 1

1 Lack of Information 2 High Cost 3 Lack of Human Resources 4 No/Weak Legal Structure 5 Lack of Govt. Support 6 Lack of Public Demand 7 Slow Rate of Return 8 Lack of Performance Measures 9 Pressure for Lower Prices 10 Lack of Alternate Technology 11 Fear of Success Dependence

2 1 1 1 1 0 1 0 0 0 0 0 5

3 1 1 1 1 0 1 0 0 0 0 0 5

4 1 1 1 1 0 1 0 0 0 0 0 5

Obstacles 5 6 7 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 6 5 6

8 1 1 1 1 1 1 1 1 1 0 0 9

9 1 1 1 1 0 1 0 0 1 0 0 6

10 1 1 1 1 1 1 1 1 1 1 1 11

11 1 1 1 1 1 1 1 1 1 0 1 10

Driving Power 11 10 10 10 4 10 4 3 4 1 2

Table 4: Final Reachability Matrix.

Iteration

Obstacle

Reachability Set

Antecedent Set

Interaction Set

Level

6 5 5 5 4 5 4 3 4 1 2

1 2 3 4 5 6 7 8 9 10 11

1,2,3,4,5,6,7,8,9,10,11 2,3,4,5,6,7,8,9,10,11 2,3,4,5,6,7,8,9,10,11 2,3,4,5,6,7,8,9,10,11 5,8,10,11 2,3,4,5,6,7,8,9,10,11 7,8,10,11 8,10,11 8,9,10,11 10 10,11

1 1,2,3,4,6 1,2,3,4,6 1,2,3,4,6 1,2,3,4,5,6 1,2,3,4,6 1,2,3,4,6,7 1,2,3,4,5,6,7,8,9 1,2,3,4,6,9 1,2,3,4,5,6,7,8,9,10,11 1,2,3,4,5,6,7,8,9,11

1 2,3,4,6 2,3,4,6 2,3,4,6 5 2,3,4,6 7 8 9 10 11

VI V V V IV V IV III IV I II

Table 5: Level identification (Iterations 1-6).

Sustainability in Manufacturing - Selected Applications

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The initial reachability matrix obtained by following the above rules is shown in Table 3. 3.3

Final Reachability Matrix

The final reachability matrix (Table 4) is developed from the initial reachability matrix after incorporating the transitivities as discussed previously in this section. The driving power and dependence of each obstacle are also shown in Table 4. Driving power for each obstacle is the total number of obstacles (including itself), which it may help achieve. On the other hand dependence is the total number of obstacles (including itself), which may help achieving it. The driving power and dependency will be used later in the classification of obstacles. 3.4

Level Partitions

From the final reachability matrix, the reachability and antecedent sets for each obstacle are found [27]. The reachability set consists of the element itself and other elements, which it may help achieve, whereas the antecedent set consists of the element itself and the other elements, which may help achieving it. Next, the intersection of these sets is derived for all elements. The element for which the reachability and intersection sets are same is the top-level element in the ISM hierarchy. The top-level element of the hierarchy would not help achieve any other element. Once the top-level element is identified, it is separated out from the other elements. This process continues till all elements are assigned levels. The identified levels help in building the final model. In the present case the obstacles along with their reachability set, antecedent set, intersection set and the levels are shown in Table 5. 3.5

ISM based model building

The structural model is generated by means of vertices/nodes and lines of edges. A relationship between the obstacles j and i is shown by an arrow which points from i to j or j to i depending upon the relationship between i and j as discussed in section 3.1. ISM model developed after removing the transitivities as described in ISM methodology is shown in Figure 1. All the eleven obstacles to

Lack of Alternate Technology

ECT adoption has been divided into six levels. The lack of information among the Indian public, government and industry is the basic obstacle to ECT adoption in Indian industry which in turn influences the public demand, legal structure, cost and human resources in this area. The general awareness among public may results in government support. Indian government is also influenced by the lack of human resources in this area to make strong legal structure. The high cost of ECT at present put the pressure on prices and rate of return which in turn influences the industry not to adopt ECT as Indian market is highly price sensitive. Lack of government support, pressure for lower prices and slow rate of return (level 4 obstacles) are supported by level 5 obstacles but not by each other. Obstacles at level 4 lead to lack of performance measures in an organization by which ECT adoption can be justified. It leads to the fear of success among the decision makers which ultimately results in the lack of alternative technologies being adopted as shown in Figure 1. 4

MICMAC ANALYSIS

The MICMAC analysis is used to analyze the driver and dependency power of obstacles. The main objective of MICMAC analysis is to analyze the driving power and the dependency of the variables [28]. The obstacles are classified into four clusters based on their driving power and dependency as shown in Figure 2. Quadrant I shows the first cluster of the obstacles, these are “autonomous obstacles” with weak driving and dependence powers. These obstacles are relatively disconnected from the system with which they have only few links. Quadrant II shows, the second cluster known as the “dependent obstacles” with weak driving power but strong dependence. Quadrant III represents the third cluster of obstacles known as “linkage obstacles” having strong driving power and dependence. Quadrant IV represents the fourth cluster of obstacles, known as “independent obstacles” having strong driving power but weak dependence. Lack of information among public, government and manufacturers is driving all other obstacles but is not driven by other obstacles. On the other hand, lack of alternate technology is driven by all other obstacles but not driving any other obstacle. The decision makers who are looking to adopt ECT should look at quadrant IV obstacles first and quadrant II obstacles at last.

11 Fear of Success

1

10

2,3 4,6

IV

III

9 Lack of Performance Measures

Pressure for Lower Prices

Slow Rate of Return

Driving Power

Lack of Govt. Support

8 7 6 5 5,7 9

4 3

Lack of Public Demand

No/ Weak Legal Structure

High Cost

Lack of Human Resourses

10

1 2

3

4

5

6

7

8

9

Dependence Figure 2: Driver-dependence diagram.

Figure 1: The ISM model of obstacles to ECT adoption.

II 11

2

1 Lack of Information

8

I

10

11

388 5

Sustainability in Manufacturing - Selected Applications SUMMARY

[13]

Mont O., Leire C. (2009): Socially responsible purchasing in supply chains: drivers and barriers in Sweden, in: Social Responsibility Journal, Vol. 5, No. 3, pp. 388-407.

[14]

Roberts C, Sims S. (2008): Cashing in on the green machine: are developers in the UK missing out?, in: International Journal of Housing Markets and Analysis, Vol. 1, No. 4, pp. 362-378.

[15]

Ang SL, Wilkinson SJ. (2008): Is the social agenda driving sustainable property development in Melborne, Australia?, in: Property Management, Vol. 26, No. 5, pp. 331-343.

[16]

Wang J, (1999): China’s national cleaner production strategy, in: Environmental Impact Assess Review, Vol. 19, No. 5, pp. 437-456.

[17]

Cooray N. (1999): Cleaner production assessment in small and medium industries of Sri Lanka, in: Proc. of the second Asia Pacific Cleaner Production Roundtable.

[18]

Zhang B, Bi J, Liu B. (2009): Drivers and barriers to engage enterprises in environmental management initiatives in Suzhou Industrial Park, China, in: Front. Environ. Sci. Engin., Vol. 3, No. 2, pp. 210–220.

[19]

Karakosta C., Psarras J. (2009): Facilitating sustainable development in Chile: a survey of suitable energy technologies, in: Intl. J of Sustainable Development & World Ecology, Vol. 16, No. 5, pp. 322 — 331.

[20]

Pitt M, Tucker M, Riley M and Longden J. (2009): Towards sustainable construction: promotion and best practices, in: Construction Innovation, Vol. 9, No. 2, pp. 201-224.

[21]

Dixon T, Colantonio A, Shiers D, Reed R, Wilkinson S, Gallimore P. (2008): A green profession?, in: Journal of Property Investment & Finance, Vol. 26, No. 6, pp. 460-481.

Thiruchelvam M, Kumar S, Visvanathan C. (2003): Policy options to promote energy efficient and environmentally sound technologies in small – and medium – scale industries, in: Energy Policy, Vol. 31, No. 10, pp. 977-987.

[22]

Veshagh A, Li W. (2006): Survey of eco design and manufacturing in automotive SMEs, in: Proc. of LCE 2006.

[23]

Sage A.P., (1997): Interpretive Structural Modeling, in: McGraw-Hill New York, pp. 91-164.

[6]

Post JE, Altman BW. (1994): Managing the Environmental Change Process: Barriers and Opportunities, in: Journal of Organizational Change Management, Vol. 7, No. 4, pp. 6481.

[24]

Jharkharia S, Shanker R. (2005): IT-enablement of supply chains: understanding the barriers, in: The J of Enterprise Information Management, Vol. 18, No. 1, pp. 11-27.

[7]

Ries G., Winkler R., Zust R. (1999): Barriers for a Successful Integration of Environmental Aspects in Product Design, in: Proc. Of Ecodesign’99, Japan, pp. 527-532.

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Soti A, Shanker R, Kaushal OP. (2010): Modeling the enablers of Six Sigma using interpretive structural modeling, in: J of Modeling in Management, Vol. 5, No. (2), pp. 124-141.

[8]

Yuksel H. (2008): An empirical evaluation of cleaner production practices in Turkey, in: Journal of Cleaner Production, Vol. 16, No. 1, pp 50-57.

[26]

Mohammed, I.R., Shankar, R. and Banwet, D.K. (2008): Creating flex-lean-agile value chain by outsourcing: an ISMbased interventional roadmap, in: Business Process Management Journal, Vol. 14, No. 3, pp. 338-89.

[9]

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[28]

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This paper identifies eleven obstacles hindering the adoption of ECT in Indian industry through literature survey and discussion with industry and academic experts in environmentally conscious manufacturing. These obstacles are mainly driven by a lack of information among public, government and manufacturers. These eleven obstacles have different influence on ECT adoption and also have relationships among them. An interpretive structural model has been developed to study the strength and interrelationship among these obstacles. The developed model gives a visual and quick understanding to decision makers in industry and government to mitigate these obstacles. However, this model has been developed with the discussion with few Indian practitioners and academicians working in this area and it need to be further statistically tested by empirical studies to validate the different obstacles and to find their degree of influence. Further studies can be carried out in different industry sectors. 6

REFERENCES

[1]

The World Factbook. (2010): United States Intelligence Agency (CIA). Data from 1993 – 2009.

[2]

Childe S.J. (2009): A vision to sustainability, in: Production, Planning & Control, Vol. 20, No.8, pp. 665.

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Kumar, V., Singh, P.J., Sangwan, K.S. (2009): Benefits and Stakeholders of Green Manufacturing: A Study of Indian Industry, in Proc. Of the 7th Global Conference on Sustainable Manufacturing, IIT Madras, India, pp. 335-340.

[4]

[5]

Central

Shi H., Peng SZ, Liu Y, Zhong P. (2008): Barriers to the implementation of cleaner production in Chinese SMEs: government, industry and expert stakeholders’ perspectives, in: Journal of Cleaner Production, Vol. 16, No. 7, pp. 842-852.

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Zhang T.Z. (2000): Policy mechanisms to promote cleaner production in China, in: Journal of Environmental Science and Health, Vol. A35, No. 10, pp. 1989-1994.

[12]

Luken R., Rompaey FV. (2008): Drivers and barriers to environmentally sound technology adoption by manufacturing plants in nine developing countries, in: Journal of Cleaner Production, Vol. 16, No. 1, pp. 67-77.

Identifying Carbon Footprint Reduction Opportunities through Energy Measurements in Sheet Metal Part Manufacturing 1

1

1

1

1

Chee Wai Patrick Shi , Fatida Rugrungruang , Zhiquan Yeo , Kenneth Hong Kiat Gwee , Ruisheng Ng , Bin Song 1

1

Singapore Institute Technology of Manufacturing, 71 Nanyang Drive, Singapore 638075

Abstract This paper measures the energy consumption in sheet metal part manufacturing to identify the opportunities to reduce carbon footprint. The scope of work focuses on the gate-to-gate sheet metal manufacturing processes, covering tool making, stamping, secondary processes and plant facilities. The case study results show that focus should not only be directed to the stamping process but extend to include secondary processes. In this case, approximately 66% of carbon footprint of the sheet metal parts is contributed by the oven curing process. Recommendations to lower energy consumption are also proposed to further reduce the carbon footprint of sheet metal part. Keywords: Sheet Metal Part; Carbon Footprint; Energy Efficiency

1

INTRODUCTION

The energy consumption in Singapore has increased as the nation becomes more industrialised. From the historical data reflected by the Energy Market Authority (EMA) [1] of Singapore, the electrical consumption for the manufacturing sector alone has risen 33.32% from the year 1986 to 2009. Figure 1 clearly illustrates the country’s energy consumption for the manufacturing industries located in Singapore. For the year 2009, the energy consumption for the manufacturing sector is approximately 35.89% of the overall energy provided by the grids. The carbon footprint for the manufacturing sector in the year 2009 amounted to 7.9M ton CO2eq/kWh. GWh 16,000 14,000 13,628 GWh 2009

12,000 10,000 8,000 6,000 4,000 2,000

4,267 GWh 1986

1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

0

Years

Figure 1: Electricity consumption of Singapore. Carbon footprint assessment is a possible mechanism to help the industry reduce their greenhouse gas (GHG) emissions and create a more sustainable manufacturing arena within Singapore. Adoption of this methodology not only allows companies to respond to the government’s call, customers and stakeholders’ demands, but benefits reaped from the exercise can also help the former to improve their energy efficiency, reduce resources consumed, and generate less or no waste. Climate change is an issue the world and its leaders have to deal with. The Intergovernmental Panel on Climate Change (IPCC) studies has shown that in order to avoid

imbalance in ecological system, the global temperature should only be limited to an increase of 2˚C before the industrial level in the 1970s [2]. The present 0.74˚C of increase has ready shown signs of the climate changing. The reduction in snow and ice in the northern hemisphere, the increase in global temperature, the rise of sea level, and the extreme weather occurring in the recent years are signs that are of great concerns. IPCC’s requirement for today’s industrial nation is to reduce carbon footprint (greenhouse gas emissions) by as much as 80% by 2050 [3]. In the recent years, many companies in Singapore have expressed their concern for climate change by assessing their environmental performance of their products and services by undertaking carbon footprint assessments. Having to produce a product with a lower carbon footprint would also distinguish one company from another. This is especially true for service manufacturers in Singapore. The paper presents the carbon footprint analysis conducted for sheet metal part manufacturing company located in Singapore. This Business-to-Business (B2B) company is involved in providing stamped parts to its customer locally and overseas. The main focus presented in the paper details the study from gate-to-gate. The results from the carbon footprint assessment would be deciphered and presented in the different stages of the product system. Besides the analysis of climate change, carbon footprint assessment is also employed to identify areas where inefficiency occurs. Very little emphasis has been placed on process energy efficiency improvement by manufacturers for both equipment and parts. Survey results conducted by Müller [4] indicate that energy efficiency has been the lowest priority when it comes to planning and operating manufacturing systems. The concern for most companies that run production is to ensure that the manufacturing line is able to meet its production schedule. This is the preoccupation of most facility engineers who have to ascertain that the machines operating are in tip top condition with the lowest down time. The industry is likely to be proactive when energy prices start rising or when carbon tax is imposed. The carbon footprint assessment can help to bring awareness to their present carbon emission levels, and identify the possible areas for reduction.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_67, © Springer-Verlag Berlin Heidelberg 2011

389

390

2.1

METHODS

2.3

Guidelines

Carbon footprint, a sub-set of data from Life Cycle Assessment (LCA), is utilised to quantify the impact of GHG in this work. This methodology focuses on the analysis of GHG emissions that accredit the cause of climate changes, one of the key elements in LCA [5]. International Standards Organisation (ISO) 14040 and 14044, which are well established framework for LCA [6], are closely followed in this study. The study conducted also follows closely the guidance of the Publicly Available Specification 2050 (PAS 2050) [7] developed by the British Standards Institution (BSI) in partnership with Carbon Trust and Department of Environment Food and Rural Affairs (Defra). Global standards have yet to be established for carbon footprint assessment although many organisational bodies are developing common standards. Many carbon footprint studies and initiatives are modelled after the two methodologies mentioned above [8] [9]. 2.2

Goal and Scope of Study

The goal of study is to provide a Life Cycle Inventory (LCI) that quantifies the carbon footprint associated with fabrication of the tool for progressive stamping of sheet metal, the progressive stamping process and all secondary processes required to complete the assembled sheet metal parts that is to be delivered to the customer. The assessment, in this case, also includes the plant facilities that are directly involved in the product system. The quantified carbon footprint results should enable identification of any ‘hotspots’ and provide insights to possible solutions that are able to lower the overall product carbon footprint. Another aspect of the work also encompasses the investigation of the electrical consumption in the metal progressive stamping process through monitoring devices to be used in the assessment.

Raw Material

Input of raw materials

Electricity, Fuel, Chemical

Transportation

Tool making

• CNC • WEDM • EDM • Grinding • Milling • Turning • Drilling Outsourced (Excluded) • Heat Treatment

Production

The Functional Unit

The functional unit of the product system is defined as one assembled cover. The assembled cover is a component found in a hard disk drive. It consists of three sheet metal stamped parts assembled together to form a complete product (Table 1). Thickness

Part Weight

Blank Weight

(mm)

(g)

(g)

Aluminium

1.5

65

68

2

Stainless steel

0.5

52

68

3

Stainless steel

0.6

65

82

Part

Material

1

Table 1: Bill of material for one assembled cover. 2.4

System Boundary

Figure 2 shows the life cycle process flow for the production of the assembled cover from tool making, stamping, secondary processes and delivery to customers. The dashed lines surrounding the process flow represent the boundary of the product to be studied. Raw material inputs to the system in this case are excluded as the focus is gate-to-gate. There is a total of three sheet metal parts to be stamped and assembled together before sending the product to the customers. Within the tool making process stage, three tools for progressive stamping are fabricated. The equipment required to produce the tool are as stated in Figure 2. In the production stage, the three sheet metal parts are produced by progressive stamping. All stamped parts are assembled in the cleanroom where all other secondary processes are located. Upon completion of the stages in the cleanroom, the product is transported to the customer.

Secondary Processes

Delivery

Printing

Progressive Stamping

Plotting

Oven curing

Assembly

Shared Resources • Conveyor belt (stamping line, cleanroom) • Air-conditioning (tool room, cleanroom) • Lighting

Stacking

Testing

Legend Included in the assessment Excluded in the assessment

Figure 2: System boundary of assembled cover.

Delivery to Customer

Greenhouse Gas Emission

2

Sustainability in Manufacturing - Selected Applications

Sustainability in Manufacturing - Selected Applications LIFE CYCLE INVENTORY

The study for this work requires the analysis of the product system from gate-to-gate. Therefore the Life Cycle Inventory (LCI) is the collection of resources consumed and emissions data from the sheet metal part manufacturer, publicly available models and reports, peer-reviewed references and databases [10]. Two types of inventory data are required in a carbon footprint assessment, mainly activity data (resource consumptions) and emission factors (amount of GHG emitted expressed in terms of CO2eq per unit of activity) [7]. The data collected can then be categorised as primary data source and secondary data source [5]. The primary data source is collated directly from the sheet metal part manufacturing company which is mainly actual input and output data. These data include the electricity and diesel consumption, production volume, wastage produced and customer’s location. Secondary sources are generic input and output data collected and can be used as representative of the actual data. Data of such kinds consist of electricity of generation from the grid and transportation using diesel emission. Details of data collection and modelling are described in the following sections. 3.1

Tool Making

Tool making is a crucial production step prior to metal stamping. The tools can be purchased or manufactured in-house. This study focus is on tools that are designed and fabricated in-house. Each tool consists of three types of component, namely plates, punches and inserts, and standard components (springs, screws etc). Only plates, punches and inserts are manufactured in-house, while the standard components are purchased from suppliers. The emissions from fabrication of such components are assessed based on the amount of energy consumed during the processes. This involves a range of machine used including Computer Numerical Control (CNC) machines, Wire Electrical Discharge Machine (WEDM), EDM, grinding, milling, turning and drilling. Some intermediate outsourced processes such as heat treatment are excluded from the study due to the lack of reliable data. It is deemed too sensitive for the suppliers to disclose information on the operating parameters and equipment efficiency. 3.2

Sheet Metal Production

The three sheet metal parts for the assembled cover are fabricated by progressive stamping. Nominal power rating of the progressive stamping machines and its auxiliary machines (e.g. sheet metal feeder) are obtained from the sheet metal part manufacturers. 3.3

Secondary Processes

A total of three sheet metal parts are stamped and assembled to form the complete product. The processes required are found in the cleanroom. The processes consist of printing, plotting, oven curing, assembling, stacking and final testing. The equipment used for the secondary process are automated by electricity, therefore the electrical consumptions of each equipment collected through a monitoring device and consumptions are normalised and used for the carbon footprint assessment. 3.4

Shared Resources

Shared resources refer to a process or equipment shared by many manufacturing processes. In the cleanroom, the primary role of the air-conditioning units are used to facilitate the movement of dust free air to ensure a controlled environment suitable for the assembly process of the stamped sheet metal parts. The energy consumed by the air-conditioning units have to be shared by all the equipment in the secondary processes which are located in the cleanroom. Compressed air is required by the progressive stamping machine and the equipment in the cleanroom. Therefore the energy consumed by air-compressor units that supply compressed air is

required to share the individual machines involved in the making of assembly cover. 3.5

Delivery to Customer

The assembled cover is partly delivered by the company’s truck to their customers situated in the northern part of Singapore. The assumption is that the return journey for the truck is empty. Some of the completed products are delivered overseas by shipment. As for the internal transport (fork lift), the vehicles are used over multilocations on ad-hoc basis. Its environmental impacts are expected to be relatively minor compared to the main production and external transportation. This project therefore excludes the fork lift consumption from this scope of study. 3.6

Energy Data

The two major energy sources for the sheet metal part manufacturer are electricity drawn from the grid and diesel used for their truck to deliver the finished produce. The use of electricity from the power grid in turn contributes to the carbon footprint. This is due to the burning of fossil fuels in the extraction and generation of electricity, and will be taken into account. Power grid emissions factor of Singapore was collected from [11]. Similarly, the emissions factor of diesel was obtained from [10]. 4

RESULTS AND DISCUSSION

4.1

Carbon Footprint Assessment Results

The overall carbon footprint for assembled cover is quantified as 0.4985 kg-CO2eq/assembled cover. Figure 3 illustrates the carbon footprint in kg-CO2eq/assembled cover of each stage. The results show that the largest contributor for the carbon footprint is the secondary processes, which is approximately 80.82% of the overall whereas the lowest (tool making section) is only 1.87%. 0.45

0.4029

0.40

kg-CO2eq/assembled cover

3

391

0.35 0.30 0.25 0.20 0.15 0.10 0.05

0.0602 0.0093

0.0145

Tool making

Stamping

0.01162

0.00 Secondary Processes

Facilities

Delivery

Figure 3: Overall carbon footprint of assembled cover. 4.2

Carbon Footprint for tool making

The carbon footprint for tool making process is only 0.0093 kgCO2eq/part, the lowest compared to the others. The individual carbon footprint of the three parts is illustrated in Figure 4. One reason for the low carbon footprint for tool making is greatly attributed by tool life. The approximate tool life for each of the three parts is 4 million stamps. As a matter of fact, the actual process carbon footprint of making the tool can be as high as 15,000 kgCO2eq/tool to as low as 3,500 kg-CO2eq/tool. Although the total carbon footprint due to tool making is large, the distributed carbon footprint per product basis is relatively insignificant. This is because the carbon footprint due to tool making is distributed evenly to a product based on a tool life of 4 million stamps resulting in low carbon footprint per assembled cover when compared to other stages.

392

Sustainability in Manufacturing - Selected Applications stamping machine at 55 SPM. The power spike seen is a common phenomenon in progressive stamping of sheet metal.

0.0045 0.00382

0.0040

0.00382

20 18

Electricity Consumption (kW)

kg-CO2eq/part

0.0035 0.0030 0.0025 0.0020 0.0015 0.0010

0.00088

16 14 12 10 8 6 4 2 0

0.0005 0.0000

Time

Part 1

Part 2

Part 3

Figure 7: Electricity monitoring of a stamping cycle.

Figure 4: Distributions of carbon footprint of tool making for individual parts. 4.3

Carbon Footprint for progressive stamping

The carbon footprint of individual progressive stamped sheet metal parts are presented in Figure 5. The total carbon footprint for the assembled cover during the stamping process is 0.0145 kgCO2eq/stamped part. Part 1 has the highest carbon footprint and is contributed by its higher electricity consumption required during the fabrication of the part. The result of the higher electricity consumption attributed to the stroke per minute (SPM) requirement during the stamping process for Part 1. It is approximately 30% higher than the other two parts.

kg-CO2eq/stamped part

0.0054

0.0053

This happens when the machine from ‘idle power’ (power required to operate basic auxiliary equipment like display panels, machine lightings and spinning of the flywheel) progresses to operational power required for the stamping process. Permanent metering for monitoring of electricity consumption is not commonly found on most manufacturing equipment due to cost or most manufacturers see it as an insignificant requirement. But for a more detailed energy management and carbon footprint assessment, electricity monitoring meters can be helpful to provide a more accurate data for analysis and study. More work is presently being carried out to create a model using the stamping parameters and electrical consumption to predict the power usage for stamping part at the design stage so that the designer can estimate the carbon footprint and optimise the process parameters and the choice of stamping machine used.

0.0052

4.4

0.0050

This section has the highest carbon footprint of 0.4029 kgCO2eq/secondary process. Figure 8 shows the breakdown of the different processes within secondary process. The highest goes to the oven curing process which accounts for 82.18%. This amount is equivalent to 66% of the total carbon footprint of the sheet metal part.

0.0048

0.0047

0.0046

0.0045

0.0044

0.3311

0.35

0.0042

0.30

Part 1

Part 2

Part 3

Figure 5: Distributions of carbon footprint of individual metal sheet stamped parts. 8000

7,775.53

kg-CO2eq/part

0.0040

Electricity Consumption (W)

Carbon Footprint for secondary processes

0.25 0.20 0.15 0.10

7500

0.05

7000

0.00

6,959.55

0.0232 Printing

6500 6,222.64

6000

5000 4500 35

40

45

Plotting

Oven Curing

0.0231

0.0008

Assembly Stacking Assembly Testing

Figure 8: Distributions of carbon footprint within the secondary processes.

5,640.29

5500

0.0231

0.0017

50 55 60 65 Stroke Per Minute (SPM)

70

75

Figure 6: Electricity consumption versus increasing SPM. It is observed that when electrical monitoring meter is installed in the progressive stamping machine (200 ton), the power rating (Watt) increases with the increase of the SPM — seen in Figure 6. Figure 7 shows the typical stamping cycle of a 200 ton progressive

Oven curing process is common in manufacturing industry and heat is required in the product system. The energy required is usually high and it is always useful if the heating process can be replaced or the equipment used can have better energy efficiency. 4.5

Carbon Footprint for facilities

The facilities section contributed to approximately 12.08% of the overall product carbon footprint and is positioned at the second highest. It is a substantial amount and reducing the carbon footprint will reduce the overall product carbon emission. From Figure 9, the highest carbon emission is generated from the cleanroom and largely by the air-conditioning units.

Sustainability in Manufacturing - Selected Applications

393

0.07 0.06

of the carbon footprint of the secondary processes and the overall product if reduction occurs.

0.0583

0.54 0.49

0.03 0.02 0.01

0.0004

0.00

Cleanroom

0.0012

0.0003

Machining

Oven Curing Process

Temperature and time taken to cure are two main factors that will result in high electricity consumptions. Therefore reducing these factors will reduce the carbon footprint which in this case is closely linked to the energy consumed. The ‘low hanging fruit’ is to optimise the oven efficiency. This can be done by ensuring that there are 1) good insulations, 2) proper sensors and controllers to detect and regulate the oven temperature and settings, and 3) regular oven maintenance. Another possible way to reduce energy consumption is to use alternative ‘gasket’ material that requires lower temperature to cure and/or shorter curing cycle time. Alternatively, improving the present design to optimise the ‘gasket’ material deployment may reduce curing cycle time and hence lower energy consumption. But changing ‘gasket’ material or product design will require further study and research. Under the scenario, the company is able to reduce the electricity consumption of the oven by 10%, the carbon footprint for the secondary processes will reduce by approximately 8% (0.3699 kgCO2eq) and the overall carbon footprint of the assembled cover will reduce by 6% (0.4654 kg-CO2eq). Figure 10 shows the new values Stamping (Active)

0.3992 0.4158

0.3699

0.39

0.3367 0.3533

Idle

% idling time Time (h) Power (W)

0.3036 0.3202

Baseline

From the study, an area identified as requiring possible improvement is the oven curing process found in the cleanroom. The process involves curing of a type of gasket that requires substantial amount of heat.

Parts

0.4323 0.4489

0.4029

0.29

Carbon Footprint for Delivery

RECOMMENDED MEASURES

5.1

0.4820 0.44

0.34

Only a small amount is contributed by the delivery section (2.33% of the product system) even though a portion of the assembled parts are to be delivered overseas. The total carbon footprint for delivery is 0.01162 kg-CO2eq and 92.02% of it is from this section is deemed to be from delivery to customer overseas. The remaining is contributed by local transportation. The reason that transportation did not surface as a main contributor is partly due to the weight of the assembled cover which is relatively light. 5

Ass. Cover

0.4654

0.3864

EDM Grinding Locations

Figure 9: Distributions of carbon footprint for facilities. 4.6

Sec. Processes

0.4985

0.04

kg-CO2eq

kg-CO2eq

0.05

5 10 15 20 25 % reduction in electricity consumption

30

Figure 10: Possible overall carbon footprint reduction for secondary process and overall product improvement. If the company was able to reduce the oven energy consumption by as much as 30%, the overall product carbon footprint would come down by approximately 20%. From the study, evidence clearly shows that carbon footprint can be reduced by a significant amount by simply improving the energy efficiency in operating the equipment within the manufacturing plant. Carbon footprint assessment is a way to aid companies to establish a baseline. Knowing their baseline would be helpful for future reduction strategies. 5.2

Stamping Process

Although the emissions due to stamping process are relatively small, the opportunities to reduce energy consumption, and hence carbon footprint, are not neglected. Preliminary energy monitoring work is conducted to investigate and understand the machine’s energy efficiency. During the energy logging studies of the stamping process for the three case study parts, it is observed from the power monitoring data that there is certain amount of ‘idling time’. Idling time refers to the time where the machine is consuming energy but no active work (such as stamping) is carried out. Table 2 shows the comparison between stamping and idling of the machine. It can be clearly observed that the idling time can go as high as 89% (Part 3). Calculation of the energy consumed by the idling time for the three parts in a working month of 25 days can amount up to approximately 2,430 kWh. One way to improve the energy efficiency per stamped part is to reduce the idle time of the machine. Presently, the amount of energy to produce one part can range from 2.23 to 11.91 Wh/part (Watt hour per part). This is calculated with the inclusion of idle time. Sensitivity analysis is carried out to find out the potential reduction in energy consumption when the idle time is reduced. Figure 11 shows this effect by increasing the active time (or reducing idle time). % of Power used during idling

Pieces produced (estimated)

Wh per part (including idle time)

Energy (kWh) consumed for idling (25 days)

2.23

246.10

Time (h)

Power (W)

Part 1

11.03

6,466.56

12.97

759.22

54%

12%

36,397

Part 2

10.56

12,043.52

13.42

3,117.53

56%

25%

25,339

6.67

1,045.87

Part 3

2.72

11,859.76

21.27

2,137.21

89%

58%

6,526

11.91

1,136.51

Table 2: Comparison of energy consumption between active and idle time.

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Sustainability in Manufacturing - Selected Applications

12.00

11.91

[4]

Müller, E., Löffler, T., (2009): Improving energy efficiency in th manufacturing plants – case studies and guidelines, in 16 CIRP International Conference on Life Cycle Engineering, pp. 465-471.

[5]

European Platform on Life Cycle Assessment European Commission – Joint Research Centre Institute for Environment and Sustainability (2007): Carbon Footprint – what is it and how to measure, pp. 1-2 http://lca.jrc.ec.europa.eu/Carbon_footprint.pdf. Last assessed 10 November 2010.

[6]

ISO, International Organisation of Standardisation – ISO 14040/44 (2006): Environmental management – Life cycle assessment – Principles and framework/Requirements and guidelines.

[7]

British Standard, (2008): Publicly Available Specification (PAS 2050) – Specification for the assessment of the life cycle greenhouse gas emissions of goods and services.

[8]

Finkbeiner, M., (2009): Carbon footprinting – opportunities and threats, in International Journal of Life Cycle Assessment, Vol 14, pp. 91-94.

[9]

Pandey, D., Agrawal, M., Pandey, J. S., (2010): Carbon Footprint: current methods of estimation, in Environmental Monitoring and Assessment.

[10]

PE International, GaBi Echterdingen, Germany.

[11]

National Environmental Agency (NEA), Information on emission factors (for CDM projects in Singapore), in http://www.nccc.gov.sg/informationOnEmissionFactors.p df. Last assessed 10 November 2010.

[12]

Sea distance calculator, http://www.searates.com/reference/portdistance. assessed 10 November 2010.

11.00 10.00 9.00

Wh per part

8.52 8.00 7.03

7.00

6.28 6.00

5.86

5.56

5.34

5.00

5.20

5.07 4.98

4.00 10%

30%

50%

70%

90%

% Active Time

Figure 11: Lower energy required per part when stamping time (active time) increases. Besides the improvement opportunities on oven curing process and the stamping process, some attention should be paid to the tool lifespan. This is because the large amount of tool making emissions is currently distributed throughout its lifespan of 4 million parts per tool. If the tool lifespan was shorter, say by half, the allocated emissions per part could be doubled. It is therefore important for the manufacturer to ensure a well maintenance in order to optimise the tool lifespan. 6

CONCLUSIONS AND FUTURE WORKS

The study concluded that the carbon footprint assessment of the sheet metal parts – assembled cover – has a carbon footprint of 0.4985 kg-CO2eq. 80.82% (0.4029 kg-CO2eq) of the overall carbon footprint of the product system is contributed by the secondary processes, while 66% (0.3311 kg-CO2eq) is generated by the oven curing process. Although some preliminary studies conducted by the team shows that the upstream production of the raw materials (sheet metal) does have a large effect on the overall carbon footprint, the focus should be placed on improvement done within the sheet metal part manufacturer. The ability to alter the carbon emission upstream seemingly at this point is not viable. Implementations of the recommended carbon footprint reduction strategies pose possibilities of further reduction of the overall product carbon footprint. The ability to produce parts at lower carbon footprint would definitely differentiate the manufacturing services company from the others. 7

ACKNOWLEDGMENTS

The authors would like to thank all that have made this work possible. 8

REFERENCES

[1]

Energy Market Authority (EMA) of Singapore (2009): Historical Yearly Electricity Consumption from 1986 to 2009, http://www.ema.gov.sg/page/38/id:75/. Last assessed 10 November 2010.

[2]

Intergovernmental Panel Climate Change (IPCC) (2007): IPCC Fourth Assessment Report.

[3]

Intergovernmental Panel Climate Change (IPCC) (1991): Climate Change, The IPCC Response Strategies, Washington Island Press.

4.3,

LCA-software,

Leinfelden-

in Last

Sustainable Production Research - a Proposed Method to design the Sustainability Measures 1

2

2

Maria Knutson Wedel , Björn Johansson , Andreas Dagman , Johan Stahre 1

2

Department of Materials and Manufacturing Technology, Chalmers University of Technology, 2

Department of Product and Product Development, Chalmers University of Technology Sweden

Abstract This paper describes a process to develop and apply measures in Sustainable Production Research. Specifically we have: A) Conducted workshops with researchers and industry on sustainability measures and monitored sustainability awareness of the participants through concept maps. B) Developed a proposal for measures based on literature reviews, results from workshops and interviews with researchers. C) Developed a generic method for evaluating sustainability measures related to production over time. 16 sustainability measures were defined as a starting set for the continuous monitoring. Concept mapping showed that participant have an uneven view on sustainability with emphasis on technology. Keywords: Sustainability Indicators; Sustainable Production; Concept Map

1 1.1

INTRODUCTION Evaluating sustainable production research

Sustainability is of great importance today and emphasized within almost every area of society from kindergarten to governmental boards. A common definition is the one by The Brundtland commission in the report Our Common future 1987 [1]: "Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs". It is also considered that sustainability as a concept can be divided into three interdependent pillars; ecologic, economic, and social sustainability. Sustainability has also become more important for universities; the current vision of Chalmers University of Technology is “Chalmers for a sustainable future”. The vision is realized through for instance The Sustainable Production Initiative, which is a concerted action together with Lund University. The Initiative tries to fulfill a multidisciplinary approach on sustainable production research, endorsed by companies in several industrial sectors. An important aspect of the Initiative is the intended impact on sustainability for our society. It was therefore decided to find a method to measure or estimate to what extent research will make a difference. The impact considered in our case is not only the actual implementations, since research in addition can result in changes in attitude leading to a long term effect. There are limited resources available on how to evaluate research, although there are plenty of resources regarding sustainability measures and indicators for evaluation of communities and industrial production [2],[3]. A multitude of different definitions and measures are available [2],[3], which complicates the process of finding the appropriate measures for a specific context. Furthermore, measuring a smaller set of indicators incorporates a risk for sub-optimizing as well as loosing the purpose of the measured indicators. Finally, measuring always brings the risk of using available data while wanting to capture more complex and immeasurable phenomena. In the described project we have investigated the possibilities to design measures suitable for evaluating research related to product

development, production systems, and manufacturing processes. These measures should aim at both tracking and improving sustainability impact of research projects as well as in industry including the long term effects. The research questions are: How can sustainable production measures be designed to: 

measure the impact of a research project within the applied area e.g. the industry?



estimate increased sustainability awareness?



inspire novel ideas and development promoting sustainable production?

1.2

The Sustainable Production Initiative – facts and figures

The Sustainable Production Initiative was granted financial support from autumn 2009. The vision of the Initiative is to produce cutting edge knowledge and increase research excellence in the area of incorporating sustainability in the core competencies in product development, production systems, and manufacturing processes. In five years and beyond the aim is to renew traditional production engineering research. The effort will create novel manufacturing technologies and production engineering methods that will support ecologic, economic and social sustainability. It will also create conditions for continuous innovation and possibilities to apply sustainable production engineering in Swedish industry. The Initiative incorporates over 100 researchers and spans, as mentioned, over two universities and numerous research groups, including cross-disciplinary efforts. The size and the width make it difficult to overview and monitor progress. 1.3

Scope of the paper

In this paper we aim to describe a method to evaluate or measure the impact of a large research effort in sustainable production. The evaluation is intended to capture actual implementations as well as changes in attitude leading to a long term effect. Specifically we have: A) Conducted workshops with researchers and industry on sustainability measures and monitored sustainability awareness of the participants through concept maps. B) Developed a proposal for measures based on literature reviews, results from workshops and

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_68, © Springer-Verlag Berlin Heidelberg 2011

395

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Sustainability in Manufacturing - Selected Applications

interviews with researchers regarding how sustainability measures can be incorporated and utilized in research. C) Developed a generic method for evaluating sustainability measures related to production research over time.

independent of the other parts. Sustainable indicators – such as Use and generation of toxic materials (both in production and by end user) - reflect the close connections of the three pillars of sustainability, in this case with emphasis on measuring activities causing pollution.

2

Finally at the National Institute of Standards and Technology (NIST) workshop “Sustainable Manufacturing: Metrics, Standards, and Infrastructure” 2009 it was recommended to pursue a multi-level approach for metrics, with simple metrics at the highest level [7]. Veleva et al. [3] has also recommended a five level approach for indicators; 1) Facility compliance 2) Facility Material use and performance 3) Facility effects 4) Supply-chain and product lifecycle and 5) Sustainable systems.

2.1

STATE OF THE ART Sustainability measures and indicators today

In industry today sustainability measures are common. Ideally measures can be a guide to where you are, where you are heading and how far you are from the ultimate vision. There are parameters (figures you measure), indicators (figures that indicate something) or index (several indicators combined into one). They can be used for benchmarking, decision making, measuring or guiding to improvement on the operational level or enabling companies to identify more innovative solutions to sustainability challenges [4]. Feng et al. [2] describes a multitude of various measurement initiatives for measuring sustainability metrics. Previous research and current developments lifted are for example [2]: Global Report Initiative, Dow Jones Sustainability Index, Environmental Sustainability Indicators, Environment Performance Indicators, United Nations Committee on Sustainable Development Indicators, OECD Core indicators, Ford Product Sustainability Index, GM Metrics for Sustainable Manufacturing, ISO 14031 environmental performance evaluation, Wal-mart Sustainability Product Index and Environmental Indicators for European Union. Four fundamental principles form a framework for sustainability upon which sustainability indicators should be built [5]: 1. Substances from the earth's crust cannot systematically increase in the biosphere. 2. Substances produced by society cannot systematically increase in the biosphere. 3. The physical basis for the productivity and diversity of nature must not be systematically deteriorated. 4. There must be fair and efficient use of resources to meet human needs. In addition, there are other important properties that indicators should fulfill. For instance, many agree on six important properties of good indicators or measures [2]: •

Relevant: Indicator must show useful meaning on the manufacturing processes under evaluation. It must fit the purpose of measuring performance.

•

Measurable: Indicator must be capable of being measured quantitatively or qualitatively in multi-dimensional perspectives, e.g., economic, social, environmental, technical, etc.

•

Understandable: Indicator should be easy to understand by the community, especially, for those who are not experts.

•

Reliable/Usable: Information provided by indicator should be trusted and useful. Reliable measurement is necessary.

•

Data accessible: Indicator has to be based on accessible data. The information needs to be available or can be gathered when needed.

•

Flexible: An indicator must be compatible with open standard expressions, such as ontology base and XML documents, to support long-term archival and flexibility for future generations.

Further, “Sustainable Measures” (a consulting firm promoting sustainable communities through development and use of indicators) [6] recommends that an indicator should be truly sustainable as opposed to traditional indicators of economic, social, and environmental progress. Traditional indicators - such as water quality - measure change in one part of a community as if entirely

2.2

Monitoring changes in awareness by Concept maps

Monitoring sustainability awareness is not a straightforward task. However, there are some examples e.g. from research regarding engineering education for a sustainable future where they used concept mapping [8]. The technique was developed by Joseph Novak and his research team at Cornell University during the 1970s as a mean to represent the increased knowledge among students [9]. The concepts are represented by squares and are connected to each other by relation lines. Along the relation lines phrases such as “is solved by” and “is realized by”, are used to describe the relation. The final visualization of concepts and the relations between the different concepts is called a concept map. The technique has been used at five European universities of technology, where nearly 500 students participated. It was concluded that concept mapping showed to be an appropriate assessment tool to evaluate cognitive knowledge or awareness [8]. A comparative study was made at Chalmers on the evaluation of increased awareness for PhD-students after participating in a course on sustainability [10]. Concept maps before and after the course were compared to evaluations of their final essays on how their research related to sustainability. A strong correlation was found between a high index of the concept map and a clear view on sustainability in the essay. Based upon the suitability of the technique and the previous well verified results this seems to be an appropriate tool to evaluate changes in awareness in our case. 3

METHOD - A PROPOSED PROCEDURE TO MONITOR SUSTAINABLE PRODUCTION RESEARCH

Based upon the nature of the Sustainable Production Initiative project the procedure for finding the proper sustainable measures is quite complex. During the early phase of procedure development it was clearly stated that the individual researchers as well as the industrial participants should be incorporated in the work of defining the measures for sustainability. It also became clear that there is a need for not only evaluating but also encourage innovative ideas. Based upon this reasoning a procedure is proposed consisting of the following three methods and tools; Interviews, Workshops and Concept mapping. In addition it is important that the measures decided upon are up-to-date, aiming for inclusion of novel thinking. 3.1

Interviews

Interviews were made with the researchers with the aim to increase the knowledge regarding what sustainability measures they could use in the ongoing research projects today as well as in the near future. These measures could both be quantitative as well as qualitative. For the industrial participants workshops were organised, as described below. The interviews with the researchers were conducted as one hour semi-structured interviews using open but structured questions, according to Kvale [11]. A total of nine interviews were conducted and a majority of these interviewees were project leaders for individual research projects within the

Sustainability in Manufacturing - Selected Applications Initiative which vouches for good insight on the measures and research projects. The interviewees were challenged to come up with possible measures regarding production sustainability in their research field; no guidance was given.

397 Economy, 9) Education and 10) Actors and Stakeholders. A more detailed description can be found in [8]. The category relevance index value (CRi) is calculated using equation 1:

One of the outcomes from the interviews was a gross list of 134 measures/indexes/parameters. These measures were then categorized into a number of groups based upon the aim with the measure. 3.2

Workshops

The aim with workshops was multifold. They gave a possibility to gather knowledge on current use of measures for sustainability in industry and academia, they facilitated communication between participants, they supported learning of basic sustainability issues and they were opportunities to perform concept maps. It was decided upon a series of workshops with solely industry or academia as well as workshops where both parts were present. The type of workshop depended on the issues to be discussed, as well as the targeted outcome needed. In the first workshop, industry was assigned as the target group. The participants were responsible for research in industry or environmental engineers. The intention with the workshop was to find out how industries are measuring sustainability today, to find ideas and directions on how to measure sustainability within the initiative and to find out the current knowledge and awareness of sustainability in industry today. Prior to the workshop a message was sent to the attendees informing them of the discussion subjects. Hence they could gather information if they, as individuals, were not updated regarding details of the company perspective on sustainability. The same workshop setup was given to academia later 2010. The outcome, regarding sustainable measures, from these two workshops was quantitatively not as comprehensive as from the interviews. However, some deepened insight in what types of measures that are used within industry as well as in academia were brought into the light. The concept map exercise was also performed by all participants during both workshops. 3.3

∑

(1)

Where CDi (Concepts’ distribution among categories) is calculated using equation 2 and SCi (Percentage of participants that write concepts assigned to a certain category) is calculated using equation 3.

∑

(2)

(3)

Where NCa is the number of categories, 10 in this case, NCi is the number of concepts per category. NSi is the number of participants referring to a specific category i and NS is the sample number of participants that participated in the observation (in our case 39). The complexity index is a relative value which means that the index should be compared with another index that has the same prerequisites. The complexity index (CO) is calculated using equation 4: (4) Where (average concept per participant) is calculated using equation 5 and (Relative measure of connections between different categories) is calculated using equation 6:

Concept mapping

As described above, among both academic and industry participants, the changes in awareness of sustainability are to be monitored by concept maps (Cmap). The maps are to be made continuously including before and after the conduction of the research projects. As described in section 2.2. Cmaps has proven useful in previous research, especially regarding sustainability [8] [12]. In this project the knowledge and the awareness of sustainable production are of interest. During the two workshops the participants were given a short introduction on the Cmap process and its essentials, thereafter given an A3 paper each with the words “Sustainable production” printed in the middle. They were then, during 15 minutes, writing down all the concepts they thought was correlated to sustainable production and made the relations between these concepts. The total number of participants during the two workshops was 39 (21 at the industry workshop and 18 at the academia workshop). The analysis of the Cmaps can be either qualitative or, as in our case, quantitative. The quantitative analysis aimed at finding out the category relevance index as well as the complexity index [8]. The category relevance index provides information about what categories the participants think sustainable production is most related to. The complexity index, evaluates how rich and connected the participants see the concepts they relate to sustainability. The categories used in this research were developed by Segalàs [8] and are categorized as: 1) Environment, 2) Resource scarcity, 3) Social Impact, 4) Values, 5) Future, 6) Unbalances, 7) Technology, 8)

∑

∑

(5)

(6)

Where NL is the number of links inter-category between concepts. In the current project the complexity index will be measured several times with different groups. The same group that participated in the two workshops will be going through the same exercise in a few years. It is thereby possible to compare the knowledge or awareness level between two occasions. 3.4

Inspiring novel thinking

In order to inspire novel thinking among researchers in the sustainable initiative, a new methodology on how to measure sustainability is needed. The reasons for a new methodology are twofold. Firstly sustainability by definition means that heed needs to be taken into account from a multitude of aspects, as stated earlier e.g. ecologic, economic and social sustainability. If researchers are to measure traditional measures such as e.g. energy consumption, kg material per product, cost per product, those measures one by one will lack the total sustainability aspect, and sub-optimization might be the outcome in the terms of sustainable production. Secondly, promotion of development towards even more

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Sustainability in Manufacturing - Selected Applications

sustainability considerations needs to be included, since what is considered sustainable thinking today might not be the case tomorrow. As an example we might choose to measure CO2 emissions and develop production to emit less CO2 during our research efforts. The technology of tomorrow might be independent of CO2 emission, hence CO2 is not relevant and the measure is not up-to-date. Hence a methodology on how to enable flexible measures and to promote updating of the measures to more sustainable ones needs to be developed. The proposed methodology is described briefly in 4.3. 4

RESULT

4.1

Proposed Measures

Table 1 contains the preliminary list of 15 indicators or measures and the links to the respective pillars of sustainability. The number of possible measures from interviews and workshops were 134, whereof some overlapping, condensed into roughly 13 topics. These were checked against areas usually covered in the more extensive lists of indicators found in the literature such as those described by Feng and Joung [2] or Sustainable Measures [6]. To make the list more comprehensive indicators No. 2, 5, 6, 8 and 14 were then added to the list. Finally, the wording was scrutinized to design extended measures that make it possible to capture several sustainability aspects simultaneously, the so called truly sustainable indicators as mentioned above. The resultant list of measures contains thus both measures used currently but also desired measures; what we would like to see measured. Lowell Center for Sustainable production suggests 22 core single indicators for manufacturing companies on level 1-4 [4]. In the proposed list below many indicators are similar to theirs, but our list is focused on research activities, leading to improvements which might not be implemented in a short term view. One difference for many of our indicators compared to those developed by Lowell is that we have tried, according to the suggestions made INDICATOR 1. Business 2. Employment 3. Work safety 4. Education 5. Finance 6. Transportation 7. Energy 8. Water 9. Hazardous materials 10. Materials

by Sustainable Measures [6], to develop the indicators to be “truly sustainable”, see above. For example Lowell measure “Fresh water consumption” while our suggestion is “Water consumption per usability of product”. To give an example; our indicator would capture if water consumption is decreased on the expense of usability (i.e. consumer satisfaction or water use during product life cycle). In addition, by evaluating “.. per usability” it is possible to capture if a company can produce more value (e.g. multifunctionality) at a fixed environmental expense. This is an important contribution to the concept of decoupling, see section 4.3. Usability is of course not quantitatively measurable in a traditional sense, it would have to been defined to 1 as a starting point and all changes are relative, estimated in percentage. Our indicators are different in terms of level of abstraction in accordance with the suggestion by NIST mentioned previously [7]. For example our indicator no. 12 is on level five according to Veleva [3] whereas indicator no. 9 is on level 2. Our list also lacks some common indicators, like tonnes of CO2 or SO2 equivalents. On the other hand we include “Reduction in environmental cost in environmental accounting” which captures CO2 today and is hopefully more robust in the sense that it would incorporate tomorrow’s unknown environmental challenges. The set of measures is still to be tested fully in action which will be starting 2011 by a dialogue procedure with a target group of researchers. A continuous improvement procedure is to follow. 4.2

Sustainability awareness as determined by concept mapping

The 39 Cmaps that were done during the workshops were quantitatively analyzed as described in section 3.3. The category relevance variables are presented in Table 2, where it is possible to note a highly uneven distribution of concepts referred to among the 10 categories.

DESCRIPTION Number of new or reformed services, products and technologies leading to decoupling Number of jobs created based on the project Ergonomic work environment increment per year Number of project member participation in societal events Percent of products and services developed where price reflects life-cycle cost Efficiency in transportation per usability

Total energy consumption per usability Water consumption per usability of product Hazardous waste generated by production operations per usability Percentage increase in life length and material throughput of materials/product 11. Recycling Number of design improvements permitting long life/reuse/recycling 12. Global Reduction in environmental cost in environmental accounting 13. Air Air quality index 14. Groundwater Groundwater quality index 15. Land use Agriculture land lost to development in square km

METRIC no. no. % no % %/% kwh/% litre/ % kg/ % % no. euro AQI GWQI 2 km

IMPACT ON SUSTAINABILITY PILLARS ENVIRONMENT

ECONOMIC

SOCIAL

X

X

X

X X

X X X

X X

X

X

X

X

X X

X

X X

X

X

X

X

X

X

X

X

X X X

Table 1: Proposed preliminary measures in the Sustainable Production Initiative.

X X X

Sustainability in Manufacturing - Selected Applications

399

Category

C1

C2

C3

C4

C5

C6

C7

C8

C9

C10

NCi

83

89

106

12

13

0

279

98

34

105

CDi

10%

11%

13%

1%

2%

0%

34%

12%

4%

13%

NSi

32

32

32

5

9

0

38

29

13

29

SCi

82%

82%

82%

13%

23%

0%

97%

74%

33%

74%

CRi

10,21%

10,95%

13,04%

0,23%

0,45%

0,00%

40,77%

10,93%

1,70%

11,71%

Table 2: Results from the category relevance of the concept mapping performed, showing an uneven CRi. Legend: NCi: No of concepts/category, CDi: Concepts’ distribution among categories, NSi: Sample no of participants in the observation, SCi: Percentage of participants that write concepts assigned to a certain category, CRi: Category relevance index.

The complexity index, CO, evaluates how rich and connected the participants see the concepts they relate to sustainability. The complexity index for the current group of persons was 19.73 and is the reference measure to be used when comparing this result with the tests done in the future along with this project. It is, as a number, not relevant until we are able to compare this with results from a reference group which could be for example, a group of students but most interesting the same group of persons after one or two years.

New research results can show that current indicator has reached targeted value, hence the goal is fulfilled and new indicators are needed to set new goals.



External conditions have changed, hence another indicator is more suitable to monitor.

I.e. there is a better more relevant and more important measure to monitor and influence with research results and development for more sustainable production. Figure 2 shows an example where the targeted value for currently monitored sustainability indicator is achieved. At that state it is possible to revise the measured indicator and switch to a more relevant one. And thus set a new target to reach out for with upcoming research efforts.

New Indicator

The category relevance can be divided into three groups. In the first group there is only one contender, the technology category (Category Relevance index (CRi), 40,8%). Environment, resources, social impact, economy and stakeholders create a group with the second most relevant categories (CRi ~10%). In the third group and in the very bottom of relevance were values, future, unbalance and education.



Indicator Value

Figure 1 shows the category relevance index, CRi, for the 39 participants at the workshop. The two groups, industry and academia, have not been differentiated from each other and are presented as a single result.

New Target Value

Target Value Time Figure 2: Measurement including a change in indicator on Y-Axis. Important to notice is also that the indicator used (or the research goal) should not have positive effect on one of the three sustainability areas while having negative influence on any of the other two. If the future is to be sustainable, decoupling of the impact on ecologic, economic, and social sustainability is desired, see figure 3. Figure 1: Category relevance index based upon the Cmaps. 4.3

Sustainable Production Measurement Methodology

A methodology was developed to fulfill the two criterions stated in 3.4 and hence inspire novel thinking. The methodology is promoting change of indicator by enabling the y-axis of figure 2 to be changed anytime. The number of changes of the monitored indicator will be collected, as well as the values of each indicator over time. A change of indicator can be done for different reasons: 

New results can show that current indicator is irrelevant.



New results can show that another indicator is more sustainable.

Decoupling Economic growth

Environmental load Quality of Life

Time

Economic growth Environmental load Quality of Life Time

Figure 3: Impact vs time for e.g. production. Right: Decoupling, where environmental load does not accompany economic growth.

400 5

Sustainability in Manufacturing - Selected Applications DISCUSSION

To support and evaluate the impact of the Sustainable Production Initiative a small number of precise measures would have been handy. The method for gathering measures showed, on the other hand, a highly complex image of a large number of possible measures. The literature study supported the complexity. However, through dialogue and workshops it was possible to introduce new thinking, relating production research to the three pillars of sustainability, ecological, economic and social as well as to the concept of decoupling. By combining results finally a starting set of sustainable measures were defined addressing at least two out of the three sustainability pillars each. It might be that researchers will find it difficult to use these measures, if one of the three sustainability aspects is not possible to measure or if it is considered not to be under influence of the actual research. In that case it should be determined that the sustainability aspect that is left out is at least not negatively affected by the research.

7

FUTURE WORK

The next step, of designing sustainability measures for sustainable production research, is coaching the participating researchers while they are implementing the proposed measures and the methodology followed by evaluation by for example conducting additional concept maps with the same set of participants. 8

ACKNOWLEDGMENTS

This work has been carried out within the Sustainable Production Initiative and the Production Area of Advance at Chalmers. The support is gratefully acknowledged. VINNOVA and the Swedish Research Council are thanked for financial support to the Sustainable Production Initiative. 9

REFERENCES

[1]

The World Commission on Environment and Development, WCED (1987): Our Common Future, Oxford University Press, Oxford, UK.

[2]

Feng, S.C.; Joung, C.B. (2009): An Overview of a Proposed Measurement Infrastructure for Sustainable Manufacturing, in: Proceedings of the 7th Global Conference on Sustainable Manufacturing. December 2-4. Chennai, India.

[3]

Veleva, V.; Ellenbecker, M. (2001): Indicators of sustainable production: framework and methodology. In: Journal of Cleaner Production, Vol 9. pp. 519-549.

The uneven result from the concept maps indicates that we need to increase the awareness of social aspects as well as the close links between the three pillars in order to achieve production solutions that are sustainable in the true sense. A continuous dialogue and arrangements of seminars, workshops and study visits are plausible solutions. This is also essential if research is to be challenged, and measures are to be refined and improved, allowing for novel thinking.

[4]

OECD, (2009): Eco-innovation in industry: enabling green growth pp.95-155.

[5]

Robert, K-H.; Daly, H; Hawken, P.; and Holmberg, J. (1997): A compass for sustainable development, in: In-Depth Articles and Related Readings for The Natural Step 5-Day Advanced Workshop, The Natural Step-US Conference, Chicago, IL, pp.1-27.

[6]

Sustainable Measures: (accessed 2010-11-15).

6

[7]

Rachhuri, S.; Sriram, R.; Narayanan, A; Sarkar, P; Lee J.H.; Lyons K. W. and Kemmerer, S. J. (2010): Sustainable manufacturing: Metrics, Standards, and Infrastructure – Workshop Summary, in: proceedings of the 6th annual IEEE Conference on Automation Science and Engineering, Toronto, Canada

[8]

Segalàs Coral, J. (2009): Engineering Education for a Sustainable Future, Ph. D Thesis, Barcelona, Spain.

[9]

Novak, J. (1990): Concept Mapping: a Useful Tool for Science Education, in: Journal of Research in Science Teaching. Vol. 27, No. 10, pp. 937-949.

The workshop discussions and the concept mapping revealed that industry has to some extent good knowledge on how to measure ecologic and economic sustainability. The social aspects were less structured. The background in technology of the industrial as well as the academic attendees might have influenced this result. A valuable aspect of the workshops was to get the main actors, the industry and academia, gathered early in the project and to receive a reference value regarding their knowledge in sustainable production.

CONCLUSIONS

In this paper we have described a newly developed method to support and evaluate impact of research in sustainable production applied to a large research initiative at Chalmers University of Technology. The results are the following: 

Dialogue by workshops for industry and academia combined with interviews with researchers and literature studies was a successful method to design a set of measures suitable for an incoherent group of production research projects



A condensed set of 15 measures have been identified, many of them truly sustainable in the sense that they are addressing several of the three aspects of sustainability simultaneously.



Concept mapping was found to be a suitable method to monitor sustainability awareness of the participants. The resultant measurement showed that the participants had a highly uneven view on sustainability where technology related issues were addressed foremost, while social issues like values and equity were not considered.



To develop generic and sustainable measures for evaluating sustainability related to production over time it is essential that measures can be changed over time to allow for technology leaps and novel thinking.

www.sustainablemeasures.com

[10] Svanström, M.; Nyström Claesson, A.; Nässén, J.; Knutson Wedel, M.; and Lundqvist, U. (2010): To improve the ability to reflect on your own research in relation to sustainable development - experiences from a course for PhD students at Chalmers University of Technology, in: Proceedings of the Engineering Education in Sustainable Development, (EESD10) Gothenburg, Sweden. [11]

Kvale. S. (1997): Den kvalitativa forskningsintervjun, Studentlitteratur AB, Stockholm, Sweden.

[12]

Shallcross D. C. (2010): Sustainable Development in Modern Engineering Curriculum, in proceedings 3rd International Symposium for Engineering Education “Education Engineers for a changing world”, University of College Cork, Ireland.

Green Production of CFRP Parts by Application of Inductive Heating 1

1

1

Michael Frauenhofer , Stefan Kreling , Holger Kunz , Klaus Dilger 1

1

Institute of Joining and Welding, Technische Universität Braunschweig, Braunschweig, Germany

Abstract Long process times, high energy consumption, low automation level and high costs for textiles, resin and production tools are the main reasons for the low acceptance of fiber-reinforced plastics (frp) in high-volume production, especially in automotive applications. This paper presents the potential of the application of inductive heating techniques for the reduction of process time and energy consumption in different CFRP manufacturing processes based on different studies that have been performed at the institute of joining and welding. The described processes are the preforming and curing steps in the RTM process and the tape warming in the ATL process for thermoplastic composites. Keywords: Green Production; CFRP; Inductive Heating

1

INTRODUCTION

Due to the increasing shortness of fossil fuels and energy costs, consumers demand more energy-efficient transportation which, especially, means cars that need less fuel. Alongside the development of more efficient engines, the only way the automotive industry can achieve this demand is a massive weight reduction. Since the consumer is not willing to accept a loss in comfort and safety, the main possibility of achieving this is a reduction of the car body weight which allows a decrease of the fuel consumption of 0,5l per 100km and 100kg [1]. The only possibility of accomplishing this aspired weight reduction is the consistent use of fiber-reinforced plastics which, in particular, means carbon fiber-reinforced plastics (CFRP). The main roadblocks for the spread of composite parts in automotive batch production are long process times, high energy consumption of manufacturing processes, the high energy demand of carbon fibre production [2], a very low automation level and high costs for the semi-finished parts and production tools. These aspects lead to very high overall costs for CFRP parts which, in turn, lead to the current situation that they are only used in a small market segment in high-priced and, especially, in sports cars [6]. However from a life cycle perspective CFRPs are an alternative to steel structures if a sufficiently long functional life time can be assured [3, 4]. Another aspect underlining the need for more efficient CFRP production technology is the increasing application of the material in the upcoming generation of short and midrange airplanes like the A320. Because of the significantly higher lot size compared to large long-range planes like the Airbus A380 or A350 (~ 480 A320/year, ~ 25 A380/year), there is a high demand for more energy-efficient and faster production technologies in aviation industry, too. 1.1

Techniques for CFRP Production

LCM / RTM process In automotive industry the demands for a high production output and low costs per part lead directly to the application of the liquid composite moulding (LCM) technique for the production of CFRP

parts. Compared to the prepreg-layup process, the LCM technique has the advantage of a lower process time, cheaper semi-finished parts and higher form variability [6]. The disadvantages of the process that are the main reasons for the low spread of CFRP parts in automotive industry are the complex and time-consuming preforming process and the low energy efficiency and thus high energy demand of the curing process.

Figure 1: LCM/RTM process chain [4]. Figure 1 describes the LCM/RTM process chain to the finished part and gives an example of the percentage of time consumption for the production of a typical CFRP part in automotive production. Manufacturing time for the whole part is in the magnitude of 25 minutes. First step is the cutting of dry fibers, this step can be automated well by the application of robot palletisers and the use of adequate handling technology. Much more optimization potential shows the preform process that accounts for up to 60% of the costs of the LCM process [5]. The process steps consist of the draping of the fiber layers and the joining to the finished preform. The joining step is conventionally performed by sewing or adhesive bonding with (often thermoplastic) binders. These process steps are quite slow and show a low automation degree which causes the high process times and high costs. The resin injection is mostly performed in a closed mould with pressures up to 50 bar. Depending on the parts complexity and size

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_69, © Springer-Verlag Berlin Heidelberg 2011

401

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Sustainability in Manufacturing - Selected Applications

the injection process takes from several seconds up to about half an hour. The subsequent curing step is mostly performed in moulds, too. In the state of the art the curing is accelerated thermally with either conductive heating of the mould in an oven or by electrically direct-heated moulds. Both processes show low heating rates and little energy efficiency and therefore are a main cause for the low process efficiency that is further reduced when a subsequent tempering process is added. In summary the RTM process for a body part like the outer part of an engine bonnet takes about 30 to 40 minutes compared to less than 3 minutes per part for a metallic structure. This indicates the high potential and need for improvement of the CFRP manufacturing process in the automotive industry [4].

The main disadvantage of thermoplastic matrix composites are, apart from the high costs for most materials, the high required processing temperatures and the high viscosities which complicate the application of LCM processes. These drawbacks lead to the current situation so that most continuous fiber-reinforced thermoplastic materials are manufactured from thermoplastic prepreg materials. The automated tapelaying process for thermoplastic prepreg materials offers the possibility for automated relatively high-volume CFRP manufacturing. A schematic view for the process is shown in Figure 3. prepreg pressure

Prepreg technology

heat

A prepreg (preimpregnated fiber) is a semi-finished product consisting of continuous fibers and a non-cured resin matrix. The materials are mostly used in form of a rolled sheet. For the production of parts, sheets are layed in a mould in several layers. Since the prepreg normally has a thickness of about 0,125 to 0,5 mm, the layup process, that is either performed manually or by large tape-laying robot palletisers, can be time-consuming.

heat

The process chain for prepreg parts is shown in Figure 2

defreezing

layup

mould

cutting

vacuum-assembly

press or autoclave curing Figure 2: Process chain for the manufacturing of prepreg parts. After cutting of the plies and layup, most CFRP parts that are manufactured using the prepreg process are cured in an autoclave process for several hours at temperatures around 180 °C (depending on the matrix resin). For the autoclave curing process, a complex vacuum assembly is needed that is built up manually, which represents another time-consuming and mostly manual performed process step. The main advantages of this manufacturing technology are the higher performance of the parts, the avoidance of resin formulation in manufacturing and the dramatic reduction of workers’ health concerns [6]. The disadvantages representing the main obstacles for efficient mass production are the need for storing the prepreg materials at temperatures of about -18 °C and the resulting efforts for defrosting and storage. Furthermore, the above-named high time consumption of the layup process, build-up of the vacuumassembly and the high energy consumption of the autoclave-curing lead to very high costs per part for the prepreg process. Thermoplastic tapelaying (ATL) The composite market is clearly dominated by thermoset matrix resins, there is, however, an intense interest in the application of thermoplastic matrix materials. The main overall reasons are related to potential improvements of manufacturing technologies (e.g. thermal shaping), recyclability and work environment issues. Furthermore, thermoplastic materials allow the possibility of very short demoulding times since no chemical reaction needs to take place for solidification. [6]

Figure 3: Schematic of automated tapelaying process. If both plies, the previously laid one and the one that is incoming, have completely melted surfaces and are joined together properly, no further consolidation step is necessary and the parts can be demoulded directly after the layup process is finished. Thus, depending on the layup speed and the achieved heating rates, a quite quick production process can be realized. One primary obstacle for a wider industrial application of this process is the necessity for rapid heating without causing local thermal degradation of the thermoplastic material. To benefit from the named advantages of thermoplastic CFRP materials and the ATL process, improved heating mechanisms are essential. Tape Laying

Prepreg technology

RTM

Machine Costs

medium

high

medium

Tooling Costs

medium

high

high

Labour Costs

low

medium

medium

Material Costs

low

high

low

Energy Consumption

low

high

mean

Lot Size

< 1000

< 3000

< 50 000

Process time

3 – 24 h

5h

15 min – 3 h

Table 1: Comparison of manufacturing processes according to [4]. 2 2.1

INDUCTIVE HEATING OF CFRP Theoretical Background

Regarding former developments, the inductive heating of CFRP is based on three different heating mechanisms. On the one hand according to [7, 8, 9], the Joule heat transfer dominates along the fibers, leading to heat transfer patterns which are matching the inductor geometry. On the other hand according to [10, 11, 12], heat transfer prevails at the crossing points and global conducting circuits are propagated through the dielectric effect. It can be assumed that the dominating heat mechanism depends on the material and process parameters. Hence, by choosing adequate parameters it is possible to reach the favored dominating heat

Sustainability in Manufacturing - Selected Applications

403

mechanism for each application, depending on the frequency, power level and laminate characteristic. For accelerated adhesive joining of CFRP bonds, the dominated heating of the fibers (Pind,Joule,fibre) is aimed for rather than heating the crossing points (Pind,Joule,cross and Pind,joule,cross) because of more effective and uniform heat distribution in the laminate and adhesive. In order to opt for the right parameters it is important to get a better understanding of the relevant mechanisms. First aim of the work was to analyze the physical background of inductive heating of CFRP. According to [8], the three mechanisms of heating can each be expressed as one term, leading to the absorbed heat power calculated as

Pind , CFK  Pind , Joule ( fibre )  Pind , Joule ( cross )  Pind , dielectric .

(1)

The following equations constitute the physical dependencies for each term.

Pind , Joule, fibre 

U 2 2    f    H  A  R R

2

Pind ,dielectric  2    f  tan    C  V Pind , Joule,cross 

U 2 2    f    H  A2  R R

(2) (3) (4)

An overview about the different parameters is given in the following table: Material parameter R

Resistance of (a) the fibre and (b) the matrix at the crossing points

tan ()

Dielectric loss factor

V

Volume of matrix at the fiber crossing points (influenced mainly by the distances between the fiber of two directions)

C

Capacity

Figure 4: Comparison of heating of dry reinforcements (15 layers: 7x UD G1175, 8x biaxial fabrics). Thermocouples measure the temperature on the upper surface, in the middle and on the lower surface. The average time out of these three measurements is shown for each heating technique in Figure 4. The error bar indicates the homogeneity level. The potential for reducing production time is remarkably recognizable. The time to consolidate the preform in all layers can be reduced from 82 s to 2.8 s. Therefore, this technology enables the reduction of production time and thus the possibility of introducing CFRP in other markets. Nevertheless heating results are strongly influenced by the process and material parameters during the preform process. This should be clarified in the following. The influence on the induction heating of fiber material, layups and the application of binder is analyzed. Therefore different preform specimens with almost the same thickness are compared. Very high heating rates are only possible for a short time of the process in order to keep the temperatures beneath the limits of vacuum bag and binder.

Process parameter H

Magnetic field (influenced by the frequency, the induction power and the inductor geometry)

A

Induction area

f

Induction frequency

Table 2: Material and process parameters. The physical terms indicate the complex relationship between the different material and process parameters and their influence on the inductive heating of CFRP. So the work object was to clarify experimentally the most important influences on the heating result. 3 3.1

Figure 5 (a): Comparison of woven textile with different thickness and binder.

APPLICATION IN THE LCM PROCESS Preforming

Using the binder process for pre-consolidation of the fibers, it is state of the art to use an oven for simple geometries and for final pre-consolidation or to use an iron for draping the fibers in case of complex geometries. These common heating techniques have rather low heating rates compared to inductive heating. Figure 4 shows the direct comparison of the average time to reach the minimal process temperature (Tmin = 80°C) in all layers of different heating resources.

Figure 5 (b): Comparison of heating rates of different textile specimens with similar grammage.

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Sustainability in Manufacturing - Selected Applications

The measured heating rates show that fast heating by induction is possible for all tested specimens. Upper plies next to the inductor can be heated locally between 20°C/s and 40°C/s using 0.8 kW electrical power. Figure 7a shows that an increased thickness of the specimen leads to a decrease in the heating rate while maintaining the same power level which is caused by the higher thermal mass. The existence of binder also leads to a decrease of the heating rate although the influence on the thermal mass is rather low. The dielectric binder entails a drop of the heating rate from 34.6°C/s to 25.5°C/s, due to the electrical insulating effect. Thus binder between the plies decreases the possible energy input, but inductive heating stays at a high and sufficient level for preforming. Further on it is shown in Figure 7b that woven fabrics, like a layup of 475T, show better inductive heating capabilities than non-crimp fabrics (biaxial and quadraxial fabrics). This is due to better electrical contact between different fibre directions in woven fabrics. Heating rates can be further raised by increasing the electrical power of the inductive device up to e. g. 5 kW without changing the power supply used in these tests. Devices with even more power are available on the market. When increasing electrical power, water cooling of inductor coils can become necessary. All tested materials show good inductive heating capability, no material or layup could be indentified which performs insufficiently. 3.2

Resin Curing

As described in chapter 1.1 in the RTM process the curing processstep is very time- and energy-consuming, due to the low heating rates and the high heat capacity of conventional metal moulds. Current research at the Institute of Joining and Welding deals with the application of fast heating technologies to achieve a faster and more energy-efficient curing of the resin. Three potential methods that are being researched are illustrated in Figure 6.

Figure 6: Schematic view of methods for accelerated resin curing in the RTM process. The third approach for fast resin curing utilizes the skin-effect heating of thin metallic foils that are connected to a middlefrequency AC-current. The surface temperature of these foils can be increased by up to 200 K/s when no thermal mass is connected, and even if this heating rate is reduced by the adjacent part or mould, very high heating rates can be realized if they are integrated in either the mould surface or the vacuum foil or both. Using all three of these methods, depending on the part thickness, heating rates exceeding 15 K/min can be achieved. Compared to conventional curing methods, like oven or autoclave curing that achieve about 2 K/min, a significant reduction in process time and also energy consumption can be realized by utilizing inductive heating which is illustrated in Figure 7.

All presented methods are based on the application of moulds manufactured from CFRP. Besides their lower weight and better machinability, these have the advantage of a significantly lower thermal capacity which allows higher heating rates and is directly connected to a demand for energy to heat up the mould in the process. Besides the application of CFRP moulds, current research work is done regarding the application of fast heating methods to these moulds. The first method utilizes the electrical conductivity of carbon fibers which allows direct inductive heating of CFRP parts due to ohmic and dielectric losses. The advantage of this heating method is that energy is directly coupled into the material that is to be cured, thus very high energy efficiency can be achieved. Furthermore, the heating of the material is volumetric which leads to a very steady heating over the parts thickness. The main disadvantage and focus of current research is that, with common inductor geometries, no laminar heating over the whole part can be realized. Another approach that utilizes the heatability of CFRP via induction is heating the CFRP mould. Several inductors that can be connected to either one or multiple induction generators are placed inside the CFRP mould and allow a laminar and steady warming of the CFRP via the thermal conductivity of the mould material with high heating rates. Due to the relatively low heat capacity of the mould proper energy efficiency can be achieve.

Figure 7: Comparison of process time depending on heating and cooling rate of a conv. Invar and a CFRP mould heated by induction. The illustrated effect is mainly caused by the lower density and thus heat capacity of the CFRP mould. Taking into account that the mechanical strength of CFRP moulds is lower than that of the ones made of steel and therefore CFRP moulds need to be about 10% more massive, the amount of energy that is needed to heat up the composite mould (∆T = 160°C: 49 kWh/m³) is about 30% of that needed for the steel tooling (∆T = 160 °C: 184 kWh/m³). When applying the method of direct heating of the CFRP parts the energy consumption can be reduced even further, because another reduction of the mass that has to be heated can be achieved. Even if the lower effectiveness of the inductive heating compared to conventional resistance heating is taken into account a significant improvement of energy efficiency and process time can be realized. 4

INDUCTIVE HEATING OF THERMOPLASTIC TAPES USING SUPERPARAMAGNETIC NANOPARTICLES

The introduction already showed that finding a new heating mechanism with high heating rates is crucial for the tape-laying process with thermoplastic materials to compete with thermosetting materials. Therefore, in this section the application of induction

Sustainability in Manufacturing - Selected Applications heating is investigated. In contrast to the previously described inductive heating of CFRP where conductive loops allow the circulation of current through the fibers, this mechanism cannot be applied to unidirectional CFRP tapes, due to the lack of perpendicular fibers. Thus, compared to the previous application, an alternative heating mechanism must be evaluated for the automated tape laying. In this paper the use of superparamagnetic nanoparticles dispersed in the tapes resin is discussed (cf. Figure 8).

405 4.2

Experimental Setup

For the presented results, a unidirectional carbon fiber-reinforced tape with a polyetheretherketone (PEEK) matrix manufactured by Evonik was used. Silica coated nanoferrits (MagSilica) were dispersed in the resin with 5 Wt.-%. The experiments described below were conducted using three induction machines with different frequency ranges (0.3 MHz, 1.5 MHz and 3-5.5 MHz) and power (510 kW). To simulate the lay-up speed, the thermoplastic tape was pulled through the induction coil (see Figure 10).

Figure 10: Experimental setup for induction heating with simulated lay-up speed. 4.3 Figure 8: Heating mechanism for thermoplastic tape with nanoparticles. The nanoparticles are inductively heated while the resin and the fibers are heated by thermal conduction. Because of the comparatively small distance between each nanoparticle, a short conduction time is provided compared to heating the surface by laser, flame or oven and conducting the thermal energy through the thickness of the tape. Therefore, the use of nanoparticles promises high heating rates and thus high lay-up speeds. 4.1

Inductive Heating of Superparamagnetic Nanoparticles

Below a certain volume, ferromagnetic particles tend to have only one Weiß domain leading to an outstanding magnetic behavior. On the one hand, just as with ferromagnetic materials, they cannot be magnetized above the so-called Curie temperature, on the other hand they depict no remanence and hysteresis like paramagnetic materials. However, since their susceptibility is significantly larger than the paramagnetic ones those particles are called superparamagnetic. In contrast to the heating by hysteresis loss (common for inductive heating of ferromagnetic metals), the nanoparticles are heated by the relaxation process which describes the losses during the reversal of magnetization. Due to [13], the nanoparticles can relax in two different ways according to their volume. While the Brown relaxation describes the change of the magnetic momenta, the Neel relaxation is characterized by the rotation of the nanoparticle itself (Figure 9). Both mechanisms lead to thermal energy comparable to the friction in damped mechanical systems.

Influence of Frequency

The induction frequency and power mainly determine the size and construction of the applied induction system which increases the machine costs and the processability of induction heating for a specific purpose. Hence, as a first step the maximal temperature reached for a certain frequency and power while using different induction machines were examined. Different induction machines had to be used to obtain the wide frequency range presented in Figure 11. Therefore the given temperatures can also vary due to the coils or machines. However, the results indicate that the maximal temperature increases nearly linearly in the examined frequency range of 0.1 to 5.5 MHz by approx. 40°C/MHz. The values measured with solenoid coils with two and five turns (and the same induction machine) in particular show the increasing tendency. The maximal temperature reached for a frequency of 5.5 MHz was about 350 °C which is slightly above the melting point of PEEK. For the other measurements, especially with the other more common induction machines, only temperatures below the melting point could be achieved. While these machines are implemented in modern semi-conductor technologies and can be applied in automated processes, the induction technology in the range of high frequencies around 5 MHz is only rarely found.

The high heating rates and the physical temperature barrier (Curie temperature) of the nanoparticles are especially interesting for the application in time- and temperature-critical applications like the tape-laying process.

Figure 11: Maximal temperatures for different frequencies and stationary measurements (no lay-up speed). 4.4

Figure 9: Comparison of the two relaxation mechanisms [13].

Lay-up Speed

The lay-up speed is a crucial parameter for the tape-laying process which determines the possible throughput and thus manufacturing times and costs. Modern thermosetting tape layers reach lay-up speeds of up to 60 m/min. Similar thermoplastic tape layers realize only a lay-up speed of about 5-10 m/min [14]. Compared to these values, the speed realized during the preliminary experiments is

406

Sustainability in Manufacturing - Selected Applications

significantly lower (see Figure 12). Using a solenoid coil with 2 turns at low lay-up speed, a temperature of approx. 320 °C could be achieved. A solenoid with 5 turns, in comparison, leads to higher lay-up speeds of about 0.5 m/min and a tape temperature of 320°C due to the longer time the tape is exposed to the alternating magnetic field. However, the results with more coil turns already indicate that an optimization of the induction equipment could allow a higher tape throughput.

to heating the surface and conducting the thermal energy through the thickness. However the lack of a thorough knowledge of the induction in CFRP and the current drawbacks of the induction technology have so far prevented the technology from being widely applied in the industry. Thus intensive research regarding the heating mechanism, the processes and the induction technology need to be performed to fully exploit the potential of this technology. 6

Figure 12: Variation of lay-up speed. 5

SUMMARY

A lot of effort has been taken to establish the infusion (like RTM) and tape laying processes (filament winding, ATL and AFP) in industry, so that essential improvements in existing technologies are more worthwhile than the invention of new techniques. Essential improvements in production time can only be achieved by simplification and acceleration of each process step. In this paper, induction heating was used to reduce the heat-up times of the two investigated processes. The results show that inductive heating can successfully be applied to the preforming step of the LCM process leading to a significant process time reduction. Especially the use of comparably low frequencies of 10 kHz has lead to homogenous heating since a high magnetic field penetration through the thickness and a heating of the fibers could be observed. The next step is adapting the heating technology to resin curing. First results indicate that energy and time savings similar to the preforming process can be achieved. The acceleration of the ATL process with thermoplastic tapes with induction heating utilizes nanoparticles dispersed in the matrix resin. The previously presented preliminary results indicate that high heating rates can be achieved and a far better process stability can be reached compared to conventional heating mechanisms. However, the lay-up speeds are, until now, too low and the available induction technology with very high induction frequencies (some MHz) uses old technologies and is thus not applicable for automated industrial processes. With the improvement of this technology and the application of the inductive heating, the primary problem of the thermoplastic ATL (the fast heating process) could be solved. All in all, the results have shown that inductive heating has got a high potential to further reduce production times and energy consumption, mainly due to the volumetric heating which is superior

REFERENCES

[1]

Braess, H.-H. (2007): “Handbuch Kraftfahrzeugtechnik”, Vieweg Verlag, Wiesbaden.

[2]

Suzuki, T. et. al. (2005): Prediction of energy intensity of carbon fiber reinforced plastics for mass-produced passenger th cars, 9 Japan Int. SAMPE Symposium.

[3]

Duflou, J.R. et. al. (2009): Environmental impact analysis of composite use in car manufacturing, Manufacturing Technology 58, pp. 9-12.

[4]

Ermanni, P. (2008): Vorlesungsunterlagen, ETH Zürich.

[5]

Weimer, C. (2005): Harzinjektionstechniken für strukturelle Hubschrauberbauteile, in: 1. Materialica Kongress, 21.-22. September 2005, München.

[6]

B.T. Aström (1997): Manufacturing of Polymer composites, Chapman&Hall, London.

[7]

Miller, A. K. (1990): The nature of induction heating in graphite-fibre, polymer matrix composite materials, in: Sampe Journal No. 26.

[8]

Lin, W.; Bunemann, O.; Miller, A. K. (1991): Induction heating model for graphite fiber thermoplastic matrix composites, in: Sampe Journal Vol. 27 No.6.

[9]

Rudolf, R. (2000): Entwicklung einer neuartigen Prozess- und Anlagentechnik zum wirtschaftlichen Fügen von thermoplastischen Faser-Kunststoff-Verbunden, Dissertation, IVW-Schriftenreihe, Bd. 10, Kaiserslautern.

[10]

Fink, B. K.; McCoullough, R. L.; Gillespie, J. W. Jr. A. (1995): Model to Predict the Through-Thickness Distribution of Heat Generation in Cross-Ply Carbon-Fiber Composites Subjected to Alternating Magnetic Fields, in: Comp. Science a. Technology.

[11]

Kim, J. H.; et al. (2003): Development of a Numerical Model to Predict Inplane Heat Generation Patterns During Induction Processing of Carbon Fiber-reinforced Prepreg Stacks, in: Journal of Composite Materials, Vol. 37, No. 16/2003, Sage Publications, pp. 1461-1483.

[12]

Yarlagadda, S. et al. (2002): A Study on the Induction Heating of Conductive Fiber Reinforced Composites, in : Journal of COMPOSITE Materials Vol. 36.

[13]

Wautelet, M. et. al. (2003); Nanotechnologie, Oldenbourg Verlag, München.

[14]

Beresheim, G. (2002); Thermoplast-Tapelegen – ganzheitliche Prozessanalyse und -entwicklung, Dissertation, Institut für Verbundwerkstoffe GmbH.

LCM-Technologien,

Saving Potential of Water for Foundry Sand Using Treated Coolant Water 1

1

1

Jefferson O. Gomes , Victor E. O. Gomes , Janaina Fracaro de Souza , Elizabete Y. Kawachi 1

1

Instituto Tecnológico de Aeronáutica, Praça Marechal Eduardo Gomes 50, Vila das Acácias, 12228 – 900 São Paulo, Brazil

Abstract This paper aims to determine the reuse conditions of treated waters from coolant in the composition of sand cast process. The conventional treated water from coolant is not allowed for reusing purpose, due to the poor efficiency of the usual treatment processes. Treated water contains harmful elements that are extremely difficult to degrade in a foundry sand mix. In this work, three technologies of effluent treatment were evaluated. Tests were performed to verify the efficiency of emulsions prepared m different types of water in order to access the feasibility of water reuse derived from emulsions discarded after the machining process. Keywords: Sand Cast Process; Emulsions Discarded; Reuse of Treated Waters

1

INTRODUCTION

Present day industries are continuously pressured by performance indicators which relate productivity to social and environmental responsibility issues. The great challenge is to conciliate the constant quest for competitiveness with the growing necessity of preserving sustainability aspects. An efficient production should be supported by a minor use of resources and emission of harmful substances. Sustainability is based on three pillars: the ecological, the economical and the social dimension. These Dimensions provide a basis for the description and evaluation of sustainability related questions. The goals of each dimension need to be tracked in the same manner to achieve sustainable stability. For that, three basis strategies of sustainability are available: efficiency, consistency, and sufficiency [1] Die casting is a very relevant process from a global perspective while complex parts play an important role in the automotive industry (e.g. gear box, engine). In 2005 over 400.000 tons of die casted aluminum parts were manufactured only in Germany causing over one million tons CO2 [2]. The process chain consists of four major steps in order to produce parts in a defined quality: smelting of material, the die cast process itself, heat treatment to set up certain metal properties and one or several machining process to realize the final geometry and surface quality. The process chain is strongly depicted by significant losses of energy as well as material. A major part of energy input is needed for heating of parts. 30-70% of input material is not part of the casted part whereas it is part of the spurred spill or gets lost through run-up processes [3]. The foundry sector is also considered a large polluter, because the productive processes generate great quantities of residues (vapors, slag, discarded foundry sand, particulate materials, among others). In 2003, approximately 231,000 tons of sand for foundry was used per month to supply the average Brazilian requirement for the production of metals. Brazil uses an outdated model for the

treatment of Discarded Foundry Sand (DFS), because a significant portion of the discarded foundry sand is sent to landfills specially prepared for this purpose. Considering productive aspects, landfills occupy areas that could be used more efficiently. Considering environmental aspects, the sand mixed with other residues at the landfills presents contamination risk to the surroundings [4]. The humid regeneration is an efficient method for cleansing spent foundry, and aims to remove substances soluble in water (such as sodium silicate) or hydrophilic substances (such as bentonite) [5]. However, constraint to be considered for choosing this method, the regeneration operations use a large volume of water (8 tons of water / 1 ton of processed sand) supplied by the public water supply [6]. This factor, apart from raising the cost of the process, due to the water tariffs, it does not close the cycle for reuse of the water, not contributing to the sustainability of the process. Besides, the manufacturing industry uses coolants for metal-cutting processes. Coolants are fluids which flow through a device in order to prevent its overheating, transferring the heat produced by the device to other devices that utilize or dissipate it [7]. 90% of soluble fluids composition is of water. Since water and oil do not mix, emulsifiers are added for the formation of these fluids, which are agents reducing the superficial tension forming a relatively stable monomolecular film in the oil-water interface. It is estimated that only in Brazil 25 to 150 liters of cooling oil circulates in the machining centers per minute, a huge volume to be managed in order not to cause a hazard to the environment and to the health of the operator. Lube oils are consumed worldwide, and this consumption was estimated at 49 million cubic meters/year [8]. The basic function of applied industrial effluent treatments in general is to reduce the impact of the discharge of the wastes in the receiving bodies or on the biological system of the sewerage systems involving physical, chemical and combined processes, used in the removal of organic compounds dissolved in the water [9]. This article seeks to define the requirements and restrictions of water resulting from the effluent treatment of cutting fluids at the

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_70, © Springer-Verlag Berlin Heidelberg 2011

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Sustainability in Manufacturing - Selected Applications

end of its useful life in transformation industries, with the aim of reusing the water from these effluents in the DFS regeneration process. The reasons for closing this cycle of the reuse of water is due to some factors such as: present cost of water, compliance with the requirements of environmental control entities and preservation of the environment.

2

THE FOUNDRY SAND CYCLE

The foundry process consists of the fusion of a metal, which in a molten liquid state is cast in a quantity necessary for filling a mold. Once molded, the two halves are joined (with the inclusion or not of a core, depending on the requirements of the product) and the liquid metal is poured into the mold, filling out the whole cavity. The molds are obtained through the molding process, generally in green sand. The sand is burned when enters into contact with the incandescent metal, producing alterations to its properties. At the end of the process, all the material contained inside the casting flasks are submitted to a vibration action, in order to separate the parts from the foundry sand. The residue is the mixture of the green sand (the portion of burned sand summed to the portion of sand still usable for a new casting), the chemically bonded sand (from the disaggregation of the cores, when used in the casting) and residues of the molten metal. The manufacturing process of the castings uses a great quantity of sand for the preparation of the molds and cores. The consumption of sand depends on the type of casting, and varies from 800 to 1,000 kg for each casting of 1,000 kg [10]. This sand is normally extracted from quarries or rivers, and are considered as nonrenewable, and processing usually causes environmental damages. The high quantity generated is extremely high due both to the abundance of raw-material required as well as to the inefficiency of the regeneration and recovery processes developed to date. Since large quantities of natural resources are used as well as the large quantities of pollutants generated (around two million tons/year, only in Brazil), the productive process of the foundry industries has a low environmental performance. Further, the visual pollution caused by the disposal of the reject in landfills is to be noted, due to its physical aspect [11]. The disposal of the DSF reject in landfills, both industrial and private, is a common measure adopted by the industries, representing about 90% of all spent sand [12]. The existence of landfills generates the accumulation of liabilities, where there are mixtures of DSF with other types of residues, generally with greater contamination potentials. This can generate a risk situation to the foundries, which are, as a rule, made responsible for any environmental damages caused. The lack of knowledge about the actual environmental impact caused by spent sand (alone) generates this type of inconvenience, apart from the fact that the landfills occupy areas that could be put to better use. The shortage of adequate areas for deposit and eminent requirement for conformity to environmental standards, has led the foundries and researchers to look for sustainable social, economic and environmental solutions. The main component of the molding sand (or foundry sand) used for foundry is fine aggregate, mineralogically pure, called “basic sand” [10] with a fineness that varies in diameter from 0.05 mm to 2 mm. The types mostly used in the foundry industry are silica sand (SiO2), olivine sand ((MgFe)2SiO4), zirconite sand (ZrSiO4) and chromate sand (FeCr2O5 or FeCr2O4) [13]. The basic requirements for a satisfactory performance of the foundry sands are [13]:



Dimensional and thermal stability at high temperatures;



Adequate grain shape and size;



Chemically inert to molten metal;



Not easily dampened by molten metal;



Not containing volatile elements producing gas upon heating;



Be available in large quantities and at reasonable prices;



Purity and pH in accordance with the requirements of the bonding systems;



Compatible with present and new chemical bonders as these are developed.

The return of the foundry sand to the system in a closed cycle is theoretically the ideal process, but in practice this becomes impossible due to the losses inherent to the process and consequent necessity of replacement of materials. The regeneration of sand aims to recycle the basic sand through the elimination or reduction of incrusted materials [14]. The regeneration of foundry sand implies in the superficial cleaning of the grains and removal of particles resulting from the cleaning. The purpose of this process is to conduct back the used sand to a condition similar to new sand. This condition permits the sand to be reused in the molds or cores, without prejudice to its qualities [15]. For regenerating the foundry sand three types of treatment are most frequently used, either singly or combined – mechanical, thermal or humid treatment. This paper analyzes aspects related to the application of the humid treatment. The humid treatment is the most efficient methods for cleaning the spent foundry sand, always when the residues to be removed are soluble in water (such as sodium silicate) or hydrophilic substances (such as bentonite). Nevertheless, the humid treatment requires large quantities of water (8 tons of water/ton of processed sand) [15]. This process, when combined with thermal regeneration, produces sand for reuse with a quality equivalent to new sand, presenting regeneration rates in the order of 90% [16]. The water used in the process must be exempt of salt-forming anions (chloride, sulfates, nitrates, phosphates), once these are potential generators of sand incrustations. Should there be any incrustation during the formation of the core, there will be a possible geometrical malformation in the cavities of the mold. For this same reason, the water for cleansing the sand should propitiate a reduction in the content of residual sodium in the sand, in order not to interfere in the properties of the cores and molds prepared. 3

THE CUTTING FLUID TREATMENT CYCLE

The basic function of the coolants (soluble oils - 90% is constituted of water) is to introduce and improvement in the metal machining process (lubrication, cooling and cleansing of the region being machined). Discharging these products in the water could cause the formation of a film on the surface. This hinders the passage of air and light, indispensable items for the respiration and photosynthesis of some organisms. Despite the fact that the legislation in force stipulates that 30% of the volume of oil present in commercialized fluids should be collected and re-refined, the existence of the specific legislation does not prevent the worldwide criminal actions of users discharging these effluents. Apart from the adverse impacts related to the uncontrolled discharge or inefficient treatment of the cutting fluids at the end of their useful lives, in the transformation industries, occupational

Sustainability in Manufacturing - Selected Applications

409

health is also a matter of extreme importance in the industrial centers. These products could be responsible for a great number of illnesses, which can be caused by spray, vapors or sub-products formed during the machining process or even by direct contact with the product [17].

To map the present conditions of the processes, four different As a result of the evaluations it was possible to verify whether the water discharged from the effluent treatment processes had the requirements for being used in the foundry sand cleansing process. 

The emulsion used in the machining process of cast iron;

The volume of discharged industrial effluents is still increasing. Nevertheless, the approaches towards management of these effluents are for reducing the areas for disposal. Moreover the operating cost of treatment plants and environmental requirements have stimulated the development of new processes for the treatment of wastewater treatment [18,19].



Water deriving from the Effluent Treatment Plant;



The emulsion resulting from the discharge of the chip receiving hopper;



Water from water utilities network

One ton of lubricant oil represents the equivalent of a pollutant load of 50.000 inhabitants. Only one liter of lubricant oil is capable of depleting oxygen of one million liters of water, and each liter of lubricant oil discharged to the soil takes 100 to 120 years to deteriorate [8, 20, 21]. Three out of the different types of effluent treatments in use by the industries were analyzed herein. 3.1

Thermal Process

The thermal breakdown is a physical process which dispenses the use of chemical products. The aqueous phase is removed from the emulsion by means of evaporation, and the oil remains, due to the fact that it has a higher boiling point. The evaporated water is condensed and, in an additional phase, the oil residues are separated. The advantages of this process are in the fact that no sediment is produced and the purity of the separated water, which is exempt of any salts. The disadvantage is the high cost of the operation [22]. 3.2

Chemical Process

In the chemical processes, acids are added in order to breakdown the emulsions through degradation of the emulsifiers. The chemical reaction can be reinforced with the addition of metal salts. These salts react with the emulsion separating it into phases, permitting the removal of the oil from the surface of the fluid in the emulsion treatment tank [9, 23]. 3.3

Mechanical Process – Use of Centrifuges

The soluble oil filtering system, using centrifuge separator filters, acts without the use of filtering elements or movable parts. The principle consists of the separation of solids through a centrifuge action, generated by the velocity in which the fluid is pumped into the separator [24]. 98% efficiency is estimated for the removal of solids, over 44 micra. The system works with recirculation, aiming towards maintaining the levels of solids in the cutting fluid tanks low. The separated solids are placed in special drums or containers to be sent for disposal [24]. 4

OBJECTIVE

This paper analyses the feasibility of reusing water resulting from the treatment of effluents from cutting emulsions in the DFS regeneration process. Three Technologies were analyzed for the treatment of effluents: chemical (acid breakdown); thermal and mechanical (using centrifuge) and thermal (evaporation). To reach the objective, the following phases were proposed for the work: 

Analysis of treated water in order to verify the residues that the treatments are not able to eliminate;



Evaluation of the pre-requirements necessary for the water to be used in the foundry process.

Chemical tests were performed in all the cases in order to verify the incoming and outgoing characteristics in the machining and foundry process. Usually, these types of industrial water treatments retain in the resulted water composition elements that are harmful to the environment, which are of difficult degradation, or chemical elements, which when mixed with the foundry sand hinder the adequate formation of the molds. 5

MATERIALS AND METHODS

Cutting fluids were collected in discharge situation of machinerytools. The predetermined situations for the tests were: T1 – aqueous phase without treatment; T2 – discharged emulsion from the chip receiving hopper; T3 – water from the effluent treatment plant; T4 – water from the water utilities network. Three types of treatments were also performed in oily effluents: thermal, chemical and mechanical. At the end of each type of treatment, the resulting water was submitted to a chemical analysis, in order to verify the quality and efficiency of each method. Before carrying out any of the treatments (chemical, thermal and photochemical) a pre-treatment was performed (a rough separation of water/oil from the effluents) with the purpose of separating the emulsion phases: oily and aqueous. Upon receiving the pre-treatment the oily phase was led to be rerefined (aggregate value), and the aqueous phase (no value) directed to each one of the treatments under analysis. For the performance of the thermal treatment an industrial evaporator was used. 5.1

Chemical and physical characterization of the effluent

The pH of the effluents was determined by a MICRONAL pH meter, model B-374, in compliance with standard ASTMD 1293-84. The chemical analyses were performed in the laboratories, in order to obtain quantitative data on the degree of saturation of the emulsions and of the treated waters. Included among the chemical analyses performed were: 

pH ;



conductivity ;



turbidity ;



alkalinity ;



chlorates ;



total hardness ;



content of tramp oils ;



refraction rate ;



degree of corrosion.

410 6

Sustainability in Manufacturing - Selected Applications RESULTS

When an oily emulsion used in machining of metals loses its specific functions, this oil is no longer a consumption material of the operation and becomes a residue, and therefore it has to be discharged to the liquid effluent treatment plant. This item represents the results of the analyses performed with the waters resulting from the three treatment methods of the aqueous phase of soluble cutting fluids. Caption – ND: Non-determined T1: Aqueous phase without treatment T2: Emulsion discharged from chip receiving hopper T3: Water from the Effluent Treatment Plant T4: Water from the Water Utilities Network (SABESP) Table 1 presents the results of the chemical analyses for the four samples : T1 – aqueous phase without treatment; T2 – emulsion discharged from chip receiving hopper; T3 – water from the effluent treatment plant; T4 – water from the water utilities network. With reference to the pH, samples T1 and T2 have values within the standard for emulsions, which indicates that the product is not contaminated. In the case of the effluents (water), the neutral pH presented fulfills the requirements of the legislation, in ideal conditions. In this manner, the pH did not present itself as a good parameter for comparison. In the analysis of corrosion, the samples presented corrosion within specifications (did not present corrosion). The refraction rate of sample T2 was very low. This occurred due to the centrifuge process of the particulate material (chips), causing the breakdown of the emulsion and separating the supernatant tramp oil from the aqueous means. This fact also justifies the high content of tramp oil found in the sample (13%). The conductivity of samples T1, T2 and T3 indicate that the quantity of disperse ions are within the requirements necessary for the process of cleansing foundry sand (molding). Nevertheless, the water from the water utilities network presented high values and does not have any condition to be used due to the high rate of ions in its composition. The hardness of the water from the Effluent Treatment Plant (T3) was very high, which indicated the presence of a high concentration of salts in the sample. This is a restriction for the process of cleansing the sand. Sample T4 (water for the utilities network) had acceptable values. The content of chlorate, which interferes directly in the reuse of the foundry sand, because it causes incrustations in the formation of the molds and cores during the sand regeneration process, was

Parameters

pH

T1

9.44

T2

9.2

T3

7.15

T4

7.05

very high for sample T3. This makes it impossible for this water to be used in the foundry sand cleansing process. Table 2 presents the results of the chemical analyses performed for samples of water resulting from the following treatments: thermal and chemical compared to the results obtained for the water from the water utilities network. The costs of the treatments being evaluates are varied. The evaporation method is the most efficient, but consumes a lot of energy and is only feasible for very large sized companies. The chemical method is more economical, because it uses simple reagents, but the water resulting from this treatment did not present adequate conditions for reuse in the preparation of new emulsions. The photochemical treatment also presents a high operating cost in the system used. With this system it was possible to emulsify a new emulsion; nevertheless the method still needs some technical alterations in order for the system to become more adequate for the machining process. Through the tests performed it was observed that the water resulting from the evaporation treatment can be used in the foundry process, nevertheless it presents some disadvantages, such as: The high cost of the treatment; The resulting water does not have a composition similar to the water supplied by the water utilities network; Analysis of he water

Water from evaporation 7 97.7

Water from chemical breakdown 6.7 81

Water from SABESP 6.7 81

pH Conductivity (µs / cm) Turbidity[NTU] Alkalinity (ppm) Chlorates (ppm) Ammonia (ppm) Total hardness (ppm) Calcium hardness (ppm) Nitrates (ppm) Phosphate content (ppm) Phosphorus (ppm) T Iron (ppm)

5.6 58.28 0 97.11 44.69

1.5 20.17 18.85 0.22 16.53

1.5 17.94 17.95 0.22 15.92

0

16.53

15.92

7.87 0.805

9.53 1.086

0.2 0.44

0.14

0.354

0.32

0.35

2.73

0.31333

Table 2: Results from the chemical analyses of the chemical and thermal treatments compared to the results of water from the water utilities network. Total

Corrosion test

Refraction rate

Conductivity in mS/cm

Content of tramp oil (%)

Aspect

0

12.5

3.84

0.8

Milky

ND

ND

0

2

4.41

13

Semimilky

ND

ND

ND

ND

2.33

ND

Turbid

160

227.7

ND

ND

70.40

ND

clear

21.4

3.66

hardness

Table 1: Characterization of samples – Inflow and outflow of manufacturing process.

Content of chlorates ppm

Sustainability in Manufacturing - Selected Applications The samples from the thermal and chemical treatments presented similar pH and conductivity values. Nevertheless, the water treated thermally presented higher values of turbidity, alkalinity, hardness, ammonia, chlorates, nitrates and phosphate when compared to water supplied from the utilities network, and the chemically treated water presented high values of nitrates, phosphate, iron and total solids. The elevated values of nitrates and phosphates could be related with anti-corrosion additives to the cutting fluids and not efficiently removed during the water treatment. Further, high contents of N and P could favor the growth of cyanobacteria and other microorganisms that use nitrogen and phosphorous as nutrients. In this manner, both the waters present elevated amounts of nutrients, in such a manner that the decrease of these values would be recommended for the reuse of these waters. In the case of the thermally treated water, the organic load, despite being high, is less than that of the chemically treated water, probably due to a greater efficiency in the separation of the oil by the membrane, prior to the heating phase. However, this method is prone to dragging volatile substances (such as ammonia, chlorates and bicarbonates), in such a manner that the alkalinity defined from the presence of calcium bicarbonates and magnesium also contribute to the increase in the hardness of this water. 7

CONCLUSIONS

It was verified that the three processes for treating cutting fluids (chemical breakdown photochemical and thermal) are within the standards established by the inspection agencies, but in accordance with the results of the analyses there is a necessity to discover more efficient and economic means of treating soluble cutting fluids. The water resulting from these processes, according to the standards, is acceptable, but may not be reused for cleansing foundry sand, and close the rational usage cycle. It is still not possible for a larger volume of water to remain available for noble purposes, avoiding unnecessary loss and discarding. Based on the results obtained, the necessity of performing microbiological analyses was verified, as well as more detailed physical-chemical analyses to verify the percentages of inorganic elements dispersed in the effluents and which prevent reuse. The results from the proposed tests supplied a perspective for a closed cycle, where the water used in the preparation of cutting fluids is treated on the same location and reused in the foundry of cast iron. In this manner the loss of water will only occur in the transformation processes, such as; dragged with the chips or through evaporation and no longer post-treatments, where, at present, industrial do not reuse these water and discharge is inadequately performed. Foundries must consider the dimensions of environmental, social and economic issues to achieve sustainability. Reuse of foundry sand reduces the accumulation of environmental liabilities in landfills and reduces the extraction of natural compounds for new sand, from an environmental point of view. In the social sphere, the reduction of landfill is related to an improvement in the areas surrounding the smelters. Therefore it is necessary to continue investing in improvements to this practice. However, the need for large volumes of water to the wet process regeneration is still a constraint in terms of environmental, economic and social development as it affects the increase of water use for less noble purposes and its cost including treatment and distribution.

411 Reuse as raw material in civil construction and covering of land waste sites is a procedure which has evidenced technical feasibility through various scientific studies developed in Brazil and abroad, becoming also environmentally feasible, by avoiding the extraction of sand directly from nature by the civil construction industry. A destination to exclusive DSF definitive landfills is more indicated for companies that do not have any demand for reused material in their region. 8

ACKNOWLEDGMENT

The authors express thanks to CNPq (Brazilian Council for Scientific and Technological Development) for financial support for the study. 9

REFERENCES

[1]

Herrmann, C., Bergmann, L., Thiede, S., Halubek, P. (2007): Total Life Cycle Management - An Integrated Approach Towards Sustainability, 3rd International Conference on Life Cycle Management, Zurich.

[2]

VAR – Verband der Aluminiumrecycling-Industrie e.V. Key Figures – Production of Aluminum in Germany; http://www.aluminiumrecycling.com/en/recycling/eckdaten.php. 2008.

[3]

Optimierung der Energiebilanz beim AluminiumDruckgießprozess, Abschlussbericht September 2007, Deutsche Bundesstiftung Umwelt, Förderkennzeichen. AZ 22197.

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[5]

Freitas, J. B.; Santos, J. A.; Almeida, M. L.; Costa, I. (2007): Aplicabilidade de tecnologias limpas para sustentabilidade dos recursos naturais: o caso de um acordo internacional que promove a substituição de matriz energética na Paraíba. In: XIV Simpósio de Engenharia de Produção, São Paulo.

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Gibbs, S. (2007): Saving on sand disposal: some metalcasters have been achieving disposal savings for their used metalcasting sand for more than a decade, but the game has grown and evolved. Modern Casting.

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DIN 51385 (1991): Lubricants; metal working fluids terms.

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Monteiro, M.I. (2006): “Tratamento de efluentes oleosos provenientes da industria metal-mecânica e seu reuso”, Doctorate thesis , Escola de Engenharia de Lorena da Universidade de São Paulo.

[9]

Paiva, T.C.B. (1999): “Caracterização e tratamento de efluente de branqueamento TCF de industria de papel e celulose”. 77 p. Tese (Doutorado) – Unicamp. Campinas / São Paulo.

[10]

Silva, T. C. (2007): Comparativo entre os regulamentos existentes para reutilização de resíduos de fundição. Monografia Engenharia Sanitária e Ambiental, Universidade Federal de Santa Catarina, Florianópolis.

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Bragança, s.r.; Vicenzi, j.; Guerino, k.; Bergmann, C.P. Waste

[12]

Matos, s. V., Schalch, V. (1997): Alternativas de Minimização de Resíduos da Indústria de Fundição. 19° Congresso Brasileiro de Engenharia Sanitária e Ambiental. Foz do Iguaçú, p.176.

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Moreira, A.S. (2008): Avaliação da utilização de resíduo gerado em sistemas úmidos de filtragem de particulados de fundição como matéria-prima na construção civil: estudo em tijolos de cerâmica vermelha. Belo Horizonte: Universidade Federal de Minas Gerais, 2006. DUNGAN, R.S. Journal of Residuals Science & Technology, 5, 111.

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Scheunemann, R. (2005): Regeneração de areia de fundição através de tratamento químico via processo Fenton. Florianópolis: Universidade Federal de Santa Catarina.

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Souza, J.F.; Gomes, J.O.; Kawachi, E. Y.; Riquelme, F. (2010): “Analysis of Processes to Improve the Reuse of Water from Cutting Fluids”, International Conference on Sustainable Life Manufacturing, Egirdir.

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Modular Grouping Exploration to design Remanufacturable Products 1

1

Nicolas Tchertchian , Dominique Millet , Olivier Pialot 1

1

LISMMA - “Ecodesign and Optimization of Product” Laboratory, SUPMECA Toulon, Toulon, France

Abstract One of the challenges of this decade is to rationalize the consumption of global resources while increasing economic activity. Remanufacturing is an option to this challenge; however this end of life strategy must be optimized. The information collected from a franking machine manufacturer, which has set up a refurbishment activity of its machines, has allowed us to qualify remanufacturing as a home-made process in many cases. This paper focuses on aspects of product Architecture. The purpose of the approach proposed in this paper is to reorganize the classical architectures towards modular architectures allowing a much more industrialized remanufacturing. Keywords: Lifecycle Design; Modular Design; Remanufacturing

1

INTRODUCTION

The environmental problems caused by the emergence of new markets and the fast development of the goods consumption require a rationalization of the world resources consumption while maintaining an economic activity increasing. To reach this objective, the remanufacturing is a process of restoring a discarded product (at the end of the lifetime) in an equivalent functional state to a new product. [1] [2] This definition constrained the architecture of the new product to take into account the operations relating to the remanufacturing defined by Steinhilper [3] or Sundin [4] such as dismantling, cleaning, the inspection, the sorting, the reconditioning and the reassembly. The modularization of the product is a way to allow the optimization of the operations related to the product end-of-life like the reutilisability, recycling, maintainability and the technological update [5]. In the literature, the modularization of the products forms part of the DfX approaches. “Design for Modularity” is an approach aiming at subdividing a system in smaller parts which can be created in an independent way and then used in various systems. In addition to the reduction of the costs, the modularity offers flexibility in the design (the addition of new technical solutions). The goal of this paper is to propose to the designer potential Product Architectures (pPA) containing modules remanufacturables, recyclables and upgradable. Three levels of improvement of architecture are distinguished: (Optimization, improvement and innovation) correspondent with various evolutions of use: necessary functions, Short term upgradable functions and Long term upgradable functions). This article is structured in the following way. In section 2, we introduce requirements of the remanufacturing on product architecture. In section 3, we define contours of the method. In section 4, we explain the operation of MGE tool. Section 5 examines validity of the approach with a case study. Finally section 6 concludes this study and positions the tool inside a more global methodology.

2 2.1

PRODUCT ARCHITECTURES REMANUFACTURING

REQUIREMENTS

FOR

Design For Remanufacturing

The literature shows a growing interest for the remanufacturing [1], [3]. The definition of the remanufacturing [2] implies several design fields such as the evaluation of remanufacturability, re-design of product to facilitate the remanufacturing processes [6], [7], [8], the research on the necessary operation to refurbish product (dismantling, cleaning, inspection and sorting, reconditioning and reassembly) [1], [3], environmental [9] and economic [10], [11] assessment. The majority of these publications treat often one aspect of this very vast field. Many research works [12], [13], [14] relate to the means to set up to optimize the dismantling of the products for their valorization. Complexity increase with the number of components and time necessary for dismantling depends on many parameters (interconnection between the components, types of fixing, direction of dismantling, etc.) The complete dismantling of a product quickly would be not easily justifiable from an economic point of view. In fact the remanufacturing must consider several criteria because, as Kara underlines it [15], “full disassembly of product tends to be unproductive due to technical and cost constraint”. Zuidwijk insists “a product recovery strategy determines the degree of disassembly of a product and the assignment of recovery options” [16]. For him four options of valorization coexist: 

The remanufacturing on a component level (requiring a complete disassembling of the product)



Recycling after complete disassembling of the product



Recycling after partial disassembling of the product (to respect quotas)



And the setting in discharge

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_71, © Springer-Verlag Berlin Heidelberg 2011

413

414

End of Life Management - Reuse and Remanufacturing

It will be noted that the option which would privilege an optimized dismantling of the product to re-use modules having an addedvalue is not mentioned. In 2002, Lambert introduces the concept of incomplete dismantling [13] justified by certain technical constraints: irreversible connections, economic constraints (since the costs of dismantling are inversely proportional to the profit generated by the re-use of the components extracted). By using CAD software, it is possible to determine if the disassembling of a part is blocked by another. 2.2

Design For Modularity

A new field emerges in answer to the need to carry out an intelligent and advantageous dismantling: “Design for Modularity”. The modularization of the products is the first step towards a sustainable design [17]. The modular products make it possible to improve valorization of materials by differentiating the modules which are potentially recyclable and which are not recoverable [18]. The design of the future products will have to take into account the definition of the modules and Product Architecture. Today most of product on the market does not have a clearly defined module. So the evaluation of the end-of-life scenarios is more complicated. In the products having a high number of components, sub-units can be defined as functional group of the product (example of the washing machine [18]). A modular decomposition is a means to optimize dismantling and to make more profits on the economic and environmental aspects. The remanufacturing makes it possible to re-use products or modules on several cycles according to the requirements of the consumer or the market evolution (update of the computers) [17]. Tomiyama [19] proposes the concept of “Post Mass Paradigm Production” to reduce the consumption of the natural resources as well as the production of waste by maintaining the standard of living or by improving it. The satisfaction of this new model passes by an increase of the modules lifespan but the consequences are the functional obsolescence of the product. The increase of product lifetime as well as the limitation of obsolescence requires to establish a strategy adapted to the value of product (repair, update, re-use, etc.): “Longer-life products should have functional upgradability besides reliability and fault-tolerance” [20] [5]. In the literature the benefits of the adoption of a modular approach in the product life cycle are less discussed. The product is not any more the result of a material assembly and a manufacturing process but a sum of inter-connected modules playing the role of central unit in the product modeling [21]. Thus in the model developed by Gehin [9] the product is composed of modules following the strategies of valorization on several cycles of use. Its approach allows an environmental evaluation of the product from these modules but by considering the operational costs on several cycles (supply chain, refurbishing…).

3

METHOD TO DEFINE POTENTIAL PRODUCT ARCHITECTURE OF REMANUFACTURABLE SYSTEM

3.1

The general principles of the methods

The general principles of our approach relate to the definition of Product Architecture concept, the integration of new uses/upgradability, the calculation of the environmental/economic evaluation and the concept of affinity. What is the definition of product architecture? “Product architecture is the scheme by which the function of a product is allocated to physical components” [22] “Each level in the product hierarchy has its architecture. Depending on the type of components, we speak about a functional, technology or physical architecture” [23] “The Product architecture is « a comprehensive description of a bundle of product characteristics, including number and type of components and number and type of interface of those components” [24] By convention, we define Product Architecture as: Current Product Architecture = ∑ Current Module i With Current Module = ∑ Component j. In the current product, the modules defined are “virtual” and depend on the function fulfilled. Architecture Nouveau Produit = ∑ Module Actuel i - ∑ Composant j + ∑ Nouveau Composant k The goal of the methodology is to suggest a more evolutive Product Architectures and taking account of new uses, new technologies, the new regulations… Integration of new usages associated with new functionalities Upgradability Criteria

Parametric Upgrade

Functional Upgrade

Integration

Planned,

No planned

By substitution of module By externalisation of module Cost

Low

High

Incertitude

Low

High

Innovation

Enhanced Functions

Enhanced Functions

New functions

Innovative Functions

…

Table 1: Functionalities extension. Economic and environmental assessment Environmental evaluation: The Environmental Impact (EI) uses to evaluate the modules corresponds to the Extraction/Manufacture Impact. Economic evaluation: The economic Costs (C) taking into account are the price of the modules.

Kimura [18] and Umeda [5] propose methods to design modular product depending on modules characteristics as life cycle options and geometrical information. Considering the product life cycle, the components which undergo the same life cycle should be gathered in a module. These modules can then undergo refurbishing and recycling processes without disassembling. Then, the management of the components throughout the life cycle is optimized and to the environmental impact and the costs of logistics and recovery are reduced. According to established criteria, impacting on the life cycle of the product, various modules can be defined. The result of modular grouping is a variety of product architectures.

Concept of affinity

It is the choice among this variety which poses problem; selected architecture must answer to impact reduction and costs controls requirements while the technical criteria are satisfied.



Grouping between modules recyclables



Grouping between modules remanufacturables



Grouping between modules upgradables

Affinity is a Potential of interaction between two modules (or submodules) according to certain criteria. According to the literature to improve modular architecture of a product it is necessary to gather modules (or components). “Considering a whole life cycle of a product, components that undergo the same life cycle processes should be grouped into one module for improving, e.g., disassemblability, maintainability, upgradability, reusability, and recyclability” [5] Types of grouping proposed in the paper:

End of Life Management - Reuse and Remanufacturing

415

MACPMR Methodology [25] is based on criteria which make it possible to gather modules having the same properties. Among these criteria:

Arel  1 

MTBF fort  MTBF fort MTBF fort

(2)

Reliability / Maintainability





Technical and visual obsolescence



Product range

Obsolescence is evaluated qualitatively according technologies evolution [5] and usages of the consumers.



3.2

Preliminary definition of the Modules

The method depends on an algorithm (Figure 1) allowing a characterization of the modules in pMR (i.e. Module potentially Remanufacturable), in pMr (i.e. Module potentially recyclable) and in intermediate modules pMU (i.e. module potentially Undefined which characterizes remanufacturables and/or recyclables modules). These modules can contain components which can be recycled and others remanufacturables (these modules pMU will be broken up in the stage of optimization into Sub-Modules SM so that there remain only pSMR and pSMr).

Obsolescence:

Data input: VLT of existing Component in Modules. VLT is defined by Umeda [5] and is calculated by Tool [27] in MacPMR [25].

Aobs  1 

VLT fort  VLT fort VLT fort

(3)

In order to classify each module identified, the environmental and economic criteria were selected because they make it possible to explain, qualitatively in first time, the true concerns in industry: decrease the environmental impacts (to respect the regulations more and more severe) and increase the profits. The characterization of the modules is done according to the distribution of the costs and the impacts of the product. The cost price was used to characterize the economic costs of the module, while the environmental impact is characterized by impact in the extraction-manufacture phases; this methodological choice (focusing on the Pre-life and not on the whole life cycle) makes it possible on the one hand to simplify the problem and on the other hand to identify objectively the strongest economico-environmental improvement source. 3.3

Modules organization

This stage makes it possible to determine quantitatively the main “potential” modules of the product. These potential modules (pMR or pMr) are groupings of evaluated modules then identified like remanufacturables or recyclable with the sub-modules resulting from the decomposition of the modules pMU (in homogeneous submodules r or R) in preliminary definition of modules. The modular grouping is based on calculation of affinity coefficient between modules (pMR or pMr), between sub-modules or modules and submodules. This affinity (eq. 1) contains 3 components presented in 3.1 like “Product criteria” influencing the remanufacturing: affinity of reliability (eq. 2), affinity of obsolescence (eq. 3) and affinity of commonality (eq.4). The purpose of this affinity is to privilege the groupings between modules whose coefficients are strongest.

Affinity    Arel    Aobs    Acom

(1)

The state of the art as of the applications carried out on an industrial case allow to privilege three criteria [5], [26]. Decomposition of affinity in several components at two strong points:  

An aggregate score allows an evaluation and an interpretation of the results more adapted for a use of the tool by a multidisciplinary team. The other advantage is the possibility to add weighting coefficients for each criteria, thus making it possible to better take into account particular strategies (for example: to support the grouping of the unreliable components in order to simplify the replacement of the module).

Characterization of grouping criteria: 

Reliability:

Data input: MTBF of existing Component in Modules.

Figure 1: Flowchart of method. 

Commonality:

Data input: The number of product in the range and the contents of each product in the range. Acom is the affinity of commonality between modules i and j, and p is the number of product in the range.

k 1 ij p

Acom 

k

p

(4)

If i and j = k then α = 1 else α = 0 The last stage of methodology is the validation of the pMR and pMr groupings. This stage is carried out by a control of functional compatibility of all the modules between them (materials, energy and information flow). This control must be carried out by the means of

416

End of Life Management - Reuse and Remanufacturing

a block function functional diagram (functional analysis) because one does not need only the presence of a component blocks the operation of the module and/or the product. When they are an incompatibility (low affinity), the grouping is not validated. It is necessary to make iteration in eliminating the component (or Sub-module) from the grouping and to compose a new grouping by a new affinity calculation. For more flexibility, design team has liberty of freedom to modify the Sub-modules (by optimizing materials, or connections…) and to make them compatible with the pMR or pMr. 3.4

Assessment of Product Architectures

The early phases of the tool allow the designer to have a large panel of modules, according to the selected sensitivity for each criterion: reliability, obsolescence and commonality. In the last phase the designer is assisted in his choice of one or more architectures. The choice of architectures depends on two criteria. First is economic, it takes into account the cost of the disassembly operations compared to the retail prices of the modules (or of the constitutive components). And second is environmental, the choice of architectures takes into account the impact of the modules in Extraction and Manufacture phase. The designer establishes, for each list of modules, various organizations helped by function block diagram (Figure 2) with information flows between modules. The objective is to chart the sequence of dismantling simply so as to withdraw in priority the pMR without disassembling the pMr. To calculate the time of dismantling it is necessary to provide information: type of connections, orientation of dismantling, accessibility, ect. The means used to estimate times of dismantling is the Prodtect software.

Figure 3: Franking machine’s Modules. INPUT DATA Environmental Impact

Modules' listing

N° M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11

User Interface ALD Service Station Power Supply Modem Main Board Main Motor Top Module Lower Module Lower Housing Cover

Production MTBF MTBF+ VLT Cost

VLT+

28,30

12,00

25

30

4

8

0,20

5,00

20

25

8

8

7,20

9,00

18

20

8

10

62,70

10,00

7

15

7

10

5,80

6,00

9

14

4

6

22,10

5,00

7

11

3

6

0,20

14,00

21

30

10

15

0,7

7

15

15

6

10

1,1

5,5

17

20

9

9

0,2

4

50

50

4

8

0,7

5

50

50

4

6

Table 1: Input data table for Modular Grouping Explorer. 4.2

Validation of remanufacturability

Then the reliability and obsolescence of the pMR are verified. The class of the 11 modules of the product is defined in Table 2.

Figure 2: Dismantling sequence. The disassembly cost of the pMR is given by:

Cdis  in1 t pMRi  C pMRi

(5)

For the environmental criteria, the designer calculates the impact generated during materials extraction and manufacture of modules. Avoided impact defines environmental impact for pMR and generated impact defines environmental impact for pMr. Solutions are compared with their Environmental Gain. 4

MODULAR GROUPING EXPLORER ON CASE STUDY

The case study considered the strategy improvement. 4.1

Initial classification of the Modules

In order to show the various steps of the proposed approach, a mechatronic product is considered (Figure 3), made up of 11 modules, marketed in the leasing form. According to the strategy of change wished by the user, the input data table is updated (Table 1). In improvement strategy only the two criteria Reliability and obsolescence, are used.

Modules

Class

Reliability fraction

Value fraction

Validation Class

User Interface ALD Service Station Power Supply Modem Main Board Main Motor Top Module Lower Module Lower Housing Cover

pMR pMU pMU pMR pMU pMR pMU pM_r pM_r pM_r pM_r

66,67 75,00 58,33 66,67 50,00 41,67 83,33 58,33 66,67 100,00 100,00

40 80 80 70 40 30 100 60 90 40 40

pMR pMU pMU pMR pMU pMR pMU pM_r pM_r pM_r pM_r

Table 2: Definition of Modules End of Life. 4.3

Modular grouping by Affinity calculation

The following stage consists in establishing pMR/pMR, pMr/pMr, pMU/pMR, pMU/pMr grouping according to reliability and obsolescence affinity. The table below is a sample of the affinity calculation between module UI and the 10 other modules. The modules with same class and having an affinity higher or equal to 80% are likely to be gathered within the same module. The designer validates or not in regarding technical and functional compatibility. For the modules whose affinity is lower than 80%, tool MGE calculates a potential affinity using BEST MTBF and BEST VLT introduced in INPUT. Finally when a couple pMU/pMX or pMX/pMX (with X=R or R) does not fill the criteria, there are a stage of iteration with decomposition of the module pMU and/or pMX Submodules when it’s possible.

End of Life Management - Reuse and Remanufacturing Modules

User Interface pMR

Class

User Interface ALD Service Station Power Supply Modem Main Board Main Motor Top Module Lower Module Lower Housing Cover

417

pMR pMU pMU pMR pMU pMR pMU pM_r pM_r pM_r pM_r

The calculation of disassembly cost is based on an hourly wage with 49€/h (tax included).

80% 72% 28% 36% 28% 84% 60% 68% 50% 50%

80% 80% 70% 40% 30% 100% 60% 90% 40% 40%

Afiab

Aobs

4. Calculation of the recovered value and the losses for the manufacture of a new machine (Table 6) GpMR=Pr – Cdis and LpMr=Pr + Cdis (6)

Table 3: Affinity calculation. 4.4

Evaluation Of Product Architectures

Five architectures are evaluated, corresponding to different strategies: (strategy economic, environmental, mixed and different levels from reliability and obsolescence). The procedure of evaluation will be detailed for the first list. 1. The designer defines the modules organization within the product and defines connections between modules. Iv Solution 1 1 M’1=M10+M11 2 3

4

M’2=M1+M4+ M5+M6 M’3=M2+M8 M’4=M3 M’5=M9 M’6=M7

5

Solution 2 M’1=M1

Solution 3 M’1=M10+M11 M’2=M1+M2 M’2=M2+M10+ M’3=M3+M4 M11 M’3=M5+M6 M’4=M5+M6

Solution 4 M’1=M10+M11

Solution 5 M’1=M10+M11

M’2=M1+M3

M’2=M1+M2+ M4 M’3=M3+M8+ M9 M’4=M5+M6 M’5=M7

M’4=M3+M8

M’4=M2+M4 M’5=M7 M’6=M8+M9

M’3=M5+M6

M’5=M7+M9 M’6=M8

M’5=M4+M7 M’6=M9

Modules

M'1 M'2 M'3 M'4 M'5 M'6

EoL

tdis (s)

Cdis (€)

pMr pMR pMr pMR pMr pMR

8,4 74,7 119,4 76,6 123,1 123,1

0,11 1,02 1,63 1,04 0 1,68

Pr (€)

9 33 12 9 5,5 7

Avoided Recovered Loss Impact Value (€) Value (€) (Pts)

Generated impacts (Pts)

9,11 31,98

0,9 118,9

13,63 7,96

0,9 7,2

5,5 5,32

1,1 0,2

Table 6: Economic and Environmental data per Modules for solution1. An economic gain is considered when pMR are extracted, whereas for the pMr the profits generated by the resale of materials to the recyclers are neglected. In the case study the resale of pMR compensates for the transport costs [28]. When a pMr is found at the end of the dismantling sequence the disassembly cost is null (Cdis=0). 5. Calculation of the avoided impacts and the pollution generated during materials extraction and manufacture of a new machine (Table 6). 6. Choice of the best Product Architectures The current scenario is modeled by taking the current Product Architecture with the dismantling process carried out in experiments. The end-of-life scenario for modules is defined table 3, i.e. M1, M4 and M6 are remanufactured and other modules are recycled or discarded.

Table 4: Potential solutions of Product Architecture defined by MGE. 2. Modeling of the dismantling sequence on Prodtect. pMR pMr

10 11

1 4

tdis=119s

2

tdis=123s

5

8

tdis=8s tdis=73s

6

4

5

6

2

8

3

2

8

7

3

9

tdis=77s

3

9

7

1

7

9

tdis=123s

7

9

Lv1

Lv2

Lv3

Lv4

Figure 4 : Dismantling sequence. 3.

Time and cost for pMR extraction

From Module 1

To Module 2

Type de fixation

M'1 M'2 M'2 M'2 M'2 M'3 M'3 M'3 M'4 M'5

M'2 M'3 M'3 M'3 M'4 M'4 M'5 M'6 M'5 M'6

Snap fit Screw Screw Screw Snap fit Snap fit Screw Snap fit Screw Screw

Nombre de fixation

Direction de désassemblage

4 4 2 2 1 1 4 1 1 2

+X +X +Y -Y +X +Y -X +Y +Y +X

Figure 5: Economic Assessment for each Solution. Economically there are more or less important disparities between the solutions (Figure 5). The dismantling of the current product cost approximately 40€. The best solution is solution 2 with a profit of 38€. From an environmental point of view the results are contrasted (Figure 6), indeed the performances of solutions from 1 to 4 are overall identical because the same modules are recovered for remanufacturing. The environmental performance of current product is less good because only three modules are remanufactured.

t (s)

8,42 64,46 1,84 4,86 35 4,86 1,84 1,84

Table 5: Potential solutions of Product Architecture defined.

Figure 6: Environmental Assessment for each Solution.

418 5

End of Life Management - Reuse and Remanufacturing CONCLUSION

The approach suggested in this article and materialized by a tool MGE allows to pre-define Modules in early phases of design process. These modules are made up in order to optimize the endof-life, by gathering the modules according to the characteristics of their life cycle. The groupings take into account the physical characteristics (reliability) of the components as well as the obsolescence of the components throughout life cycle (VLT). This approach was tested on a B2B product “A Franking Machine” with the goal to design a modular architecture remanufacturable. The tool determines a variety of solutions classified economically and environmentally. This tool is part of a more comprehensive methodology integrating the definition of Upgrade cycles, structure of Reverse Supply Chain and allowing the activities of remanufacturing economically viable while taking into account environmental and social considerations. 6

ACKNOWLEDGMENTS

This work was financially supported by ADEME and CETIM foundation in the framework of MacPMR research program. We thank them. 7

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[1]

Lund, R.T., (1996), The Remanufacturing Industry: Hidden Giant. Boston. Boston: Argonne National Laboratory study.

[2]

Ijomah, W.L., (2002), A model-based definition of the generic remanufacturing business process. University of Plymouth.

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Steinhilper R., (1998), Remanufacturing - The Ultimate Form of Recycling: Fraunhofer IRB Verlag, Stuttgart.

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Sundin E., (2004), Product and Process Design for Successful Remanufacturing. Department of Mechanical Engineering. Linköping, Sweden: Linköping University.

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Umeda Y, Fukushige S, Tonoike K, Kondoh S., (2008), Product modularity for life cycle design. CIRP Annals – Manufacturing Technology, 57, pp.13-16.

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Van der Laan, E., Salomon, M., (1997), Production planning and inventory control with remanufacturing and disposal. European Journal Of Operational Research, 102, pp.264-278. Ijomah, W.L., McMahon, C.A., Hammond, G.P., Newman, S.T., (2007), Development of design for remanufacturing guidelines to support sustainable manufacturing. Robotics and Computer-Integrated Manufacturing, 23, pp.712-719. Duflou, J.R., Seliger, G., Kara, S., Umeda, Y., Ometto, A., Willems, B., (2008), Efficiency and feasibility of product disassembly: A case-based study. Paper presented at the CIRP Annals - Manufacturing Technology. Gehin A., (2008), Développement d’une Méthodologie de Conception de Produits Durables. PhD Thesis INPG Génie Industriel.

[10] Kerr W., (1999), Remanufacturing and eco-efficiency: A case study of photocopier remanufacturing at Fuji Xerox Australia. International Institute for Industrial Environmental Economics: Lund University, Sweden. [11] Mont, O., Dalhammar, C., Jacobsson, N., (2006), A new business model for baby prams based on leasing and product remanufacturing. Journal of Cleaner Production, 14(17), pp.1509-1518. [12] Gungor A, Gupta S M., (1997), An evaluation methodology for disassembly process. Computers &Industrial Engineering, 33, pp.329-332.

[13] Lambert A. J. D., (2002), Determining Optimum Disassembly Sequences In Electronic Equipment. Computers &Industrial Engineering, 43, pp.553-575. [14] Desai, A., Mital, A., (2003), Evaluation of disassemblability to enable design for disassembly in mass production. International Journal of Industrial Ergonomics, pp.32, 265–281. [15] Kara S, Pornprasitpol P, H. Kaebernick H., (2006), Selective Disassembly Sequencing: A Methodology for the Disassembly of End-of-Life Products. Annals of CIRP, 55, pp1-4. [16] Zuidwijk R, Krikke H., (2007), Strategic Response to EEE Returns: Product Eco-Design Or New Recovery Process? European Journal of Operational Research, 191, pp.12061222. [17] Seliger G, Zettl M., (2008), Modularization as an enabler for cycle economy. Annals of CIRP - Manufacturing Technology, 57, pp.133- 136. [18] Kimura F, Kato S, Hata T, Masuda T., (2001), Product modularization for parts Reuse in inverse manufacturing. Annals of CIRP, 50, pp.89-92. [19] Tomiyama, T., Sakao, T., Umeda, Y., (2005), The Post Mass Production Paradigm, Knowledge Intensive Engineering, and Soft Machine. In International Conference on Life Cycle Modelling for Innovative Products and Processes. Berlin. [20] Kondoh, S., Umeda, S., Yoshikawa H., (1998), Development of Upgradable Cellular Machines for Environmentally Conscious Products. Annals of CIRP, 47(1). [21] Tchertchian, N., Liang, H., Millet, D., (2009), The Influence of the Multiple Life Cycles on the Environmental Impact of a Product. Proc. ICED 2009 17th Int. Conf. Engineering Design. [22] Ulrich, K. T., (1995), The role of product architecture in the manufacturing firm, Research Policy. 24: 419-440. [23] Erens, F. Verhulst, K., (1997), Architectures for product families. Computers in Industry, 33, 165–178. [24] Fixson, S.K., (2005), Product architecture assessment: a tool to link product, process, and supply chain design decisions. Journal of Operations Management. v23. 345-369. [25] Tchertchian, N., Millet D., El Korchi A., (2010), A method helping to define eco-innovative systems (product architecture + RSC structure + scenario usage). 17th CIRP International Conference on Life Cycle Engineering, Hefei. [26] Tseng H.-E., Chang C.-C., Li J.-D., Modular design to support green life-cycle engineering. Expert Systems with Applications,34:25, 24–37, 2008. [27] Pialot, O., Millet D., Tchertchian, N., (2010), Definition of potential upgrade scenario in early design phases of remanufacturable system. Proceedings of IDMME - Virtual Concept Bordeaux, 2010. [28] El Korchi, A., (2010), Conditions stratégiques d’émergence d’une reverse supply chain fondée sur le remanufacturing chez le fabricant d’origine, The 8th International Conference on Logistics and SCM Research, Bordeaux, 2010. 8

CONTACT

Nicolas Tchertchian Supmeca toulon, LISMMA laboratory, Maison des technologies, 83000 Toulon, France, [email protected]

Development of Part Agents for the Promotion of Reuse of Parts through Experiment and Simulation 1

1

1

1

Hiroyuki Hiraoka , Kazuma Ito , Kengo Nishida , Kazuki Horii , Yusuke Shigeji 1

1

Department of Precision Mechanics, Chuo University, Tokyo, Japan

Abstract For the management of individual part throughout their life cycle that is a requisite for an effective reuse of parts, a part agent system is being developed that consists of a network agent and a radio frequency identification electronic tag attached to the corresponding part. To develop functions of part agent and methods for effective reuse, an experiment system consisting of computers connected with a network and a life cycle simulator to simulate behavior of parts, users and part agents throughout the life cycle of parts are developed. This paper describes functions developed in part agents and their preliminary results. Keywords: Reuse of Parts; Network Agent; Life Cycle Simulation

1

INTRODUCTION

The effective reuse of mechanical parts is essential for developing a sustainable society [1]. To realize effective part reuse, we believe that it is essential to manage individual parts over their entire lifecycle because the appropriate maintenance is necessary for individual parts each of which has a different reuse history. The maintenance based on this management would promote the reuse of parts. Manufacturers need to capture data concerning the quantity and quality of the parts returned for reuse. In cases of leased products such as photocopiers, effective reuse of parts is achieved [2], because the products are under the management of the manufacturer throughout their lifecycle. However, many kinds of products, once sold, are not under manufacturer control; this makes it difficult to for manufacturers predict the quantity and quality of returned parts. Parts from products such as small computers and automobiles may be reused through markets that are beyond the manufacturer’s control. Privacy and ownership issues, as well as the uncontrollable and unpredictable diversity of user behavior, hinder the management of parts by manufacturers.

FMEA HDD JRCCE PEID

Failure mode and effect analysis Hard disk drive The Japan RFID consortium for consumer electronics products Product embedded identifier

RFID

Radio frequency identification

RPN

Risk priority number

SMART TPI

Self-monitoring technology

analysis

and

On the other hand, it is difficult for product users to manage and carry out appropriate maintenance on the large number of a variety of parts of manufactured products owned by them. Difficulties in managing all these parts—not to mention inaccessibility to appropriate maintenance information—impede management by users, in spite of the fact that more environmentally friendly actions are required from users if they are to reuse parts effectively. On the basis of these considerations, we propose a scheme whereby a part “manages” itself and supports user maintenance activities. For this purpose, the authors propose a management system that includes network agents and radio-frequency identification (RFID) tags [3]. The network agent is assigned to an individual part of a product to which an RFID tag is attached. It is programmed to follow its real counter part throughout its lifecycle. We named this network agent as “part agent” [4] [5] [6] [7] [8] [9] [10] [15]. The part agent provides users with appropriate advice on the reuse of parts and promotes the circulation of reused parts. Using this mechanism, consumers can also be advised about environmentally friendly ways of product use and predicted product failures. Such advice helps users to manage the product during the use phase of its lifecycle. In this paper, we describe these advice functions, as implemented in an experiment system for prototype part agent and simulation system for parts, part agents and users. With the parts of notebook PCs as examples, experiment and simulation indicate the effects of developed functions. The concept of the part agent system is described in section 2. section 3, the life cycle simulation of parts and part agents explained with its model. Functions developed are described section 4 and their preliminary results are shown in section Finally, the paper is summarized and concluded in section 6.

In is in 5.

reporting

Total performance indicator Table 1: Abbreviations used in this paper

2

PART AGENT LIFECYCLE

FOR

SUPPORTING

THE

PRODUCT

The proposed part agent system is based on the following usage scenario. The system uses the part agent to manage all information

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_72, © Springer-Verlag Berlin Heidelberg 2011

419

420

End of Life Management - Reuse and Remanufacturing

about an individual part throughout its lifecycle. The proposal assumes the spread of networks and high-precision RFID technology. The part agent is generated at the manufacture phase of the main parts, when an RFID tag is attached to its corresponding part. The part agent identifies the ID of the RFID tag during the part’s lifecycle, and tracks the part through the entire network. In contrast to Product Embedded Identifier or PEID technology [11] that involves a small computing chip, an RFID tag, and sensors to support the middle and end of life of the products, our goal is to promote multiple reuses of individual parts that may not necessarily be managed by manufacturers, which require a “lightweight” system. Figure 1 shows the conceptual scheme of the part agent. The part agent collects information needed to manage the corresponding part, by communicating with the various functions within the network. These functions may involve a product database that provides product design information, an application that predicts deterioration of parts, one that provides logistics information, or one that provides market information. Further, the part agent communicates with the functions in the local site, such as sensory functions that detect the state of the part, storage functions for individual part data, and management and control functions of the product. Communication is established using information agents that are subordinate network agents generated by the part agents.

Figure 1: Conceptual scheme of part agent.

On the basis of the collected information, the part agent provides users with appropriate advice on managing the corresponding part. When the user makes a decision concerning product usage, the part agent provides necessary directions vis-à-vis product management and control functions. The agent also contacts a part manufacturer regarding the repair of the part, when it foresees part failure. 3

LIFE CYCLE SIMULATION OF PARTS

We simulated the behavior of parts containing part agents throughout their lifecycle, to investigate the effectiveness of part agents and the conditions that promote parts reuse [10]. When parts are reused, they may follow different individual lifecycle paths, given that they are used differently by each user. To address this diversity of parts behavior, we simulated individual parts separately, observing various lifecycle phases; we also investigated the effect of the situation, user, and history of each part on its behavior. 3.1

Part and part-agent models for lifecycle simulation

Figure 2: Models of part and part agent for life cycle simulation. These features make it possible to simulate the behavior of each individual part, throughout its lifecycle. Lifecycle information is represented by the lifecycle design, which consists of a network of lifecycle phases. In this simulation, there were seven lifecycle phases: the production phase and assembly phase, for production; the product market phase; the use phase, where products are used and parts deteriorate; the maintenance phase, where parts are replaced; the part market phase, where reusable parts are stored for use; and the disposal phase.

To simulate the behavior of parts and part agents throughout their lifecycles including reuse, we developed part and part-agent models as shown in Figure 2. In that figure, blocks represent the conceptual elements of the model and lines indicate the relationships between them; the cardinality numbers for the occurrence of elements are shown on their sides. For example, N and 1—as shown on the line between “Part instance” and “Part design”—indicate that multiple Part instances exist for one Part design. Lines with hollow arrows represent inheritance relationships, with higher concepts shown on the arrow side.

3.2

In this model, the following features were implemented:

Models of cost and environmental load are developed for evaluating the lifecycles of parts. The cost and environmental load of producing the parts, assembling the product, distributing the parts and product, and disposing of the parts are assumed to be fixed values. Environmental load values were obtained from data associated with the environmental label Eco Leaf [12], for computers. The environmental load of exchange is also assumed to be constant, but we make the exchange cost for a case with agent assistance cheaper than that for a case without agent assistance.



To represent individual parts, part instances and part designs are modeled separately.



Lifecycle information is represented by a lifecycle design containing a network of lifecycle phases.



An action represents information concerning which part instance is in what lifecycle phase and in which site, or, the behavior of an individual part in a specific time-step.

Assumptions inherent in the simulation

The simulation is performed under the following assumptions and conditions. The target product selected for the simulation was a notebook PC, Fujitsu FMV-BIBLO NF70W. It consists of four parts that are classified as high-level management parts, according to the definition provided by the Japan RFID Consortium fro Consumer Electronics products (JRCCE): a CPU, memory, a hard disk drive (HDD), and a DVD drive. Due to the technical difficulty of failure prediction, the failure prediction function of the part agent supports only the HDD.

End of Life Management - Reuse and Remanufacturing We assume that the cost and environmental load of a product increase in proportion to the time for which the consumer uses the product. The cost and environmental load are estimated as follows: cost is a product of the power consumed, the duration and the electricity bill coefficient representing the electricity bill per kilowatt hour; environmental load is a product of the power consumed, the duration and the CO2 coefficient representing the CO2 emission per kilowatt hour. Parts were replaced in either of two cases: when a part failed, or when a part agent advised that the user replace a part. We assumed that parts deteriorated according to their volume of operation. In this simulation, the volume of operation was represented by a small random value; each part had a value representing its health level. When a part was in operation, its health level was reduced as per a possibility distribution [13] where the accumulated failure rate increased gradually with the part’s volume of operation. 4

FUNCTIONS OF PART AGENT FOR SUPPORTS IN USE PHASE

To realize an effective reuse of parts using part agents, it is necessary to provide both users and manufacturers adequate information relating to the reuse of parts in use phase of parts. In this purpose, we have developed functions to be implemented within a part agent that support consumers as well as manufacturers in maintaining notebook computers and hard disk drives (HDDs), as examples of products and parts. We consider three issues exist in use phase of parts. First, users may use their product in a way that produces excessive CO2 emissions. This is not directly related to the reuse of parts, but it is an important issue for a sustainable society. Secondly, users do not know when and with which parts their parts should be replaced. If an adequate advice is provided on the information in accordance with the user preference, reuse of parts will be promoted. And the last but not least issue is that users do not know when their parts fail. If failures of parts can be predicted, not only users but also manufacturers can prepare the failure, which leads to effective reuse of parts. Functions have implemented in the prototype based on above consideration, that are: (a) control of the environmental load in a consumer’s product use phase, that corresponds to the first issue; (b) advice of replacement based on user’s maintenance preference, and (c) resolution of the conflicts in acquisition of user parts, that correspond to the second issue; and (d) prediction of HDD failures by using self-monitoring analysis and reporting technology (SMART) [14], and (e) support for maintenance of product, that challenge the last issue. 4.1

Warning of excessive environmental loads

In achieving a sustainable society, controlling the environmental load in a consumer’s product use phase is essential. One of the functions of the prototype part agent for achieving environmental load control is the control of CO2 emissions that promotes environmentally friendly actions of the consumer [15]. The part agent calculates the environmental load by taking into account the consumer’s product usage time against power consumption during usage. When the calculated environmental load exceeds a reference value—such as the average domestic CO2 emission— the part agent warns the consumer that his product usage is not environmentally friendly. We believe that such a warning function would encourage not only the control of environmental load during the use phase but also improvements in consumers’ environmental consciousness.

421 4.2

Reuse of part maintenance

based

on

users

preferences

in

As stated in the introduction, one of the main purposes of part agent is to provide adequate advice on the replacement of parts, which helps consumer’s voluntary actions on their reuse. In the lifecycle simulation, the part agent advises part replacement based on forecast part behavior and user’s maintenance preference [10]. Projected part behavior for a period is forecast and anticipated cost and environment load for the period are calculated based on whether the part continues to be used as is or is replaced. The following three preferences on user maintenance are assumed: 

Preference to reduce costs



Preference to reduce environmental load



No preference, i.e., use a part until it breaks down

The forecast determines whether a part should be replaced based on user preference. If the user prefers cost reduction, estimated cost in the case the part is replaced and that in the case the part continues to be used are compared. The part agent advises the replacement of the part when the former cost is smaller than the latter. If the user prefers environment load reduction, the decision is made in the same way but based on estimated environment load. To forecast part behavior for a period, all possible series of actions are enumerated based on the failure time step. The probability of failure in a period is estimated and corresponding actions are predicted, determining the probability of each series of actions. Based on the cost and environmental load for each action, anticipated cost and environmental load for the period are calculated for when the part is replaced and for when it continues to be used. 4.3

Resolution of the conflicts in acquisition of used parts

When a part is broken or its level becomes lower than the preference of the user, the part agent searches a suitable part from used part market and picks it up as a substitute. In this process of part exchange, conflict may occur when multiple agents want a same part. This conflict may hinder the adequate delivery of replacement parts and the smooth reuse of parts. If a value is defined to represent how the user wants the part, we can use the value to resolve this conflict. We named it “desire level”. A function is developed for the maintenance site that compares the desire level of every candidate part users and provides the part to the part agent whose user has the highest desire level. The users who are not provided with the part proceed to the next round of search. The user who cannot acquire the used part, a new part is provided. Desire level is defined as a ratio of the level of the used part and the level acceptable for the user. For example of performance, it is the ratio of the current performance of the used part and the lowest acceptable performance defined for the preference of the user. As preference is defined as the combination of multiple aspects such as performance, cost and environmental burden, the desire level is calculated as the average of ratio for the aspects. 4.4

Prediction of HDD failures using SMART

Predicting product failures is an effective tool for assisting in the maintenance of consumer products. Although the prediction is difficult, it is a critical issue in the lifecycle management of products. If the part agent system predicts failures, consumers can prepare for maintenance prior to the potential breakdown of the product. The prediction also enables manufacturers to foresee the number of parts that require repair and hence adjust the volume of parts being manufactured at that time; this would lead to a stable supply of repair parts, which in turn would lead to improvements in consumer satisfaction.

422

End of Life Management - Reuse and Remanufacturing

For predicting HDD failure we use SMART functions that most HDDs manufactured in recent years have embedded. Pinheiro et al. [14] reported four SMART parameters that were recognized as having a strong correlation with HDD failure: scan errors, reallocation counts, offline reallocations, and probational counts. The failure rate of an HDD increases within the 60 days following the detection of errors in these parameters. Monitoring the four SMART parameters enables the prediction of nearly 50% of an HDD’s failures. HDD failures can inflict serious damage upon a computer. When such a failure is predicted, the part agent sends a warning, via the network, to the consumer, store, repair factory, and manufacturer. Consumers can prepare for HDD repair by creating a backup of its data and requesting spare parts; the spare-part manufacturer, in turn, can estimate in advance the urgency and number of the spare parts required, enabling a stable supply of parts to the consumers. 4.5

Support for maintenance of products

As described above, some parameters such as SMART parameters indicate errors that are not serious themselves but may lead to a fatal problem. Because such parameters in other products are not necessarily identified, it would be helpful if part agents have a function to evaluate the seriousness of the detected error based on the experience data. We have developed a scheme that, when a part agent of a component detects and reports such errors, the product agent evaluates its seriousness for the product by referencing parameters on the use of product such as temperature, duration and workload. If those parameters imply excessive use of the product, the product agent issues a warning to the user. If the use is in normal level, the product agent judges it as deterioration. The risk of the error is also evaluated using the method of failure mode and effect analysis (FMEA). We assume FMEA is performed in design process of the product and the part agents can use its results. The seriousness of a failure is represented by risk priority number (RPN) that is defined as the product of severity level of the failure, its occurrence rate and possibility of its detection. FMEA evaluates RPN by following the tree of analysis that represents the propagation of effect of failure mode. As the detected error is recognized as an occurrence of failure mode in FMEA, its frequent detection means the change of occurrence rate. The product agent re-calculates the RPN and if necessary, changes the priority of maintenance. 5 5.1

To investigate the effects of the support functions mentioned in the previous section, we developed an experiment system that simulates the lifecycle of a computer product and its component parts with an envisioned lifecycle scenario. For that purpose, we built a Local Area Network where computers are installed as the main lifecycle phases of products and carry out the simulated processing for the phase. Parts and products are produced as virtual objects simulated in the computer and are represented by RFID tags. They move among computers i.e., lifecycle phases of the product. A prototype part agent collects and manages information about its corresponding part or product and cycles through the network by following the movement of the part. The results of the simulation of the functions in 4.4 and 4.5 are described in 5.5 and 5.6. 5.2

A notebook PC is used for 208 weeks, or four years. The PC is used for 15 h per week as an initial value, where 10 h are of normal-power work and the remaining 5 h are of low-power work. We assumed that consumers tend to gradually increase their usage hours as they get accustomed to using a product; therefore, with the passage of time, we increased the duration of time for normalpower work per week and decreased that for low-power work. The cost and environmental load of the product increase accordingly. When a part agent warns a consumer that a product is generating a high environmental load, the consumer resets the length of time for normal-power work and that for low-power work back to the initial values. This reduces the environmental load of the product in its use phase. The simulation is performed in two cases: an assisted case scenario, where the consumer uses the notebook PC following the advice of the part agent, and an unassisted case scenario, where the consumer uses the PC without advice from the part agent. As shown in Table 2, the simulation of the consumer use phase indicates that the implementation of the part agent’s function for controlling environmental load results in a 10% reduction in environmental load during the use phase. This leads to the increase of TPI by approximately 2% when no repair is required.

EFFECTS OF PROPOSED FUNCTIONS Simulation and experiment for part agents

To evaluate the functions of part agents proposed in the previous section, simulations and experiments are performed. First, we developed a life cycle simulation of parts and part agents without implementing network agents and RFID tags [10]. The objective of the simulation is to inspect the feasibility of part agents, to investigate conditions to promote reuse of parts and to test the functions of part agents. The functions in 4.1, 4.2 and 4.3 are developed based on this simulation and their results are described in 5.1, 5.2 and 5.3, respectively. Next, a prototype part agent system is implemented using network agents [16] and RFID tags [17]. The RFID tag contains part identifier and identifiers for the current and destination sites. To assist the part agent, we have developed basic functions such as synchronized transfer of the actual part and its corresponding part agent. We have also implemented a prototype Web-based user interface to allow users to communicate with the part agent.

Warning of excessive environmental loads

The influence of the function in the consumer use phase that provides warning of excessive environment load was observed in the simulation under the following assumptions and conditions [15].

Warning of part agent

CO2(kg)

Support

37.78

Without support

42.66

Table 2: Environmental loads in consumer use phase 5.3

Reuse of part maintenance

based

on

users

preferences

in

We conducted the life cycle simulations to evaluate the effect of users preferences using data of a notebook computer that consists of 4 components. The simulations are conducted for 4 cases, that are 1) all 40 users prefer cost reduction, 2) all 40 users prefer environment load reduction, 3) all 40 users have no preference and 4) 40 users are mixed i.e., are composed of 15 cost reduction users, 15 environmental load reduction users and 10 no preference users. To evaluate the effectiveness of the scheme, we measured aggregate data such as cost, environmental load, workload, and value of the total performance indicator (TPI) [18]. The TPI is calculated by dividing the workload by square root of product of the cost and environmental load, which indicates the effectiveness of product use. Consumer’s satisfaction is also estimated by the reduced rate of cost or environmental load of the part he is using

End of Life Management - Reuse and Remanufacturing

423

Cost reduction

User preference

Environmental reduction -2

TPI

load

No preference

-2

Three types mixed -2

-2

1.92 X 10

1.88 X 10

1.70 X 10

1.88 X 10

Consumer’s satisfaction rate (%)

6.61

4.97

9.96

25.35

Total number of reuses

162

40

0

172.7

Part replacements suggested by agents

155

0

0

121.7

7

40

0

51

Part replacements due to troubles

Table 3: Comparison of user preference in the life cycle simulation. from its nominal average value for the whole part life. The result is shown in Table 3. Note that consumer’s satisfaction is high in the case with three types of users compared to the case with single type of users. We found many parts with various qualities in the part market in the mixed users case, which promotes reuse of parts and results in higher satisfaction of consumers. 5.4

Resolution of the conflicts in acquisition of used parts

To evaluate the effect of the function, a simple simulation was done for 6 users who want a substitute part. It was done in two cases for comparison, one where the parts are exchanged using the developed function and the other where the parts are exchanged in random. Figure 3 shows the results of 1000 exchanges where the desire level is shown in the horizontal axis and the difference of original desire level and the desire level of part that is actually acquired is shown in the vertical axis. We can see in this simple simulation, that users with high desire level acquired used parts in

the case with the developed function, whereas they did not necessarily acquire desired parts in the random case. 5.5

Prediction of HDD failures using SMART

Prediction of failures of parts enables proactive replacement of parts. In this simulation [15], we assume the following for HDD failure prediction. When the part agent supports a consumer, the agent contacts a store to make reservations for a spare part in advance of the predicted failure. This enables a smooth exchange after an HDD breaks down. In contrast, when the agent does not support a consumer, we assume a lead time of two weeks for the delivery of the replacement part, following the breakdown of the HDD. This shortens the time during which the consumer can use the product. The incidence data of HDD failure for each SMART parameter error is used in the simulation, that were derived by converting annualized failure rates for each SMART parameter error [14] to the time distribution of failures. We assumed that an HDD breaks within the 60 days following the detection of the first error. When the part agent supports a consumer, it makes a reservation for repair within the 60 days after the SMART parameter errors are detected. The simulation revealed that the TPI increases as the number of repairs increases, as shown in Table 4. This is the effect of the reduction in lead time, created by the failure-prediction function. Because of the repair reservation made by the part agent and the subsequent smooth transition in obtaining spare parts, consumers can continue to use their products without downtime, allowing them to work efficiently, which results in a large TPI. We consider that the result indicates a service improvement by the manufacturer, as offered to the consumer. The part agent’s support would enable manufacturers to reduce the loss of sales opportunities.

(a) Distribution of parts based on desire level.

Number of repairs

Increase rate of TPI (%)

0

102.3

1

102.8

2

103.4

3

104.2

Table 4: Rate of increase in TPI by reduction in lead time. 5.6

Support for maintenance of products

To support the evaluation of the detected error based on the experience data, we have implemented a function to compare the occurrence of errors and the parameters that is supposed to be related with the errors, such as temperature. If the errors are estimated due to the user’s excessive use of product, the product agent provides a warning. (b) Distribution of parts in random. Figure 3: Simulation of conflict resolution.

Part agent also evaluates the risk of error using FMEA. It recalculates RPN of the error based on the repetition of detected error

424

End of Life Management - Reuse and Remanufacturing

and advise the user to change the priority of maintenance as required. We are considering that this scheme is more effective when multiple product agents cooperate and gather the information. If a clear increase of detections on an error without apparent cause is identified by the information gathered from product agents, this might be a sign to start examining the possibility of the recall of the product.

Preference of Consumers, in: the 11th International Conference on Precision Engineering. August 16–18, 2006. Tokyo, Japan. [7]

Hiraoka, H., Fukuda, N. and Hanatani, T. (2007): Handling the Variety for Reuse of Mechanical Parts, in: the Proceedings of EcoDesign 2007. December 10–13, 2007. Tokyo, Japan.

[8]

Hanatani, T., Fukuda, N. and Hiraoka, H. (2007): Simulation of Network Agents Supporting Consumer Preference on Reuse of Mechanical Parts, in: the Proceedings of the 14th CIRP Conference on Life Cycle Engineering. June 11–13, 2007. Tokyo, Japan.

[9]

Hiraoka, H., Hanatani, T. and Tanaka, A. (2008): Life Cycle Simulation of Mechanical Parts with Part Agents for Promoting their Reuse based on User’s Preferences, in: the Proceedingd of the 5th International Conference on Product Lifecycle Management. July 9–11, 2008. Seoul, South Korea.

[10]

Hiraoka, H. and Tanaka, A. (2009): Simulator for Reuse of Mechanical Parts with Network Agents, in: International Journal of Automation Technology, Vol. 3, No. 1, pp. 77–83.

[11]

Jun, H. B., Kiritsis, D. and Xirouchakis, P. (2007) Research Issues on Closed-Loop PLM, in: Computers in Industry 58, pp. 855–868.

[12]

Japan Environmental Management Association for Industry (2009): Ecoleaf homepage, http://www.jemai.or.jp/english/ecoleaf/index.cfm.

[13]

Further research is needed to bring about the part agent system. These include issues pertaining to assembly information, data management, privacy, and security [19].

Weibull, W. (1951): A Statistical Distribution Function of Wide Applicability, in: Journal of Applied Mechanics, Vol. 18, No. 3, pp. 293–297.

[14]

Pinheiro, E., Weber, W.D., and Barroso, L.A. (2007): Failure Trends in a Large Disk Drive Population, in: the Proceedings of the 5th USENIX Conference on File and Storage Technologies. February 13–16, 2007. San Jose, CA.

7

[15]

Nakada, T., and Hiraoka, H. (2009): Network agents for supporting consumers in the lifecycle management of individual parts, in: the Proceedings of the 6th International Conference on Product Lifecycle Management. July 6-8, 2009. Bath, UK.

[16]

Recursion Software, Inc. (2009): Voyager homepage, http://www.recursionsw.com/Products/voyager.html.

[17]

Hitachi Ltd. (2009): The World’s Smallest RFID IC mu-chip, http://www.hitachi.co.jp/Prod/mu-chip/index.html.

[18]

Kondoh, S., Masui, K. and Hattori, M. (2006): Proposal of the Index to Measure Total Performance through Product Life Cycle. in: the Proceedings of the 13th CIRP Conference on Life Cycle Engineering. May 31–June 2, 2006. Leuven, Belgium.

[19]

Ohkubo, M., Suzuki, K. and Kinoshita, S. (2005): RFID Privacy Issues and Technical Challenges, in: Communications of the ACM, Vol. 44, No. 9, pp. 66–71.

6

CONCLUSION

We are developing a part agent system comprising network agents and RFID chips, and it manages individual parts throughout their lifecycles. Its development has been carried out combining two ways: prototype implementation of part agents and the simulation of the behaviors of parts and part agents throughout their lifecycle. In this paper, we implemented functions of the part agent, for the support in the use phase of a product lifecycle. The developed functions are; 

Warning consumers about excessive use for the control of environmental load;



Replacement of parts in accordance with user preference and resolution of the conflicts in acquisition of used parts;



Prediction of HDD failures using SMART and support for maintenance of products, that enables smooth repairs by making reservations for spare parts as soon as failures are predicted. Simulation results regarding these implementation functions showed that these functions improve TPI, control environmental load, and reduce lead times.

ACKNOWLEDGMENTS

This research is partly funded by Grants-in-Aid for Scientific Research, the Ministry of Education, Culture, Sports, Science and Technology, Japan. 8

REFERENCES

[1]

Hauschild, M., Jeswiet, J. and Alting, L. (2005): From Life Cycle Assessment to Sustainable Production: Status and Perspectives, in: Annals of CIRP, Vol. 54, No. 2, pp. 535– 555.

[2]

Sakai, K. (2007): Ricoh’s Approach to Product Life Cycle Management and Technology Development, in: the Proceedings of the 14th CIRP Conference on Life Cycle Engineering. June 11–13, 2007. Tokyo, Japan.

[3]

Borriello, G. (2005): RFID: Tagging the World, Communications of the ACM, Vol. 44, No. 9, pp. 34–37.

[4]

Suzuki, M., Sakaguchi, K. and Hiraoka, H. (2001): Life Cycle Support of Mechanical Product Using Network Agent, in: Inasaki, I. (ed.), Initiatives of Precision Engineering at the Beginning of a Millennium, (pp. 912–916), Kluwer Academic Publishers.

[5]

Hiraoka, H. and Iwanami, N. (2005): Network Agent’s Advice for Promoting the Reuse of Mechanical Parts, in: the Proceedings of EcoDesign 2005. December 12–14, 2005. Tokyo, Japan.

[6]

Fukuda, N., Hiraoka, H. and Ihara, T. (2006): Supporting the Reuse of Parts Based on Operation Histories of Products and

in:

Systematic Categorization of Reuse and Identification of Issues in Reuse Management in the Closed Loop Manufacturing Takako Sakai, Shozo Takata Department of Industrial and Management Systems Engineering, Waseda University, Tokyo, Japan

Abstract For reducing environmental loads induced by the manufacturing industry, reuse of manufactured products is an important measure. To obtain the maximum benefits of reuse, however, we have to understand the mechanisms of reuse and select the correct reuse type according to product characteristics. For this purpose, we propose a systematic categorization of reuse types and identify issues regarding reuse implementation in this study. We also investigate two typical issues that arise: determining the sales period of the reconditioned product and the order and stock management for the reconditioning process, taking copying machines as our example. Keywords: Reuse; Closed Loop Manufacturing; Operation Management

1

INTRODUCTION

Recently, there has been growing concern regarding environmental problems. The manufacturing industry should greatly consider reduction of the environmental load created by the entire life cycle of the products that are manufactured and delivered to the users. There are several life cycle options such as “reduce,” “reuse,” and “recycle,” which are means of reducing the environmental load. In particular, reuse is one of the most efficient options. It is effective for reducing material consumption and waste by using the products or parts for multiple life cycles while providing the required functions to the users. Besides, the environmental load resulting from material circulation is usually smaller than that from recycling. This is because used products or parts are disassembled into parts or module levels in reuse, whereas they are disassembled to the material level in recycling. Therefore, promoting reuse is of importance in making manufacturing systems sustainable. However, there are not many cases in which reuse is implemented effectively in real-world situations. In product reuse, for example, returned products have to be passed on to other users who have different requirements from those of the original users. Therefore, the matching of supply and demand in terms of timing, quality, and volume is more difficult than that in selling virgin products. This occasionally causes an imbalance between supply and demand. For this reason, we need to control the circulation of products or parts, rather than placing this responsibility in the users’ hands, to achieve effective reuse. When discussing methods of circulation control for product or part reuse, it is essential to understand mechanisms for reducing environmental load through reuse, and the variations in these reuse types. The primary focus of this paper is on categorizing reuse and identifying the issues related to each type of reuse. We adopt several criteria such as objects to be reused, means of product collection, required functionality, and end-of-life treatment. We identify the issues of supply and demand balance and uncertainty in volume and quality of returned products and investigate the influence of these issues on each type of reuse. This analysis will indicate the correct strategy for implementing reuse based on their

characteristics. In section 2, we discuss the mechanisms of reuse, as well as the categorization of reuse types in terms of several criteria. We also discuss control issues in managing each type of reuse operation. In section 3, we investigate two issues identified in section 2. We discuss timing and volume fluctuation in selling reused products. 2 2.1

CATEGORIZATION OF REUSE Definition and categorization

In recent years, many people have been disposing of products at the end of their functional life, although the products have remaining physical lifetimes. We define “product reuse” as sharing products among multiple users, and “part reuse” as sharing parts among multiple products for effective utilization. There are two mechanisms in reuse: one is of the time-sharing type and the other is of the pass-on type. Time-sharing reuse is applicable only to product reuse; this type enables a single product to provide functions to multiple users during one usage. On the other hand, pass-on reuse can improve the usage rate of a product’s physical lifetime. In time-sharing reuse, a product can be shared by multiple users due to the difference in usage periods among users. As depicted in Figure 1, user A and user B drive a car in different time periods. For example, user A drives a car on weekdays, whereas user B uses a car only on weekends. In such a case, the total number of cars is reduced to one (from two) by having one car shared between users A and B. On the other hand, in pass-on reuse, the residual physical life of a product or part is subsequently used by another user or in another product. In the case of product reuse, it is realized due to the difference in requirements or amount of usage among users in the case of the product reuse. In the case of part reuse, this is realized due to the difference in lifetimes between the product and its component parts. An example of pass-on reuse is illustrated in Figure 2. The figure shows physical and functional degradation versus usage time. We assume that functional degradation is

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_73, © Springer-Verlag Berlin Heidelberg 2011

425

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End of Life Management - Reuse and Remanufacturing

user A user B Sharing time

Physical degradation

Physical level

100%

Functional degradation

100% Required level of user A Required level of user B

Functional level

Figure 1: Mechanism for reuse of time-sharing type.

user A user B Figure 2: Mechanism for reuse of pass-on type. proportional to usage time regardless of the users, while physical degradation depends on the amount of use by the users. Additionally, the functional levels required by different users are frequently different. When the functional level falls lower than the level required by user A, user A stops using the product. At this time, there is still physical life time remaining and the functional level is higher than that required by user B. Therefore, the product can be reused by user B. This can increase the utilization rate of the product lifetime. In pass-on reuse, the residual physical life at the time of disposal by the first user is subsequently utilized by another user. In case of part reuse, if used parts have enough residual life when the products are collected (at the end of either physical or functional life), they are disassembled and assembled into other products so as to fully exhaust their lives. It should be noted that only pass-on reuse is considered reuse in many cases, although both time-sharing and pass-on types are technically reuse, in the sense of sharing the life of the product or part among multiple users or products. Reuse is characterized mainly by the objects to be reused, the means of product collection, the required functionality, and end of life treatment. Object to be reused There are two kinds of objects to be reused: product and part. A product is reused by other users, whereas a part is reused in other products. A part may describe a module or unit in this case. Means of product collection Products are usually collected when users stop using them at their convenience. We call this case spontaneous collection. In addition to spontaneous collection, there is planned collection. In the case of spontaneous collection, products are usually owned by users, whereas in the case of planned collection, they are owned by providers. In the latter case, providers are able to control the product collection because the provider has the authority to manage the products. A provider can set the criteria for collecting the products, such as having a rental period and an amount used for executing planned collection. Planned collection is exemplified by mat and mop rental services. Takata et al. suggest reuse planning through planned collection to allow effective product utilization, taking copying machines as their example [1]. Required functionality In the case of part reuse, there are two categories with regard to the types of products in which the parts are reused. When the part is reused in the same product type, reused parts are required to have the same functional characteristics as those required in the previous products. We call this first case “providing the same

function.” An illustrative example is a long-life part reused for producing a new copying machine. This category is further divided into three subcategories: part reuse for manufacturing new products, part reuse for remanufacturing the same products, and part reuse as spare parts. They differ in their required quality levels. In part reuse for manufacturing new products, the quality level that a reused part should meet is the same as the quality standard for new products. In the second category, reused parts are used for remanufactured products that predominantly consist of reused parts. The reused parts should meet the quality standard of remanufactured products, which is different from that of new products. In the third category, the reused parts are used as spare parts for maintenance purposes. In this case, the reused parts should meet yet another quality requirement. The second category involves reusing parts in different product types. In this case, the function of parts remains the same, but the required functional characteristics are different. One example is the lithium-ion battery for electric vehicles reused as an energy storage system in a photovoltaic power generation plant. In this case, the battery provides the same function of providing electric power whether it is used for the electric vehicles or the energy storage system. However, required functional characteristics are different. In this sense, this category corresponds to providing different function. In the case of product reuse, the functional characteristics of the reused product are the same as those of the original product, although there may be differences in required quality levels in some criteria among users. Therefore, these products only provide the same function in product reuse. End of life treatment There are three levels for end-of-life treatment in the case of product reuse. This categorization can be applied to modules or units that are sold individually. The difference is in the levels of work content, warranty, and quality, as shown in Figure 3 [2]. The first level is called cleanup. In this case, the collected products are refurbished and repaired as necessary. They are normally sold second hand and without a warranty. According to these conditions, the quality level is rather low relative to that of new products. An example of this method is a used car. The next level is called reconditioning. In this level, the collected products are disassembled into their component parts, and the quality of the parts is checked. Faults are repaired using reused parts that are extracted from other collected products; otherwise, they are replaced by new parts. Thereafter, the products are reassembled. The reconditioned product is warranted, but its assured quality level is not equivalent to that of a new product. Examples of this are reconditioned copying machines and refresh PCs. Last, remanufacturing is similar to reconditioning in terms of work content. The collected products are disassembled into modules or parts. The parts are checked, and those that meet the required quality levels are supplied to the production line for remanufacture. That is, unlike reconditioning, parts from one product are not necessarily reassembled into a single product. The remanufactured product is also warranted and its assured quality level is almost Work content

Quality

Remanufacturing Reconditioning Cleanup

Warranty

Figure 3: Levels of end of life treatment [2].

End of Life Management - Reuse and Remanufacturing

427

Mechanisms of sharing product

Object to be reused

Means of product collection

Required functionality

Examples (End of life treatment)

Time-sharing

Product

Planned collection

Providing the same function

Car sharing, Rental service (Cleanup)

Spontaneous collection

Providing the same function

Used car (Cleanup), Reconditioned copying machine, Refresh PC (Reconditioning)

Planned collection

Providing the same function

Mop and mat rental service, Copying machine (Cleanup)

Product Pass-on

Providing the same function - For producing new products Spontaneous collection Part

Planned collection

Long life modules of copying machine, Toner cartridge (Reconditioning)

- For producing remanufactured products

Single-use camera (Remanufacturing)

- As spare parts

Used part of cars (Cleanup)

Providing different functions

Lithium-ion battery, Car engine to motorboat, LCD panel (Cleanup)

Providing the same function

Tire rotation (Cleanup), Photo conductor drum unit (Reconditioning)

Figure 4: Categorization of reuse.

All classifications are summarized in Figure 4. Only product reuse within the time-sharing mechanism has been illustrated. Additionally, this classification is limited to the product reuse of the planned collection type, providing the same function, and cleanup type. This is understandable from the fact that all users require the same function in the time-sharing type, since multiple people share the same product at different times in the same time period. Regarding means of product collection, products in the reuse type are owned by providers and are collected in a planned manner. When the products are collected, they are just cleaned up. In this way, there are not many variations within time-sharing reuse. On the other hand, there is more variety in our categorization scheme in the case of the pass-on type. Thus, we focus our discussion on this type. 2.2

Conditions for reuse applications

In this section, we discuss the factors to be considered in implementing reuse options to reduce environmental load in manufacturing. Umeda et al. discuss the conditions of reuse applications using the following four factors, lifetime, costs, value, and quality, and balance the supply and demand of reusables [3]. Regarding lifetime, the residual life of the product or part needs to be longer than the guaranteed life for the next use. In order to implement reuse from an economical perspective, the cost of reuse has to be less than the sum of the cost of producing new products or parts and that of recycling where reuse is not implemented. Regarding value and quality, the remaining value and quality need to satisfy the requirements for the next use. With respect to the last point, they propose the marginal reuse rate. Figure 5 shows changes in production volume and disposal volume for a particular product model after the beginning of sales. If we implement reuse such that parts from collected products are reused in the products being processed, only the shaded area can be reused. Marginal reuse rate is defined as the ratio between the number of reusable

products and the total number of products manufactured during its sales period [3]. Matsumoto has also addressed the factors that affect the reuse business [4]. In Matsumoto’s study, eight factors are identified. In particular, four of them are recognized as prerequisites for conducting reuse businesses. These factors are product property, collectability of used products, cost benefit, and consumer preference. These four correspond to the four factors described by Umeda et al. Product property implies reusability of products in terms of technological innovation and physical deterioration. Therefore, this factor is mainly related to lifetime. Collectability of used products represents the controllability of product return. Therefore, it corresponds to the balance between supply and demand of reusables. Cost benefit directly corresponds to the costs. Finally, consumer preference is relevant to value and quality. This is because whether consumers have a positive or negative attitude to the products is determined by the value provided by the reused product. In summary, the essential factors to be taken into consideration in reuse implementation are lifetime, costs, value and quality, and the supply and demand balance. As described above, these four factors are reflected in the conditions of reuse implementation. They are also related to the means of implementing reuse. Therefore, the categorization represented in the previous section can be related to these four factors. Means of product collection connects to the supply and demand balance. If the means of product collection is spontaneous collection, the disposal volume increases slowly after the beginning of sales. Therefore, the marginal reuse rate cannot be large, as

Production distribution

quantity

equivalent to that of a new product. Thus, the quality of a remanufactured product is higher than that of reconditioned or cleaned-up products. An example of this is a single-use camera.

Disposal distribution

Figure 5: Marginal reuse rate [3].

time

428

End of Life Management - Reuse and Remanufacturing

shown in Figure 5. However, in the case of planned collection, products can be collected in a known period of time, so as to increase the marginal reuse rate. Planned collection is also effective for collecting those products or parts with enough residual life left for reuse. The category of required functionality is associated with value. In the case of providing the same function, the reused parts are used to provide the same function and to meet the same requirements. On the other hand, if the reused parts are used to provide different functions, then they are used according to the different requirements. Lastly, the end-of-life treatment is related to costs, value, and lifetime. The end-of-life treatment should be selected according to acceptable costs, required value, and the condition of the collected product. 2.3

Critical issues of reuse implementation

Difficulty in implementing reuse is caused by various issues related to the abovementioned factors. The most difficult factor among them is the supply and demand balance because it is usually out of the control of the providers. The demands for the reused products or parts depend on the market. Product return is also at the users’ discretion once the products have been sold to users. In addition to the imbalance between supply and demand, there is uncertainty in estimating volume and quality of returned products that are also out of the control of the providers. Therefore, dealing with these issues is essential for implementing reuse. We next see these two issues from the perspective of reuse categorization. When objects are to be reused with the requirement of providing the same functionality and with the means of product collection being spontaneous collection, the supply and demand imbalance could create serious problems. Collected products that serve as candidates for reuse may be outdated compared to the products on sale. In such a situation, reused products have to be sold while considering their relation to new products. With regard to this problem, there is an issue of setting an appropriate sales period or price. Few concrete discussions have been conducted so far regarding this issue. Uncertainty affects the production volume of new products or parts when it is assumed that the reused products or parts and new products or parts are regarded as having the same value in the marketplace. In such a situation, many studies have focused on decisions regarding production volume and production policy to optimize costs by modeling uncertainty in the quantity of collected products [5], [6]. Planned collection is one measure for correcting the supply and demand imbalance. In this type of reuse, however, it is necessary to control the timing of planned collection and to establish rules for product reallocation. For this purpose, appropriate criteria for product collection should be addressed, including the amount of usage or the total period of usage. Takata et al. have discussed these issues taking a copying machine as an example [1]. In the case that the object is to be reused as parts and the means of product collection is spontaneous, studies have been conducted for increasing the marginal reuse rate by adopting common parts over multiple product generations or by introducing spare part reuse for manufacturing new products [7]. With respect to uncertainty, there are many studies on procurement policies for newly manufactured parts considering the use of reused parts with uncertainty included [8]. In the case of planned collection, the supply and demand imbalance may be avoided, but the criteria for product collection should be addressed, as in the case of product reuse.

3 3.1

REUSE MANAGEMENT FOR RECONDITIONED PRODUCTS Issues in reuse management of reconditioned copying machines

As we stated in the previous section, the supply and demand imbalance and uncertainty in volume of collected products are the most important issues in reuse. In the following, we discuss these issues in terms of the object to be reused (product), required functionality (same functionality), means of products collection (spontaneous collection), and end-of-life treatment (reconditioning). This is one of the most common practical cases within reuse categorization in the current market. With regard to the issue of supply and demand matching, we take the example of reconditioned copying machines and show how to determine their optimal sales period so as to maximize potential sales volume assuming that product models are changed at regular intervals. With respect to the uncertainty problem, we discuss an inventory management strategy for collected products to decrease the out-ofstock rate for the reconditioned products based on demand and supply forecasts from an autoregressive model 3.2

Determining optimal sales period for reconditioned products

Usually, each new model of copy machine is sold within a period of two years. Using this condition, we want to determine the sales period for the corresponding reconditioned machine to maximize its sales volume assuming that the reconditioned model is put into the market several years later than the end of sales of the new machine and is sold for two years. We call the new machines that are later reconditioned as “base machines.” There are two major factors affecting the potential sales volume of the reused product. From the supply side, one key factor is the ratio of the recoverable quantity to the collected quantity. On the demand side, we need to take product obsolescence into consideration. Considering these two factors, we set the following two conditions for determining the sales period. 

The usage period of the base machine shall be less than four years, as excessive usage periods decrease the recoverability of the collected machines.



The sales period shall be before that of the fourth generation product model from the base model, since it can be assumed that large technological improvements occur with every third model.

Under these conditions, we calculate potential sales volume by changing the sales start point for the reconditioned product. In this case, the latest sales start point is 48 months after that of the base machine, according to the abovementioned second condition. We use a life cycle simulation (LCS) for this purpose, as we need to conduct a calculation taking the circulation of each product into account. Based on the sales of the base machine, which is estimated from real sales data, the simulation provides the collected product quantity. The amount of recoverable products among them is then calculated with the criterion that the collected products are used for less than four years [9]. The results are shown in Figure 6. On the other hand, we set the demand for reconditioned machines assuming that the total demand for the reconditioned product is 25% of the total demand for the base product. We assume that the demand for the reconditioned machines is filled each month by the machines reconditioned during the previous month. We conduct LCS under the condition above with a calculation cycle of one month by shifting the start point of sales, and calculate the potential sales amount for reconditioned products as shown in Figure 7. The figure shows that the largest amount of potential sales can be obtained when the sales of the reconditioned products start 42 months after the release of the base product.

End of Life Management - Reuse and Remanufacturing

2500

quantity

2000 1500

Sales quantity of base product

1000

Product return

500

Recoverable product quantity

0 0

12

24

36

48

60

72 [month]

Figure 6: Change in products sales and returns. 10000

quantity

8000 6000 4000 2000 0 0

42 48 [month] start point of reconditioned products sales 12

24

36

Figure 7: Change in potential sales. 3.3

Inventory management of collected products in the reconditioning process

Results from the LCS show approximately 10% stock-out relative to the total demand during the 2 years sales period, even if we began to sell them at the optimum time. This is because there are fluctuations in returns, as well as in demand. Therefore, the collected product quantity cannot satisfy demand at certain points in time. To solve this problem, the collected product is set aside to meet future demand based on the demand and supply forecast.

429 of recoverable products. The rest are reused for parts or disposed of. At the reconditioning point, transferred products are first stored in an inventory of recoverable products. Then, the number of products ordered from the sales point are reconditioned using the stored products and are shipped to the sales point. Thus, depending on the quantity in the recovered inventory, both opportunity loss and excess inventory can occur. Therefore, we need to establish the ordering policy between the reconditioning point and the collection point. The ordering policy, in which the predictive quantity is not taken into consideration, is represented by formulae (1) and (2). We assume backlogging of inventory for unsatisfied demand is not permitted. The nomenclature is summarized in Table 1.

Ot  Dˆ t 1  I t  st

(1)

I t  I t 1  min(Rt 1 , Ot 1 )  Ft

(2)

On the other hand, when the predicted values of demand and collected products are available, the amount for an order is determined considering not only current demand but also future demand. When the prediction indicates that future demand exceeds the number of the recoverable products obtained from the collected products in that term, the estimated deficiency is ordered in advance and stored in the inventory of the recoverable products. The period of inventory holding is required to be as short as possible so as to minimize holding costs. For this reason, the additional order to compensate for future deficiency starts at the latest possible point in time such that the accumulated excess of collected products is equal to the deficiency expected within the prediction period. The prediction of demand and collection usually have errors. During the period when the excess amount of collected products is saved as stock, the order at each term is adjusted so as to compensate for the difference between actual stock and planned stock.

Sale

Market

Rt

Methods of forecasting We first explain the forecast method for collected product quantity. As there is a period of 42 months between the release of the base machines and the start of sales of the reconditioned machines, it is possible to gather enough data about the fluctuation in collected products before starting the sale of reconditioned products. We therefore adopt an autoregressive model for forecasting the amount of collected products. Since the changes in the amount of collected products have a trend and seasonal variations, as shown in Figure 6, we first remove these components and then apply an autoregressive model with twelve degrees. Secondly, we explain the forecast method for demand. Unlike collected product quantity, we could not obtain enough sales data regarding each model of reconditioned machine, due to the limitations of the sales period. Therefore, we estimate the demand considering only seasonal variations, which are extracted from the sales data of the reconditioned machines of previous models. Order and stock management of reconditioned products We assume the situation illustrated in Figure 8 in considering order and stock management of reconditioned products. At the collection point, used products are stored and are later transferred to the reconditioning point, according to the order quantity at the reconditioning point at the end of each term. The products shipped from the collection point are limited by the number

Collection point

Reconditioning point

Ft

Reconditioning Process

Recoverable product inventory

Dt

Collected product inventory

Ot

Part reuse, Disposal Figure 8: Reuse process model of reconditioned products.

Ot

: Order quantities of collected products at time t

Dt

: Demand for reconditioned products at time t

I t : Inventory quantities in the recoverable inventory at the end of time t

st : Safety inventory at time t Rt : Returns at time t Ft : Inputs of recoverable products to the reconditioning process at time t

Table 1: Nomenclature.

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End of Life Management - Reuse and Remanufacturing

Results We apply the above method to copying machines using the same data as used in the previous section. We investigate the change in the stock-out quantities and cumulative inventory quantities of reconditioned products when the prediction period is changed from 0 to 6 months. Regarding the stock-out quantities, the results are shown in Figure 9. We do not attempt to measure compensation for future deficiency when the prediction period is equal to 0 months. In this case, the quantity of stock-out is over 1300. Quantities significantly decrease as the prediction period extends from 0 to 3 months. However, the quantities remain stable at approximately 880 from 3 to 6 months. The reason for this trend is that the cycle of shifts between the deficiency period and the excess period is approximately 3 months. The results regarding the change in the cumulative inventory are shown in Figure 10. The quantities increase gradually as the prediction period increases up to 3 months. This is consistent with the results regarding the stock-out quantities shown in Figure 9. However, the cumulative amount of inventory when the prediction period is 5 or 6 months is larger than that when the prediction period is 3 months, although the values of stock-out quantities are almost equal when the prediction periods are 3, 5, or 6 months. This derives from cumulative prediction error, as prediction over longer terms tends to have more error. Therefore, the prediction period should be as short as possible, so long as it can cover the cycle of shifts between the deficiency period and the excess period. 4

CONCLUSION

Stock-out quantity

This paper presented a systematic categorization of reuse. We first described the principles of reuse for increasing usage efficiency for both products and parts. We categorize reuse in terms of the object to be reused, means of product collection, required functionality, and end-of-life treatment. Thereafter, the issues associated with each category are identified. The results show some of the potential research issues in the area of reuse management.

1400 1300 1200 1100 1000 900 800 700 600 0

1

2

3 4 5 6 Prediction period [month]

Cumulative inventory quantity

Figure 9: Stock-out quantity against prediction period.

2500 2000 1500 1000 500 0 0

1

2

3 4 5 6 Prediction period [month]

Figure 10: Cumulative inventory against prediction period.

We investigated two typical issues: the method of determining the sales period for a reconditioned product, and order and stock management methods in the reconditioning process. The former method can increase the total sales of reconditioned products, and the latter method can improve the out-of-stock rate. In the latter case, however, the current method does not consider economic aspects. In future work, we need to balance opportunity loss and inventory holding costs taking both environmental and economic aspects into consideration. 5

REFERENCES

[1]

S. Takata, K. Tsubouchi, (2009): Maximizing utilization rate of office automation equipment by intraoffice circulation, in: CIRP Annals - Manufacturing Technology, Vol. 58, pp. 33–36.

[2]

Winifred L. Ijomah, Christopher A. McMahon, Geoffrey P. Hammond, Stephen T. Newman, (2007): Development of design for remanufacturing guidelines to support sustainable manufacturing, in : Robotics and Computer-Integrated Manufacturing, Vol. 23, pp. 712–719.

[3]

Yasushi Umeda, Shinsuke Kondoh, Takashi Sugino, Hiroyuki Yoshikawa, (2006): Analysis of Reusability using ‘Marginal Reuse Rate’, in: CIRP Annals - Manufacturing Technology, Vol. 55, pp. 41–44.

[4]

Mitsutaka Matsumoto, (2010): Development of a simulation model for reuse businesses and case studies in Japan, in: Journal of Cleaner Production, Vol. 18, pp. 1284–1299.

[5]

G. P. Kiesmüller, (2003): A new approach for controlling a hybrid stochastic manufacturing/remanufacturing system with inventories and different leadtimes, in: European Journal of Operational Research, Vol. 147, pp. 62–71.

[6]

Moritz Fleischmann, Roelof Kuik, Rommert Dekker, (2002): Controlling inventories with stochastic item returns: A basic model, in: European Journal of Operational Research, Vol. 138, pp. 63–75.

[7]

Marcus Schroter, Thomas Spengler, (2004): Designing control management systems for parts recovery and spare parts management in the final phase within closed-loop supply chains, in: International Journal of Integrated Supply Management, Vol. 1, pp.158–179.

[8]

Samar K. Mukhopadhyay, Huafan Ma, (2009): Joint procurement and production decisions in remanufacturing under quality and demand uncertainty, in: International Journal of Production Economics, Vol. 120, pp. 5–17.

[9]

S. Takata, M. Watanabe, Y. Ohbayashi, (2006): Collection Rate Estimation Model in Closed-Loop Manufacturing, in: Proc. of 13th CIRP-LCE, Vol. 2, pp. 601–605.

Approach for Integration of Sustainability Aspects into Innovation Processes 1

1

1

Semih Severengiz , Pia Gausemeier , Günther Seliger, Fernando Augusto Pereira 1

2

Institute of Machine Tools and Factory Management, Technische Universität Berlin, Berlin, Germany 2

Universidade Federal de Santa Catarina, Florianópolis, Brazil

Abstract The growing awareness for sustainable products and production is changing the business environment, forcing companies to revise the way they think about products, technologies, processes, and business models. The contribution of technical innovations to sustainable development needs to be systematically examined in the early stages of product development. The development of a systematic approach, which integrates sustainability aspects in the product development, is necessary. Scenario-technique offers an adequate method for catalyzing innovation processes towards sustainable development. This paper introduces a case, which illustrates how an analysis of remanufacturing technologies, using scenario-technique, can help to identify drivers for sustainability. Keywords: Sustainability; Innovation Process; Remanufacturing Scenarios

1

INTRODUCTION

The acceleration over the past decades in demand for natural resources has reached a point where it is now considered to be a serious threat to the functioning of economies and societies. If the lifestyle of rapidly advancing nations becomes shaped by the predominant technologies of the industrialized countries, the global resource consumption will exceed every ecologically, economically and socially responsible level [1]. This is associated with environmental problems such as biodiversity loss, climate change, desertification and ecosystem degradation [2], [3]. It also affects a fair wealth distribution economically, and the needs of future generations socially.

knowledge on sustainability impact of the product idea

Human creative imagination combined with knowledge, experience and skills provides for continuous change in living conditions. Mankind’s survival on our globe is dependent on how we handle the challenges of ever increasing global population and ecological threat [4]. A study on sustainability and innovation among German CEOs revealed that already today the majority of interviewees consider social and environmental challenges as the motor for product innovations and new business models. In this survey, 86% of the interviewed managers stated that/regard developments that enable sustainable economic activity as having a significant impact on their company‘s strategy. In the long run, 90% regard social and environmental risks as chances for the company as they envisage business growth and competitive advantages from sustainable products and business models [5]. Especially, early innovation stages have a great impact on sustainability aspects of products [6]. Figure 1 shows the relation between knowledge and influence on sustainability in the early stages.

orientation

influence on the sustainability impact of the product idea

idea generation

idea selection

idea realization

Figure 1: Knowledge and influence on sustainability [6]. 2 2.1

STATE-OF-THE-ART Innovation

Innovation comes from Latin “innovare” standing for renew. So etymologically it is not something totally new but rather a new mode of something already existing. In 1912 the economist Schumpeter defined innovation as “establishing new combinations” [7]. He distinguished between product and process innovation. Modern management literature defines innovation as combining technological invention and economic exploitation [8]. CIRP Unified Terminology on Design defines innovation as the process of taking an invention forward into the first marketable product [9]. Invention covers all efforts aimed at creating new ideas and getting them to work. Exploitation includes all stages of commercial development, application, and transfer, including the focussing of ideas or inventions towards specific objectives, evaluating those objectives, downstream transfer of research and development results, and the even-

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_74, © Springer-Verlag Berlin Heidelberg 2011

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End of Life Management - Reuse and Remanufacturing

tual broad-based utilization, dissemination, and diffusion of the technology-based outcomes. The famous economist Adam Smith once stated that the division of labor is limited by the size of the market [10]. Due to ever increasing market sizes by international trading and globalization the division of labor has been developed continuously. But not only economic market exploitation also exponential knowledge increase and resulting technological inventions have stimulated the division of labor in arts and sciences. On the other hand reintegration of arts, sciences and engineering by modern knowledge processing and communication can enhance innovation potentials in cross disciplinary cooperation. 2.2

Remanufacturing

Closed-loop economy systems are a cost and eco-efficient architecture to all actions aiming at avoidance, reduction, reuse and utilization of old products, materials and the disposal of waste. One element of an overall product life cycle strategy or product recovery operation that can aid in achieving this goal and close the supply loop is product remanufacturing [11] [12]. Product recovery activities further include used-product acquisition, reverse logistics, product disposition (sort, test and grade), remanufacturing/ repair, and remarketing [13]. Remanufacturing can be defined as the process in which a recovered good, or core, is transformed through cleaning, testing, and other operations into a product that is tested and certified to meet technical and/or safety specifications and has a warranty similar to that of a new product [14]. Parkinson defines remanufacturing as reprocessing used products in such a manner that the quality of the products is as good as or better than the new one in terms of appearance, reliability and performance [15]. 2.3

Scenario Technique

The term scenario, within the area of future research, was coined by Khan et al. in the 1960s. Their study “The Year 2000: A Framework for Speculations on the next Thirty-Three Years” is considered to be the driver for today’s scenario technique [16]. As stated by Börjeson et al., scenarios can be classified into three different types: predictive, explorative, and normative scenarios (see Figure 2) [17]. Scenarios

Predictive

Forecasts

What-if

Explorative

External

Strategic

Normative

Preserving Transforming

Figure 2: Classification of scenarios [17]. According to Gausemeier et al., scenario creation builds on two main principles. Firstly, system thinking describes the environment of enterprises, stating that it must be perceived as a complex network of influence factors, which may influence each other. Secondly, influence factors may have different projections for the future. Thus, taking different projections of influence factors into account, different multiple futures can be considered [18] [19]. Scenarios are defined as a generally intelligible description of a possible situation in the future, based on a complex network of influence factors [18]. This scenario technique approach can be classified to the category of exploratory scenarios. It consists of five phases: scenario preparation, scenario field analysis, scenario prognostic, scenario development and scenario transfer. This approach has been adapted towards the usage of sustainability influence factors and then been used for scenario creation.

3 3.1

APPROACH Idea

The question of whether sustainability requirements foster the development and diffusion of innovations is currently discussed as controversially as the question whether, and to what extent, innovations can contribute to sustainable development. The idea of the paper shows two views on this: 1. The worsening environmental quality increases the pressure for innovation. Threat scenario: If we do not act in a sustainable manner, the very basis of our existence is threatened. 2. The principle of sustainable development is the creative director and source for competitive advantages. Chance scenario: If we act in a sustainable manner, we better unlock competitive advantages. Both theses clearly show that the environmental and social dimensions of sustainability actually constitute no potential barriers to innovation, but that in economic terms they are in fact a rational necessity. The old concept, which basically constitutes of the so called magic triangle between costs, time and quality, no longer fulfills the more demanding requirements of future products. Sustainability requirements may have an inhibitory effect on individual innovation processes. Generally, however, they constitute no substantial barriers to innovation, if one succeeds in capitalizing on the business chances that in turn arise from these sustainability requirements. Such a concept thus leaves little room for a truly differentiated discussion of the relationship between innovation and sustainability. The approach is based on sustainability as chance and risk scenarios. Such a conception helps in taking advantage of the dynamics of global competition in order to foster the rationally given sustainability of our global living environment by means of technological innovations. Areas of demand must hence be quickly identified – sustainability as incitement – and a consistent integration of sustainability requirements both within product concepts and within the later phases of development has to be assured – sustainability as orientation. Sustainability is not only a key driver for innovation and an important strategy for competition, but at the same time ecological, economical and social criteria to navigate innovation processes for sustainable development must be considered as well. The threat scenario that results from a non-sustainable development, e.g. environmental collapse leads to economic demise which in turn results in social upheavals, requires a rethinking. This rethinking affects both the supply and the demand for products and services. In order to meet the requirements of the three sustainability dimensions, sustainability has to be seen as the very basis of orientation in innovation processes. For the development of products this means that environmental and social product requirements have to be considered in the operational set up. Sustainability has to serve as a point of orientation for the management of innovation projects and hence be the basis for decision processes and selection procedures. The chance scenario of sustainable development extends the conception of innovation and sustainability. The growing world population and the increasing environmental threat are regarded as incitements for the solving of tasks in the chance scenario, which suppliers and users of product and services have to meet with own initiatives. The sustainability task leads to the development of initiative and has a stimulating effect on creativity in the search for solutions. The widening of the spectrum for solutions enables developments that preserve resources, foster qualification, are competitive and more equitable through sustainable innovations. Sustainability as incitement also supports the identification of search and demand

End of Life Management - Reuse and Remanufacturing areas and to reveal the competitive advantages of sustainable solutions. 3.2

Concept

The innovation process model of Herstatt/Verworn was adapted for the suggested approach [20]. Furthermore, the idea of the stagegate-model of Cooper was integrated in the approach [21]. Figure 3 depicts the conceptual overview of the planned approach. The dynamics of global competition shall be used to model the relationship between humans and their global realm of life with technical innovation processes along the principles of sustainability. Collaboration between actors contributes to the opening up of sustainability potentials. The process is divided into five innovation phases, i.e.: ideas generation (phase I), concept development and

433 product planning (phase II), research and development (phase III), building of prototypes and pilot testing/ application (phase IV), and production and market launch (phase V). The focus here is on the early phases of the innovation process (phase I and phase II). In these, sustainability is on the one hand used as catalyst for ideas generation, and on the other hand it serves as the basis for product innovations. The assessment of the different sustainability contributions of the phases takes place in the respective gates. These are the selection of ideas while safeguarding the contribution to sustainability (Gate 1), ensuring the competitiveness (Gate 2), the verification of the achievements from research and development (Gate 3), the testing phase of the prototype and pilot application (Gate 4), and the adherence to the overall target criteria (Gate 5).

Figure 3: Approach for integration of sustainability aspects into innovation processes.

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End of Life Management - Reuse and Remanufacturing

The first phase uses scenario technique to identify sustainability potentials and defines the overarching principles for the idea generation. It addresses the chance scenario: If we act in a sustainable manner, we better unlock competitive advantages. In the second phase, eco design methods/measures are used to manage product concepts, and cooperation potentials are identified through analysis of scenarios. One possible means for the selection is a sustainability compass. In this phase mainly the threat scenario is addressed: If we do not act in a sustainable manner, the very basis of our existence is threatened. The third phase takes sustainability requirements into account, uses synergies and potentials of distributed development, and prepares design reviews for Gate 3, at which the fulfillment of requirements is reviewed and the decision on whether or not to continue the project is taken. Besides, environmental, economic and social targets are defined for later verification. In the fourth phase, the entirety of results from the development phase is combined into a prototype. The determined performance data are compared with the previously set target contributions and are adjusted if necessary. In the fifth phase market launch takes place. The focus here concerns the vertical relationships. The process ends with the adjustment of the planned concept for usage. 4

APPLICATION

The approach is going to be demonstrated through results of a joint Brazilian and German collaborative research project. As mentioned in the introduction section, in particular, early innovation stages have a great impact on sustainability aspects of product innovations. The application is addressing the idea generation of the first stage of approach. To meet the challenges of sustainability, Brazil and Germany established the Brazilian German Collaborative Research Initiative in Manufacturing Technology (BRAGECRIM) in 2008. The goal is to research how production technology can foster sustainable innovation. Within this initiative, the application section presents results of Identification of the systems and components for grinding

the joint research project entitled “Remanufacturing oriented production equipment development”. Remanufacturing scenarios for sustainable value creation are developed, whereby scenario technique helped to structure complex interrelationships between various areas of influence. In the initial phase of the project, field scenarios for the remanufacturing market in Brazilian were developed. In order to identify fields of application out of these consistent illustrations of the surrounding field of remanufacturing in the future, perspective remanufacturing technologies have to be identified, analyzed and combined with perspective market fields. For this purpose, technology scenarios were developed for idea generation and selection, using grinding machines as an example. The technology scenarios illustrate both the processes, necessary for the remanufacturing of grinding machines available on the market, the technologies for the realization of the processes as well as their combination. In the following section the method for the development of the technology scenarios (Figure 4) will be briefly presented in order to exemplarily illustrate two of the resulting scenarios. In the primary phase of the scenario creation, the main, remanufacturing relevant components of grinding machines are identified. A distinction between components and parts which cannot be remanufactured must take place. The necessary remanufacturing processes for the identified components must be determined. The number of indentified processes has then to be reduced to a smaller number of key processes, in order to reduce the complexity. An influence analysis is undergone for this purpose, in which the systemic integration of the processes is identified. Those processes with a significantly large influence on the other processes and which are also strongly influenced by the others are then determined to be the key processes. Eight key processes were identified in this example. Technologies for the realization of these factors, which are either currently in use or are perceived as perspective solutions, were determined in the following stage. Using an evaluation matrix and a branch and bound algorithm, the technologies are grouped to consistent technology combinations. Eight scenarios resulted from this constancy analysis, two of which are described in the following sections.

Identification of required Remanufacturing processes  Disassembly

Influence-Analysis to reduce the processes to the key processes

 Cleaning  … Cleaning Pre-Cleaning •Rough cleaning •Depositions get solved

8 TechnologyScenarios

Main-Cleaning •Removal of small particles •Thoroughly surface cleaning

...

Consistency-Analysis to determine how likely the different technologies are to appear together

Identification of technologies to carry out the key processes  Disassembly  Water-

cutting  …

Figure 4: Approach for gaining technology scenarios for remanufacturing of grinding machines.

End of Life Management - Reuse and Remanufacturing 4.1

Scenario 1: A cost driven attempt

The remanufacturer will perform a low depth separation and recover predominantly cores of high value. In this scenario, the market demand is such, that only such cores have enough value to be recovered. As a result, the disassembly operation has to be performed in a short time and therefore simple processes are chosen. The remanufacturer can unscrew to dismantle connections or separate the single parts by using an angle grinder. Key Process

Technology

1

Disassembly depth

2

Disassembling

A,F

3

Main-Cleaning

C,D

4

Post-Cleaning

A

5

Quality control

6

Updating

7

Surface and material enhancement

8

Part joining

1-8: Key-Processes

A

Low Angle grinding, unscrewing Wire brushing, grinding

435 cleaning process, the core components are cleaned with a grinder that removes remnants. In a next step, the CO  dry ice blasting and laser cleaning are used to prepare the parts for post-cleaning operation. The remanufacturer needs to verify that all components and parts achieve the necessary tolerances and has thus to perform a quality control survey. In the case of scenario 2+3, this will be the laser measurement or the comparison with a reference model. Part reconfiguration will become important for updating the grinding machines’ components and cores. Key Process 1

Flushing Thermal visualization, F,G,H rotation measuring device, acoustic testing CNC update - resource A,B management, part reconfiguration C

Disassembly depth

Scenario 2 C

Detailed

2

Disassembling

G

Thermal treatment

3

Main-Cleaning

B

Dry ice blasting

4

Post-Cleaning

F

Laser cleaning

Grinding and polishing

Plugging together, C,F clinching A-I: Possible Technologies/Solutions

As the latter approach leaves sharp and indefinite edges the following processes cannot be too precise. With a wire brush, chips and other contaminations are removed during the main-cleaning and the cores are prepared for the next step. Brushing also results in an outcome that requires further treatment. Both approaches match the aim of this scenario, e.g. finding a fast and easy way to recover the core components. During the post-cleaning the remanufacturer flushes a solution to eliminate remaining particles. The cores’ functions are still fully available, as they have been recovered as singly separated parts. Additional, less attractive solutions are rotation measuring device, and the acoustic testing method. This form of control allows the remanufacturer to quickly recognize a malfunction of the component. In this scenario, the remanufactured grinding machine will have a large share of new components. The exchange or even loss of some components makes the reconfiguration of some old parts necessary. Another technology that can be applied is the updating of the CNC software to improve the energy consumption and machine efficiency. For the part joining the scenario suggests using either plugs that establish a connection between the single components or to clinching. Scenario 1 describes a highly time and therefore cost driven approach to remanufacturing. The remanufacturer has mainly to focus on the valuable core components. Since the main determinants are cost and time, these forces decide what kind of components can be reused and in what way they are to be remanufactured. Due to these factors, small and cheap parts will most likely not be remanufactured, but rather be recycled. Scenario 2+3: A high tech solution

Due to the high concurrency of scenario 2 and scenario 3 - eight out of nine processes have the same solutions the combination of these scenarios is therefore beneficial. Both scenarios are based on a detailed disassembly depth. This means that the remanufacturer should execute a disassembly method, which will not cause damage to the cores. Therefore scenario 2+3 suggests firstly solving all possible form-locked joining fasteners and secondly applying a thermal treatment that removes adhesive bonds. During the main-

Laser measurement, A,B visual reference model

5

Quality control

6

Updating

B

7

Surface and material enhancement

B

8

Part joining

Table 1: Technology scenario 1 – a cost driven attempt.

4.2

Technology

1-8: Key-Processes

Scenario 3 C

Detailed

Thermal G, treatment, I Interference fit solving Dry ice blasting, B Grinding, Laser cleaning Ultrasonic D cleaning A

Laser measurement

Part reconfiguration

B

Part reconfiguration

Quenching and tempering

B

Quenching and tempering

All solutions equally D Laser welding matched A-I: Possible Technologies/Solutions

Table 2: Technology scenarios 2 and 3 – a high tech solution. The subsequent step, the surface and material enhancement ought to strengthen the surface characteristics. This can be realized by the quenching and tempering, the varnishing with special nano particles or the improvement through grinding and polishing. Finally, the reassembling is performed. Here the scenario shows various possible solutions. Laser welding could be used to reestablish the connections, riveting could be another possible approach. While laser welding advantageous concerning price, quality and scope of applications, the automation needs precise CAD data, which can be difficult to gain. Scenario 2+3 shows a wide spectrum of possible solutions and emphasizes that need to improve the grinding machine’s performance. According to the scenario, this enhancement is implemented by the careful cleaning that allows an easy conversion of the machine tool and the improvement of the grinding machine’s features and costs drivers, e.g. the introduction of minimal lubrication, the stiffness enhancement and the grinding and polishing. 5

CONCLUSION

The approach is based on sustainability as chance and risk scenario. Such a conception helps in taking advantage of the dynamics of global competition in order to foster the rationally given sustainability of the global living environment by means of technological innovations. Areas of demand must hence be quickly identified – sustainability as incitement – and a consistent integration of sustainability requirements both within product concepts and within the later phases of development has to be assured – sustainability as orientation.

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End of Life Management - Reuse and Remanufacturing

An approach for integration of sustainability aspects into innovation processes shows how remanufacturing scenarios for sustainable value creation are developed, whereby scenario technique helped to structure complex interrelationships between various areas of influence. The first phase uses scenario technique to identify sustainability potentials and defines the overarching principles for the idea generation.

[11] Nasr, N., Thurnston, M. (2006): Remanufacturing: A Key Enabler to Sustainable Product Systems. In: Proceedings of the 13th CRIP International Conference on Life Cycle Engineering, Leuven.

The technology scenarios for the remanufacturing of currently available grinding machines include both combinations of existing technologies as well as perspective combinations. Process solution combinations for different levels of technological advance can be recognized in the scenarios as well. The scenarios so provide ideas for remanufacturing based both on current technologies as well as ideas for its realization in the future. Fields of application are then be identified by combining the technology scenarios with perspective market environments. The constancy of the individual technology scenarios with the described environment is checked in order to exploit technological potentials for their useful application.

[13] Guide, V., Van Wassenhove, L. (2009): The evolution of Closed-Loop Supply Chain Research. Operations Research, Vol. 57, No. 1, pp. 10 – 18.

Furthermore, design requirements for grinding machines can be derived from the developed technology scenarios. Although the scenarios are based on grinding machines, which are currently available on the market, inconstancies between particular technology combinations suggest, how grinding machines would have to be designed in the future in order to facilitate remanufacturing.

[16] Kahn, H. et al. (1967): The Year 2000: A Framework for Speculations on the next Thirty-Three Years, Macmillan, New York.

6

ACKNOWLEDGMENTS

The financial support of DFG, CAPES, CNPq and FINEP is highly appreciated. 7 [1]

[2]

REFERENCES Seliger, G. (2007): Nachhaltige industrielle Wertschöpfungsnetze, Tagungsband 12., Produktionstechnisches Kolloquium, PTK 2007. Stern, N. (2006): The Economics of Climate Change, The Stern Review. Cambridge University Press, Cambridge.

[3]

Intergovernmental Panel on Climate Change (2007): Climate Change 2007: The Physical Science, Basis. Summary for Policy Makers, IPCC.

[4]

Seliger, G. (2001): Product Innovation - Industrial Approach: Keynote Paper, in: CIRP Annals - Manufacturing Technology. No. 50-2, pp. 425-443.

[5]

Brands & Values (2010): Sustainability as a driver for innovation. Study No 3 – Sustainovation: Sustainability as catalyst for radical innovation and growth.

[6]

Lang-Koetz, C.; Heubach, D.; Beucker, S. (2006): Abschätzung von Umweltwirkungen in früheren Phasen des Produktinnovationsprozesses, in: Pfriem, R.; Antes, R.; Fichter, K.; Müller, M.; Paech, N.; Seuring, S.; Siebenhüner, B. (Hrsg.): Innovation für eine nachhaltige Entwicklung. Deutscher Universitätsverlag, GWV Fachverlag GmbH, S. 417-432, Wiesbaden.

[7]

Schumpeter, J. A. (1911): Theorie der wirtschaftlichen Entwicklung, Duncker und Humblot, Leipzig.

[8]

Rogers, E. M. (1983): Diffusion of Innovations, Prentice Hall, New York/London.

[9]

Corbett, J. (1994): Unified Terminology on Design, CIRP.

[10] Smith, A. (1904): An Inquiry into the Nature and Causes of the Wealth of Nations, 2 Vols., Everyman’s Library, Dent & Sons, London.

[12] Seitz, M. (2007): A critical assessment of motives for product recovery: the case of engine remanufacturing. Journal of Cleaner Production, Vol. 15, pp. 1147 – 1157.

[14] World Trade Organization (2005): Negotiating Group on Market Access. Market Access for non-agricultural products. Negotiating NTBs Related to Remanufacturing and refurbishing. [15] Parkinson, H., Thompson, G. (2003): Analysis and taxonomy of remanufacturing industry practice, Journal of Process Mechanical Engineering, Vol. 217 (E3), pp. 243.

[17] Börjeson, L. et al. (2006): Scenario types and techniques: Towards a user’s guide. Futures, Vol. 38, pp. 723 – 739. [18] Gausemeier, J., Fink, A., Schlake, O. (1998), Scenario Management: An Approach to Develop Future Potentials. Technology Forecasting and Social Change, Vol. 59, pp. 111 – 130. [19] Gausemeier, J., Plass, C., Wenzelmann, C. (2009): Zukunftsorientierte Unternehmensgestaltung: Strategien, Geschäftsprozesse und IT-Systeme für die Produktion von morgen. Carl Hanser Verlag, München. [20] Herstatt, C.; Verworn, B. (2007): Management der frühen Innovationsphasen: Grundlagen - Methoden - Neue Ansätze. Betriebswirtschaftlicher Verlag Gabler, Wiesbaden. [21] Cooper, R. G. (2008): Perspective: The Stage-Gates Idea-toLaunch Process—Update, What’s New, and NexGen Systems, in Journal of Product Innovation Management, 25:213– 232.

Remanufacturing Engineering Literature Overview and Future Research Needs 1

1

2

Qingdi Ke , Hong-chao Zhang , Guangfu Liu , Bingbing Li 1 2

1

Texas Tech University, Lubbock, TX, US

Hefei University of Technology, Hefei, Anhui, China

Abstract: In the past ten years, the remanufacturing engineering has become a very popular topic in the industrial area as it is one of the most effective and potential strategies for the “end-of-life” product management. However, the available literature and theory in the remanufacturing area are limited; this paper is designed to present an overview over the remanufacturing engineering, including literature about: reverse logistics, remanufacturing process, product design and economic and environmental analysis. This paper aims to compile a thorough survey and provide a foundation for the further research of remanufacturing engineering. Key words: Remanufacturing Engineering; Sustainable Engineering; Industrial Application

1

INTRODUCTION

Since the 90s of the last century, the remanufacturing engineering has become a very popular topic as one option of the recycle system in sustainable production. Some significant efforts and applications have been made by academic and industrial communities, and they have developed the theory, methodology, technical method and tools as well as equipments for remanufacturing engineering. Generally speaking, remanufacturing engineering has been considered an effective and potential technique to save the limited resources and energy and also to reduce the serious pollution from human manufacturing on earth. 1.1

Remanufacturing Engineering — the Recycle Need

Since industry has excessively consumed the resources and energy on earth and has generated large quantites of pollution to the environment, the governments have legislated several rules (such as WEEE and RoHS) to put a legal or financial pressure on the industrial companies to change the current situation. Thus, the recycle engineering developed quickly and started to reduce and reuse the traditional waste (end-of-life products).

end-of-life product with little or no treatment before extending life usage. The recycle strategy is taking the end-of-life product as a supplier of the primary materials, while the remanufacturing strategy is looking at the used product as the “core”, in which the used parts might be reconditioned and used like new ones [1]. However, due to the reusability limitations of the products, the pollution and energy consumption in materials extraction processes (such as separating, melting, etc.) during the recycling, remanufacturing may well be the best strategy. The remanufacturing enables the embodied energy of virgin production to be maintained, preserves the retained ‘added value’ of the product for the manufacturer and enables the resultant product to be sold ‘as new’ or be restored with updated features if necessary [2]. In Sutherland’s study, the use of energy for remanufacturing components of a six-cylinder diesel engine is only 10.22% of the energy required to create new components[3]. Since the benefits of the remanufacturing are much higher compared to recycling [4], remanufacturing has the potential to be quite profitable for an Original Equipment Manufacturer (OEM).

There have been three end-of-life strategies available for industrial companies (shown in Figure 1). The reuse strategy is utilizing the

Ore mining

Raw material extraction

Recycle

Manufacturing Machining

Utilization

Remanufacturing

Reuse

Use

Waste disposal

Figure 1: Three end-of-life strategies.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_75, © Springer-Verlag Berlin Heidelberg 2011

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Moreover, if the environmental impacts are considered, remanufacturing presents a significant improvement of the environmental protection. When we consider the commonly used “carbon footprint”, the remanufactured components have a much smaller carbon footprint than the equivalent virgin products [5]. In conclusion, since the quality of the remanufactured products is not lower than of the new ones, while it is only half as expensive [6], remanufacturing engineering will have a tremendous potential for our sustainable development. 1.2

Historical Background

Remanufacturing has been around for at least 60 years and provides significant economic, social and environmental benefits [1]. Since World War II, the implicit processes have already existed in the manufacturing industry. In the 90s of the last century, the “3R” strategy (Reduce, Reuse and Recycle) system was founded in the USA [6] and remanufacturing operations have grown substantially and become common practice in many industries. In the Hauser and Lund’s study from 2008, the estimated number of remanufacturers in the U.S. is close to 2000 firms, which are widely distributed across different industries and multiple functional applications [7]. And in 1996, a report about the remanufacturing industry named "Remanufacturing, a hidden giant'' was published in the USA [8]. It showed the total output and the bright prediction of the remanufacturing companies in the USA. In developing countries, the remanufacturing engineering also developed rapidly and has been applied to industry. In China the exploration of remanufacturing engineering began in the late 1990s. The “National Key Laboratory for Remanufacturing” was granted to be built in 2001[6]. Shanghai Volkswagen established a modern engine remanufacturing plant aiming at its after-sales market [9]. 1.3

has merely been founded 20 years ago, many problems still exist in its applications, and a number of interesting academic questions remain unanswered. Such as: the high uncertainty about the “core” quality; high labor costs [10]. Thus, we must continue our study for remanufacturing. What are the detailed definitions, scopes and the potential of remanufacturing engineering? What are the objectives, systems and barriers of remanufacturing engineering? This paper discusses these issues, and tries to answer these questions by providing an overview of remanufacturing engineering.

Current Challenges

In most discussions, Remanufacturing is defined as “recycling by manufacturing ’good as new’ products from used products [1]”. However, since the modern remanufacturing engineering system

2

ESSENCE OF REMANUFACTURING ENGINEERING

2.1

Definition

Currently, many experts have presented multiple definitions for remanufacturing engineering, such as remanufacturing is an industrial process in which worn-out products are restored to a “like new” condition [1], and some similar definitions are also presented [11][12]. Generally speaking, remanufacturing is the industrial process that is applied to a “core”, which is the international term for the end-of-life product to remanufacturing industry, through a series of sequential steps which include inspection, disassembly, cleaning and inspection, part reconditioning and replacement, cleaning, reassembly, and testing, to meet the same product requirements as a new one [2-6]. And in one sentence, remanufacturing is a recycling procedure to restore a large quantity of products to an “as good as new” state. 2.2

Remanufacturing Process

Based on many different industries and on functioning practice, although most remanufacturing processes are different from each other and depend on the variable physical frames of the products, twelve commonly accepted processes [1][13][14] have been confirmed (as shown in Figure 2).

1. Warehousing

2. Sorting of

3. Cleaning of

4. Disassembly of

“Core”

of incoming cores

incoming cores

Cores

cores

preparation

5. Inspection of cores 6. Cleaning of specific parts Recondition 7. Reconditioning parts

processes

8. Testing the parts

12. Shipping

11. Packaging

10. Testing the

9. Reassembly of

Assembly line

finished products

parts and products

of products

Figure 2: Twelve main processes in general remanufacturing process [14].

End of Life Management - Reuse and Remanufacturing

Manufacturers

439

Distribution Centers

Customer Zones

OEM Remanufacturer Forward flows Disassembly Centers

Collection Centers Reverse flows

Figure 3: A supply chain including forward and reverse flows for remanufacturing [15].

2.3

Benefits in Remanufacturing

The remanufacturing industry will develop into a large and important industry that includes many market sectors and provides significant economic, social and environmental benefits. In XU’s study, the remanufactured products and virgin products are compared: the energy consumption of the remanufacturing processes is less than 50% of that of the manufacturing production, the labor force consumption is 67% and the raw materials consumption is only 11.1%- 20 % compared to the manufacturing production of virgin products [6]. Besides, a large quantity of environmental impacts, generated from the material extraction and energy generation, such as CO2 emission [5], have been reduced to protect the environment and human health. As mentioned above, the governmental regulations are another promoter of the remanufacturing applications [10]. To sum up, remanufacturing is an eco-innovation driver, with potentials on the economic as well as the ecologic side [1]. 3

AREAS OF STUDY

The researches and studies on remanufacturing engineering cover a variety of activities, including the reverse logistics analysis and modeling, remanufacturing decision-making, surface engineering, product design for remanufacturing economics analysis, life cycle assessment for remanufacturing products, etc. From the perspective of engineering, the following content is divided into four aspects: (a)

Reverse Logistics Management; (b) Processes technology; (c) Design for Remanufacturing; (d) Economic and environmental analysis. And some other important topics such as the market strategies, the improvements of regulations, etc. are not covered. 3.1

Reverse Logistics Management

Compared with the fixed location of natural raw materials, the distribution of the “core”, which is seen as the raw material in remanufacturing, is in a large and wide range. Since the supply of the “core” is similar to gathering the waste products from customers, the raw material supply through collection of the used products is called “closed-loop supply chain” (as shown in Figure 3). Currently, many professionals start their research in closed supply chains by different approaches, such as Markov’s chain method, etc. Thus, lots of study models have been established. Georgiadis developed a system dynamics model to study a closed-loop supply chain with remanufacturing [16]. Some researchers want to optimize the reverse logistics for a higher efficiency. Dowlatshahi analyzed and evaluated the cost-benefit structure with two different industrial company’s reverse logistics [17]. And the mixed models for multiple products have been examined by some persons. Sasikumar developed a mixed integer nonlinear programming model for maximizing the profit [18]. Also, there are some studies focused on detailed products or any other phases. Dowlatshahi explored the role of inbound and outbound transportation in reverse logistics systems [19].

Washing and cleaning (debris)

Disassembly

Inventory

Inspection and sorting (cracks) Recondition Recondition (Welding, Polishing) Remanufacturing Components Store Reassembly Remanufacturing Product Product testing Figure 4: main process flow for one remanufacturing product [1].

440

End of Life Management - Reuse and Remanufacturing

Besides, the remanufacturing system is inefficient because of built-in uncertainties and complexities of its operations. Thus, the core suppliers’ main focus is on recovering and supplying used parts in the required unit types, part numbers, and quantities. And the “core” inventory system has attracted many people to solve the uncertainty matter. Wee provides a time-weighted inventory approach for decision-making in a green supply chain inventory control [15]. Some researchers have put their attentions on the optimization. Teunter applied three methods to determine the lot sizes to minimize the total cost in remanufacturing [20].

Surface Engineering technologies have been utilized widely in this process. Wu introduced Automatic brush-plating technology with Ni/nano-alumina composite coatings [28]. And some studies are carried out on simulation and analysis of the process mechanisms. Zhang concluded the fatigue resistance and failure mechanisms of plasma-sprayed CrC–NiCr cermet coatings [29]. In recent times, the microstructure simulation such as FEA [30], for the mechanical performance of the parts in the reconditioning with surface technologies, has been a hot topic and has been studied and widely applied in the remanufacturing industry.

The remanufacturing is very different from manufacturing, thus, it is important to analyze it and use it for the design the “core” supply system with a close-loop consideration [21]. The firms must know the design of closed-loop supply chains to enhance their profits and market demand, and the closed-loop supply chain can increase the used-product return rate as well as reduce the total cost.

3.3

3.2

Process Technology

As mentioned above, there are several processes needed to get from one “core” to a remanufactured product (as shown in Figure 4). Due to the uncertainties and complexities of the used products, the disassembly process is widely studied to seek an optimized remanufacturing ratio [22]. And many disassembly models have been established based on the economic and environmental factors. Tang established a model for the disassembly processes on evaluating their economic consequences [23]. Some of the researchers have focused on the decision-making for the recycling options with economic and time factors. Lee established an decision model for remanufacturing options [24]. Moreover, some persons considered the remanufacturing potential as an important factor. Xing proposed a mathematical model of product upgradeability to measure a product’s remanufacturing potential [25]. As manufacturing, the disassembly line balance problem is also been emphasized. Gupta presented the solutions to the disassembly line balancing problem [26]. And there are also some studies with other perspective. Ketzenberg considers the problem of designing a mixed assembly–disassembly line for remanufacturing [27].

Design for Remanufacturing

In contrast to the practices currently followed in the reverse supply chain, disassembly optimization and recondition technologies, the product development with higher remanufacture ability might solve lots of problems in the remanufacturing processes [31]. Like the design for recycling, design for remanufacturing was related with the other life-cycle design-for-x methodologies (as shown in Figure 5). Some ecodesign methods are utilized for remanufacturing. Pigosso presented some ecodesign methods focused on the remanufacturing to reduce the life cycle impacts of products [32]. Some of them have provided the software. Zwolinski proposed an approach to integrate remanufacturing constraints with the tool REPRO2 (REmanufacturig with PROduct PROfiles) [33]. However, due to different objectives in design, the “trade-off” assessment methods are still needed for an optimized product design. Um described a recovery management system with architecture design, product data model and infrastructure for information [34]. In contrast to the practices currently followed in the remanufacturing technologies, developing the products with a higher remanufacture ability would reduce the energy and material demands of the entire industrial process rather than breaking them down and reconditioning them with complicated remanufacturing processes [31, 35]. With only a few industrial examples being developed, it is now necessary to convince product designers to accept the design for remanufacturing rather than to improve the remanufacturing processes.

Another highlight process is the recondition process. Recently,

Material

Part

Configuration

Process

Database

Database

Database

Database

Designers End-of-life Strategies

Design Scheme of Product

Optimum remanufacture ability of a product

Environmental and economical information

Environmental Impact Assessment

Figure 5: Overview of the work in design for remanufacturing [32].

End of Life Management - Reuse and Remanufacturing 3.4

Economic and Environmental Analysis

In remanufacturing, resource consumption for possibly unnecessary reprocessing of material while preserving this added value is avoided [36]. Moreover, the energy consumption and some environmental impacts which are generated in the production of new products can be avoided. Thus, it is necessary to study the quantitative benefits for validating the qualitative conclusions. Liu analyzed benefits statistics of remanufacturing 10 000 Styer engines [37]. Some researchers have established a cost model. Sutherland established a remanufacturing facility cost model for the total costs related to diesel engine remanufacturing [38]. And some studies are comparison analysis. Intlekofer analyzed the effects on energy usage between leasing the product and selling it in life spans [39]. In addition, some researchers explored the decision-making with economic models. Linton presented the assessment of the economic rationality of remanufacturing for an OEM’s production [4]. And the optimal benefits have also been studied. Gosavi presented an optimal strategy of switching between the “cores” and natural material with reinforcement learning algorithm [40]. Meanwhile, the environmental perspective has attracted more and more interest. Yang used the method of life cycle assessment to assess the life cycle index of remanufactured engines [41]. Differentiation from manufacturing; the environmental performance of remanufacturing has not been well quantified in the life cycle. And along with higher pressure of the environmental issues, it is quite necessary to undertake further studies based on the life cycle analysis for current remanufacturing allocations. 4

CONCLUSION AND REMARKS

The future of the remanufacturing engineering appears positive with huge opportunities for industrial applications on the large quantity of end-of-life products. However, there are considerable challenges in the remanufacturing applications. This paper describes a comprehensive overview of remanufacturing engineering, and intends to stimulate and inspire both academic and industry for further benefits from remanufacturing studies and applications. And based on the above literature review, the following three main issues in remanufacturing are presented: 1. The first issue is the uncertainty in the qualities and availability of cores [42], which causes the unsteadiness of the material flows, remanufacturing process planning and other serious problems. Product diversity and proliferation also increase the uncertainty of the qualities and availability of cores; 2. The second issue is the design for remanufacturing, since the operations of the remanufacturing strongly depend on skilled labor, and the remanufacturing experience and knowledge is not yet established in a design database. And the diversity of the products increased the difficulty to set the variation in the remanufacturing processes, which also reduces the feasibility of a general design method for remanufacturing; 3. The third issue is that the environmental performance of remanufacturing has not been well quantified. Although lots of companies have recovered a large quantity of materials every year from remanufacturing, the magnitude of remanufacturing benefits is not well known. Moreover, the environmental impacts study is based on a large quantity of the industry – wide data, which could cost lots of time and labor. Thus, there is little quantitative evidence to convince the public and government for an environment-friendly image of remanufacturing. The environmental assessment, especially the life cycle assessment of remanufacturing products is necessary and important to introduce and extend itself;

441 With the above issues, many studies have been carried out as mentioned before. A “closed-loop chain” has been developed to solve the uncertainty problems, while, some design approaches and tools are established for product design, and some environmental studies, especially the comparison between remanufacturing and manufacturing [43], are presented to demonstrate the remanufacturing. All of these efforts have been introduced in this paper. And one of the most important solutions should be the life cycle engineering [39][40][41]. The remanufacturing engineering should add itself as an important end-of-life phase to the entire product life cycle. Considering the whole life perspective, the remanufacturing could become a positive phase which could improve the total energy and material using efficiency in the entire product life. And based on the directions of life cycle, the remanufacturing could be identified as the extend phase of the product, and its development will be truly successful with more and more applications in industry, 5

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Effects of Lateral Transshipments in Multi-Echelon Closed-Loop Supply Chains 1

2

1

Kirsten Tracht , Michael Mederer , Daniel Schneider 1

Bremen Institute for Mechanical Engineering (bime), Universität Bremen, Bremen, Germany 2

2

m hycon, Oberolm, Germany

Abstract Spare part supply for machines is realized with multi-echelon closed-loop supply chains, in which spare parts are repaired and led back to stock after removal from a broken machine. Spare parts have to be provided fast for avoiding revenue loss due to Poisson distributed part failures. This requires distribution warehouses, which are located close to the machines and one central warehouse, replenishing the distribution warehouses. If a spare part is requested, the part is supplied by the central warehouse or the distribution warehouse assigned to the requesting location. Emergency transshipments from distribution warehouses that are not assigned to the requesting location, can improve supply chain performance. Keywords: Logistics; Simulation; Transshipment

1 1.1

INTRODUCTION Problem Statement

Operators of high-tech machines need quick and reliable spare part supply if an unexpected part failure occurs. As keeping stock at the location of each machine is very expensive, spare parts supply is realized with a system of different interconnected warehouses. For fast spare part supply distribution warehouses, which are located close to the machines, hold stock. Each machine is assigned to the closest distribution warehouse and is provided with spare parts from that warehouse in case of a part failure. Stock of the distribution warehouse is refilled by replenishment deliveries from a central warehouse. Spare parts are delivered by the central warehouse to the location of a broken machine if the distribution warehouse is out of stock. After removal from the machine, the broken spare part is sent to a repair shop, repaired and put back into stock. The system considered in this investigation is a two echelon closed-loop supply chain for repairable items.

are introduced in the succeeding chapter. With the simulation model total costs of the supply chain with and without lateral transshipments are compared. Results are summarized in the conclusion. 2

LITERATURE REVIEW

In order to improve supply chain performance lateral transshipments within the same echelon are useful. Numerous papers have dealt with analysis of rules and settings for transshipments between different locations. Paterson et al. provide an overview of investigation results published in the last decades on that topic [1]. They classify the papers as shown in Table 1. Feature

Value

number of items

1, 2, or any number M

number of echelons

1, 2 or P

If neither the distribution warehouse nor the central warehouse holds spare parts in stock to fulfill a request, the spare part has to be loaned by a competitor. The loan costs increase, the longer the spare part has to be loaned.

number of (depots)

2, 3 or any number N

identical locations?

identical costs, not identical costs

In the initial setup transshipment of spare parts between distribution warehouses in case of empty stock is not allowed. As every request is assigned to one distribution warehouse, the spare part has to be loaned in case of a stock out in the central warehouse or the assigned distribution warehouse. The effects of emergency transshipments between different distribution warehouses and possible cost savings will be analyzed in this paper.

unsatisfied demand

backorder or lost sales

timing orders

(R, Q), (s,S), (S-1, S), general or other

1.2

transshipment structure

Course of Investigation

The literature review presents transshipment strategies that were developed and analyzed during the last decades. Different settings, consideration of transshipments costs, one- or two-echelon systems, closed-loop or open-loop supply chains have been subjects of investigation. The supply chain considered in this paper, the corresponding simulation model, and the utilized cost functions

locations

of

regular

type of transshipment

proactive or reactive

pooling

complete or partial

decision making

centralized or decentralized cost

per item, per transshipment, both or none

Table 1: Characteristics of transshipment problems. The first author to analyze a closed-loop supply chain for repairable items, a central based depot and a one-for-one ordering system is Sherbrooke [2]. Lee considers a similar system and combines

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_76, © Springer-Verlag Berlin Heidelberg 2011

443

444 distribution warehouses to pooling groups within which warehouse are allowed to transship spare parts [3]. All warehouses are identical and transshipment lead times are neglected. He analyzes four different strategies: random selection, maximum stock on hand, smallest number of outstanding orders and calculation of service level. The results of the strategies only differ slightly, but are all far better than without transshipping. Axsäter considers non-identical locations and includes stock-holding at the central warehouse [4]. Kukreja, Schmidt and Miller consider one echelon and choose the location by the lowest transshipment costs [5]. Kukreja and Schmidt extend this model for a compound Poisson process and (s,S) replenishment [6]. They introduce dynamic programming rules for selection of the source location, when transshipping. Kutanoglu and Mahajan also find that lateral transshipments lower costs and raise service levels. In their model a request has to be fulfilled within a certain time window [7]. The authors mentioned up to here, assume backordering if a request cannot be fulfilled. Requests queue and can be satisfied at a subsequent point in time. In comparison to backordering Dada [8] analyzes metric models with lost sales. A request can only be fulfilled at the time of the request, and not later. In case of lost sales, the transaction and revenue are lost if not fulfilled at the time of request. As a result, in the long term the customer might change to a competitor. Other authors also consider lost sales. Wong et al. investigate transshipments in a supply chain with decentralized control, every warehouse optimizing its own transshipment strategy [9]. Grahovac and Chakravarty find that lateral transshipments reduce costs and increase inventory levels [10]. In his model stock levels increase at the distribution warehouses and decrease at the central warehouse due to the lateral transshipments. Needham and Evers analyze the influence of individual cost factors on emergency transshipping in different transshipment strategies [11]. A warehouse can transship if stock level is greater than its reorder point, if it is greater than its safety stock, or if it is greater than the demand expected for the next period. A fourth option is not transshipping at all. Stock out costs are set to 50 % of the spare part purchasing price in their model. They find that all the transshipment policies raise service levels, compared to scenarios without transshipments. The best ordering point of a warehouse for minimzing holding and transshipment costs is presented by Hou and Li [12]. Hu, Watson, and Schneider develop formula solutions for calculation of benefits of emergency transshipments. They assume that transshipments are only allowed at the end of the week (periodic review) [13]. Utterbeeck et. al. analyze the effects of resupply flexibility on the design of service parts supply systems [14]. He finds that increased supply chain flexibility and emergency deliveries save costs. Olsson considers both – backordering and lost sales – in his model, finding that the assumption of symmetry does not mean that the optimal solution is symmetric, when optimizing normal replenishments [15]. Following Table 1, the problem discussed in this paper is a single item problem in a two-echelon supply chain where the six warehouses incur identical costs and have a one-for-one timing (S1, S) for regular replenishment orders. Unsatisfied demand is backordered. The missing spare part is loaned from a competitor for the time elapsing during emergency shipping. Transshipment of spare parts is reactive and only takes place in case of stock out. If one warehouse is out of stock, another warehouse will directly provide the spare part to the location of the request. Decision making is centralized, and transshipment costs incur per item. The analysis assumes complete pooling, since warehouses do not hold back stock in case of an emergency transshipment request. In comparison to existing publications the model presented here is a

End of Life Management - Selected Applications closed-loop, multi-echelon supply chain, taking into account stock out costs that increase with increasing loan duration. Other authors assume that stock out costs are only incurred once and do not depend on the length of the stock out. Results can vary from findings published to date and are motivation for the work presented. 3 3.1

CLOSED-LOOP SUPPLY CHAIN Spare part supply

repair shop

cw

dw1

dw2

dw3

dw4

dw5

dw6

machine

Figure 1: Two-echelon supply chain for repairable items. The system under investigation is a closed-loop supply chain for quick and reliable spare part supply. It was set up to avoid extensive downtimes of the machines, when a part fails unexpectedly. Elements of the supply chain are spare part stock, machines, and a repair shop for overhauling of replaced parts. Figure 1 shows the two-echelon supply chain with a central warehouse and several distribution warehouses. The central warehouse (cw) receives the parts leaving the repair shop. Six distribution warehouses (dw) are located close to the machines, for quick spare parts supply in case of part failure. A requested spare part is delivered from the distribution warehouse, which is assigned to the requesting location. In case of a spare part request, the part is taken from stock of a distribution warehouse and shipped to the location of the broken machine. The part arriving from stock replaces the broken one in the machine. The broken part is sent to the repair shop, repaired and put back into stock in the central warehouse. After delivery the distribution warehouse is replenished by the central warehouse to maintain minimum stock levels. If there is more than one replenishment request by the distribution warehouses, the oldest request will be served first. In case the distribution warehouse is out of stock when a request occurs, the spare part will be provided by the central warehouse. As delivery lead time from the central warehouse to the requesting location is longer than from the distribution warehouse, the spare part arrives at its destination too late. The spare part has to be loaned from a competitor during the transportation time in order to avoid downtimes of the machines. It is returned as soon as it arrives at the distribution warehouse. These loan costs will be called transport loan costs. The spare part is also loaned if both, the assigned distribution warehouses and the central warehouse, are out of stock. The spare part will be returned to the lender as soon as a repaired spare part from the shop arrives at the central warehouse. These loan costs

End of Life Management - Selected Applications

445

will be called inventory loan costs. In both cases loan costs are incurred daily, accumulating during the loan duration. Transshipments

In the initial hierarchical setup transshipments are not allowed. If a spare part is requested and the distribution warehouse is out of stock, the spare part is demanded at the central warehouse. In case of a stock out at the central warehouse, the spare part is loaned. Spare parts of a distribution warehouse are available for the machines assigned to that warehouse only. The investigations consider effects of transshipments in a twoechelon closed-loop chain. The spare parts can be delivered from any other distribution warehouse if the central warehouse and the assigned distribution warehouse are out of stock. 4 4.1

Assumptions

For analyzing the effects of transshipments a discrete event simulation model of the closed-loop supply chain with replenishments is utilized. Loan costs are calculated once a day, thus loaning only a few hours incurs costs for the entire day. Demand for the spare parts at the distribution warehouses is Poisson distributed and based on historical data. Every distribution warehouse holds minimum stock for supplying spare parts in emergency cases, when delivery time from the central warehouse is too long. The repair time in the repair shop is exponentially distributed. Transportation times between warehouses, to the machines and from and to the repair shop follow a triangular distribution. If replenishment requests queue at the central warehouse in case of stock out, the oldest request is served first, once a spare part arrives at the central warehouse from the shop. Spare parts are stored at the central warehouse if all the distribution warehouses have their minimum number of spare parts in stock. Total costs and service levels are used to evaluate supply chain performance. 4.2

Total Costs

(1)

The capital costs cc depend on the purchase price cp of a spare part, the number of spare parts in the supply chain np, the depreciation pd and the interest rate pi.

cc (c p , n p , pd , pi ) cc cp np pd pi

(2)

= capital costs = purchase price of spare part = number of spare parts in the supply chain = depreciation = interest rate

The loan costs cl are a function of the purchasing price cp, the number of spare parts np, the demand d, and the transportation times tt.

cl (c p , n p , d, tt ) cl d tt

Service Level

The service level is an indicator for supply chain performance equaling the percentage of the requests that are fulfilled by spare parts in stock. For example, if all the requests are served by the distribution or the central warehouses, the service level is 100 %. If the distribution and the central warehouse are out of stock and the spare part has to be loaned, the service level is lower. Validation

The simulation model has been validated extensively before being used for simulation experiments. Different validation techniques have been applied, for proving the accuracy of the model. The most important among them are a fixed value test and a comparison with historical data. After testing and calibrating, the model has been found to be validated for the scheduled simulation experiments. 5

SIMULATION RESULTS 100 80 60 40 20 0 20

21

capital costs

The total costs ct, which are subject of investigation in this paper, consist of capital costs cc and loan costs cl.

ct  cc  cl

4.3

4.4

SIMULATION

(4)

Impacting parameters for both types of loan costs follow equation (3). As pre-investigations have shown, transportation costs do not impact the results of total costs ct. Compared to the loan costs cl and capital costs cc handling and transportation costs are negligible and will not be considered.

costs [€]

3.2

cl  cli  clt

(3)

= loan costs = demand = transportation time

Loan costs are subdivided in inventory loan costs cli and transport loan costs clt, depending on whether the warehouses are of stock or the transportation time is too long.

22 23 24 25 26 27 28 29 30 number of spare parts np [pcs] transport loan costs inventory loan costs

Figure 2: Costs without transshipments. A maintenance, repair and overhaul provider of the aviation industry supplies the historical demand level for an electronic aircraft device of the years 2008 and 2009 as input data to the simulation model. Experiments are repeated until the width of the largest confidence interval of total costs ct (np) is lower than 6 % of the mean total costs ct,mean (np). Experiments for all other np are conducted with the same number of repetitions. To allow for settling of transient effects, measuring is started on January 01, 2009. Figure 2 shows the inventory loan costs, transport loan costs, and total costs ct over the number of spare parts np that incur when transshipments are not allowed. For loan costs, and capital costs only mean values are given, omitting confidence intervals for simplicity. The confidence interval for total costs ct, using a 95 % confidence coefficient, is displayed at the top of every bar. The top of each bar equals the expected mean value of total costs ct. The total costs ct are minimal, when there are np=28 spare parts in the system. Capital costs cc rise with increasing number of spare parts np. The greater np is, the smaller inventory loan cost cl become, since fewer parts have to be loaned because of a stock out. Transport loan costs that incur because transportation time is too long, increase with np.

446

End of Life Management - Selected Applications types is lower for the scenario with lateral transshipments, applying to all values of the number of spare parts np.

100

For every np, the service level is lower in the scenario without transshipments. Taking into account spare parts in all the warehouses decreases the probability of a stock out and improves the service level. The smaller np, the greater is the improvement of service level by transshipments.

60 40 20 0 20

21

capital costs

22 23 24 25 26 27 28 29 30 number of spare parts np [pcs] transport loan costs inventory loan costs

Figure 3: Costs with transshipments. Figure 3 displays the different cost types over np for the scenario with transshipments. Capital costs cc rise and inventory loan costs cli lower with increasing np as before. Contrary to the scenario without transshipments, transport loan cost clt decrease slightly with raising np. The cost minimal number of spare parts np,min=28 also. A comparison of both scenarios is given in Figure 4, displaying costs for scenario without transshipments at the left hand bar and with transshipments at the right hand bar for each value of np. Similar to the Figures above, the bars equal the mean expected values and the confidence interval is given for total costs ct only. The service level, whose scale is on the ordinate to the right, is displayed for every np and both scenarios. The corresponding confidence interval also uses a 95 % confidence coefficient. With transshipments total cost ct are lower for every np. Service levels of the scenario with transshipments are higher for np below the optimal number of spare parts np,opt=28. At the optimal number of spare parts service levels in both scenarios are very similar. Total costs ct are 5 % lower for np,opt=28 if transshipments are allowed. Total cost ct are lowered, because spare parts in stock are available for all requesting locations and not only to the location assigned to the distribution warehouse. Inventory loan costs are significantly lower, if lateral transshipments are allowed. Without transshipments every time the distribution or the central warehouse are out of stock, when a spare part request arrives, a part is loaned, raising inventory loan costs.

costs [€]

If np<24, the transport loan costs are greater with transshipments. Spare parts are provided by other warehouses in case of stock out at the assigned warehouse. As the transportation time is longer, spare parts have to be loaned for the time of the transport. The transport loan costs are greater with lateral transshipments, but inventory costs are significantly lower. The sum of both loan cost

Worsening of supply chain performance due to numerous transshipments cannot be recognized. When a spare part is transshipped from another warehouse a request can arrive shortly after at the distribution warehouse that has provided the emergency transshipment. If that warehouse is out of stock, an additional emergency transshipment has to be initiated. The additional transportation time when repeatedly delivering from other distribution warehouses, can worsen supply chain performance. This effect, however, does not show at the simulation of the scenario with transshipments considered here. Further investigations – i.e. different distribution of spare parts to the warehouses – have to be conducted for determining whether transshipments worsen supply chain performance under certain conditions. 6

CONCLUSION

A simulation model was developed to determine total costs and service levels of a two-echelon closed-loop supply chain with repairable items. With the simulation model the effects of lateral transshipments were analyzed, assuming loan costs in case of stock out. The loan costs increase, the longer the stock out lasts. The comparison shows that total costs with transshipments are lower than without transshipments for every number np of spare parts in the system. The cost optimal number of spare parts in the system np=28 in both scenarios. The total costs ct are 5 % lower with transshipments. The service level can be increased significantly by transshipment. The lower np, the greater the improvement in service level by transshipments is. When determining optimal inventory levels, lateral transshipments have to be considered for achieving cost optimal supply chain settings. Improved inventory strategies lower costs and raise reliability of the supply chain. 7

ACKNOWLEDGEMENTS

The results presented in this paper were developed in the research project dLP – dynamic LRU planning (03CL02H). dLP is part of the Aviation Cluster Metropolitan Region Hamburg funded by the German Federal Ministry of Education and Research (BMBF).

100

100

80

95

60

90

40

85

20

80

0

service level [%]

costs [€]

80

75 20

capital costs

21

22

transport loan costs

23

24 25 26 number of spare parts np [pcs]

inventory loan costs

27

service level (transshipments)

28

29

30

service level (w/o transshipments)

Figure 4: Costs and service level with transshipments and without transshipments.

End of Life Management - Selected Applications 8

REFERENCES

[1]

Paterson, C.; Kiesmüller G; Teunter, R.; Glazebrook, K. (2010): Inventory Models with Lateral Transshipments: A review, in: European Journal of Operational Research, in Press.

[2]

Sherbrooke, C.C. (1968): METRIC: A Multi-Echelon Technique for Recoverable Item Control, in: Operations Research Logistics 39, pp. 29-30.

[3]

Lee, Hau L. (1987): A Multi-Echelon Inventory Model for Repairable Items with Emergency Transshipments, in: Management Science, Vol. 33, No. 10, pp.1302-1316.

[4]

Axsäter, S. (1990): Modeling Emergency Transshipments in Inventory Systems. Management Science Vol. 36, No. 11, pp. 1329-1338.

[5]

Kukreja, A., Schmidt, C.P., Miller, D.M. (2001): Stocking Decisions for Low-Usage Items in a Mulit-Location Inventory System, in: Management Science Volume 47, Issue 10, pp. 1371-1383.

[6]

Kukreja, A., Schmidt, C.P. (2005): A Model for Lumpy Demand Parts in a Mulit-Echelon Inventory System with Transshipments, in: Computers & Operations Research Vol. 32 Vol. 8, pp. 2059-2075.

[7]

Kutanoglu, E. Mahajan, M. (2009): An Inventory Sharing and Allocation Method for a Multi-Location Service Parts Logistics Network with Time-Based Service Levels, in: European Journal of Operational Research, Vol. 194, Issue 3, pp. 728742.

[8]

Dada, M. (1992): A Two-Echelon Inventory System with Priority Shipments, in: Management Science Vol. 38, No.8, pp. 1140-1153.

[9]

Wong, H., van Oudheusden, D., Cattrysse, D. (2007): Cost allocation in Spare Parts Inventory Pooling, in: Transportation Research Part E: Logistics and Transportation Review Vol. 43, No. 4, pp. 370-386.

[10]

Grahovac, J., Chakravarty, A. (2001): Sharing and Lateral Transshipments of Inventory in a Supply Chain with Expensive Low Demand Items, in: Management Science Vol 47. No. 4, pp. 579-594.

[11]

Needham, P.M., Evers, P.T., (1998): The Influence of Individual Cost Factors on the Use of Emergency Transshipments, in: Transportation Research Part E. Vol. 34, No. 2, p. 149-160.

[12]

Hou, J., Li, H. (2007): Batch Ordering Policy of Multi-Location Spare Parts Inventory System with Emergency Lateral Transshipments, in: Systems Engineering – Theory & Practice, Vol. 27, Issue 12, pp. 62-67.

[13]

Hu, J., Watson, E. Schneider, H: Approximate Solutions for Multi-Location Inventory Systems with Transshipments, in: International Journal for Production Economics 97, pp. 31-43.

[14]

Utterbeek, F.V., Wong, H., Oudheusen, D.V., Cattryse, D. (2009): The Effects of Resupply Flexibility on the Design of Service Parts Supply Systems, in: Transportation Research Part E. 45, pp. 72-84.

[15]

Olsson, F. (2009): Optimal Policies for Inventory Systems with Lateral Transshipments, in: International Journal of Production Economics, Volume 118, Issue 1, pp. 175-184.

447

Development of an Interpretive Structural Model of Barriers to Reverse Logistics Implementation in Indian Industry 1

Anil Jindal , Kuldip Singh Sangwan

1

1

Mechanical Engineering Department, Birla Institute of Technology & Science, Pilani, India

Abstract Sustainability is an important concept for twenty first century organizations and one approach for managing corporate sustainability is through the introduction of reverse logistics (RL). But there are many barriers to the implementation of RL in developing countries like India. This paper identifies sixteen barriers to RL from the literature survey. An interpretive structural modeling (ISM) technique has been used to develop a structural model to obtain proper hierarchy and interrelationship among the barriers. The model will help the decision makers in government and industry to prioritize the focus on the barriers for implementation of RL. Keywords: Reverse Logistics; Reverse Supply Chain; Interpretive Structural Modeling

1

INTRODUCTION

Reverse logistics has gained increasing attention among researchers and practitioners of operation and supply chain management because of growing green concern, sustainable development, fierce global competition, pressure on profitability and increase in flow of returns of the products due to product recall, warranty returns, service returns and so on[1]. Sustainability is an important concept for twenty first century organizations and one approach for managing corporate sustainability is through the introduction of reverse logistics (RL) [2]. RL is mainly regulatory driven in Europe where governmental regulations are compelling businesses to address recovery and disposal of end-of-life products; profit driven in USA where value is recovered where ever possible; and in incipient stage in other parts of the world including India [3]. The implementation of RL is not an easy task in emerging countries like India because of the absence of societal pressure and insensitiveness to environmental issues, in addition to the price sensitive market. In India product returns are often regarded as a cost of doing business and are generally carried out by the unorganized sector for recyclable material such as paper and aluminum. Successful implementation of RL needs not only financial and economic support from government but also cooperation among the supply chain partners. A critical analysis of the barriers hindering reverse logistics and their interaction with various aspects in integrative planning can be a valuable source of information to decision makers [4]. In this paper, an attempt has been made to identify the barriers to implementation of reverse logistics through a study of 20 research articles during 1995-2009. These barriers are further scrutinized by discussion with practitioners and academicians working in the area of reverse logistics or reverse supply chain management in India. An ISM model has been developed showing the hierarchy and interrelationship among the identified barriers. This paper is structured as follows: the next section gives an overview of the

identified barriers. Section 3 presents the ISM model. Results are discussed in section 4 and section 5 presents the summary of the study. 2

OVERVIEW OF BARRIERS TO REVERSE LOGISTICS

In this paper, 16 barriers have been identified from literature review of 20 peer-reviewed research journal articles [2-21] as shown in Table 1. The 16 barriers can be further classified into 4 groups, viz, economical, organizational, market related and government related. An overview of these barriers is presented below: 2.1

Economical Barriers

These barriers are related to the cost and benefits of RL implementation in economic term as given below: Lack of Economic Benefits Despite the advantages that may be obtained by implementation of RL many organizations are still reluctant to implement RL simply because they think the barriers confronted in implementing RL would be greater than the economic benefits. Moreover there is a general reluctance to pay for waste recycling and disposal services, particularly when consumers can make money by selling their old and broken appliances [5] [6]. The manufacturing sector claims to have too small a profit margin to bear the increasing costs of green design, testing and recycling [7]. Thus, the economic benefits derived from reverse logistics are very limited at this stage. High Set-up and Operating Cost High set up and operating cost (comprising mainly transportation and reprocessing costs) is a key barrier to reverse logistics programs [8] [9]. Information and technological systems require more funds because without these, the return product tracking, tracing and product recovery is not possible in the present environment. The training of personnel related to the reverse logistics is also very important for efficiently managing and eventually making the reverse logistics profitable. However, all these require financial support [2] [4].

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_77, © Springer-Verlag Berlin Heidelberg 2011

448

Number 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Name of Barrier Lack of Awareness about Reverse Logistics Lack of Law, Legislation and Supportive Economic Polices Lack of Top Management Commitment Lack of Economic Benefits Lack of Strategic Planning High Set up and Operating Cost Company Policies Resistance to Change Lack of availability of Technology and Information System Lack of Training and Education Stochastic Return and Demand Marketing of Remanufactured Product Extensive Informal Waste Sector Lack of Economy of Scale Lack in Support of Supply Chain Partners Lack of Appropriate Performance Metrics

1 √

2

3 √

√

√

7 8 √ √

√

√

√

√ √ √

√

√

√

√

√

√ √

√ √ √

√

√ √

√ √ √

√ √

Rahimifard et al ( 2009), [20]

√ √

√

√

√ √

√ √

√

√ √

√ √

√

√

√ √

√ √

√ √

√

√ √ √

Srivastava, S.K. (2008), [21]

Chapman et al (2005), [19]

Pokharel and Mutha (2009), [18]

Daniel et al ( 2009), [17]

Rogers et al (2002), [16]

Inderfurth, K. (2005). [15]

Fleishmann, M. (2003), [14]

Van der Laan et al (1999),[13]

Stock , J.R. (2001), [12]

Barker and Zabinsky (2008), [11]

9 10 11 12 13 14 15 16 17 18 19 20 √ √

√ √ √ √ √

√

Daniel et al (1997), [10]

Lau and Wang (2009), [9]

6

√ √

Roggers and Tibben-Lembke (1998), [8]

4 5 √ √

√ √ √ √ √

Xiaoming and Olorunniwo (2008), [7]

Thierry et al (1995), [6]

Hicks et al (2005), [5]

Ravi and Shankar (2005),[4]

Author(s) and Year Presley et al (2007), [2]

Barriers

449

Srivastava and Srivastava (2006), [3]

End of Life Management - Selected Applications

√ √

√ √

√ √ √

√ √

Table 1: Literature review of barriers to RL implementation. Lack of Economy of Scale Manufacturers in developing countries are still not able to recapture value and recover assets from recycling probably due to low volume of returns [9]. So, lack of EoL products is one of the greatest threats to their industry [10]. 2.2

Organizational Barriers

These barriers are organization specific and are not related to any particular industry sector as given below: Lack of Top Management Commitment Lack of commitment by top management is a crucial barrier for successful reverse logistics [8]. Because of high initial investment and slow rate of return, managers give priority to other type of investments that have more rapid and visible economic returns on investment. Top management should provide continuous support for reverse logistics in the strategic plans, for successfully implementing them [4] [11]. Moreover, the executives who look for forward supply chain are given the additional responsibility of RL. This results in high costs, problems and delays [12]. Lack of Strategic Planning Reverse logistics can be used as a strategic weapon in the present industrial environment [8]. Strategic planning is the identification of reverse logistics goals and the specification of long-term plans for managing them. In the present scenario, due to the rapid changes in technology and also due to changes in the behaviors of competitors, consumers, suppliers, etc., a sound strategic planning is necessitated for the reverse logistics programs. For

implementation of reverse logistics in any organization, the role of strategic planning is very important to achieve the goals for the survival of the organization in the global market [4]. Company Policies Restrictive company policies are an important barrier to the reverse logistics [8]. The lack of the importance of the reverse logistics and the management inattention are related to the policies followed by the companies. Companies want to create a brand image to the customers. They do not want to compromise on the end-product quality by using the returned products [12] [7]. Resistance to Change A fundamental barrier in the implementation of the reverse logistics is the resistance to change. People avoid change and the reverse logistics requires a change in the mindset and practice. The company policies and organizational structures get in the way rather than facilitate change. The lack of awareness of the benefits of the reverse logistics both from economic and social angles could be a major factor for the resistance to change to reverse logistics. The resistance to change is more pronounced at middle level management and among shop floor personnel as those people are not able to comprehend the social and economic benefits of RL [4]. Lack of availability of Technology and Information System A very serious problem faced by the firms in the implementation of reverse logistics is the lack of availability of good technology and information systems [8]. Efficient information systems are needed for individually tracking and tracing the returns of the product, linking with the previous sales, thus helping in the inventory

450

End of Life Management - Selected Applications

management. Very few Indian firms have successfully automated the information surrounding the return process [4]. Lack of Training and Education Lack of personnel resources and education is a major challenge to commercial recycling. Education and training are prime requirements for achieving success in any organization. The need for training on reverse logistics extends throughout the organization. New or revamped technology necessitates changes and the personnel should be given adequate training in the new technology and processes that will be implemented [4] [8].

be enhanced as end of life (EoL) returns from consumers for recycling are still relatively small in volume. Low public awareness of environmental protection in the developing countries is one of the obstacles to widespread reverse logistics implementation [2] [9]. Lack of Law, Legislation and Supportive Economic Polices

These barriers are specific to the reverse logistics and the surrounding market situation as given below:

The major difficulty in implementing reverse logistics in developing countries is the lack of enforceable laws, regulations or directives to motivate manufacturers. Furthermore, economic support and preferential tax policies are absent to help manufacturers offset the high investment costs of reverse logistics. To expedite development of reverse logistics, the government can play the role of coordinator or facilitator by stipulating rules and regulations on the sharing of responsibilities and obligations among manufacturers, distributors, and end-users [9] [11].

Stochastic Return and Demand

Extensive Informal Waste Sector

Stochastic return and demand of remanufactured products makes RL a complex issue. A high degree of uncertainty in supply, both in terms of quantity and quality of used products returned by customers is one of the complicating characteristics impacting production planning and control large variety of inventories (used parts, new parts, spare parts, finished goods and work-in-progress), which is an important issue and obstacle in RL[13] [14] [15].

Extensive informal waste sector is one of the major barriers to the implementation of reverse logistics in India because it collects, recycles and disposes of the major part of the EoL products before it can reach officially sanctioned recycling and disposal enterprises, leading to reduction of its economic benefits. With the expenses of environmentally sound processing, it is very difficult for formal recycling business to compete with small, unlicensed collectors and workshops that operate with limited environmental protection measures [21].

2.3

Market Related

Marketing of Remanufactured Product Marketing a remanufactured product is much more complicated than marketing a new product because of the competition from the new products in the market [6] [16]. This is a sensitive issue in India and affects the sale of products to a large extent. Moreover, seller of remanufactured product gets lower commission than selling a new product. The pricing of remanufactured product is also a complex and challenging issue due to stochastic returns and demands. This makes it difficult to determine the price of remanufactured product vis-à-vis new product [17] [18]. Lack in Support of Supply Chain Partners Reverse logistics are poorly managed because of the lack of collaboration among the supply chain partners. The ability to collaborate with various players in the reverse chain is as important as in the forward supply chain. In fact, what makes a forward supply chain successful is the visibility of products in motion as well as collaboration and trust amongst the various entities in the chain [7]. A similar approach is also required for RL which demands close collaboration among partners and perhaps a redesign of the existing forward logistics processes to form a closed-loop [9] [19]. Lack of Appropriate Performance Metrics Lack of performance metrics is a major barrier to the reverse logistics programs. Performance metrics form the basis of integrated work management systems. Simply stated, “work not measured cannot be managed”. The performance measurement of any system is a key element in enabling the process of performance management, performance improvement, performance documentation, etc. [4] [7]. 2.4

Government Related

Following barriers, in emerging economies like India, can be mitigated by government to start with: Lack of Awareness about Reverse Logistics An important barrier to reverse logistics seen in supply chain is lack of awareness about the benefits of reverse logistics and the potential hazards of end of life products [5]. The reverse logistics can lead to economic benefits by the recovery of the returned products by reuse, remanufacturing, recycling, or a combination of these options. The implementation of the reverse logistics also leads to direct benefits to the environment [4] [8] [20].Public awareness of environmental protection and conservation needs to

3

DEVELOPMENT OF ISM MODEL

ISM is an interactive learning process whereby a set of different directly and indirectly related elements are structured into a comprehensive systemic model, employing graphics as well as words. ISM methodology helps to impose order and direction on the complexity of relationships among elements of a system for complex problems, like the one under consideration [22] [23]. The direct and indirect relationships between the barriers describe the situation far more accurately than the individual factor taken into isolation. Therefore, ISM develops insights into collective understandings of these relationships. The ISM is interpretive as the judgment of the group decides whether and how the variables are related. It is structural as on the basis of relationships an overall structure is extracted from the complex set of variables. It is a modeling technique as the specific relationships and overall structure are portrayed in a graphical model. It is primarily intended as a group learning process but can also be used individually. ISM is a well established methodology for identifying relationships among specific items, which define a problem or an issue [23], and is recommended by many researchers [24-25]. Therefore, in this research, these barriers are analyzed using ISM, which shows the interrelationships of the barriers and their driving power and dependence. The various steps, which lead to the development of ISM model, are illustrated below. 

Identification of elements, which are relevant to the problem or issues, this could be done by literature survey or any group problem solving technique.



Establishing a contextual relationship between elements with respect to which pairs of elements will be examined.



Developing a structural self-interaction matrix (SSIM) of elements indicates pair-wise relationship between elements of the system.



Developing a reachability matrix from the SSIM, and checking the matrix for transitivity. Transitivity of the contextual relation is a basic assumption in ISM which states that if element A is related to B and B is related to C, then A is related to C.

End of Life Management - Selected Applications Barrier Barriers Name Number 1

Lack of Awareness about Reverse Logistics

2

Lack of Law, Legislation and Supportive Economic Polices

3

Lack of Top Management Commitment

4

Lack of Economic Benefits

5

Lack of Strategic Planning

6

High Set up and Operating Cost

7

Company Policies

8

Resistance to Change

9

Lack of availability of Technology and Information System

10

Lack of Training and Education

11

Stochastic Return and Demand

12

Marketing of Remanufactured Product

13

Extensive Informal Waste Sector

14

Lack of Economy of Scale

15

Lack in Support of Supply Chain Partners

16

Lack of Appropriate Performance Metrics

451 Barriers 1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16

1

O V

V

V

V

V

V

V

V

V

V

V

V

V

V

1

V

V

V

V

V

V

V

V

V

V

V

O

V

V

1

A

V

A

V

V

V

V

V

V

O A

V

V

1

V

X

V

V

V

V

V

V

A

A

V

V

1

A

V

V

V

V

V

V

O A

V

V

1

V

V

V

V

V

V

O A

V

V

1

V

V

V

A

A

O A

V

O

1

X

X

A

A

A

A

V

V

1

X

A

A

O A

V

V

1

A

A

O A

V

V

1

X

A

A

V

V

A

A

V

V

1

X

V

V

1

V

V

1

V

1

1

Table 2: Structural self-interaction matrix. The following shows the development of an interpretive structural model of 16 barriers to the implementation of RL in Indian industry: 3.1

Structural Self-Interaction Matrix(SSIM)

ISM methodology suggests the use of expert opinion management techniques such as brain storming etc., in developing the contextual relationship among the variables. Thus in this research experts, from academia with research interest in RL and from the supply chain manager working in SME were consulted for the same. For analyzing the barriers in developing SSIM Table 2, the following four symbols have been used to denote the direction of relationship between barriers (i and j): V = Barrier i will help achieve barrier j; A = Barrier j will be achieved by barrier i; X = Barriers i and j will help achieve each other; and O = Barriers i and j are unrelated. 3.2

Reachability Matrix

The SSIM has been converted into a binary matrix, called the initial reachability matrix by substituting V, A, X and O by 1 and 0 as per the case. The substitution of 1’s and 0’s are as per the following rules: 

If the (i, j) entry in the SSIM is V, the (i, j) entry in the reachability matrix becomes 1 and the (j, i) entry becomes 0.



If the (i, j) entry in the SSIM is A, the (i, j) entry in the reachability matrix becomes 0 and the (j, i) entry becomes 1.



If the (i, j) entry in the SSIM is X, the (i, j) and (j, i) entry in the reachability matrix becomes 1.



If the (i, j) entry in the SSIM is O, the (i, j) and (j, i) entry in the reachability matrix becomes 0.

After incorporating the transitivity’s in initial reachability matrix the final reachability matrix is shown in Table 3.Transitivity of the contextual relationship is a basic assumption is ISM which states that if element A is related B and B is related to C, then A is necessarily related to C. The driving power and dependence of each barrier are also shown. Driving power of each barrier is the total number of barrier (including itself), which it may help achieve. On the other hand dependence is the total number of barrier (including itself), which it may help achieving it. 3.3

Level Partitions

From the final reachability matrix, the reachability and antecedent set for each barrier are found [22]. The reachability set consists of

the element itself and other elements, which it may help achieve, whereas the antecedent set consists of the element itself and the other elements, which may help achieving it. Then the intersection of these sets is derived for all elements. The element for which the reachability and intersection sets are same becomes the top-level element in the ISM hierarchy. Once the top-level element is identified, it is separated out from the other elements, and the same process is repeated to find the next level of element. This process continues till the levels of each element are found. 3.4

ISM Based Model Building

The ISM model is developed with the help of partition level arrived in section 3.3 and the final reachability matrix generated in section 3.2. The level partitioning provides the hierarchy and the reachability matrix provides the interrelationship among the various barriers. A relationship between the barriers i and j is shown by an arrow which points from i to j if barrier i promotes barriers j and viceversa. If i and j are interdependent on each other then there Barriers 1 2 3 4 5 6 7 8

Barriers 1 1 0 0 0 0 0 0 0

2 0 1 0 0 0 0 0 0

3 1 1 1 1 0 1 0 0

4 1 1 0 1 0 1 0 0

5 1 1 1 1 1 1 0 0

6 1 1 0 1 0 1 0 0

7 1 1 1 1 1 1 1 0

8 1 1 1 1 1 1 1 1

9 1 1 1 1 1 1 1 1

Driving 10 11 12 13 14 15 16 Power 1 1 1 1 1 1 1 15 1 1 1 1 1 1 1 15 1 1 1 0 0 1 1 10 1 1 1 0 0 1 1 12 1 1 1 0 0 1 1 9 1 1 1 0 0 1 1 11 1 0 0 0 0 1 1 6 1 0 0 0 0 1 1 5

9

0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 1

5

10 11 12 13 14 15 16

0 0 0 0 0 0 0

5 8 8 14 14 2 1

0 0 0 0 0 0 0

0 0 0 1 1 0 0

0 0 0 1 1 0 0

0 0 0 1 1 0 0

0 0 0 1 1 0 0

0 1 1 1 1 0 0

1 1 1 1 1 0 0

1 1 1 1 1 0 0

1 1 1 1 1 0 0

0 1 1 1 1 0 0

0 1 1 1 1 0 0

0 0 0 1 1 0 0

0 0 0 1 1 0 0

1 1 1 1 1 1 0

1 1 1 1 1 1 1

1 1 7 6 8 6 11 14 14 14 10 10 4 4 15 16 Dependence Table 3: Final reachability matrix.

452

End of Life Management - Selected Applications 16 15

1, 2 13, 14 Independent 4, 6

14 13

Driving Power

12

Linkage

11 10

3

9

5 11, 12

8 7

Autonomous

Dependent

6

7 8,9, 10

5 4 3 2

15

1

16 1 2

Figure 1: ISM based model of barriers to RL. will be a double headed arrow showing this interrelationship. The final ISM model of barriers to RL is shown in Figure 1. 4 RESULTS AND DISCUSSION An analysis of Figure 1 shows that lack of awareness, lack of laws, legislations and supportive economic policies are the critical barriers affecting all other barriers to the implementation of reverse logistics in India. Both these barriers are related to the government. All the three barriers related to the government are at the bottom of the model so it can be said that the implementation of RL in India need to be initiated by the government for its successful adoption. Next in hierarchy are the economical barriers which are influenced by the government and in turn influence the top management commitment. Organizational and market related barriers promotes each other (see Figure 1) as lack of strategic planning by the organization(organization barrier) promotes stochastic returns and lack of enthusiasm to market remanufactured products (market related barriers), which further promotes the lack of company policies about reverse logistics (organizational barrier). Implementation of RL without structured company policies generally leads to non availability of technology and information systems, resistance to change and non-existence of training and education programmes for employees. Lack in support by supply chain partners and performance metrics are last in the hierarchy of barriers. The barriers are classified into four clusters, as shown in Figure 2, based on their driving power and dependency for the easy understanding and prioritizing the actions to mitigate these barriers. The first cluster consists of the “autonomous barriers” that have weak driving power and weak dependence. These barriers are generally disconnected from the system. In this case there are no autonomous barriers. Second cluster consists of the “dependent barriers” having weak driving power but strong dependence. All the four market related barriers and four organizational barriers are in this category which reflects that these barriers do not influence other barriers and less priority can be assigned to these for the

3

4

5

6

7 8 9 10 11 12 13 14 15 16 Dependence

Figure 2: Driver power–dependence diagram. successful implementation of RL. The third cluster consists of “linkage barriers” having strong driving power and strong dependence. Fourth cluster includes the “independent barriers” having strong driving power but weak dependence. These are the key barriers to be mitigated first on priority. All government related and economical barriers fall in this category. Lack of top management commitment and lack of strategic planning are also independent barriers. Lack of top management commitment influences all other organizational and market related barriers. 5

SUMMARY

This paper identifies 16 barriers classified into four categories – economical, organizational, government related and market related – hindering the implementation of RL in Indian industry through literature survey and discussion with practitioners and academicians working in this field. An ISM model has been developed to study the hierarchy and interrelationship among them. The developed model gives a visual and quick understanding to the decision maker to mitigate these barriers. The lack of awareness, laws, legislation and supportive economic policies are at the base of the model influencing all other barriers. Hence government has to bring laws and legislations in addition to provide economic incentives to start the implementation of RL by formal sector in India. However, this model has been developed with the discussion with few Indian practitioners and academicians working in reverse logistics/reverse supply chain areas and it need to be further statistically tested by empirical studies to validate the different barriers and to find their degree of influence. Further studies can be carried out in different industry sectors. 6 [1]

REFERENCES Sasikumar, P., Kannan, G. (2008): Issues in Reverse Supply Chain, Part 1: End-of Life Product Recovery and Inventory Management- an Overview, in: International Journal of Sustainable Engineering, Vol.1, No. 3, pp. 154-172.

End of Life Management - Selected Applications [2]

[3]

Presley, A., Meade, L., Sarkis, J. (2007): A Strategic Sustainability Justification Methodology for Organizational Decisions: A Reverse Logistics Illustration, in: International Journal of Production Research, Vol. 45, Nos.18-19, pp. 4595-4620. Srivastava, S.K., Srivastava, R.K. (2006): Managing Product Returns for Reverse Logistics, in: International Journal of Physical Distribution & Logistics Management, Vol. 36, No. 7, pp. 524-546.

[4]

Ravi, V., Shankar, R. (2005): Analysis of Interactions Among the Barriers of Reverse Logistics, in: Technology Forecasting and Social Change, Vol. 72, pp. 1011-1029.

[5]

Hicks, C., Dietmar, R., Eugster, M. (2005): The Recycling and Disposal of Electrical and Electronic Waste in China— Legislative and Market Responses, in: Environmental Impact Assessment Review, Vol. 25, pp. 459– 471.

[6]

Thierry, M., Salomon, M, Van Nunen, J., Van Wassenhove, L. (1995): Strategic Issues in Product Recovery Management, in: California Management Review, Vol. 37, No. 2, pp. 114135.

453 [18] Pokharel, S., Mutha, A. (2009): Perspectives in Reverse Logistics: a review, in: Resources, Conservation and Recycling, Vol. 53, pp. 175-182. [19] Chapman, R.L., Corso, M.(2005): From Continuous Improvement to Collaborative Innovation: The Next Challenge in Supply Chain Management, in: Production Planning & Control, Vol. 16, No. 4, pp. 339-44. [20] Rahimifard, S., Coates, G., Staikos, T., Edwards, C., AbuBaka,r M. (2009): Barriers, Drivers and Challenges for Sustainable Product Recovery and Recycling, in: International Journal of Sustainable Engineering, Vol. 2, No. 2, pp. 80–90. [21] Srivastava, S.K. (2008): Network Design For Reverse Logistics, in: The International Journal of Management Science, Vol. 36, pp. 535-548. [22] Warfield, J.W. (1974): Developing Interconnected Matrices in Structural Modeling, in: IEEE Transcript on Systems, Men and Cybernetics, Vol. 4, No.1, pp. 51-81. [23] Sage, A.P. (1977): Interpretive Structural Modeling: Methodology for Large-Scale Systems, McGraw-Hill, New York, pp. 91-164.

[7]

Xiaoming Li, Olorunniwo, F. (2008): An Exploration of Reverse Logistics Practices in Three Companies, in: Supply Chain Management: An International Journal, Vol. 13, No. 5, pp. 381–386.

[24] Soti A, Shanker R, Kaushal O.P. (2010): Modeling the Enablers of Six Sigma using Interpretive Structural Modeling, in: Journal of Modeling in Management, Vol. 5, No. (2), pp. 124-141.

[8]

Rogers, D.S., Tibben-Lembke, R.S. (1998): GoingRogers, D.S., Tibben-Lembke, R.S. (1998): Going Backwards: Reverse Logistics Trends and Practices, Reverse Logistics Executive Council, Pittsburgh, PA.

[25] Mohammed, I.R., Shankar, R., Banwet, D.K. (2008): Creating Flex-Lean-Agile Value Chain By Outsourcing: an ISM-based interventional roadmap, in: Business Process Management Journal, Vol. 14, No. 3, pp. 338-89.

[9]

Lau, K.H., Wang, Y. (2009): Reverse Logistics in the Electronic Industry of China: A Case Study, in: Supply Chain Management: An International Journal, Vol. 14, No. 6, pp. 447–465.

[26] Mandal A., Deshmukh S.G. (1994): Vendor Selection Using ISM, in: International Journal of Operation and Production Management, Vol. 14, No. 6, pp. 52-59.

[10] V. Daniel R. Guide, Jr., Srivastava, R. (1997): Buffering from Material Recovery Uncertainty in a Recoverable Manufacturing Environment, in: The Journal of the Operational Research Society, Vol. 48, No. 5, pp. 519-529. [11] Barker Theresa, J., Zabinsky, B. (2008): Reverse Logistics Network Design: A Conceptual Framework for Decision Making, in: International Journal of Sustainable Engineering, Vol. 1, No. 4, pp. 250–260. [12] Stock, J.R. (2001): The 7 Deadly Sins of Reverse Logistics, in: Material Handling Management, Vol. 56, No. 3, pp. 5-11. [13] Van der Laan E., Dekker R., Salomon M., van Wassenhove L. (1999): Inventory Control in Hybrid Systems with Remanufacturing, in: Management Science, Vol. 45, No. 5, pp. 733-747. [14] Fleischmann, M. (2003): Reverse Logistics Network Structures and Design, in: Business Aspects of Closed Loop Supply Chains, Pittsburgh, PA, USA: Carnegie Mellon University Press, pp. 117–48. [15] Inderfurth, K. (2005): Impact of Uncertainties on Recovery Behavior in a Remanufacturing Environment: A Numerical Analysis, in: International Journal of Physical Distribution and Logistics Management, Vol. 35, No. 5, pp. 318–36. [16] Ronad, S., Tibben-Lembke and Rogers (2002): Differences between Forward and Reverse Logistics in Retail Environment, in: Supply Chain Management: An International Journal, Vol. 7, No. 5, pp. 271-282. [17] V. Daniel R. Guide Jr., Luk N. Van Wassenhove (2009): The Evolution of Closed-Loop Supply Chain Research, in: Operations Research, Vol. 57, No. 1, pp. 10-18.

Recycling of LCD Screens in Europe - State of the Art and Challenges 1

2

Stefan Salhofer , Markus Spitzbart Kurt Maurer 1

3

Institute of Waste Management, BOKU University Vienna, Austria 2

KERP Centre of Excellence Vienna, Austria

3

Saubermacher Dienstleistungs AG, Austria

Abstract Screens (monitors and TV-sets) actually undergo a rapid change in technology from cathode ray tubes to flat panel displays. Up until now, only small quantities of flat panel displays have been recorded at waste collection sites. Increasing quantities in the future make an adequate recycling infrastructure necessary. This paper aims to provide basic data on quantities, composition, recycling technology and experience from a case study on economic impacts of liquid crystal display screens recycling. Keywords: WEEE Recycling; Flat Screens; Resources

1

INTRODUCTION

Based on the EC directive (2002/96/EG) on waste electrical and electronic equipment (WEEE directive), in the EU member states take back and recycling schemes for end-of life electrical and electronic appliances have been installed. Among the 10 product categories listed in Annex IA of the WEEE directive, screens are found mainly in category 3 (Information technology) and category 4 (consumer electronics); displays can also be present in category 10 appliances (automatic dispensers). While screens in the past were dominated by CRT-technology (cathode ray tube), since around the year 2000 flat screens started to gain market share. For CRT screens recycling technologies have been established, but the recycling of flat screens is a new challenge for recyclers. In this paper, the material composition of LCD (liquid crystal display) screens is analysed and technologies of dismantling and processing are discussed. The results aim to supply recyclers with data about materials streams they have to handle in the future as well as bottlenecks in the present technology. 2

conservative approach, the same sales figures for monitors and laptops as in 2008 were used. This estimation, see Figure 1, leads to a potential mass of end-of life appliances with LCD screens in 2018 of 569,000 t (equal to 1.2 kg/cap/yr) in EU 25. Year

QUANTITIES AND COMPOSITION OF FLAT SCREENS

Based on literature data for the use phase [3] with 4 years for monitors and laptops and 10 years for TV sets, in 2012 in EU 25 a mass of 231,000 t (equal to 0.5 kg/cap/yr) of appliances with LCD screens will reach the end-of life stage, mainly as monitors and laptops. From 2012 onward LCD TV sets are expected to reach end-of life, but the estimation has a larger uncertainty, as no data on sales figures beyond 2008 are available at the moment. As a

LCD monitors

Laptop PC

0.1

0

40

2001

0.3

10

13

2002

2

26

16

2003

12

78

22

2004

37

104

30

2005

111

135

40

2006

211

166

46

2007

270

187

56

2008

326

198

62

Table 1: Mass of appliances with LCD screens put on the market in EU 25 (in 1000 t) 600

In the last ten years flat screens (LCD and plasma screens) have replaced CRT screens increasingly at the point of sale. Table 1 shows the mass of appliances with LCD screens put on the market in EU 25.

500 400 (1000 t)

Mass was calculated from sales figures for LCD monitors and laptop PCs [1] and LCD TV [2] as well as average weight data [3]. An estimation of the future arising of end-of-life appliances with LCD screens can be made by assuming a typical life expectancy of the product taken from after the date of sale.

LCD TV

2000

300 200

Laptop PC LCD monitors LCD TV

100 0 2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

Figure 1: Estimation of the mass of end-of life appliances with LCD screens in EU 25 (in 1000 t).

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_78, © Springer-Verlag Berlin Heidelberg 2011

454

End of Life Management - Selected Applications

455

Quantities of LCD screens in the municipal waste stream today are much lower than the figures estimated presented here. In Austria, a survey among recycling facilities for WEEE in 2006 [4] revealed a share of 2.8% of LCD appliances in the category “monitors and screens”. Similar figures for Switzerland are reported [5]. In 2007, the Swiss take back system SWICO has collected and recycled 9,200 t of monitors, among these 5% LCD monitors were found. Data in Figure 1 for 2009 for monitors and LCD TV equal to 0.3 kg/cap/yr, while collection quantities from Austria in 2006 and Switzerland in 2007 represent only 0.05 respectively 0.06 kg/cap/yr. To understand the difference between expected and registered mass, it must be considered that collection schemes for WEEE have been built up only since 2005 in most European member states, but by far they do not cover 100 % of the potential. It is estimated [3], that in 2005 only 35% of CRT monitors were collected separately in the European Union; most other product groups showed a collection rate below 40% as well. Secondly, there is not too much practical experience for the length of the use phase of LCD screens, as theses appliances are relatively new on the market. This could lead to an overestimation of the potential mass for disposal. There is very little published data on the material composition of LCD screens. A general composition of LCD monitors is shown in Table 2, but no further information is given about the size or technology of this monitor. Parts of LCD monitors and TV sets were quantified [6]. Here the LC display of a 15” monitor has a mass of 678 g, of which 134 g are assigned to the “LC assembly” (glass, liquid crystals, electrode, alignment layer and spacers) and 544 g to the “film set” (plastics used as diffuser and light guide). Material/component Steel low alloyed

Mass (g/unit) 1771

Aluminium

130

Printed circuit boards

410

Cables

340

Backlight

2

LC display

645

ABS

360

PC

520

PMMA

450

Other plastics

651 total

5279

Rem: ABS … Acrylonitrile butadiene styrene; PC … Polycarbonate; PMMA … Polymethyl methacrylate Table 2: Material composition of LCD monitors (Source: [3]). 3

RECYCLING TECHNOLOGY

For most of the materials from dismantling CRT screens, recycling or disposal paths have been established. This is true for metals (ferrous and non ferrous metals) or metal rich components (cables, printed circuit boards) going to recycling while components containing hazardous substances (as listed in Annex II of the WEEE directive) undergo specific treatment. In Austria, in 2006 13.400 t (equal to 1.7 kg/cap/yr) of screens were processed in 16 plants, in the first stage by manual dismantling, 7 of these plants separated CRTs further [4]. Bottlenecks in recycling of CRT screens are adequate processes for the recycling of plastics and glass. For glass from the dismantling of CRTs a survey of recycling options is given by [8].

Besides the use for the production of new CRTs – which is no expandable path for the future, as the production is decreasing – glass can be used for the manufacturing of ceramic products. The use in ceramic industry to produces glazes was analysed more in detail by [9]. Further options are the use of the glass material as slag-forming constituents in secondary lead of copper mills or the input into secondary copper production with integrated recovery of lead and tin [8]. The use of CRT glass in a Swedish copper mill is described more in detail by [10]. For Japan, [11] report a legal requirement to recycle not only metals such as iron, aluminium and copper, but also glass from CTRs. For the recycling of LCD screen, the situation is similar: while for metals and metal rich materials the recycling and disposal paths are well established, the treatment of the LC displays is still in development. Composition of liquid crystal displays is described by [12] with 87.2% glass, 12.7% plastics and 0.1% liquid crystals. The mass of the ITO layer is about 0.01 %, this estimate is based on a content of Indium of 102 mg/kg [13], when Indium is the major components of the ITO layer. Backlights containing mercury are a component that must be removed in the dismantling process. The hazardous nature of liquid crystals was intensively discussed. Data and results of toxicological and eco-toxicological investigations by Merck, a major producer of liquid crystals lead to the conclusion, that liquid crystal substances produced today are neither classified as toxic, mutagenic, skin or eye irritating. Further no ecotoxicological effects were observed [14]. Nevertheless, in Austria LCD panels are classified as hazardous waste (FestsetzungsVO, see http://www.umweltnet.at/article/articleview/26426/1/6933 for details). In most cases, LC displays today are disposed of, e.g. by incineration. This leads to a loss of resources. Glass from flat panels, similar to glass from CRT is discussed as input material to produce building materials. [15] investigated the use for its pozzolanic behaviour in concrete, but this paper neither analyses the recovery of other materials form liquid crystal panels nor potential emissions. Further glass from LCD panels was analysed for its use to fabricate glass ceramics by sintering [16]. A further material relevant for recycling from liquid crystal panels is Indium. It is used as Indium tin oxide (ITO), typically consisting of 80 to 90% In2O3 and 10 to 20% SnO2 by mass [7]. Indium is a scarce resource, with estimated global reserves of 2800 t in 2006 (11000 t in 2007) and an annual consumption of 510 t in 2007 [17]. The trend in consumption is increasing, as Indium is not only used in liquid crystal displays, but is also essential for photovoltaic components. For 2030, [17] estimate an annual consumption of more than 1900 t. The production of Indium is concentrated on a few countries; China, South Korea, Canada and Japan in total have a share of more than 85% in 2007. Recycling of Indium today mainly takes place from ITO scrap in manufacturing, where 70% are recovered [7]. Recycling of Indium from end-of life products is not state of the art today, but considering the scarcity and significance of this material, recycling could be a promising source for the European industry. [7] describe technological options to recover Indium from LCDs in mobile phones: hydrometallurgical processes, pyrometallurgy and chloride induced vaporization are potential approaches. A more comprehensive procedure for the recycling of LC panels is given by [13] to recover Indium and other valuable materials. It includes a dismantling process to separate films, the removal of liquid crystals through ultrasonic washing and the recovery of Indium by acid extraction. A recovery rate of 92% is reported. Although these technologies are not state of the art today, it seems worth to develop is further as a source of secondary Indium.

456

End of Life Management - Selected Applications

Considering the costs of recycling, the manual dismantling step is of specific importance. Beside the optimisation of this process, where also automation is under investigation, cf. e.g. [12] the influence of the product design is crucial. The inclusion of environmental effects already in the design phase is called DfE (design for environment), basic principles are described by [18]. The consideration of recycling steps is known as DfR (design for recycling). Methods using washing machines as a case study are shown by [19], the application of DfR methods for the housing of a PC described by [20] and their application for end of life vehicles is demonstrated by [21]. In Germany, a technical standard (VDI 2243 – Recycling orientated product development, 2002, see www.vdi.de/2243) was developed, to support the design process. 4

Size (diagonal)

21%

17 inch

30%

19 inch

17%

20 inch

11%

The sample material was taken from stocked material at the recycler and comprised LCD monitors and LCD TV-sets. As actually only few end-of life LCD screens are collected from households, most of the sampling material originated from repair activities. Only LCD monitors and TV sets were included in the sample, no plasma display panels or other screens were dismantled in the trial. The size distribution in the sample is shown in table 3. For monitors, size ranged from 15” to 42” with a most frequent size of 17“. The size distribution of the sample seems to be typical compared to sales figures for 2006 [22]. TV sets in the sample reached from 15” to 42” dominated by the size of 32”. This indicates, that the distribution of TV sets is not typical compared to sales figures [2], large appliances are dominating the sample. For the trial, a dismantling plan was developed. As the results should be used to establish a routine dismantling procedure at the recycler, two aspects were of importance: 

to fulfil the requirements from the WEEE directive (removal of materials listed in Annex II like printed circuit boards, liquid crystal displays and gas discharge lamps used as backlights and all PCB-containing capacitors and electrolyte capacitors if larger than 25mm)



to separate materials as marketed after dismantling (separation of ferrous and non ferrous metals, separation of major plastics types, etc.)

After exclusion of incorrect datasets (where the total mass of dismantled fractions deviated more than 5% from the input mass) a total of 47 datasets for LCD monitors and 41 of LCD TV was obtained. The average material composition of both types of products is shown in Table 5. Both monitors and TV sets had a metal content (ferrous metals, aluminium and cables) larger than 45%, printed circuit boards as a valuable material had a content of 8.1% (monitors) respectively 6.1 % (TV sets). The share of gas discharge lamps as backlights was 0.3% (monitors) respectively 1.1 % (TV sets). In this trial, capacitors were not separated from the printed circuit boarding and are included in the mass of printed circuit boards. As potential valuable and marketable plastics PMMA from the film sets, ABS and PC-ABS (Polycarbonate - Acrylonitrile butadiene styrene) as housing materials were identified.

LCD TV 2% 2%

21 inch

2%

22 - 23 inch

9%

27 - 29 inch

4%

20%

32 inch

4%

51%

40 inch

CASE STUDY: ECONOMIC FEASIBILITY

In order to gain more information about the economic feasibility of LCD screens recycling, in 2009 an analysis was undertaken in cooperation with Saubermacher (a recycling company in Austria) and KERP Centre of Excellence Vienna. Material composition for a sample of LCD screens was investigated in dismantling trials. For specific material outputs, a market research was undertaken and costs and revenues of dismantling and recycling were calculated.

LCD Monitors

<15 inch

42 inch total

17% 2%

7%

100%

100%

Table 3: Sample of the dismantling trials by size distribution (diagonal in inches). No statistical evaluation was undertaken as the sample was taken from the stock at the recycler and is not representative for the future waste stream. The average material composition of monitors, as a share of the total weight for each analysed appliance was compared with the literature data [3] and is shown in table 4 and can be seen to be similar for metals, printed circuit boards and plastics. Besides the material balance, in the trial the dismantling time was recorded per unit. Monitors in average needed 18 min per unit, ranging from 10 min to 35 min. TV sets took in average 24 min per unit, ranging from 14 min to 40 min. Based on the average dismantling time from the dismantling trial and potential revenues for the material output, a cost and profitability assessment was undertaken. While for most materials like metals prices from the recycler’s daily business were available, for plastics from flat screens a market survey was undertaken by mid of 2009. After a first contact with six recycling companies in Europe specialised in plastic recycling, photographs and material samples were sent to the recyclers. Finally three recyclers provided prices for PMMA, ABS and PC-ABS, all without flame retardants for pickup at the dismantling facility.

Material groups Metals

Dismantling trials 473

Literature data 425

Printed circuit boards

81

78

LC displays

81

122

Backlight Plastics total

3

0,4

362

375

1000

1000

Table 4: Comparison of composition of LCD monitors by material groups from dismantling trials and literature data (Source: [3]) in kg/t.

End of Life Management - Selected Applications

457

Composition monitors

Composition TVsets

Revenues/costs

Revenues monitors

(kg/t)

(kg/t)

(€/kg)

(€/t)

Ferrous metal

Revenues TV-sets (€/t)

409

535

0,04

16

21

Aluminium

52

6

0,55

29

3

Printed circuit boards

81

61

2,00

163

122

Cables

11

9

0,70

8

7

3

11

-0,70

-2

-8

81

77

-0,60

-49

-46

120

179

0,13

16

23

Backlight LC display ABS PC-ABS

0,13

6

124

43 17

0,15

19

5

43

0,05

0

2

20

36

-0,16

-3

-6

50

26

-0,16

1000

1000

PMMA PS Other plastics Plastics (FR) total

2

-8

-4

194

117

Table 5: Material revenues from dismantling output of LCD monitors and LCD TV. Rem: PS … Polystyrene; Plastics (FR) … Plastics containing flame retardants. Potential revenues for PMMA ranged from 74 to 330 €/t, an average value of 150 €/t was used for further calculations. For ABS, the range of revenues reached from 120 to 132 €/t (in average 130 €/t), while for PC-ABS revenues ranged from 92 to 135 €/t, in average 130 €/t were assumed. Material revenues for 1 t of monitors and TV-sets based on material composition from the dismantling trials are shown in table 5. In this calculation, positive values mean material revenues, while negative values stand for costs of disposal. For LC displays, cost of 600€/t are displayed, as this component is actually treated in an incinerator for hazardous waste, although valuable materials like Indium und potentially valuable LC materials are contained.

disassembly costs, but such systems to date are subject of research, cf. [12] and not state of the art.

For the calculation of dismantling cost, an hourly rate of 18€, incl. an overhead of 25 % was used. This is a simplified approach that does not include the installation of a dismantling workplace and the storage of the appliances. Dismantling costs per t of monitors and TV-sets from the case study are shown in table 6. A balance of costs and revenues is given in table 7. Both for monitors and TVsets, costs of dismantling were considerably higher than material revenues. Labour costs were a main cost factor in the dismantling process. In the trials, specifically the removal of the fragile backlights took much time in the dismantling process.

Table 7: Balance of costs and revenues for LCD monitors and TVsets.

Dismantling time

Average weight

Dismantling costs

(min/unit)

(kg/unit)

(€/t)

Monitors

18

5,7

-948

TV

24

15,1

-477

Table 6: Dismantling costs for monitors and TV-sets. Costs and revenues shown here are valid for this trial, which took place mid of 2009 in Austria and are are representative of that time. As material revenues can change considerably over time and labour costs may be different in other regions this can lead to a different balance. Nevertheless at the moment is seems unrealistic, that material revenues cover the costs of dismantling. Automated disassembly systems for flat screens could be an approach to lower

Monitors Material (€/t)

TV

revenues

Dismantling (€/t)

194

117

-948

-477

costs

total (€/t)

-755

-359

total (€/unit)

-4,30

-5,43

5

CONCLUSIONS

A lack of data on future quantities and material composition of endof life LCD screens is an obstacle for the planning of recycling infrastructure. Data gained in this case study are not representative for the typical appliances to be recycled in the future, although they show the general trend. Costs of dismantling and recycling today are not covered by material revenues. Costs of dismantling may decrease by optimisation of the work flow, and material revenues have shown to be changeable through the last years. However, it seems more realistic, that within European Union cost have to be covered by the producers due to their obligation from the WEEE directive. When liquid crystal displays today are disposed of in Europe, valuable and scarce materials like Indium are no longer available. Considering the strategic importance of such materials – Indium is a crucial material in photovoltaic technology – the development of a recycling infrastructure in Europe seems to be useful and urgent. 6 [1]

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[2]

Öko-Institute and Fraunhofer IZM (2007). Final report EuP study Lot 5 task 2. See http://www.ecotelevision.org for details. Accessed 26/04/2010.

[3]

Huismann J., Magalini F., Kuehr R., Maurer C., Ogilvoe S., Poll J., Delgado C., Artim E., Szlezak J and Stevels A. (2007). Review of Directive 2002/96 on Waste Electrical and Electronic Equipment (WEEE), Final Report.

[4]

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[5]

Braendli P.: Green Swico http://www.swicorecycling.ch for 23/06/2010

[6]

Lee S.J. and Cooper J. (2008). Estimating Regional Material Flows for LCDs. Proceedings of the IEEE International Symposium on Electronics and the Environment, May 2008. See http://sisfur.coa.gatech.edu/download/Estimating_Regional_Material_Flows_for_LCDs_ISEE.pdf for details. Accessed 12/05/2010.

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Angerer G., Marscheider-Weidemann F., Erdmann L., Scharp M., Handke V., Marwede M. (2009). Rohstoffe für Zukunftstechnologien (Resources for future technologies). Project report. See http://www.bmwi.de/BMWi/Navigation/Energie/rohstoffpolitik.html for details. Accessed 26/04/2010.

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[19]

Park P.-J., Tahara K., Jeong I.-T., Lee K.-M. (2008). Comparison of four methods for integrating environmental and economic aspects in the end-of-life stage of a washing machine. Resources, Conservation and Recycling Vol. 48, pp. 71–85.

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Masanet E., Horvath A. (2007). Assessing the benefits of design for recycling for plastics in electronics: A case study of computer enclosures. Materials and Design Vol. 28, pp. 1801–1811.

[21]

Santini A., Herrmann C., Passarini F., Vassura I., Luger T., Morselli L. (2010). Assessment of Ecodesign potential in reaching new recycling targets. Resources, Conservation and Recycling Vol. 54, pp. 1128–1134.

[22]

Kernbaum S., Franke C. and Seliger G. (2006). Flat Screen Monitor Disassembly and Testing for Remanufacturing. Proceeding of the 13th CIRP International conference on life cycle engineering, pp. 435 – 440.

Recycling. See details. Accessed

Takahashi K., Sasaki A., Dodbiba G., Sadaki J., Sato N. and Fujita T. (2009). Recovering indium from the liquid crystal display of discarded cellular phones my means of chlorideinduced vaporization at relatively low temperature. Metallurgical and Material Transaction A. Vol. 40A, pp. 891 – 900.

[8]

Bipro (2006) Verwertungsmöglichkeiten von Bildröhrenglas aus der Demontage von Elektroaltgeräten (Options for the recycling of screen glass from dismantling of WEEE). See www.umweltnet.at/article/articleview/43923/1/6932 for details. Accessed 26/04/2010.

[9]

Andreola F., Barberi L., Corradi A., Lancellotti I. (2007). CRT glass state of the art. A case study: recycling in ceramic glazes. Journal of the European Ceramic Society Vol. 27, pp. 1623–1629.

[10]

Mostaghel S., Samulsson C. (2010). Metallurgical use of glass fractions from waste electric and electronic equipment (WEEE). Waste Management Vol. 30, pp. 140 – 144.

[11]

Aizawa H., Yoshida H., Sakai S. (2008). Current results and future perspectives for Japanese recycling of home electrical appliances. Resources, Conservation and Recycling Vol. 52, pp. 1399–1410.

[12]

Kim H.J., Kernbaum S. and Seliger G. (2009). Emulationbased control of a disassembly system for LCD monitors. Int J Adv Manuf Technol Vol. 40, pp. 383 – 392.

[13]

Li J., Gao S., Duan H., Liu L. (2009). Recovery of valuable materials from waste liquid crystal display panel. Waste Management Vol. 29, pp. 2033–2039.

[14]

Martin, R., Simon-Hettich, B. and Becker, W. (2004). Safe Recovery of Liquid Crystal Displays (LCDs) in compliance with WEEE. Proceedings of the Conference Electronics goes green 2004, pp. 147 – 150.

[15]

Lin K.-L., Huang Wu-Jang, Shie J.L., Lee T.C., Wang K.S. and Lee C.H. (2009a). The utilization of thin film transistor liquid crystal display waste glass as a pozzolanic material. Journal of Hazardous Materials Vol. 163, pp. 916–921.

[16]

Lin K.-L., Chang W.-K., Chang T.-C., Lee C.-H. and Lin C.H. (2009b). Recycling thin film transistor liquid crystal display (TFT-LCD) waste glass produced as glass-ceramics. Journal of Cleaner Production Vol. 17, pp. 1499 – 1503.

End of Life Strategies in the Aviation Industry 1

1

1

Jörg Feldhusen , Judith Pollmanns , Jan Erik Heller 1

Chair and Institute for Engineering Design (ikt), RWTH Aachen University, Aachen, Germany

Abstract Until approx. five years ago, it was common practice in the aviation end of life cycle phase to store the vehicles on aeroplane scrap yards. However, this procedure will not be suitable for the predicted amount of aeroplanes. This paper presents an analogy observation of the end of life cycle approaches in the naval, railway and automobile industries and the applicability of process steps to the aviation end of life strategy. In addition to that, relevant economic and ecological drivers of the possible strategies will be shown. Keywords: End of Life Phase; End of Life Vehicles; Recycling

1

INTRODUCTION

2

For a long time recycling has been quite a neglected topic in the aviation industry, as the number of decommissioned aeroplanes was still small. Due to the boom of civil aviation starting in the 1970s and life cycle ranges of approx. 30 years, their amount continuously increases quicker and quicker. After millions of miles and numerous cycles of refurbishment, reconditioning of the aeroplane is no longer worthwhile for the airlines. If it is not resold to a third world airline it can be altered to a cargo plane for the last phase of its utilization, continuing until maintenance and overhaul is no longer worthwhile. It can also be uneconomical to operate a plane, which is out of date, due to high fuel consumption and risen fuel costs. Uneconomic aeroplanes do not even reach the average age. Some experts estimate a number of 2000 decommissioned civil aeroplanes parked and awaiting their final disposal or recycling and in addition to that about 250 aeroplanes a year for the next two decades. Military vehicles are not taken into account. Therefore, the actual number of end of life aeroplanes will actually outrank the mentioned units. [1].

2.1

CURRENT END OF LIFE SRATEGIES IN THE AVIATION INDUSTRY Regulations

Until now, there are no governmental regulations for the handling of end of life aeroplanes. This can be justified by the pretended small amount of occurring waste. The aviation industry is only indirectly affected by existing regulations. Handling of electronic scrap (cf. [3]) as well as handling of hazardous materials and disposed waste have to be carried out according to the existing laws. Composites for example will be a future challenge as they may not be disposed on landfill sites since 2004 and cannot be provided for incineration of refuse due to toxic ingredients. 2.2

Common / previous practice

Common practice in the aviation end of life cycle phase was, until approx. five years ago, the storage on aeroplane scrap yards e.g. in the desert areas of the United States, where enough storage space is available on favourable conditions and where climate conditions (hot and dry) are conserving for the aeroplane. [4]

[Estimated units] [estimated units]

On aeroplane scrap yards, used planes are maintained by authorized personnel until the owner brings them back to service or is able to resell them. Aeroplanes that are not intended to be brought back into service remain without maintenance. By degrees, parts, which can be used as spare parts, are removed until, in the end, only the fuselage remains. There have been incidents of nonserious aeroplane disposal where planes have been demounted and component parts have been disposed in the sea. [1]

1995

2005

2015

2025

2035

[time] [time]

Figure 1: Estimated amount of end of life units in the next decades. Other experts predict slightly different numerical data [2], but all studies commonly estimate an increasing rise for the next decades. Figure 1 qualitatively displays the estimated amount of end of life units in the next decades.

2.3

Further trends and research

Due to the increased number of decommissioned aeroplanes and the image loss feared for, airlines and manufacturers feel the urge to replace the scrap yard disposal. Additionally, the reuse of material e.g. aluminium and avionic systems could counter the increasing cost for raw materials and systems. Especially for third

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_79, © Springer-Verlag Berlin Heidelberg 2011

459

460 world airlines this can be a worthwhile alternative. [1] Today, businesses can be found that are specialised in aeroplane “recycling”. Their processes focus on taking out as many useable parts as possible, always regarding the economical aspect. Like on aeroplane scrap yards, valuable spare parts are sold individually whereas cabin equipment and insulation material, which cannot be reused and are not valuable enough for investment into recycling research, are conventionally disposed. The whole process can only start if the business expects to gain more profit by selling parts individually than it has to pay for the decommissioned plane and the disposal of nonrecyclable materials. [1] As mentioned before, the number of decommissioned aeroplanes is to increase rapidly so that not only the storage on aeroplane scrap yards but also the limitation of recycling to valuable planes will no longer be suitable. Hence, it will be necessary to implement a widely accepted process, applicable to the broad range of decommissioned civil aircrafts. Costs as well as ecological factors have to be considered.

End of Life Management - Selected Applications Different approaches were tested here. Exemplarily, wing sections were shredded as a whole using material separation processes afterwards. Other parts were separated on site and directly provided for recycling; a total sum of 61 tonnes. The remaining 13.5 tonnes, mainly insulation material and casings, could not be recycled and had to be disposed conventionally. Conclusion: The research team demonstrated that a recycling proportion of 60 % is already possible. Due to perfectly sorted material, the secondary aluminium (originating from the recycling process) can be provided in a quality complying with the aviation specifications. Additionally a generic plan of methods, which is not publicly available, has been worked on and enables the industry to dispose and recycle any given aeroplane in an environmentally friendly way and with highest respect to safety measures.

D1: Decommissioning

Servicing: Fuel Water WC tanks

D2: Disassembling

Re-Use: Engines APU Landing Gears Avionics Equipment RAT

In the first place, an overview of two already existing research projects is given, before a detailed analysis of possible analogy observation fields is appended. PAMELA The PAMELA (Process for Advanced Management of End of Life of Aircraft) project, initiated by Airbus, EADS, SITA and the working group “LIFE” (French: l’Instrument Financier pour l’Environnement;) of the European Union in 2005, aimed at designing a process that can be used to recycle and reuse the risen number of decommissioned aeroplanes environmental friendly. An industry amalgamation was to be developed, too, being able to run the process according to existing laws and environmental specifications as well. Here, the handling of spare parts is to be considered additionally so that the risk of bogus parts (parts with unknown origin and fake documents) is avoided. Safe working conditions and political impulses were also expected as an outcome of the research project. As European legislation is expected to enact recycling regulations for end of life aeroplanes in the nearer future one could conclude, that Airbus planned anticipating these laws designing possible models for it on their own.

D3: Dismantling

Non recovered waste: Cabin lining Cargo lining Insulation Miscellaneous wastes

The three step approach (cf. figure 2) for the deconstruction of a reference plane was defined as follows [2], [5]: D1 (decommissioning): The reference plane (A300 B4) with a total weight of 106 tonnes was parked, decontaminated and cleaned. The WC, water and fuel tanks were emptied and the according liquids were orderly disposed or, concerning the fuel, stored for reuse. This process resulted in a total weight of the plane of 88 tonnes, which is the reference weight for the upcoming process steps. D2 (disassembling): All possible spare parts as the APU (auxiliary power unit), avionic systems, the RAT (ram air turbine), the landing gears as well as parts of the cabin equipment (e.g. oxygen masks and inflight entertainment systems) were dismantled. These parts were checked, cleaned, and documented according to existing laws before they were approved for resale. If necessary, they were reworked in advance. Parts that could not be classified airworthy and could not be reworked were immediately destroyed or disabled. A total weight of 13.5 tonnes could be built out for reuse. The remaining 64.5 tonnes (fuselage) was craned on a lifting rack allowing the research team to perform spectral analysis of the remaining parts in order to complete the material plan (location of different materials within the body). Different portable devices were tested for this application. D3 (dismantling): In this process step all used materials should be separated and provided for the according recycling channels.

Valorisation: Fluids Fuselage Wings, Tail Systems Avionics, Wirings Miscellaneous

~15 % Re-Use

~15 % Non recovered waste

~70 % Valorisation

Figure 2: PAMELA three step approach (cf. [5]).

End of Life Management - Selected Applications

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AFRA

3

In contrast to Airbus, Boeing is currently not approaching the whole topic of recycling via the subject of research. Therefore, Boeing founded the Aircraft Fleet Recycling Association (AFRA) in April 2006, in cooperation with more than ten European and American companies. The founding members originated from industries such as waste management, commodity production and aircraft maintenance in addition to suppliers and service providers.

Comparable thoughts, as how to handle the upcoming amount of waste, can be expected for different means of transportation than aeroplanes, where great numbers of decommissioned vehicles already exist. For the analogy observation, first the approaches used in the naval, the railway and automobile industries are presented.

Boeing also is expecting more than 7000 aeroplanes to be disposed in the next twenty years [6]. So, regulatory requirements seem to have been the reason for this establishment. It has been the goal, to found a self-financing nonprofit organisation, whose members work corporately according to a certificate of approval in the area of aircraft vehicle disposal.

In the naval sector life times of 30 or more years are common (average age of 29 years at the time of deconstruction). Afterwards the ships become decommissioned because of being either outdated or unprofitable, due to risen maintaining or repairing costs. In addition to that, ships have to be shut down due to legal regulations. This usually affects a whole type of vessels, like singleshell oil-tankers were prohibited after the “Erika” and “Prestige” accidents in 1999 and 2002.

A directive has been elaborated from already existing sets of guidelines to completely cover the aeroplane end of life process. This document is entitled “AFRA Best Management Practice” (BMP policy) and contains detailed specifications on how to perform each single step in the process of recycling, like handling spare and refurbished parts, recycling different materials, choosing tools and documenting maintenance operations. If this directive is followed, it guarantees that operating companies fulfil their tasks in the most sophisticated way, regarding environmental friendliness and safety. Companies willing to become a member of the AFRA can get accredited. It can then be assured to requesting customers that their aeroplane gets recycled in a correct and ecological way. [7] Right now, over forty enterprises are member of the AFRA, having contracted access to more than half of the world’s installed base of aircraft vehicles and their operators. Furthermore, AFRA currently tries to get their BMP policy accredited by official aviation authorities, especially by the Federal Aviation Administration (FAA) and the European Aviation Safety Agency (EASA). [7] Refurbished and used parts originating from members of AFRA are supposed to be a lot more valuable to aeroplane carriers, since they provide a higher level of security. Just like Airbus, Boeing tries to control the spare part market to eliminate safety risks. [1] An active participation in the process, probably as first level aviation recycler like Airbus (through TARMAC Aerosave), is not intended by Boeing. They see themselves in the role of consulting the AFRA members with their expertise. Moreover, Boeing tries to integrate the results from the ongoing recycling process directly into the development of next generation aircraft vehicles, because they are claiming a holistic, environmentally friendly approach of the entire product life cycle and a responsible way of dealing with natural resources. [6] 2.4

Upcoming challenges

Considering the social interest in climate change and exhaust gas emission, as well as the rising costs of resources, the aviation industry is strongly interested in reducing fuel consumption by means of mass reduction. Both market leaders therefore rig their new plane models with higher proportions of composite materials [8]. Composite recycling however is considerably more complex than the reuse of exclusively metal based materials. Planes, which came to service earlier and will be decommissioned in the near future, usually show a lower rate of composites. As the need to handle composites in the end of life phase is still rare, processes are not yet optimised. Hence, the processes that could now be defined and regulated could hardly include the consideration of composite materials to the extent necessary.

3.1

ANALOGY OBSERVATION

Naval industry

“Ship breaking” usually takes place in shipyards in India, Pakistan and Bangladesh, where safety regulations are far less strict than in Europe. Vessels planned for deconstruction are sold to the shipyard for the price of the included material/steel leaving the former owner without responsibility for the upcoming process. The ship, which is first steered onto the beach at full throttle, is afterwards deconstructed manually at high speed. 95 % of the weight is defined by the steel mass, but it is covered with 10 to 100 tonnes of coating, containing lead, cadmium, TBT, arsenic, zinc and chromium. Other harmful or toxic substances in the vessels are PCB (polychlorinated biphenyl), asbestos, fuel and oil leftovers. These substances are either directly run into the ground or scantily stored. A suitable disposal is not realized. [9] Legally spoken at the time of their disposal, vessels are nothing but waste. According to the Basel Convention hazardous waste must not be processed in countries not being signatory to the convention, e.g. India, Pakistan and Bangladesh. This regulation is consequently flouted. To comply with the IMO convention, which is expected to start in 2013, vessels bigger than a total of 500 gross tonnes have to carry an “Inventory of Hazardous Materials” and shipyards deconstructing the ships have to be authorized by their relevant authority. This convention aims at decreasing environmental damage caused by the “recycling process” and improving the labour conditions in the deconstruction yards. Until now, there is no standardised process that could be adopted for the aviation industry and upcoming regulations have to prove their applicability. 3.2

Railway industry

There is hardly any recycling information available for the railway sector. Especially in Germany “Deutsche Bahn” arranges the disposal of wagons that are no longer required disregarding their condition and value. It can be concluded that a resale to competitors is not aimed for. [10]. There is no special regulation for the treatment of decommissioned railway wagons. They are classified as “waste” and have to be recycled according to the applicable law. Hence, no impulse for the end of life cycle strategy in the aviation industry can be found. 3.3

Automobile Industry

In the EU, 10 mill. tonnes of used cars occur for recycling each year. Due to the great number of concerned objects and the resulting amount of waste, the need for action was considerably higher here than in the aviation industry [11]. The recycling and disposal of cars is extensively regulated in the European Union as well as in the United States.

462

End of Life Management - Selected Applications

It is common practice to first destroy the pyrotechnical elements such as airbags and belt pretensioners and then dry up the car by extracting all liquids from it. These liquids are professionally disposed if reuse is not possible. Afterwards, all reusable components as engines, transmission systems, electric and electronic systems or body parts are removed. [12] Even though most of the elements within the end of life cars could be reused, due to economic, logistic or other reasons, limitations occur. Typical procedures for the different components can be found within most of the recycling processes [12]: 

Electro-mechanic parts are usually remanufactured and resold.



Structural body parts are usually used in repairing accidentdamaged vehicles.



Aluminium and copper parts are sold to nonferrous processors or the nonferrous scrap market.



Vehicle fluids like oil, transmission fluid etc. are recycled. [12]



…

For the remains the material recycling process is applicable, following the rules and regulations given. [13] Exemplarily an excerpt of the German regulation is presented here, which is said to be precedential for future regulations in different sectors [14]. The applicable law (“Verordnung über die Überlassung, Rücknahme und umweltverträgliche Entsorgung von Altfahrzeugen”, Regulation for the surrender, acceptance of returned goods and the environmentally compatible disposal of end of life vehicles) was enacted in 1998 and regulates the entire process of disposal, the retirement of the car, the authorisation of the recycling firm, the acceptable documentation and the handling of different materials. The recycling margins to be achieved are also mandatory. The quintessence of the regulation is: 

Manufacturers have to accept end of life vehicles back without charge starting in 2002.



Starting in 2006, 85 % of the vehicles’ weight has to be recycled, with a minimum of 80 % of actual reuse, these values increase to 95 % and accordingly 85 %.



Starting in 2003 manufacturing has to avoid lead, cadmium, chromium and mercury. [15]

3.4

Comparison of approaches and applicability

Neither the end of life approach in the naval industries nor in the railway sector can be seminal for the following process application in the aviation industry. Both vehicles are considered “waste” in their end of life and are supposed to be disposed accordingly, even though the naval industry still has to remedy process defects. Especially the naval industry faces, in some points, similar challenges, e. g. the paint stripping and the environmentally friendly disposal of the occurring coating, but as the newly enacted laws have to show there applicability first, suggestions for the aviation sector are not due. However, the automobile industry can be seen as a model for the aviation industry when it comes to end of life vehicles as the given processes resemble. In both sectors, the end of life vehicle is, first of all, released of all potentially harmful objects, as pyrotechnical objects. In a second step, all liquids are extracted and the vehicle is drained. If possible, these liquids are stored for reuse or have to be disposed. Spare parts, which might have to be reworked, are extracted from the vehicles and made available to the spare part market afterwards. As a next step, all used materials are prepared for recycling or disposal. They are removed, separated and enter their common recycling processes. With regard to recycling, both industries in general face comparable challenges as for example

recycling materials to a quality that permits a reuse in the same use case with the same specifications. Autobody sheets for example can only be used as construction steel if recycled as specifications for the primary use case cannot be met anymore [14]. Additionally the use of composite increases in the automobile industry as well as is does in the aviation industry. Suitable recycling processes have to be designed for these materials, e.g. a way to costeffectively and ecological friendlily recycle them must be found [16]. But not only similarities can be found. There are important differences apparent. Due to the conducted studies in the PAMELA and AFRA projects, the possible process (that can surely be optimized) is well known but as mentioned before it is, until now, only realised if it is considered profitable. For aeroplane types whose spare parts are not in demand it can be expected that they will, again, be stored on aircraft scrap yards. A regulation of the responsibilities for processes as well as costs would, in analogy to the automotive sector, avert this behaviour. The main points of the automotive regulation, as mandatory proportions of recycled materials, the responsibilities within the recycling process and the avoidance of harmful materials (cf. [15]), can certainly be adapted to the aviation industry; whereas other crucial parts have to be considerably changed. For example, the handling of spare parts differs in both sectors. They are closely monitored and traceable during their lifetime in the aviation industry which has to be considered for the recycling regulation. In the automobile industry the spare parts are less relevant to security than here and are therefore monitored less closely and not traceably. As OEMs are responsible for the end of life vehicle recycling, they consider this phase of the lifecycle in detail during the design of new models simplifying future deconstruction. As safety reasons have a greater regulative role in the aviation industry these simplifications are not necessarily possible. Even more tests and verification activities than in other sectors have to be realised if considerable changes are planned. This characteristic has to be considered when designing the process and regulation. Even though not all aspects of the regulation for end of life vehicles can be adapted for a new aviation regulation, it can surely be used as a model regulation and guideline. Additionally the designed process can show weak spots in the upcoming processes in advance. 4

ECONOMIC AND ECOLOGICAL DRIVING FORCES IN THE END OF LIFE PROCESSES

Defining a process applicable to all reuse processes concerning end of life aeroplanes is constrained by economic and ecological limitations. Environmentally optimal processes run the risk of being to complex and costly, binding funds and therefore inhibiting the research on new aeroplanes, which are possibly more eco-friendly during service. As opposed to that, economically optimised processes might not cope with the responsibility for our planet, jeopardising the environment. Hence, it is necessary to identify the driving forces of both aspects in order to define processes giving the industry the opportunity to handle end of life vehicles eco-friendly without losing its ability to compete on the market. Synergy effects have to be demonstrated to optimize the process in both ways. It is important that the handling of planes that face decommissioning now or in the near future is considered as well as new models that entered the market recently or are currently

End of Life Management - Selected Applications developed. Impulses for new developments are to be given additionally. 4.1

Environmental driving forces

Looking at the recycling process from the environmental point of view there are obvious drivers apparent. Examples are provided in the following: Aluminium Until now, in most cases 60 to 80 % of the aeroplane structure consists of aluminium alloys, causing a total production need of 192000 tonnes in 2008. It can be won from bauxite, which is transformed to alumina. After fused-salt electrolysis primary aluminium is available. Multiple studies calculated a total energy consumption of the described process of 188.2 to 257 MJ/kg primary aluminium [17], [18], [19]. As opposed to primary aluminium the production of secondary aluminium only needs 5 to 10 % of the reference energy quantity. Hence, it is crucial to emphasise the mono-material sortation of aluminium to recycle in order to achieve an acceptable quality of secondary aluminium. But not only the reduction of energy consumption, when using recycled aluminium, is an advantage. The avoidance of red mud, which contains heavy metals, as for example arsenic and lead [20], emphasises the importance of recycled aluminium. Contamination of soil A decommissioned aeroplane contains fuel and oil leftovers, which have to be handled carefully. There are already regulations for the disposal of these liquids, but their extraction from the vehicle and their storage has to be anchored in the deconstruction process. Titanium For the generation of titanium, titanium tetrachloride (TiCl4) is gained form the minerals rutil or ilmenite. The acceptable temperature range for the chemical transformation process is 850 to 950 degrees Celsius and a batch of 10 tonnes of titanium tetrachloride needs about 10 days to transform to titanium [21]. Long processing times and high process temperatures cause vast energy consumption. The energy intensity of titanium is 50 % higher than the aluminium energy intensity. Recycling of titanium is comparatively unproblematic. Due to the enormous energy consumption it should surely be embedded in the regulated end of life process. Emphasis must be put on the monomaterial sortation, again.

463 that can be accepted for ambitious applications and aviation specifications [22], but research is ongoing here. Research has to be fortified in this field, so that the expectable amount of composites (e.g. 50 % of the Boeing 787’s weight consists of composites) can be handled ecologically worthwhile. Coating As described in the naval deconstruction process (cf. 3.1), coating can contain numerous hazardous and toxic ingredients. For the material recycling process, metal based material has to be perfectly sorted, obliging the recycling organisation to remove the coating. The removal process can produce toxic dust, contaminating the environment or endangering the personnel. Hence, a safe process and storing regulation has to be defined here. 4.2

Economic driving forces

For a suitable process the economic drivers have to be considered as well. Here, too, factors with strong impact are apparent: Labour costs Great parts of the assembly as well as disassembly processes in the aviation industry are carried out manually and certified personnel are mandatory for many steps. As automation does not seem suitable for the varying process, its steps must be optimised in order to minimise the working effort. Nevertheless, labour costs are expected to be a main cost driver in the process. Costs for disposal of nonrecyclable and hazardous materials Even with optimised processes and new regulations, recycling will not be possible for all used materials (cf. 3.3, mandatory recycling proportion in the automobile industry). In the end, there will be parts, which have to be disposed conventionally causing fees and expenses. Those will also occur, in increased dimensions, for the handling of hazardous materials. Documentation costs Each part that is linked to the airworthiness of an aeroplane has to be permanently traceably and working steps, performed at the parts, also have to be documented. If end of life vehicles are used as suppliers for spare parts, their deconstruction has to be documented and the storage of reusable parts will be more complex. This additional demand on documentation does not solely increase the working effort, but also the documentation itself causes costs as e.g. data storage. Documentation based costs are expected to have a noteworthy effect on the total process costs.

Insulation material Insulation material is an important part of the interior trim. But there is no recycling process for it by now. Disposal is realised on landfill sites or, depending on its calorific value, by incineration of refuse. Considering the amount of waste (cf. 2.3, PAMELA, step D3) ongoing research is necessary here. The future regulation should encourage the industry to either find ways to recycle the isolation material or think of alternative materials for the development cycles to come. Electronic components Handling of electronic scrap (cf. [3]) is already regulated and has to be applied on aeroplanes as well. Nevertheless, its handling has to be mentioned in a prospective regulation, too, since hazardous materials such as lead, cadmium or mercury can be integrated. Composite Materials Composite materials are the “rising star” of aviation materials. So their occurrence will increase tremendously in the future. [8] But it has not yet been possible to define an operational recycling procedure for glass or carbon fibre laminates, resulting in a quality

5

CONCLUSION AND FURTHER RESEARCH

The end of life phase of aeroplanes can no longer be neglected as the amount of decommissioned planes is going to increase considerably in the future. It has not yet been legally regulated even though several specialised laws have to be applied here already. There has been research carried out by the two market leaders Airbus and Boeing supplying the legislator with facts and knowledge about possibilities and limitations of the aircraft end of life process for the prospective development of a regulation. These research programmes clearly showed the recycling potential of aeroplanes using different approaches. The proclaimed goal of an eco-friendly process can unfortunately not be used as a base for further research, as it is not fully released. The analogy observation demonstrated that only the automotive industry can be considered when modelling the aviation process. General process steps and recycling challenges are similar, so that lessons learned in the automobile industry can be applied to the aviation sector, of course with the adjustments necessary. Neither

464

End of Life Management - Selected Applications

the general naval nor the railway industry provides valuable impulses for the process definition. Several economical drivers as well as cost drivers were presented as both aspects are crucial to the definition of the end of life strategy and have to be considered. The demonstrated factors can neither represent the entire process nor life cycle phase. For further insight, the process first has to be generically defined without bias. Each process step has to be analysed for possible drivers either economically or ecologically relevant and the interdependences have to be identified. Knowing the determinant factors the process has to be optimised in both directions. 5.1

Project reference

This study is embedded in an interdisciplinary research project that aims at analysing the entire life cycle of a civil aircraft starting with the conceptual design and ending with its disposal. Each phase of the life cycle is evaluated considering the three pillars of sustainability, to wit economic, ecological and social impact subject to the defined requirements. Using a modular concept, an evaluation methodology will be developed offering parameter and sensitivity studies for optimisation.

[12] Staudinger, J., Keoleian, G. A. (2001). Management of Endof-Life Vehicles (ELVs) in the US, University of Michigan, available online: css.snre.umich.edu/css_doc/CSS0101.pdf [13] Funazaki, A.; Taneda, K.; Tahara, K.; Inaba, A. (2003). Automobile life cycle assessment issues at end-of-life and recycling, JSAE, Vol. 24, No.3, pp. 381-386 [14] Weiner, M. (2002). Werkstoffe auf Rädern, Fraunhofer Magazin weiter.vorn, No. 3.2002, pp. 52-54 [15] German Ministry of Justice (2002). Altfahrzeug-Verordnung in der Fassung der Bekanntmachung vom 21. Juni 2002 (BGBl. I S. 2214), die zuletzt durch den Artikel 1 der Verordnung vom 9. November 2010 (BGBl. I S. 1504) geändert worden ist, 2010. German Ministry of Justice [16]

Deffke, U. (2010). Auch Stabile Kohlefaser lassen sich wiederverwerten, Stuttgarter Zeitung 04.01.2010, Stuttgarter Zeitung Verlagsgesellschaft mbH, Stuttgart

[17] Song, Y. S., Youn, J. R.; Gutowski, T. G. (2009). Life cycle energy analysis of fiber-reinforced composites, Composites Part A: Applied Science and Manufacturing, Vol. 40, Issue 8, pp. 1257-1265

The project is supported by the funds of the German excellence initiative of the federal and state government.

[18] Stiller, H. (1999). Material intensity of advanced composite materials. Wuppertal Institut für Klima, Umwelt, Energie GmbH, Wuppertal

6

Jahanshahi, S.; Rankin, W. J. (2006). [19] Norgate, T. E.; Assessing the environmental impact of metal production processes. Journal of Cleaner Production, Vol. 15, Issues 8-9, pp. 838-848

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Pamela (2008). PAMELA Life Training Kit, available online: www.pamelalife.com/english/results/Pamela-TrainingKitEnglish.pdf

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European Parliament (2009). Directive 2002/96/EC of the European parliament and the council of 27 January 2003 on waste electrical and electronic equipment

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Harbison, I. (2009). Aircraft recycling: A cut above, available online: www.afraassociation.org/NewsDocs /09_Dec_MRO%20Management.pdf

[8]

Michaels, K. (2009). Outlook for Aerospace Raw Materials, 3rd Annual AMM Aerospace Metal Conference. Pittsburgh, AeroStrategy Management Consulting

[9]

Bernsstortff, A. (2004). Gefahren bei der Schiffsabwrackung – Verschrottung von Hochseeschiffen – Ein globales Umweltund Gesundheitsproblem, available online: www.greenpeace.de/themen/chemie/schiffsabwrackung/a rtikel/gefahren_bei_der_schiffsabwrackung/

[10] Krieger, R. (2009). Endstation Opladen – Lokomotiven hinter Stacheldraht, Kölner Stadtanzeiger, 31.03.2009, Expedition der Kölnischen Zeitung GmbH & Co KG, Colonge [11] Martens, H. (2011). Recyclingtechnik, Spektrum Akademischer Verlag, Heidelberg

[20] Umweltbundesamt (2010). Unfall im Ungarischen Aluminiumwerk: Fragen und Antworten zu den Umweltauswirkungen, Umweltbundesamt GmbH, Wien, available online: http://www.umweltbundesamt.at/aktuell/presse/ lastnews/newsarchiv_2010/news101012/ [21] Oi, T.; Okabe, T. H. (2007). The 3rd Workshop on reactive Metal Processing: Fundamental Study on Titanium Production Process by the Disproportionation Reactions of Titanium Subchlorides, Institute of Industrial Science, The University of Tokyo, Tokyo [22] Horwitz, D. (2007). The end of the line – aircraft recycling initiatives, Aircraft Technology engineering & maintenance; Issue 87, pp. 28-33

Contribution of Recycling Processes to Sustainable Resource Management 1

Alexandra Pehlken , Klaus-Dieter Thoben 1

1

Institute for Integrated Product Development, Bremen University, Bremen, Germany

Abstract Many raw materials are restricted and far away from being endless available; therefore there is a strong intention of developing raw material- and energy-efficient production processes. Recycling processes provide a substantial contribution to sustainable resource management due to the supply of valuable secondary raw materials for new applications. This paper will demonstrate a metamodel strategy that considers these facts and demonstrates a model architecture based on Material Flow Assessment for recycling processes. The case study represents scrap tire recycling. Keywords: Recycling; Material Flow Assessment; Life Cycle Assessment

1

INTRODUCTION

Sustainable resource management can be understood as providing secondary resources derived from recycling processes to be suitable as substitutes for primary resources. This implies a preservation of our raw materials. Raw materials are essential to satisfy our needs in energy and products. Many raw materials are restricted and far away from being endless available; therefore there is a strong intention of developing raw material- and energy-efficient production processes. Recycling processes provide a substantial contribution to sustainable resource management due to the supply of valuable secondary raw materials for new applications. Processing solid waste materials generate new secondary resources from residues as resources for new products. This saves primary resources and keeps up a long material life cycle. Every single recycling process is unique and the input material has a high influence on the process performance. Uncertainties belong to most recycling processes and have to be taken into account during process assessment. To evaluate the potential of secondary resources to substitute primary resources Material Flow Assessment and Life Cycle Assessment respectively are useful methods. Material characterization is also an important issue to look at and needs to be included into the methods. Material properties ascertain the following application possibilities. It has to be noted that no processing technique can guarantee solely material flows with properties to substitute primary raw materials. Material flows of minor quality are present as well. This makes it difficult to assess the future potential of secondary raw materials to be available for following applications with specific quality demands. 2 2.1

MATERIAL FLOW ASSESSMENT (MFA) MFA and Life Cycle Assessment (LCA)

Life Cycle Assessment (LCA) covers the entire lifecycle of a product, process or activity. According to the International Organization for Standardization (ISO), an environmental lifecycle assessment is analyzing the environmental interventions and potential impacts throughout the life (from cradle to grave) from raw material acquisi-

tion through production, use and disposal [1]. During the whole life cycle of products and materials the amounts of materials involved, the inputs of energy and water resources along the life cycle, the amounts of waste materials and the associated environmental impacts all along the product chain have to be assessed. Material Flow Assessment (MFA) clearly is useful here, but it can be only a part of the whole equation. MFA can illuminate the amounts of materials involved and the amount of material waste, but it does not include all the information necessary to assess potential impacts on the environment. With regard to material management MFA must be used in conjunction with other types of data [2]. According to Finnveden [3] the interest in LCA grew rapidly during the 1990s, also when the first scientific publication emerged [4]. Since then a strong development and harmonization has occurred resulting in an international standard [1]. Since there are still open questions while performing LCAs there are several international initiatives to provide recommendations, including the Life Cycle Initiative of the United Nations Environment Program (UNEP) and the Society of Environmental Toxicological and Chemistry [5], the European Platform for LCA of the European Commission [6], and the emerging International Reference Life Cycle Data System. LCA helps decision makers taking into account environmental contribution on the basis of material and energy flows. Material Flow Analysis (MFA) is a systematic assessment of the flows and stocks of materials within a system defined in space and time [7]. It connects the sources, the pathways, and the final sinks of a material. An MFA delivers a complete and consistent set of information about all stocks and flows of a particular material within a system. The MFA can be regarded as a method to establish the inventory for an LCA. A short history of MFA and can be found in Binder [8] and is going back to the roots of the 1960’s to studies on material balances. The publication of Brunner and Rechberger [7] is now established as a textbook in the application of Material Flow Assessment.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_80, © Springer-Verlag Berlin Heidelberg 2011

465

466 2.2

End of Life Management - Selected Applications MFA in Recycling Processes

Material Flow Assessment can be easily applied to recycling processes because is takes into account all material flows entering and leaving the recycling process (system boarder). Since the input in recycling processes is often a mixture of various material streams the exact composition is never known. There is often a lack of information due to unknown parameters in material composition or processing steps [9]. Due to the high potential of recycling processes contributing to a sustainable management of resources (e.g. energy savings and material efficiency) it is necessary to assess the material flows with the regard to their environmental impact [10], [11]. Assessing the material flows involves the characterization of materials and their properties. According to secondary (recycling) materials this is only possible in determining a range of properties values (e.g. water content lies between 5 and 7 %). In general assessing sustainable resource management the following conditions for a reasonable recycling process have to be achieved: 

adequate material mass for the recycling process;



adequate material mass for further product manufacturing;



defined material properties, and



very little variation of material properties.

It is desirable to forecast the above mentioned conditions for choosing processes that fit best to these conditions and achieve therefore a good performance. A rough prediction on material flows, costs and environmental impacts can be assessed through combining the methods Material Flow Assessment (MFA) and Life Cycle Assessment (LCA). While performing an LCA the evaluation of the environmental impact as carbon footprint, water footprint, ecological footprint and others is possible [12], [13], [14]. As mentioned above these methods lack of the description of material properties, their variations and uncertainties respectively. Material flows should rather reflect a fundamental basis than being reduced to the assessment of mass and volume. Future prospects of the quality of secondary resources, including their input and output properties may be helpful to assess their potential to substitute primary resource for example. Information on material properties generated with LCA and MFA can contribute to the product design, the production phase and the recycling performance of a product. Traditional LCA models are static and are not suitable for dynamic modeling. To be able to plan for changes in waste flows, decision-makers require future studies of material flows. A high potential on research work is identified according the field dynamic modeling to forecast material flows with regard to Life Cycle Assessment.

It is evident to see the necessity to develop a dynamic model to consider future studies over multiple years for the assessment of the potential of recycling material flows to substitute primary material flows. 3 3.1

DEVELOPING A MODEL FOR RECYCLING PROCESSES Materials – Scrap tire

The case study for modeling represents the process of scrap tire recycling. Scrap tires have the advantage to consist of a variety of different makes, like winter, summer, all-season, passenger, truck tires and more. But they all consist of the main components rubber, carbon black, steel and fibre. Therefore, they are an ideal product to study. Passenger tires tend to contain more synthetic rubber than natural rubber; truck tires consist of more natural rubber; and off-the-road (OTR) tires, including heavy mining tires as well as agricultural and industrial tires, have nearly no synthetic rubber (Table 1) The rubber composition may be due to the fact that passenger tires have to meet higher quality standards (low rolling resistance, improved skid resistance and good wear) to succeed in the competitive market. Truck and OTR tires, on the other hand, have to cope with heavy loads and longer distances more than high speed. The fibre content in passenger tires can be as much as 5% of the total tire weight, whereas OTR tires tend to have little or no fibre content and contain about 15% steel. Exact tire compositions are not known because each company keeps their recipes secret. As a result, all data are assumptions and an average of all tires. Only data ranges can be used for the process modeling and the uncertainty has to be taken into account. Scrap tire processing can be simplified in three major processing steps: crushing and/or grinding, sieving and magnetic separation. By way of example Figure 1 shows basic processing steps of an ambient scrap tire recycling plant. This is the base for further examinations. In a typical plant layout, the tires are first processed using a preliminary shredder (crushing), where the chips are reduced in particle size. This liberates most of the steel and fibre from the rubber crumb. Upon leaving the granulator, the steel is removed magnetically, and the fibre fraction is removed by a combination of shaking screens and wind sifters. The amount of rubber products is caused by an arbitrary screening and/or grinding process which is dependant on customer demand. To get information for modeling from scrap tire processing the main processing steps like crushing, grinding and separation must be investigated. The main material flows can be identified as: rubber, fibre and steel.

Composition

Passenger Tire

Truck Tire

Natural rubber

22,0%

30,0%

Synthetic rubber

23,0%

15,0%

Filling Components

28,0%

20,0%

5%

1,0%

Steel

13%

25,0%

Oil and others

9,0%

9,0

Fibre

Table 1: Average European Scrap Tire Composition [15].

End of Life Management - Selected Applications

Scrap Tires

467 particles (or even components) is essential to provide material flows that are suitable to serve as raw material for following products.

Crushing

Grinding 1

Particle Size Magnetic Separation 1

high

low

Steel low

Screening

high

Liberation Grade

Fibre Rubber Product 1

Grinding 2

Figure 2: Relation of particle size and liberation grade. 3.3

Screening

Fibre

Rubber Product 2 Rubber Product n

Figure 1: Simplified flow sheet of an ambient tire recycling process. The crushing process is identified as the process step with the highest influence on the material properties because it liberates materials from the compound. Therefore, any following processing steps are dependent on the effectiveness of the crushing and grinding process. The success of magnetic separation is related to the liberated steel particle. Parts of rubber stuck to the steel fibre may cause the loss of steel in the rubber flow or the loss of rubber in the steel flow. 3.2

Information Processing

Due to the efficiency of the recycling process and the liberation behavior of the materials the material flows are contaminated with the other materials. The total amount of steel in the rubber product or rubber in the fibre product for example is dependent on previous processing steps as mentioned in chapter 3.1. While using the method Material Flow Assessment the material flows cannot be reduced to their mass, additionally the material quality has to be taken into account as well. To assess the properties of material flows it is necessary to examine the flow in detail and determine the particles of a material flow. The contamination of materials is caused by material compounds that are related to the liberation of particles. Schaik and Reuter were the first to model recycling systems with the combination of particle size distribution and liberation classes in one model to investigate the interrelation between product design and recycling rate [16]. The particle size reduction and the liberation of materials during crushing and grinding will both effect the recycling of end-of-life products. Due to the design and construction of many products it is difficult to measure exact grain sizes of the elements in the product. But grain sizes often include the separation of material sizes and there is a correlation between particle size and separation and/or liberation degree as shown in Figure 2. Often the components are well combined and made to never separate by itself due to quality assurance. In future time more attention is paid to an environmental product design that includes the construction of products to have the potential for easy separation. Information on the deliberated

Model Architecture

Recycling processes generate material flows in various qualities. A complete separation of waste material components is not possible but quality standards can be met through defining separation grades as categories (high, medium, low). Therefore, modeling is useful to describe the correlation of material properties. Please note that the modeling in recycling processes is not related to specific data (numbers) but rather to data ranges (or quality issues). The modeling can help in decision making processes if the uncertainty of the model has an acceptable level. The acceptable level depends on the aim of the modeler and the model user. Assessing the information of the processing steps for modeling purposes with the availability of data ranges and the focus on uncertainties is necessary for the model system. Uncertainty can be understood as the variation of a parameter in a model. This variation is not known and at random. Additionally data-defects can be located in recycling processes due to incomplete or missing data [17]. Modeling recycling processes and the assessment of uncertainty and data defects regarding the input and process parameters are firmly connected.

Collecting information Flow Out

Flow In Data processing

Knowledge based decision support system

Figure 3: Concept of model architecture. The combination of MFA and LCA with the description of material properties needs the evaluation of materials streams. A knowledgebased decision support system (see Figure 3) uses mainly the information generated by processing steps resulting in an abstract combination of the elements of the model and its linkages. Therefore, this technique allows developing the model. Instead of specific data it processes the information of a process (e.g. dismantling of waste products into components of different shapes and compositions). Collecting information on the “flow in” can be made accessible through existing databases like ecoinvent (ecoinvent Centre, Switzerland), international databases for LCA (ELCD/ILCD), recycling stock exchanges or own data pools. Calculating input data are

468

End of Life Management - Selected Applications

performed with program interfaces on statistical basis. Finally, information on output data (flow out) can be generated through a developed knowledge-based decision support system. The accuracy of the model relies on the data availability and its quality. Therefore, it is necessary to have a well operated network. The case study scrap tire recycling provided data on the particle size distribution of rubber particles derived from scrap tires after a second crushing process. The input into the crusher (Jaeckering Company, Model Ultra Rotor) represented rubber particles smaller than 8 mm, and the output was characterized in particle sizes below 1 mm. During the experiments we varied the motor speed, the air flow and the particle size distribution of the input material. Each machine setting was performed in ten repeats. After the experiment the output material was sieved and the particle size distribution recorded in a graph to demonstrate the variation of the machine performance under same condition. The intention of the experiments was to show the variability of man-made experiments with exact measured machine settings. With the knowledge of the variation of output parameter a data interpretation can be added to the model. The scrap tire results are shown in Figure 4 and Figure

Due to data interpretation of all trials with various machine setting and material inputs a mathematical function has been found to suit for modeling. One result is shown in Figure 6. It is visible that not all findings are exact within the measured data points but the results are considered as successful for the first attempt. In particle size classes 1 and 2 we had already matching predicted data to the measured data.

5. In Figure 4 the sieving data is classified into 6 particle size fractions (1-6) and their percentage by weight. The variation of mass percentages within one particle size class is highest in the classes 4 and 6.

Figure 6: Forecast of data points based on experiments.

Mass - %

The knowledge on material properties is needed to develop a knowledge based decision support system. This knowledge is either generated through own experiments or data bases. In this paper the model architecture is based on own experiments and the modeling is performed by mathematical functions. 4

Particle size class

Mass - %

Figure 4: Particle size classes after rubber comminution process.

Machine speed in Hz

Figure 5: Cross-section view for particle class 4 with relation to machine speed. In Figure 5 the cross-section of class 4 for the machine speed of 30 to 45 Hertz is depicted. It is clearly visible that the variation of the machine parameter 30, 35, and 40 Hz is fairly low whereas the variation of the parameter of 45 Hz is out of question for modeling.

SUMMARY

Raw materials are essential to satisfy our needs in energy and products. Recycling processes provide a substantial contribution to sustainable resource management due to the supply of valuable secondary raw materials for new applications. There is a need in developing dynamic models that are able to handle the variations in material flows of recycling processes. This paper presents the development of a model architecture that is based on a knowledge based decision support system. The knowledge is generated through data processing of process information. Related to the case study of scrap tire recycling the material availability is connected with the particle size. Therefore, we examined the particle size distribution of rubber particles after a comminution process with various machine settings. After processing the data the statistical distribution was interpreted through mathematical functions based on the generated data. Due to the performance of all trials with various machine settings and material inputs a mathematical function has been found to suit for modeling. First attempts in modeling have shown that a model based on a knowledge based decision support system is able to serve as a prediction tool on material flows and their properties. Since the research is just at the beginning more information on recycling processes and their material flows have to be generated to develop a model that satisfies the user’s needs. 5

ACKNOWLEDGMENTS

We extend our sincere thanks to the German Research Foundation (DFG) who funded the project Metadis at Bremen University.

End of Life Management - Selected Applications 6 [1]

REFERENCES ISO 14040 International Standard (2006). In: Environmental Management – Life Cycle Assessment – Principles and Framework, International Organization for Standardization, Geneva, Switzerland.

[2]

Allen, F.W., Halloran, P. A., Leith, A.H., Lindsay, M.C. (2009); Using material flow analysis for sustainable materials management; Journal of Industrial Ecology Vol 13 No 5, pp. 662665.

[3]

Finnveden, G., Hauschild, M.Z., Ekvall, T., Guinée, J., Heijungs, R., Hellweg, S., Koehler, A., Pennington, D., Suh, S. (2009); Recent Developments in Life Cycle Assessment, Journal of Environmental Management 91, pp. 1-21.

[4]

Guinée, J.B., Heijungs, R. (1993); A proposal for the classification of toxic substances within the framework of Life Cycle Assessment of products; Chemoshere 26(10), pp. 1925-1945.

[5]

United Nations Environment Programme (2002); Life Cycle Initiative Homepage http://www.uneptie.org/pc/sustain/lcinitiative/home.htm

[6]

European Commission (2007); Directorate General Joint Research Centre (JRC), European Reference Life Cycle Database (ELCD); http://lca.jrc.ec.europa.eu/lcainfohub/

[7]

Brunner, P., Rechberger, H. (2003); Practical Handbook of material flow analysis. Advanced methods in resource and waste management; Boca Raton; USA; Lewis Publishers.

[8]

Binder, C.R., van der Voet, E., Rosselot, K.S. (2009); Implementing the results of material flow analysis; Journal of Industrial Ecology Vol 13 No 5; pp. 643-649.

[9]

Pehlken, A., Müller, D.H. (2009); Using information of the separation process of recycling scrap tires for process modelling, Resources, Conservation and Recycling (54) 2009; pp. 140-148. http://dx.doi.org/10.1016/j.resconrec.2009.07.008

[10] Bringezu, S., Bleischwitz, R. (2009); Sustainable resource management: global trends, visions and policies; Sheffield, UK, Greenleaf Publishing Ltd. [11] Salhofer S., Wassermann G., Binner E. (2004): Strategic Environmental Assessment as a Participatory Approach Environmental Planning: Experiences from a Case Study in Waste Management. In: Pahl-Wostl C., Schmidt S., Jakeman T. (Hrsg.): Complexity and Integrated Resources Management. iEMSs 2004 International Congress, 14. – 17. Juni 2004, Osnabrueck, Germany. Proceedings on CD and on the internet: http://www.iemss.org/iemss2004/; International Environmental Modelling and Software Society, Osnabrück, Germany. [12] Ekvall, T., Assefa, G., Björklund, A., Eriksson, O., Finnveden, G., (2007); What life cycle assessment does and doesn’t do in assessments of waste management; Waste Management Vol. 25. No. 3. pp 263-269. [13] Fatta, D., Moll, S.(2003); Assessment of information related to waste and material flows – a catalogue of methods and tools; Technical report 96 of the European Environment Agency, Copenhagen. [14] Hashimoto, S.; Mariguchi, Y. (2004); Proposal of six indicators of material cycles for describing society’s metabolism: from the viewpoint of material flow analysis; Resources Conservation and Recycling 40 (2004) pp.185-200. [15] Wdk, 2002. Wirtschaftsverband der deutschen Kautschukindustrie, www.wdk.de. [16] Schaik van, A., Reuter, M.A., Heiskanen, K. (2004) `The influence of particle size reduction and liberation on the recy-

469 cling rate of end-of-life vehicles´ Minerals Engineering 17, pp. 331-347. [17] Marx Gómez, J., Prötzsch, S., Rautenstrauch, C.; (2004); Data Defects in Material Flow Networks - Classification and Approaches, Cybernetics and Systems: An International Journal (CBS).

Business Issues in Remanufacturing: Two Brazilian Cases in the Automotive Industry 1

2

Olívia Toshie Oiko , Ana Paula B. Barquet , Aldo Roberto Ometto 1

2

2

Universidade Estadual de Maringá, Maringa, Brazil, Escola de Engenharia de São Carlos, Universidade de São Paulo, São Carlos, Brazil

Abstract Remanufacturing can be regarded as a more sustainable way of manufacturing due to its economical and environmental benefits, compared to traditional manufacturing. Consequently, there is an ever increasing body of literature on remanufacturing, but there is still a lack of empirical data on it. This paper describes and analyses two Brazilian remanufacturing cases in the automotive industry. Based on them, some business issues are discussed, such as the quality of remanufactured products and the motivation for remanufacturing. Although it is not possible to make generalizations, both cases were not motivated by ecological reasons, but are derived from specific market niches. Keywords: Remanufacturing; Automotive Industry; Business Issues

1

INTRODUCTION

Stiff competition, the concern with the environment and the enforcement of laws related to product end-of-life management are forcing companies to look for new ways of doing business, survive and reach new target customers [1]. Therefore, adopting end-of-life strategies, such as recycling, reconditioning and remanufacturing is becoming more important in business. Among these strategies mentioned, remanufacturing is the alternative with the most benefits related to [2] [3], as the remanufacturing process preserves raw materials and the value added to the product when it is being manufactured. Moreover, it enables companies to increase their productivity and revenue [3]. The concept of remanufacturing is growing in importance on a global scale. However, few companies and studies recognize this fact, especially in Brazil. There is also a lack of empirical data on it. This can be explained by the fact that few companies are involved in environmental issues and are concerned with product end-of-life management [5]. In addition, Zanette [6] states that 80% of research on remanufacturing is performed in countries technologically developed such as the USA and Sweden. Only 11% of this research is conducted in countries such as Brazil, Portugal and Singapore. In Brazil, since 1997 a National Law for solid waste (PNRS) has been under discussion. Recently (in August, 2010), this law was approved by the Senate, the upper house of the National Congress, but it is still waiting for approval from the President. This PNRS encourages Extended Producer Responsibility in general. Until now, only sectoral laws and specific initiatives have been drawn up. PNRS should require companies in Brazil to adopt end-of-life strategies for their products, as can be seen in other parts of the world. Despite this lack of regulations and research in Brazil, some successful case studies can be identified, particularly in the automotive sector. The aim of this work is to describe two Brazilian remanufacturing cases in the automotive industry, focusing on some business issues, such as the quality of remanufactured products, motivation for

remanufacturing, market positioning, take-back instruments (core acquisition) and forward and reverse supply chain settings. The next section presents the literature review of remanufacturing, considering its definition and business issues, followed by a description of the applied methodology and two Brazilian remanufacturing cases. Finally, these cases will be analyzed and the main conclusions will be drawn. 2

REMANUFACTURING

This section addresses the remanufacturing concept and the main business issues regarding this concept. 2.1

Definitions

Remanufacturing is an end-of-life strategy that reduces the use of raw materials and energy required to manufacture new products. Economically, remanufacturing is a strategy that aims to preserve the value added to the product during its design and manufacturing processes. From the environmental point of view, the importance of remanufacturing lies in extending the product’s lifetime by enabling it to have more than one life cycle, meaning less material to be used in meeting customers´ needs [7]. Remanufacturing is a process of bringing used products to a functional state like new and with warranty matching [8]. Remanufactured product has to have at least the same performance and quality specified by the OEM (Original Equipment Manufacturer – OEM). Therefore, remanufacturing can include product update, as well as new functionalities, software update and so on [9]. Despite the importance of OEM specifications for remanufacturing, Gray and Charter [10] suggest that the product can be remanufactured with or without brand identity. The remanufacturing process can be defined as a product recovery strategy focusing on recuperating products and parts in order to rebuild them according to their original design and quality. It is an effective way to keep products in a closed-loop and to ensure a product’s proper end-of-life management. Remanufacturing helps reduce the environmental and economic costs of manufacturing, as well as final product and component disposal costs [11] [12].

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_81, © Springer-Verlag Berlin Heidelberg 2011

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End of Life Management - Selected Applications

471

The remanufacturing process consists of five essential steps, namely: (1) disassembly of the product, (2) cleaning all the parts, (3) inspection and sorting, (4) reconditioning of parts and/or replenishment by new parts and (5) reassembly. Each step includes quality control [10].

Companies also face barriers about how to structure and align the reverse supply chain stages. Forward supply chains require similar requirements, however the context related to reverse supply chains are not well understood and they have more complex issues compared to forward supply chains [1].

2.2

It is also important to mention that recovering used products can be made for different supply chain actors, classified in original equipment remanufacturers (OEM) or third parties (non-OEM). Therefore, three different remanufacturing business models can be applied [22] [23] regarding the different supply chain links. In the first model, an independent operator remanufactures the used product. In the second, OEM engages a third party service provider to carry out the remanufacturing. In the last model, the OEM remanufactures the product that was manufactured for it, which describes a closed cycle supply chain.

Business issues

According to Steinhilper [13], “A business strategist might discover that remanufacturing rewards the world of manufacturing with new business opportunities in the after sales service market enabling one to offer their customers new solutions with a minimum total cost of ownership”. Thierry et al [14] point out some important information to analyze product recovery opportunities. The authors classify this information into four categories; product composition; magnitude and uncertainty of return flows; markets for remanufactured components and products and; actual product recovery and waste management operations.

3

METHODOLOGY

In addition, it is important to consider other factors that influence the remanufacturing business, such as quality of remanufactured products, the motivation for remanufacturing, market positioning, takeback instruments (core acquisition) and forward and reverse supplychain settings.

The methodology used in this work was a case study procedure, conducted in two Brazilian remanufacturing companies in the automotive industry. According to Yin [24], the case study methodology explores current phenomena, especially when the limits between the context and the phenomena are not totally defined.

A challenge faced by remanufacturing companies is the remanufactured products low acceptance [15], causing a low demand for these products [16]. Clients´ uncertainties about the quality of remanufactured products make them wary of acquiring these products. Therefore, marketing strategies have to be developed to build up the trust of the clients [1] [8] . It is also important to emphasize that, according to the concept, remanufactured products have the same quality and warranty as a new product.

A semi-structured questionnaire was used for the interviews at the companies. In both cases, the interviewees were responsible for remanufacturing in each company. The questions contained general business issues related to the features of remanufacturing, but the interviewers had the freedom to express themselves about whatever they considered to be topics in their remanufacturing context.

Other challenges are related to implementing remanufacturing and some reasons that cause this are: lack of knowledge about the concept [6], how to implement remanufacturing [2] and the lack of considerations about the strategic and business issues regarding remanufacturing [17]. Consequently, developing strategies to overcome these challenges appears to be essential. In addition, for companies that already remanufacture and even for the ones who want to start remanufacturing, it is important, in terms of understanding the drivers and remanufacturing design, to note that remanufacturing is divided into two categories [10]: 

Spare parts e.g. automotive clutch, starter motor;



Products e.g. CR Scanner, Vending Machine.

This distinction is necessary to understand that drivers and design issues for remanufactured spare parts and products may be different. This in turn has implications for the design of business models. The spare part industry, which consists of 2/3 of all remanufacturing activity, is primarily driven by the market; this is particularly prevalent in the automotive sector. In contrast, legislation is a significant driver for products [10]. In the case of legislation, which is a significant driver for remanufacturing products, the take-back system is the most well-known. This system forces the customer and the original equipment manufacturer to return used products, e.g. the waste electrical and electronic equipment directive (WEEE) [18], and the end-of-life vehicle directive [19] [19]. Without these laws, this system is based on the idea that the customer will voluntary give back the core [20]. According to King and Burguess [21], it is necessary to develop incentives to motivate this return, such as financial benefits, making it possible to remanufacture products.

Observation and documentation complemented information for the analyses of the two cases. The next section presents the results obtained from these cases. 4

CASE STUDIES

According to Buxdey [24], remanufacturing in the automotive industry is not a new approach as it started in 1940 in the USA and the UK and in 1947 in Germany. Moreover, Steinhilper [13] claims that remanufacturing has always been a strong partner throughout the growth of the automotive sector, which undoubtedly has been the main industrial driving force so far. Remanufacturing will continuously strengthen its important role in the automotive industry. Unlike the European Union, for instance, in Brazil there is no law related to end-of-life vehicles, so all remanufacturing initiatives in this sector are voluntary. Having said that, there are original manufacturers and independent reconditioning companies who compete with each other in the market to replace car parts in Brazil. In 1994, an association was set up to communicate the concept of remanufacturing to the market, as well as to reduce competition against independent reconditioning companies. This association, called ANRAP (Associação Nacional dos Remanufaturadores de Autopeças), which means National Association of Auto Parts Remanufacturers, was founded by a group of large car part manufacturers (OEMs). The purpose of this group is to promote the benefits of remanufactured products. These companies have found an effective way to do this by labeling the products that they remanufactured, and thus building up trust with their customers. According to ANRAP, only the OEM can guarantee the quality of remanufactured products [5]. The companies which belong to ANRAP are benchmarks of remanufacturing in the Brazilian automotive industry and the two compa-

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End of Life Management - Selected Applications

nies investigated in this work, which belong to this association, are hereafter Company A and Company B.

three other manufacturer’s units to be equivalent to one original unit.

4.1

Scrap dealers. Given the “Exchange schema” is not enough to supply all the cores needed, Company A also acquires used units from scrap dealers. The value to be paid is predefined and depends on the conditions of the parts. All the components from Company A found in scrap dealers are bought, even if there is no demand for that specific product model. This is done in order to prevent remanufacturing by third party companies and also introduces low quality products into the market.

Company A

Company A is a clutch manufacturer and started remanufacturing in 1991. However, since 1968, the company has been reconditioning car components for passengers because they noticed that their products were being reconditioned and commercialized by third party companies. It is important to notice that recovered products were and are sold in the aftermarket, as replacement components. Today, Company A no longer remanufactures lightweight car components, but just the heavy ones. This is because the labor (manhour) and other resources are almost the same as remanufacturing a lightweight or a heavy unit. However, added-value of heavy parts and prices are much higher. Therefore, remanufacturing lightweight components is not considered cost effective. From this point of view, it is critical for remanufacturing to find the right market niche. One of the most important clients for these remanufactured clutches is sugar cane mills and their transportation service providers as these parts wear out easily. Market positioning Remanufactured products are sold in two different ways. However, there is a great difference compared to selling new products. In order to sell remanufactured products, the seller needs to be more knowledgeable about the product and the implications of using it. This in turn takes more time to advise and support the client and is called a technical sale. Thus, remanufactured products are considered to have better customer service because technical assistants are better trained. The two ways of selling are: Distributors of remanufactured products. Among all the distributors of the brand, some are selected and developed to market remanufactured products. Remanufactured products are usually sold by small distributors as large distributors focus on “easy” high profit margins from new products. Direct Sales. This kind of selling is related to large final users (companies with large fleets, such as passenger or cargo transportation companies). In this case, the selling price can be higher for Company A (compared to selling to distributors) and the buying price is lower for the final user as one stage in the supply chain is eliminated. Occasionally, direct sales can include a fee for distributors. Take back instruments

When a new product model is launched, there are no used units to start the remanufacturing process. In these cases, a “bet” can be made, i.e. the earlier units sold as “remanufactured” are, in fact, new spare parts. Organizational structure for remanufacturing The organizational areas responsible for remanufactured products are separate from the other ones. For marketing and distribution, there is a department for Remanufacturing, subject to Aftermarket managing separate from traditional Sales and Exportation. In Industrial areas, Remanufacturing supervision can be found in plant units where remanufacturing takes place. All remanufacturing operations are performed on site in the same production line as the new ones. Different management strategies for new and remanufactured products can be considered a success factor for product recovery in Company A. However, company A believes that one area would not put enough energy into dealing with remanufactured products if it can sell new products more easily. 4.2

Company B

Company B has nine branches in Brazil, but remanufacturing operations take place in just one of them. Products which are remanufactured by Company B are: 

Air compressors for brake system. This product only applies for commercial heavy vehicles – buses and trucks. Disassembly and cleaning of cores are done by a third party partner. Products are reassembled internally by ten employees. Products are sold only by an exchange system: in order to buy a remanufactured unit, you have to give a used unit back.



Steering gear (hydraulic or mechanical). This line serves both passenger cars and commercial vehicles. Remanufacturing operations are conducted in conjunction with a partner company.

Company A has two ways of obtaining cores for remanufacturing:

Market positioning

Exchange schema. Every time one remanufactured unit is sold to a distributor or a final client (transportation company), one used product is required to be given back to Company A. In order to prevent the client from spending a period of time without the clutch (between the moment the worn unit is removed from the vehicle for being given back, to the moment the remanufactured product is installed), Company A agrees to the used parts being given back some time after the client takes the remanufactured product away. This procedure increases the service to the client, but also the complexity of controlling required operations. Company A manages a “virtual stock”, which refers to used units that the client still has not given back. When the client does not have a used unit to exchange, he pays a pre-defined price.

Remanufacturing operations started in Company B in around 2004, and are focused on passenger cars components. It is considered as strategically important because it fits a market niche which other products lines from the company don’t. So, initially, there was no ecological motivation for recovering.

Company A also accepts other brands’ used components, which are destroyed, because they consider this is a way to increase the market share. Therefore, a client who has a component from another manufacturer in his/her vehicle could choose to exchange this component for a remanufactured product from company A. The distributor can take the concurrent component back and share the costs and responsibility to dispose of it. Company A considers

The remanufactured product line is seen as one more line, which is why it does not have a strategic orientation and is separate from the others. Despite this, remanufactured products are not sold by every distributor or retailer, but there are special stores where the recovered products can be found. Original products sold to automakers are the main part of company sales. In the Aftermarket, there are “genuine” (new) products, and remanufactured ones. The latter are sold for 60-70% of the “genuine” price, although they offer the same quality and same warranty. The remanufactured products slogan is “products with original quality and like-new warranty”. Even selling the remanufactured goods, Company B sells kits to repair steering gears as there are good opportunities to use the repair kits and the remanufactured ones. Steering gears can often be easily repaired at a low cost. They can usually be repaired in

End of Life Management - Selected Applications auto repair centers, using the steering gear kits manufactured by Company B. When it is not possible to repair, a product from the remanufactured line is an option. A “genuine” component can be up to 16 times more expensive than a maintenance kit. Another characteristic of Company B´s recovered line is that it is for old vehicles, whose parts are not produced anymore. Considering the purchasing power of these owners, a remanufactured line is a good option for components in which quality and reliability are crucial. According to the interviewees, commercial vehicles are not a very important market niche as these components are not items which take a lot of wear and tear or are often replaced, even for the heaviest ones. When they require maintenance, they can often be repaired for a better price. Take back instruments Company B obtains used products to remanufacture from the following main sources: Exchange schema. The final client can find a remanufactured product at a retailer, where there are stocked units. The client should give his used unit to the retailer. Afterwards, the used part will run the reverse channel, going from the distributor to Company B. This is the only way to acquire remanufactured air compressors. If the client does not have a used unit from Company B, he/she (and also the Retailer and the Distributor) pays a surplus predefined amount to obtain the remanufactured component without the used unit. When a distributor wants to start remanufacturing operations and, therefore has no used parts to start selling on an exchange basis, the Aftermarket can negotiate special conditions to make stocks for the distributor. This can be done by selling remanufactured goods without exchanging them for used products, but with a total or partial discount on the differential value paid by the used parts or on condition that the parts will be delivered at a later time. However, this is done case by case without previous standardized orientation. Scrap dealers and auto repair centers. The steering gears are completely remanufactured at one of Company B´s partners, which are hereafter called Partner B. This partner keeps cores supplied by scrap dealers and auto repair centers. Sometimes the cores are bought in bulk quantities of scrap, in which there are cores of different qualities, but acquiring them this way is unusual. Return or rejected items. Occasionally some units are returned from the consumer (within the warranty period) or are rejected by quality inspection during manufacturing and can be directed to remanufacturing. Company B works alongside some companies in remanufacturing operations. The most important, Partner B, receives used products (steering gears) from exchange schema or from scrap dealers, goes through every remanufacturing stage (disassembly, cleaning, tests, parts substitution and reassembly) and sends remanufactured products to Company B for redistribution. Used cores and processed products are transported in the same vehicles by Milk run, which increases the load capacity utilization rate. Regarding compressors, Company B has another partner, which is responsible for receiving the cores, disassembling them, cleaning them and sending them back to be reassembled by Company B. The rate of recovery of the cores from the exchange basis is practically 100%, although some have experienced strong blows, which results in cracks and dents and impedes remanufacturing these cores.

473 Organizational structure for remanufacturing As remanufactured products are considered common aftermarket products, it is hard to estimate how much employees are related to the remanufacturing processes. In manufacturing operations, there are just ten employees to assemble brake compressors. Nevertheless, there are more employees working on design and engineering, quality and marketing of remanufactured products. The Product Development Sector, subordinate to the Independent Aftermarket sector, identifies the need of new products (new and remanufactured products) and co-ordinates other sectors to launch these products. This area has closer contact with clients (distributors of replacement parts). Product Engineering is responsible for technical specification to be followed by the Supplier Development Engineer. The latter is also responsible for starting production and providing support to suppliers and partners, if necessary. Purchasing proceeds follow-up with third party remanufacturers. 5

ANALYSES

Based on the two case descriptions, some analyses and comparisons can be made, as shown in Table 1. First of all, it is important to notice that both companies offer remanufactured products according to the definition in the literature, with the same quality and warranty equivalent to new products for a lower price compared to the virgin products. It is an advantage compared to their competitors, the independent reconditioning companies, which do not have the OEM expertise. It should be mentioned that this is always a strong argument for OEM marketing. Aligned with Steinhilper [13] and Gray and Charter [10], it can be observed that by finding some specific market niche is the driver for remanufacturing in both companies and they market only spare parts, and not the complete product. In both cases, the remanufactured products are better options for the consumer, compared to new ones. Moreover, they are positioned in niches that used to be occupied only by independent reconditioning companies, with the advantage of relying on OEM expertise. Despite some similarities between the products, it is important to note that there are certain specific technical features which define the position of these two companies in the market. Components for lightweight or heavy vehicles may prove to be more profitable depending on the wear and tear, the possibility of repairing them, the material and the manufacturing process. Concerning distribution channels, remanufactured products can not always be found at all selling points where new products are found. To distribute the remanufactured products, both companies came up with special ways of selling. However, there are no distributors that sell only remanufactured products. In both cases, the exchange schema is the main way of obtaining cores, but with some particularities, such as: a “bank” of cores that allows clients to give the core back after getting the remanufactured one; acquirement by the OEM of other brands’ cores, as a way of enlarging the market share. Scrap dealers are other important core sources. As well as collecting cores from other brands, it can be observed that the OEM can collect cores from their own brand which will not be used. Thus, preventing outsiders from recovering the used OEM product, also causes decrease in the remanufacture profit margins. It could be expected that the demand for remanufactured products and the returns of cores are equivalent, as the cases refer to spare

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End of Life Management - Selected Applications

parts sold on an exchange basis. However, various factors seem to affect this balance. 

Beginning of the remanufacturing operation when used products are not available yet;



Bad quality of collected cores, which make them unusable;



Collection of other brands’ cores, implying a deficit of recoverable cores;



Collection of any core that is found, despite the quantity or quality required.

The place to process the recovery varies considerably. One of the companies does it by at its own plant. Another company relies on contracted remanufacturers, but depending on the product, either the whole process is done by the partner or simply some operations. Although there were many similarities in terms of motivating factors of manufacturing and the selling points and collecting cores, an important difference refers to the organizational structure. Within Company A, there are parallel sectors for Remanufacturing and new products, subordinated to Aftermarket and Industrial Departments, respectively. In Company B, such dedicated organization for remanufactured products does not exist. The recovered products are considered common products, although in practice they require different selling, and also supply channels. 6

CONCLUSION

This work investigated remanufacturing business issues in two OEM auto parts in Brazil. It is important to point out that the OEM is concerned with the possibility of independent third parties acquiring used products manufactured for them and remanufacture these ones, putting into the market low quality recovered products. This can cause a negative impression on clients, who can start to associate the OEM brand with low quality products. In addition, third parties will use the resources spent by OEM, who added value to the product.

Moreover, it is interesting to highlight other findings of the two cases. In both cases, the companies studied recover their own OEM products in the aftermarket to reach some specific niche in the market, which otherwise would be served by independent remanufacturers (or refurbishers). However, both studied OEMs emphasize there are some products which are not worthwhile remanufacturing. Another similarity refers to the price of remanufactured products, which is lower than the new ones. Despite the price, the quality and warranty equivalent to the original product are highlighted, as a result of the expertise of the OEMs. Another common point refers to the need to have special selling points for remanufactured products. Not all distributors and selling points for virgin products are able to sell remanufactured products. Despite the topics discussed, some points are distinct in both companies. Regarding remanufacturing operations, Company A run operations fully in house. Company B finds some benefits in outsourcing some stages of the operation. In the two companies, coordinating the remanufacturing is the responsibility of the Aftermarket sector. However, company A has a remanufacturing sector, which has a manager who is responsible for remanufacturing. This can be considered as a good way of structuring and aligning remanufacturing with strategic activities of the company. It is important to highlight that this comparison is not meant to generalize. The similarities between both companies are not intended to be the best or the only way of doing this. Nor is it an objective way to say a company do it better than the other regarding the differences found in this study. The objective here was to illustrate how these factors interrelate to each other in real cases and discuss them from the point of view of the literature. However, it is necessary to investigate other companies to obtain more information about remanufacturing business issues in Brazilian auto part companies. Regarding Brazil, some interesting points can be mentioned. Firstly, it can be seen that a barrier to develop and increasing the remanufacturing of products is a lack of legislation, which is a significant driver for products remanufacturing. The same does not happen in

Company A

Business issues

Company B

Quality of remanufactured products

Same quality and warranty as new products

Same quality and warranty as virgin new products

Motivation for remanufacturing

Market niche

Market niche

Market positioning

Transportation companies with high replacement rates.

Owners of old vehicles. Low cost market, new components are not produced anymore

Distribution of remanufactured products

Technical sales:

Specific distributors

Take-back instruments

Exchange schema

Exchange schema

Acquisition from scrap dealers

Acquisition from scrap dealers or auto repair centers

Specific distributors Direct sales

Return or rejected items Remanufacturing operations

Fully in house (OEM)

Fully performed by partner (steering gear) Partially in house, partially by partner (air compressor)

Organization structure

Separate from virgin products

Same as virgin products

Coordination of new remanufacturing initiatives

Remanufacturing management, under Aftermarket

Product Development management, under Aftermarket

Table 1: Comparison between Companies A and B according to remanufacturing business issues.

End of Life Management - Selected Applications the case of remanufacturing spare parts, which is motivated by opportunities of positioning in the market. Brazil is one of the countries which remanufacturing spare auto parts is considered to be an opportunity to make a profit, as environmental issues related to manufacturing are not considered. Therefore, the lack of rules can be considered a barrier to gain environmental benefits related to remanufacturing.

475 [11]

White, C. et al. (2003): Product Recovery With Some Byte: An Overview Of Management Challenges And Environmental Consequences In Reverse Manufacturing For The Computer Industry. Journal of Cleaner Production, V. 14, p. 445-458.

[12]

Kerr, W.; Ryan, C. (2001): Eco-Efficiency Gains from Remanufacturing: A Case Study of Photocopier Remanufacturing At Fuji Xerox Australia. Journal of Cleaner Production, V. 9, p. 75-81.

[13]

Steinhilper, R. (1998): Remanufacturing - The Ultimate Form of Recycling, Fraunhofer IRB. Verlag, Stuttgart.

Finally, it is important to mention that associations such as ANRAP can generate interest in remanufacturing, as well as trust from the customer concerning remanufactured products.

[14]

Thierry, M.; Salomon, M.; Nunem, J.V.; Wassenhove, L.V. (1995): Strategic issues in product recovery management. California Management Review, vol.37, no.2, p.114-134.

For future work, it is important to investigate other companies that remanufacture, such as home appliance, capital and electronic goods, to obtain information about how remanufacturing is being done in other companies.

[15]

Ijomah, W. L.; Childe, S.; Mcmahon, C. (2004): Remanufacturing: a key strategy for sustainable development.

[16]

Geyer, R.; Jackson, T. (2004): Supply Loops and their Constraints: The Industrial Ecology of Recycling and Reuse. California Management Review, V. 46, N. 2, p.55-73.

7

[17]

Ferguson, M. E.; Toktay L. B. (2004): The Effect of Competition on Recovery Strategies. Technology and Operations Management, Insead,

[18]

EU, Directive 2002/96/EC of the European Parliament and the Council of 27 Jan. 2003 on waste electrical and electronic equipment. Official Journal of the European Union.

[19]

EU, Directive 2000/53/EC of the European Parliament and of the Council of 18 September 2000 on end-of life vehicles. Official Journal of the European Communities, (L269): p. 34-42.

[20]

Ostlin. J. (2005): Effectiveness in the Closed-Loop Supply Chain: A Study Regarding Remanufacturing, IEEE.

[21]

King, A. M.; Burguess, S. C. (2005): The Development of a Remanufacturing Platform Design: A Strategic Response to the Directive on Waste Electrical and Electronic Equipment. Proc. Imeche Part B: Journal of Engineering Manufacture, V. 219, P. 623 – 631.

Secondly, the existence of this legislation, similar to the take back system, could be advantageous for OEM as it would be difficult for independent third parties to acquire the used products.

REFERENCES

[1]

Guide, V. D. R. Jr.; Harrison, T. P.; Van Wassenhove; L. N. (2003): The Challenge of Closed-Loop Supply Chains, V. 33, N. 6, p. 3–6.

[2]

Jacobsson, N. (2000): Emerging Product Strategies: Selling Services of Remanufactured Products. Dissertation. The International Institute of Industrial Environmental Economics – Lund University, Sweden.

[3]

Steinhilper, I. R.; Brent, A. (2003): Saving Product Lives in Global and Local Remanufacturing Networks: A Scientific and Commercial Work Report and an Outlook. Third International Symposium on Environmentally Conscious Design and Inverse Manufacturing. Tokyo, Japan.

[4]

Giuntini, R.; Gaudette, K. (2003): Remanufacturing: The Next Great Opportunity for Boosting US Productivity. Business Horizons.

[5]

Barquet, A. P. B. (2010): Barreiras e Diretrizes para a Implementação de um Sistema de Remanufatura. 235f. Dissertation (Master on Prod. Eng.) – Curso de PósGraduação em Eng. De Produção, UFSC, Florianópolis.

[22]

Zanette, E. T. (2008): A Remanufatura No Brasil E No Mundo: Conceitos e Condicionantes. 2008. Monografia. Escola de Engenharia de São Carlos, Universidade De São Paulo, São Carlos, SP.

Parlikad A, McFarlane D. (2004): Recovering value from endof-life equipment—a case study on the role of product information. In: Technical report, centre for distributed automation and control. University of Cambridge.

[23]

Um, J.; Yoon, J.; Suh, S. (2008): An architecture design with data model for product recovery management systems. In: Resources, Conservation and Recycling 52, p. 1175–1184.

[24]

Yin, R. K. (2005): Estudo De Caso: Planejamento E Métodos. 3 Ed. Porto Alegre: Bookman.

[25]

Buxcley I. (2007): Remanufacturing in the Automotive Industry. Remediation for Remanufacture Seminar. Leeds.

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Zwolinski, P.; Lopez-Ontiverosa, M. A.; Brissaud, D. (2006): Integrated Design of Remanufacturable Products Based on Product Profiles. Journal of Cleaner Production, V. 14, p. 1333-1345

[8]

Ijomah, W.; Hammond, G.P.; Childe, S.J.; McMahon, C.A. (2005): A robust description and tool for remanufacturing: a resource and energy recovery strategy. In: Yamamoto, R., Furukawa, Y., Koshibu, H., Eagan, P., Griese, H., Umeda, Y., Aoyama, K., eds. Eco Design 2005. Proc. of the Fourth International Symposium on Environmentally Conscious Design and Inverse Manufacturing. IEEE, pp. 472-479.

[9]

Ijomah, W. (2002): A model-based definition of the generic remanufacturing business process. Doctoral thesis, University of Plymouth.

[10]

Gray, C., Charter, M. (2006): Remanufacturing And Product Design: Designing For The 7th Generation, University College For The Creative Arts, Farnham, UK.

A Systematic Investigation for Reducing Shredder Residue for Complex Automotive Seat Subassemblies 1

Siobhan Barakat , Jill Urbanic 1

1

Faculty of Engineering, University of Windsor, Windsor, Canada

Abstract Automotive shredder residue is a byproduct of the automotive recycling infrastructure and represents 15% of the overall weight of a vehicle. The byproduct is currently diverted to landfill and although the potential for recycling exists, none are currently being utilized within Canada. Consequently, the possibility of dismantling vehicle seats separately from the current vehicle dismantling process in order to remove a large portion of automotive shredder residue before the shredding process is investigated using a systems approach. Issues such as government regulations, expenses and potential revenues are discussed to determine the economical success of vehicle seat recycling. Keywords: Automotive Shredder Residue; Dismantling; End-of-Life Vehicles

1

INTRODUCTION

The end-of-life vehicle (ELV) recycling industry, which is a profit driven business in Canada, only removes parts, assemblies and fluids that are of value or require mandatory removal. The remainder of the ELV is sent through a shredder which breaks up the ELV into a mixture of ferrous metals, nonferrous metals and nonmetallic materials. The nonmetallic material contains a mixture of plastics, foam, rubber, glass, textiles and carpeting, ceramics, paper and any other types of nonmetallic materials that were in the ELV at the time of shredding. The mixture is known as automotive shredder residue (ASR) and is a byproduct, or waste, of the shredding process. Although technologies do exist to separate and clean ASR, none have been commercially proven; therefore, this mixture, which represents approximately 15% of ELVs weight, is currently sent to landfill. Proactive legislation changes have been created to prevent such a large percentage of ELVs from being sent to landfill. The European Union (EU) was the first, in 2000, to enact such a document; the EU must now work towards their goal of 95% by an average weight per vehicle and year to be diverted from landfill by the year 2015. Other countries are now also setting similar aggressive goals. Ontario, a province of Canada, is in the process of approving their own type of vehicle end-of-life management practices and guidelines that will also prevent automotive recyclers from sending ASR to landfill. The problem arises in whether Canadian automotive recyclers can attain goals similar to those outlined by the EU. 2

CANADIAN AUTOMOTIVE RECYCLING INDUSTRY

There is a well developed ELV management industry in Canada; however it is still lacking operational guidelines to regulate dismantlers. Due to the fact that dismantlers currently are not regulated and most are small independent businesses, there tends to be a wide variation in practices from region to region. Dismantlers are also not strategically located within Canada and like the population, are widely scattered throughout the country. There are organizations such as OARA (Ontario Automotive

Recyclers Association) that give certifications to recyclers that comply with set standards and practices; however there is nothing in place to stop dismantlers that are not certified from operating. Vehicle Recycling

Dismantler

Further Processing for Reuse

Parts requiring removal

Landfill

Parts requiring removal

Shredder

Nonferrous metals

Ferrous metals

ASR

Figure 1: Big picture view of the ELV recycling outputs and their final destination. In Ontario, dismantlers are required to remove components and fluids that are harmful to the environment. Automotive shredders require the removal of certain components and fluids to prevent fires, explosions and damage to their equipment. Fluids and refrigerants, mercury switches, gas tanks, tires and batteries are all required to be removed according to the Recycling Council of Ontario [1]. ELVs are then further dismantled to remove all parts for direct reuse and for remanufacturing. The remainder of the vehicle is referred to as the hulk and it is typically crushed and sent to the shredder for shredding for subsequent material separation and processing. Shredding involves the mechanical processing of ELV hulks and other metal-rich scrap material using a hammer mill [2]. Various material separation techniques are employed to isolate ferrous and nonferrous metals from the ASR and the metals are sent for further processing. The shredder’s feed material is often of concern for

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_82, © Springer-Verlag Berlin Heidelberg 2011

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477

shredder operators. If any type of hazardous material enters the shredder the quality of the ferrous metal, nonferrous metal and the ASR will be compromised; however the most significant concern is the ASR. Some areas classify ASR as hazardous waste and it must be disposed of accordingly which increases costs to the shredders [3]. This is why dismantlers are required to remove certain components and fluids as previously discussed.

themselves to MOE because they are primarily smaller, independent family-run businesses. OARA therefore exists to act on behalf of all recyclers within Ontario and is responsible for negotiating with MOE to ensure set regulations are attainable. OARA also attempts to educate the public (or vehicle owners) of the automotive recycling industry and what steps they can take to properly repair and retire their vehicle.

2.1

The core problem that exists in this framework is the lack of communication between the vehicle producers and the recyclers. The vehicle producers are not informing the dismantlers the best way to recycle their vehicles and the dismantlers are not telling the producers what design changes could be made to facilitate easier dismantling. The EU Directive has a good strategy to encourage vehicle producers to inform the recyclers of their vehicles by requiring each producer to make available dismantling instructions and guidelines. This does not however present a way for dismantlers or shredders to promote their ideas to vehicle producers. Good communication may not be possible given the current automotive recycling infrastructure; however improvements can be made to the current infrastructure to increase efficiency of recycling by improving communication.

Actors and Scope

The vehicle end-of-life management systems will be examined within Canada, with the majority of work relevant to Ontario. The automotive recycling industry in Ontario cannot be described without fully defining all the actors involved; their roles and responsibilities; and the interactions between actors. 

OARA acts as the voice of the automotive recycling industry (dismantlers and shredders) and represents them to both the government and public. OARA also helps keep the automotive recycling industry up-to-date on current industry trend and government initiatives. All provinces within Canada have similar representative bodies and without such organizations it would be nearly impossible for recyclers to interact with the public as most recycling companies are relatively small private operations.



MOE (Ministry of Environment of the Province of Ontario) is a government ministry that has many divisions responsible for environmental protection. The main roles of MOE are to act as the guardian of public interest, carry out enforcement and lead/approve environmental protection programs.



Vehicle producers range from a variety of manufacturers present within Canada. Manufacturers typically design vehicles in the most economically viable way. Presently little time is spent on end-of-life management planning and coordination with ELV recyclers.



Vehicle owners can change multiple times throughout a vehicle`s useful life. The owner`s environmental knowledge will determine how the vehicle is to be discarded at the end of its life.

Vehicle Lifecycle

Vehicle Owner

MOE

Negotiation Dismantler OARA Shredder

WDA 2002

The Waste Diversion Act, 2002 is Ontario’s main legislation to promote the reduction, reuse and recycling of waste through the development, implementation and operation of waste diversion programs [4]. In October 2008, MOE began a public dialogue on how to achieve greater waste diversion and to explore extended producer responsibility (EPR) as the foundation for Ontario’s waste diversion while working towards a zero waste society [5]. Waste diversion can be defined as any act that prevents waste from reaching landfill. WDA more specifically defines waste diversion as [5]: 

Diversion will continue to be reduce, reuse and recycle



The material value recovered and preserved from all processes and technologies will be counted as diversion



Burning waste without recovering material for reuse will not be counted as diversion

While this legislation change is currently wide in scope, it does address ELVs. ELVs are planned to be incorporated into the WDA 2002 in the long term horizon, or approximately five years from its start date. The document currently does not address a specific target in term of percentage of recycling however it is implied that the whole vehicle must be diverted from landfill (i.e. 100%).

Vehicle Producer

Lack of Communication

2.2

Overall the goal of the WDA is to help shift society’s thinking that waste does not have any value; materials such as wood, glass and metals do have value, especially considering the amount of energy saved eliminated raw material extraction. Through these changes, it is Ontario’s goal to become a zero waste society by making the waste of one product the input of another.

Communication

3 Figure 2: Current actors within the Canadian automotive recycling industry. The interactions between all actors in the system can depend on the roles and responsibilities of the actors. MOE holds the power to create legislation that would govern how the vehicle producers and recyclers operate; as a result, MOE has great influence on these businesses through the creation and enforcement of regulations. In turn, vehicle producers and recyclers need to let MOE know what challenges they are facing, and what goals are attainable. Unlike vehicle producers, recyclers do not have the capacity to represent

AUTOMOTIVE SEAT RECYCLING

Over time the ferrous metals within vehicles have been decreasing while the nonferrous and plastic content increases. This has led to vehicles that require more complicated recycling processes that are increasingly more labour and energy intensive. Over the past 20 years, the amount of ferrous metal has decreased about 10%, from 85% to 75% of the total vehicle weight [6]. The majority of the recycling profits are derived from the metal-rich content in vehicles and their high recyclability rates; ferrous and nonferrous metals shredding operations can recover approximately 95% of the materials [7]. With these trends in material content increasing, vehicle recycling rates will continually decrease, as will the profits of

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End of Life Management - Selected Applications

automotive recyclers, until something is done to effectively address the increasing nonmetal content in vehicles. The mass flows of the ELV management process are shown in Figure 3. The only component of this pie chart that does not currently have a system in place to correctly manage it, is ASR. ASR contains a combination of plastics, foam, rubber, glass, textiles and carpeting, ceramics, paper and any other types of non-metal materials that are present in the vehicle when shredding takes place. Although some technologies exist to handle ASR, none have been proven commercially successful in Canada [7] and as a result, ASR is currently sent directly to landfill. The increasing trend of movement towards government regulated recycling targets has created a need for research to find ways to address ASR. The goal of this research is to present opportunities to address ASR preshredding by removing those major contributors of ASR at the dismantling stages.

9% 6%

Ferrous metal

3%

ASR Nonferrous metal

68%

14%

Fluids Tires

Figure 3: Pie chart of the mass flows of the ELV management process (adapted from [3]). It was decided to investigate vehicle seats’ contributions to ASR and the possibility of developing a recycling process to divert the non-metals within the seats from landfill. Vehicle seats were chosen due to the assumption that they are a significant contributor to ASR. In the past, the recycling of assemblies with high plastic content has been plagued by high disassembly costs and lack of market demand for materials. It is still however necessary to determine how much vehicle seats contribute to ASR and how much it could potentially cost dismantlers in the event that recycling targets are put in place. The development of markets for used polyurethane foam and seat fabric could also become a reality through government support programs and the growing demand for green products. For example, in Canada, a Used Tire Program was developed by the government that collects and redistributes used tires to be recycled into new products [8]. Companies that remanufacture these tires are given government grants, and dismantlers are paid a set price per tire, regardless of their condition.

3.1

Disassembly vs. Dismantling

In order for a comprehensive business plan to be developed, it is necessary to have an understanding of how long it would take an operator to dismantle a vehicles seat in entirety, as well as insight into the tools, tasks and related overhead requirements. For this case study, a 2001 Dodge Neon was chosen for the analysis. This is an average or typical sized vehicle in the Canadian market. The Dodge Neon is a front wheel drive, 4 door vehicle with an EPA highway (l/100km): 7.1[9]. The curb weight of this vehicle is approximately 1160 kg. This vehicle option has two bucket seats and a bench seat that has the ability to fold down and provide access to the trunk. In order to understand the structural make-up of the vehicle a thorough disassembly was performed and all operations, part types, weights and material compositions were recorded. The major differences that will be realized through calculating the times for dismantling will be through material separation. It is not necessary for an operator to separate all parts and assemblies. Only parts and assemblies that are of different material composition must be separated. For example, to dismantle, it is not necessary for the operator to fully disassemble the bucket seat frame as was done in the full disassembly. The operator will therefore use a utility knife to remove the fabric from the seat frame, remove the foam, and remove any other plastic based materials such as the headrest, side panels and reclining lever. These differences result in an almost 40% reduction in time from disassembly to dismantling for the bucket seats. The problem however is presented in the bench seat which has multiple material interfaces. For example the bottom portion of the bench seat has a metal frame embedded inside the foam. The only way to remove this metal frame is by using a knife to rip apart the foam, piece by piece. Unlike the bucket seats, the bench seat is predominantly made of plastic, at 76% whereas the bucket seats are made up of 72% metal. This difference in composition makes the bench seats much more difficult to dismantle. Furthermore, unlike the bench seats, where the disassembly time was different than the dismantling time, the dismantling and disassembly operation for the bench seat is identical. The best example of this can be realized through Figure 4, where the back structure of the seat has already had the fabric and foam removed from it. In order for the seat to be fully reused or recycled, all materials must be separated from each other. Figure 4, shows the different colours for the different materials, blue on blue assemblies can be left unassembled, similar to red on red. For this assembly however there are no blue on blue or red on red assemblies; therefore everything must be fully disassembled. The Weights of Parts and Materials (g)

Part Type Back Seat (bench)

Driver Seat Pass. Seat

Assembly

Overall

Metals

Fabric

Foam

Plastic

Bench seat upper frame Bench seat upper left seat Head Rest Bench seat upper right seat Head Rest Bench seat lower portion Driver seat upper portion Head rest Driver seat lower portion Driver seat upper portion Head rest Driver seat lower portion

4853 2654 893 3736 893 4417 5911 700 9509 5616 700 9004

801 644 560 326 560 1017 4111 367 7197 4016 367 6793

1000 410 96 610 96 800 800 96 600 600 96 500

52 400 200 800 200 2600 1000 200 1400 1000 200 1400

3000 1200 37 2000 37 0 0 37 312 0 37 311

Table 1: Breakdown of subassembly material composition.

End of Life Management - Selected Applications

479

Operation Number

TMUs

Time (sec)

Separate frame from seats

1020

36.72

Sub Op 11

Remove mounting clips

1390

50.04

Sub Op 12

Remove hog rings

5270

189.72

Sub Op 21

Remove seat material

670

24.12

Sub Op 22

Remove head rest

2010

72.36

Sub Op 23

Remove pull bracket

820

29.52

Sub Op 24

Remove brackets

1380

49.68

18830

677.88

Op 1

Figure 4: Chrysler Neon bench seat upper portion, the red identifies metal parts and the plastic are in blue. result of this is identical disassembly and dismantling process with equal time. 3.2

Description

MOST Time Study

Maynard Operation Sequence Technique (MOST) is a time measurement technique used to calculate the amount of time a task should take an operator. The tasks are broken down in individual elements and are all assigned a value in a unit called time measurement units (TMU). For example, one element could be considered removing a screw. This calculation will consider the time it takes to get the screwdriver, put the screwdriver to the screw, the action of loosening the screw, putting the screwdriver away, and returning to the workstation. This value is converted into time (1 TMU is equal to 0.036 seconds) and used as an average, which includes time allowances, for further calculations and will be used in the business plan.

TOTAL

Table 4: Sample MOST time calculation for upper portion of bench seat dismantling. Process: Dismantle Back Seat Upper Op 1: Separate Frame from Right and Left Seats

The times that were calculated assuming that the seats were already removed from the vehicle and the operator had a work bench on which to dismantle the seats, enabling him access to the seats without bending. The times calculated for the seats and the operations required to dismantle are displayed below (note that the bench seats were removed from the vehicle in two pieces which is why the bench seat dismantling time has separate calculations): Operation Number

TMUs

Time (sec)

Remove accessories

2100

75.6

Sub Op 14

Remove fabric with knife

860

30.96

Sub Op 21

Remove fabric with knife

700

25.2

Sub Op 11-3

Sub Op 22

Description

Cut fabric off head rest TOTAL

1540

55.44

5200

187.2

LEFT SEAT Sub Op 21:

Sub Op 31:

Remove Mounting Clips (x2)

Remove Seat Material (velcro)

Remove Seat Material (velcro)

Sub Op 12: Remove Hog Rings Along Frame Perimeter to Remove Fabric

Sub Op 22:

Sub Op 32:

Remove Head Rest Assembly

Remove Head Rest Assembly

Sub Op 23: Remove Bracket that Pulls Chair Down

Remove Bracket that Pulls Chair Down

Sub Op 13: Remove Mounting Brackets (x2)

RIGHT SEAT

Sub Op 33:

Sub Op 24:

Sub Op 34:

Remove Bracket that Connects to Frame

Remove Bracket that Connects to Frame

Figure 5: Dismantling structure for the upper portion of the bench seat.

Table 2: MOST time calculations for bucket seat dismantling. Operation Number

Description

TMUs

Time (sec)

Sub Op 1

Remove hog rings

4950

178.2

Sub Op 2

Remove foam from frame

10610

381.6

15560

560.16

TOTAL

FRAME Sub Op 11:

Table 3: Calculated MOST times for bottom potion of bench seat dismantling.

(1)

Upon assessing the results, the total calculated time for the complete dismantling is: 1612.44 seconds or 26 minutes and 53 seconds (see equation 1). This is a 14% reduction from the total dismantling time which was also calculated. With this time it is possible to determine how many seats could be dismantled and the potential revenues from separated materials. 4

BUSINESS PLAN

Presently, the seats are quickly removed from the vehicle body to allow dismantlers access to other more valuable interior features. They are then placed back into the vehicle hulk when it is sent to the shredders. In the event that recycling mandates are put into effect in Canada this would be a simple way for Canadian

480

End of Life Management - Selected Applications

dismantlers to increase their percentage of a vehicle that is recycled. Therefore, it is assumed in this business plan that the vehicle dismantlers will willingly donate the vehicle seats in order to reduce the amount of non-recyclable materials present. The vehicle seats will therefore no longer represent a source of income for the recyclers and sending them through the shredder could incur the recycler penalty fees for not meeting recycling mandates. For the vehicle studied, the plastic based materials in the vehicle’s seat represents only 1.9% of the vehicle’s overall weight.However considering that 14% of vehicle weight (on average) consists of those materials that contribute to shredder residue[3], the vehicle’s seats represent 13% of the 14%. It must be noted that the data gathered in [3] was generated using vehicles from 1990; therefore it can be assumed that over the past 10 years a significantly larger amount of plastic based components have been utilized in vehicles. Although, statistically, it cannot be proven how much removing vehicle seats will reduce ASR, it can be assumed this percentage will be significant. Labour Rent Expenses Utilities Dismantle Vehicle

Equipment/ Supplies Ferrous metal Revenue

Polyurethane Foam

Figure 6: Potential expenses and revenues from seat dismantling facility. It is assumed that the amount of space that is required for the operators to dismantle the seats is 36.75 square meters (400 square feet), with an additional 13.75 square meters (150 square feet) per every additional operator after two. It is assumed that the dismantling occurs at the dismantler with a separate space for the vehicle seats to be dismantled, in order to reduce unnecessary transportation. For expense purposes it is assumed that the business rents the space from the dismantler and acts as its own separate business. The potential expenses and revenues for the business are expressed through Figure 6. The revenues are generated mainly through ferrous metals from the seats, and this source of income is the only one that is considered for the business model at this time.

These revenues are calculated with the assumption that the metals are shredded and sent directly for further metal refinement. The potential for generating profit from the polyurethane foam is dependent on the availability of polyurethane re-bonding facilities within the area and their ability to accept ELV foam that has not been cleaned, as a raw material. Although the foam has not been sent through the shredder, there is still a trace of contaminates present in the polyurethane foam and may be required to be cleaned to be accepted as raw material [10]. Selling the polyurethane foam present within the vehicle seats could create an increase in revenue by up to 44% [11]. The ideal scenario for automotive manufacturers, if EPR was put into effect, would be to implement closed-loop recycling for all the plastic based components present in the vehicle. The polyurethane foam along with fabrics from the seats could be re-bonded and be utilized as sound dampening material in vehicles. Re-bonding is a process in which scrap polyurethane foam is shredded and an adhesive mixture is used to re-bond the materials. Although rebonding has typically been used as carpet underlay or for athletic mats, it has been proven to be an effective sound dampening material [12]. The remaining plastics in the vehicle seats could potentially be remanufactured as similar parts in newer model vehicles. With the labour and overhead expenses remaining constant, the two factors that affect the business’ success are: the price of shredded ferrous scrap, and the availability of vehicle seats. Approximately 400,000 [1] vehicles are retired each year in Ontario, with 65% of the population centred around the Greater Toronto Area (GTA) it is reasonable to assume that a single dismantler in this strategic location could acquire approximately 14,000 vehicles (or 5% of retired vehicles in the market) to dismantle with 3 employees (as required according to Table 5). To illustrate this point, a sensitivity analysis was done using the monthly price averages of shredded ferrous metal scrap from the past three years (2008, 2009 and 2010) to determine how it affects the business. The number of workers necessary to break even or to generate the lowest negative balance was calculated and is used to evaluate how the shredded scrap value affects the business. The lowest value over the three years was observed to drastically affect the business, as it results in a $34,201.54 debt; this low ferrous price however also occurred in the same year as the high prices, which would generate a profit of $62,749.76 (with two workers). One can therefore assume that in general the business will gain a profit and yearly lows will be counterbalanced by yearly highs. Challenges would be associated with labour availability and retention, and managing overhead costs. A functional business model would ideally have workers working variable hours per week to take into

Expenses Revenues # Workers = 2 Cars/hr = 4.47 $/tonne = $369.12 tonne/car = 0.0267 $/hr = $44.10 8 hours per day, 252 days per year TOTAL: $88,915.39

-Minimum wage @ $10.25 - Rent $6/sq ft - Utilities $3.25/sq ft Labour = $41,328 Rent = $28,800 Storage = $1,200 Utilities = $15,600 Tools = $747.43 Safety Eq. = $39.05

Profit

$1,200.90

TOTAL: $86,514.49

Figure 7: Total revenues and expenses of dismantling business when scrap ferrous = $369.12.

End of Life Management - Selected Applications

481

consideration the price of ferrous scrap in order to maximize profit. However, this model does serve its purpose to prove that the business would, on average, be profitable for dismantling seats. Shredded Ferrous Scrap PRICE ($CDN) per tonne 3 YR low

Workers

ELVs per year

Annual Net Profit

2

9,003

-$34,201.54

$212.17

3 YR high

$619.65

1

4,501

$9,174.88

3 YR AVG

$348.30

3

13,504

$1,628.52

2010 AVG

$369.12

2

9,003

$2,400.90

Table 5: Sensitivity analysis of the business plan, with the assumption that workers work 8 hours per day, 5 days per week, 252 days per year (basic standard in Canada). 5

SUMMARY, CONCLUSIONS AND FURTHER WORK

Recycling in Canada is a profit driven business and is typically performed by small to medium size business enterprises. There are regulations that require dismantlers to remove substances harmful to the environment and shredding equipment, but not ASR. Seeing as though a significant amount of ASR is comprised of materials present in vehicle seats, a systems approach was taken to investigate the viability of recycling. An understanding of the material composition and interfaces is necessary to distinguish between disassembly and dismantling operations for the vehicle seats. Dismantling times were calculated using MOST and assumptions were made relating to factors that influence the business: labour, facilities and potential revenues. These factors will vary based on regional regulatory guidelines and market forces; however within the Ontario market the business was found to be marginally viable. Future work includes addressing supply chain and logistics issues. A bottleneck may be found when finding a dedicated re-bonding facility in the area and although the polyurethane foam could present an additional source of income the ability to find a customer could be supplemented through decreasing this profit margin. The generation of markets for polyurethane foam could also become a reality through a change in legislation. In the event that WDA 2002 is passed and automotive recyclers have to meet strict recycling targets, the government could develop grants to help businesses develop that recycle ASR materials into new products. If polyurethane foam could be sold to manufacturers, it could potentially increase business profits up to 44%. Regardless of changes in government, market conditions, or vehicle design the parameters of the business model will stay predominantly the same, the only difference will be in data. Further research will be required to compare the cost effectiveness of preshredder versus post-shredder ASR recycling. Little research has been done focusing on pre-shredder ASR recycling within the North American market in comparison to the amount done on postshredder solutions. This will be essential to determine which ASR solution to pursue, once ASR is required to be diverted from landfill. 6

ACKNOWLEDGMENTS

The authors would like to thank ACME Auto Parts in Windsor, Ontario for their generous contribution of vehicle seats for the data collection.

7

REFERENCES

[1]

Recycling Council of Ontario. (1999): Management of End-ofLife Vehicles in Ontario: Report, Proceedings and Draft Recommendations of the RCO Roles and Responsibilities Forum.

[2]

Sawyer-Beaulieu, S. S.; Tam, E. K. (2005): Applying Life Cycle Assessment (LCA) to North American End-of-Life Vehicle (ELV) Dismantling and Shredding Processes. SAE Technical Paper Series, SAE International 2005-01-0846.

[3]

Staudinger, J.; Keoleian, G. A. (2001): Management of Endof-Life Vehicles (ELVs) in the US. University of Michigan: Center for Sustainable Systems.

[4]

Ministry of Environment of Ontario. (2008): Towards a Zero Waste Future: Review of Ontario`s Waste Diversion Act, 2002, Ontario.

[5]

Ministry of Environment of Ontario. (2009): From Waste to Worth: The Role of Waste Diversion in the Green Economy, Ontario.

[6]

Coulter, S.; Bras, B.; Winslow, G.; Yester, S. (1996) Designing for Material Separation: Lessons from Automotive Recycling. The 1996 ASME Design Engineering Technical Conference and Computers in Engineering Conference, pp. 1-11, Irvine, California.

[7]

Sawyer-Beaulieu, S. S.; Tam, E. K. (2008): Constructing Gate-to-Gate Life Cycle Inventory (LCI) of End-of-Life Vehicle (ELV) Dismantling and Shredding Processes. SAE Technical Paper Series, SAE International 2008-01-183.

[8]

Ontario Tire Stewardship. (2010): Tire Recycling in Ontario. Retrieved June 8, 2010, from Tire Recycling in Ontario: Industry Rolls Old Tires into Green Products: https://www.ontariots.ca/?q=TireRecOntario.

[9]

Motor Trend. (2010): 2001 Dodge Neon Specifications. Retrieved November 14, 2010: http://www.motortrend.com/cars/2001/dodge/neon/specifi cations/index.html.

[10]

Mark, F. E.; Kamprath, A. (2004): End-of-Life Vehicles Recovery and Recycling Polyurethane Seat Cushion Recycling Option Analysis. SAE Technical Paper Series, SAE International 2004-01-0249.

[11]

Recycle Net (2010): Scrap Index. Retrieved November 15, 2010, from Historical Prices of Baled Preconsumer PU: http://www.scrapindex.com/plastic/usa/polyurethane/index.ht ml.

[12]

Parikh, D. V.; Chen, Y.; Sun, L. (2006): Textile Research Journal, Vol. 76, No. 11, pp. 813-820.

Eco Quality Polymers-EQP 1

Conrad Luttropp , Emma Strömberg 1 2

2

Department of Machine Design, Royal Institute of Technology (KTH), Stockholm, Sweden

Department of Polymeric Materials, Royal Institute of Technology (KTH), Stockholm, Sweden

Abstract Polymers are materials worth recycling rather than incinerate. This calls for higher efficiency in recycling. To take a step in this direction a study is made on how much of the polymer fraction of an electric product that is allocated to the housing of the product. The study showed that a presorting of products according to polymer content of the shell and afterwards a fragmenting process where polymers and metals are separated would give a polymer fraction dominated by the housing polymer. Keywords: Life Cycle Engineering; Polymer Recycling; EcoDesign

1

INTRODUCTION

Recycling of polymer waste is growing; from landfill or incineration to material reuse. Mechanical recycling of polymers involves collecting, separating and sorting of products containing polymers. Recycling processes have so far been concentrated on extracting the most valuable materials or components out of the waste stream; gold, copper, steel etc. The Eco Quality Polymer (EQP) concept is a research project where present priorities on polymer recycling are questioned. A lot of efforts are today spent on separating polymer qualities according to type of polymer. However, recycled ABS is not the same as virgin ABS. The aim of EQP project is to investigate whether a sort in strict polymer families is necessary or not. The difference between recycled and virgin polymer is large and the two together makes a third quality that should be regarded as a new less quality on its own. Recycling of valuable metals concentrates on extraction at lowest cost, leaving the rest in a mess. A more general recycling strategy would give higher outcome and efficiency for all materials in the waste stream. Waste electrical and electronic equipment (WEEE) [1] contain valuable metals but also large amounts of polymers. Small house hold equipment generally has a plastic shell. A recycling process taking this into account with an initial separation of polymers and the WEEE-core (the electrical and electronic intestines), will raise recycling efficiency. Extraction of polymers is more expensive if done after fragmentation of the product. At this point metal residues are likely to be blended into the polymer fraction, putting demands on extra cleaning of the polymer fraction. 1.1

Polymer recycling

Increasing the recycling of polymer materials is important, since recycling of polymer materials has been mostly focused on energy recovery of the material. Stricter legislation demands not only energy recovery but recycling and reuse of polymeric material.

life-cycle perspective. As shown by Dodbiba et al [2] mechanical processing and reuse of polymers is, compared to energy recovery, beneficial from a green house effect perspective. This point of view is supported by Finnveden et.al. Recycling is according to their life cycle assessment study better than energy recovery for all solid waste [3]. More specifically, if one or a few specific product groups are diverted into a separate waste stream by means of a controlled source sorting that would facilitate recycling. 1.2

Quality of recycled polymers

How much does mixing, degradation of, and additives in recycled polymers influence properties of future products? The quality parameters for recycled polymers were first defined by S. Karlsson [4] Villaplana et al has defined a number of parameters influencing the quality of mixed recycled polymers [5], see Figure 1.

Degree of mixing Presence of mixed fractions in recycled plastics

Variation in the Mechanical properties

Degree of degradation

Structural changes (crystallinity, Tg) Chemical changes Contaminants Degradation products Additives

Presence of low Molecular weight compounds Figure 1: Key parameters for the quality assessment of recycled plastics. [5]

Using recycled polymers at a higher value level is important from a

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_83, © Springer-Verlag Berlin Heidelberg 2011

482

End of Life Management - Selected Applications All of the parameters presented in Figure 1 influence the outcome from WEEE polymer recycling. Some of these parameters could be controlled during the product development process, such as additives. Degree of mixing could be influenced by source sorting schemes and stricter use of polymers in products. Reducing the number of different polymers in a product is important in this respect. Parameters relating to the environment during the use phase are harder to target since polymers degrade during the use phase of a product. Better selection of polymers tied to the useenvironment could improve the situation. However, this is depending largely on the users and the user environment. A conclusion from Figure 1 is that defining a polymer recycling process model demands considerations both concerning design and post-use processes. These areas influence the recycling result. 1.3

483 from e-waste must also be recycled, and focusing on the majority resins is the most viable recycling strategy [8]. Dalrymple et al [9] suggests that 20-25% by weight of WEEE is polymeric supporting Fishers earlier statement and in the e-waste polymers there are 20% (by weight) that contain brominated flame retardants, Research performed by Arola and Biddle [10] highlights an important issue; the “chicken and egg” dilemma. Producers of polymer products will not use recycled material if they are uncertain on a steady supply of known quality polymers. Recyclers will not start investing in the necessary plants unless they are certain that they will have a market for recycled polymer material. Furthermore, they present a decision tree for recyclers, see Figure 2.

Improving polymer recycling

It is also possible to sort products in advance based on the housing polymer of each product. If the cord is removed in a pre-step the remaining product is easy to separate with present polymer recognition techniques. Our hypothesis is that sorting small house hold appliances according to polymer content in housing before fragmentation but after removing the power cord will raise recycling efficiency. Preliminary results confirm this hypothesis. 2 2.1

METHOD Recycling unit in Arboga, Sweden

An experiment was made by picking 33 products out of the normal WEEE stream in Sweden. The products were disassembled and weighed in 8 fractions. Two fractions, the shell polymer and the polymers inside, are especially at focus in this paper. 3 3.1

BACKGROUND Recycling in general

Recycling of metals has been done since long due to material prices. Polymers are recycling fractions gaining more and more interest due to raising prices on raw material and environmental concerns. Prior to the implementation of the WEEE directive a lot of work was done to facilitate the anticipated disassembly operation of WEEE products. Economic reality and differences on implementing the WEEE directive in different member states, has given a set of different recycling strategies for WEEE: 

Manual disassembly and sorting of the product and fragmenting of fractions afterwards.



Crushing of the product, separating metals and polymers and fragmenting



Fragmenting of products followed by separation of fractions.

Figure 2: Recycling decision tree. [10] In a previous study, Arola et al [11] compared automated and manual sorting of polymer parts. The aim was to separate different types of polymers for use in high grade applications. They concluded that the sorting degree necessary, defined by them as 99.9% purity, was too costly and could only be achieved by particleby-particle sorting. Instead, they suggested that recycled mixed polymers be used in low grade filler applications. In their automated line they used a near infra-red (NIR) spectroscopy detection device with a throughput of 2.2 ton/h. The manual sorting was done by visually reading labels and when this was not possible by using a spectroscope. The manual line achieved 270 kg/h per worker . To address this issue Fisher suggests using feedstock (chemical) recycling over mechanical recycling in order to, among other aspects, decrease risks connected to processing of end-of-life products containing brominated flame retardants [12]. In comparison to Arola and Biddle [11], Fishers suggestion of a recycling decision tree in view would include feedstock treatment; see Figure 3, [12].

Fragmenting in hammer mills is common for automotives, giving a low quality polymer fraction due to e.g. heat from the fragmenting operation. A so called Hurricane machine used mostly for refrigerators and freezers is giving a higher polymer quality due to the inert atmosphere in the fragmenting chamber. 3.2

Recycling of polymers

As early as 1993 strategies for recycling of polymers was contemplated by Biddle and Christy, then employees at Dow Chemical Company [6]. Fisher et.al presented 10 facts to show the possibilities in polymer recycling. But, as they state, infrastructure is much needed to create a productive recycling environment [7]. The need for efficient collection and transport infrastructure is further stressed by Fisher et al. They point out that from an economical point of view; polymers is a small of part of mixed e-waste, polymer recycling must be seen from a broad perspective: other materials

Figure 3: Recovery processes options for plastics from end-of-life electrical and electronic equipment. [12]

484 3.3

End of Life Management - Selected Applications Present technique

4

What is the then best strategy if we want a high level of polymer recycling on a high quality level? 

Fragmenting first and then separation of polymers out of the resulting WEEE flake stream. Cheap but with a doubtful accuracy and harmful for polymers in general.



Manually disassembly and during the process also sort into fractions. A reliable process with a price much dependent on price labor.



Mill down WEEE separate in a few fractions and export to developing countries for manual final disassembly and sorting. Reliable and cheap dependent on labor prices but also connected to work environment problems



3.4

Mill down WEEE, separate polymers from metals and then sort the polymer material in homogeneous polymer family fractions. Rather expensive and with a semi quality due to over valuing of polymer properties after use and fragmentation. New recycling concept

A more simple way of doing this is to sort products according to the polymer present in the shell this way giving a number of fractions dominated by the housing polymer. The procedure can be the following: 1. Remove the cord or/and the battery 2. Sort products according to housing polymer into batches 3. Fragment gently each batch and separate polymers and metals The result will be batches of polymers dominated by the housing polymer

4.1

POLYMER OUCOME STUDY Recycling unit in Arboga, Sweden

El-kretsen is the Swedish organization handling the practicalities in the WEEE directive in Sweden. Organized by El-kretsen, in a random way, deliveries from collecting facilities in Sweden are picked and delivered to a recycling plant in Arboga Sweden, working for El-kretsen The batch, normally a fully loaded truck, is examined in details concerning type of product, brand, weight, etc. The purpose is for El-kretsen to get a fingerprint of the WEEE stream in Sweden over time. 4.2

Disassembly of 33 samples

From one batch like this, in June 2010, 33 products were picked. The largest product, the smallest product and one intermediate from 11 different categories: Drilling machine, Vacuum cleaner, Computer accessory, Food processor, Home, Hygiene, Hairdryer, Toy, Telephone, TV, Kettle The samples were disassembled and weighed on total weight, of the product, polymer weight in shell and weight of inside polymers. The result can be seen I Figure 4. At the x-axis the 33 samples are oriented in an ascending order related to the y-value. The y-axis show how much of the total polymer fraction that was present in the shell compared to polymer content on the inside. This we call the polymer content distribution (PCD). The PCD value is 100% when there is no inside polymer parts and 0% when there is no visible polymers on the outside. The lowest PCB, sample 1 in Figure 4, was a dvd player with a metal housing and most of the polymer fraction on the inside. Products with a 100% PCD was e.g. a TV-box containing just a WEEE core and a polymer housing.

120% 100% 80% 60% 40% 20% 0% 1

3

5

7

9 11 13 15 17 19 21 23 25 27 29 31 33

Figure 4: The graph show polymer percent content in housing shell compared to polymer on the inside of the product.

End of Life Management - Selected Applications 5

CONCLUSION

This study has so far confirmed our hypothesis that most of the polymers in WEEE are present in the product housing. The consequence is that polymer fractions can be concentrated by a first product sorting step with shell content as sorting argument.

485 [8]

Fisher, M., Kingsbury, T., Headley, L., (2004), “Sustainable electrical and electronic plastics recycling, IEEE International Symposium on Electronics and the Environment”, 2004, Conference Record.

[9]

Dalrymple, I., Wright, N., Kellner R., Bains, N., Geraghty, K., Goosey M., Lightfoot, L., (2007), “An integrated approach to electronic waste (WEEE) recycling”, Circuit World Vol. 33, No. 2, Page(s) 52–58.

[10]

Arola, D.F., Biddle, M.B. (2000), “Making plastics recycling from electronic equipment a commercial reality”, Proceedings of the 2000 IEEE International Symposium on Electronics and the Environment, 2000. ISEE 2000, Page(s): 75-80.

[11]

Arola, D.F.; Allen, L.E.; Biddle, M.B., (1999), “Evaluation of mechanical recycling options for electronic equipment”, Proceedings of the 1999 IEEE International Symposium on Electronics and the Environment, ISEE -1999, Page(s): 187191q.

[12]

Fisher, M., M., (2006), “Feedstock recycling technologies in the sustainable recycling of plastics from end-of-life electrical and electronic products”, Proceedings of the 2006 IEEE International Symposium on Electronics and the Environment - Conference Record, Page(s) 292-297.

The next step will be to identify the different polymer fractions of each sample. A typical polymer fraction, using the EQP concept will contain 85% or more polymer of one type and a variety of polymer types in the resting 15%. Preliminary result shows that the distribution of the secondary fraction is more important than the actual quality of this fraction. The present sorting of polymers in original fractions might be unnecessary since the mechanical properties, melting index etc. will differ so much according to products life cycles that recycled polymers is out of the question for exchanging virgin material. Another aim for the EQP project is to organize quality parameters and design guidelines for recycled polymers, using them as original material on a lower level not as exchange for virgin polymers of the same kind. 6

ACKNOWLEDGMENTS

This research is funded by “The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning”, which is highly appreciated. It is made possible by the interested and helpful personal at the WEEE recycling plant in Arboga Sweden. 7

REFERENCES

[1]

WEEE (2002), WEEE Directive (Directive 2002/96/EC of the European Parliament and of the Council 27 January 2003 on the waste electrical and electronic equipment).

[2]

Dodbiba, G., Takahashi, K., Sadaki, J., Fujita, T., (2008), “The recycling of plastic wastes from discarded TV sets: comparing energy recovery with mechanical recycling in the context of life cycle assessment”, Journal of Cleaner Production vol. 16, Page(s) 458-470.

[3]

Finnveden, G., Johansson, J., Lind P., Moberg, G., (2005), “Life cycle assessment of energy from solid waste—part 1: general methodology and results”, Journal of Cleaner Production, vol. 13, Page(s) 213–229.

[4]

Karlsson, S. (2004) Recycled Polyolefins. Material properties and means for Quality Determination in Advances in Polymer Science 169:p 201-229.

[5]

Vilaplana, F, Ribes-Greus, A., Karlsson, S.,(2007) "Analytical strategies for the quality assessment of recycled high-impact polystyrene: A combination of thermal analysis, vibrational spectroscopy and chromatography", Analytica Chimica Acta 604, 18-28.

[6]

Biddle, M. B., Christy, M. R., (1993), “Here today, here tomorrow: challenges of recycling engineering thermoplastics”, Proceedings of the 1993 IEEE International Symposium on Electronics and the Environment, ISBN: 07803-0829-8, Page(s): 194-202.

[7]

Fisher, M., Biancaniello, J., Kingsbury, T., Headley, L., (2003), “Ten facts to know about plastics from consumer electronics”, IEEE International Symposium on Electronics and the Environment, 2003, Page(s): 260- 264.

Intelligent Products to Support Closed-Loop Reverse Logistics 1

1

1

Karl A. Hribernik , Moritz von Stietencron , Carl Hans , Klaus-Dieter Thoben 1

1

BIBA - Bremer Institut für Produktion und Logistik GmbH, Bremen, Germany

Abstract This paper aims to show that Intelligent Products may be used to facilitate closed-loop reverse logistics processes. An analysis of the actors and processes in reverse logistics processes is presented to identify requirements towards the characteristics of a technical concept suitable to support closed-loop reverse logistics processes. That Intelligent Products fulfill the requirements is shown by presenting use cases in selected application scenarios. A critical evaluation of the applicability of the results of the analysis of the actors and processes and their implications for the design of Intelligent Products concludes the contribution. Keywords: Closed-Loop Product Lifecycle Management; Intelligent Products; Sustainability

1

BACKGROUND AND MOTIVATION

Sustainability and consequently reverse logistics has become a vitally important topic for today’s economy. The dramatic increase in global demand for raw materials in contrast with dwindling natural resources, the impact of waste on the ecosystem coupled with the resulting repercussions for society combine to put pressure on industry to develop more sustainable products and services. Moreover, European customers increasingly insist upon such sustainable products and services. Consequently, sustainability has also become a significant marketing instrument, used to attract customers with terms such as “Green Production”. One example of this is how Apple, Inc. advertises its products using a lifecycle-wide analysis of their emitted pollutants. [1] Unfortunately, the unscrupulous use of sustainability topics in advertising is gaining increasing notoriety and has coined the term “Greenwashing”. [2] European Union legislation obliges manufacturers to establish organizational concepts which are supported by suitable technological infrastructures to ensure the profitability of affected products. For example, EU Directive 2002/95/EG restricts the use of hazardous substances in electrical and electronic equipment [3] This directive has been implemented as various national legislations throughout Europe, for example in Germany as the “Elektro- und Elektronikgerätegesetz.” [4] Furthermore, the recycling of waste electrical and electronic equipment (WEEE) is promoted by the EU Directive 2002/96/EG. [5] Since 2003, the disposal of used cars is also regulated by the European Union. Besides directives regarding the use of heavy metals in automobiles, Directive 2000/53/EC specifies the minimum allowable quotient for the reuse end-of-life vehicles. [6] On average, 95% of the average weight of a vehicle is to be reusable by the year 2015. Again, this directive is implemented in European national laws, for example in the German ”Altfahrzeug-Verordnung” or used vehicle act. [7] Last but most definitely not least, the main benefit for companies implementing reverse logistics processes is a significant return-oninvestment. One example is the resale of used products to

customers with lower demands towards quality. Refurbishing, the reuse of individual product components and the recycling of raw materials are other examples of how otherwise “useless” products can be monetised beyond the ends of their lives. [8] Whatever approach is taken to increase the sustainability of a product, it generally implies adopting a holistic perspective upon its entire lifecycle. This means that the interest and investment of the manufacturing company needs to be extended beyond the product’s beginning-of-life (BOL) not only into its middle-of-life (MOL) when it in use and possibly serviced, but also into its end-oflife (EOL) when it is ultimately decommissioned and disposed of. The consequence of this is the need for an information management approach which facilitates knowledge of the product‘s status at any point in its lifecycle. Additionally, information loops need to be closed between the individual lifecycle phases (BOL, MOL and EOL), processes and stakeholders in order to create added value by acting the managed lifecycle information. This paper aims to show how Intelligent Products may be used to facilitate closed-loop reverse logistics processes. An analysis of the actors and processes in reverse logistics processes is presented to identify requirements towards the characteristics of Intelligent Products suitable to support closed-loop reverse logistics processes. Exemplary Intelligent Products fulfilling the requirements are presented in application scenarios. A critical evaluation of the applicability of Intelligent Products to reverse logistics processes concludes the contribution. 2

RELATED WORK

This section presents an overview of related work in literature. It begins with a look at the topic of reverse logistics in general. Subsequently, the state-of-the-art in closed-loop product lifecycle management is discussed. To conclude this section, a brief summary of currents definitions and applications of intelligent products is laid out.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_84, © Springer-Verlag Berlin Heidelberg 2011

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End of Life Management - Selected Applications 2.1

Product Lifecycle

A number of different perspectives towards the product lifecycle exist. Literature broadly differentiates marketing and production engineering ones. [9] The marketing perspective tends to adopt a sales-oriented view upon the product lifecycle, in which the lifecycle is divided into the Introduction, growth, maturity, saturation and degeneration of a product. Here the product seen not as a physical thing only in terms of the degree of its economic success. [10] The scope a product refers to in this view may be a model, type or category.

Figure 1: The Three Phases of the Product Lifecycle. The production engineering perspective used here follows [11] and is shown in Figure 1. In this model, the processes related to the development, production and distribution of the product are arranged into the beginning-of-life (BOL) phase. A product’s utilisation, service and repair are labelled middle-of-life (MOL). Finally, reverse logistics processes take place in the end-of-life (EOL) phase. 2.2

Product Lifecycle Management

Organisational, economic and IT perspectives as well as some more comprehensive views towards product lifecycle management (PLM) are widespread. Today, organisational views highlight the management of lifecycle knowledge in distributed, multidisciplinary and cooperative teams in extended enterprises. [12], [13] Economic views stress the business activity of effectively managing a company's product through their entire lifecycle, from the ideation to disposal, i.e. from “cradle to grave”. [14], [15], [16] The aim here is to increase product revenues, reduce product-related costs, and maximize the value of the product portfolio. From an IT perspective, Product Lifecycle Management (PLM) is commonly understood as a concept which “seeks to extend the reach of PDM […] beyond design and manufacturing into other areas like marketing, sale and after sale service, and at the same time addresses all the stakeholders of the product throughout its lifecycle.” [16] Classic PDM functionality encompasses object, component and document management, classification and search functionality, change management and tools for system administration and configuration. [17] PLM consequently encompasses strategically modelling, capturing, exchanging and using information and data in all decision-making processes

487 throughout the product lifecycle. [14], [18] It implements an integrated, cooperative and collaborative management of product data along the entire product lifecycle. [19] 2.3

Reverse Logistics

Once a product has fulfilled its original use, it is decommissioned and enters into the “disposal” or EOL phase of its lifecycle. The processes which EOL consists of are generally summarised with the term “reverse logistics”. However, the term is not always used coherently in literature. The following exemplify the main schools of thought in the field. Kroon and Vrijens define reverse logistics as “the logistic management skills and activities involved in reducing, managing and disposing of hazardous or non-hazardous waste from packaging and products.” [20] In this definition, on the one hand logistics activities such as the transportation of a product to the disposal plant and on the other processing tasks such as repairing a product for reuse are conflated in the term. This definition furthermore encompasses organisational processes. In contrast, Dowlatshahi [21] focuses more specifically on logistics processes: “Reverse logistics is a process in which a manufacturer systematically accepts previously shipped products or parts from the point for consumption for possible recycling, remanufacturing, or disposal.” Furthermore, a reverse logistics system encompasses a “supply chain that has been redesigned to manage the flow of products or parts destined for remanufacturing, recycling or disposal.” [ibid.] A supply chain is generally understood to span manufacturers, suppliers, all intermediate stakeholders and concludes with the end customer. In the field of reverse logistics this idea is reflected in concept of the reverse supply chain, i.e. the expended product is transported “back” either to the beginning of a “new lifecycle” or towards its terminal disposal. [22], [23] Both positions are summarised by Fleischmann, et al. [24] Here, reverse logistics “encompasses the logistics activities all the way from used products to no longer required by the user products to products again useable in the markets.” This approach to reverse logistics closes the loop in the material flow from EOL to BOL. 2.4

Closed-loop Product Lifecycle Management

Traditionally, IT solutions supporting PLM focus on classes of products and variants rather than individual items. Furthermore, they mostly address the initial phases of the lifecycle. They offer document, workflow and project management functionality. This approach renders their potential for enhancing reverse logistics processes limited from the perspective of the seamless availability of data, information and knowledge from the entire product lifecycle, including MOL and EOL phases. Many different technical and non-technical approaches address reverse logistics processes. One which has raised significant industry attention is the concept of Closed-loop Product Lifecycle Management. [25] Closed-loop PLM describes an approach to PLM which facilitates the closing of information loops between the individual phases of the product lifecycle. It aims to achieve a pervasive availability of relevant product information at any point in the product lifecycle. Furthermore, the concept deals with closing information loops between different IT layers, from the data acquisition, through middleware and knowledge transformation layers to the business application layer. In order to do so, the concept proposes different methods of applying information technology. [26], [27], [28], [29], [30] With Closed-loop PLM, a paradigm shift from „cradle to grave” to “cradle to cradle” is put forward. [31] 2.5

Intelligent Products

“Intelligent Products” are physical items, which may be transported, processed or used and which comprise the ability to act in an intelligent manner. McFarlane et al. define the Intelligent Product as

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End of Life Management - Selected Applications

“a physical and information based representation of an item [...] which possesses a unique identification, is capable of communicating effectively with its environment, can retain or store data about itself, deploys a language to display its features, production requirements, etc., and is capable of participating in or making decisions relevant to its own destiny.” [32] The degree of intelligence an intelligent product may exhibit varies from simple data processing to complex pro-active behaviour. This is the focus of the definitions in [32] and [33]. Based on these definitions, the level of Intelligence of Intelligent Products can be divided into three dimensions and characterised as follows: [34] Information Handling, Event Notification and Decision Making. This is the first dimension of the Intelligent Product. When each object has its own intelligence, it does not necessary mean that the intelligence is located at the object. In the second dimension, two extremes can be identified: Intelligence through the Network and Intelligence at the object. Finally, the third dimension of the Intelligent Product is the aggregation level of the product intelligence. In general, two levels can be differentiated: Item level and Container level. 3

ANALYSIS OF THE REVERSE LOGISTICS

PROCESSES

AND

ACTORS

creation of a new product are shown. These include, for example, all intra-logistics processes in which products, component parts and materials are transported through end-of-life processes, as well as the organization, managerial and financial control of the reverse logistics processes. Finally, the core EOL processes are illustrated on the top left of the EOL segment in Figure 2. After identifying the processes in EOL in literature and modelling them using BPMN, the next step was to develop a system of categorisation. A harmonisation of terminology was required, due to the often inconsistent use in literature. For example, “recycling” is often used to describe reverse logistics in general, whereas it can also carry the specific meaning of breaking products down into raw materials. The resulting categorisation is meant to be applicable to a wide spectrum of products and consequently does not drill deeply into detailed process layers.

IN

The review of related work presented above shows that current IT solutions supporting PLM are often not adequate for the management of item-specific product information beyond BOL. This is mainly due to the fundamental changes in the context of the product and the resulting consequences for data management approaches. During the conception and the production phase, only a few stakeholders are involved in the management of product data. These either belong to a single organisation or are tightly coupled to the IT landscape prescribed by the main stakeholder. Responsibility for the product lies with the manufacturer, who also grants physical access to it. The data models and management systems used serve a limited amount of well-known tasks and objectives which are dictated by the manufacturer coordinating the PLM network. It follows that, in order to develop an IT concept capable of supporting PLM in the EOL phase, first a sound understanding of the processes and actors involved in reverse logistics needs to be developed. 3.1

Methodology

In order to comprehensively identify the processes and actors in EOL, the first step was a thorough analysis of general EOL descriptions and use cases and in literature. First, UML (Unified Modelling Language) Use Case diagrams were used in order to capture the actors involved in EOL activities. In a second step, the processes themselves were modelled as BPMN (Business Process Modelling Notation) diagrams. The aim of the application of the methodology was to achieve as generic a view of EOL processes and actors as possible. The focus was laid upon identifying processes and actors common to a wide range of reverse logistics cases. Consequently, very individual characteristics of specialised, domain-specific EOL processes and actors were subsumed under more generic headings where possible. The following sections present the results of the identification of processes and actors. 3.2

Categorisation of the Processes and Actors of Reverse Logistics

The identified categories are shown in Figure 2 integrated into the product lifecycle model from Figure 1. On the top right of the EOL process segment, the preparatory processes common to all reverse logistics cases are grouped. These encompass the decommissioning of a product, its collection, sorting and inspection. At the bottom, the organisational and logistics processes which permeate the entire EOL phase from decommissioning to the

Figure 2: Reverse Logistics Processes in the Product Lifecycle. In its most simple form, Reuse describes the redistribution of a product without extensive post-processing. Two alternatives are possible – the whole product or individual component parts may be reused. Refurbishing means the overhauling of a product before it is redistributed. Similar to reuse, this process may be applied to the whole or parts of a product. Also, some parts may be overhauled whilst others are simply reused. The aim of Remanufacturing is to make a product or parts thereof new. This means, some components of the product might be replaced with new ones. A remanufactured product should fulfil the same quality standard as a new product. Whereas the previously described core processes target the reinstatement of the product’s original functionality, Recycling disregards this aspect. The aim here is to break down the product into as homogeneous as possible raw materials. These raw materials may then be used to create new products in a further loop of the product lifecycle. As touched upon above, a single product may be dismantled and its individual components may be introduced to different core EOL processes. Also, the target lifecycle phase may be different from product to product. A refurbished product, for example, may be returned to the original owner or resold in retail. These flows are illustrated in Figure 3. Here, circular nodes represent XOR decisions, and square nodes OR decisions.

End of Life Management - Selected Applications

489 legislation influences all processes, but acts directly only in an organisational manner. 4

The above analysis reveals that reverse logistics processes encompass preparatory processes such as decommissioning, collection, sorting and inspection, the core end-of-life processes such as reuse, refurbishing, remanufacturing, recycling, and disposal, as well as the auxiliary organizational and logistics processes. Here, approaches to information management are often less developed than in other fields of logistics. The characteristics of the stakeholders involved in reverse logistics identified in Table 1 processes exacerbate this problem. For example, manufacturers are often involved only in the initialization of end-of-life processes and have little contact with recycling contractors. This lack of an integrated information management approach leads not only to inefficiency in the end-of-life processes themselves but also to the neglect of information sources which may be of value to other processes in the product lifecycle.

Figure 3: Process Sequence in Reverse Logistics.

Organisational Processes 

Disposal 

Recycling 

Remanufacturing 

Refurbishing 

Reuse 

Sorting 

Collection 

Inspection

 

Product Owner 

 

 

 

 

 

 

 

 

 

 

Product User 

 

 

 

 

 

 

 

 

 

 

Executive Officer of the Plant Operator 

 

 

 

 

 

 

 

 

 

 

Worker at the Plant 

 

 

 

 

 

 

 

 

 

 

Vendor of the Plant Operator 

 

 

 

 

 

 

 

 

 

 

Executive Officer of the Logistics Company 

 

 

 

 

 

 

 

 

 

 

Worker at the Logistics Company 

 

 

 

 

 

 

 

 

 

 

Product Manufacturer 

 

 

 

 

 

 

 

 

Product Distributor 

 

 

 

 

 

 

 

 

Municipality 

 

 

 

 

 

 

 

 

Legislator 

 

 

 

 

 

 

 

 

Logistics Processes 

The distribution of actors across the individual reverse logistics processes is shown in Table 1. These actors consequently participate in all four preparatory processes. In some sectors, the municipality may be responsible for organising the decommissioning of certain goods. Examples can be found in communal waste collection. Reverse logistics plant workers are also involved in all of these processes except for decommissioning. They are also involved in all of the core processes, as are the executives and vendors of EOL plants. Executives and workers at service providers providing reverse logistics services are involved in the collection process, as well as the logistics processes underlying the core processes. The logistics executives are furthermore responsible for organisational processes. In some cases the logistics actors may be the same as the plant actors. Decommissioning 

IMPLICATIONS FOR CLOSED-LOOP REVERSE LOGISTICS

Table 1: Distribution of Actors over Reverse Logistics Processes. The product manufacturer is a special case. For most products, the manufacturer is not directly involved in reverse logistics processes. At best the manufacturer will subcontract service providers to carry out EOL activities. There are however, cases in which the manufacturer deals with EOL directly. In this case, the reverse logistics plant and logistics operators may belong to the manufacturer. In any case, the manufacturer’s product design and production choices directly affect the type of reverse logistics processes the product can be introduced to at EOL. Finally,

4.1

Closing EOL Information Loops with Intelligent Products

It follows that such a Closed-loop Product Lifecycle Management approach necessitates an IT concept and infrastructure capable of acquiring, transmitting and managing such information for individual products throughout their entire lifecycles. A technological means is required to integrate the disparate actors and respective information systems across the product lifecycle. Often, the product or component part to be disposed of is the sole link between all of the product’s stakeholders. One promising concept to address this problem may be found in Intelligent Products. By implementing identification and information processing capability directly into products and component parts, information may be exchanged to and from reverse logistics processes. 4.2

Use Cases of Exemplary Intelligent Products

The following two use cases exemplify their use in sectors in which, as described in section 1, legislative and societal pressure is high to find solutions for more sustainable products – the automotive and electronic and electrical goods sectors. The first exemplary use case of closing information loops in reverse logistics with Intelligent Products deals with the recycling of plastic automotive parts. The second deals with the lifecycle management of electronic equipment including reverse logistics processes. Recycling Plastic Automotive Parts In this use case, a continuous product information management is achieved by means of RFID and sensor-based Intelligent Products from the usage phase, over the preparatory and core reverse logistics processes back into the BOL phase of a new product. Plastic automotive parts are heterogeneous goods which are transported employing a variety of containers. In this use case, two forms of Intelligent Product are used. Firstly, Product Embedded Information Devices (PEIDs, for example RFID tags) are embedded into the plastic parts in order to both identify the type of part and the material it is made of and to track any changes made to the material by repairs, service or replacement in the usage phase. Secondly, the recycled material is also made “intelligent”. In this case, embedded devices are packed in such a way that they are immersed within the recycled material (plastic granulate), as shown in Figure 4. These embedded devices provide unique product identification, memory for the storage of product data and sensor facilities, for example a thermometer for the monitoring of easily inflammable plastic granulates. The embedded devices establish a wireless connection available to devices equipped with suitable readers. Terminals are used as an example of such devices and are understood to represent PDAs, workstations or stand-alone

490

End of Life Management - Selected Applications

readers connected to the main enterprise systems. For example, PDAs or other devices can be employed e.g. by shop floor personnel or logistics operators to carry out a number of operations upon information transmitted by the embedded devices. These devices are then used as relay stations to backend systems through a dedicated middleware layer which in turn provides input to a Decision Support and Product Data Management system. Supplier

Recycler

Customer

PP-EPDM

PP-EPDM

PP-EPDM

PP-EPDM

PEID

PEID

PEID

PEID

Plastic Products

Reader/ Terminal

Milled

Granulate

Reader/ Terminal

Reader/ Terminal

Granulate

Reader/ Terminal

Figure 5: Example of EOL Events in EOL (Decomposition).

Data Filter / Middleware Decision Support System

5

Product Data Management

WMS

Track + Race

WMS

PPS

WMS

Figure 4: Intelligent Products in EOL of Plastic Automotive Parts. Reverse Logistics of Electronic Goods This use case exemplifies the application of RFID-based Intelligent Products in the field of electronic goods. It encompasses the entire product lifecycle, from the assembly of the electronic product, through its usage phase into the preparatory and core reverse logistics processes. The electronic product comprises of a chassis upon which a mainboard, a processor, an ISDN modem, a mains unit, a display and a hard drive are mounted. Each needs to be handled separately in EOL, dictating the requirement of an individual tracking and tracing of each component throughout the product lifecycle. Furthermore, the management of the aggregation of these components comprising the main product needs to be taken into account, allowing for the management of parts replacement and maintenance in the middle, usage phase of the product’s lifecycle. Each of the component parts is assigned a unique identifier which, stored on an RFID chip applied to each component, is used to track and trace the components throughout the lifecycle. On this basis, each individual object can be tracked independently and real-time information about each individual object can be collected, stored and acted upon. In order to enable cooperation partners to seamlessly query such information throughout the product lifecycle, including the collaboration partners in the EOL phase, a standard interface to that information is required. This may be realised using e.g. EPCIS (Electronic Product Code Information Services) or PMI (PROMISE Message Interface). In EOL, the Intelligent Product is decommissioned, decomposed, and its individual product parts selected for recycling, refurbishing, reuse or disposal. Using the information stored on the RFID and the data generated throughout the lifecycle, component parts can be precisely identified and disposed of, the type of disposal along with the time need to be documented in order to fulfil legal requirements. By leveraging EPCIS or PMI, the precise time, location and responsibility details of the decomposition operation can be recorded (cf. Figure 5), along with information regarding the type of disposal (for example recycle, refurbish, or reuse). The event information can be used by the manufacturer and the part suppliers to document their fulfilment of their legal obligations to provide suitable disposal services which satisfy their legal obligations.

CONCLUSIONS AND OUTLOOK

This contribution has presented the results of an analysis of the processes and actors in reverse logistics. It has shown that closing the information loops arising between BOL, MOL and EOL and in EOL itself is difficult due to the distribution of actors across the processes. On that basis it has suggested Intelligent Products as potentially beneficial for closing the information loops found in reverse logistics and achieving an integrated closed-loop PLM. Two use cases from prominent sectors of industry with relation to sustainability demonstrate the feasibility of that approach. The categorisation of reverse logistics processes and the actors involved is, as previously mentioned, a generic, high-level view of the EOL phase. It is designed to be applicable to a wide range of products. However, it cannot do justice to the details of highly specialised EOL processes in each sector. Consequently, future work in this area could include a detailed analysis of the processes and actors in individual sectors of industry. On this basis, a complimentary categorisation of the required characteristics of Intelligent Products to fulfil the requirements of individual types of products in these sectors could be established. 6

ACKNOWLEDGMENTS

This research was partially funded by the German Research Foundation (DFG) within the Collaborative Research Centre 637 Autonomous Cooperating Logistics Processes - A Paradigm Shift and its Limitations. 7

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Kiritsis, D.; Bufardi, A.; Xirouchakis, P. (2003): Research issues on product lifecycle management and information tracking using smart embedded systems. In: Advanced Engineering Informatics 17, Nr. 3-4, pp. 189–202

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Terzi, S., Ball, P. D., Bouras, A., Dutta, D., Garetti, M., Gurumoorthy, B., et al. (2008): A new point of view on Product Lifecycle Management. In Proc. of 5th International Conference on Product Lifecycle Management, Seoul, Korea. Garetti, M., Terzi, S., Bertacci, N., Brianza, M. (2005): Organisational change and knowledge management in PLM implementation. International Journal of Product Lifecycle Management, 1(1), pp.43-51.

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Stark, J. (2005): Making Progress with PLM. A Manual to Support PLM Initiatives and PLM Projects. John Stark Associates

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Gomes, J., Vallejos, R. (2007): Applying a benchmarking method to organize the product lifecycle management for aeronautic suppliers. In M. Garetti, S. Terzi, P. D. Ball & S. Han (Eds.), Product Lifecycle Management Special Publication 3, pp. 3-10. Bergamo/Milano.

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Golovatchev, J. D., Budde, O. (2007): A holistic Product Lifecycle Management framework facing the challenges of 21st century. Paper presented at the 3rd International Conference on Lifecycle Management, ZurichAmeri, F.; Dutta, D. (2005) Product Lifecycle Management - Closing the Knowledge Loops. Computer-Aided Design and Applications 2 (5). pp. 577-590. Abramovici, M.; Sieg, O. (2001): PDM – Technologie im Wandel – Stand und Entwicklungsperspektiven. Orientierung für die Praxis. Industrie Management 17, Nr. 3. pp. 71-75.

The Prospects of Managing WEEE in Indonesia Jessica Hanafi*, Helena J. Kristina, Eric Jobiliong, Agustina Christiani, Audry V. Halim, Dwiyono Santoso, Eliss Melini Department of Industrial Engineering, Faculty of Industrial Technology, Universitas Pelita Harapan Karawaci, Banten 15811, Indonesia

Abstract The problem of managing e-waste (WEEE) is an emerging issue in developing countries. Currently, developing countries, such as Indonesia, often become the e-waste landfill of developed countries. Some local communities are starting to raise awareness in this issue. Therefore, this paper is focused on identifying Indonesia's current status on environmental labeling, customers' willingness-to-recycle behavior and current e-waste recycling methods. The research is conducted based on literature survey, field survey and a questionnaire. This paper aims to acquire information on how the Indonesian households manage their e-waste, the technology applied to recycle those e-wastes and the prospect of managing WEEE. Keywords: WEEE; Customer Behavior

1

INTRODUCTION

Electrical and electronics equipments have become inseparable parts of daily human activities. This is not the condition that only occurs in developed countries but also in many developing countries. In 2007, Indonesia produces more than 3 billion units of electronics equipment, comprises of household electronics, IT equipments and consumer equipments [1]. In the same year, the annual consumption of television reached 4.3 million units while refrigerator reached 2.1 million units and air conditioners and washing machine each reached 900,000 units [2]. This made Indonesia as one of the biggest consumer of household electronics in Asia. Based on the data provided by the Indonesian Cellular Telephone Association, there are approximately 180 million mobile phone users in Indonesia up until 2010. Indonesia is also the second largest user of Blackberry smartphones. This data implied to a massive amount of potential waste that will be discarded or are already in the landfill. This excludes the amount of electronic waste sent from developed countries. Although the Bassel Convention has restricted e-waste trading, Indonesia is still receiving a certain amount of illegal import of e-waste [3, 4]. The management of e-waste has been strictly regulated in Europe and other developed countries through EU Directives on Waste Electrical and Electronics Equipment (WEEE) and other similar regulations. However, this is not the case in developing countries such as Indonesia. The objective of this paper is to identify the current condition in Indonesia. This condition is captured from four aspects, namely legal aspect, social aspect, supply chain network aspect, and technological aspect. These aspects will structure the layout of this paper. First, we will discuss the regulations related to electronic waste management in Indonesia. Second, the social aspect is captured from a survey conducted in Jakarta Capital Region to discover the willingness of the society to recycle their end-of-life electronics and their current behavior. The next section discusses the supply chain network of e-waste currently found in Indonesia, especially in Jakarta and Bandung. This network is investigated based on a field survey. The survey also discovered how the

recyclers in the network reprocess e-waste to recover precious materials. Finally, this paper is concluded with the prospects of managing WEEE in Indonesia and its challenges. 2 2.1

LEGAL ASPECT Environmental Regulation

Currently Indonesian government does not have specific regulation on managing electronic waste. Therefore, e-waste management is regulated through hazardous waste regulation. The Law of the Republic of Indonesia No. 23 year 1997 on Environmental Management stipulates that every liable person or any business and or activity must be responsible to manage the waste resulted from their activity. Generator of hazardous waste, in addition, should comply with regulation concerning hazardous waste management. Hazardous waste management is then further regulated on Article 7 of the Government Regulation number 85 year 1999. This regulation defines and classified hazardous waste into three groups, namely hazardous waste from non specific sources, specific sources and unused material contain or is contaminated by hazardous material or substances such as expired chemicals, spills, packaging waste and off-specification material or products. This also includes other wastes that exhibit hazardous characteristics. Furthermore, other regulations related to e-waste management are also enacted. These are regulation on the importation of used product for reconditioning, remanufacturing or re-use (Decree of Ministerial Trade No. 63/M-DAG/PER/12/2009), regulation on importation of Non Hazardous Waste, such as scrap (Decree of Ministerial Trade No. 39/M-DAG/PER/9/2009) and the regulation of prohibition of hazardous waste import (Decree of Ministerial Trade and Industry No. 520/2003) [4]. Although using these regulations it seems that WEEE can fall into hazardous waste category, the problem is that hazardous waste management law is often regulated to industrial consumers. Meanwhile, WEEE is usually discarded privately from households. Therefore, this problem should also be indicated by household

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_85, © Springer-Verlag Berlin Heidelberg 2011

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End of Life Management - Selected Applications waste management regulations. Currently, most of the domestic wastes are sent to the landfill. Some of the e-waste may be sent to the landfill as well together with domestic waste. However, domestic waste management is still a huge problem in Indonesia. As Meidiana and Gamse [5] suggested that the reason why the waste management in Indonesia is still low is due to the lack of waste policies in national level and low waste regulation enforcement in local level. The level of service for municipal waste management was 41.288% in 2005. This percentage increased to 56% in 2006 and is still a work in progress if they want to achieve the target of 70% in 2014 for urban waste service [5]. What happened to WEEE in Indonesia will be discussed further in the technological aspect of this paper. 2.2

Environmental Labeling

In addition to government environmental regulation, environmental labeling or eco-labeling programs are widely used in the developed countries to inform consumers of environmentally friendlier products. These labels provide means for regulatory authorities to encourage firms to improve the environmental quality of their products. Currently, the Indonesian government is working on Eco-label Type I, based on ISO 14024, and Eco-label Type II for a small number of products. Products that are currently in process of certifications for Eco-label Type I are still limited, such as uncoated printed-paper, detergents, textiles, leathers apparels and leather shoes. Meanwhile, the products that are targeted to fall into Eco-label Type II category are detergents, dry-cell battery, electronics and electrical equipments and “green” vehicles. However, government is still discussing on the development of Eco-label type II. Different to those in the developed countries, the objective of implementing Eco-label in products produced in Indonesia is not for fulfilling Indonesian customer’s requirement of environmentally friendly products. The main aim is to have a product that can be sold to developed countries, especially the European market. However, because Eco-label is still under development, there are two approaches that are implemented by the Indonesian government to bridge the gap.

493 3

SOCIAL ASPECT

Previous section has discussed the legal aspect of WEEE management, how WEEE has not been addressed specifically in a regulation and what is Indonesia’s position regarding environmental labeling. Although regulations may trigger environmental awareness, currently society has become more aware to the environment. Green communities and environmentalist exist commonly in the form of electronic mailing list forum, internet social network [6-8] and many others. However, these communities only represent a minuscule part of Indonesian society. These communities usually address issues such as reforestation, domestic waste management and natural disasters. Very few have addressed issues on WEEE management. Therefore, to address this issue, information on the society’s knowledge about e-waste is required. A survey was conducted in this research to capture the Indonesian consumer behavior on managing their e-waste and their willingness to recycle. The survey was conducted for five weeks around Jakarta Capital Region by using in-person and electronic surveys. There were 180 respondents, which comprises of male (50%) and female (50%) respondents. Twenty eight percent of the respondents lived in East Jakarta while 26%, 21%, 17% and 8% lived in West Jakarta, South Jakarta, North Jakarta and Central Jakarta, respectively. These figures represents the actual households percentage of Jakarta Capital Region where 28% lived in East Jakarta, 24%, 23%, 16% and 10% lived in West Jakarta, South Jakarta, North Jakarta and Central Jakarta, respectively. Most of the respondents were university graduates (57%), 24% were high school graduates, and 19% were postgraduates. The survey result shows that 23% of the respondents did not know about e-waste issues, while 33% heard it from a campaign organized by environmental community and 18% from educational institution. This is shown in Figure 1.

The first one is by setting up an Indonesian National Standard (SNI) to protect the local industry and consumer. SNI was first used as a standard for eleven types of products in 2009. These products include primary battery, helmet and safety shoes. In 2011, Indonesia and other South East Asian countries have agreed to standardize 199 more products, including electronics and electrical equipments. The second approach is by getting an accreditation for the government-owned surveyors (SUCOFINDO) as the national certification organization by the International Electrotechnical Commission (IEC). This accreditation allows SUCOFINDO to test and certify electronics and electrical equipments in Indonesia. Manufacturers of certified products will be able to market and sell their products globally. The products which are eligible for certification includes electric iron, washing machine, small household appliances, electric kettle, refrigerator, water pump, electric fan, air conditioners and electric sockets. Nevertheless, it is not impossible that these labeling can be useful for Indonesian market as well. This is due to the fact that Indonesian market is getting more critical in choosing their products.

Figure 1: Respondent’s awareness to e-waste issues. Although 77% have heard about e-waste issue from somewhere, only 8% recycled their old electronics, as shown in Figure 2. Those who recycles usually recycles their electronics through electronic trade-in programs conducted by electronic retailers and through scavengers. Those who did not recycle claimed that they did not know the benefit of recycling (38%) and that it was hard to do (37%). Others claimed that it was not worth the effort, takes time and that it was expensive. 55% of those who claimed that they did not know the benefit were male respondents, where 64% of them were in the age range of 20-30 years old. These figures suggested that the main reason they do not recycle was due to the lack of information and education regarding electronic waste management and the impact of WEEE to the environment.

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Figure 2: Current treatment to household electronics waste. Regarding who should be responsible for these e-wastes, majority of the respondents believed that everybody should be responsible for this issue. Although, 20% and 16% of the respondents agreed that original equipment manufacturers (OEM) and government should be responsible for e-waste management. This survey also examined the willingness to recycle behavior of people in Jakarta. Although most people were not willing to pay more taxes for environmental sustainability, most of them agreed that the tax they paid should be allocated more to the environment. Most of them were also willing to pay more for environmentally friendly products or “green products” but they are not willing to pay any recycling fee associated with it. Since Indonesia is still a developing country, economy is still major consideration in their decision-making. 45% of the respondents stayed neutral in supporting the environment if it sacrificed economic growth. 30% of them were not willing to support it. Nevertheless, when they were asked about whether they are willing to support economic growth that sacrificed the environment, 61% were opposed to that idea. These results show that the respondents actually have some level of awareness of the environment. However, they are not willing to pay extra money for any end-of-life schemes. The idea of paying for recycling is still beyond their imagination. They believe that any recycling activities will produce profit at some level. As a consequence, they should not be paying anything to these collectors. Moreover, the low level of awareness of the environment indicates the need of environmental education and campaign to the society. The willingness of the respondents’ to recycle e-waste is again confirmed from the survey. Based on the question regarding their participation in recycling e-waste in the next five years, the result shows that 58% and 12% of the respondent may be and definitely willing to be involved in the activity (Figure 3). Meanwhile 18% of the respondents still have not decided what they would do in the future. The question lies on how to educate and attract this fraction of the society, who are still uncertain and who would not participate, to be involved in the future. The survey also enquired about the possible method of e-waste collection that they would choose. 39% of the respondents preferred shopping malls as the place for dropping off their e-waste. At around the same percentage (15%) of the respondents agreed that it should be at the office building, school or universities, supermarkets and gas station. Concur to the economy-minded society discussed previously; most of the respondents also prefer trade-in programs to participate in recycling programs rather than using drop-off points or kerbside collection.

Figure 3: Respondents’ willingness to participate in e-waste recycling in the next five years. 4

REVERSE SUPPLY CHAIN NETWORK

Although the Indonesian government legislation has not regulated e-waste management in Indonesia and there is little knowledge about e-waste management in the society, an e-waste management activity is already in practice by informal sectors. A field survey was conducted to investigate the existence of reverse supply chain network of electronics waste, especially on waste of computers and their peripherals. The survey was conducted by interviewing some e-waste recyclers around Jakarta Capital Region and its satellite cities, such as Bogor and Bekasi. Some of them are e-waste dealers and some are e-waste recyclers. The survey found that currently there are four levels of reverse supply chain network for computer waste. These four levels are: 1. End-users; comprises of individual and corporate users. 2. Scavengers and service centres. 3. Sub dealers; some acts as e-waste recyclers. 4. Dealers; export e-waste which cannot be recycled in Indonesia. The procurements of these used electronics are differentiated based on the type of users. E-waste from individual users were gathered by scavengers and service centres. Scavengers usually buy out-of-date or broken electronics from one household to another. They usually travel by foot around a neighbourhood in search of valuable materials. They gather their findings in a collection centre where recyclers come to buy them. Meanwhile, the service centre collects unrepairable products. The parts that still in working condition are sent to the remanufacturing centres while the unrepairable ones are sold to the sub dealers to be recycled. This is accorded with the collection programs conducted in other developing countries [9]. Corporate users usually operate a large number of electronics and electrical equipments, such as computers. Every once in a while the computers, which no longer fulfill the requirement of the company, are discarded. The company then will hold a regular auction to recycle these e-wastes. The bidders are sub dealers or agents representing the sub dealers, who then reprocess and recycle these e-wastes for material recovery. There are a number of sub dealers in Indonesia. They usually reside in the city. Widyarsana et al [10] categorized these sub dealers into three categories according to the amount of e-waste collected per month, namely small collectors (<100 units/month),

End of Life Management - Selected Applications

495

medium collectors (100-1000 units/month) and large collectors (>1000 units/month).

mixed metals and plastics in PCBs. Each of these streams are sorted and sent to their respective industries for recycling.

As mentioned previously, some of these sub dealers also recycle the e-waste, especially wastes of printed circuit boards (PCB) from computers. Details of the technology used for recycling these ewastes will be explained in the next section. These sub dealers are the last chain of the recyclers. However, as traders of e-waste, there is another level in the supply chain. Some of the e-wastes, which are less profitable to be recycled by the sub dealers, are sold to the big dealers.

The CPU case and other parts that are made of iron are sold to iron processing plants. Similar procedures occur to those made of copper and aluminum. Meanwhile, since the plastics contained in electronics and electrical equipments consist of various types of plastics, the process of recycling these plastics is not a simple procedure. Most of the plastic recyclers currently operating in Indonesia recycle plastics waste from drinking bottles and cups that are made of polypropylene and polyethylene. These recyclers do not process other types of plastics. As indicated in [11], there are at least four types of thermoplastics contained in electronic wastes, namely acrylonitrile butadiene styrene (ABS), polycarbonate (PC), polyvinyl chloride (PVC) and high-impact polystyrene (HIPS). There are two obstacles in reprocessing these plastics wastes from electronics. First, there are a limited number of recyclers who can reprocess these plastics. Second, these plastics are mixed in the components and it requires a certain technology to sort them out. This technology is not yet available in Indonesia.

Based on the field survey, there are four main dealers in Jakarta Capital Region. These dealers are investors from Korea and China who trades e-wastes in bulk. They do not recycle any of the ewastes they collected. They export those e-wastes to buyers in China, Hongkong and Taiwan to be reprocessed. These main dealers provide warehouses to store the collected e-waste and act as distribution centres. These dealers are connected to each other and do not only collect wastes from Jakarta Capital Region but also from other regions in Indonesia, such as in Bandung [10]. For them, it is more profitable to reprocess these e-waste overseas than in Indonesia because the selling price of these e-waste in overseas is higher than in Indonesia. For example, Indonesia can reprocess waste motherboard at US$ 4/kg while China can pay a higher price. Summary of the supply chain network of e-waste is presented in Figure 4.

One of the reasons that people recycle e-waste in Indonesia is due to the high economic value of it. One thing that they after is the gold contained in many electronics parts such as PCBs. Consequently, PCB recycling is the new gold mine for the recyclers. There are various ways that the recyclers do to extract this precious metal. The methods that most recyclers use in Indonesia are chemical processing and heat processing. The method practiced in Indonesia to recover gold from the integrated circuit (IC) is as follows. First, the ICs are burned in open air to make it soft and brittle until it is fiery red. After that, it is pulverized by using mortar and pestle. The pulverized IC is then screened and further pulverized. After it has been pulverized evenly, it is rinsed by using water and detergent to extract the burnt plastics. The metals will then sink to the bottom and form sediment. The sediment is separated from the solution and Boric acid is then added to the sediment. The mixture of boric acid and the sediment is heated up to 3000 C. After it has been heated, lead is added to the mixture to separate gold from the mixture. The residue is then separated from the gold [12]. The whole process is done in a small space around 4 by 4 meters room with minimum ventilation. The most disturbing issue in this processing is the hazardous way that it was conducted. It was conducted in a cramped residential area with no treatment to its air and water waste. The operators also did not use any safety equipments. The recycling process is shown in Figure 5.

Figure 4: Supply chain network for e-waste in Indonesia. 5

TECHNOLOGICAL ASPECT

In addition to the supply chain network for e-waste in Indonesia, this field survey also investigated the technology applied by the sub dealers/recyclers to reprocess the e-waste collected. This survey focused on the technology used to reprocess the e-waste from endof-life (EOL) computers. As indicated in the previous section, the sub dealers received goods from the scavengers’ collection centres, service centres and brokers. These EOL computers are then disassembled and sorted according to its material. There are three streams of recycling process occurred in e-waste reprocessing, namely recycling of metals, recycling of plastics and recycling of

The method described above is not the only method that is currently applied in Indonesia. There are many other methods used to recover gold from electronics. However, one thing in common is that all of them are conducted by informal sectors, without using proper technology and proper handling of e-waste. 6

DISCUSSION AND CONCLUSION

The current condition of electronics waste management in Indonesia has been presented in this paper. Based on these findings, it can be concluded that there is a wide prospects of managing a better e-waste management in Indonesia. The prospect of managing e-waste in Indonesia can be summarized into the following: 

Currently there is no specific regulation on managing electronics waste in Indonesia. To support the proper management of e-waste, there is a need of formalizing all the chains in the network. With specific regulations on e-waste and a formal supply chain network, the process of monitoring the recycling activities is more controllable.

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End of Life Management - Selected Applications 8 [1]

REFERENCES BPS. (2007): Quantity and Value of Goods Produced by Item Badan Pusat Statistik, Jakarta

[2]

Indrietta, N. (2009, 01 May 2009): Konsumsi Barang Elektronik Indonesia Tertinggi se-Asia. Tempo Interaktif. Available: http://www.tempointeraktif.com/hg/bisnis/.../brk,20090501 -173880,id.html

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ANTARA News. (2006): Fakta - Limbah Elektronik (e-Waste) di Indonesia. Access date 20 October 2010 Available: http://www.antaranews.com/view/?i=1166588246&c=WBM &s=

[4]

Agustina, H. (2010): The Challenges of E-Waste/WEEE Management in Indonesia, in: Proceedings of Regional Workshop on E-Waste/WEEE Management, Osaka, Japan.

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Meidiana, C. and Gamse, T. (2010): Development of Waste Management Practices in Indonesia, in: European Journal of Scientific Research, Vol. 40, No. 2, pp. 199-210.

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Indonesia

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http://www.gerakanindonesiahijau.blogspot.com/ [7] Figure 5: Gold recovery process from e-waste.

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Community.

Green

(2009,

Community.

October

2010):

Available:

http://www.indoyouthcenter.org/en/about-us/green

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



Although there are some regulations on domestic and hazardous waste management, there is a lack of strict monitoring on the implementation of the regulation. As a result, there are some recycling activities conducted by the informal sector without considering the environmental impact of their actions. Based on the survey to 180 people in Jakarta Capital Region, more education and campaigns on the hazard of e-waste and methods to recycle e-waste are required; paying for recycling may not be applicable in Indonesia; and Trade-in programs to induce electronics waste recycling are encouraged Since the recycling industry supports the low economy society, the resolution to e-waste management should also supports the low economy society. A suggestion is to incorporate cooperative organization between scavengers, dealer and recyclers into e-waste management system.

ACKNOWLEDGMENTS

This research is supported by Universitas Pelita Harapan Research Centre (LPPM).

GreenlifeStyle. (2010): Komunitas GreenLifestyle. Access date August 2010. Available: http://greenlifestyle.or.id/

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Hanafi, J., Kara, S., and Kaebernick, H. (2005): Comparative assessment to identify the characteristics of collectors in reverse logistics, in: Proceedings of International Conference on Operations and Supply Chain Management,

Bali,

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Widyarsana, I. M. W., Winardy, D., Damanhuri, E., and Padmi, T. (2010): Identification of e-waste from computers and its recycled components in e-waste collection centres (in Bahasa Indonesia), in: Proceedings of Seminar Nasional Pascasarjana X, Surabaya, Indonesia.

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Williams, J. A. S., Qu, X., Rios, P., Wieland, J., and Grant, E. (2008):

Environmentally friendly alternatives to recycle e-waste are urgently required to replace hazardous methods. This includes thermoplastics recycling technologies and PCB recycling technologies.

However, these strategies will be a waste without a commitment from everyone in the country. Therefore, the future work of this study is to propose a method to communicate these messages effectively to the society, conduct a pilot project to formally set up an infrastructure for e-waste collection and management, and to find the environmentally friendly ways to recycle e-waste while utilizing the low economy society. 7

community.html [8]

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electronics recycling, in: International Journal of Computer Integrated Manufacturing, Vol. 21, No. 6, September 2008, pp. 730-743. [12]

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2010.

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Medical Electrical Equipment Good Refurbishment Practice at Siemens AG Healthcare 1

Martin Plumeyer , Markus Braun 1

1

Siemens AG Healthcare Refurbished Systems, Forchheim, Germany

Abstract Used medical equipment is a valuable asset that has to be preserved. If used medical equipment is re-used it needs to be processed in a dedicated way to avoid risks for users, patients and healthcare providers to make sure that the medical equipment is as safe and effective as when it was new. The concept “Good Refurbishment Practice” (GRP), defined and published by COCIR [1], [2] describes such a dedicated way to process used medical equipment. Knowing the quality requirements for refurbishment and regarding the lack of clear guidelines for refurbishment, the companies organized in COCIR developed an standard on GRP that defines the requirements for refurbishment. Keywords: Good Refurbishment Practice; Medical Device; Siemens AG

1

SIEMENS AG HEALTHCARE SECTOR

Siemens AG Healthcare brings together innovative imaging equipment, information technology, management consulting and services to help customers achieve tangible, sustainable clinical and financial outcomes.

safety and effectiveness for a certain period under the assumption of scheduled maintenance procedures. The effective lifetime of medical equipment can differ from the planned lifetime by the manufacturer. There are functional and economic reasons:

From imaging systems for diagnosis, to therapy equipment for treatment, to patient monitors to hearing instruments and beyond, Siemens AG Healthcare innovations contribute to the health and well being of people across the globe, while improving operational efficiencies and optimizing workflow in hospitals, clinics, home health agencies, and doctors’ offices.



The medical equipment is no longer safe and effective



The medical equipment meets no longer the applicable safety or performance standards



Replacement of medical equipment due to new technology available

The business unit Refurbished Systems has been founded in Forchheim, Germany 2001. Apart from environmental issues, managing quality the trade of safe and effective used medical equipment have been important drivers for the foundation of Refurbished Systems. The current product portfolio of Refurbished Systems comprises medical imaging equipment like x-ray, angiography, ultrasound, computer tomography, molecular imaging, magnetic resonance and radiation oncology. Siemens AG Healthcare Sectors’ business unit Refurbished Systems is a reliable partner for its customers and is part of the Healthcare Sectors’ strategy.

Figure 1 gives an overview about the correlation between planned lifetime, effective lifetime and refurbishment. Refurbishment enlarges the functional and economic life of medical equipment. At the end of its life cycle medical equipment needs to be processed for recycling as electrical and electronic waste.

Refurbished Systems has been growing constantly since its foundation. In the last years sales was about a three figured million Euro amount and still growing. 2

INITIAL SITUATION

Innovation cycles for medical equipment are much shorter than the economic life cycle of these investment goods. Rapid innovation cycles in medical technology often makes it necessary to replace the medical equipment a long time before it reaches its economic end of life. Early replacement of newest technology in medical equipment worldwide makes sense if the value of the replaced equipment is saved for reuse. Medical equipment is designed for a planned lifetime by the manufacturer. When putting the medical equipment into service for the first time the manufacturer provides

Figure 1: Context of planned and effective lifetime and refurbishment [1]. As a result of the replacement of medical equipment and in the context of a recycling economy a sustainable resource management is required. At the end of the day the replacement and the proper refurbishment of medical equipment provides value to a new user.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_86, © Springer-Verlag Berlin Heidelberg 2011

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In the last years manufacturers in the healthcare industry established refurbishment processes and delivered their equipment across the world. The list of users of refurbished systems is not only limited to small hospitals or countries with limited healthcare budget but to well-known leading medical institutes as well. The worldwide market for used medical equipment has been growing rapidly - the largest market for Siemens AG is the USA followed by the EU [3]. In most countries around the world the market for used medical equipment is mostly not regulated by the governments. Some countries established bans or restrictions on the import of used medical equipment to protect public health and safety [4]. Usually the ban on import does not distinguish between high-quality refurbished medical equipment and second hand equipment of undefined quality, with the effect that healthcare providers of more limited means can only have denied access to the safe and economical medical equipment they need. Not only improper refurbishment is a risk of used medical equipment. Compared to new medical equipment used medical equipment may bear additional injury risks for patients, users and the environment (e.g. contamination, missing required maintenance). Beyond these equipment and market related issues the initial situation is characterized by the environmental relevance of the reuse of used medical equipment due to the increased environmental awareness (e.g. climate change). Reuse of used medical equipment may be a way for organizations to contribute to a closed loop recycling management and to a sustainable society. 3

OBJECTIVES

significantly changing the finished medical equipment’s performance, safety specifications and/ or changing intended use as in its original registration. Other initiatives like StEP (Solving the E-Waste Problem) identified the lack of missing or mixed definitions of key terms regarding ReUse as well and proposed definitions [5]. The StEP initiative focuses on the re-use of electrical and electronic equipment in the context of waste hierarchy [5], [6]. The Siemens AG and COCIR approach defining a Good Refurbishment Practice process (see chapter 4) is not seen under waste hierarchy because the medical equipment used for refurbishment according to GRP will not extend the planned lifetime defined by the original manufacturer (see figure 1). Compared to other approaches discussing preservation of valuable assets by closed material loops [7] the planned lifetime of medical equipment will not be extended by companies following the GRP process. This issue could be a valuable field for further research to set up definitions and requirements extending the planned lifetime of a product by re-use. 4

SOLUTIONS

Refurbished medical equipment placed on the market and put into service shall meet the requirements for safe and effective use as specified by the manufacturer. In an organization performing refurbishment of medical equipment a dedicated process for refurbishment needs to be established. The established refurbishing process has to meet the requirements of the applicable standards for quality and risk management according to table 1. Quality management system (ISO 13485:2003)

Safety and effectiveness are the most important aspects for reuse of medical equipment. Not all sold used medical equipment fulfils these ethical and social criteria. To offer safe and effective used medical equipment and to eliminate risks for patients, users and for the environment it needs to be processed in a dedicated way.

Resource management (ISO 13485:2003, 6.1)

Refurbished medical equipment placed on the market and put into service shall meet the requirements for safe and effective use as specified by the manufacturer. There shall be no difference whether the medical equipment is new or refurbished.

Control of nonconforming product (ISO 13485:2003, 8.3)

Not all used medical equipment is suitable for refurbishment. There are different key factors whether medical equipment is suitable for refurbishment. 

The intended use defined by the manufacturer which means that e.g. single used devices should not be refurbished.



The medical equipment fulfils all applicable safety and performance standards.



The planned lifetime defined by the manufacturer i.e. medical equipment that reaches its useful end of life defined by the manufacturer should not be refurbished.



Existing service/ maintenance history for the medical equipment.



Existing service/ maintenance procedures for the medical equipment.

It is important to understand that refurbishment is different from maintenance, fully-refurbishment or remanufacturing. Refurbishment means actions taken, such as repair, rework, update of software/ hardware, and/ or replacement of worn parts against original parts, to restore used medical equipment into a condition of safety and effectiveness comparable to when it was new. All actions during refurbishment shall be performed consistent with product specifications and service procedures defined by the manufacturer for the type of the respective medical equipment without

Corrective and preventive action (ISO 13485:2003, 8.5)) Customer feedback (ISO 13485:2003, 7.2.3 c) Production and service provision (ISO 13485:2003, 7.5) Refurbishment labelling (ISO 13485:2003, 7.3.3) Post market surveillance process (ISO 13485:2003, 8.2.1 and 8.5.1) Process of instructions for validation and document control (ISO 13485:2003, 4.2.3) Supplier management process (ISO 13485:2003, 7.4) Risk management requirements (ISO 14971:2007) Process of evaluating market access requirements (e.g. language requirements for technical documents) Authentication of a Good Refurbishment Practice refurbishment medical equipment (i.e. authenticate any refurbished medical equipment that was processed according to the requirements of the GRP concept through means that allow inspection by authorities and verification by customers) Table 1: Processes to be established to meet the requirements for the organizational framework of Good Refurbishment Practice and related ISO documents [1], [2], [8], [9]. Good Refurbishment Practice - Process Good Refurbishment Practice makes sure that medical equipment processed in this way will meet all quality, performance and safety standards applicable when the medical equipment was put into service for the first time. Figure 2 describes the five step Good Refurbishment Practice.

End of Life Management - Selected Applications

499 

For any medical equipment refurbished according to the Good Refurbishment Practice performance and safety tests are to verify so that it meets the defined performance and safety specifications for its type.



After successful completion of all necessary refurbishment actions, the refurbisher has to release the medical equipment, shall declare compliance to GRP (GRP declaration) and must label the medical equipment accordingly. The product label must include name and place of the refurbisher and date of refurbishment.

Figure 2: Five steps of Good Refurbishment Practice [1]. Selection of medical equipment for refurbishment The selection of used medical equipment is based on: 

Intended use of the medical equipment



Planned lifetime by the manufacturer



Applicable standards, this includes a process to evaluate the market access requirements



Service/ maintenance history and existing procedures

Packing, shipment and installation of refurbished medical equipment 

The packing and shipment of the refurbished medical equipment should be processed in the same way as for new medical equipment to meet the applicable performance and safety standards. Refurbished medical equipment must be installed following the same installation procedures as new medical equipment.

Disassembly, packing and shipment of used medical equipment for refurbishment 

The used medical equipment needs to be checked before disassembly regarding unit identification





The used medical equipment needs to be disassembled in a way that it will not be damaged. It should be in the same condition as it was before disassembling (e.g. avoid additional risks due to disassembling).

Post-market services



If the medical equipment was used in a special environment (e.g. emergency room, laboratory) it might be necessary to decontaminate it before disassembly.



The medical equipment must be packed and shipped accordingly so it will not be damaged.



Appropriate actions shall be taken to avoid violation of privacy rules concerning patient data stored on the relevant medical equipment.



After the installation of refurbished medical equipment, the refurbisher shall provide services and support similar as for the relevant type of new medical equipment.

Refurbishment of used medical equipment according to Good Refurbishment Practice (GRP) produces safe and effective medical equipment.



A refurbishment plan has to be described and followed to define the equipment configuration (e.g. according to customer order) within the scope of the original product registration from the manufacturer when the equipment was put into service for the first time.



The used medical equipment must be systematically cleaned and disinfected before refurbishment due to its use in a medical environment.

Refurbishment contributes to a sustainable society. But only if the refurbishment is performed according to GRP and the refurbished medical equipment is as safe and effective as when new it is applicable for users, patients and healthcare providers and can contribute to a sustainable society. With regards to a recycling economy refurbishment safes resources and energy. Average refurbished xray medical imaging equipment needs to be processed with 73 % less energy compared to new medical equipment based on the life cycle phases material supply and parts of production phase. The life cycle assessment (using the cumulated energy demand method) of an typical x-ray system with a mass of approximately two tons covers the life cycle phases material supply, production, use and end of life [10].



Cosmetic refurbishment is done in conformance to the refurbishment plan (e.g. take care of biocompatibility).

5



Mechanical and electrical refurbishment and system configuration in accordance with the refurbishment plan e.g.

Refurbishment







Inspection, identification and replacement of worn parts or components.



Worn parts or components are to be repaired or replaced with original parts or original spare parts or original components.



Additional parts or components necessary to meet customer’s requirements must be original parts or original spare parts or original components or original accessories.



Provide original manufacturers user documentation in the required language or in a verified translation.

With the installation of safety updates (hardware/ software) all applicable safety updates which are released for this type of medical equipment are performed. With the installation of performance updates all applicable performance updates which are released for this type of medical equipment are performed.

CONCLUSIONS

Safety and effectiveness are the most important aspects to be considered with medical equipment and this is no different when reutilizing used medical equipment. To provide the safety and effectiveness, used equipment has to be processed in a dedicated way: In practice, there is a wide variety in the interpretation of refurbishment. Therefore, the companies organized in COCIR like Siemens AG defined a COCIR Standard on Good Refurbishment Practice [2]. The concept of GRP aims to support: 

Healthcare service providers to enable them to distinguish refurbished medical equipment processed according to the concept of GRP from second-hand equipment when making a purchase decision.



Patients to get easier access to safe and effective diagnostic procedures and therapies.



All stakeholders with information about Good Refurbishment Practice (GRP) for healthcare;



Industry to improve the safety and effectiveness of used medical equipment with a clearly defined quality process.

500

End of Life Management - Selected Applications



Preservation of created values of used medical equipment and contribution to a sustainable society.

6

REFERENCES

[1]

COCIR: Good Refurbishment Practice Guideline for Medical Electrical Equipment Version 2, http://www.cocir.org, October 2009.

[2]

COCIR: Industry Standard Medical Electrical Equipment: Good Refurbishment Practice (GRP), http://www.cocir.org, Version June 2009.

[3]

Braun, M.; Arglebe, C. (2007): Gebraucht und doch wie neu – Aufarbeitung von bildgebenden medizinischen Systemen, In: Medizinprodukte Journal 14. Jahrgang Heft 4.

[4]

U.S. Department of Commerce, International Trade Administration: Global Import Regulations for Pre-Owned (Used and Refurbished) Medical Devices, http://www.ita.doc.gov, Washington, D.C., May 2008.

[5]

Solving the E-Waste Problem (StEP): One Global Understanding of Re-Use – Common Definitions (White Paper), March 2009.

[6]

Directive 2008/98/EC of the European Parliament and of the Council of 19 November 2008 on waste and repealing certain Directives, 2008.

[7]

Hesselbach, J.; Herrmann, C.; Luger, T. (2007): Assessment of Recyclability, In: Seliger, G: Sustainability in Manufacturing – Recovery of Resources in Product and Material Cycles, pp. 90-103, Springer.

[8]

CEN the European Committee for Standardization: Medical devices - Quality management systems - Requirements for regulatory purposes, 2003.

[9]

CEN the European Committee for Standardization: Medical devices - Application of risk management to medical devices, 2009.

[10] Plumeyer, M.; Rosemann, B.; Bock, H.-C.; Nissen, N. F.; Bömmel, F. (2005): Life Cycle Management for Complex Medical Products: Using the Cumulated Energy Demand in Practice, In: Innovation by Life Cycle Management LCM 2005 International Conference, Vol. 1, pp. 571-575, Barcelona.

Sustainable Product Lifecycle Management: A Lifecycle based Conception of Monitoring a Sustainable Product Development 1

2

1

Martin Eigner , Michael von Hauff , Patrick D. Schäfer 1 2

Institute for Virtual Product Engineering (VPE), University of Kaiserslautern, Kaiserslautern, Germany

Institute of Economic Policy and Environmental Economics, University of Kaiserslautern, Kaiserslautern, Germany

Abstract Several solutions for the monitoring of sustainability of product development processes have been developed but the subject is still not solved satisfactorily. All of them focus on the three dimensions of sustainability as single pillars. In this paper a monitoring concept is being proposed, that is based on the Integrated Sustainability Triangle. The concept introduces a method for the quantification and monitoring of sustainability by using an integrated interpretation of the 21st century paradigm dimensions. In addition, the concept includes parameters on the whole product lifecycle. It contributes to extending the Product Lifecycle Management concept. Keywords: Product Lifecycle Management; Sustainable Development; Lifecycle Sustainability

1

INTRODUCTION

Sustainable Development, conceptually founded on the three dimensions economical, ecological and social sustainability is the main paradigm for the future improvement of humankind in the 21st century [1]. One of the guiding principles for product development is to develop products that are conforming to the sustainability paradigm. Already in the early phases of the product lifecycle, the engineer defines key properties of a product, implicitly defining the resulting lifecycle costs as well as environmental and social effects. The process of creating a sustainable product needs to be monitored and managed, whether a new product is to be designed or an existing one is to be improved [2]. To address the product development process, appropriate methods and tools are required. This paper considers Product Lifecycle Management (PLM) as one key concept for the establishment of sustainable product development processes. Within the scope of this paper, one ´glocalized` solution for more sustainability in manufacturing or rather in product development is presented. It contributes to extending the Product Lifecycle Management concept as it enables the monitoring of a product lifecycle, under aspects of sustainability, already in the early phases of the product development process. The paper is organized as follows: Section 2 introduces sustainability, facing two oppositional appreciations to quantify sustainability. In section 3 Lifecycle Thinking as one current principle in Sustainable Development is introduced. In section 4 the role of Product Lifecycle Management is investigated with regard to a sustainable manufacturing or particularly in a product development process and in section 5 the main elements and general framework of the proposed Sustainable Product Lifecycle Management conception is introduced. Section 6 gives a first approach of the new conception and the last sections conclude the paper. 2

OPERATIONALIZATION OF SUSTAINABILITY

The awareness of limited resources availability, environmental problems and pollution, the increasing demand for goods, energy and materials from the already developed and the new developing

countries, as well as the increase of costs of scarce resources, all are calling for a new paradigm of life, overcoming the obsolete consumerist model of modern societies [3]. ´Sustainable` became the buzzword these days but means even more than something that is able to be kept. The call to sustain our welfare is neither new, nor an invention by the economic system. The word sustainable is used very often and actually is a term which deeply is anchored in the human history. The term originates from the 18th century, describing the problems of the coeval silviculture and the use of wood in the Saxonian silver mines. Hans Carl von Carlowitz, superintendent of the mines, declares formerly that only as much wood ought to be removed from the forest as grows again. He even recognized the economic and social implications of this decision. In 1987 the term became renowned by its use in the report of the World Commission on Environment and Development. After this so called Brundtland report, the United Nations Conference of Environmental and Development, better known as the 1992 Conference of Rio de Janeiro, picked up the issue and laid down the most important task of the 21st century [1]: Sustainability considers the three dimensions Economy, Ecology and Society. However, in current literature, Sustainable Development is also defined as a development that meets the needs of present without compromising the ability of future generations to meet their own needs. The characterization stresses on the responsibility that humankind has toward future generations [4]. The economic system as well as science and politics are claimed to enable a sustainable change. Tremendous improvement of current technologies is required. In such a setting, a sustainable manufacturing will become one of the most relevant topics in future engineering. Within this rethinking, the product concept with all participating and involved processes has to be reshaped, especially taking into account the lifecycle view [5]. The standard model to quantify sustainability used by industry is the interpretation with three pillars. It is also called “The Triple Bottom Line Model” founded by Elkington [6]. Economic, environmental and social aspects are the three classes for the differentiation. In an

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_87, © Springer-Verlag Berlin Heidelberg 2011

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Information and Knowledge Management

assessment of sustainability, all of the dimensions have to be checked against each other. But this interpretation of sustainability appears to be problematic and it is animadverted in sciences. The engineering mechanics would call the system of three pillars overdetermined. Apparent from the drawing (a), one pillar could be removed without influencing the structural stability. The structure shows that a model with single, segregate and parallel pillars is not capable to show the complex interactions between the dimensions of the 21st century paradigm dimensions [7].

To organize the product development a consideration of the information flow is of central meaning. Already in the early lifecycle phases, the engineer defines key properties of the product. Here 80% of the resulting lifecycle costs as well as 80% of environmental effects are determined [2] [8]. Assuming a similar rate to social effects a sustainable improvement of a product design is appointed in this early step. Enterprises today have to deal with new arising challenges like globalization. As a result they have to collaborate more directly with others like their suppliers and their customers. Furthermore the rising demand for product innovation, product reliability and product liability have caused new challenges in the product- and processmanagement. The information about a product throughout its complete lifecycle, from the early phases up to recycling, often is distributed across a global network of data handling systems, supporting different lifecycle phases and different engineering disciplines [9]. Beside these product lifecycle phases which are introduced in the following Figure 2, separate disciplines which are involved in a product development processes as well as all parts of the supply chain have to be considered in a holistic lifecycle view.

(a) not long lasting

(b) long lasting

Figure 1: The three pillars of sustainability in a not long lasting conception on the left and in a long lasting conception on the right. In (b) the pillars are moved in space. Now each pillar is necessary for the structural stability of the construct. In an equilateral triangle, with the corners ecology, economy and society, all of the targetdimensions are on an equal footing in a discussion [7]. According to the guiding principle, a sustainable monitoring has to consider aspects of all dimensions in the same manner [3]. 3

LIFECYCLE THINKING

In 2002, ten years after the United Nations Conference in Rio de Janeiro, the United Nations World Summit on Sustainable Development stipulate Lifecycle Thinking as one self-contained principle in the sustainability paradigm [1]. This rethinking causes new requirements related to a sustainability assessment of a product. Accordingly a monitoring for a sustainable product development has to attend to the whole lifecycle, ranging from raw material extraction, across the production, the use to the recycling or waste disposal [5]. This ecological view of the product lifecycle refers to the material flow.

To manage the product development process and to handle the product complexity, the engineer has to administrate all kinds of data and information about the product. This would not be possible without using modern IT-tools. The ability of using IT-tools to support the integration and federation of distributed product data and their related processes, as well as the administration of a high number of product variants have already been recognized as driving factors for success, survival and competitiveness [9]. One benefit of such a computer aided product development might be that it facilitates the development of sustainable products by a better availability of relevant information. Even today a computer aided lifecycle assessment with an automatic calculation and monitoring of energy and material flows caused by the processes of the product and the linkage with conventional lifecycle databases could be customized. Therefore the product structure, available in a Product Data Management (PDM) system, has to be extended with lifecycle processes like transport-, production-, use- and end-of-life processes [10]. Product Data Management systems offer first answers to these problems. IT is one relevant part of a complex Product Lifecycle Management strategy, enterprises tend to use challenging today’s complex business [11].

Figure 2: Dimensions influencing enterprises in product development processes today.

Information and Knowledge Management 4

PRODUCT LIFECYCLE MANAGEMENT

Product Lifecycle Management is gratefully assisting the engineering [2]. The concept is concerned with both: the product and the engineering processes. The aim consists in supporting product data generating and manipulating processes in a multidisciplinary, federated and integrated way, as it is shown in Figure 2. ´Integrated` means that IT solutions have to handle the whole product lifecycle beginning with the first idea up to the recycling. The ´federated` component calls for an engineering collaboration in distributed enterprises as well as within suppliers, customers or even the whole supply chain. ´Multidisciplinary` refers to the cooperation of different disciplines or specialized divisions which are involved in the product development. Therefore Product Lifecycle Management is the administrative and managing backbone in product engineering [12]. Product Lifecycle Management represents a concept rather than a monolithic ITSystem. Its core components are Product Data Management to describe the product structure and Workflow Management which is respectively responsible to describe the product related information throughout the lifecycle and for modeling the deployment of enterprise business processes [11].

503 agement even supports more than only an assessment form the cradle to the grave. As the backbone of an Enterprise Architecture, the engineering concept is certainly a question of data visualization and transformation [2]. The following section introduces the Integrated Sustainability Triangle as a recent conception of monitoring a sustainable product development with aspects of a holistic product lifecycle. It contributes to expand the Product Lifecycle Management concept and opens up the discussion to a Sustainable Product Lifecycle Management. 5

THE INTEGRATED SUSTAINABILITY TRIANGLE

The Integrated Sustainability Triangle, originally introduced as a promising new possibility of quantification and monitoring the Sustainable Development of a national economy, is also an appropriate instrument for the systemization and evaluation of the performance of a company regarding sustainability management. It is above all a graphical representation of actions and achievements, based on the three dimensions of sustainability: economy, ecology and society [1] [7]. The segments of the Integrated Sustainability Triangle are shown in the following Figure 4.

Product Lifecycle Management, as the overall engineering concept is based on the idea of connecting knowledge and seeks to provide the right information at the right time in the right context. It offers a solution to systematize the various operational tasks in design and production so that processes are rationalized and optimized [13]. In addition to engineering, the support of activities in later phases of the product lifecycle is parts of the concept as well.

Figure 3: Product Lifecycle Management as a part of an Enterprise Architecture (adapted from [14]). The solution is supporting the engineer’s activities and moreover, it is one part of the so called enterprise architecture. This enterprise architecture interacts with other relevant concepts, such as Supply Chain Management (SCM), Customer Relationship Management (CSM) and Enterprise Resource Planning (ERP), shown in Figure 3. The Management of a product lifecycle starts with the definition of requirements. The requirements for a sustainable product traditionally focus from an economic perspective on costs, time and quality. The efficiency of energy and resources are in focus of an ecological perspective and standards and values are necessary for a social assessment. The objective of product planning and product development includes the creation of parameters that define the product and the process of its production. For example, the product structure specifies in detail the raw materials and preliminary products that are used in the manufacturing process. The process planning derives production plans from the bill of material. These plans describe the relationship in each production step while considering the capabilities of manufacturing facilities. Accordingly it follows the real production [13]. In all steps or early phases of the product`s lifecycle, the concept refers to the overall 21st century paradigm. Product Lifecycle Man-

Figure 4: Subdividing the fields of economical, ecological and social relevancies in the Integrated Sustainability Triangle (adapted from [1] first [7]). The assignment of corporate policy tasks with the Integrated Sustainability Triangle is a concept to systemize and evaluate the many indefinite and complex challenges of sustainability management. Among other things, the goals, indicators and stakeholders can be represented, structured and operationalized with the Integrated Sustainability Triangle. This will be demonstrated below using selected indicators. Indicators or measures are a triangle component for establishing the continuous improvement processes for Corporate Social Responsibility performance. Indicators aid in the development, implementation, evaluation, and the improvement of learning and tracking processes for sustainability management, as sustainability is not a given thing, rather it must be developed in a cooperative process with the stakeholder. After some years of intensive discussions at an international level, several indicator catalogs are now available, even for the development of a sustainable product [15]. Many of these catalogs are arranged in the three dimensions of Sustainable Development as well as being differentiated according to both mandatory and optional, perhaps company specific indicators. Hence, there is no generally valid set of indicators. However, a foundation of important indicators does exist that enjoys wide acceptance today [1] [7].

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Information and Knowledge Management

The illustrations of the Integrated Sustainability Triangle are limited to the major relationship. The individual fields of action in the three dimensions, ecology, economy and society are systematically arranged in the Integrated Sustainability Triangle by subdividing the triangle into the fields shown in Figure 4. Then, the corresponding indicators are derived for the individual fields of action, as discussed below. In addition to the mapping and allocation of indicators which refer to a qualitative assessment, an evaluation of the sustainability performance can be facilitated by a weighted aggregation of the single indicators. This subsequent weighting of indicators defines the asserted contribution of a respective field. In general a field includes several indicators. Each indicator may contribute to a different extent to the outcome for that field but together all used indicators illustrate 100% of the subject field. This rule applies for each field within the Integrated Sustainability Triangle. By setting additional indicators there is a possibility to adjust the calculation procedure to a desired context. The option to set divergent weighting factors allows considering that individual fields or sustainability dimensions can have a stronger or weaker influence on the total outcome. The value indicators are in effect key to the interpretation of a status and an initiation of required measures.

Figure 6: The representative and absolute coordinates of the Integrated Sustainability Triangle (adapted from [1] first [7]). The Integrated Sustainability Triangle monitors the sustainability performance and supports communication via graphic elements. The value indicators are assigned to points indicating the degree of goal achievement. These points, without any aggregation in every field, may range from zero to some maximum, or perhaps positive and negative monitoring assessment points can be used.

~ y

z

y

y*

~ x

z*

x* x k

Figure 5: The Interaction of economical, ecological and social relevancies in the Integrated Sustainability Triangle (adapted from [1] first [7]). As shown the Integrated Sustainability Triangle is a crossdisciplinary solution, originating from the engineering and material science. It is based on the operations of a triangle founded by Josiah Willard Gibbs used to describe mixing ratio of ternary mixtures in the chemistry and physics. Altogether the mixed components merge 100% of the whole. The most varied properties are continuously entered into that triangle. The example in Figure 5 presents an alloy of XYZ which consists 20% x, 50% y and 30% z. The restrictions for the mixing ratio are proposed in the following scheme:

x  y  z  100 %

mit

x, y , z  0%,100 % 

(1)

In Figure 6 the systematic, forwarded to the three dimensions economic, ecologic and social, is reflected. A sustainable product has to unify aspects of all dimensions in an equal allowance. The representative and absolute coordinates such a product is located with are: x=33.3%, y=33.3% and z=33.3%.

Figure 7: Showcase of the current performance to an analyzed product (adapted from [1] first [7]). In a first aggregation the partial results will be represented in relation to the dimensions economical, ecological and social sustainability. The performance rating is determined by combining the summed assessments for the performance of the nearby fields. The field located directly at a corner strongly influences the overall performance of the respective dimension, while the more distant fields only have a weak impact. In a last aggregation, as it is given in Figure 7, the system loses the most complexity. The overall performance is shown by on circle inside the triangle. The circle represents the main focus and the total of the individual assessments. The position of the circle is indicating whether the performance is uniformly distributed across all dimensions and the size shows the content of sustainability.

Information and Knowledge Management 6

FIRST APPROACH AND CURRENT IMPACT

A Sustainable Product Lifecycle Management is the central backbone of holistic information processing. Regarding the aimed extension, the concept is realized by the integrated consideration of an advanced product model and process model as it is shown in Figure 8. The precision of the outlined model consists in a consistent enrichment of the conception by scenarios and use cases. It is also linked to several environmental and resource databases supporting the compliance of the product. The extension of the product model encloses material values of as well as the used amount of all resources. The evaluation can be drawn to an energy balance. Regarding the process model, the conception becomes a computer aided lifecycle assessment as well. Indicators used in this model to describe the energy efficiency and resource productivity correlate to the catalogs VDI 4070 [16] and GRI 2006 [17]. But as it is shown, also social aspects are relevant to describe the focused energy efficiency and resource productivity. The monitoring of the used hazardous materials is only one part of the complex compliance management. In this conception there is also a focus on technologies which contribute to preserve resources by reducing the overall energy demand as well as negative environmental effects. The usage of aluminum or carbon fiber instead of steel causes new challenges. The production of these materials is more energy intensive so that the energy demand of the product lifecycle must be taken into consideration and not just the later lifecycle phases. Another example the introduced conception takes into account is the usage of recyclates. In comparison to the production of materials like aluminum, nickel, polypropylene, etc. the energy demand for producing these materials from recyclates is less more energy intensive [18]. The Sustainable Product Lifecycle Management is gathering and representing all product lifecycle information to support and optimize a sustainable Product Development which will play an increasingly important role in the future. Lessons learned

505 6.1

A paradigm change occured

According to Sendler Product Lifecycle Management implicates a fundamental change in business processes, maybe the most significant change in the last hundred years. From his point of view, the change will be less a question of new methods, tools and practices, but even more a question of changing human behavior [19]. Recently the macroeconomics attributes the sustainable paradigm to a similar change. The question has been posed, whether the economic system is already changing from a social market economy to a sustainable market economy [1]. This paper announces the Sustainable Product Lifecycle Management to link discrete theoretical scientific models with applied use cases in industry. The introduced Sustainable Product Lifecycle Triangle shows a first solution statement to solve the pressing problem of time. The lifecycle based conception of monitoring a sustainable product development helps to identify critical components and optimize the product in the early phases. To achieve this, the engineering is supported by computer aided approaches, methods and tools ´crossing` the three dimensions for achieving sustainability oriented results. Within this view, Sustainable Product Lifecycle Management is known as an opportunity applying scientific knowledge to design and implementing products and processes that take into account the three dimensions of economical, ecological and social sustainability. In a line of arguments, engineering and technological progress, therefore innovation, are key drivers of human development. Engineering is one key driver of technology based human development. It is leveraging on a large collaboration from a number of individual disciplines such as mechanical engineering, electrical engineering and information technology. To derive a sustainable engineering from such an industrial ecology view, Sustainable Product Lifecycle Management could be defined as one concept to achieve the common purpose.

Figure 8: Model for gathering and representation of Product Lifecycle information to support a sustainable Product Development.

506 6.2

Information and Knowledge Management A holistic approach is to be claimed

Any ecological, economic or social monitoring method for products has to take into account the full lifecycle or in other words a systems approach has to be taken. Kloepffer argues that only in this way, trade-offs could be recognized and avoided. From his point of view Lifecycle Thinking is the prerequisite of any sustainability assessment. For example, it does not make sense at all to improve one part of a product in one country, in one step of the lifecycle or in one environmental, cost or social compartment, if this improvement has negative consequences for other parts which may overweigh the advantage achieved. Additionally the problems shall not be shifted into the future. The argumentation refers to the lifecycle initiative launched by the United Nations Environment program (UNEP) [20]. But the systematic introduced by the UNEP still discusses sustainability on the triple bottom line interpretation. To meet the demands of a sustainable product development, an integrative conception is necessary. The Sustainable Product Lifecycle Management solution incorporates methods and strategies to reach this aim. 7

SUMMARY

As result, a paradigm change occurred but a holistic approach is to be claimed. The Integrated Sustainability Triangle provides new possibilities as discussed. It enables the justification and also the quantification of sustainability. In this process, the aggregation of individual economic, ecologic and social contributions to a sustainable development can create an overall impetus to the entire industrial sector. Being Sustainable Product Lifecycle Management, an IT infrastructure is able to support product data, information and knowledge sharing. This will be the foundation of the business model needed to comply with sustainability requirements. In expression to extend Product Lifecycle Management for Sustainability, there is an urgent need for a holistic view. The expanded Product Lifecycle Management represents an important approach for achieving a more sustainable paradigm of work and life and even a more sustainable product development. 8

Elkington, J. (1999): Cannibals with forks - the triple bottom line of 21st century business, 2. ed., Capstone Publishing, Oxford.

[7]

Kleine, A. (2009): Operationalisierung einer Nachhaltigkeitsstrategie - Ökologie, Ökonomie und Soziales integrieren, 1. Ed., Gabler, Wiesbaden.

[8]

Posch, A.; Perl, E. (2007): Regionale Verwertungsnetze und industrielle Symbiose, in: Isenmann, R.; von Hauff, M. (ed.): Industrial Ecology - Mit Ökologie zukunftsorientiert wirtschaften, 1. Ed., Elsevier, München, pp. 265-276.

[9]

Mogo Nem, F.; Weidlich, R.; Eigner, M. (2008): Engineering Networks: A concept for the coequal modeling of data and processes in the product engineering, in: Proceedings of the 10th International Design Conference - Design 2008, Dubrovnik, Croatia, pp. 849-856.

[10]

Feikert, S. (2007): Ökologisches Product Lifecycle Management - Ein Integrationskonzept der ökologischen Produktbilanzierung in betrieblichen ERP-Systeme, 1. Ed., Shaker, Aachen.

[11]

Eigner, M.; Gerhardt, F.; Langlotz, M. and Mogo Nem, F. (2009): Integrated visualization for supporting decision making in engineering processes, based on JT, in: Proceedings of the 6th International Conference on Product Lifecycle Management, Bath, UK, paper ID: 118.

[12]

Eigner, M.; Langlotz, M.; Reinhardt, P. (2009): Case Study Based Education for Product Lifecycle Management, in: Proceedings of the 11th International Conference on Engineering and Product Design Education, Brighton, UK, Paper ID: 09/183.

[13] Moeller, A.; Rolf, A. (2001): Eco Product Lifecycle Management, in: Proceedings of the 2nd International Symposium on Environmentally Conscious Design and Inverse Manufacturing, Tokyo, Japan, pp. 739-744. [14]

Bitzer, M. (2008): Entwicklung einer Methode zur prozessorientierten Planung und Optimierung von Product Lifecycle Management Lösungen - am Beispiel der Automobilindustrie, Technische Universität Kaiserslautern, Schriftenreihe VPE, vol. 6, Kaiserslautern.

[15]

von Hauff, M.; Wilderer, P. (2008): Industrial Ecology: engineered representation of sustainability, in: Sustainability Science, Springer, vol. 3, no. 1, pp. 103-115.

[16]

VDI 4070 (2006): Guidance notes for sustainable management, part 1, Beuth, Berlin.

[17]

GRI (2006): Sustainability Reporting Guidelines, URL: http://www.globalreporting.org/NR/rdonlyres/17D902C9E3D1-422A-8D61-BE210D7D823E/0/G3_Leitfaden.pdf.

[18]

Demel, H.: Comparison of the well-to-wheel energy efficiency of different vehicle concepts in: Proceedings of the 30th International Wiener Motorensymposium, Wien.

[19]

Sendler, U. (2009): Das PLM Kompendium – Referenzbuch des Produkt Lebenszyklus Managements, 1. Ed., Springer Berlin, Heidelberg.

[20]

Kloepffer, W. (2008): Life Cycle Sustainability of Products, in: International Journal of Life Cycle Assessment, Section Life Cycle Management, 13 (2008) 2, pp. 89-95.

ACKNOWLEDGMENTS

The Integrated Sustainability Triangle has been developed originally within a research project for the German state Rhineland-Palatinate (RLP) to purpose the advancement of the Agenda 21 RLP. The authors would like to thank Alexandro Kleine, who co-developed this new structure. 9

[6]

REFERENCES

[1]

von Hauff, M.; Kleine, A. (2009): Nachhaltige Entwicklung – Grundlagen und Umsetzung, 1. Ed., Oldenbourg, München.

[2]

Eigner, M.; Stelzer, R. (2009): Product Lifecycle Management - Ein Leitfaden für Product Development und Life Cycle Management, 2. Ed., Springer, Berlin, Heidelberg.

[3]

Blank, J. (2001): Sustainable Development, in: Schulz, W.; Burschel, C.; Weigert, M. (ed.): Lexikon Nachhaltiges Wirtschaften, Oldenbourg, München, Wien, pp. 374-385.

[4]

Hauff, V. (ed.) (1987): Unsere gemeinsame Zukunft - der Brundtland Bericht der Weltkommission für Umwelt und Entwicklung, Eggenkamp, Greven.

[5]

Ciceri, N. Duque; Garetti, M.; Terzi, S. (2009): Product Lifecycle Management Approach for Sustainability, in: Proceedings of the 19th CIRP Design Conference, Cranfield University, pp. 147-154.

Semantic Web Based Dynamic Energy Analysis and Forecasts in Manufacturing Engineering 1

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1

Ken Wenzel , Jörg Riegel , Andreas Schlegel , Matthias Putz 1

Fraunhofer Institute for Machine Tools and Forming Technology IWU, Chemnitz, Germany

Abstract This paper proposes an approach for supporting the analysis of collected energy consumption data in combination with structured system models to reveal correlations between energy usage and related properties of products, operations and equipment. The described method serves as a starting point for the creation of tailored simulation models for energy consumption forecasts that can be used in the planning phase of manufacturing systems. Therefore several energy-oriented simulation methods are introduced and discussed regarding their suitability for different use cases in manufacturing engineering. Keywords: Energy Efficiency; Linked Data; Simulation

1

INTRODUCTION

Resource efficiency is gaining importance for manufacturers. Rising energy costs and an increasing request for green products demands producers not only to provide energy-saving products, but also to establish energy efficient production processes. This also holds for the automotive industry where more than 20 percent of a car's life-cycle energy usage may arise during its manufacturing process. Hence it is essential to analyze all aspects of energy usage comprehensively for improvement of energy efficiency in manufacturing. Since today's widely used planning tools are unable to predict and optimize energy consumption of planned processes and systems, methods and tools are required that allow for integrated energy forecasts throughout industrial and manufacturing planning. As a first step towards realizing this vision we propose a method that leverages Semantic Web technologies in order to support analyzes of energy consumption data by linking measured values to descriptions of products, operations and equipment (Section 3). The method can be used to select and filter measurement data for the creation and verification of generalized simulation models that allow predicting energy consumption of different planning alternatives (Section 4). Our approach is developed and applied within a research project that aims at improving the overall energy efficiency of manufacturing systems for body-in-white parts. 2

STATE OF THE ART

Currently, manufacturing data analysis is mainly applied for resolution of bottlenecks or quality problems. Hence most computer-based analysis systems aim at calculation of performance indicators from process and product data or prediction of process properties for preventive maintenance tasks. More complex evaluations of manufacturing data regarding varying objectives is usually performed with the help of data mining methods and software tools. Data mining requires preprocessing (aggregation, reduction) and manual selection of relevant data sets. The latter

becomes increasingly complex with higher amount and diversity of available data. While other domains like biology [1] or meteorology [2] try to find computer-aided solutions for exploration and selection tasks, similar approaches in the field of manufacturing engineering are unknown. Regarding production planning processes in the automotive sector, advanced tools of the digital factory are used to design work cells and assembly lines. These software systems are mainly evaluating planning solutions regarding time and space requirements. Since the behavior of media consumers often cannot be modeled sufficiently such tools lack support for energy-related decisions. Furthermore, there are no solutions for using digital planning models to support manufacturing data analysis during the operating stage of planned systems, e.g. by linking collected data to related products, processes and equipment. 3 3.1

ANALYSIS AND MODELING PRODUCTION SYSTEMS

OF

BODY-IN-WHITE

System Analysis and On-Site Data Acquisition

The reference batch production system is a highly automated assembly line for sheet metal parts which consists of sequential work groups. Almost all process steps are realized by industrial robots. Workers are essentially utilized for placement and removal of parts as well as for quality assurance. In the current state of technology, joining of sheet metal parts is realized by welding or brazing processes. Within body-in-white applications a welding process is mostly divided into two sequential steps. In a first step the parts are fixed by spot welds. Secondly, the whole weld seams are created. Brazing is used in critical areas for corrosion protection. Both technologies require high process temperatures as well as additional operating media. Beside these core processes, compressed air is of high importance for part handling and clamping. For this reason, the following media-related values have to be monitored during a defined period of operation:

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_88, © Springer-Verlag Berlin Heidelberg 2011

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Electricity: current, voltage, frequency, effective and apparent power, effective power factor (cos )

these is the MAnufacturing’s Semantics ONtology (MASON) [6] as proposal for an upper manufacturing ontology.

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Coolant water: temperatures (inflow, return flow), volume flow



Compressed air: pressure, volume flow



Inert gas: pressure, volume flow

Our approach uses OWL to define lightweight models of the production systems and the collected data. Hence our ontologies do only specify a small core vocabulary required for data analysis tasks that can be combined with existing manufacturing ontologies like MASON to increase the expressiveness.

Additionally, temperatures of welding guns and welding fumes are captured. Therefore, measuring devices were installed by automation specialists who are involved in the research project. As a result, two main data collections are obtained for each media consumer (Figure 1). The first collection contains all media consumption data, the second collection aggregates all operating states of the consumers monitored by their primary controller. Both collections are synchronized by time stamps for each measured value. Media Supply Media Flow

Monitoring Point Media Consumer

Media Consumption Collection

Material Flow ...

...

Joining Process Information Flow

Operating States Collection

Programmable Logic Controller

Figure 1: On-site acquisition of media and process data. In this way, we aim at deriving correlations between resource states and media consumption. In order to assist the data analysis, our approach uses models for the description of production systems. These models represent structural aspects of the considered system along with behavioral descriptions for the corresponding production processes. These models are intended for guiding and simplifying data exploration tasks like retrieval of media consumption data related to the creation of weld seams or other types of assembly features. 3.2

We’ve identified three types of elements required to describe the highly automated assembly processes within our reference production system including body-in-white products, operations and equipment. These concepts are defined in separate ontologies which are related to each other like depicted by Figure 2. The following models are utilized to create a detailed description of our reference system. Equipment model The equipment model reflects the hierarchical and topological structure of all relevant body-in-white resources within the reference system. It contains media equipment, e.g. power supplies and distribution equipment, hardware used for process data collection, e.g. monitoring points, as well as all connected media consumers. We distinguish between core processing devices, e.g. robots and welding guns as well as secondary equipment used for tool maintenance, labeling, insertion control, pretreatment and post processing of parts. Furthermore, different cylinders, feeders as well as disposal and safety devices are represented. Product Model This model focuses closure parts, particularly a rear door produced by the reference production system. The hierarchical structure of sub-assemblies and individual parts are modeled as well as important attributes like materials, weights, sheet thicknesses, potential clamping points and joints. Operations Model All steps performed during production including processing, transportation, handling and storage are contained in that model. Beside core processes, we consider security-related operations as well as jig-related operations. Operations are linked to the utilized equipment and modified parts (Figure 1). utilizes

Operation

Equipment

modifies

Product

Ontology-based system models

Advanced modeling techniques are required to cope with the diversity of information about production systems that needs to be integrated for the purpose of guided data analysis. The Semantic Web as an extension to the World Wide Web enables information sharing across application boundaries and data repositories. Its building blocks are the Resource Description Framework (RDF) [3] enabling unified data representation supplemented by a stack of languages for knowledge modeling using ontologies. One of these is the Web Ontology Language (OWL) [4] that was widely adopted for ontology definitions in a variety of domains. For example, two extensive research projects COGents and IMPROVE [5] showed that OWL-based ontologies are well-suited to integrate knowledge from different domains into a unified system model. Although these projects considered the engineering of chemical process systems similar concepts can be applied for modeling manufacturing systems. There are also some efforts towards the creation of standardized manufacturing core ontologies, one of

Figure 2: Relationships between models. 3.3

Semantic Data Representation

Large scale data analysis requires deep insight into the systems and processes that produced the data under consideration. Especially in the case of production systems, an analyst has to cope with complex structures of products, operations and equipment. Hence, the analysis of collected production data is often time-consuming and error-prone. We try to solve this problem by introducing an approach for guided data exploration of production data. Our method is based on the idea of linking sensor descriptions and collected sensor data to models of products, operations and equipment. Recent research concentrates on publishing and analyzing sensor data using Semantic Web technologies. There are ongoing efforts to describe the topology of sensor networks with ontologies [7] along with complementary investigations for linking collected sensor data with sensor network models to simplify retrieval and analysis tasks [2].

Information and Knowledge Management

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biw:RobotSystem robot5

biw:RearDoorPart innerPart biw:utilizes

biw:canUse

biw:contains ssn:FeatureOfInterest biw:SpotWeldingOperation operation2

biw:utilizes

biw:SpotWeldingGun gun2

biw:modifies

biw:SpotWeld weld

ssn:hasProperty

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time:Instant 2010-10-21 16:08:19.163

time:DateTimeInterval 10 ms

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ucum:UnitOf-si ucum:degreeCelsius

xsd:float 243

lce:hasQuantityUnitOfMeasurement

lce:hasQuantityValue

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ssn:observes ssn:SensingDevice lce:Thermometer thermometer1

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muo:PhysicalQuality ucum:temperature

ssn:madeObservation

ssn:Observation lce:TemperatureObservation observation23

ssn:observationResult ssn:isProducedBy ssn:SensorOutput lce:TemperatureSensorOutput output1

ssn:hasValue

ssn:ObservationValue lce:QuantityObservationValue value1

Figure 3: Collected sensor data linked to operation, equipment and product. The W3C Semantic Sensor Networks Incubator Group (SSN-XG) aims to build a unified ontology for sensors and collected sensor data. The resulting Semantic Sensor Network (SSN) Ontology provides means to describe sensors, observations and related concepts. It is targeted at a wide range of applications and hence has a very general nature that is achieved by omitting descriptions for domain concepts like time, locations and others. These can be added for different use cases by utilizing OWL’s import facility. Figure 3 illustrates an example that shows how sensor data, in this case temperature data, expressed in the SSN ontology can be linked to the data-producing process. The SSN ontology speaks about SensingDevices that make Observations regarding Properties of a FeatureOfInterest. In our example the sensing device is a thermometer that observes the temperature of a spot welding operation. The sampling time of these temperature observations is fixed to 10ms, meaning that the ObservationValue of the associated SensorOuput is regarded valid for this duration. The connection between collected sensor data and the production system model is established by using manufacturing operations as features of interest for observations. The example in Figure 3 illustrates this by connecting the temperature observation to a concrete instance of SpotWeldingOperation. This allows for further traversal of associated model elements like modified parts and utilized equipment. Since the SSN ontology does not define concepts for representing time and other physical quantities it has to be supplemented by other ontologies for this purpose. We’ve decided to use the widely accepted OWL-Time ontology [8] to represent temporal concepts like observation result time and sampling time. Physical qualities and associated units are represented using the Measurement Units Ontology (MUO). MUO provides a formal framework for defining base units and their derived forms. There exists a set of basic instances for MUO that was extracted from UCUM, the Unified Code for Units of Measure. This UCUM ontology

was reused to express physical units like °C (ucum:degreeCelsius) in an unambiguous way. 3.4

Guided Data Exploration

The semantic linking of sensor data with model elements supports the analyst in exploring and examining the collected data to identify relevant energy-usage patterns. The starting point is a graphical representation of the production system that reflects its hierarchical and topological structure along with attached sensing devices. The general idea is to use an equipment object as source for observations regarding properties of its state or properties of its associated manufacturing operations. Figure 4 exemplifies the visualization of observed property values for a robot system. The view can be generated by leveraging the semantics of the ontology-based production system model. The integrated retrieval of model and measurement data is realized by using SPARQL [9] (SPARQL Protocol and RDF Query Language) which is part of the W3C Semantic Web stack and provides tailored querying facilities to access RDF-based data. The following SPARQL query retrieves manufacturing operations or operating states along with their observed properties for a given equipment object. PREFIX biw: PREFIX ssn: SELECT DISTINCT ?foi ?property WHERE { # feature of interest is either an operation or a # system state {?foi biw:utilizes ?equipment} UNION {?foi biw:possibleStateOf ?equipment} ?foi ssn:hasProperty ?property . ?property a ssn:Property . # there is at least one observation for this property ?observation a ssn:Observation . ?observation ssn:featureOfInterest ?foi . ?observation ssn:observedProperty ?property }

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Based on the results of this query it is possible to construct an analysis view composed of diagrams for each observed property as depicted by Figure 4. As can be seen, the observed properties in this example are temperature and power consumption. Complementary to the diagrams for property values, a timeline is available to visualize the active intervals of manufacturing operations or system states. Additional properties of these objects (like actual system state or modified parts) can selectively be retrieved and visualized for a deeper understanding of the observation results.

SIMULATION-BASED FORECASTS

MEDIA/ENERGY

(CONSUMPTION)

power consumption

In these cases, simulation tools may be applied. A rough distinction is drawn between discrete and continuous simulation. In contrast to continuous simulation, the value of a state variable is not recalculated and can not be accessed at any time within discrete simulation [10]. On the other hand, material flow-related aspects can be modeled more easily for piece goods.

temperature ssn:FeatureOfInterest

Idle

lce:systemState

Idle

Welding

Handling Busy

weld

innerPart

Figure 4: Visualization of observed property values. Exemplary, the actual values for each property can be queried by the following SPARQL query: PREFIX dul: PREFIX time: PREFIX ssn: PREFIX xsd: SELECT ?value ?rtime WHERE { ?o a ssn:Observation . ?o ssn:observedProperty ?property . ?o ssn:featureOfInterest ?foi . ?o ssn:observationResultTime [ time:inXSDDateTime ?rtime ]. ?o ssn:observationResult [ ssn:hasValue [dul:hasRegionDataValue ?value] ]. FILTER (?rtime > ?startTime && ?rtime < ?endTime) } This query takes a given feature of interest (foi), a property of this feature of interest (property) and the bounds of a time interval (startTime, endTime) as input. The results are pairs of scalar property values and corresponding event times determined by observations within the given time interval. We term the described method guided data exploration since it enables combination of knowledge about the structure and behavior of the production system with knowledge about process observations helping the analyst to navigate and interpret large sets of collected process data. 3.5

4

Obviously, on-site measurements of energy consumption as foundation for energy usage predictions are only applicable for constant conditions, e.g. fixed system configurations. Such measurements cause high investment costs and temporary shutdowns of production for installations. For virtually planned systems they can not be used at all.

ssn:observedProperty

biw:modifies

Our proposed approach to data exploration can support the iterative creation, verification and modification of energy-oriented simulation models for manufacturing processes. The described linking of collected process data with products, operations and equipment aids the analyst to retrieve the measured energy consumption data required for comparison with simulation results.

Verification of energy-oriented simulation models

Section 4 introduces a method for energy consumption forecasts using simulation. The verification of constructed simulation models requires sample data which was produced by real world systems.

Discrete event simulations are well-established within production planning. As energy consumption can not be a single objective for optimization, other important facts [11], e.g. cycle time, utilization and output ratio of the system have to be evaluated in advance using such systems. Continuous simulations are mainly used for process modeling, e.g. process engineering or for product development, e.g. design and engineering of mechatronic systems. In order to predict energy consumption for a system of resources using simulation, we distinguish different realization options: 1. Complete representation of the production system including all resources within continuous simulation (cp. [12]). 2. Online coupling of discrete simulation of the production system and continuous simulation of resources (cp. [13, 14]). 3. Successive discrete and continuous runs tracing events from log file. In the following part, we demonstrate two approaches for energy consumption forecasts within common continuous and discrete simulation systems. 4.1

Physical Modeling of Energy Consuming Resources

This approach requires knowledge about the structure and the physical behavior of the resource. For example, our Modelica model [15] of a simplified robot consists of several sub-models (Figure 5). Structural model This model of the robot structure contains a path planning component generating required kinematic movement angles, a controls bus, body shapes, a world coordinate system, revolute joints and an axis model. Axis model This sub model of a driven axis comprises a proportional-integral axis controller, an axis control bus, a gearbox, different sensors, a signal generator and a drive model. Drive model The structure of the motor is made up of different sensors, electrical and electronical components as well as a rotational component with inertia and an electromotoric force by means of an electric/mechanic transformer. Furthermore, the electromotoric force block is linked with a power sensor and an integrator block in order to add up its energy consumption during a simulation run.

Information and Knowledge Management

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We used a fictional operation as input for the path planning block. For a vertical circular rotation of a defined mass by 180 degrees, we obtained an energy profile as shown in Figure 5. The negative integration values in the upper region are caused by recovery of braking energy. Structural Model

The characteristic value function of each state variable is discretized [16] to enable the integration into a discrete-event simulation model. Within the discrete-event simulation individual value functions can then be represented by combining simple timevalue lookup tables for each state variable with an event generator that triggers the required value changes at the right time. State changes of resources are modeled by activating corresponding representative flow objects for each state (Figure 6). In that way, the characteristic behavior of state variables, e.g. effective power, for individual resource states can be simulated using discrete-event simulation systems.

Operation

The following simplifications were applied for the example shown in Figure 7: Axis Sub-Model



Values of state variables solely depend on the elapsed time within the corresponding state.



The elapsed time of a state is not reset if it is interrupted by an exceptional state, e.g. when processing is interrupted by maintenance. This is based on the assumption that the original activity can be continued and does not require restarting.



The states Waiting/Empty, Blocking, Pausing and Non-planned are merged into a state called Other.

Drive Sub-Model Energy Consumption Forecast

w

t

Value

p

Figure 5: Hierarchical simulation model of a simplified robot. 4.2

State-based Simulation Models of Energy Consuming Resources

s

This approach implements time-dependent state variables, e.g. effective power, using an object-oriented discrete-event simulation system. Each resource is regarded as a finite state machine that contains several distinct states. Considering simple material flow resources, these distinct states may consist of Working, Set-up, Failure, Pausing, Blocking, Waiting resp. Empty and Non-planned. An individual state of a resource is modeled by using a representative material flow object that is characterized by one or more state variables. Each state variable is described by a predetermined timedependent value function that can, for example, be computed by continuous simulation runs. Assembly Line

State Representative

m o

Time Processing (p)

Maintenance (m)

Set-up (s)

Other (o)

Figure 7: Simulated development of state value within different states of the main resource. For illustration purposes, the resource has a low availability ratio requiring some maintenance states while processing. It is also part of an unbalanced line where blocking and waiting states can occur. The described method enables modeling complex material flow systems while also considering characteristics of state variables like power consumption. A resource’s energy consumption w within can for example be approximated by Equation 1 where n is the number of events that triggered changes of the effective power pi. The value of pi is considered constant within the interval ti. Better approximations are possible by using some kind of interpolation.

State 1

State 2

n

... State n

Figure 6: Resource network for modeling state variables.

w   pi  ti

(1)

i 1

This method enables the determination of energy consumptionrelated characteristics for evaluating different planning solutions. Therefore, it provides the basis for further optimizations.

512 5

Information and Knowledge Management OUTLOOK: INTEGRATION INTO PROCESS PLANNING (CAPP)

An integration of energy-related objectives into body-in-white planning processes is necessary to obtain energy efficient solutions. In a first step, energy-related objectives must be developed, e.g. reduction of lines’ energy consumption by 25% while retaining equal throughput and product quality. As it is hard to numerically qualify such targets in the beginning, a maximum decrease of energy consumption in conformance with main planning objectives like time, quality and costs would be a more generic approach. Since energy suppliers are usually aggregating consumed power over a certain period of time for accounting, consumption rhythm and load peaks may form additional important objectives. Secondly, different solutions are developed leveraging common planning and engineering tools. For body-in-white processes, collision tests and accessibilities relating to robots, tools, jigs, parts and other equipment are of great importance. Currently, all processes are optimized to duration and space requirements. This influences the formation of work cells, as cycle times determined from process simulation have to be balanced in order to reduce the cycle time of the whole line. Iterative planning helps to evaluate and optimize different solutions concerning planning objectives defined in advance. The second step lacks support for energy-related decision, since current tools are unable to support congruent determination of energy consumption, temporal and spatial objectives within process simulation. Thus, planning solutions are tested for energy-related objectives by leveraging simulation as described in section 4. In order to reduce iteration loops, an integration of energetic aspects into process planning tools would be worthwhile. Automatic approaches like introduced in [17] can be a starting point for energy-sensitive planning by using integrated optimization techniques. 6

SUMMARY

This paper presented a Semantic Web-based approach to manufacturing data analysis regarding energy consumption and accompanying generalization of findings by simulation models for dynamic energy forecasts during the planning phase. We showed that the application of ontologies for production system descriptions enables their combination with collected product and process data. Based on this technology, an approach for guided data exploration was introduced that supports the selection of relevant data sets in manufacturing data analysis. Furthermore, it can be used to compile relevant data for the verification of simulation models.

[2]

Patni, H.; Henson, C.; Sheth, A. (2010). Linked sensor data, in: Proceedings of International Symposium on Collaborative Technologies and Systems, pp. 362-370.

[3]

Resource Description Framework: Concepts and Abstract Syntax, http://www.w3.org/TR/rdf-concepts/.

[4]

OWL 2 Web Ontology Language Document Overview, http://www.w3.org/TR/owl2-overview/.

[5]

Morbach, J.; Wiesner, A.; Marquardt, W. (2009). OntoCAPE– A (re)usable ontology for computer-aided process engineering. Computers & Chemical Engineering, 33(10), pp. 1546-1556.

[6]

Lemaignan, S.; Siadat, A.; Dantan, J.; Semenenko, A. (2006). MASON: A Proposal For An Ontology Of Manufacturing Domain, in: IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications, 2006. DIS 2006, pp. 195-200.

[7]

Compton, M.; Henson, C.; Neuhaus, H.; Lefort, L.; Sheth, A. (2009): A Survey of the Semantic Specification of Sensors. 2nd International Workshop on Semantic Sensor Networks, at 8th International Semantic Web Conference.

[8]

Hobbs, J. R.; Pan, F. (2004). An Ontology of Time for the Semantic Web. ACM Transactions on Asian Language Information Pocessing, 3, pp. 66-85.

[9]

SPARQL, http://www.w3.org/TR/rdf-sparql-query/.

[10] Klingener, J. F. (1995): Combined discrete-continuous simulation models in ProModel for Windows, in: Proceedings of the 1995 Winter Simulation Conference, , Arlington, VA, United States, pp. 445-450. [11] Spieckermann, S.; Gutenschwager, K.; Heinzel, H.; Voß, S. (2000): Simulation-based Optimization in the Automotive Industry – A Case Study on Body Shop Design, SIMULATION 75:5, pp. 276-286. [12] Proß, S.; Bachmann, B. (2009): A Petri Net Library for Modeling Hybrid Systems in OpenModelica. Proceedings 7th Modelica Conference, Como, Italy, pp. 454-462. [13] Bouchhima, F.; Brière, M.; Nicolescu, G.; Abid, M.; Aboulhamid, E. M. (2006): A SystemC/Simulink CoSimulation Framework for Continuous/Discrete-Events Simulation. IEEE International Behavioral Modeling and Simulation Conference, San José, CA, USA, pp. 1-6. [14] Sanz, V.; Uriquia, A.; Dormido, S. (2008): Introducing Messages in Modelica for Facilitating Discrete-Event System Modeling, in: Proceedings of 2nd International Workshop on Equation-Based Object-Oriented Languages and Tools, Paphos, Cyprus, pp. 83-93.

Regarding such simulation models, several methods were introduced that enable the consideration of energy efficiency for planning purposes.

[15] Mattsson, S.E., Elmqvist, H. (1997): Modelica - An international effort to design the next generation modeling language. 7th IFAC Symposium on Computer Aided Control Systems Design, Gent, Belgium, pp. 1-5.

7

[16] Weinert, N.; Chiotellis, S.; Seliger, G. (2009): Concept for Energy-Aware Production Planning based on Energy Blocks. Proceedings of the 7th Global Conference on Sustainable Manufacturing, Chennai, India, pp. 75-80.

ACKNOWLEDGMENTS

The research is part of the innovation alliance "Green Carbody Technologies", funded by the German Federal Ministry of Education and Research (BMBF). 8 [1]

REFERENCES Coulet, A.; Smail-Tabbone, M.; Benlian, P.; Napoli, A.; Devignes, M. (2008): Ontology-guided data preparation for discovering genotype-phenotype relationships. BMC Bioinformatics, 9(Suppl 4), S3.

[17] Neugebauer, R.; Friedemann, M.; Riegel, J.; Wenzel, K. (2009): Planning of job-shop factories leveraging genetic algorithms, in: Proceedings of the 7th International Conference on Manufacturing Research, Warwick, UK, pp. 242-247.

Energy Data Acquisition and Utilization for Energy-Oriented Product Data Management 1

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Thomas Reichel , Gudula Rünger , Daniel Steger , Uwe Frieß , Markus Wabner 1

Department of Computer Science, Chemnitz University of Technology, 09107 Chemnitz, Germany 2 Fraunhofer IWU, Reichenhainer Straße 88, 09126 Chemnitz, Germany

Abstract The development of energy-efficient products requires a consideration of energy information of all life cycle phases. Product data management (PDM) systems support this development process by providing the design engineer with relevant product data and models, but lack the incorporation of energy simulation models and energy usage measurements of manufacturing, operation, and recycling. This article defines requirements for an energy-oriented product life cycle management and investigates whether existing PDM systems can manage energy models and data. The utilization of prospective and retrospective energy data of machine tools is identified as being essential and is discussed in detail. Keywords: Energy Efficiency; Product Data Management; Energy Data

1

INTRODUCTION

Limited resources and increasing endeavors for climate protection emphasize the importance of the development of resource-efficient products. The development process has to consider all product life cycle phases, such as manufacturing, operation, and recycling [1]. IT systems in product development, e.g., product data management (PDM) systems, play an important role in providing design engineers with relevant models and data. In addition to models and data of product development, the approach of product life cycle management (PLM) tries to provide models and data of all life cycle phases, such as manufacturing, operation, and recycling [2]. A major task of PLM is to collect, store, and distribute knowledge of the products life cycle to all stakeholders [3]. Energy-oriented PLM considers the energy usage of products. It provides the design engineers with prospective and retrospective energy data of all life cycle phases. In product development, prospective data anticipates properties of a product in subsequent life cycle phases, such as manufacturing, operation, and recycling. Retrospective data represents the actual energy usage of an already existing product and its components, e.g., in operation. To provide prospective and retrospective energy data, an IT system for energy-oriented PLM has to integrate existing IT solutions of the product life cycle, such as PDM systems, manufacturing execution systems (MES), and enterprise resource planning (ERP) systems [4]. Furthermore, this IT system for energy-oriented PLM integrates product structure, process, resource, and cost models into life cycle product models with regard to available energy information. These life cycle models can be utilized to assess the energy usage of product designs. PDM systems are fundamental components of an IT system for PLM [5]. PDM focuses on the management of product models that contain all relevant product data. Life cycle assessment (LCA) has been recently integrated into PDM systems to provide information about energy expenses of raw material fabrication and logistics. With the information about the kind and the amount of raw materials, LCA data can be utilized to estimate the energy usage of product materials. However, existing PDM systems insufficiently

incorporate retrospective energy data from manufacturing and operation phases [6]. Additionally, prospective energy data is missing to estimate energetic impacts of product designs. Therefore, existing PDM systems cannot be utilized to assess the energy usage of a product in life cycle phases after product development [1]. The exchange of energy usage information of products is currently performed by implicit knowledge of domain experts and not explicitly by IT systems that support design decisions of engineers [6]. The contribution of this article is to define major functionalities of an energy-oriented PDM system that are necessary to support the management of prospective and retrospective energy data. Stateof-the-art PDM systems are evaluated and it is investigated whether these systems already provide IT features that can help to implement these functionalities. As an example, use cases of prospective and retrospective data for machine tools are described in detail and a corresponding IT implementation is proposed. The following sections are organized as follows: Section 2 proposes major functionalities of energy-oriented PDM systems from the design engineers’ point of view and evaluates existing PDM systems with respect to these functionalities. Section 3 discusses the acquisition and utilization of prospective and retrospective energy data for machine tools. Section 4 presents an implementation of an IT system that collects and aggregates energy data of machine tools in operation. The section outlines an approach to integrate this data into the manufacturers’ product model. Section 5 concludes the article. 2

REQUIREMENTS FOR ENERGY-ORIENTED PDM

This section specifies functionalities of energy-oriented PDM systems and describes enhancements of existing PDM systems that are necessary to incorporate prospective and retrospective energy data. Also, it is investigated whether state-of-the-art PDM systems already provide features that can help to implement the functionalities described.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_89, © Springer-Verlag Berlin Heidelberg 2011

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Autodesk Inventor® and Autodesk Data Management Server 3 (2010, Student Version)

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PTC Windchill® (Windchill PDM-Link 9.1, PRO Engineer)

4

In the following, the six major functionalities of energy-oriented PDM systems (see Figure 1) are discussed. Also, relevant IT features that can help to implement these functionalities and limitations of the systems evaluated are emphasized. a) Product model management

Figure 1: Major functionalities of an energy-oriented PDM system. 2.1

Functionalities of energy-oriented PDM systems

Usage scenarios of existing PDM systems mainly focus on the management of data created during product development. An extraction of decision-relevant knowledge or even decision-relevant data from other life cycle phases, such as manufacturing and operation, is scarcely supported. Therefore, an energy-oriented PDM system has to provide prediction models, which deliver prospective data that can help to assess the energy usage or the carbon footprint of products. The models focus on the prediction of selected properties of a product or a component in a specific life cycle phase. One example is the prediction of the energy consumption of a product in operation. Furthermore, an energyoriented PDM system incorporates operating and maintenance data. This data is called retrospective data. With the help of this data, the design engineer can analyze the actual behavior of an existing product or component in specific usage scenarios. Also, this data can be used to compose new products based on components with available energy data. Thus, the management of prospective and retrospective data should be organized such that the design engineer can assess the energy usage of a product as early as possible in the development process. Since relevant life cycle data is stored in PDM systems as well as in MES and ERP systems, an integration of these IT systems is mandatory for an energy-oriented PDM system. One example is the integration of an ERP system at the customer site with a PDM system at the manufacturer site. With such an integration, maintenance data and utilization data of a machine tool used by the customer can be automatically transmitted to the PDM system of the manufacturer of this tool.

A key task of PDM systems is the management of product models. Existing product models compose product components (assemblies, parts, etc.) in a hierarchical product structure that can be linked with other domain models, such as virtual models, (mathematical) simulation models, ECAD models, and resource (material) models [3]. In the PDM systems evaluated, domain models are usually treated as documents linked to the product structure. These models are not integrated into a life cycle product model and the information contained is used by specialized systems. For instance, simulation models are handled by the simulation system exclusively and the results of the simulation cannot be utilized by a PDM system (e.g., by component properties or features). Energy relevant data, such as energy usage measurements and environmental impacts of materials used, are also not integrated into the life cycle model or in part libraries. In order to include retrospective and prospective energy data into an energy-oriented PDM solution, this data has to be linked to the product structure. Therefore, the product model management has to support energy considerations of product components. This forms a basis for the prediction of the energy consumption in different usage scenarios and life cycle phases for products to be developed. b) Document management The product structure is commonly used to link related documents to components of the product. Existing PDM systems focus on the integration of CAx documents and are also able to store any other kind of documents (e.g., text, drawings) [9]. The systems evaluated provide IT features to trace change histories of documents as well as features to import/export, classify, search, and archive documents. Apart from document-related features, the consistency between the product model and linked documents is essential in case of product model changes. Windchill, for instance, provides mandatory references that require the user to update documents referenced if the corresponding product structure element is changed.

Since several domain experts are usually involved in the development process, collaboration management plays an important role for PDM systems. Additionally, this management has to involve suppliers and customers of the manufacturer [3].

All systems evaluated provide a repository to store the product model and all kinds of documents. Additionally, Windchill and PRO.FILE offer a customizable print and electronic archiving management as well as features to inspect document structures.

Figure 1 depicts six major functionalities of an energy-oriented PDM system. An implementation of an energy-oriented PDM system should be based on IT features of existing PDM systems. The functionalities may overlap as some IT features can be utilized for multiple functionalities.

Energy and environmental data of the product can be stored as documents. Nevertheless, the systems evaluated cannot utilize the document content to extract relevant energy data. For example, a document that contains all consumers of a product and their energy usage in a specific usage scenario can be linked to the product structure. However, an identification of the main consumers based on the document content is not supported by the PDM systems evaluated.

2.2

Evaluation and limitations of existing PDM systems

A first evaluation of IT features of existing PDM systems has been presented in [7]. This section expands this evaluation with the focus on the management of prospective and retrospective data. The following systems are evaluated:   1

Aras Innovator® (Version 9.1) PROCAD PRO.FILE® [8] http://www.aras.com/

2

1

2 3 4

http://www.procad.de/plm_eng/profile/pro_philosophy.html http://students.autodesk.com/ http://www.ptc.com/products/windchill/pdmlink/

Information and Knowledge Management c) Project and stakeholder management Since different company divisions (of possibly different companies) collaborate in the development of complex products (integrated product development [4,10]), access policies and customized views as well as time planning/scheduling and project management (monitoring, reporting) are necessary in the development process. One example is the integration of suppliers of sub-systems of a product. The suppliers have restricted access to the PDM system of the manufacturer to exchange product data of sub-systems. This integration requires security access rules (e.g., to keep trade secrets) and standardized interfaces to interact with third party PDM systems. All systems evaluated provide project management features, such as project planning, user roles, email communication, and tools for the reporting and monitoring of projects. Additionally, these systems support the integration of suppliers in the development process. For example, the systems support the import of assemblies (their product structures and linked CAx documents) and the involvement of suppliers in quality management processes. Vendor-specific data formats and interfaces restrict the exchange of product relevant data between different PDM systems. Vendorindependent formats (e.g., STEP) may not be able to incorporate all details of vendor-specific data formats. d) Configuration and variant management Configuration and variant management is a mandatory functionality to compare different design solutions. The design of product variants (product structures with alternative branches) is provided by supplementary system components by each system evaluated. Autodesk Inventor and Windchill provide a generic part management, so called family tables, in order to represent parts with parametric geometries. PRO.FILE, Windchill, and Innovator offer IT features to search for similar assemblies based on geometric properties. Since prospective and retrospective energy data cannot be utilized by the systems (see product model management), a search for similar assemblies based on performance indicators and usage scenarios is not supported. Apart from the systems evaluated, there are databases to compare components based on performance and efficiency indicators for selected product types, such as the Eurodeem database for electric motors [11]. An energy-oriented PDM system has to support the comparison of design solutions based on prospective and retrospective energy data. This comparison enables the design engineer to select components for new products with regard to the energy usage of the components. e) Life cycle integration A major task for life cycle-oriented product development is the application of models and documents created during product development in subsequent life cycle phases. Feedback of these subsequent phases is also needed that requires a mapping of life cycle data to product development models. In the PDM systems evaluated, product models can be used for computer aided process planning and manufacturing (bill of material). However, feedback of these phases is usually given by change requests or failure reports. Innovator, Inventor, and Windchill supply additional components for integrating LCA. The LCA integration ranges from user defined properties for parts in the Innovator Environment plugIn (e.g., to attach energy indicators) to life cycle evaluations based on existing LCA solutions, such as SustainableMinds (Inventor) and Insight (Windchill). These LCA solutions focus on the environmental footprint of material production and material compliance with respect to governmental guidelines. However, these solutions do not integrate prospective and retrospective energy data for a

515 specific product in the operation or in the recycling phase. Therefore, only rough estimations of the costs and the energy usage of a specific product are available. Such estimations may be insufficient for machine tools, as the operation phase is mainly responsible for their life cycle cost and energy consumption [12]. Collecting operating data for products requires the integration of (customer) ERP data. The systems evaluated already provide interfaces to integrate ERP systems. However, the customer integration is scarcely supported. Nevertheless, Windchill provides a component named Reflex, which allows statistical analyses of operating data. The results can be used in processes for total cost of ownership (TCO) and life cycle costing (LCC). To incorporate operating energy data in the development process, an energy-oriented PDM solution has to utilize existing ERP interfaces to acquire this data from customer ERP or MES systems. f) Business process management Business processes implement repeated procedures of product development with manual and automatic process steps and involve different stakeholders. For example, the systems evaluated provide advice, change, and release processes for documents and product designs. These processes incorporate design engineers and management. Innovator, PRO.FILE, and Windchill allow the specification of workflows that represent individual business processes of a company. In an energy-oriented PDM system, process management is not limited to document and model management. Business processes help to implement methods to compare product configurations and support the application of prediction methods by input/output data preparation. Business processes can also be utilized to integrate external systems, such as simulation frameworks. 2.3

Summary

The management of prospective and retrospective energy data is currently performed by IT systems that are not integrated with the PDM systems evaluated. Thus, the integration of energy data into the PDM systems remains a manual task. An energy-oriented PDM system supports the aggregation/storage of this data and simplifies its collaborative usage. In the following section, the acquisition and the utilization of prospective and retrospective energy data during product development is discussed, drawing on the example of machine tools. 3

ENERGY DATA ACQUISITION WITH PDM SYSTEMS

Analyzing the energy usage of virtual and physical technical products, such as machine tools, by an examination of prospective and retrospective energy data is a core issue for optimizing a product towards energy efficiency [13]. It is the task of an energyoriented PDM system to provide a platform for managing and distributing energy data. This PDM system is of special significance, because it is available for the different divisions with different perspectives on the product. 3.1

Indicators for energy-oriented product development

A central requirement of a PDM system with the purpose of energyoriented product design consists of filtering and preparing different energy data to provide meaningful and standardized indicators for different divisions. The indicators are the basis for design decisions made in the product development process (e.g., described in [14]). The energy usage of a technical product in operation is the most relevant energy data. This usage data has to be analyzed for each sub-system (components and devices) of a machine tool (see Figure 2). The energy data for the sub-systems has to be provided

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PDM system Product model Product configuration 1

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Map energy usage of parts and subsystems to the product model • Model • Configuration • Layout • Assemblies • Parts

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Map energy usage of parts and subsystems to the product model • Model • Configuration • Layout • Assemblies • Parts

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• Design • Transport, handling • Material, machining

• Measured energy usage over time • Energy usage per operation state

• Design • Transport, handling • Material, machining

• Energy usage (part, subsystem, machine tool) • Carbon footprint (part, subsystem, machine tool)

• Work pieces per kWh • Eoverall per machining cycle • Carbon footprint per work piece • Carbon footprint per cycle

• Energy usage (part, subsystem, machine tool) • Carbon footprint (part, subsystem, machine tool)

Figure 2: Generation of energy data and implications to the PDM system. for different time intervals and has to contain context information about usage scenarios, such as machine states of the machine tool (e.g., stand by, ready for machining). Besides this “raw” energy data, indicators that are relevant for the product development allow the comparison of different design layouts. These are in particular output-related indicators, like work pieces/kWh [15] or chip volume/kWh. Apart from economical data, indicators that represent the impact of a technical product on the environment are a growing concern. The most important currently discussed indicator is the so called product carbon footprint [16] that measures the overall equivalent carbon dioxide (CO2) output of a product over the entire product life cycle. Life cycle considerations are central to this indicator. To calculate the carbon footprint, the energy usage of the product is determined for different phases of the product life cycle. Examples of this energy usage are the consumption of electrical energy and the energy equivalent of the additives used in auxiliary systems, e.g., oil consumption. The carbon footprint is the CO2output which is necessary to generate the amount of energy with regard to the specific ways of power generation used at the location. In current product development, data of the energy demand for the production and the removal of a technical product can only be estimated or calculated based on comparable products and experience. A detailed measurement of the energy demand of the manufacturing and the removal of individual parts and derived components of the product are only available for parts that are machined and assembled in the company itself. If component suppliers provide detailed energy data for buy parts, it is possible to calculate the energy usage for manufacturing complex technical products, such as machine tools. Besides the energy demand for manufacturing, the suppler has to provide ecological indicators for the component, such as the carbon footprint.

3.2

Utilizing energy data in product development

The energy efficiency of a machine tool can be improved by addressing the energy usage of the machine tool in the operation phase. This phase generally accounts for more than 90% of the overall energy usage in the life cycle of a machine tool [12]. Figure 2 shows options of the energy data generation and the derived consequences for the storage and the manipulation of this data by an energy-oriented PDM system. A first step to design a machine tool with reduced energy consumption is the simulation of the energy usage of the machine tool for different usage scenarios in operation with a virtual prototype. To achieve this, a special trained engineer creates a simulation model of the energy usage of the machine tool (including every relevant sub-system) with mathematical tools (e.g., Matlab/Simulink) [17]. The prospective energy data resulting of this simulation has to be linked to the product model. On the one hand, energy consumers (components and devices with energy usage) have to be linked to the product model in the PDM system, i.e., assemblies of the product model refer to the energy usage of subsystems. If the energy usage cannot be tracked down to a single energy consumer, it has to be distributed among several subsystems. On the other hand, the energy usage has to be associated with different product configurations according to the configurations used in simulations to compare different designs. Example simulation models can focus on energy efficiency, static machine behavior, thermal machine behavior, and manufacturing costs. Since detailed CAD data that contains all energy using sub-systems (e.g., sensors or small drives) is not available in early product development, product models should be able to represent multiple design layouts. Each design layout has to handle multiple sets of energy data for different usage scenarios of a machine tool. For example, the specific energy demand to manufacture a specific work piece on a machine tool can be used to determine the energy consumption per work piece. Other scenarios can include the

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Enterprise Service Bus DMZ

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Control data Energy Energy Energy Data Data Data Broker Broker Broker

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Figure 3: Architecture of an IT system to gather and evaluate retrospective measurements. manufacturing of different work pieces on a machine tool or combining different work pieces to a special machining cycle. To compare different machine tools with each other, standard work pieces (e.g., NCG-2004, NCG-2005), standard machining cycles or standard machining operations can be defined. One example is a milling operation that includes a tool change and a following drilling operation. As a result of the simulations, different design layouts of product models in the PDM system are associated with data sets for multiple usage scenarios, such as energy usage per work piece or energy usage per defined cycle. Product development can support the acquisition of operating energy data, for example by integrating sensors that measure the electrical energy consumption. The planning of measurements for the energy usage has to include the entire product and specific subsystems. In most cases, the manufacturer of machine tools wants to investigate its machine tools in operation at the customer site. Therefore, a connection has to exist between the PDM system of the manufacturer and the customer IT infrastructure. The energyrelevant data is correlated with context information, such as the condition monitoring of the machine tool. This data is delivered to the PDM system of the manufacturer. The energy data has to be assigned to a detailed product configuration with its allocated data (CAD data, electrical CAD data, etc.). Hence, different energy data sets that include different work pieces and different usage scenarios are linked to a product configuration implemented. Furthermore, an energy-oriented PDM system has to integrate software tools to filter retrospective data. This data filters can be utilized to prepare the data for different divisions of the manufacturer. For a product that is implemented and in operation, an energyoriented PDM system stores prospective and retrospective energy data. This energy data may exist for different product components, product layouts or product configurations. Furthermore, the structure and type of the data may vary according to the usage scenario, the machine state, and the context information. An energy-oriented PDM system has to provide functionalities to organize and to manipulate the energy data. Thus, energy data becomes comparable, for example simulation results with actual measurements for a component, and energy data from different usage scenarios for a sub-system with each other. 4

REFERENCE IMPLEMENTATION FOR RETROSPECTIVE ENERGY DATA RETRIEVAL

Energy data acquisition in an energy-oriented PLM solution requires a number of IT systems that collect and evaluate energy data of the product life cycle, e.g., operation phase, and make it available to product development. The IT systems operate at the customer and

the manufacturer (OEM) site and have to exchange energy data and context information. For this purpose, an existing IT infrastructure may be utilized and extended. For example, an IT solution for life cycle costing [1] may already collect data about machine utilization and maintenance. The proposed implementation represents a software architecture for a machine tool OEM and a customer that utilizes the machine tool for manufacturing processes (Figure 3). At the customer site, energy data has to be collected for individual machine tools on a factory level. To achieve this, an energy data broker or another existing data collection system retrieves sensor data from the machine tool and the machine components. The energy data can be structured using an existing machine tool structure and states, e.g. based on [18]. Additional context information, such as a work piece description, enriches the measured data at machine control and factory level. The aggregated measurement and context data are stored in a designated measurement database. As the process of senor data collection, structuring, and association with context information may run at a high frequency, the energy data broker has to be designed to handle high data volume transfer. The solution for an automated energy data collection proposed by [19] uses a complex event processing system to achieve this. Such a system can be utilized to reduce the data quantity by triggering a high sampling rate for sensor data only if an event occurs that marks the beginning of an “interesting” process on the machine tool. An end event of this “interesting” process causes the switch back to a lower sampling rate. On the other hand, parallel data broker instances can handle the amount of data effectively and store the data in a distributed database system. A factory-wide solution for energy data collection demands a standardized machine tool interface for energy data. Promising ®5 ®6 examples are PROFINET or MTConnect . The energy data broker can use such a system to retrieve machine control data and available sensor data as well context data. Storing the energy data in a centralized measurement database enables a factory-wide utilization, for example in an energy management system, which monitors the actual energy usage of the factory. The delivery of measurement information about a machine tool to its OEM requires a security infrastructure to protect the intellectual property of the customer and OEMs of other machine tools in the factory. A proven solution for this scenario is a software portal for the OEMs (OEM Connector) within a restricted 5 6

http://www.allthingsprofinet.com/ http://www.mtconnect.org

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zone (DMZ) that is separated from the local network by an extra firewall. The customer can create access rules and can install filters that configure the kind of data an OEM may retrieve. The data exchange between the customer and the OEM is usually designed as an on-demand interface using enterprise business-to-business communication. At the OEM site, an Energy Data Storage component retrieves the filtered measurement data and stores it in a centralized database for retrospective data. This storage keeps an energy data model for the measured sensor data with control and context data. Mapping this customer-specific product configuration to the product structure allows the PDM System to retrieve energy data for existing products and product components. For a new product design, for example, a design engineer wants to compare the energy usage of product components. Thus, a search through the PDM system includes an inquiry of available data for product components in the energy data storage. The search result is a list of product components and their energy profiles. These profiles describe the energy usage of a component assembled in a customer machine tool and the corresponding machine states. A PDM system has to provide a suitable visualization to evaluate these profiles. As a result, the engineer can decide which product component fits best to a new product design. Instead of storing energy data with the product context in the PDM system, the centralized energy data storage can be utilized from different IT systems outside the product context. An Enterprise Service Bus serves as common data exchange platform. 5

CONCLUSION

The integration of energy data of the entire product life cycle into PDM systems is a key issue of energy-oriented PLM. The management of prospective and retrospective energy data by energy-oriented PDM systems and the availability of this data during product development have the following benefits. First, the major energy consumers of a product can be determined and all stakeholders of the product life cycle can be informed by the stakeholder management of the PDM system. Second, results of simulations of components can be used to assess and compare entire product configurations and design solutions. The comparison of the predicted behavior with retrospective measurements is a third benefit, which enables the design engineers to improve the simulation models incrementally. Finally, a standardized format to manage retrospective energy measurements in a PDM system leads to comparable components of different vendors, if key indicators for components, such as a carbon footprint for specified usage scenarios, are available. Energy costs are a driving factor for reducing the energy usage of machine tools in operation. This is also true for manufacturing and recycling. Nevertheless, the perceived savings have to justify the costs for developing and implementing an improvement in a machine tool. Therefore, energy-oriented PLM that includes cost management can evaluate costs as well as energy usage in the product life cycle. This allows the budgeting of all improvements to reduce the energy usage of a machine tool. Future work focuses on the integration of costs into energy-oriented PLM. 6

REFERENCES [1]

Niemann J.; Tichkiewitch S.; Westkämpfer E. (Eds) (2009): Design of Sustainable Product Life Cycles, Springer Berlin Heidelberg.

[2]

Ameri, F.; Dutta, D. (2005): Product Lifecycle Management: Closing the Knowledge Loops, in: Computer-Aided Design & Applications, Vol. 2, No. 5, pp. 577-590.

[3]

Stark, J. (2007): Global Product: Strategy, Product Lifecycle Management and the Billion Customer Question, Springer.

[4]

Pahl, G.; Beitz, W.; Feldhusen, J.; Grote, K. (2007): Engineering Design. A Systematic Approach, Springer London.

[5]

Stark, J. (2005): Product Lifecycle Management, Springer London.

[6]

Bufardi, A.; Kiritsis, D.; Xirouchakis, P. (2008): Generation of Design Knowledge from Product Life Cycle Data, in: Bernard A.; Tichkiewitch S. (Eds), Methods and Tools for Effective Knowledge Life-Cycle-Management, pp. 375-389, Springer Berlin Heidelberg.

[7]

Reichel, T.; Rünger, G.; Steger, D.; Xu, H. (2010): ITUnterstützung zur energiesensitiven Produktentwicklung, Technical Reports of the Department, CSR-10-02, Chemnitz.

[8]

Sendler, U.; Wawer, V. (2008): CAD and PDM. Optimizing Processes by Integrating them, Hanser Fachbuch.

[9]

Eigner, M.; Stelzer, R. (2009): Produktdaten-Management und Product Lifecycle Management, Springer Berlin.

[10]

[10] Magrab, E.B. (1997): Integrated Product and Process Design and Development: The Product Realization Process, CRC-Press.

[11]

Council of the European Union (2007): European database of efficient electric motors. http://sunbird.jrc.it/energyefficiency/ eurodeem/ [Accessed 2010 Oct 14].

[12]

CECIMO (2009): Concept Description for CECIMO’s SelfRegulatory Initiative (SRI) for the Sector Specific Implementation of the Directive 2005/32/EC (EuP Directive).

[13]

Brecher, C.; Boos, W.; Klein, W.; Kuhlmann, K.; Triebs, J. (2009): Ressourceneffizienzbewertung einer Werkzeugmaschine zur Steigerung ihrer Wirtschaftlichkeit, in: ZWF - Zeitschrift für wirtschaftlichen Fabrikbetrieb, Vol. 104, No. 9, pp. 711-715.

[14]

International Organization for Standardisation (2007): ISO 14000 – Environmental management.

[15]

Neugebauer, R.; Wabner, M.; Thomas, K.; Drossel, W. (2009): Discussion of Key Parameters and Methods for Comparison of Energy Needs of Machine Tools, 59th CIRP General Assembly, Boston.

[16]

Quack, D. (2008): Product-Carbon-Footprint: Der ökologische Fußabdruck von Produkten, Öko-Institut e.V.

[17]

Neugebauer, R.; Wabner, M.; Rentzsch, H.; Scheffler, C.; Kolesnikov, A. (2010): Development Approaches for Energy Efficient Machine Tool Structures, IMS Summer School: Maufacturing Strategy, Zurich.

[18]

Dietmair, A.; Verl, A. (2009): A generic energy consumption model for decision making and energy efficiency optimisation in manufacturing, in: International Journal of Sustainable Engineering, Vol. 2, No. 2, pp. 123-133.

[19]

Vijayaraghavan, A.; Dornfeld, D. (2010): Automated energy monitoring of machine tools, in: CIRP Annals - Manufacturing Technology, Vol. 59, No. 1, pp. 21-24.

ACKNOWLEDGEMENT

The Cluster of Excellence “Energy-Efficient Product and Process Innovation in Production Engineering” (eniPROD ©) is funded by the European Union (European Regional Development Fund) and the Free State of Saxony.

Integrating Energy-Saving Process Chains and Product Data Models 1

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Gudula Rünger , Andreas Schubert , Sven Goller , Björn Krellner , Daniel Steger 1

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Department of Computer Science, Chemnitz University of Technology, Chemnitz, Germany Department of Mechanical Engineering, Chemnitz University of Technology, Chemnitz, Germany

Abstract The evaluation of energy efficiency in the product life cycle should include the energy used for manufacturing. An early consideration of manufacturing processes during product development can help to optimize the product design in order to achieve an energy-efficient production. Existing approaches and product data management systems lack the integration of energy data for production processes and do not cope with the manufacturing of complex products. Therefore, an integration of energy-saving process chain models with the product structure is proposed in this article. Based on such process chain models, estimations of time, energy and cost for manufacturing parts can be calculated. Keywords: Product Data Management; Process Chain; Energy Efficiency

1

INTRODUCTION

Using resource energy efficiently has become an economic and ecological requirement for the manufacturing industry [1]. Efforts concentrate on the efficient usage of energy in production processes and on energy reuse. Depending on the specific product, manufacturing accounts for a considerable amount of the energy used during the product life cycle. On the one hand, an early consideration of manufacturing processes in product development can help to optimize the product design for an energy-efficient production and, thus, can save energy in the product life cycle. On the other hand, manufacturing processes can be planned and optimized while the product is designed. To achieve the data exchange between product development and manufacturing planning, product life cycle data of both fields have to be collected and linked together. This energy data link is an important part of energy-oriented product life cycle management (PLM), which focuses on collecting, storing, and distributing energy data during the product life cycle. There exist several solutions that implement parts of PLM for sharing product or environmental data between, e.g., product development and manufacturing. To evaluate the environmental impacts of a product, methods like life cycle assessment (LCA) are utilized. Recent efforts make LCA easily available in product development by integrating LCA data with the product data management (PDM). As a consequence, the material composition of a product that is designed can be analyzed instantly. PDM systems also provide interfaces to the manufacturing phase, e.g. by exporting product data models to computer aided manufacturing (CAM). In this way, a CAD model becomes the input for the software control of a machine tool. Nevertheless, these interfaces between product development and manufacturing or LCA lack the integration of energy related process data. However, this energy data plays an important role when evaluating sustainable manufacturing, as stated in [2], and should be included. Developing a new product and planning its manufacturing are collaborative activities for which IT systems organize information and communication flows. Integral IT systems for product

development are PDM systems [3]. PDM systems contain a central repository for product data models and activities which are used to create and manipulate product data. A key functionality of PDM systems is to set up and store product configurations that can be used in manufacturing planning. Based on the design specification from product development, the production engineers plan all manufacturing steps and resources for manufacturing the product. The whole production includes manufacturing processes, logistic processes, and assembly processes. Software support exists for all the different aspects of manufacturing planning, but usually does not consider energy aspects. This article focuses on the aspect of modeling energy-saving process chains and the corresponding processes to manufacture the parts. Energy-saving process chains consist of mathematical models of process steps with pre- and post-conditions as well as specific machine data to calculate time, energy and costs. Constraints for manufacturing processes can be combined with part data (geometry, materials, stresses, strains, etc.) to evaluate whether a part can be manufactured within the process limits. The process chains specify the technological processes, material and energy flows that are necessary to manufacture the parts. This article shows an approach to model process chains and to integrate the process chains and the product structure for product development. The process chains are modeled such that energy can be saved in the manufacturing process. Additionally, process chain models can be used for energetic optimizations and energy reuse. An integration of these energy-saving process chains with product structures can provide the means to estimate time, energy and cost for manufacturing parts while they are designed. This energy data link between parts and process chain models can also provide helpful feedback to manufacturing planning by identifying manufacturing processes with a high energy usage and the corresponding parts. In the following two sections the product data models for product development and process chains for manufacturing process planning are described. Use cases for an energy data link and the gains of the approach are summarized. An IT implementation for

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_90, © Springer-Verlag Berlin Heidelberg 2011

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the data model and the necessary interfaces of an energy data link is proposed. Section 6 compares the approach with related work. The final section concludes the article and gives an outlook. 2

PRODUCT DATA MANAGEMENT

This section starts with an introduction on how current PDM systems prepare product data models for manufacturing planning. After discussing drawbacks of existing solutions, the integration of the product data models and process chains is proposed to enable an energy-oriented manufacturing process planning. 2.1

Product structure in PDM systems

In a typical PDM system, a product is described by a tree structure, which contains the product as a root node, assemblies or other sub products as inner nodes, and parts as leaf nodes. Along the product development process more and more details are added to the product structure by inserting additional nodes and attaching documents to existing nodes. Still during development, less important details such as screws are left out. For the manufacturing of the product, a complete specification of the product has to be created, including the parts to be manufactured and the buy parts. This specification is managed in PDM systems through the product structure. The product structure managed by the PDM system corresponds to the structure of the detailed geometry in a CAD model. CAD systems allow the input of additional information for a CAD model to specify parameters, such as tolerance or material, and pre-defined geometry elements (features), e.g., for drill holes. The CAD model and its features already describe the part manufacturing and can be used for CAM to create and manipulate numerical control (NC) programs. As central repository, the PDM system stores parts with associated CAD models and NC programs. The product structure can contain alternatives or substitutions for individual parts. From this information, product configurations and variants can be inferred and can be managed through the PDM system in the form of a bill of materials (BOM). The manufacturing engineer uses the BOM for planning the manufacturing resources. This includes adding standard parts, or determining the sequence of manufacturing and assembly processes to build the final product. These existing approaches for integrating product development with manufacturing represent a sequential workflow of actions. Manufacturing planning takes place in the late product development phases. The information flow is usually from product development to manufacturing, but not vice versa. Thus, information about the energy used to manufacture parts is not available to product development. However, a variation of the part design may introduce an energy saving potential into the process chain. Therefore, a data link between the structure of a product and the process chains can provide support for such an approach. This link allows the data exchange in both directions: part data are required for manufacturing process planning, and manufacturing restrictions set limits for the product design. The benefits of the integrated approach for product development are discussed in the next section. 2.2

Integration of product structure and process chains

The integration is based on a data link between the product development view and the manufacturing view on the product structure as shown in Figure 1. Leaf nodes in the product structure (parts) are associated with appropriate process chain models that describe their manufacturing. The data link between parts and process chains can be utilized in the following ways. The product development view shows the links between the product structure and different CAD models, drawings and other documents

Figure 1: Illustration of the data links between product structure, CAD documents (top), and process chains (bottom). in the PDM system (see Figure 1, top view). A part can be associated to a process chain by creating a link to a model in the manufacturing repository of process chains (see Section 5). If a CAD model and a corresponding process chain for a part exist, energy usage information for manufacturing the part can be invoked from the appropriate IT system, the process chain modeler. In case it is a buy part and no process chain exists, energy usage for manufacturing this part can be estimated either from information of the supplier or from an energy equivalent calculated from the price of the part. Another approach is to calculate the carbon footprint of a part which can be done as described in [4]. The manufacturing view lists the process chains and associated parts to be manufactured. Additionally, manufacturing engineers attach raw parts to the process chains. To achieve this, CAD models of raw parts from a part library of the PDM system or a supplier database are linked with the process chains. In the process chain modeler, the process chains and associated CAD models of the part as well as raw parts are utilized to calculate energy usage of manufacturing. The value of the integration of product development and manufacturing planning can be summarized by sharing product life cycle data between these two phases. Product designs can be improved by selecting parts with respect to their manufacturing impact and by making manufacturing knowledge available for new product development. 3

MANUFACTURING PLANNING

This section first describes an approach for designing process chains for the manufacturing of parts. An overview of data and data models necessary for planning process chains in detail is given. Then, the description is extended to the assembly of parts resulting in assemblies and in the final product. 3.1

Defining and detailing process chains

A manufacturing engineer has to plan the manufacturing steps for a product based on the design specification resulting from the product development. For the planning of the manufacturing several approaches and methodologies can be used. The first step is to define the order of the processes in a process chain. In practice,

Main Shape Forming

521

Roughing,

Properties Setting

Finishing,

Semi-Finishing

(Hardening …)

Super Finishing

Part I

Raw Part I

Information and Knowledge Management

Assembly I

Roughing,

Properties Setting

Finishing,

Semi-Finishing

(Hardening …)

Super Finishing

Part II

Raw Part II

Main Shape Forming

Final Assembling

Product

Assembling Backward Planning

Assembly I

Assembly II Forward Planning

Figure 2: Planning process chains: Initially, the sequence is planned from raw part to assembling. Based on the experience with part I, the processes for part II may be planned vice versa. For product completion the final-assembling also from other parts is intended. two typical principles exist: If a part or a similar part has already been manufactured in the past, the principle of analogy is used. Otherwise, the principle of optimization leads to a new process chain, for which the engineer could use the forward and backward planning of processes. The forward planning starts at the point of the raw part, the backward planning at the point of the finished part [5]. Thus, the process sequence can be defined step by step. Both planning methods are often used in parallel, as shown in Figure 2. When planning the process chain the following phases of manufacturing have to be considered: 1. Main shape forming, 2. Roughing and semi-finishing, 3. Setting of chemical and physical properties, 4. Finishing and super-finishing. This order is typical for machining metallic materials. For other groups of materials with similar properties this order can also be used to plan the process chains. However, the characteristics of the materials have to be considered. The following descriptions concentrate only on details of manufacturing metallic materials. In the main shape forming phase the workpiece gets its rough geometrical dimensions, e.g., by massive forming, casting, or joining. Alternatively, using near-net-shape forming processes can reduce the efforts of the following chipping processes. In Phase 2, chipping processes approximate the geometric shape of the workpiece to the desired end geometry. The difference between actual and desired geometry should be very small after this step, because after hardening areas of the workpiece in Phase 3, it becomes difficult to chip the material. Besides hardening also other chemical, mechanical and physical properties can be set selectively. During the last manufacturing phase, cutting or abrasive processes finish the final geometrical dimensions and surface properties. Although all process chains follow this general order, they differ in the processes used to create the geometry and functional properties of the part. Besides distinct process chains for different parts, there may exist distinct process chains for the manufacturing of one part. Considerations, such as the technical feasible manufacturing technology of the company, significantly reduce the high number of process chains. After determining the order of the processes (of the different process chains) the detailing of the processes takes place. This includes the allocation of the machine tool, tools and additional equipment as well as the definition of process parameters under consideration of technical and economic issues. Although, the procedure described seems to be quite short, a lot of data and rules are needed to define and detail a process chain. The manufacturing engineer can use IT support to handle the large amount of data nowadays. However, IT support is usually restricted to specialized solutions to assess time and costs in a production

company. Current research focuses on including other factors, such as the energy usage for manufacturing parts. 3.2

Requirements, structure and functionality of a process chain modeler

Process chain modelers provide models which describe different pieces of the manufacturing process. For manufacturing planning, it is necessary to have a description of the workpiece, the machine tools, the tools, and the additional technical equipment. Suitable description methods are necessary to specify the workpiece that is machined in the manufacturing process considered. A simple geometrical description is insufficient. The description of the workpiece has to include additional physical and chemical properties for a workpiece region or the complete workpiece. A description of the influence of these properties on the process helps to identify properties with invalid values according to the process specification. The description of the overall technical equipment consists of geometrical, technical, manufacturing, and economic information [6]. With this information, it is possible to decide whether a clamping device or a tool can be used in a certain machine tool or whether a workpiece could be machined because of its geometrical dimensions and the available workspace of the chosen machine tool. Furthermore, some of this information is useful for the determination of economic quantities that are needed for the assessment of the manufacturing process. The process is described by the interaction between the workpiece and the technical equipment. Besides process parameters also equations on physics and technical mechanics for a model, such as a description of the manufacturing process, are used. If a process requires certain pre- and post-processes, they should be included in the process description. Pre-processes are often necessary to set the technical conditions for the process. For example, a joining process assumes a defined quality of the joint edges. Thus, it may be necessary to prepare these edges by cutting before the joining process is executed. Post-processes improve the process result. For example, edges have to be debured after chipping the workpiece. Similar restrictions exist for combining process chain fragments in a manufacturing phase or in a complete process chain. They can be specified by rules for necessary, possible and forbidden sequences of manufacturing processes. With these rules in mind, the manufacturing engineer plans the process chain and details the processes. Besides the information being relevant from a manufacturing point of view, additional information and rules for the calculation of economic quantities, such as manufacturing time, energy demand and cost of production, complement the manufacturing process description. At this point, information of the machine tool description can be used to determine the quantities required.

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Additionally, there is information with an interdisciplinary relevance. For example, to evaluate the demand of additional materials and supplies used in a manufacturing process it is necessary to consider manufacturing, economic and ecological issues likewise. The description of the machine tool determines whether the kind of material and its demand are feasible for the process. The additional materials and supplies lead to costs that need to be calculated. The ecological impact including the energy used by a supply has to be evaluated as well.

manufacturing the part. If multiple process chains are assigned, all valid process chains should be considered. Additional manufacturing context information, such as lot size or time, is necessary for an evaluation of time, energy or cost for the process chain.

In summary, process, machine and workpiece information enable the manufacturing engineer to evaluate the manufacturing process in a first step and the process chain in a second step. Time, energy usage and cost considerations have a significant influence on the decision, which process chain and manufacturing processes are implemented to produce a part.

Use case III (product configurations):

3.3

Assembly planning

In addition to the manufacturing planning, the assembling of the manufactured parts has to be planned. At this point, the engineer has not as much freedom as in planning the process chain for manufacturing parts. Product development often sets constraints on the assembly process. The product structure defines an initial assembly sequence of the product. Additional constraints result from accessibility of parts in an assembly. As a result, there are often fixed assembly sequences, which follow the principle “from inside to outside”. The main task of the engineer is to plan the assembly process by assigning the technical equipment to the process. The engineer uses descriptions of the equipment to decide, which one suits best the assembly step. Primarily, geometrical, functional and economic information are used to specify the assembly step in detail. Based on this information alternative assembly processes can be assessed and the most appropriated one can be chosen. The approach of planning assembly processes corresponds in most cases to the planning of manufacturing processes.

The PDM system can preserve the energy data links between a part and process chains, if the part is inserted in a standard part library. This will reduce the setup effort for a new product that uses standard parts. Nevertheless, a check is necessary to confirm that the assigned process chain is valid. An interesting new scenario in product development is a prognosis of the energy consumption for manufacturing different product configurations. Alternative parts exist for a node in the product structure. Each part has a data link to a different process chain to evaluate the manufacturing process. By considering energy and cost as well as the manufacturing context, cost-efficient and energysaving parts can be selected for the final product configuration. Use case IV (dimensioning of generic parts): Generic parts are created by defining a geometric parameter instead of setting a fixed value for it. As a result, a number of similar parts are created, which vary only in this parameter. PDM systems can organize these parts in family tables. To complete a product configuration, a value for the geometric parameter has to be chosen. An energy data link of a generic part with a process chain can support product development and manufacturing planning in two ways. The given range for a parameter can set the requirements for the process chain, or the process chain can automatically restrict the parameter based on the calculated process limits. Use case V (Change management of manufacturing processes):

Energy data links between a PDM system and process chain planning can be utilized for a number of scenarios in product development and manufacturing planning. The following use cases focus on the energy usage for manufacturing.

If new or improved manufacturing processes become available, their impact on the manufacturing of existing parts and products can be assessed. To achieve this, the process chains are organized in a version-controlled way. The change of a process chain, e.g. a new or improved process, will result in a new version of a process chain. Existing links between an old version of the process chain and parts can be used to notify design engineers about changes of manufacturing limits that may lead to design changes. As a result, changes become traceable and can be communicated.

Use case I (early manufacturing planning):

Use case VI (Improved material compliance for products):

In the early phases of product development, only preliminary product structures and first CAD drafts are available. Nevertheless, the energy data links can bring some benefit. In this stage, the principal manufacturing steps may already be predetermined. If process chains already exist for a similar product or part, attaching an energy data link is similar to selecting parts from a part library. By attaching pre-defined process chains to parts in the product structure, a manufacturing engineer can define a possible process chain. An advantage of an early data link to possible process chains is that the product can be designed with the manufacturing limits in mind. A validation tool can check whether these limits are still satisfied while the product data is updated in the PDM system. If this is the case, the linked process chain is marked as valid for the part.

Process chain models can include a description of auxiliaries for product processes. Currently, a part description from CAD covers only the actual materials used. Thus, with a data link between part and process chain additional materials and substances for manufacturing can be evaluated. An improved material compliance analysis becomes possible.

4

USE CASES FOR ENERGY DATA LINKS

During the product development, process experts may include additional or alternative process chains as more and more details are added to the product model. This alternative process chains can serve as input for a process chain optimization. Use case II (preliminary energy prognosis for manufacturing): Based on a process chain that is connected to the part and has raw parts attached, the energy data links allow an energy prognosis for

5

SYSTEM IMPLEMENTATION

In this section a data model is proposed which models energysaving process chains with detailed process information using specified workpiece data. Also, the interface functionality necessary for the energy data link to the PDM system is given. 5.1

Data model for process chain and workpiece data

The software tool proposed should be able to model energy-saving process chains and to provide an energy consumption calculation. The implementation of the energy data link is based on a comprehensive manufacturing data repository. The repository stores detailed process information, machine tool data, and workpiece data. In Figure 3, the basic data entities and their properties are displayed. A process chain references workpieces and consists of input/output energy/material flows. A process chain

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consists of entities that describe the processes. To describe the process order, the process chain uses constraints that specify pre-, post- and alternative processes. Additionally, the process chain saves manufacturing parameters, such as lot sizes or time constraints.

Process chain Lot size Optimizing criteria Process order constraints ...

Input and output workpieces for a process chain can be specified by the raw part and the part information from the PDM system. For this purpose, workpiece data including the surface properties and geometrical details are linked with CAD model data that is stored in the PDM system. Detailed material properties for geometry elements of the workpiece or surface coatings can be provided with the same data link, if a material database is integrated with the PDM system.

Process Technology name Energy calculation formulas Time calculation formulas Cost calculation formulas Process attributes Process constraints …

A process entity contains all data to specify a complete manufacturing process. The description is based on formulas specifying the physical, chemical and energy correlations and constraints. For instance, the process data and calculation formulas for the manufacturing process turning, described in [7], use the output workpiece geometry to evaluate the time, energy and costs of a turning process. Furthermore, the process references a specific tool or several tools used for the process. The formulas describing a tool are either related to the process or to the machine that utilizes the tool. It is assumed that the specified machine type used can mount different tools for a particular process. Having defined several machine tool types and tools that are available, it is possible to automatically choose the best tool applicable for a specific manufacturing process. A machine type and its tools used can result in constraints for the workpieces, e.g., they may require specific surface properties or geometric dimensions. Additionally, tools may also put constraints on a machine tool and have to be considered. The energy and material flows of a machine tool or for a process chain are described by the data entity energy/material flow. In a machine tool, this may include the auxiliaries necessary for operation or certain processes. The flows for a process chain describe the energy sources and energy reuse between processes. The energy and material flows use LCA data for energy sources and substances to evaluate costs, sources and composition of the consumed energy and materials. The workpiece dimensions and materials can be used as input data to calculate energy usages during the product life cycle, especially the energy usage for manufacturing a part. The LCA data comes from an external LCA database or an LCA system with metrics for energy and material flow analysis. 5.2

Data exchange and PDM system functionality

The process chain modeler is the graphical modeling tool for the process chains. The engineer enters possible process orders and the given constraints for the manufacturing of a part. The established graphical elements and business workflows can be used. With a process library, a tool library, and a machine library the specific process details are available and editable. For the implementation of the interface between the process chain modeler and a PDM system existing standards for data exchange can be used, such as STEP ISO 10303 [8]. Most PDM systems are able to export geometry data in CAD models of the product via STEP. Beside the geometry, the data exchanged has to include tolerance values, surface constraints (roughness, waviness) and material details/constraints (raw material composition, stresses, strains). For a calculation of the energy usage, the manufacturing parameters for a process chain can be exchanged between PDM system and process chain modeler in both ways. First, the parameters can be set in the process chain modeler. Second, for energy usage calculations during product development, the parameters may be changed through the PDM system. Other data

Workpiece Name Part constraints CAD model …

Surface

Tool Tool attributes Tool process formulas Workpiece constraints Machine constraints …

Machine Machine attributes Machine formulas Workpiece constraints Auxiliaries …

Geometry

Roughness Waviness Coating …

Form/size Tolerances Material …

Material Material name Chemical properties Physical properties Stress properties …

Energy/ material flow Attributes Constraints Input/Ouput …

LCA Substances Energy sources LCA metrics

Figure 3: Data model for process and process chains (white) referencing workpiece data from a PDM system (light gray) and LCA data (dark gray). The filled rhomb arrow means “consists of”, whereas the blank rhomb arrow stands for “references”. exchanged may include CAD model visualizations to be used in the process chain modeler’s user interface. The energy data links can be supported with new PDM system functions to integrate the process chain modeler. The process chain modeling tool stores process chains to manufacture specified workpieces and their constraints with respect to process, tool, and machine type. If an output workpiece is assigned to a process chain, the process chain modeler may perform a check whether the workpiece geometry can be manufactured by the defined processes in the process chain. These constraints can also be used for searching existing process chains. The input, given in the PDM system, is a part and its raw parts. The process chain modeler looks up process chains in the manufacturing data repository, where the constraints are fulfilled to manufacture the part. A similar search can provide constraints for manufacturing techniques (geometry, roughness, waviness, etc.) used to manufacture a part during product development. If a part, its raw parts, and its process chain are defined, the process chain modeler can provide time consumption, summarized energy usage and estimated costs for manufacturing to the PDM system. These results can be visualized in a new PDM screen. The proposed energy data links are one approach to integrate IT systems of product development and manufacturing planning. Other approaches will be discussed in the next section. 6

RELATED WORK

Existing approaches for manufacturing planning either concentrate on the integration of product development with production process planning for single manufacturing steps or address process chain modeling and optimization. An integration of product models with

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energy-saving process chains to optimize energy usage in manufacturing, however, is not part of the concepts. The following section gives an overview on existing work in these different directions. There are a number of extensions made to the product model to integrate manufacturing and product development information. The approach in [9] integrates a commercial process planning tool with the product development process based on a feature-based product model. The user can attach features to a CAD model and manually describes the process chain by assigning processes to the features in the process planning tool. The approach can be utilized to optimize individual processes by evaluating process parameters and proposing alternative processes, but neither sufficiently addresses energy flows nor addresses process chain optimization beyond discrete part manufacturing. The data structure for a PDM system proposed in [10] can be used to enrich CAD data with semantic information for process planning. The approach models the interface from product development to manufacturing and provides a knowledge base for assembly processes. Nevertheless, an explicit modeling of energy in the process models is missing in this approach. Life cycle assessment (LCA) provides the means to analyze the environmental impact of the product including energy usage and product manufacturing. LCA systematically collects material and energy flows for an existing product. The scope of LCA is extended to manufacturing processes by efforts, such as the CO2PE! initiative [11]. A major goal is to catalogue, analyze and document production processes, which allows the creation of LCA models for discrete part manufacturing. These models can be used to assess the environmental impact of manufacturing processes. LCA databases can be utilized in product development to analyze and optimize the manufacturing of a product. In [12] a methodology is described that enhances a virtual reality model for numeric control (NC) programs with LCA data. The approach described in [13] integrates LCA into a PLM concept. The LCA solution is based on a life cycle inventory analysis for the parts and assemblies in the product structure and calculations of environmental parameters for individual production processes. An LCA or energy usage analysis of a complete process chain is not possible with these approaches. Approaches used for process chain modeling and optimization are not integrated with product data models. The methodology for process chain optimization, which is introduced in [14], for example, targets a holistic planning of manufacturing processes. An implementation is based on a process database and simulation models of the manufacturing steps, which are created and extend through the method itself. 7

CONCLUSION

In a PLM concept, product development and manufacturing planning are parallel activities that depend on each other and may have interrelations. The product should be designed with energy consumption for its manufacturing in mind. The process chains should be optimized for energy saving and require access to product data. Especially, if the goal is to reduce the energy usage in the product life cycle, these interactions become important. This article proposes an integration of a PDM system and a process chain modeler that can be used with a minimum data redundancy between product models and process chain models. This approach can be considered to be a first step to a PLM solution that can exchange energy data between product life cycle phases. So far, the approach only considers the manufacturing of parts. To extend the integration concept to the whole product, future work has to cope with assembly processes. This requires a transformation of the product structure into an assembly tree. Based on this

information the resources for manufacturing the product can be planned. Additionally, logistic processes have to be included in the modeling of the manufacturing processes. As a result, the energy usage of assembly processes can be evaluated and optimized for an energy-efficient manufacturing. 8

ACKNOWLEDGEMENT

The Cluster of Excellence “Energy-Efficient Product and Process ® Innovation in Production Engineering” (eniPROD ) is funded by the European Union (European Regional Development Fund) and the Free State of Saxony. 9

REFERENCES

[1]

Heemann, S. VDMA - German Engineering Federation (Ed) (2010): Green Production Technologies, Gabler.

[2]

Kibira, D.; McLean, C. (2008): Modeling and Simulation for Sustainable Manufacturing, in: Proc. of the 2nd IASTED 2008 Africa Conf. on Modeling and Simulation.

[3]

Eigner, M.; Stelzer, R. (2009): Product Lifecycle Management, Springer Berlin Heidelberg.

[4]

Quack, D. (2008): Product-Carbon-Footprint: Der ökologische Fußabdruck von Produkten, Öko-Institut e.V.

[5]

Jacobs, H.; Dürr, H. (2002): Entwurf und Gestaltung von Fertigungsprozessen. Planung und Steuerung der spanenden Teilefertigung, Fachbuchverlag Leipzig.

[6]

Trommer, G. (2001): Methodik zur konstruktionsbegleitenden Generierung und Bewertung alternativer Fertigungsfolgen, Shaker Verlag Aachen.

[7]

Goller, S.; Götze, U.; Helmberg, C.; Krellner, B.; Lau, A.; Rünger, G.; Schubert, A.; Sygulla, R. (2010): Integrating Energy Flows in Modeling Manufacturing Processes and Process Chains of Powertrain Components, in: Proc. of the 1st Int. Coll. of the Cluster of Excellence eniPROD, pp. 409– 437, Chemnitz, Germany.

[8]

STEP Application Handbook ISO 10303 Version 3, SCRA, North Charleston, SC.

[9]

Kunz, A.; Moryson, R. (2003): CAPP basierter Assistent für digitale Fabrik Tools innerhalb des Produktentstehungsprozesses, in: Design for X: Beiträge zum 14. Symposium, pp. 11–24.

[10]

Rueckel, V.; Koch, A.; Feldmann, K.; Meerkamm, H. (2005): Process data management in the whole product creation process, in: Proc. of the 9th Int. Conf. on Computer Supported Cooperative Work in Design, vol. 2, pp. 1029–1033.

[11]

Duflou, J.; Kellens, K. (2010): Unit Process Impact Assessment for Discrete Part Manufacturing: A State of the Art, in: Proc. of the 1st Int. Coll. of the Cluster of Excellence eniPROD, pp. 81–98, Chemnitz, Germany.

[12]

Shao, G.; Kibira, D.; Lyons, K. (2010): A Virtual Machining Model For Sustainability Analysis, in: Proc. of ASME 2010 Int. Design Engineering Technical Conf. & Computers and Information in Engineering Conf.

[13]

Abele, E.; Anderl, R.; Birkhofer, H. (2006): Environmental Product Lifecycle Management-Customizing the Enterprise Specific Manufacturing Processes, in: Proc. of 13th CIRP Int. Conf. on Life Cycle Engineering, pp. 651–656.

[14]

Denkena, B.; Rudzio, H.; Brandes, A. (2006): Methodology for Dimensioning Technological Interfaces of Manufacturing Process Chains, in: CIRP Annals - Manufacturing Technology, Vol. 55, No. 1, pp. 497–500.

Challenges in Data Management in Product Life Cycle Engineering 1

2

3

3

3

Tommaso Fasoli , Sergio Terzi , Erkki Jantunen , Juha Kortelainen , Juha Sääski , Tapio Salonen 1

3

Politecnico di Milano, Department of Management, Economics and Industrial Engineering 2

Università di Bergamo, Department of Industrial Engineering, 3

VTT Technical Research Centre of Finland

Abstract It is expected that the capability of managing the complete product life cycle in its phases will give the necessary boost for European Manufacturing Industry. Many efforts have been put into the creation of product lifecycle management systems, but it would seem that there is a gap between the existing reality and the specification of expected features. The article addresses this subject from critical point of view and tries to pinpoint the weaknesses of the existing solutions such as standards and database solutions. This work also tries to show the possible ways to follow that could help in solving the problems. Keywords: Product Lifecycle Management (PLM); Product Data Management (PDM)

1

INTRODUCTION

Today, companies are forced on constantly come up with innovative products to face with the modern global economy. Work is often organized in a multi-site, multi-project, and multi-cultural environment leading to a situation where enterprises should pay attention to ensure that product data (PD) are correct and flowing fluently between all the stakeholders of the value chain [1]. Product data management (PDM) has become one of the most important considerations for companies, especially in engineering and manufacturing industries. In order to be competitive, companies require a common presentation of PD that is electronically transferable over organisations [2]. This is yet to be fully realised [3]. This article studies the different standards used in PDM systems and discusses the actual weakness of Data Management in PLM systems. This includes a gap analysis between the existing reality and the expected features in Data Management. This work tries also to clarify the evolving direction of product lifecycle management (PLM) in relation to the problem of data management. The article provides a report on the PLM software available on the market and how they cover the lifecycle phases. The analysis will help to highlight the problem of data flow along the product life-cycle.

2 2.1

DATA MANAGEMENT ENGINEERING

IN

PRODUCT

LIFECYCLE

Product data management

Management of product data has become a challenging task for manufacturing companies that need to simultaneously design and re-design their products in a shorter time while trying to respond to changing market needs, environmental concerns, and to improve the reliability of their products and services [4] [5]. Product development process requires improved solutions for handling PD in order to better support collaborative engineering and management

of product development projects, product structures, documents, and quality [4]. In order to develop product design, feedback from the field is required [6]. PD is created and utilised in different business functions with different ways [7] and PD are referred to as “information broadly related to a product” [2]. Thus, the term PD is often used interchangeably with the term product information. In addition, the term information system, which covers business related topics, is often used interchangeably with data systems that address the operational problems. PD can be divided into product definition, product lifecycle data and metadata [2]. Product definition and lifecycle data can furthermore be classified into static and dynamic data. It can be said that PDM involves managing the static PD, specifications such as bill of materials, and operational instructions while PLM covers also the dynamic PD which occurs during distribution, usage, and end-of-life [4]. 2.2

Product lifecycle management

Over the last few years PLM has become a central approach for the integrated management of product related data, engineering processes, and applications along the different phases of the product lifecycle. Although the information technology (IT) tools are important enablers for PLM, the PLM approach is much more than just a piece of software. PLM is an integrated approach including a consistent set of methods, models, and IT tools for managing product information, engineering processes, and applications along the different phases of the product lifecycle. PLM addresses not only one company but a globally distributed, interdisciplinary collaboration between producers, suppliers, partners, and customers [3]. The core of the PLM approach is an integrated data and process meta model managed by a database management system and a central controlled data vault for the storage of all created models and documents (e.g. CAD models, text documents) as shown in Figure 1.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_91, © Springer-Verlag Berlin Heidelberg 2011

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Figure 1: PLM approach [3]. Available PLM methods and tools can be clustered into three groups [1]:

releasing and changing processes as well as in the strong integration of CAD and ERP systems and data.



Information management (e.g. methods for identifying, structuring, classifying, modelling, retrieving, sharing, disseminating, visualizing, and archiving product, process and project related data).

The main gaps of the available PLM solutions are the scarce support of product lifecycle tasks outside product development, system engineering activities, and integrating mechanic, electronic, and software components.



Process management (e.g. methods for modelling, structuring, planning, operating, and controlling formal or semi-formal processes like engineering release, review, change or notification processes). The strong link between the different process stages and the resulted product models are covered by socalled configuration management methods and tools.

Another weakness in current PLM solutions is the very high customizing efforts required. Although big efforts have been put into the research of general industry standards for PLM meta-data models and PLM processes, they are still missing.



Application integration (e.g. methods for defining and managing interfaces between PLM and different authoring applications like Computer-aided design (CAD), Computer-aided Manufacturing (CAM), Computer-aided engineering (CAE) and integrated enterprise software such as ERP, SCM or CRM systems).

The PLM solution providers today on the market belong to one of the following four groups [3]: 

Enterprise resource planning (ERP)/supply chain management (SCM) tool providers.



Computer-aided technologies (CAx) and engineering software providers.



Independent PDM or web-based collaboration tool providers.



Independent integrators and service providers.

The focus of all existing commercial solutions for PLM is on support of product development activities. Usually the available solutions have pre-configured data models, processes, and functions, which are partially aligned to specific sectors [3]. The strengths of available PLM solutions are in managing CAD models and documents,

2.3

Product lifecycle management evolving directions

CIMdata’s most recent poll [8] asked participants to indicate where they expected to receive the most value from PLM. The main results of the poll show that design engineering (34% of responses) was the first adopter of PLM and has the most deployed and mature use of PLM solutions. PLM solution suppliers have provided tailored applications for design engineering departments in many industries and these can provide significant benefits to those organizations. System engineering and requirements management (21% of responses) was rated the second. This reflects the need to consider the entire product (e.g. mechanical, electronic, and software) as a whole unit. Requirements management reflects the need to understand the “voice of the customer” and track those requirements to the product design decisions. Enterprise Simulation Management (20% of responses) is becoming an area that can deliver major, sustained benefit. Using PLM to manage simulation and analysis more effectively is an area that more companies will focus on in the future to complement the management of the design information. Digital manufacturing (16% of responses) is also growing in importance. As digital manufacturing solutions become more widely available, the ability to more effectively bridge design engineering and manufacturing should produce quantifiable benefits for companies.

Commercial PLM software solutions

Lifecycle processes N Y N Y Y Y Y P Y Y Y Y N Y Y N P N N N N N N N Y N N N Y N Y N P N Y N N N N N Supporting processes Community Collaboration Y P Risk Management Y N Product Governance & Compliance Y N Project Management Y P Knowledge Management Y P Quality Management Y Y Document Management Y P

There are four players comprising the major part of the market and these are Siemens, Dassault Systemes, (PTC), and SAP [9]. The vendor count for CIMdata's PLM surveys now exceeds 300 companies, but at the same time big players may consolidate and also the total number of PLM technology providers may grow [9]. However, it may be claimed that these forecasts give an idea of the direction of change. 3.2

Product planning Design Engineering Bill of Materials Manufacturing Assembly Testing Marketing Packing Storage Transportation Unpacking Site Assembly Adjustment Site testing Operation/Use Service Maintenance Recycling Disposal

Lifecycle Phases covered by PLM software solutions

Table 1 presents an assessment of the PLM support throughout the life cycle stages of the vendors mentioned above. The analysing method is qualitative and refers to the features of selected PLM systems according to the information found in the vendor’s web sites, listed in Table 2. If any of the PLM systems covers a product lifecycle phase it is given a “Yes = Y” in Table 1 and if a lifecycle phase is not covered then “No = N” is shown in the table. This is to say that these detailed requirements are generally covered by these PLM systems and it does not mean that a commercial PLM system does have all the “Yes” and “No” answers. “Partly = P” indicates that the phase is not covered completely or is not a core functionality of the software. The last column indicates whether at least one set of software covers the phase shown on the specific line. The last column of Table 1 shows the lifecycle phases that are not covered today by any of the selected software. While the middle of life of the product and especially the end of life are still lacking of ad hoc PLM applications, the main supporting processes are well cover by the existing solutions. 3.3

Open source PLM software solutions

Supported by PLM software

3.1

SAP

The aim of this paragraph is to cover the solutions that are on the frontier of the current state of the art. Also, a brief analysis of the positioning of free software packages is provided.

PTC

THE CHALLENGE OF PRODUCT LIFECYCLE SOLUTIONS Siemens

3

527 Dassault Systemes

Information and Knowledge Management

Y Y Y N Y Y Y Y N N N N N N N N N N N N

Y N Y Y Y N N Y N N N N N N N N N N N N

Yes Yes Yes Yes Yes Yes Yes Yes Par No No No Yes No Yes Yes Yes Yes No No

Y N Y Y Y Y Y

Y Y Y Y Y Y Y

Yes Yes Yes Yes Yes Yes Yes

Table 1: Life-Cycle Stages covered by PLM software solutions.

In the market for PLM software there are also some open source solutions. The fragmented distribution of a sample of 48 freeware solutions selected from http://www.plant-maintenance.com/ is shown in Figure 2. These products are often able to handle only very specific stages of the product lifecycle. In fact, the development of integrated solutions is even more difficult in this environment.

PLM vendor Siemens Dassault Systemes PTC SAP

Web address http://www.plm.automation.siemens.com http://www.3ds.com http://www.ptc.com http://www.sap.com

Table 2: PLM vendor WEB addresses.

The number of PLM open source initiatives that have achieved even a limited distribution is rather limited: the Aras Innovator, Convelo Rapid Transform, and IPLM of ImpactPLM.





Convelo is distributed under MPL (Mozilla Public License), built in Java and using other open source platforms (Spring Framework, Hibernate) [11].



IPLM uses a 'stack' based on open source code (database and application server) and makes available the source code, but does not provide a free use of it [12].

Aras in January 2007 transformed its conventional business model of selling licenses into an open licensing model [10].

Finally, Arena Solutions offers a commercial product, ArenaPLM, but in SaaS mode and based on open platform (Red Hat, Websphere CE, Nagios, Snort) [13]. 4 4.1

Figure 2: Areas covered by freeware software packages.

   

TECHNICAL SOLUTIONS AND PROBLEMS RELATED TO DATA EXCHANGE The gap between the existing reality and the expected features in Data Management

The need for easy, quick, and secure access to valid data was accomplished by the introduction of PDM in 1980s [14]. The purpose of PDM was to control and manage product information created by the information authoring tools. PDM provided the users with their required data through a single data repository. PDM also maintain the validity and integrity of data by continual data updating as well as controlling the way people created and modified the data.

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At this time PDM was considered to be effective within the engineering perspective, for example PDM solutions expanded to change management, documentation, work flow management, and project management, which resulted in enabling concurrent engineering and streamlining business processes within the enterprises. However, PDM failed to show its further expansion in functional areas such as sales, marketing, finance, and supply chain management. This was because PDM was difficult to use and also limited to the engineering scope as it was designed to support and supplement computer aided design, manufacturing, and engineering (CAD/CAM/CAE). PDM software focuses primarily on engineering tasks, specifically the design release and change cycle and doesn't offer a complete data view over the entire product life cycle. Since PDM software is often acquired to manage technical design data, PDM software frequently makes assumptions that limit its wider application. PDM software is generally weak in accommodating non-technical documents (such as marketing requirements) and physical item records (such as sales brochures) or post-sales documentation and spares inventory affecting product support, service, and disposal. Because PDM software often assumes that the users are engineers, even simple capabilities can be too "technical" [2]. For example, item search in PDM software often requires an understanding of how item attributes are stored and indexed in the PDM database as well as Boolean logic syntax – certainly not a benefit to the average marketing manager or purchasing agent. The above issue was further resolved by the introduction of PLM in the late 90s [2]. PLM aimed to move beyond engineering aspects of products and provided a shared platform for creation, organization and dissemination of product related knowledge across the extended enterprise and from “the cradle to the grave”. CIMdata considers PLM as a business approach for solving the problems of managing the complete set of product information from its creation, management, dissemination, and use of product [8]. Furthermore, PLM is also defined as an organized concept for the integrated management of all product related information and processes through the entire lifecycle, from the initial idea to the end of life. The questions related to time-to-market, cost, and quality standards describe the methodology of PLM by linking it with different product development stages. From these concept definitions, PLM seems to represent a strong approach to improving a company’s strategic and operational excellence. However, due to dependency of strategic and operational excellence on company specific conditions, overall PLM solutions cannot exist. It is further recommended that PLM needs to be aligned to boundary conditions and must support the company’s strategies [15]. 4.2

[17]. An example of this is the Java language. Although its use is widespread today, the fact that one company has great control over Java’s development process defines it as an industry standard, not as an open standard. The third type of standards is de facto standard. They are "in use today because of their value or association with other technologies and not necessarily because they were produced by a standard organization” [17]. Therefore, it cannot be the best option for a company to choose when interoperability between PLM systems’ vendors is of the greatest importance for them. As mentioned above, although these three types of standards are nowadays being implemented to facilitate the exchange of data, the different types of standards described above create differences between suppliers and customers that obviously cause them to disagree about which standard should be used in the development of their software. However, the PLM software vendors usually want to make their products in line with the de facto standard, because this allows them to control the content and the price of their products [17]. This conflict adds to the difficulty in providing really interoperable systems despite similarity in PLM suppliers. Today there is a large amount of standards that companies are using, as shown in Figure 3. The map in Figure 3 shows that different types of standards are needed at different stages of the product’s lifecycle. The standards have been classified based on the work of Terzi [18] and according to their position among the lifecycle and content: product, process or enterprise service. It is clear from the Figure 3 that there is no standard that provides full coverage of the PLM support spectrum. Also, note that standards such as System Modelling Language (SysML) and Process Specification Language (PSL) cover aspects of PLM with notable discontinuities in scope. The ISO 10303 is the most widely accepted open standard for the exchange of product model data for PLM. It was developed by the International Standards Organization (ISO) and is known as STEP. A major advantage of STEP is that it is possible to develop standards for exchange of data between different domains in the product lifecycle. STEP is the most used because of its well-defined standard content models, but its implementation requires plenty of time. Product life cycle support (PLCS) is part of ISO STEP standard family (ISO 10303-239). It enables the creation and management of an assured set of product and support information (APSI) through time, which can be used to specify and control required support activities throughout a complex product life [18].

Existing solutions such as standards and database solutions and their weaknesses

There are three different categories of standards that are currently in use [16]. These are explained in detail below. The first one is known as an open standard, which refers to “an agreement that people make it so that products and systems made by different parties can work together” [17]. It’s important to note that open standards are nothing more than the specifications that describe how information should be formatted and presented. They were developed by standards organizations ranging from small industrial groups to large, official international bodies. Some examples of open standards in PLM are ISO 10303 known as STEP (Standard for Exchange of Product Model Data), XML, and UML. The second category of standards is industry standards. These standards are "technologies that are commonly used, but are not necessarily open and democratically managed by a group of users"

   

Figure 3: Map of interoperability standards in the product lifecycle.

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Figure 4: Service Oriented Architecture [21]. Machinery Information Management Open System Alliance (MIMOSA) has since the middle of the 1990’s hosted open conventions for information exchange between plant and machinery information systems, i.e. a way to enhance, amongst other things, the compatibility issue between different vendor products. Furthermore MIMOSA's open standards were able to enable collaborative asset lifecycle management in both commercial and military applications. Extensible markup language (XML) and Unified modelling language (UML) are two modelling languages currently in use and, for example, XML can be used for serializing STEP data; this is defined in STEP-XML (ISO 10303-28). Another example is the open archival information system (OAIS) reference model which facilitates a much wider understanding of what is required to preserve and access information for long term [18]. These new open standards are important because they provide rich environments of standardized syntax [17] to capture all the semantics needed in PLM, such as billing, creating forms, describing design geometry, and other business functions [16]. SysML is currently under development to be able to manage systems engineering information from the basis of actual standards [17]. However, although these last types of systems can be deployed by customers on a much faster scale than ISO, sometimes the lack of detail in coordination can hinder the development of necessary standards. The only development that has allowed each of the above systems to really work for their customers is the integration of the Internet into PLM systems and the development of service-oriented architecture (SOA). This feature allows companies to be able to access other companies’ product data at any time and from anywhere. A well-designed SOA should use a native XML database-powered metadata repository and data orchestration engine at its core, as shown in Figure 4. A full-featured SOA repository is the core component of a well-designed service-oriented architecture. A SOA repository natively embeds data administration and governance services. It provides a comprehensive dictionary with semantic reconciliation

capabilities and it allows the organization of data and services into meaningful taxonomies as well as provides lifecycle management and versioning services. 4.3

Semantic Web Technologies and Ontologies

In this context is also important to consider the potentiality of semantic interoperability. Semantic interoperability is the ability of two or more computer systems to exchange information and have the meaning of that information accurately and automatically interpreted by the receiving system [18]. It implies the existence of a common and shared understanding of the meaning underlying the exchanged information. To achieve perfect semantic interoperability, all communicating systems must use symbols and definitions that are identical or can be accurately translated. Then a common ontology is the ideal solution for semantic interoperability [18]. The growth of the World Wide Web (WWW) and the expansion of the data available through the Internet have raised a new challenge: how to distil the requested information out of the data mass. To overcome the challenges of the future, the World Wide Web Consortium (W3C) has started the development of the next generation Web, the Semantic Web. The emphasis in this development is to increase the utilization of the content of the Web by including information about the meaning of the data, i.e. the semantics of the data, together with the data itself. This enables e.g. software agent based search, interpretation, and utilization of the data. The development of the Semantic Web has already provided several core technologies that together form the basis for the Semantic Web. The technologies are versatile enough to be utilized also in other application areas. The basis for the Semantic Web is the resource description framework (RDF), which defines the basic concepts, such as a data triple [22]. This fundamental data model is simple but versatile, and enables different kind of data to be represented. Resource description framework schema (RDF-S) adds features, such as vocabularies to describe properties and semantic classes [23]. RDF and RDF-S together form the foundation for the Web

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Ontology Language (OWL) [24]. The layered and extensible architecture of these technologies form a solid and versatile framework for knowledge representation in computer interpretable form.

[5]

Trappey A.J.C., Taghaboni-Dutta F., Trappey C.V. (2008): A framework for a green product lifecycle management system, in: Information Systems, Vol. 9, No. 2, pp. 123-131.

One of the challenges in application of semantic data model and the Semantic Web technologies is that there are not many industrial strength solutions available, either for end users or for software developers. This is due to the fact that these technologies are relatively new and are still developing. From software development point of view, one challenge is the performance of semantic database systems. Semantic applications are known to be resource intensive, i.e. to manage the same amount of data in semantic form usually requires more computational effort than managing the same data in e.g. relational database systems.

[6]

Jun H.-B., Kiritsis D., Xirouchakis P. (2007): Research issues on closed-loop PLM, in: Computers in Industry, Vol. 58, No. 8-9, pp. 855-68.

[7]

R. Sudarsan, S.J. Fenves, R.D. Sriram, F. Wang (2005): A product information modeling framework for product lifecycle management, in Computer-Aided Design, Vol. 37, No. 13, pp. 1399-411.

[8]

CIMdata, Christine Bennett (2009): PLM Industry summary, Vol. 11, No. 50, pp. 2-4.

Brunner [19] explored the use of Semantic Web technologies for product information management and affirmed that suchlike technologies can be used for customer data integration. They pursed the use of ontology for expressive product information management (PIM) representation and built a PIM prototype on top of one of the state-of-art ontology repositories. His work shows the value of using the OWL and in particular how to use the OWL in order to make more efficient the product information model.

[9]

AMR Research, Jeff Hojlo, Marianne D’Aquila, Karen Carter (2007): Releases Enterprise Applications Market Sizing Reports, in Product Innovation and PLM, pp. 1-14.

[10]

Aras, Available: www.aras.com, Last accessed 12/11/2010.

[11]

Swik: Convelo, Available: http://swik.net/Convelo, Last accessed 12/11/2010.

[12]

IPLM, Available: http://www.impactplm.com, Last accessed 12/11/2010.

5

[13]

ArenaPLM, Available: http://www.arenasolutions.com/, Last accessed 12/11/2010.

[14]

Ameri F., Dutta D. (2008): Product Lifecycle: Management: closing the knowledge loops, in Computer-Aided Design & Applications, Vol. 2, No. 5, pp. 577-590.

[15]

Schuh G., Rozenfeld H., Assmus D., Zancul E. (2007): Process oriented framework to support PLM implementation, in: Computers in Industry, Vol. 59, No. 2-3, pp. 210-218.

[16]

Duran F. (2007): Interoperability and Standardization Between PLM Systems in: Computer Applications

[17]

Srinivasan V. (2006): Open Standards for Product Lifecycle Management, in International Conference on Product Lifecycle Management

[18]

Terzi S., Bouras A., Dutta D., Garetti M., Kiritsis D. (2010): Product lifecycle management – from its history to its new role, in Int. J. Product Lifecycle Management, Vol. 4, No. 4, pp.360-89.

[19]

Brunner J., Ma L., Wang C., Zhang L., Wolfson D., PanY, Srinivas K. (2007): Explorations in the Use of Semantic Web Technologies for Product Information Management, in WWW 2007, pp.747-756.

[20]

Terzi S., Garetti M. (2005): Organisational change and knowledge management, in Int. J. Product Lifecycle Management, Vol. 1, No. 1, pp.43-51.

[21]

SOA for the real world. Available: http://www.javaworld.com, Last accessed 10/11/2010.

[22]

Manola, F., Miller, E. RDF Primer. The World Wide Web Consortium, 2004. http://www.w3.org/TR/2004/REC-rdfprimer-20040210/ (Cited November 15, 2010).

[23]

Brickley, D., Guha, R. RDF Vocabulary Description Language 1.0: RDF Schema The World Wide Web Consortium, 2004. http://www.w3.org/TR/2004/REC-rdf-schema-20040210/ (Cited November 15, 2010).

[24]

Hitzler, P.; Krötzsch, M.; Parsia, B.; Patel-Schneider, P., Rudolph, S. OWL 2 Web Ontology Language Primer The World Wide Web Consortium, 2009. http://www.w3. org/TR/2009/REC-owl2-primer-20091027/ (Cited November 15, 2010).

SUMMARY

PDM/PLM technologies are still seen immature and not adequately supporting all the required functionalities. Regardless of PDM and PLM covering to the entire PLC, data management is focused towards the management of product development and design data. The methods used to collect PD from middle and end stages of life are still incomplete. Furthermore, in practice the relevant feedback information from the field cannot be properly obtained and used for later versions of the product. Standard definition of product related data is then a key for integrating assets in a value-chain and for making application integration possible and more functional. The purpose of this study was to obtain understanding over current PD management practices, together with related challenges. PDM is a topical, increasingly important research area. This article was not intended to be all-inclusive, but rather to highlight the weaknesses of these systems and to obtain potential development ideas. A wider set of interviews to the stakeholders of these processes might provide a widened and possibly somewhat different view to the obtained one. 6

ACKNOWLEDGMENTS

The authors gratefully acknowledge the support from the research project “Computational models in product life cycle – Codes” funded by the Finnish Funding Agency for Technology and Innovation, Tekes, and the following companies Fortum Oyj, Nokia Oyj, and Wärtsilä Oyj. 7

REFERENCES

[1]

Giménez D.M., Vegetti, M., Leone, H.P., Henning G. (2008): Product Ontology: defining product-related concepts for logistics planning activities, in: Computers in Industry, Vol. 59 Nos 2/3, pp. 232-40.

[2]

Saaksvuori, A. and Immonen, A. (2004), Product Lifecycle Management, Springer, New York, NY.

[3]

Abramovici M. (2007): Future trends in product lifecycle management (PLM), in: The Future of Product Development, Springer, pp. 665-67.

[4]

   

Yang X., Moore P.R., Wong C.-B., Pu J.-S., Chong S.K. (2007): Product lifecycle information acquisition and management for consumer products, in: Industrial Management & Data Systems, Vol. 107, No. 7, pp. 936-53.

Business Game for Total Life Cycle Management 1

2

2

2

1

1

Stefan Böhme , Tim Heinemann , Christoph Herrmann , Mark Mennenga , Rolf Nohr , Julius Othmer 1 2

Braunschweig University of Art (HBK), Institute of Media Research, Germany

Technische Universität Braunschweig, Institute of Machine Tools and Production Technology, Product- and Life-CycleManagement Research Group, Germany All Authors are listed in alphabetical order.

Abstract Life Cycle Management (LCM) has established as research area to foster sustainability in all fields of action of organizations. To provide an understanding for this broad research area suitable teaching methods are required. This paper presents the concept for a business game based on the Framework for Total Life Cycle Management (TLCM). It enables participators to understand the interdependencies of four different management disciplines: product, production, after sales and end-of-life management. The educational objective is to continuously develop a holistic life cycle strategy. The game requires communication of all actors and reasonable activities towards sustainability. By that prospective managers can understand relationships and interdependencies of TLCM. Keywords: Total Life Cycle Management; Business Game; Higher Education

1

INTRODUCTION

The striving towards sustainable development through entrepreneurial activities in companies presupposes the knowledge and understanding of the theory of corresponding methods and concepts and also about their practical application in real business environments. By the proclamation of the United Nations Decade of Education for a Sustainable Development (ESD) it has been accepted that sustainability and the underlying principles, methods and concepts have to be anchored in educational systems. Essential new skills to ESD are envisioning, critical thinking and reflection, systemic thinking, dialogue and negotiation, collaboration and building of partnerships [1]. From these activities universities can deduce the mission to develop new teaching methods in order to qualify their students and to be prepared for the development of sustainable business models when entering their individual work environments. Therefore engineering and management students have to enrich their competencies with interdisciplinary views on all disciplines that are represented by Life Cycle Engineering (LCE) and Life Cycle Management (LCM). This enables prospective managers to be aware about the impact of their decisions along the entire life cycle regarding all dimensions of sustainability (social, ecological, economic) and to understand the complex interdependencies between products, business processes and the companies’ environment.

2

TOTAL LIFE CYCLE MANAGEMENT

The framework for TLCM as it has been introduced by Herrmann [3] is based on the Viable System Model [4] and the St. Galler ‘concept of integrated management’ [5] [6]. TLCM provides a life cycle phase comprehending point of view on products and the corresponding processes [7] [8] [9] (see Figure 1). In the centre of the framework are the life cycle phases of a physical product – from product idea and development via production, distribution, usage and redistribution to disposal. Start of the entrepreneurial acting is the statement of a sustainable development as a super-ordinate philosophy. The statement has to be part of the normative management and has to be transformed into the strategic and operational management. Thereby, the normative and strategic management have a rather forming function with regard to the development of the company [10]. The fields of action are classified into structures, activities and behavior. Activities in the individual product life cycle phases lead to the output of the company. The activities take place according to the organizational structures and the behavior of management and employees. These fields of action are part of all sectors of the concentric management rings.

Education of students in this broad topic often lacks of teaching methods that make LCM perceptible. Business games have proved to be suitable for the teaching of complex and abstract topics but there is no business game yet for the education of students in the field of LCM. As an extension of the application range of business games this paper introduces the concept for a business game that is based on the Framework for Total Life Cycle Management (TLCM) [2] and addresses the implementation of TLCM in the academic education of future engineers and managers. Figure 1: Framework for Total Life Cycle Management [8][9].

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_92, © Springer-Verlag Berlin Heidelberg 2011

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In addition to management fields of action, the TLCM framework is divided into different LCM disciplines. These are classified in life cycle spanning disciplines (process management, information- and knowledge management, social life cycle evaluation, economic life cycle evaluation, ecological life cycle evaluation) and life cycle phase related disciplines (product management, production management, after-sales management, end-of-life management). The disciplines aim at a life cycle oriented design of products and processes and are based on the organization structures and the behavior of involved actors [8]. 3 3.1

EXPERIENCING TLCM THROUGH A BUSINESS GAME Overview

Education based on a broad framework like TLCM asks for adequate teaching methods. Otherwise students will not be able to develop useable competencies and merely accumulate factual knowledge. As TLCM relies on a deep understanding of the underlying principles as well as on practical skills in teamwork, interlinked thinking and decision-making, teaching methods are required which close this gap between knowledge (the university) and action (the professions) [11]. A common response to this problem are internships and work placements. While these certainly are good opportunities to get hands-on experience, a business game is much easier to integrate within the normal term and class schedule. Business Games – also called Management Games, Executive Games, Management Decision Games or Business Simulations – are therefore widely-used in higher education [12] [13]. The number of business games has grown rapidly: from war games, like Hellwig’s game from 1780, to the first known use of a business game in a university course, 1957 at the University of Washington (the Top Management Decision Game) till today. In 1968 already 30,000 business executives and countless students in the US had participated in business games [14]. Starting in the 1960s, business games also found their way to Germany. The German Survey of Management Games from 1985 named 200 business games being used in German-speaking countries [15]. Nowadays, business games have become a major educational tool for use in business education [14]. In 2000 one third of all German chairs for economics, for example, had used business games additionally to or instead of lectures [12]. 3.2

Character of business games

Basically a business game is a model which reproduces parts of specific economic, political or social systems, and offers a simplified access to the complex correlations in these systems. Models in business games are based on closed loops and are therefore part of the cybernetic approach of economics [12]. Through a system of rules and interfaces the participants have possibilities of interacting with the model and thereby determining the outcome of the game. As the consequences of their actions are limited to the context of the game the participants can experiment with new strategies and rather difficult decisions. By reflecting the result of their decisions they form a personal model about the internal model of the game. The players experience the responsibility for their decisions and make an assumption about the facts and relations of the system [17]. Thus, not only is knowledge transformed into action but new knowledge is generated, as well. This two-way connection of knowledge, action and feedback leads to experience [11] as well as decision-making and responsibility [13]. Business games come in all shapes and sizes and there are various systems to classify them. Table 1 shows a common listing of characteristics applied to the Business Game for TLCM.

Characteristic

Business Game for TLCM

Operative coverage

Specific

Complexity

Middle

Regulation of complexity

Fixed

Degree of freedom

Fixed

Determination

Deterministic

Data processing

Computer-assisted

Degree of specialization

Trade-specific

Detail level

Specific

Form of organization

Teams

Relationship of players

Competitive, interactive, open

Number of languages

Monolingual (German)

Interfaces

None

Access method

Local

Table 1: Classification of business games by Fischer [13]. 3.3

Design of business games

Although a vast number of business games have been developed in the past fifty years, hardly any game design guidelines have been published so far. At the moment no general formula for designing business games exists. However, the knowledge about fundamental game structure has turned out to be a practicable guideline to find a remedy for this situation. A detailed description of all elements of game and play would go beyond the scope of this paper. Nonetheless, to provide a better insight into the Business Game for TLCM some basic game ideas and elements will be represented. The overall aim of design in case of business games is to create a learning environment which stimulates cooperation and communication and offers the capability to achieve useable skills [18]. The player’s experience and learning progress cannot be determined directly, but are indirect results of the game structure [19]. This structure is influenced by the following key aspects: The magic circle Playing a game means to step deliberately over a border. This border circumscribes a space with special rules and meanings [20]. Accepting this limitation is the mayor prerequisite for gameplay. Complexity The combination of different game elements produces different degrees of complexity. From a certain level of complexity games become so-called emergent systems. At this point they can generate unpredictable elements which enlarge the range of options [21]. Representation Games could be considered as simulations. From this point of view they are complex and dynamic systems that compose representation about some selected parts of reality. In this context representation is not a static fact but the outcome of the act of playing. This points to a very important fact of business games: The gap between the game and reality [21][22]. Game elements Beside these fundamental ideas some more specific game elements exist on which game design has to focus: Information economy, uncertainty and conflicts. Information economy manages which information is hidden or revealed. Information can be classified in several categories: known to all players, known to just one player/team or known to the game direction only. How much information is viewable affects the play behavior significantly. As games of much viewable information incline to be more strategic and analytical, games with imperfect information incline to fuel mistrust and risk-taking [21].

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Another key element of a game is uncertainty. Uncertainty defines the relationship between a player’s action and the reaction of the game. The scale for uncertainty ranges from completely uncertain over risky to certain outcome. Without uncertainty a game is complete foreseeable and mostly unplayable, with less uncertainty a game could become dry and boring, while too much uncertainty could result in a “feeling of randomness” [21][23]. A further relevant part of every game is the aim to reach the final goal. Thereby a conflict accrues directly from the rules of a game. The major conflict in a game is fundamental to keep up the gameplay and to prevent the magic circle from collapsing back upon itself. ”Changing existing (dysfunctional) situations into preferred ones” [18] represents the final goal in most business games. Beside the main conflict many different conflicts on different levels exist. Their principal task is to frame the possibilities available to the players. Implementing and balancing these game elements has to be done step by step in detailed test series, as they mark important issues for game design. 4

BUSINESS GAME FOR TOTAL LIFE CYCLE MANAGEMENT

The business game for TLCM has been developed in joint cooperation of the Institute of Machine Tools and Production Technology of the Technische Universität Braunschweig and the Institute of Media Research of the Braunschweig University of Art (HBK). It has already been applied within the lecture “Product- and Life-CycleManagement (PLM) at the Technische Universität Braunschweig. 4.1

Idea and general concept

The educational objective of the business game is to continuously develop a holistic life cycle strategy for a company which comprises of different departments. The game requires communication of all actors and reasonable activities towards sustainability. In this way game participants are able to understand the relationships and interdependencies that result from holistic decision-making. The game has been developed on the example of an automotive company. Within the business game every game participant is part of one company and responsible for its strategic orientation. His or her operations determine if the company is popular, profitable and environmental friendly and to what extent these goals are achieved. Thereby different companies compete against each other. Within each company four departments exist to which at least two game participants are assigned. These departments refer to the life cycle phase related disciplines of TLCM, namely product management, production management, after-sales management and endof-life management. Beside the four company departments that are individually supervised by the game participants, further facilities exist. These facilities are coordinated by the game directors and can be utilized by all participants. The departments of the game direction are the research center, the personnel service center, the controlling and external consulting. 4.2

Figure 2: Strategy card, left: front side, right: back side. A main object of the business game is strategy cards. Implementing, that means playing, a strategy card influences the strategic orientation of the company. Thereby each company department can develop and implement its own strategies. For example, the product management can develop and implement the strategy ‘electric vehicle’ whereas the after sales management can develop and implement the strategy ‘maintenance of batteries’. An example of a strategy card is displayed in Figure 2. The front side on the left contains a short description, advantages and disadvantages as well as impacts of the strategy. The impacts refer to economic, ecological as well as customer oriented consequences that result from the successful implementation of the strategy. The back side on the right includes information regarding required experts and preconditions within the company department. This means that a successful implemented strategy can be a precondition for the successful implementation of another strategy. Resources to develop and implement the strategy are listed at the top of the card. The values of evaluation criteria as well as of the costs and required personnel for strategy cards arose from estimations of experts and have been balanced by comparing different strategy cards in detailed test series. At the beginning not all information is available. Rather each game participant has access to an overview of strategy cards that are available within his department. The overview involves only the properties like name, short description, strategy level which refers to the complexity of a strategy, advantages and disadvantages as well as costs for the development and the required personnel that are needed for the implementation of a strategy. Thus, valuable information regarding possible preconditions of a strategy as well as the economic, ecological or customer oriented consequences of a successful implemented strategy, is not given at the beginning. In addition to strategy cards two kinds of personnel cards are relevant within the business game. Whereas the resource ‘personnel’ refers to the numerical value of personnel required to implement a strategy within a company, personnel cards stand for specifically skilled staff. They are divided into two different categories: 

Experts: Experts are required to implement strategies that are connected with a technically challenging background. For example, the expert ‘information scientist’ is required to implement the product management strategy ‘enhancement of telematics’.



Managers: Whereas experts are needed in order to head for a certain strategic direction of the company, managers are named characters, e.g. Tina (see Figure 3). They are not preconditions of a certain strategy but enable management activities, such as conducting a life cycle assessment analysis of different strategies. Thus, managers allow for implementing a life cycle oriented culture within a company.

Game materials

To enable different kinds of operations of game participants two different resources exist: 

Company funds are required to develop new company strategies, hire new personnel or develop the infrastructure of the company.

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Personnel are needed in order to implement developed strategies within the company department of game participants.

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Dr.-Ing. Tina Life Cycle Assessment Level 1 Effect: Enable a consultancy regarding environmental impact of a level 1 strategy Requirements: None

Group work phase

Management meeting

 only intra-departmental debating  develop and implement strategies  withdraw strategies  hire and implement managers and experts  do research  ask for external consulting

 inter-departmental debating  exchange of resources between departments  documentation of strategy changes

Figure 3: Example of a manager card.

Table 2: Operations in the business game for TLCM.

Each company department is located at a separated table with an independent playing field illustrating the department from a bird's eye view. The playing field is divided into seven different areas that are used to put on strategy, manager and expert cards as well as tokens representing the resources. The playing field is shown in Figure 4.

Allowed operations during the group work phase and the management meeting are summarized in Table 2. The total playing time of the business game is determined by the game directors depending on the success and experiences of game participants. Normally the game endures between seven and eight hours including set-up and dismantling. 4.4

Evaluation of game play and success

The success of game play is measured using four evaluation criteria: eco-efficiency, business profit, customer attractiveness and degree of linkage within a company. The first three categories are calculated by adding up each economic, ecological as well as customer oriented consequences resulting from the successful implementation of a single strategy. The degree of linkage within a company refers to the quota of implemented strategies and successful implemented strategies within one company. During the game play game participants are informed about their actual score within the four evaluation criteria. Figure 5 shows the screen that is displayed.

Figure 4: Playing field. 4.3

Course of the game

At the beginning of the game every game participant is introduced to the game scenario. It describes the surrounding conditions of the company and comprises the main task of the game participants, i.e. to develop a business model for establishing a new car brand in the automotive market. Thereby three critical success factors are told to be measured: eco-efficiency, business profit and customer attractiveness. After this each company helds a seperate management meeting wherein all company members from the four company departments determine a common strategy. It relies on the given scenario and the information regarding available strategies and their consequences coming from the overview of strategy cards. The determined strategy needs to be documented and should contain the general strategic direction and a prioritization of goals.

Within the prototype the values of evaluation criteria in each company are calculated using Microsoft Excel. Figure 6 shows a part of the preconditions matrix that has been set up in order to determine the evaluation criteria. The matrix contains all available strategy and personnel cards. The matrix is to be read as follows: the successful implementation of a strategy in row 2 is a precondition for the successful implementation of a strategy in column C if the corresponding value is one. For example, the after sales management strategy ‘maintenance of batteries’ is a precondition for the product management strategy ‘‘electric vehicle’. Only if all preconditions of a strategy are implemented successfully the positive (or negative) consequences of a strategy are added to the overall values of the company meaning the evaluation criteria eco-efficiency, business profit and customer attractiveness. Knowing that stats influence not only the result of a game but also the learning effect, balancing between gameplay and realistic values comes to the fore. However the main goal of the game is not to reach high (abstracted) indicators but rather to get a deep understanding of holistic life cycle thinking. This will be addressed in the following section. Ecoefficiency

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During the group work phase every game participant acts in his company department. Only intra-departmental debating is allowed. The group work phase endures between 15 to 30 minutes, depending on the game directors. At the beginning a longer period of time is provided in order to accustom the game participants to the game materials, phases and possible actions. The management meeting takes place in between the group work phases of the business game. It allows for interdepartmental debating where all game participants of one company have the chance to discuss. The management meeting endures 10 to 20 minutes, depending on the game directors. At the beginning a longer period of time is provided as coordination and communication is more complex in the beginning.

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Figure 6: Preconditions matrix. 4.5

Life cycle orientation of the business game

As pointed out in chapter 3.2 the gap between a game and reality is a main task for game design. This point is of particular importance in a business game, because its focus is not on a precise simulation of each and every process found in reality but on providing spaces of possible experiences that are comparable to those the players might face in real business situations. This matter of fact becomes clear when looking on the four evaluation criteria. Although these criteria are used to give the participants a sense of the company success the main goal of the business game does not refer to the question whether a company is successful in the four categories or not. Thus the teams are not ranked according to the different indicators. The goal of the game rather refers to the life cycle orientation and is to give the participants a feeling of what life cycle thinking is about. This is why a central aspect of the business game for TLCM focuses on life cycle oriented operations during the group work phase. Life cycle oriented operations refer to the life cycle spanning disciplines of TLCM and are provided by the following management activities: 

Life cycle assessment enables game participants to ask for the ecological impact of different strategies.



Life cycle costing analysis enables game participants to ask for the economic impact of different strategies.

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The optimization of business processes enables transparency within a company department regarding different strategic options.

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The analysis of the total cost of ownership enables game participants to understand the economic impact of strategies regarding the customers of the company.

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Information management provides a life cycle oriented company culture and allows for inter-departmental exchange of knowledge regarding strategy requirements.



Cooperation with universities allows for focussing research activities.

Within the business game a life cycle oriented company culture needs to be established in order to be more successful regarding the critical success factors. Strategies have different impacts as well as inter- and intra-departmental pre-conditions that are not visible to the game participants at the beginning. Thus, the need for focusing on management activities as mentioned above is a hidden goal of the business game and leads to a turning point in the mindset of game participants. 4.6

automobile manufacturing supply chain consisting of the OEM, the first-tier supplier and the second-tier supplier. Whereas the game play structure of Shortfall is very similar to the Business Game for TLCM the strategical focus is not. Game participants also have to choose between different strategies influencing the possibilites of other departments but the decisions that have to be made In Shortfall are more on an operational and tactical level. The decisions in the Business Game for TLCM have a rather strategical meaning (e.g. game participants have to chose weather the company should focus on electric cars or fuel cell cars). Another difference is that Shortfall does not cover the whole life cycle in detail, from product idea and development via production, distribution, usage and redistribution to disposal. In Shortfall the foci are rather set on production and environmental issues. Furthermore, the game designers do not make use of a turning point in the mindset of game participants to convey life cycle thinking to the students. This is a distinctive part of the Business Game for TLCM. Nonetheless, an integration of both business games shows great promise for improving both of them. 5

OUTCOME AFTER THE INITIAL IMPLEMENTATION IN THE LECTURE PRODUCT AND LIFE CYCLE MANAGEMENT

During the course of the PLM lecture in the winterterm 2009/10 a first prototypical version of the introduced business game for TLCM has been tested during a game seminar over eight hours with about 70 students from the faculties of mechanical engineering and the faculty of architecture, civil engineering and environmental sciences (see Figure 7). This test has been conducted three times and the students’ qualitative feedback was noted in a subsequent colloquium. The game has been played at the end of the term so that the students had significant factual knowledge from the lecture, e.g. regarding methodologies like life cycle assessment, life cycle costing or design-for-x approaches. This knowledge is required before students can play and understand the game properly. The students have been asked to give quantitative feedback using an anonymized and standardized feedback form that is used for the evaluation of all lectures at the Technische Universität Braunschweig. Figure 8 shows some examples of the evaluation criteria that were interrogated during the evaluation of the corresponding lecture PLM. Although there are no direct evaluation criteria for the success of the business game for TLCM that are interrogated in the standard form it can be stated that the PLM lecture is regarded to be very attractive to the students at the Technische Universität Braunschweig which also results from the use of innovative teaching methods like the TLCM business game. The results of the qualitative feedback colloquium have shown that the business game serves as a driver for a better understanding of the overlapping activities that arise from the sequential life cycle phase related management disciplines in combination with the life cycle spanning disciplines. Therefore the business game helps to foster the philosophy of TLCM in the mindsets of students.

Comparison to Shortfall: The enhanced board game

2006 ISAACS ET AL. presented the business game Shortfall: The enhanced board game [24]. In Shortfall players also take on one of four roles in a company. However in contrast to the Business Game for TLCM each four-player company is situated in a position in an

Figure 7: Impressions after initial implementation.

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Ulrich, H., Krieg, W. (1974): St. Galler Management-Modell, 3. edition, Bern.

[6]

Bleicher, K. (1995): Das Konzept Integriertes Management, 3. edition., Frankfurt a. Main.

[7]

Herrmann, C., Mansour, M., Mateika, M. (2005): Strategic and Operational Life Cycle Management – Model, Methods and Activities, in: 12th International CIRP Seminar in LCE 2005, Grenoble.

[8]

Herrmann, C., Bergmann, L., Thiede, S., Zein, A. (2007): Total Life Cycle Management – A Systems and Cybernetics Approach to Corporate Sustainability in Manufacturing, in: Sustainable Manufacturing V: Global Symposium on Sustainable Product Development and Life Cycle Engineering, Rochester, USA.

[9]

Herrmann, C. (2009): Ganzheitliches Life Cycle Management - Nachhaltigkeit und Lebenszyklusorientierung in Unternehmen, Heidelberg.

[10]

Herrmann, C. (2006): Ganzheitliches Life Cycle Management, in: Herrmann, C.; Leitner, T.; Paulesich, R. [Ed.]: Nachhaltigkeit in der Elektro(nik)industrie, Düsseldorf, pp.1-29.

[11]

Crookall, D., Thorngate, W. (2009): Action, Knowing, Learning, Simulating, Gaming, in: Simulation & Gaming 2009, Vol. 40, No. 1, pp. 8-26, SAGE, Thousand Oaks, USA.

[12]

Hartung, S. (1999): Förderung der Lerneffizienz beim Einsatz von Unternehmensplanspielen, Göttingen.

[13]

Fischer, H. (2006): Ein systemorientierter Ansatz zur Modularisierung von Planspielen mit dem Ziel der Komplexitätssteuerung und Integration in Standardsoftware, Göttingen.

[14]

Faria, A. J., Hutchinson, D., Wellington, W. J., Gold, S. (2009): Developments in Business Gaming : A Review of the Past 40 Years, in: Simulation & Gaming 2009, Vol. 40, No. 4 , pp. 464-487, Thousand Oaks, USA.

[15]

Rohn, W. (1988): Deutsche Planspiel-Übersicht, 4. edition, Wuppertal.

[16]

Nohr, R., Böhme, S. (2009): “Die Auftritte des Krieges sinnlich machen”. Johann C. L. Hellwig und das Braunschweiger Kriegsspiel, Braunschweig.

[17]

Ahlbrecht, R. (2003): Komplexität im Unternehmensplanspiel: ein integrierter systemtheoretischer und kognitionstheoretischer Ansatz unter Bezugnahme auf den Gegenstand Unternehmensgründung, Göttingen.

[18]

Kriz, W. C. (2009) Bridging the Gap: Transforming Knowledge Into Action Through Gaming and Simulation, in: Simulation & Gaming 2009, Vol. 40, No. 1, pp. 28-29, Thousand Oaks, USA.

[19]

Salen, K., Zimmerman, E. (2006): The Game Design Reader: A Rules of Play Anthology. Cambridge, Massachusetts, USA.

[20]

Huizinga, J. (2008[1939]): Homo ludens: Vom Ursprung der Kultur im Spiel, 19. edition. Hamburg.

Figure 8 : Evaluation of PLM lecture (sample criteria). On the other hand, one has to criticize that the prototypical version of the TLCM business game can be used for the evaluation of the overall business strategy that has been evolved during the game but it cannot be used for giving the students a detailed quantitative feedback of each individual decision that has been made within the individual company during the game seminar. This defect results from a very high manual and technical effort to keep the game running and therefore ties up the academic staff for the management of the game. A severe supervision of the students during the game and linked to that a direct feedback to all individual management decisions that are made during the game will be in the focus of the next evolutionary step of the game. 6

SUMMARY AND OUTLOOK

Academic education programs often lack of methods for making complex contents perceptible for their students. This is true especially for abstract disciplines like the Framework for Total Life Cycle Management (TLCM). In this context the business game for TLCM is one approach to provide tangible experiences while teaching abstract and complex academic contents in order to foster the learning effect of students. The business game for TLCM simulates the development and evolution of a sustainable business strategy in an industrial company as a result of manifold management decisions of different protagonists. Therefore it also enables first experiences with intra-company communication and decision processes. A first prototype of the business game for TLCM has been introduced. Based on the outcome of this first prototype and the evaluation of the corresponding lecture a second prototype will be developed focusing on the evaluation of management decisions, a permanent supervision of the students and a reduction in the manual effort for the management of the game. 7

ACKNOWLEDGMENTS

As the development of the business game has been funded by tuition fees we would like to extend our sincere thanks to all who contributed to the development process. 8

REFERENCES

[1]

Tilbury, D., Wortman, D. (2004): Engaging people in sustainability, Gland, Cambridge.

[21] Salen, K., Zimmerman, E. (2004): Rules of Play: Game Design Fundamentals. Cambridge, Massachusetts, USA.

[2]

Herrmann, C., Bergmann, L. (2009): Total Life Cycle Management – A System Approach, in: 16th International Conference on Life Cycle Engineering, Kairo, Egypt.

[22]

Rollings A., Adams E. (2003): on Game Design. Berkeley. California. USA.

[23]

Schell, J. (2008): The Art of Game Design: A Book of Lenses. Amsterdam. Netherlands.

[24]

Isaacs J. A., Cullinane, T., Qualters, D. M., McDonald A., Laird, L. (2006): Games as Learning Tools to Promote Environmentally Benign Systems, in: Proceedings of 13th International Conference on Life Cycle Engineering, Leuven, Belgium, pp. 167 - 171.

[3]

[4]

Herrmann, C (2010): Ganzheitliches Life Cycle Management: Nachhaltigkeit und Lebenszyklusorientierung in Unternehmen, Springer-Verlag, Berlin. Beer, S. (1995): The Heart of Enterprise, London, New York.

Requirements Management – a Premise for adequate Life Cycle Design 1

1

Sandra Klute , Constanze Kolbe , Robert Refflinghaus 1

2 2

Chair of Quality Engineering, Dortmund University of Technology, Dortmund, Germany, RIF e.V., Dortmund, Germany

Abstract When developing products many different stakeholder requirements have to be considered to provide customer-oriented products and achieve customer satisfaction. Hence, an adequate requirements management including surveying, structuring and weighting of requirements is essential. Thereby, it has to be considered that the requirements differ regarding their level of specification, weighting and the stages of life cycle in which they occur or rather are important. Therefore, a 10-dimensional structuring model has been developed and implemented for data processing. This model goes beyond existing structuring models because it also comprises a feedback between requirements and their fulfilment. The model and its implementation for data processing are presented in this paper. Keywords: Requirements Management; Structuring; Data Processing

1

INTRODUCTION

When planning and developing products, a multitude of stakeholder requirements have to be taken into account to provide customeroriented products and achieve satisfied customers. Especially in the case of complex products like for example intra-logistical facilities the number of stakeholders and consequently requirements which have to be regarded is very high. Hence, an adequate requirements management including surveying, structuring and weighting of requirements is essential. Thereby, it has to be considered that the requirements are different regarding their level of specification, their weighting and the stages of life cycle in which they occur or rather in which they are important. Nevertheless, this is not important for the planning and developing process. In fact, in the planning and developing process, all requirements have to be considered and feedback resulting from the customers’ use of a product or in general requirements from customers, new technology internal sources and external sources like for example environmental protection have to be integrated into the product development [1], [2]. By this, costs which go along with scrap, failure corrections or belated corrections could be minimized or even avoided [3]. However, companies often do not know all of the stakeholder requirements or are not able to handle the great amount of them adequately. For solving this problem the gap between the stakeholder requirements and the design of complex products has to be bridged. The German Collaborative Research Centre 696 “Logistics on demand” deals with this topic. In this context, an adequate requirements management is the base for planning and developing customer-oriented products. Therefore, requirements have to be surveyed and structured afterwards. This serves as a preparation of their subsequent implementation into product characteristics, e.g. by applying the established method Quality Function Deployment (QFD). Also, only regarding the requirements is not sufficient, particularly in long-term customer relationships. Moreover, it is requisite to deal with customer satisfaction which results from the degree of requirements’ fulfillment. This is again determined by the requirement’s importance for the stakeholder, i.e. the requirement’s weighting.

For dealing with these aspects, a 10-dimensional structuring model has been developed within the sub-project A1 and implemented for data processing by the central project D. This model goes beyond existing structuring models because it comprises a feedback between requirements and their fulfilment in addition to the requirements’ structuring. The model and its implementation within a data processing system are presented in this paper. 2

10-DIMENSIONAL REQUIREMENTS

MODEL

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The basic idea of the developed structuring model is that a consideration of merely requirements and the product core is insufficient. In fact, a holistic approach is necessary. This approach should include the stakeholders‘ evaluation of the requirements‘ fulfillment as well as the customer satisfaction which results from it in addition to the regarded product respectively the requirements made on it. This allows a feedback between requirements and their fulfillment. Furthermore, it enables to consider latent requirements which otherwise are often neglected. Moreover, it is necessary to consider services and delivery in addition to the “product core”, because they are of increasing importance for the customers and their buying decisions [4]. Hence, the extended product should be the reference object (Figure 1).

Creation

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Figure 1: Basic idea of the model. The ten dimensions of the model are: obligations, surroundings, information, economy, qualification, technical-functional requirements, product, weighted level of performance and customer satis-

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_93, © Springer-Verlag Berlin Heidelberg 2011

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faction. The dimensions differ from each other regarding their content and meaning because they serve different purposes. Whereas the first six mentioned dimensions, disregarding the dimension time, serve to structure the requirements, i. e. the nominal condition, the dimension weighted level of performance serves to measure the reaction of the stakeholders with respect to the fulfillment of their requirements by comparing nominal and actual condition. The dimension customer satisfaction shows the satisfaction of the stakeholders which results from their evaluation of the requirements’ fulfillment. Hence, the customers’ reaction to existing attributes of the (real) product or within the framework of tests, like for example threedimensional simulations has to be surveyed. By comparing nominal condition and actual condition it is shown whether and to which extent the stakeholder requirements are fulfilled. Consequently, the dimensions “weighted level of performance” and “customer satisfaction” capture the actual condition and are temporally behind the other ones. The dimension product serves to structure the reference object to which the requirements refer, i.e. a product or a process. Structuring of requirements with regard to content

Structuring of the reference object

• Obligations

• Product (Reference object)

• Surroundings • Economy

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Temporal structuring of requirements • Time

performance • Customer satisfaction

• Information • Qualification • Technical-functional requirements

Figure 2: 10-dimensional model. Beyond that, time aspects have to be regarded. In this context, it has been considered that requirements are of different importance in different stages of the life cycle and that they are dynamical. That means they change over time regarding their meaning, their content and their level of specification. For instance, stakeholders may not be able to articulate all of their requirements at the beginning of the planning process and may not be precise in their requirements [5]. Hence, time has been considered as a separate dimension because this is essential for adequate product design and service over the whole life cycle. Originally, the model has been developed for the fields of intralogistics and thus the development of complex facilities. Nevertheless, it is possible to apply and extend it to other fields because it is generic. This can be done by adapting the dimensions and their categories if necessary. Thereby, all dimensions which serve to structure requirements can be divided into several categories and subcategories. This allows an adequate matching of the requirements which considers the requirements’ level of specification. In doing so, laminations should be avoided so that a valid interpretation by comparing these categories is enabled. Consequently, categories of different dimensions should not be too similar [6]. Nevertheless, it is inevitable that they deal with the same topic but from a different point of view and with different focus. For instance, the aspect of environment is treated within the dimensions obligations and surroundings. The dimension “obligations” thereby deals with requirements regarding environmental protection by observing laws and provisions concerning this matter. Whereas the dimension “surroundings” deals with aspects which are not necessarily dealt with by law like for example stakeholder requirements concerning radiation and sonic which go beyond legal requirements.

Moreover, it should be taken into account, that requirements should be classified in the space which is spanned by the ten dimensions although the requirements should not necessarily have to be sorted into all dimensions. The dimensions allow to determine and to structure all requirements on intra-logistical facilities in the case at hand and complex products or processes in general. Therefore, a further detailing and categorizing of the dimensions is requisite to ensure a topical classification of the requirements which takes their level of specification into account. Following, exemplarily for the dimensions which serve to structure the requirements the dimensions surroundings, information, technical-functional are presented in more detail. Also the dimensions weighted level of performance and customer satisfaction are described in more detail because they give feedback to the gathered requirements. 2.1

Surroundings

This dimension can be divided into the categories “direct facility surroundings”, “resources”, “environment” and “safety”. Requirements are sorted into these dimensions, if they do not concern the regarded product but its surroundings. The category “direct facility surroundings” comprises requirements that concern the direct surroundings of the facility. This includes for example the facility’s area and the interference factors. Interference factors are devices or components whose operating or existence near the facility bear (negative) consequences for the facility. Personnel and material resources which are needed for manufacturing and operating the facility are part of the category “resources”. The personnel resources may be of a quantitative or of a qualitative kind. Hence, this category includes requirements concerning the number of the needed personnel as well as requirements concerning its qualification. Requirements concerning material resources can be differentiated by the kind of resource into, for example, water, gas and power. Within the category “environment” the subcategories “macroenvironment” and “micro-environment” can be distinguished, depending on whether the requirements are of a global kind or just concerning the close facility-environment. The first one comprises requirements of a social, political or technological kind. Consequently, it refers to factors which cannot be influenced by the company directly. Requirements concerning the micro-environment are focused on the direct facility-environment and usually can be influenced by the company. This includes aspects like radiation, sonic and so on. Requirements concerning the facility’s security belong to the third category in this dimension. In this context, the aspect of occupational safety is very important. Requirements referring to this aim are workplace-design and the facility’s construction. Therefore, the facility’s dangerous spots have to be marked respectively to be secured, so that the danger of an accident or an injury is reduced or even avoided. The following figure summarizes and depicts the dimension “surroundings”.

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Figure 3: Structuring requirements in line with the dimension “surroundings“. 2.2

Information

Requirements can be structured regarding the aspect “information”. All requirements that refer to type, provision, contents and volume of information for the planning and construction of intra-logistical facilities have to be sorted into this dimension. Within this dimension the categories “source”, “object”, “data”, “data transfer” and “data processing” can be distinguished. In this context, the categories source and object refer to the source and the recipient of the data or rather requirements which result from this. The category “data” can be further divided into the sub-categories “type of data”, “data content” and “data volume”. Requirements that concern the type and speed of data transfer and belong to the category “data transfer”. As an example the requirement “The data transfer should be wireless.” can be named. Furthermore, requirements may concern the data processing. Thereby, the subcategories “type of data processing” and “speed of data processing” can be differentiated. The following figure gives an overview of the dimension “information”.

tion-specific requirements” a further differentiation into the subcategories reliability, functionality, robustness, load capacity and flexibility can be made. In this context, reliability is an important aspect. Thereby, reliability is defined as the ability of a reference object to perform its functions during a period of time [7]. It can be measured for instance by using “mean time to failure”,” mean time between failure” and “failure rate” to reach a higher level of specification [8]. The category “supportive requirements” includes requirements that deal with aspects that are not part of the core functions of the facility. It can be sub-divided into the sub-categories for “planability”, “producibility”, “installability”, “maintainability”, “operability”, “removability”, “recyclability” and “disposability”. Requirements which belong into this category are for example “The product should be able to be disposed eco-friendly” or “The parts of the facility should be removable easily.”. Thereby, the first named requirement has to be sorted into the sub-category “disposability” and the latter one into the category “removability” (Figure 5). Furthermore, in this context maintainability has become an important factor for customers, especially for complex products with longevity. Hence, many requirements deal with this topic. Thereby, maintainability is defined as the condition of an entity concerning its appropriateness for maintenance. As an example for a requirement on the maintainability the requirement “The facility should feature a good maintainability.” could be mentioned. The maintenance includes measures to maintain or if necessary to return to the required functional status. Moreover, maintenance can be further differentiated into the sub-groups “preventive maintainability”, “reparability” und “inspectability”. [9]. Technical-functional requirements

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Figure 4: Structuring Requirements in line with the dimension “Information”.

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Technical-functional requirements

Requirements might also be of a more general kind. That means they do not concern directly individual parts of the regarded product. In fact, they concern the whole product and/or its function capability and performance like for example low energy consumption and low fault liability. Hence, for considering these requirements one dimension of the model for structuring requirements is the dimension “technical-functional requirements”. This dimension can be further differentiated into the categories “function-specific” and “supportive requirements”. Thereby, within the category, “func-

Removability

Figure 5: Structuring in line with the dimension “technical-functional aspects”.

2.4

Weighted level of performance and Customer satisfaction

In contrast to the dimensions which serve to structure requirements respectively the reference object, these dimensions serve to give feedback if the requirements have been fulfilled in the stakeholders’ point of view. Consequently, these dimensions are set temporarily behind the surveying and structuring of requirements and show the actual condition. Checking the requirements’ fulfillment may be done by persons or suited measurement devices. Thereby, it has to be taken into account that it is hardly possible to measure a property’s “true condition”. Consequently, it is mandatory to differentiate between the objective and the subjective evaluation. Requirements like, for

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example, “The floor space required for the facility must not exceed 2 250 m .” can be measured objectively with measurement devices. Nevertheless, the results which are reached respectively reachable vary. This is because of an uncertainty of measurement so that the “true” value is only determinable with a certain probability. Requirements like “The facility should be as flexible as possible.” cannot be measured objectively. Those requirements respectively their fulfillment can only be evaluated by persons. However, these requirements and their fulfillment are very important for the stakeholders and hence for their satisfaction [10]. Beyond that, the requirement’s weighting for a stakeholder may be important and consequently should be considered. It is also crucial for the customer satisfaction as it results from the evaluation. This is because the fulfilment of those requirements is a significantly determining factor for the extent of customer satisfaction (Figure 6). The dimension “customer satisfaction” shows if the customers are satisfied. Therefore, information needed for this dimension results from the evaluation of the stakeholders whether and how far their requirements were met. Thereby, customer satisfaction is the result from the perceived difference between expectation and performance respectively between performance-standards and the perceived quality or performance of the product [11], [12]. In this context, the requirements’ importance for the stakeholders respectively their weighting of the requirements is an essential aspect. For this purpose, the KANO-model can be used but a modification is necessary so that the weighted requirements and the weighted degree of satisfaction can also be regarded. In accordance with the original model, attractive, one-dimensional and must-be-requirements can be differentiated. Moreover, it is assumed that a linear correlation between meeting requirements and satisfaction does not necessarily exist [11], [13]. Although the integration of a weighting-factor leads to the inability to depict graphs of requirements exactly. In fact, the graphs may have a flatter or steeper progress. This means that the weighting-factor causes a weaker or more intense impact of the requirements’ fulfillment on customer satisfaction. This effect is shown by arrows in Figure 6. Fulfilling of a must-be-rated requirement is essentially. Though it does not increase the customer satisfaction, not fulfilling this requirement causes dissatisfaction. In contrast, attractive requirements possess the highest influence on customer satisfaction. Customer satisfaction high One-dimensional requirements

3

IMPLEMENTATION FOR DATAPROCESSING

For managing the requirements and applying the model a data processing system has been developed in form of a java-application in the central project D of the SFB 696 (Figure 7). The system consists of different components which are linked to each other. In addition to the presented model these are a “linguistic analysis”, a “template” (for storing a single requirement), an “ontology” (for machine interpretable knowledge) and a “wiki” (for human interpretable knowledge). The model’s terms (in form of dimensions and categories) can be also found within the ontology (in form of classes) and within the wiki (in form of definitions). Due to that, the three components are compatible with each other which is mandatory. During the planning process and consequently during the surveying and structuring of requirements stakeholders interact with the data processing system. After a stakeholder has formulated his requirement and entered it into the system the system provides functionalities that are needed in order to prepare the subsequent implementation of requirements, e.g. by QFD. In the following, the different functionalities will be explained. Data Processing System

Wiki

Expert Knowledge

Template

10dimensional Model

Ontology Interaction

Linguistic Analysis

Subsequent Processing Requirement Implementation (Quality Function Deployment)

Stakeholder Java-Application Requirement

Formalization of Requirement

Requirement Intepretation

Structuring Specification Requirements analysis into Groups

Figure 7: Data processing system. 3.1

Requirement formalization and Interpretation

At first, a single requirement given in natural language has to be made accessible to the system before it can be processed by it. Therefore, the functionality “Formalization of Requirement” has to be performed with the help of the component “linguistic analysis”. Thereby, this component matches the terms of the requirements with the content of the “ontology” which is a “formal, explicit specification of a shared conceptualization” [14]. It also acts as a database that contains knowledge about requirements and their dependencies in form of classes and properties [15] (Figure 8).

Attractive requirements

low

high Must-be/basic requirements

time

Requirement Implementation

Degree of performance (weighted)

low

Figure 6: Modified KANO-model. Figure 8: Schematic overview of the ontology.

Information and Knowledge Management The result of the formalization is stored within a template (Figure 9). Therewith, information which represents the content of a single requirement can be mapped structuredly. Information about the core requirement is stored under the headline “reference”. The core requirement can be represented by a “reference object” (which is with respect to its content related to the dimension “product”), an “attribute” and a “value” (which is with respect to its content related to the dimension “qualification”). Using the requirement “The facility should feature a good maintainability.” which has been already mentioned above, within the template the “reference object”: facility, the “attribute”: maintainability and the “value”: high should be stored.

541 • Obligations • Surroundings • Economy

specification “The facility should feature a good maintainability.”

“The facility should feature a good repairability.”

• Information • Qualification–Qualitative • Technical–Functional Requirement– Supportive Task–Maintainability

– Repairability

• Product–Product Core

Figure 10: Sorting of requirements into the model. 3.3

Figure 9: Template for mapping a requirement. The system also provides a link to the wiki. During the formalization a stakeholder can check if the terms of his requirement were correctly interpreted by the system. A wiki is composed of web-sites ([16], [17]) and the content can be read and also edited by the stakeholders. It provides definitions of the ontology´s and the model’s terms. Due to the wiki stakeholders can interpret the requirements of each stakeholder. Thereby, problems in misunderstanding between stakeholders can be prevented. In order to control the coherence of the information contained in the wiki, new contents are only released by the administrator after the content has been reviewed by the stakeholders. By means of the formalization the requirement is now positioned in relation to the knowledge of the ontology and the knowledge of the wiki. This is the precondition for further analysis of the requirements within the system. 3.2

Sorting of requirements into the model

Afterwards, the stakeholders have to structure the gathered requirements of all stakeholders into the 10-dimensional-model. Hence, within the data-processing system the single dimensions and its single categories are presented to the stakeholders during the assignment of a requirement. In order to facilitate the assignment, the classification of the considered requirement by other stakeholders which were made beforehand, can be seen. The stakeholder can choose the classification he corresponds with or he can search for his desired dimensions. Therefore the system contains a search function which enables the user to search by term in all dimensions or in one selected dimension. The system provides also statistics concerning the structured requirements. By this it can be checked whether all dimensions of the model are taken into account and whether all stakeholders are respected or if there are informational gaps within the requirement collection. The considered requirement concerning the maintainability could be structured into the sub-dimension “Qualitative”, “Maintainability” and “Product Core” (Figure 10).

Specification analysis

During the various stages of the life cycle requirements are different regarding their level of specification. At the very beginning of a planning process, especially abstract requirements are uttered by the stakeholders in order to receive a first overview of the system [18]. One aim of the planning process is to receive more precisely requirements during the selection of requirements. In order to drive the development process forward, stakeholders should substitute their abstract requirements by more precise requirements. In this case the subordinated requirements define precisely the superordinated requirement allocated to them [19]. In order to support the stakeholders with the specification of the abstract requirements, the functionality “specification analysis” is provided by the system. Therewith, the stakeholder can perform an optional, automatic specification analysis of his requirement. It provides automatically detailed requirements, with which a considered requirement can be specified. This allows an optimization of expressing requirements by substituting abstract requirements with more concrete requirements. By this, a secured deriving of concrete requirements is enabled. Within the system a differentiation between object-, attribut- and value-specification is carried out. In the following, an example for a specification of attribute will be shown. This kind of specification concretizes the attribute of the given requirement. To provide more precisely attributes, the system identifies all attribute-classes within the ontology that are connected to the “maintainability”-attribute class. This could be a connection over the class hierarchy as well as a connection over a “specifies”property. In order to obtain a meaningful output a test is carried out to check whether the reference object “facility” can have the more concrete attributes. For these attribute-classes it will be checked whether they are connected over a “has_attribute”-property to the “facility”-class of the abstract requirement. This ensures that only meaningful requirements will be provided by the system. For our given example the system outputs a set of the more concrete requirements shown in Figure 11. Now the stakeholder has the possibility to substitute his abstract requirement by all or by several of these more precise requirements. After the specification the detailed requirements have to be sorted into the upper levels of the model. For example the concrete requirement “The facility should feature a good repairability.” could be sorted into the sublevel “Repairability” of the abstracts requirements category “Maintainability” (Figure 10). Due to the functionality “Specification analysis” the upper levels of the model can be filled with structured and systemized requirements.

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Facil it y Maint ainabil it y

[1]

Ehrlenspiel, K. (2009): Integrierte Produktentwicklung. Denkabläufe, Methodeneinsatz, Zusammenarbeit, München: Carl Hanser Verlag.

[2]

Schäpp, B.; Andreasen, M.;Kirchgeorg, M.; Radermacher, F. (2005): Handbuch Produktentwicklung, München: Carl Hanser Verlag.

[3]

Mateika, M. (2005): Unterstützung der lebenszyklusgerechten Produktplanung am Beispiel des Maschinen- und Anlagenbaus, Schriftenreihe des Instituts für Werkzeugmaschinen und Fertigungstechnik der TU Braunschweig, Essen.

[4]

Hartel, D. (2009): Consulting in Industrieunternehmen. Praxisleitfaden mit Fallstudien, Oldenbourg Wissenschaftsverlag GmbH, München.

[5]

Gautum, N.; Singh, N. (2008): Lean product development: Maximizing the customer perceived value through design change (redesign). Journal of Production Economics, 114, pp 313-332.

[6]

Crostack, H.-A.; Klute, S.; Refflinghaus, R. (2010): A multidimensional model for structuring stakeholder requirements. Proceedings of the 20th CIRP Design Conference, 19.-21.04., Nantes/Frankreich.

[7]

Smith, D.-J. (2005): Reliability, maintainability and risk: practical methods for engineers, Oxford: Butterworth-Heinemann.

[8]

Blischke, W.; Murthy D. (2000): Reliability: modeling, prediction, and optimization, Wiley.

High

Facil it y

Facil it y

Facil it y

Facil it y

Facil it y

Maint enance effort

Repairabil it y

Prevent ive maint ainabil it y

Inspect abil it y

…

Low

High

High

High

…

Figure 11: Results of the automatic specification analysis.

4

SUMMARY

The developed 10-dimensional model fulfills several purposes. It enables to check the completeness of the gathered requirements during the planning process in order to avoid informational deficits and hence supports the surveying of requirements. It also considers the evaluation of requirements´ fulfillment by the stakeholders as well as the satisfaction of the stakeholders. This model has been implemented as part of a data processing system. Both, the model and the system, benefit from each other. The system as a whole provides different functionalities and comprises also a knowledge base for machine-interpretable knowledge (in form of an ontology) and a knowledge base in for humaninterpretable knowledge (in form of a wiki). Therewith a knowledge based data processing of a large set of requirements uttered by the stakeholders in natural language is possible. The aim of the system is the preparation of the huge amount of requirements for their later translation into quality characteristics, like for example in the framework of a QFD. The first functionality of the system is the “formalization of requirement” in order to make the requirement machine-interpretable. This formalization ensures that only complete and meaningful requirements are sorted into the 10-dimensional model. The second functionality is the “requirement interpretation” which is needed to make the requirements human-interpretable and to solve problems of understanding between stakeholders. The third functionality of the system is “Sorting requirements into the Model”. This functionality is enabled by the implemented 10-dimensional model within the system and indicates informational deficits. Only due to the model, the system is able to ascertain whether all necessary requirements are captured. The system supports the user whilst he is sorting his requirement into the model by providing search and display functions as well as a functionality for a statistical analysis. The fourth functionality “specification analysis” performs an automatic specification of a considered abstract requirement and provides more precisely requirements with which a user can specify his abstract requirement. This functionality promotes a fast and systematic adding of requirements in the upper levels of the model. Summing up, a successful planning process is provided by a correct interpretation of the requirements, by a complete selection of requirements and an appropriate structuring of requirements into groups with regard to their abstract level as well as by a systematic specification of requirements over time. 5

ACKNOWLEDGMENTS

The authors wish to thank the Deutsche Forschungsgemeinschaft (DFG) for supporting their work within the framework of the Collaborative Research Centre 696.

REFERENCES

[9]

DIN 31051 (2003): Grundlagen der Instandhaltung. Juni.

[10]

Chen, C.; Chuang, M.-C. (2008): Integrating the Kano model into a robust design approach to enhance customer satisfaction with product design. Journal of Production Economics, Vol. 114, pp 667-681.

[11]

Sauerwein, E. (2000): Das KANO-Modell der Kundenzufriedenheit. Reliabilität und Validität einer Methode zur Klassifizierung von Produkteigenschaften, Wiesbaden: GablerVerlag.

[12]

Tse, D., Wilton, P. (1988): Models of Consumer Satisfaction Formation: An Extension. Journal of Marketing Research, Vol. 25, pp 204-12.

[13]

Hölzing, J. (2008): Die KANO-Theorie der Kundenzufriedenheitsmessung. Eine theoretische und empirische Überprüfung, Wiesbaden: Gabler-Verlag.

[14]

Gruber, Thomas R. (1993): A Translation Approach to Portable Ontology Specifications. Technical Report KSL 92-71. Knowledge Systems Laboratory, Computer Science Department, Stanford University, California.

[15]

Crostack, H.-A.; Kolbe, C.; Refflinghaus, R. (2010): Creating an ontology for requirements on an Intra-Logistic facility. In Proceedings of the 13th QMOD Conference on Quality and Service Sciences ICQSS2010, 30.08.-01.09, Cottbus/Deutschland.

[16]

www.mediawiki.de.

[17]

Cimiano, P. (2006): Ontology Learning and Population from Text: Algorithms, Evaluation and Applications, Springer Verlag, Berlin.

[18]

Rupp, C. (2002): Requirements-Engineering und – Management – Professionelle, iterative Anforderungsanalyse für die Praxis, 2. Aufl., München: Carl Hanser Verlag.

[19]

Lilien G.-L., Rangaswamy A.; De Bruyn A. (2007): Principles of marketing engineering, DecisionPro.

Towards a Methodology for Analyzing Sustainability Standards using the Zachman Framework 1

1

1

Sudarsan Rachuri, Prabir Sarkar , Anantha Narayanan , Jae Hyun Lee , Paul Witherell 1

1

Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, USA

Abstract There exists a multitude of standards and regulations related to sustainability. It is critical to enable users to identify applicable standards across entire lifecycles of products, processes, and services. To synthesize this variety of standards, it is important to analyze them from the information modeling point of view, while incorporating the requirements of various stakeholders. Here, we propose such a multi-perspective approach based on the Zachman framework. Using this approach it is possible to identify gaps and overlaps, harmonize, and develop implementation strategies for sustainability standards. We then introduce our case study results as part of the Sustainability Standards Portal. Keywords: Sustainability Standards; Zachman Framework; Sustainable Manufacturing

1

INTRODUCTION

“Sustainability” is a term commonly used to express the capability to use a resource without permanently depleting it, thus preserving the resource for future use. The popular definition of sustainability comes from the World Commission on Environment and Development (WCED), which expresses sustainability in terms of a development, “..that meets the needs of the present without compromising the ability of future generations to meet their own needs [1].” Sustainability, according to the US National Research Council [2], is “the level of human consumption and activity, which can continue into the foreseeable future, so that the systems that provide goods and services to the humans persists indefinitely”. Though there are a multitude of definitions that address various aspects of sustainability, as Sitarz [3] interestingly observed, “In the final analysis however, agreeing on a formal definition of the term is not as important as coming to agreement on a vision of a sustainable world.” Standards play a critical role in enabling the sustainability of products, processes, and services. The American National Standards Institute (ANSI) [4] states that “Standards are critical to establishing and maintaining a business and a strong economy.” According to standards.gov [5], standards are “Common and repeated use of rules, conditions, guidelines, or characteristics for products or related processes and production methods, and related management systems practices.” Therefore, a standard is an agreed, repeatable way of doing something. Regulations are understood to “specify mandatory (legal) requirements that (1) must be met under specific laws and (2) implement general agency objectives [5].” It is our view that standards and regulations will play a crucial role in mitigating the complexity of the activities and interactions required to create a sustainable world. The adoption of sustainability standards as best practices will aid in the reduction of the environmental impact of products (e.g., usage, recycling, and endof-life), processes (e.g., manufacturing, supply chain, and production), and services. Despite their noble intentions, the increasingly large number of voluntary and regulatory standards

related to sustainability makes it difficult to select and study the relevant suitable standards associated with a product line. In addition to this, many of the standards are defined within extensive documentation and therefore are difficult to interpret from the information modeling and implementation points of view. From our interactions with industry, academia, and standards development organizations, we have found that to comprehensively understand standards and regulations, it is important to analyze them from different perspectives. For instance, the information requirements of a manufacturer trying to comply with a regulation will be different from the information requirements of a regulatory organization (standards and regulations will henceforth be treated synonymously and collectively referred to as ‘standards’). In this paper, we propose a methodology for the analysis of these standards using the Zachman framework, taking into account the multiple perspectives of various stakeholders with the understanding that their goals may vary. The paper is structured as follows: In Section 2, we describe the status quo, the problems with existing sustainability standards and common inquiries into these standards. In Section 3, we discuss our approach to address the above issues and the reasoning behind it. In Section 4, we provide insight into the Zachman framework, some specific application domains where this framework was used, analysis of sustainability standards based on stakeholder perspectives, and the technical analysis of standards using the Zachman framework. In Section 5, we provide a case study describing how our approach is used and introduce our webbased Sustainability Standards Portal [6], and in Section 6 we finish this paper with conclusions and ideas for future work. 2

UNDERSTANDING WHAT IS REQUIRED

To achieve sustainability, products, processes, and services should meet the challenges not only related to traditional design issues such as functions and performance, but also environmental and social issues. This paradigm shift requires manufacturers, who have traditionally aimed at minimizing capital and maximizing profits, to

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_94, © Springer-Verlag Berlin Heidelberg 2011

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aim at minimizing resources and maximizing value to society at large. Companies interested in developing sustainable products should be sensitive to sustainability related standards, design methodologies, and manufacturing techniques and tools. For many small and medium enterprises (SMEs), it is difficult to identify and comply with the standards applicable to the products that they manufacture due to the limited resources (personnel or capital) available to invest in standards compliance. This is compounded by the fact that many of these standards are updated frequently, therefore requiring recurring investments. Some of the questions SMEs may ask are: Why should we follow this standard? Who developed this standard? How do we get a product certified as compliant to a standard? Who is the certifying agency? How long does it take to get certified? Such questions often come with no simple answers, and the answers require valuable time and resources to acquire. To address these concerns and issues, we need to create a structured methodology, for understanding standards, that is repeatable for a variety of standards and regulations, and a clear way of disseminating the information to the different stakeholders. The specific aims of this work are to provide the following: i. ii.

3

Given the diverse nature of sustainability concerns, and the many stakeholders involved, we found it necessary to consider the problem from different stakeholders’ perspectives. We used this perspective-oriented analysis as a means for providing general observations of what the detailed technical analyses may entail. Our stakeholders approach takes these factors into account and offers a means for insight into these sustainability standards. The Zachman framework (described in Section 4) then provides a way to critically analyze a problem by separation of concerns. It helps us break down the issues into a number of distinct partitions, so that finer issues may be addressed at various levels of detail. The proposed methodology for analyzing sustainability standards has three components:

Create a comprehensive understanding of standards that are related to sustainability by providing an overview, analysis, and other details for each standard. Help identify the applicable standards and implementation strategies for different stakeholders of these standards such as customers (consumers), industries (producers), government (implementers), software developers (support providers), researchers (support developers), and standard developers (developers).

TOWARDS A COMPREHENSIVE UNDERSTANDING OF SUSTAINABILITY STANDARDS

There are many factors that contribute to sustainability, and all of them must be considered when measuring the sustainability performance of a company. Sustainable manufacturing “is a systems approach for the creation and distribution (supply chain) of innovative products and services that: minimizes resources …across the entire life cycle of products and services [7].” Ensuring sustainable manufacturing requires an integrated system of systems approach that spans technical, economic, ecological, and societal issues. Interactions within and across these levels are critical to the fundamental understanding of sustainable design and manufacturing. Tackling any one of the issues in isolation could result in an inadequate solution and unintended consequences. Figure 1 illustrates the diverse range of metrics, methods, and tools that are required to satisfactorily measure sustainability performance. The first category, “What to measure?” is concerned 1 with the specific metrics and indicators that are used to measure various sustainability factors. These can be further classified into different levels, such as process level and product level. The second category, “How to measure?” is concerned with the process of measuring the metrics and indicators in different situations. It considers data availability, engineering and business tools, and measurement methods. The third category, “How to report?” addresses the methods of reporting the measured data, such as through globally accepted reporting formats. The final category,

1

“How to verify/validate?” is concerned with verifying and validating the reported data. There is a complex interaction between the metrics, tools, and standards involved in gauging the overall sustainability performance. This calls for a structured and detailed analysis for the better understanding of sustainability standards.

Measurement: A quantitative, physical attribute. Metric: A category that reflects a combination of individual measurements and that can be used to provide a large-scale view of a system and gauge system performance. It may be quantitative or qualitative. Indicator: A selected subset of metrics that is judged helpful for projecting future performance of a system [8].

Figure 1: Measuring sustainability performance. 1)

Analyzing the requirements of various stakeholders Information for a given sustainability standard is collected in this process from a variety of resources. The collected information is classified according to measurement performance views such as those seen in Figure 1. These metrics and indicators are defined for products, processes, and services across entire life cycles (cradle to grave and cradle to cradle). The concerns of different stakeholders are then considered by addressing cognitive primitives as viewed from different perspectives. The concerns/issues identified comprise the requirements of the standard for different stakeholders and should be answered by the detailed technical analysis. This will be explained further in Section 5.

2)

Technical analysis of standards using Zachman framework The sustainability standard is analyzed from the information modeling point of view while considering the results of the stakeholder’s analysis. The Zachman framework is used to capture different aspects of a given sustainability standard. The collected information and knowledge about the sustainability standard are analyzed and organized according to the Zachman framework in this process. Each cell in the Zachman framework contains its meta-model, which describes what information should be captured and how to express it in the cell. Since meta-models of each cell describe independent

Information and Knowledge Management

Scope (Contextual) Enterprise Model (Conceptual) System Model (Logical) Technology Model (Physical) Implementation (Detail) Functioning Enterprise

545

What (Data)

How (Function)

When (Time)

Who (People)

Where (Location)

Why (Motivation)

List of things

List of processes

List of events

List of organizations

List of locations

List of goals

Semantic model

Business process model

Master schedule

Work flow model

Logistics network

Business plan

Logical data model

Application architecture

Processing structure

Human interface architecture

Distributed system architecture

Business rule model

Physical data model

System design

Control structure

Presentation architecture

Technology architecture

Rule design

Data definition

Programs

Timing definition

Security architecture

Network architecture

Rule specification

Usable data

Working function

Usable network

Functioning organization

Implemented schedule

Working strategy

Table 1: Zachman framework. concerns, models in each cell can be revised without changing models in other cells. 3)

Integrating models in Zachman framework Models in each cell of the Zachman framework can exist independently, but this does not mean that these models do not have relationships with each other. Each model can be related to other models in the same column as well as in the same row. The composite or integration of all cell models in one row constitutes a complete model from the perspective of that row [9]. This statement derives from the fact that any one cell of one column is merely a single abstraction of reality.

In Section 4.4, we explain how to harmonize and integrate the models in the Zachman framework. 4

AN APPROACH FOR ANALYZING SUSTAINABILITY STANDARDS USING THE ZACHMAN FRAMEWORK

Many sustainability standards have been developed and will be developed in the future. The information models of these standards and the relationships among them are difficult to describe and understand because of their complexity. The Zachman framework can contribute to their understanding and describe complex relationships and information models in sustainability standards. 4.1

Introduction to the Zachman framework

The Zachman framework [10] was designed to describe any idea that is complex to understand [9]. It is widely used for enterprise architecture modeling. It is depicted as a 6 x 6 matrix, as shown in Table 1, with cognitive primitives as columns and abstraction levels of information as rows. Each cell classifies enterprise information, and helps people to describe and understand the total enterprise architecture. The six cognitive primitives used in this framework are What, How, When, Who, Where, and Why. They are fundamental question primitives for communication, and integration of each question enables the comprehensive and composite description of the enterprise information. The six rows in the matrix help to separate the problem into different levels of detail, with more detailed information being introduced in the lower levels. The top row describes the context of information, and is used to set up the domain of discourse. The second row is for domain experts to describe their business concepts. The third row describes system logics specialized from the second row, and the fourth row describes the technology applied to the system logics. The fifth row describes solutions that are actually implemented for the technology, and the bottom row denotes the operation of the enterprise.

Given its versatility, the Zachman framework has been used in the past to describe standards through categorization. In [11], the authors use the Zachman framework [12] to create 36 different characterizations to categorize healthcare and healthcare information system standards. In this scheme, each standard had a primary category based on its placement into one of the 36 cells. This serves as a useful way to group different standards, but does not provide the necessary insight into the standards themselves. We propose the need for a more descriptive approach to provide information about standards to different stakeholders, most similar to that seen in Panetto et al.’s work [13]. Here the authors are able to map the International Electrotechnical Commission (IEC) 62264 [14] standard to the Zachman framework “in order to make the framework as a guideline for applying the standard and for providing the key players in information systems design with a methodology to use the standard for traceability purposes.” We take this approach one step further by associating the Zachman analyses with stakeholder’s perspectives, similar to what is presented through a security engineering application in [15]. In [15] the author uses the Zachman framework to describe the architecture for a cyber security system. The rows of the Zachman framework, which denote the different abstraction levels, are mapped to different stakeholders such as consumer, designer, and builder. Though we have adopted a parallel approach, in our scenario the different stakeholder viewpoints do not directly map to different levels of abstraction. For example, an industry observer might be interested in different aspects of a standard as compared to a software solutions developer, but the two stakeholders’ viewpoints need not be on different abstraction levels. 4.2

Analyzing the requirements of various stakeholders

In order to perform a Zachman framework based analysis, it is essential to define the domain of discourse precisely. Sustainability standards have a wide-ranging impact, which adds a level of complexity in establishing the domain of discourse. In order to properly analyze sustainability standards, we must identify the specific requirements of different stakeholders. Through our interactions with the industry, academia and other government agencies, we have identified a list of stakeholder groups based on the nature of information and support they require in dealing with sustainability standards. We call these perspectives, as the same individual may have different views of the same standard. The list of stakeholder perspectives we have identified includes the following: 1) Generic user, 2) Consumer or buyer, 3) Manufacturer or producer, 4) Government or regulatory agency, 5) Software solution provider, 6) Researcher, and 7) Standard developer. Our stakeholder’s analysis approach is comprised of the following steps: 1) Identify a set of perspectives from which stakeholders may view

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a standard, 2) Identify a set of concerns/issue for each perspective, based on the question primitives of the Zachman framework. For instance, a software solution provider may be interested in the scalability and analytics of the data, while an industry stakeholder might be interested in how to become compliant and get certification. We must note that for a given cognitive primitive, different stakeholders may have different concerns. For instance, if we consider the primitive “How,” a consumer or buyer is mainly interested in: “How to verify that a product is standard compliant?” The answer to this question will include information such as logos and text annotations that can be found on compliant products. An industry user will be more interested in questions such as “How to become compliant and obtain certification?” This question is answered by giving information on certifying agencies and compliance guidelines for that standard. A government or regulatory agency will be interested in how to regulate the standard and how to promote and support it. A software solutions provider will be interested in data availability (for example, design, manufacturing, and material data), scalability issues of the standard (e.g., part, product, system, and enterprise level data), and how this standard affects other related software. A researcher will be interested in how one can contribute to the development of the standard, and how to obtain statistics for its evaluation. Finally, a standard developer will be interested in how fast this standard needs to be developed, and how training can be provided for this standard. This representative set of questions illustrates the need to analyze standards from different perspectives in order to address the concerns of all the stakeholders involved. The proposition and consideration of these issues/concerns lead to a set of terms and concepts that are used in the first row of the Zachman framework. Therefore, this analysis plays a crucial role in setting up the domain of discourse for further analysis. The information required for addressing these concerns/issues is organized and obtained by performing a detailed technical analysis of the standard based on the Zachman framework, as described in the next section. 4.3

Technical analysis using Zachman framework

In the Zachman framework, the columns Who, What, Where, When, Why, and How can also be understood as people, data, network, time, motivation, and function, respectively. This synonymy allows for enterprise model associations to clearly be made with the “5 W’s and an H.” Similar synonymy exists for the rows, where the contextual, conceptual, logical, physical, and out-of-context can be directly associated with an enterprise’s scope, business model, system model, technology model, and detailed representations, respectively. These associations provided additional guidance when using the Zachman framework to support our transition from concerns from the stakeholder’s perspective to answers through a technical analysis. To better explain how the Zachman framework can be used in the technical analysis of a sustainability standard or directive, we will describe an analysis of RoHS (Restriction of Hazardous Substances Directive) [16]. When analyzing a subject matter with the Zachman framework, each cell of the 6x6 matrix should provide an extensive analysis for its designated subset of the problem. Subsequently, it is important to acknowledge that this analysis can begin from any position of the 6x6 matrix due to the independence of each cell. Here we will initially concentrate on the first row, which will analyze the contextual aspect, or scope of RoHS. In analyzing the contextual level, it was important to focus on what the objective was, to provide a scope for RoHS. In defining the scope, we defined the most abstract level of RoHS. This was vital to

understanding when RoHS should be taken into consideration, and stresses the importance of the previous stakeholder analysis. As defined by Zachman, the information model in each cell in the contextual row is a list. These lists provide a high-level scope of the subject matter being analyzed. Figure 2 shows how the understanding of different perspectives achieved during the stakeholder analysis (shown here are “consumer” and “software provider”) assists in the development of the more thorough technical analysis. In evaluating the “What” column of the contextual artifacts, it can be seen that different stakeholders have different needs. As rows are added and the levels of abstraction decrease the separation of stakeholder’s needs become increasingly distinct, making the stakeholder analysis increasingly important.

Figure 2: Stakeholder to Technical Analysis. In first defining ‘What’, we considered the many entities associated with RoHS. This level of abstraction included the materials involved, the products considered, and the information involved. When identifying ‘How’, we took into consideration the Supply-Chain Operations Reference (SCOR) [17] model and identified the Source, Make, and Deliver processes of the supply chain as processes where RoHS becomes pertinent. This high level definition of processes was intentional, so as not to narrow the scope to a point where the RoHS application becomes ill-defined and perspectives are overlooked, yet not broaden the scope to a point where the analysis loses its effectiveness. Continuing along the contextual level, the ‘Where’ aspect of Zachman defined which geographical areas RoHS is active. The ‘How’ aspect was used to identify the parties or organizations to which RoHS is critical. Parties identified included all stakeholders from which perspectives must be considered, including electronics manufacturers and suppliers, government agencies, and customers. The ‘When’ row was used to identify events that will initiate cycles. At the most abstract level, we defined these events as the buying and selling of electronic goods. The ‘Why’ was used to identify the high level goals of RoHS, namely reduce environmental contamination by limiting hazardous waste, and from the perspective of the manufacturer also to avoid penalties and improve brand image. The purpose of Directive 2002/95/EC (RoHS) on the restriction of the use of certain hazardous substances in electrical and electronic equipment is to approximate the laws of the European Union (EU) Member States on the restrictions of the use of hazardous substances in electrical and electronic equipment and to contribute to the protection of human health and the environmentally sound recovery and disposal of waste electrical and electronic equipment. After a carefully executed analysis using the Zachman framework, the scope of RoHS was broken down, providing a transparent

Information and Knowledge Management definition for all stakeholders involved. As the Zachman analysis progresses downward from row to row, the level of abstraction is reduced, as can be inferred from the row labels. To demonstrate these changes in levels of abstraction, let us consider the ‘What’ column. Recall at the highest level of abstraction, the contextual level, the ‘What’ column was used to provide the scope of what RoHS covers: the materials involved, the products involved, and the relevant information involved. The second, conceptual, row is used to define the “business model” used in RoHS. At this level of abstraction, a simple list is no longer used, instead a traditional “business entity-business relationship” model is employed. This level of abstraction provides some detail into how entities associated with RoHS interact. For instance a “product” is composed of an “assembly,” which is composed of a “homogenous 2 material .” As implied by its label, the second row allows for the conceptualization of interactions between entities through relationships, which can be considered as the “semantic model.” These business models differ based on the stakeholder perspective taken. Progressing downward in the 6x6 matrix, the third row provides the logical data model. At this level of abstraction, elements which were once abstract concepts are now considered logical data models. This level of abstraction is where data entities and their relationships exist, where a data entity is a logical representation of an element from earlier levels of abstraction. Here is where an information model, including attributes, of what a “homogenous material” is, can be found. The fourth row is where the Physical Data model is located. This row is technology constrained, so where the third row provided the attributes of a “homogenous 3 material,” it is this row that describes how it is defined . And finally the fifth row, or the detailed row, is where the data definition can be found. Where row 4 defines how a homogenous material should be defined, row 5 is where its actual definition can be found, for instance the composition of the solder used in an electronic product. 4.4

Integrating models in the Zachman framework

The Zachman framework was used to describe RoHS with thirty independent cells (we ignored the last row that denotes actual physical operations), each with content that can be modified without directly affecting the content of the other cells. Although each cell in Zachman framework can exist independently, it is useful to take them in context of the others. In fact, we found this a helpful means for promoting the continuity of the levels of abstraction between columns. For instance, consider the statement “RoHS applies to manufacturers who buy hazardous materials to produce electronic products in Europe.” In this statement, we were able to tie together the ‘who,’ ‘what’, ‘where,’ ‘when,’ and ‘how'” as it applies to RoHS, giving one particular piece of insight into the scope of RoHS. This same practice was repeated often when defining the “conceptual,” “logical,” “physical,” and “detailed” rows for the Zachman analysis. Figure 3 shows the integrated model for describing a business scenario in which a company wishes to manufacture a product for sale in the European Union market. RoHS compliance is an 2

"Homogeneous material" means a material of uniform composition throughout that cannot be mechanically disjointed into different materials, meaning that the materials cannot, in principle, be separated by mechanical actions such as unscrewing, cutting, crushing, grinding and abrasive processes. 3 The maximum permitted concentrations are 0.1% or 1000 ppm (except for cadmium, which is limited to 0.01% or 100 ppm) by weight of homogeneous material. This means that the limits do not apply to the weight of the finished product, or even to a component, but to any single substance that could (theoretically) be separated mechanically.

547 important issue in this scenario. The figure lists the steps the company may follow in order to ensure that they are placing a compliant product in the market. It is easy to see that the individual steps, decisions and processes listed in the figure can be traced to the various cells of the Zachman framework. For instance, “what” types of components belong to this scenario is given by the conceptual and contextual layers (rows 1 and 2) of the “what” column in the framework. The types of manufacturing processes for these components is given by the conceptual layer (row 1) of the “how” column of the framework. The nature of the manufacturing processes that can affect RoHS compliance is given by the logical and physical layers (rows 3 and 4) of the “how” column of the framework. The time point of the component test is given by the “when” column of the framework. Having performed the detailed technical analysis of RoHS using the Zachman framework, we will be able to integrate the models to describe the business scenario in complete detail. 5

AN EXAMPLE TO DEVELOP AN IMPLEMENTATION STRATEGY FOR COMPLIANT CONFORMANCE

The steps required to implement a standard depend on the stakeholder and implementation need. To explain this implementation process, for instance, let us assume that a product manufacturer in the US is interested in having a product (e.g., hair dryer) RoHS compliant. This section breaks this certification into a three step process. In each step, we will discuss how our approach will assist RoHS certification. In this section we will also introduce our Sustainability Standards Portal (SSP) [6] as a means for referencing information in determining RoHS compliance. This online web portal has been developed at the National Institute of Standards and Technology (NIST) to serve as an unbiased source for information pertaining to sustainability standards. This information also includes detailed stakeholder and technical analyses of selected sustainability standards. The information infrastructure will provide valuable guidelines to develop such in-house certification procedure initiatives, avoiding costly consulting fees. An example of how our support can provide these guidelines is given below. Step 1. Acquisition of Knowledge: In this step, the manufacturer is interested in gathering information about the Standard/Directive that is affecting the export of a product or a service. Some of the questions the manufacturer might ask are: What is RoHS? Why get RoHS certified? What product to get RoHS certified? Who would certify? How it is certified? Support: The manufacturer can acquire answers to these questions through our stakeholders’ analysis approach. A RoHS-based version of this approach has been implemented in the SSP (See step in Figure 3). Step 2. Analysis of business and manufacturing procedures: In this step the manufacturer needs to analyze different business processes within the company and model them. Support: The manufacturer would adopt our technical analysis approach of RoHS based on the Zachman framework. For instance, if the manufacturer wants to know who are the people responsible for making sure that a product has less than the specified amount of Lead (Pb) and what roles these people have, then the manufacturer would refer to the ‘who’ column of the Zachman analysis of RoHS (See Table 1 and step in Figure 3). Step 3. Implement and verify: In this step, the manufacturer would develop actual implementation strategies in the form of steps to be followed to get the product RoHS compliant, implement them, and verify the outcome through report and certification. Support: The manufacturer would refer to the information provided in the “who”,

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Information and Knowledge Management

“how,” and “what” columns respectively to identify the certification agency, certification procedure followed and instruments used. While this will differ depending on needs, examples can be found in the SSP (See Table 1).

endorsement by NIST, nor does it imply that these products are necessarily the best for the purpose. This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. Approved for public release; distribution is unlimited. 8

Figure 3: Business scenario: Manufacturing and selling RoHS compliant products. 6 SUMMARY Standards and regulations play a crucial role in realizing the vision of a sustainable world. However, if they are not clearly understood by all parties involved, these standards will fail. It is therefore important to critically analyze sustainability standards by considering different perspectives, and addressing the requirements of all stakeholders. In this paper, we have described a rigorous and organized approach for analyzing and understanding sustainability standards. We first consider a given standard from the perspectives of different stakeholders, establishing a domain of discourse that takes into consideration the concerns of all parties involved. We then perform a detailed analysis of the standard using the Zachman framework, Once we have constructed this repository of information that addresses all the aspects of a standard at various levels of detail, we integrate the information to describe specific scenarios of interest to specific stakeholders. We believe that this organized and detailed approach is essential for sustainable practices in today’s world, and brings together disparate parties with widely different concerns to the same table. Based on this study, we have also created thematic structures for promoting the fast understanding of standards, captured the essence of the performance issues related to sustainability, and created a primitive framework for querying a database of standards information, all of which are publicly available online in the Sustainability Standards Portal. Our next step is to compare these standards to find gaps and overlaps in their domains of discourse. 7

DISCLAIMER

Certain commercial software products or services may be identified in this paper. These products or services were used only for demonstration purposes. This use does not imply approval or

REFERENCES

[1]

World Commission on Environment and Development (WCED) (1987): Our Common Future, Oxford University Press, also Known as Brundtland Report, pp. 43.

[2]

Board on Sustainable Development and National Research Council (1999): Our Common Journey: A Transition Toward Sustainability, National Academy of Sciences, URL: http://www.nap.edu/catalog.php?record_id=9690.

[3]

Sitarz, D. (1998): Sustainable America, America's environment, economy, and society in the 21st Century, EarthPress.

[4]

ANSI Course : Why Standards Matter (2010): URL: http://www.standardslearn.org/coursedetails.aspx?key=4 4.

[5]

Standards.gov: (2010): What are Standards? URL: http://standards.gov/standards_gov/standards.cfm.

[6]

National Institute of Standards and Technology (2010): Sustainability standards portal, URL: http://www.mel.nist.gov/msid/SSP.

[7]

Rachuri S., Sriram R.D., Narayanan, A., Sarkar, P., Lee J.H., Lyons K.W., Kemmerer, S.J., (Eds.) (2010): Sustainable Manufacturing: Metrics, Standards, and Infrastructure Workshop Report, NISTIR 7683, 2010.

[8]

National Research council (2010): Monitoring Climate Change Impacts: Metrics at the Intersection of the Human and Earth Systems, URL: http://www.nap.edu/catalog/12965.html.

[9]

Sowa J. F. and Zachman J. A. (1992): Extending and Formalizing the Framework for Information Systems Architecture, IBM Systems Journal, vol. 31, no. 3, 1992.

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Zachman, J. A. (1999): A Framework for Information Systems Architecture, IBM Systems Journal, 38(2), pp. 449-452.

[11]

University of California, Irvine (2010): Zachman Framework for Healthcare Informatics Standards, URL: http://apps.adcom.uci.edu/EnterpriseArch/Zachman/Reso urces/ExampleHealthCareZachman.pdf.

[12]

Zachman institute (2010): Zachman Institute for Framework Architecture URL: www.zifa.com.

[13]

Panetto H., Baina S., Morel, G. (2007): Mapping the IEC 62264 models onto the Zachman framework for analyzing products information traceability: a case study, Journal of Intelligent Manufacturing, (18) 679-698.

[14]

ISO (2010): IEC 62264-2:2004, URL: http://www.iso.org/iso/ catalogue_detail.htm?csnumber=37892.

[15]

University of California, Irvine (2010): Zachman Framework for Computer Security, URL: https://apps.adcom.uci.edu/EnterpriseArch/Zachman/Res ources/AppliedToSecurity.pdf.

[16] B-Lands Consulting (2010): Restriction Substances Directive: URL: www.rohs.eu. [17]

of

Hazardous

Supply Chain Council, Inc. (2010): SCOR Frameworks, URL: http://supply-chain.org/resources/scor.

Sustainability through Next Generation PLM in Telecommunications Industry 1

Julius Golovatchev , Oliver Budde 1 2

2

Detecon International GmbH, Bonn, Germany;

Research Institute for Rationalization and Operations Management at RWTH, Aachen, Germany

Abstract Sustainability plays in telecommunication industry a major role. Product lifecycle management (PLM) safeguards the value creation process of companies therefore PLM can be considered as the strategic weapon to achieve the goal of business sustainability. The authors give reasons why the holistic view on the PLM is critical for an efficient and sustainable PLM and present an integrated approach for developing of products and services compatible with the requirements of sustainability and profitability for the business. Keywords: Next Generation Product Lifecycle Management (PLM); Telecommunications Industry; Complexity Management

1

MOTIVATION

Product Lifecycle Management - PLM is the activity of managing a company’s products across the complete lifecycle, from the early stages of conception to the final disposal or recycling of a product. From this definition, a strong interrelation between the value creation process and the PLM of the company can be deduced (compare [1]). Safeguarding the value creation process leads to a sustainable growth. A valid approach for implementing PLM is therefore necessary for achieving sustainability on a company level. When companies seek to reduce waste during the product life cycle by considering lean management principles then the social and ecological dimensions of sustainability (compare [2]) can be achieved. As Grieves [3] points out PLM drives the next generation of lean thinking and therefore motivates our design for a holistic approach for a sustainable development of hybrid products in the telecommunication industry (compare [4]). The products in the telecommunication typically consist of several modules that in sum create the customer benefit (e.g. Multi-Play products). Each module embodies its own lifecycle, which implies an additional product complexity in terms of module design, module management and module removal from the product. Especially in telecommunication industry sustainability plays a major role, since long-lasting investment decisions have to be made for example in new radio transmission technologies like WIMAX or UMTS. Main social challenges currently facing the telecommunications industry as being the responsible handling of highly sensitive customer data, the protection of children and young people from media content which is pornographic or glorifies violence, and measures to narrow the digital divide. On the environmental side climate protection, the energy efficiency of telecommunications networks, extending the service life of equipment, equipment take-back arrangements and the demand for a reduction in the toxic substances are key topics. Sustainability and energy efficiency is not a trend that will vanish anytime soon. It is an emerging industry sector.

For making the linkage between PLM and sustainability clearer, we have to look at the term sustainability first. Probably the most popular definition of sustainability comes from the World Commission on Environment and development in the report “Our common Future”, also named as the Brundtland Report: „Sustainable development seeks to meet the needs and aspirations of the present without compromising the ability to meet those of the future“ For companies profitability is the cornerstone of their activities. By taking the previous definition of sustainability into account we define business sustainability as A pro-active approach to ensure the long-term viability and integrity of the business by optimizing resource needs, reducing environmental, energy or social impacts, and managing resources while not compromising profitability. As stated in the beginning of this article PLM safeguards the value creation process of companies therefore PLM can be considered as the strategic weapon to achieve the goal of business sustainability, if it fulfils the premises on reducing of waste (not only physical waste, but the whole concept of waste), elimination of harmful emissions; use of renewable energy, utilizing resource efficient transportation throughout the product life cycle. To develop, produce, maintain and sell physical products, companies have to use material, expend energy and use people to do so (compare [3], p.7). By following the lean management principles the efficient and effective use of these resources throughout the product life cycle is the main goal and needs to be addressed in a valid Next Generation PLM-approach. In the following sections of the paper we will first present the four building blocks of a holistic Next Generation PLM-approach witch was developed for the telecommunication sector and then present a short case study demonstrating the impact of our model in the contemplated industry.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_95, © Springer-Verlag Berlin Heidelberg 2011

549

550 2

Information and Knowledge Management HOLISTIC PLM-APPROACH

The integrated Next Generation PLM Approach consists of four components depicted in Figure 1.

PLM-Strategy

Next Generation PLM - Holistic View Lifecycle Oriented Portfolio Management Customer Need Management

Value Chain Integration Operational PLM- Process Empowerment of People

Supports

PLM-Process

Determines Multi-Project Mgnt System DMS Collaboration Tools WFMS PDM

ProductArchitecture

Shapes

PLM IT-Architecture

DSS

Strategic Process Management

Process Model Product Model

IntegrationArchitecture

Product Data Information Framework

Figure 1: Four components constituting the integrated Next Generation PLM-approach 2.1

PLM Strategy

The purpose of the domain ‘PLM strategy’ is the alignment of the innovation and marketing strategy with the overall PLM strategy to allow for a synchronization of the product development, market management and retirement processes. In order to do so, a strong link to customer needs management has to be ensured, as well as the safeguarding of lifecycle-oriented product and project portfolio management – controlling and monitoring the innovation and product pipelines. A strategic PLM process management defines the cornerstones of the PLM process by introducing PLM process variants according to innovation level and by implementing consistent PLM process reporting (compare [1], p.14). . There are three different but supplementary building blocks of PLM Strategy: Value oriented portfolio management Increased complexity of product marketing in the telecommunication company without an appropriate and efficient data foundation results in a lack of business transparency and low synergies in the value network. The modular structure of the portfolio promotes the use of common parts in the production processes, increasing the ratio mass production to overall production. Strategic alignment and value based product portfolio management enable an effective product lifecycle management. Focusing on clearly defined products makes a significant contribution to effective portfolio management. The products can be positioned without overlaps and in accordance with market demand. Value oriented portfolio management helps to prioritize product investments (eg. under consideration of environmental and sustainable development). Sales and marketing departments benefit from the increased transparency of the product range and the improved comprehensibility for the customers. Customer Needs Management Customer Needs Management incl. Requirement Management builds interface between PLM and Customer Relationship Management (CRM) and gives input for the collaborative product design. The marketing research also shows that customers expect that products will not negatively affect their environment. To respond to drivers for customer purchasing decisions, telecommunication companies should also include environmental performance in consideration. The effective Customer Need Management ensures that product content matches customer

requirements and allows delivering more personalized products by facilitating mass customization. Reporting and controlling process regarding the product lifecycle management process The referencing of different divisions (sales, resources and production planning; cost/profit accounting, etc.) to a standard product definition lays the foundation for the application of important controlling instruments (e.g. product success accounting). The unambiguous correlation of the basic data to business management indicators (incl. Environmental Key Performance Indicators) along the lines of a standard product structure provides staff and management with precise and timely information about all of the critical success factors that help staff and management to make the right decisions at the right time. Implementation of these three building blocks combined with a modular product data structure ensures the “state-of-the art” Lifecycle Value Management: 

Individual product performance information available at realtime.



Product Manager retains product accountability throughout life cycle.



Strategy for product growth, maturity, and withdrawal stages is defined up front.



Product and service replacement strategy also considered.



Systematic (e.g. annual) review and clean-up/optimization of product portfolio.



Accountability and responsibility for environmental performance within all levels of the business is created



Company leadership with environmental design goals is presented, that increase product sales through improved environmental performance.

2.2

PLM IT-Architecture

Many present quality deficiencies in the product development in the telecommunication industry originate from a diffuse definition of products as well as from the inconsistent view on the object “product“. The studies show that 80% of the total cost structure over a product’s lifecycle is pre-determined during the concept and design phase. Especially in the service industry, the product (or service) should be clearly and precisely defined to be developed, commercialized and to be understood from the customer. The product as the main subject of the process needs to be defined and this definition of product should be taken from the customers´ perspective. A product is an entity the customer perceives in its entirety and is characterized by being offered to a market place. Only with such definition of their products the service companies can stay ahead of their competitors and make their product and services clearly identifiable to consumers. From internal point of view, there should be a constant product definition with the overall product lifecycle and for all business process. The product of the telecommunication company, in the eyes of endusers, is becoming an unified “experience” that is based on the delivery of multi-dimensional packages (such as in the telecommunication industry: voice, video, and data as an integrated package across mobile and fixed infrastructure which, deconstructed reveals multiple layers of hardware, software applications, and services ). The precise definitions of the complete product range and their categorization still remain a problem. For example, in the telecommunication industry essentially four categories of products can be differentiated: market product (service), standard solution, customized (individual solution) and

Information and Knowledge Management bundle. All offered products and services can be assigned to one of the mentioned categories. Product definition is not simply a reflection of the engineering design. It also includes the entire set of information that defines how the product is designed, manufactured, operated and managed on the market and finally withdrawed from the market. This product definition is continually updated throughout the entire lifecycle from idea generation until withdrawal from the market and it is the same for all business processes. This view allows considering the product as a core information object (CIO). Product definition should be furthermore detailed by the companywide specific product architecture to decrease complexity costs in the service industry. Such architectuure defines the product (service) on an even more detailed level for the optimization of time to market and decreasing of resembling components. The purpose of the domain ‘product architecture’ is to enable product component reusability by defining constraints and rules for decomposing the product functionality into meaningful modules with coherent product-data models – critical for ensuring mass customization of telco products. For communication service providers, the product structure includes modelling the product service modules from a market perspective, as well as FAB processes and technical resources modules. A product data information framework ensures efficient information logistics in order to translate the conceptual models into operations. Already in the specification of products the environmental aspect has to be integrated. Product architecture is the basis for standardization and modularization of products (services). Modular product data structure as core element of product architecture ensures linking the sales perspective to the internal (production) perspective in relation to the offered products and services. The main aim of introducing a modular product structure is the optimization of the product development in the telecommunication company. The unique product Architecture and the corresponding processes should be implemented by considering the existing processes, company structures, cultures and environmental issues. Requirements from the affected functional areas flow into the definition of the product data structure (see Figure 2). One master product data management fits all needs of the main processes and its interfaces. The right Product Architecture leads to simplification, cost optimisation and sustainability of “product and service engineering” through the re-use of the production and service modules, shorten “time-to-market”, avoiding overlaps in development and reduce technical variance, availability of the product modules range of all service lines (factories) for all division of the telecommunication company. 2.3

PLM IT-Architecture

The foundation for moving a product through its complete lifecycle beginning with the product idea and ending with the product removal from the market is a solid PLM IT-Architecture, that is customized for the company-specific PLM- requirements. In our perspective, such a PLM IT- Architecture must support the PLMprocess in the dimensions: (1) Decision support, (2) Operational support and (3) integration of supplemental business applications. A standardized off-the-shelf PLM-System is therefore not the tool of choice as Ausura and Deck (compare [5]) point out. Instead we suggest to rely on a PLM IT- Architecture that re-uses, respectively customizes existing IT- components as far as possible. In the next paragraphs a description of the essential IT-components is given that build up the PLM IT- Architecture. Decision Support System (DSS):

551 The main purpose of a DSS is to gather and consolidate data from operative systems in order to provide the senior management with aggregated information regarding the product lifecycle. The Computer Aided Selling (CAS) module provides functionality for the product configuration and product pricing. The component Strategic Resource Management focuses on the long-term resource capacity planning on a strategic level. Product portfolio management aspects are covered with the last Value Management component. Operational Support System (OSS) On the operational level the PLM- process execution is supported by the OSS. The Workflow Management Systems (WFMS) enables a higher degree of process automatization. Especially in the context of distributing and releasing unstructured content like a product specification in cross-functional teams, the WFMS plays an essential role through a strong link to the Product Data Management System (PDM). The Product Modelling System and the PDM are closely coupled. The former defines the product structure, in which types of modules the product is decomposed into. In the database context this functionality is similar to the schema definition. The PDM-systems stores all product relevant data according to this definition and provides different views for each stakeholder e.g. marketing and engineering. The Multi-Project Management System as well as the Collaboration Tools are instruments for managing the product in different phases in a collaborative environment. Integration of supplemental business applications A PLM IT-Architecture is supposed to hold the promise of seamlessly integrating and presenting all information produced throughout all phases of a product’s life cycle to everyone in an organization, along with external business partners. For ensuring this functionality, an EAI-approach has to be implemented. According to recent research activities a Service Oriented Architecture (SOA) is most suitable to integrate the business applications from external partner e.g. suppliers as well as integrating the own business applications like ERP, CRM etc. in order to fulfil the promise of seamless integration for becoming a real-time enterprise (compare [6]). 2.4

PLM-Process

The importance of well-designed processes has been stressed by many authors, e.g., Hammer and Champy (compare [7]). Since PLM plays a crucial role for organizational success in such highly competitive markets as the telecommunications industry, the relevance of an adequate PLM-process is self-evident. As indicated in the earlier section, the requirements on such a PLM-process have changed. Long-living products with a limited variance in their product structure along their lifecycle are becoming less and less relevant. Those products have been replaced by a new type of product-service-system, that is characterised by the fact that it consists of a bundle of components/modules, each with a different lifecycle and a high variance in functionality. As the product concept has changed, the PLM-process has to be adapted accordingly regarding sustainability and environmental issues. Companies in the telecommunication industry should take a disciplined, analytical approach to developing new products (services), relying on targeted customer input just as companies outside the service sector do (compare [8], p 25) . The main design goals of this approach is 

to facilitate the execution of this collaborative process (efficiency goal) and equally important to align the activities with the strategic goals of the company (effectiveness goal) under consideration of product environmental performance and

552 

Information and Knowledge Management to develop organizational structures, that align customer expectations for product functionality and price with regulatory requirements, environmental performance and company business goals.

Our PLM-Process approach is based on three principles: Enhanced Stage Gate Approach, Multi-Perspective, Metrics based Management. These principles are subject for further explanation in the following paragraphs. Principle One: Enhanced stage-and-gate approach Most telecommunications companies utilise the Stage-and-Gate approach as a conceptual and operational model for the development, marketing and removal of a product during its lifecycle. This approach is very meaningful to the management because it restricts investment and expenditures in the next stage until the management is comfortable with the outcome of the current stage. The gate can be effective in monitoring and controlling product quality as well as development progress and costs. The ‘typical’ PLM process in the telecommunications industry consists of several stages – from idea generation to withdrawal from the market. This structure is oriented at the lifecycle of the ‘standard’ telecommunications product, and has been validated in several projects by Detecon International – primarily in the telecommunications industry. Every stage consists of a distinct number of activities (organised in perspectives, refer to the next section), which have to be accomplished by specific process stakeholders at the given phase. The entrance to each stage is a gate; these gates control the process much like quality control checkpoints. Each gate is characterised by a set of deliverables as input, a set of exit criteria and an output. Gates are manned by senior managers that form the so-called “Product Board”. The product board acts as a gate-keeper that evaluates the results from one stage by a given set of criteria. On the basis of this evaluation, the product board can either decide whether the product idea proceeds to the next stage, re-starts at the previous stage or is archived. The standard Stage-and-Gate PLM-Process with its ‘frozen’ gates has several characteristics that lead to significant problems (e.g., time-to-market delay) in the development of low complexity telecommunications products as well as high innovative extended products and solutions. Weaknesses of the Stage-and-Gate model, such as narrow criteria, long review preparation time and slow and serial decision-making provide reason for the necessity of the new PLM-Flex and PLM-Fast approaches. The process solution for standardised products could be a simplification and automatisation of gate decisions and elimination of some gates/stages. For extended products with a high level of innovation, the Stage-and-Gate approach exhibits additional weak points. Stage-and-Gate processes force fundamental project decisions to be made earlier than necessary, thereby restricting flexibility to respond to change and increasing the cost of change. Moreover, flexible development techniques are more suitable for development projects rather than phased approaches. The introduction of ‘fuzzy gates’, which allow for ‘go forward’ decisions to be made in the absence of complete information – with the expectation of achieving specified outcomes at a later date – does not solve the problem in this case. A newer alternative to Stage-and-Gate processes is the BoundingBox approach, which is essentially a Management-by-Exceptions technique in which certain critical parameters of the project, such as profit margin, project budget, product performance level, and launch date, are negotiated as the bounding box. Then, the team is free to move ahead unimpeded as long as it stays within the box.

The adoption of Stage-and-Gate and Bounding-Box models allow to develop a new approach for designing variants of a PLM-process in the telecommunications industry and for better integration of sustainability targets in the product development. Principle Two: Multi- Perspective Product Lifecycle Management has always to cope with the conflict of objectives between the product marketing and the technical side. Several case studies have documented that this conflict often results in product failure in the market. Either because the product specification is too much technical driven and therefore far from the market demand or the product marketing has defined product specifications without collaborating with the technical department about technical feasibility beforehand. For solving that conflict of objectives three perspectives on the process have to be taken into account in order to ensure an efficient coordination and collaboration of the relevant departments or business partners. In the market perspective all activities are assigned to that relate to the product marketing. Referring to the telecommunication industry, typical tasks like the definition of product specifications and the management of the product on the market-place belong into this category. By contrast the technical perspective subsumes all technical or production- oriented activities. Additionally the financial implications of moving the product through the life cycle are grouped in the financial perspective. Principle Three: Metrics based Management In addition to the process definition the organisational component must not be neglected. Since products, and consequently the PLMprocess, become more complex and involves internal as well as external partners along the value chain, there is a greater need to balance top- management control with the empowerment of selfmanaged, cross functional teams. As a prerequisite for achieving this balance, the company has to implement a metrics-based management approach in which teams are measured on strategic performance indicators such as development cost, time to market, customer satisfaction and environmental issues. The definition and selection of the indicators is critical for the successful implementation of the PLM-concept. By setting the weights properly the teams will self-steer to the greatest short- and long-term profit, which results in less coordination effort and efficiency gains especially in the context of for cross- departmental teams. 3

CASE STUDY

A renowned company in the telecommunications industry carried out an extensive restructuring program which would enable it to maintain its position in a deregulated market environment. The objective was on the one hand to convert the previously technical driven approach for the product design (i.e., their orientation towards technical performance features) to an approach focusing on the customers’ needs and requirements. On the other hand, the aim was to develop and implement the integrated management approach - Next Generation PLM. In the initial situation the PLM and the platform was not “state-ofthe-art“ (eg. no withdrawal phase, missing of decision gates, long “time-to-market” etc). A portfolio management process was not designed and implemented. The current portfolio structure was oriented on the organizational or technical structure and not organized from the customer’s point of view. The product portfolio was characterized by a large number of product variants and features. All these products needed to be handled individually from an IT management perspective. This broad variety of products needed to be realized and implemented within all operative processes, IT-applications and –systems as well

Information and Knowledge Management as sales information tools. This led to an enormous complexity that impedes the maintenance of IT-landscape and the management and optimization of the processes. No integrated IT-solutions were available at company and at its affiliates. During the project the integrated PLM approach valid for the company and its affiliates was developed. Implementation of Next Generation PLM at this company showed the valuable benefits for solid product development, marketing and strategy:

553 5

This work was in part supported by the AIF (German Federation of Industrial Research Associations) under the sign EBA-10760/09 in the European Cornet Project Eco2Cut. 6

Sound marketing strategy due to the early recognition of market needs, standardized information and environmental issues.



More detailed input for controlling for exactly allocation of revenue and costs to products.



Simpler allocation at cost centres and cost unit.



Introduction of the harmonized product portfolio for all national and international affiliate companies.

Product Architecture: 

Easier know how exchange and using of the “same language” during product development as well as fast and efficient communication between international partner.



Introduction of the harmonized product definition and product portfolio for all national and international affiliate companies.



The product portfolios across all of the company were to be reduced by 50% and integrated into a modular structure.



New ways to re-use of materials.



Adoption of the product data platform at all international subsidiaries.

REFERENCES

[1]

Golovatchev, J.; Budde, O. (2010): Next Generation Telco Product Lifecycle Management: How to Overcome Complexity in Product Management by Implementing BestPractice PLM; Published by Detecon, Bonn.

[2]

Lehtonen, M. (2004): The environmental-social interface of sustainable development: capabilities, social capital, institutions, Ecological Economics, vol. 49, no. 2, pp. 199 214.

[3]

Grieves, M. (2006): Product lifecycle management, McGrawHill, New York [u.a.].

[4]

Wöhler-Moorhoff, F.; Dieter, S.; Schwill, M. (2004): Telco 2010. Telekommunikation im Wandel: Die Karten werden neu gemischt. Published by Detecon. Bonn.

[5]

Ausura, B.; Deck, M. (2007): The new product lifecycle management systems: whar are these PLM systems? and how can they help your company do NPD better? Visions Magazine. Online available at http://www.pdma.org/visions/jan03/plm.html, last visit 26.01.2007.

[6]

Abramovici, M.; Sieg, O. (2002): Status and Development Trends of Product Lifecycle Management Systems. In: Proceeding of International Conference on Integrated Product and Process Development, Wroclaw, Poland, p. 2122.

PLM Strategy: 

ACKNOWLEGEMENT

PLM Process 

Acceleration time-to-market up to 25% by several product groups.

[7]

Hammer, M.; Champy, J. (2003): Business Reengineering, 7th ed., Campus-Verlag, Frankfurt/Main.



Reduction of quantity energy and material used in product development and production up to 20%.

[8]



Efficient cost savings along the PLM process by using standard support system and re-using of modules and components (process costs saving up to 170 m USD/year in the product realization phase).

Golovatchev, J.; Budde, O.; Hong, C. G. (2010): Integrated PLM-process-approach for the development and management of telecommunications products in a multilifecycle environment. In: International Journal of Manufacturing Technology and Management, Jg. 19, H. 3, p. 224–237.



Effective and similar procedure of innovation and market management projects execution.

PLM IT-Architecture 

An implemented shared platform for document and project management.



One physical server is used to support separate product lifecycle management processes in all divisions and subsidiaries.

4

CONCLUSION

In this paper the authors introduced a holistic Next Generation Product Lifecycle Management - PLM approach consisting of a process model, product meta-model, IT-architecture and a lifecycle value management concept. By applying the model to a real world case, the potential of the approach could be demonstrated. The customer can be sure that through the implemented Next Generation PLM all his wishes and the requirements such as environmental protection, data protection are considered and implemented in the company’s products and services in the systematic, transparent, and manageable way.

Challenges of an Efficient Data Management for Sustainable Product Design 1

1

1

Thomas Leitner , Marek Stachura , Andreas Schiffleitner , Nick Stein 1

1

KERP Center of Excellence Electronics & Environment, Vienna, Austria

Abstract Legal frameworks regarding usage of substances placed huge demands on company’s data management. Data exchange provides technical and logistical problems. Some online systems offer core collection of data. This central method means manually interfacing with an internal system, problems with data security and intellectual property protection and dependence on externally controlled systems. A key problem with existing systems is the compatibility between them. Currently, no data exchange between systems has been possible. The paper shows recent developments and possible solutions in this area and provides the first solution that will implement all requirements of a modern system. Keywords: Sustainable Development; Material Data Management; Laws

1

BACKGROUND: CURRENT SITUATION

Production companies usually operate on a global market, therefore they need to meet different requirements throughout the different regions of the world, countries or districts (e.g. in Europe with Registration, Evaluation, Authorization and Restriction of Chemical substances - REACH and Restriction of the Use of Certain Hazardous Substances in Electrical and Electronic Equipment - ROHS, in Asia, China and Japan RoHS or the Asian REACH adaptations, or the Toxic Substances Control Act from USA or California's ROHS). This demands a huge effort through the introduction of the necessary and usually very specific legal knowledge on the one side (like interpretation and fulfillment of the requirements for the target markets) but on the other side a massive data flow (like the material data exchange in the complex supply chains). Although the legislative sector increased the requirements permanently consequently in the development stage more aspects have to be considered through product design. At the same time the constrained companies have to rapidly and cost-effectively launch its product on the world market to remain competitive (permanently shorten timeto-market margins while keeping lower prices). The balance between the very complex (and growing) legal requirements and the market pressure increases the risk that compliance with the law, for some products will not be secure enough. This pressure comes from the complexity of legal requirements around the world and is connected to the amount of data which has to be managed with a permanent reduction of time for analysis of different requirements and relevant data. That situation can be very critical for the company. The risk of regulatory non-compliance increases with time as the regulations do not stay static and will be continuously developed and adapted (e.g. regularly extension of the SVHC-list of REACH). For these reasons, manual processing of the compliance problems is, in everyday operation, not feasible. The first software tools that consider the issue of legal compliance for products and try to solve this problem with varying success are already available on the market.

2

OVERVIEW OF SOFTWARE SYSTEMS FOR MATERIAL DATA MANAGEMENT AND LEGAL COMPLIANCE

For supply chain communication and legal compliance checks, and to cope with sustainability and Corporate Social Responsibility (CSR) strategies, different types of solutions are currently used in the industry. The easiest way to check the legal compliance of a product considering the supplier of parts, components and auxiliary materials, is the outsourcing to a third party service provider. In the present transition period (launch of new legal regulations like REACH) outsourcing is a common way and can be a practicable solution in this stage. However as a durable/long term solution for a production company it is not feasible, due to cost reasons (transaction costs). In that case an automated data management is not possible. Hence some big companies developed their own company-centric solutions connected to existing PDM (Product Data Management) and PLM (Product Lifecycle Management) systems. The flexibility, technical options and automation of processes are, in that case, almost unlimited but the cost is not portable for smaller companies. On the other side a number of existing online platforms offer standardised functions with centrally held databases with component/material information. Some of them include legal compliance information in regards to specific legal standards. Usage of these systems usually means the outsourcing of critical know how. These systems have generally no concept for handling incomplete data (it is in practice implausible that every supplier worldwide would upload their data on time or at all). Further important disadvantage of these systems is no flexibility to individual requirements. Big global PDM system providers have started to launch solutions for data management with legal compliance support. But none of them currently provides an effective industrial “ready to go” solution. Table 1 summarises the advantages and disadvantages of the above described different systems and services (with some examples of sources).

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_96, © Springer-Verlag Berlin Heidelberg 2011

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Information and Knowledge Management Type of Solution Outsourcing to a third party service provider

555

Advantage Flexible, fast, low investment cost

Disadvantages

Examples (& Sources)

High transaction costs, no data integration into internal or external systems, no automation of recurring processes, no economies of scale, outsourcing of critical know-how and confidential information, no sustainability or CSR function

- www.kerp.at - www.environlex.com - www.greensofttech.com

Self-developed, proprietary companycentric systems

Tailored to individual requirements, connection to an existing PDM, flexibility,

Very high implementation costs, very high legal knowledge, limited possibility to re-use existing data on the supplier side,

- Motorola Materials Disclosure (http://responsibility.motorola.com)

Online Platforms

Simple to use, Re-Use of existing data

Outsourcing of critical know how, lack of concept for incomplete data; missing strategy for data maintenance, no support for supplier communication, no flexibility to individual requirements

- International Material Data System IMDS (http://www.mdsystem.com)

- Nokia Substance and Material Management (www.nokia.com)

- China Automotive Material Data System CAMDS (/www.camds.org) - BOMCheck (www.bomcheck.net) - Part Mminer (www.partminer.com)

In-house Database

good position for integration to their own respective PDM system

Lack of integration into all other systems, and missing functionality (user and task support)

- SAP “C2P compliance for products” (www.sap.com) - PTC “InSight” (www.ptc.com) - Siemens UGS “TeamCenter” (www.plm.automation.siemens.com)

Table 1: Overview of systems for material data management and legal compliance. 3

CONCEPT OF A DATA MANAGEMENT AND COMPLIANCE SYSTEM

In the electronics industry there are a number of parallel systems for the communication, changing of material data and compliance checks in the supply chain. This is to be expected because the number of suppliers in this field is almost unlimited and a joint system for all could not be achieved until yet hence it is in the future not realistic to expect an united branch solution (as the practice has shown). Most production companies prefer to develop their own or to join different systems (see chapter 2). Therefore, a flexible exchange of information between the systems is needed. The exchange of information shall take place between the commercial software solutions, such as IMDS and BOMcheck, the existing inhouse IT environments and between various public data systems, such as the European Chemicals Agency (ECHA) or the German hazardous materials information system (GESTIS). The software integration tool, iPoint Compliance Agent (IPCA), implements this approach. The system accesses the existing component, material and substance data throughout the value chain. Additionally, for the communication outside of existing systems iPCA offers a module for data delivery/import e.g. the Supplier Entry Portal (see Figure 1). Figure 1 shows the core modules of iPCA with an expanded material and supplier management functionality, including the ability to connect and communicate with the in-house PDM/PLM system. Connection with supplier’s own systems is possible via Supplier Entry Portal (data communication with supplier). Here special interfaces allow for data to be uploaded from the supplier’s own system or through manual data input. Further interfaces connect the system with other third party systems (like “EnvironLex”, the European Chemicals Agency ECHA or the German hazardous materials information system GESTIS). Additionally an agent technology searches the available data online which is provided by supplier.

With the iPCA an open communication between different systems is implemented. Thereby a corresponding user administration with clearly defined rights has been developed. This ensures high data security (intellectual property), while providing filtered and taskoriented access to the required data. In order to effectively secure the intellectual property of the manufacturers, the iPCA application runs locally on the in-house system. Thus, all product-specific data (bill of material, specifications, compliance documents, etc.) are saved and managed exclusively on the in-house PDM systems.

Figure 1: Integration of systems in iPCA. Figure 2 shows the complete process of conformity assessment by iPCA. The compliance check of a product is started by the user (legal or quality managers) by automatically importing the bill of

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material (BOM) from the in-house PDM system. The input data will be automatically imported and verified by iPCA. The data check includes both the correctness of the individual items in the bill of material (that means questions like completeness of parts, naming of used units, correctness of part numbers etc.) and, for all components, a part number search will be conducted in the system database. If the component is already saved in the system and contains sufficient supplier information it will be identified and used for the current and future bill of material analyses and compliance checks. For new, unknown components or components with insufficient information, the appropriate suppliers will be asked to deliver the relevant information via the Supplier Entry Portal (SEP). This way the system constantly monitors information already existing in the system or available on publicly held sources. The input information (material declaration, conformity certificate, negative declaration, etc.) will be checked for plausibility and completeness by the user and by positive results saved in the system (that means questions like naming of substances, used units, form and contents of specification related to a given regulation etc.). Otherwise a further query will be sent to the supplier. The process of information collection is automated and the user interaction is reduced to a necessary minimum (input data control). In the next step the complete bill of materials will be checked for compliance with pre-defined legal requirements (e.g. ROHS, REACH, ELV etc.). That means, for example, that the legal requirements (e.g. restrictions of use of specific substances according to REACH) will be indentified, calculated and compared to the current limits defined by the regulation. If a substance included in a sub-part exceeds the tolerable concentration (defined by regulation) a warning and an adequate report will be create by the system. Changes in the legislation are supported by experts/system managers and regularly updated. A completed compliance check must be approved by user before saving the information in the in-house PDM system. Based on the BOM proved and the generated information the relevant reports will be created automatically by the system (e.g. MSDS, reports for public regulators, declaration letters etc.). The iPoint Compliance Agent organizes, and manages the entire process of information collection, integration into in-house systems, analysis and reporting. Legend User-Interaction System Automatic Supplier - Interaction

4

PRODUCT DATA MANAGEMENT FOR SUSTAINABILITY

Environmental considerations are becoming increasingly significant in the product development process. As a result, the developer must also consider the product’s environmental characteristics through the whole life cycle. The iPoint LCA Module provides a user-friendly tool which enables the user to swiftly generate a detailed product image of its entire life cycle (see Figure 3). This enables the user to calculate the environmental impact caused by the product and take action where necessary according to ISO 14040. A huge detailed set of environmental data is needed for a comprehensive analysis of products. Using the iPoint LCA Module means no more tedious research. The iPoint LCA Module connects to an existing database and integrates the data into the structural product model. According to Figure 3 the database offers prepared recycling and disposal process data. In this case data input from the user is not necessary. The recycling performance of the defined product will be calculated automatically using the given product material data and using the process data stored in the database (see “automatic by material flow” in the Figure 3). The built-in wizard mode helps to minimize the time needed for user inputs and makes the using of the iPoint LCA Module really easy. So the wizard helps to find the relevant processes for the material production and manufacturing stages (see “selection of predefined processes” in the Figure 3) and to define the parameter of the use stage (like energy consumption, maintenance material, etc. in an easy way – see “define user parameter” in the Figure 3) The degree of product assessment can be set independently to the product or individual assemblies and components. Of course it is possible to add fast and easy, unique and individual LCA processes.

Compliance Agent Data Import (PDM) Material library

Data Check

Process library

Data

Data request to supplier

Input

Entrance test / data confirm Documentation Save Risk Management

LCA library

(MSDS, etc.)

selection selection ofof selection of predefined predefined predefined processes processes processes

define automatic selection of define use automatic selection define use use automatic selection phase phase by by material material phase predefined of material of parameter parameter flow flow flow parameter processes predefined predefined processes processes

automatic automatic automatic by by material material material flow flow

Wizard Life Cycle Impact

material production

manufacturing

use

recycling

Calculation Eco indicator 99

Compliance – Check Feedback to PDM

(RoHS, REACH, etc)

(Data Saving in PDM)

50 40 30 20

fossil fuels

10

Results

0

ozone layer depletion

ecotoxicity

Data Passing Creation of Reports

mineral extraction

acidification

disposal

desig n relevant inform ation

Data Declaration/Export: (Substances, MSDS, etc)

the development of a product. For example the material specification build an appropriate basic information for a Life Cycle Assessment of products, or the type and amount of auxiliary materials used e.g. in production and can be later used for the optimization of the environmentally performance of production processes. Moreover, the information about the origin of components could be used for further optimization of sustainability aspects.

climate change

(substance/preparation/part etc)

(Self-Declaration, MSDS etc.)

Figure 2: Process flow to compliance checks by iPCA. As well as the compliance check, the information collected in the system gives a good basis to provide the sustainability strategies in

Figure 3: Work flow for LCA with the iPCA. As result of the analysis an eco profile is available. Different indicators like Global Warming Potential (GWP) or Cumulative Energy

Information and Knowledge Management

557

Demand (CED) can be calculated. These results are available for customers and public authorities via an export function. As part of the iPoint Compliance Agent materials management system, the RRR module (Reduce, Reuse, Recycle), provides the means to quantify precisely these issues. It supplies the developer with information on end-of-life product characteristics, which can otherwise only be compiled through the expensive process of physically disassembling a prototype. Thanks to the product’s structured presentation and its pre-loaded recycling profiles, the occasional user will find it simple and efficient to use. Furthermore, using the tool for complete material flow simulation, expert users can exploit the full range of RRR calculation opportunities. The recycling profiles used in the calculations contain essential end-oflife technical and financial data on recycling and disposal processes. This makes it possible to conduct an assessment of end-of-life properties for various markets and technologies without additional modeling costs. 5

CONCLUSION

A modern data management in business should not only rapidly and efficiently collect and evaluate the necessary data but also be able to use the full potential of the given information portfolio and thereby protect the sustainable existence of the company and its products. Furthermore, this system should be at the forefront of innovation, obtaining an advantage in competition on the market. With the base of legal accomplishment being effectively covered the Compliance Agent takes the next step into the modern sustainability of products and production organizations. This step will be done with a minimum of additional effort because of a very efficient management of the given information (e.g. information in the house intern PDM system and different external sources like for instance the “EnvironLex” as mentioned chapter 2) and accessible data (e.g. the required supplier information) (see Figure 4). According to a recent analysis of global active companies; sustainably oriented organizations have a clear higher longevity and increased development opportunities in the global market. Figure 4 lists the system requirements and its implementation by iPoint Compliance Agent. Supplier Information

PDM Information

Extern Sorces

(e.g. material declarations)

(e.g. BOM)

(e.g. IUCLID, GESTIS, ..)

Material Data Management

REACh, RoHS etc.

RRR

LCA

Further Aspects (?)

Legal Conformity

Recycling Parameters

Environmentally Information

?

Product Design Optimization

Figure 4: iPCA overview about Data and functions.

6

LIST OF REFERENCES

[1]

Hargroves, K.; Smith, M.H. (2005): The Natural Advantage of Nations: Business Opportunities, Innovation and Governance in the 21st Century, Earthscan, London.

[2]

Ottman, J. (2005): Beyond New and Improved - New frontiers of Design Innovation, Green@Works

[3]

Manenti P.; Parker R; Micheletti G. (2009): The business case for environmental excellence is real, IDC/Atos Origin.

[4]

International Standard ISO 14040 (2006): Environmental management–Life cycle assessment–Principles and framework.

[5]

International Standard ISO 14044 (2006): Environmental management–Life cycle assessment–Requirements and guidelines

[6]

Salhofer S.; Schiffleitner A. (2009): “Relevance of recycling processes for complex products”, SETAC Europe 15th LCA Case Studies Symposium.

Product and Policy Life Cycle Inventories with Market Driven Demand: An Engine Selection Case Study 3

1

2

3

4

Hillary Grimes-Casey , Carol Girata , Katie Whitefoot , Gregory A. Keloeian , James J. Winebrake , Steven J. Skerlos 1

2

1,2

3

{ Mechanical Engineering, Design Science, Natural Resources and Environment}, University of Michigan 4

Public Policy, Rochester Institute of Technology

Abstract This paper introduces consequential life cycle assesment with market driven demand (LCA-MDD) to permit endogenous estimation of economic effects that are important in evaluating the environmental characteristics of product and policy design options. While the derivation of a computational LCI-MDD framework is shown to be straightforward, a major challenge is appropriately managing and communicating the uncertainties. To better understand and explore these uncertainties, this paper develops a case study that estimates the life cycle greenhouse gas emissions associated with selecting an engine for a mid-sized vehicle. A comparison is made between extrapolating a reference LCI model and employing LCI-MDD. Keywords: LCA; Sustainable Design

1

INTRODUCTION

Industrial ecology “focuses on the potential role of industry in reducing environmental burdens throughout the product lifecycle [1]. To enable that focus, life cycle inventory (LCI) - a stage of life cycle assessment (LCA) - characterizes materials, energy, wastes, and emissions flows through a product or service system [2,3]. While LCI as a formality is intended only for the evaluation of an existing system, it is often called into service as an aid to future product or policy design [4-8]. The more prevalent attributional LCI quantifies product system material and energy consumption and emissions using average production and environmental data, often for existing systems [9]. Otherwise, attributional LCI often relies on use of exogenous assumptions to extrapolate existing economic and behavioral interactions intofuture product system scenarios. These assumptions can neglect how those market interactions may change as a result of design changes to provide the same service, with the result that environmental performance may be much different than anticipated. Conventional, process-based LCI has rarely utilized economic models that demonstrate how product design attributes influence market response in purchasing and use, ultimately dictating much of the life cycle environmental performance. The result is a potential for industrial design improvements based on attributional LCI to be later thwarted by otherwise unforeseen consequences such as economic rebound effects which have been found through general equilibrium modeling to reduce or even reverse intended improvements in performance such as energy efficiency [10-11]. On the other hand, the lesser-used consequential LCI employs marginal production and environmental data to quantify the material, energy and emissions consequences of changes in product systems, often due to policy decisions [8, 9, 12]. This modeling approach may better incorporate economic and technical simulations to determine environmental feedback (disproportionate decrease or increase in resource use or emissions for a change in technology that also impacts demand for that technology) and rebound effects of changes in product designs.

This paper contributes to the consequential LCI methodology, extending the boundaries of process-based LCI (Figure 1A) to include the impacts of economic behavior of markets and individuals on a product system via endogenous models (Figure 1B). Figure 1B can be considered an approach to life cycle inventory with market driven demand (LCI-MDD), which pursues the idea that the utility of LCI can be enhanced with respect to the needs of stakeholders such as policymakers and designers when economic and behavioral information is incorporated. While this area has not been widely studied, the idea itself is not new. In fact it is well known that prices, economic policy instruments, and other socio-economic factors change material flows and influence the environmental burdens of a product system [13-14], and that changes in materials flows through a product system can have macro-economic repercussions [15-16]. Michalek et al. (2005) demonstrated that a game theoretic approach could be used to evaluate the impact of government policies on vehicle design decisions made by automotive producers [17]. Below we propose to extend the example using a game theoretic approach to LCI-MDD and its application to product and policy design. The objective is to better understand the feasibility of LCIMDD and to demonstrate its application for the study of rebound effects in product and policy design contexts. Another objective is to stress the need to develop a set of standards and best practices for LCI-MDD – recognizing that additional uncertainties must be managed when incorporating market simulations within a LCI framework. These additional uncertainties, and the modeling approaches used to address them, should be presented in a transparent and clear manner. For this reason it is important to distinguish between LCI and LCI-MDD as the distinction denotes a host of uncertainties in market simulation modeling that are separate from, and in addition to, the system and data uncertainties already present in LCI. Section 2 introduces a case study used to test the feasibility of the LCI-MDD approach. Section 3 presents the results of the case study. Section 4 offers a discussion of the usefulness and practice of LCI-MDD based on the learning of this research.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_97, © Springer-Verlag Berlin Heidelberg 2011

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Figure 1: (A) The life cycle inventory approach, and (B) the predictive life cycle inventory framework. Solid arrows indicate the flow of materials and information (including market information). In 1B, the dashed arrows indicate a potential extension of the framework to test policy strategies. 2

LCI-MDD CASE STUDY OVERVIEW: ENGINE SELECTION FOR MID-SIZE VEHICLE

This case study considers the selection of engine power during the design of a mid-size vehicle. As the engine power varies, the body mass of the vehicle also must vary to support the selected engine while all other aspects of the vehicle are assumed fixed and equivalent to the mid-sized vehicle considered in [4]. A larger engine power decreases fuel economy and increases acceleration and production costs. It also increases upstream material and manufacturing emissions as well as downstream end-of-life unit processes. Also varying with engine power is the vehicle operating cost (e.g., dollars per mile driven) and so vehicles with larger engine sizes will on average have fewer miles driven per year. The following paragraphs summarize the life cycle unit processes and models employed. In the interest of brevity and focus, many of the details are left to references. The descriptions are only meant to show that realistic models from the literature were utilized, leading to results presented in Section 3. We do not intend for the actual numerical results in Section 3 to reflect real-world results; rather the goal here is to explore LCI-MDD concepts in the form of Figure 1B and share the findings. Life Cycle Unit Processes (Materials, Manufacturing, and End of Life). The unit process model begins with the generic vehicle life cycle inventory from the US Automotive Materials Partnership [4], which estimates the material and energy profile for a mid-sized vehicle with a gasoline engine (3 L, 104 kW). The baseline vehicle material inputs represent 90% of the body mass, 86.5% of the powertrain mass and 97% of the suspension mass. The vehicle

characterization is simplified and does not account for certain processes and components not impacted by the powertrain system (further discussed below). In the LCI-MDD model, producers are allowed to select different engines in the range of 75%-150% of the power ratings of the base vehicle from the USAMP study. To determine the mass of these engines, the analysis here combines the power-displacement data from [18] with the displacement-mass data from [19]. The vehicle frame and body must support the weight of any engine option while taking into account the ‘secondary’ weight effects for the entire vehicle. This effect is accounted for with a weight-compounding factor of 0.5 from [20]. In manufacturing engines and vehicle bodies, the appropriate quantity of materials are combined with energy inputs. Here it is assumed that energy inputs for engine manufacture are constant for any engine size, and that energy used in body manufacture varies with body mass. A suspension system of constant size is also manufactured with materials and energy as modeled in the generic vehicle LCI of [4]. Vehicles are assembled from the manufactured systems with additional inputs of materials (no other systems manufacturing is modeled) and energy. After production, the new vehicles are driven their useful life and then sent to a shredder, which recovers metals and sends non-metals to a landfill. Other non-metal inputs are not currently modeled and the model also does not consider transportation between processing facilities. Life Cycle Unit Processes (Use Phase). A typical LCI might calculate the total number of miles travelled during the lifetime of the vehicle using a fixed age (in years) and constant VMT per year.

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Figure 2: (A) Effect of varying VMT on life cycle CO2-equivalent emissions using LCI framework, and (B) Emissions from the 104kW engine when VMT is 11,200 miles broken down by life cycle stage.

Figure 3 : Life cycle CO2-equivalent emissions as a function of fuel price where (A) VMT is a function of fuel price, engine size is constant (104kW), and demand (3.8 million) is assumed and (B) engine size and demand are a function of fuel price with constant VMT (11,200 miles/vehicle/year). This analysis considers a vehicle lifetime of 15 years with the number of miles travelled per year varying depending on vehicle fuel economy, fuel price and age. It is recognized that vehicles might be replaced after a fixed mileage or that vehicles can be used longer than 15 years but for brevity these issues are not considered in Section 3. VMT per year is estimated using two independent econometric models that have been derived to explain fuel consumption trends for light duty vehicles in the US [21-22] and compared to US Department of Transportation VMT data. Demographic and transportation infrastructure variables that factor into these models were assigned constant average values using 1990’s data to align with the input LCI data. Vehicle operating costs and price variables were dependent on the results of the marketoptimal product design emanating from the LCI-MDD producer decision model. Producer Decision Model. The LCI-MDD methodology utilizes profit-maximization in game-theoretic Nash equilibrium as a model of producer decision-making and follows the approach described in [23]. Five producers are nominally modeled, but the qualitative results of the analysis for this case study do not change as a result of this assumption. To start, each producer k decides on a set of

products to produce including design decisions, prices, and production volumes. Specifications of the design variables xj (engine size and final drive ratio) determine the product characteristics yj (fuel consumption and acceleration) that are observed by the consumer (subscript is “for vehicle j”). The mapping xj to yj occurs using the vehicle simulation and production costs described in [17]. Consumers make purchasing choices among the set of all products based on the product characteristics and price of each product, resulting in an overall number of products sold for each engine size calculated by the demand model. Each producer k attempts to maximize its profit πk (sales revenue for quantity qj at price pj, minus costs cj) by making the best possible design, pricing, and production decisions according to Equation 1:

(1)

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Figure 4: Life cycle CO2-equivalent emissions as a function of fuel price’s effect on engine selection, demand, and VMT models. Demand Model Selection. A logit model is used to represent consumer preferences based on [24]. Again, the model is used for illustrative purposes only. While dated, this econometric analysis presents attractively simple relationships between vehicle attributes and vehicle demand, and serves this paper’s purpose for testing the LCI-MDD approach by deriving a representative vehicle demand estimate. The model incorporates the possibility that consumers will reject the product offering and not purchase a vehicle. This means lower fuel economy vehicles are kept on the road, since the distribution of ‘pre-existing’ mid-size vehicles on average had 0.7 MPG less than new mid-size vehicles in 1995, while pre-existing cars on the road of all types got on average 1.9 MPG lower than a average 1995 new vehicle in the US. Market Simulation. To account for competition as a driver for producers to select a specific engine size, game theory is used to find the market (Nash) equilibrium among competing producers. In game theory, a set of actions is in Nash equilibrium if, for each producer k=1,2,…,K, given the actions of its rivals, the producer cannot increase its own profit by choosing an action other than its equilibrium action. In order to find the Nash equilibrium point for a set of K producers, the decision variables of each producer are optimized to maximize the profit of that producer while holding the decisions of all other producers’ constant. This process is then iterated, optimizing all producers k = 1,2,…,K in sequence until convergence, yielding the Nash equilibrium for K producers, where K in the example below is set to the largest value that yields positive profit for the producers. Additional details on this approach can be found in [17]. 3

RESULTS AND DISCUSSION: LCI-MDD CASE STUDY

Results. In order to provide context for the LCI-MDD results, a foundational LCI (to be compared with LCI-MDD below) was developed as described in Section 2. Figure 2A provides life cycle greenhouse gas emissions expressed as CO2-equivalents. The results are presented assuming 3.8 million vehicles were sold and each of these vehicles is driven the same amount. Both VMT and engine size are variables for which a sensitivity analysis is provided. VMT ranges from 5,000 to 30,000 miles/vehicle-year and three different engines are considered (75kW, 104kW, and 150kW, or 56 hp, 78 hp and 112 hp). Results are generally as expected showing a dominance of the use-phase; values differ slightly from previous total vehicle life cycle results [4] due to the vehicle system boundary simplifications defined in Section 2. For example, the results show that doubling VMT will cause a 79% increase in life cycle CO2equivalent emissions for the 104 kW engine and an 83% increase for the 150 kW engine. Figure 3B illustrates how the life cycle CO2-

equivalent emissions are broken down by life-cycle stage for the case where VMT is 11,200 miles and the selected engine is 104kW. As a first example to demonstrate the conversion of an LCI (Figure 1A) to a LCI-MDD (Figure 1B), econometric models of VMT were incorporated inside the system boundary to derive total life cycle CO2 emissions as illustrated in Figure 3A. In this case VMT is a dependent variable calculated using fuel price as an independent variable for which a sensitivity analysis is performed. The influence of model uncertainty on life cycle outcomes is illustrated by implementing two different VMT models [21-22] that differ in their form and responsiveness to fuel price. Figure 3A shows the “VMT rebound” as higher fuel prices lead to lower life cycle emissions. The importance of considering model uncertainty in addition to fuel price uncertainty is strongly evident: Goldberg’s model shows a strong dependence on fuel price while Jones’ model has minimal sensitivity. Both models are compared with the LCI that doesn’t consider these effects. In Figure 3A, engine power (104kW) and the quantity of vehicles demanded (3.8 million) are exogenous to the analysis. Figure 3B brings these decisions inside the system boundary while holding VMT constant at 11,200 miles/vehicle-year. First, using market simulation it is possible to estimate the engine that would maximize producer profit under the assumption of market equilibrium. In general different firms would select different engines, but under the logit model considered here [24] all producers would select the same engine and sell the vehicles at an identical price. Capturing heterogeneity in the market leads to different solutions for different producers and is not considered here (e.g., see Frischknecht et al., 2009). Since no vehicle with a given engine size can capture 100% of the market, a fraction of the 3.8 million consumers calculated by the model will not buy the vehicle and are assumed to “walk away” from the market while continuing to drive a vehicle with fuel economy equivalent to the average 1995 mid-sized vehicle. Sensitivity and Uncertainty Given Policy Scenarios. We believe the most important application of LCI-MDD is within a hypothesis evaluation framework, given the inherent uncertainties of the approach and its likely use as a tool in product or policy design. To demonstrate the use of LCI-MDD in a hypothesis evaluation example, we first considered the following policy hypothesis: a fuel tax greater than $0.19 per gallon ($20/ton CO2-equivalent) would reduce life cycle emissions of mid-sized vehicles by at least 5%. In Figure 5 we develop scenario landscapes (a collection of 32 scenarios) under which the hypothesis is evaluated. The scenarios are created by varying the fuel tax at 4 discrete levels from $10/ton ($0.08/gallon) to $40/ton ($0.39/gallon) and by considering the baseline fuel price ranging from $1.10 to $2.60 (also at 4 discrete

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Figure 5: Scenario landscape results for a policy hypothesis with varying tax levels and fuel price.

 

  Figure 6: Scenario landscape results for the design hypothesis with varying fuel prices. levels). Using two different VMT models with one landscape each containing 16 scenarios yields 32 scenarios in total. Scenarios for which the hypothesis is rejected under the model assumptions are indicated with (X), and those scenarios which exhibit support for the hypothesis are indicated with (check). Since the Boyd and Mellman (1980) model is an econometric model with parameters estimated from data, a parametric uncertainty analysis was also performed. In some cases, the uncertainty of the parameters would not allow a clear determination of support or rejection of the hypothesis. In these cases an (O) is indicated in Figure 5. Figure 6 shows that it is also possible to establish hypotheses related to the consequences of design decisions. For instance, one could hypothesize that a new technology costing $3000 that can increase fuel economy by 5 miles per gallon is able to reduce life cycle CO2-equivalent emissions by 10%, even if the manufacturing emissions would need to double to achieve this fuel economy improvement. Figure 6 is the scenario landscape plot created by evaluating this hypothesis under 8 scenarios (four different base fuel prices and two different VMT models). The results show that at low fuel prices, where VMT is relatively high, the new technology can be effective to reduce life cycle CO2-equivalent emissions by 5% relative to the vehicle without the new technology. Results at higher fuel prices are mixed since VMT is reduced and therefore the manufacturing phase of the life cycle is relatively more important. 4

CONCLUSIONS

Sustainability is ultimately a challenge to technology and policy design processes that urges them to consider economic success simultaneously with environmental and societal performance. Life Cycle Inventory (LCI) considers environmental performance independent of economic behavior while Predictive Life Cycle Inventory (LCI-MDD) considers environmental performance as an outcome of economic behavior. A LCI-MDD is constructed by considering the consequences of incorporating economic and behavioral models within the system boundary of an LCI. This paper has shown that LCI-MDD is useful when considering the ramifications of future technology or policy design decisions, particularly ones which may exhibit rebound effects that would

otherwise be undetectable by extrapolating the foundational LCI on which the LCI-MDD is based. While LCI-MDD as a concept is shown to be feasible, it creates additional structure, models, parameters, and variables that inherently make the system more complex. This complexity increases the already stringent demands within LCI to explicitly manage uncertainty and to transparently communicate results. To better understand the challenges of LCI-MDD, a hypothetical case study of engine selection for a mid-sized vehicle was considered. While the case study itself was not meant to be representative of today’s automotive market, the constituent models selected were realistic enough to explore the details of LCI-MDD methodology. For instance, it was found that the rebound effects that are known to exist in the design stage and in the use-phase of the vehicle life cycle are detectable as a function of the price of fuel. In the design stage, assumptions of higher future fuel prices lead producers to select smaller engines with higher fuel economy since consumers will be more interested in these vehicles. In the usephase of the life cycle, consumers drive less as the fuel price increases. Comparing these rebound effects, it was found that the “use-phase rebound” is more significant than the “design-stage rebound”. Although neither rebound effect is a surprise, the true power of LCI-MDD lies in its ability to quantify the results under uncertainty and to provide the basis for hypothesis evaluation. Hypothesis evaluation is relevant both for technology design and for policy design and examples of both were provided in this article. For instance, it was shown that 1) the impact of carbon taxes on engine selection and life cycle emissions could be estimated, and 2) the life cycle benefits of new technologies designed to reduce usephase emissions could be estimated. While these examples were hypothetical, the models employed could be updated to more closely capture real market behavior. For instance, research that is required to improve the demand models (e.g., [25]), vehicle performance models [26], and simulation approaches [27] is ongoing. Instead of incorporating these more sophisticated models, this work was meant to serve as a basic blueprint for the predictive life cycle inventory method in the hope of inspiring interest for future research in this area within the life cycle assessment community

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and beyond, working together with needed experts in technology design, behavioral research, policy, economics, etc. We expect the resulting discussion will advance LCI-MDD and further increase its relevance to the sustainable design of products and the design of technology policies intending to promote sustainable development.

[12]

Ekvall, T. and B. Weidema (2004): System boundaries and input data in consequential life cycle inventory analysis. International Journal of Life Cycle Assessment,9(3): 161-171.

[13]

Kandelaars, P. P.A.A.H. and JCJM van den Bergh (1997): Dynamic analysis of materials-product chains: an application to window frames. Ecological Economics, 22:41-61.

5

[14]

Frischknecht, R. (2000): Allocation in life cycle inventory analysis for joint production. International Journal of Life Cycle Assessment 5(2):85-95.

[15]

Suh, S., G. Huppes (2005): Methods for life cycle inventory of a product. Journal of Cleaner Production, 13, pp.687-697.

[16]

Takase, K., Y. Kondo, A. Washizu (2005): An analysis of sustainable consumption by the waste input-output model. Journal of Industrial Ecology 9(1-2): 201-219.

[17]

Michalek, J.J., P.Y. Papalambros, and S.J. Skerlos. A study of fuel efficiency and emission policy impact on optimal vehicle design decisions. Transactions of the ASME, 126(November):1062-1070.

[18]

Arnold, S., C. Balis, D. Jeckel, S.Larcher, P.Uhl, S.M. Shahed. (2005): Advances in turbocharging technology and its impact on meeting proposed California GHG emission regulations. SAE Technical Paper Series, SAE World Congress, Detroit MI, April 11-15.

[19]

Messner, C. (2007): Werkstoffe fur Antriebssyteme, I Otto- und Dieselmotoren.

[20]

Lave, L., H. Maclean, C. Hendrickson, and R.Lankey (2000): Life cycle analysis of alternative automobile fuel/propulsion technologies. Environmental Science and Technology, 34:3598-3605.

[21]

Jones, C.T., Another look at US passenger vehicle use and the 'rebound' effect from improved fuel efficiency, Energy Journal, 14:4, pp.99-110, 1993. Boyd, J.H. and R.E. Mellman. 1980. The effect of fuel economy standards on the US automotive market: an hedonic demand analysis, Transportation Research Record A, 14:367-78.

[22]

Goldberg, P.K. (1998): The effects of the corporate average fuel efficiency standards in the US. Journal of Industrial Economics, 46(1):1-33.

ACKNOWLEDGEMENTS

This research was supported by the Michigan Memorial Phoenix Energy Institute, Alcoa Foundation’s Conservation and Sustainability Fellowship Program and a National Science Foundation MUSES (National Science Foundation Materials Use: Science, Engineering and Society) grant (CMMI 0628162). One of the authors was funded through the Alcoa Foundation Conservation and Sustainability postdoctoral fellowship program which is a separate entity from Alcoa. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. The authors are grateful for valuable input from Colin McMillan, Bart Frischknecht, Dr. Hyung-Ju Kim, and Esra Suel at the University of Michigan, and for contributions from Professor Jeremy Michalek, Carnegie Mellon University. 6

REFERENCES

[1]

Lifset, R. (2006): Industrial ecology and life cycle assessment, what’s the use? International Journal of Life Cycle Assessment 11(1):14-16.

[2]

SETAC. (1993): Guidelines for Life-Cycle Assessment: A “Code of Practice”, Edition 1, Society of Environmental Toxicology and Chemistry Workshop, Sesimbra, Portugal.

[3]

ISO (1997): ISO 14040: Environmental Management-Life Cycle Assessment—Principles and Framework, International Organization for Standardization, Geneva.

[4]

Keoleian, G.A., G.M. Lewis, R.B. Coulon, V.J. Camobreco, and H.P. Toulon (1998): LCI modeling challenges and solutions for a complex product system: a mid-sized automobile. SAE Technical Papers Series, no.982169.

[5]

Ehrenfeld, J. (1997): The importance of LCAs—warts and all, Journal of Industrial Ecology, 1(2).

[6]

Nielsen, P.H., H. Wenzel (2002): Integration of environmental aspects in product development: a stepwise procedure based on quantitative life cycle assessment. J. Cleaner Production, 10:247-257.

[23]

Skerlos, S.J., Morrow, W.R., and J.J. Michalek (2005): Sustainable Design Engineering and Science: Selected Challenges and Case Studies. Sustainability Science and Engineering, M. Abraham Ed., Elsevier, 477-525.

[7]

Spielmann, M., R. Scholz, O. Tietje, and P. de Haan. Scenario modeling in prospective LCA of transport systems. International Journal of Life Cycle Assessment, 10(5):325335.

[24]

Boyd, J.H. and R.E. Mellman 1980: The effect of fuel economy standards on the US automotive market: an hedonic demand analysis, Transportation Research Record A, 14, pp.367-78.

[8]

Sanden, B.A., and M. Karlstrom (2007): Positive and negative feedback in consequential life cycle assessment. Journal of Cleaner Production 15(15):1469-1481.

[25]

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Finnveden, G., M. Hauschild, T. Ekvall, J. Guin’ee, R. Heijungs, S. Hellweg, A. Koehler, D. Pennington, S. Suh. (2009): Recent developments in life cycle assessment. Journal of Environmental Management, 91:1-21.

Frischknecht, B., K. Whitefoot, and P.Y. Papalambros (2009): Methods for evaluating suitability of econometric demand models in design for market systems, 2009 ASME International Design Engineering Technical Conferences, San Diego, CA, August 30-September 2, DETC2009-87165.

[26]

Frischknecht, B. (2009): Exploring public/private tradeoffs in vehicle design through engineering models and market simulation. Doctoral Thesis, University of Michigan, Ann Arbor.

[27]

Morrow, R. (2008): Equilibrium pricing in empirically relevant differentiated product market models. Doctoral Thesis, University of Michigan, Ann Arbor.

[10]

[11]

Allan, G., N.Hanley, P. McGregor, K. Swales, K. Turner. (2007): The impact of increased efficiency in the industrial use of energy: a computable general equilibrium analysis for the United Kingdom. Energy Economics, 29:779-798. Turner, K. (2009): Negative rebound and disinvestment effects in response to an improvement in energy efficiency in the UK economy. Energy Economics, 31:648-666.

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A Case-study: Finding References to Product Development Knowledge from Analysis of Face-to-Face Meetings 1

1

Barry Piorkowski , James Gao , Richard Evans 1

1

University of Greenwich, Chatham Maritime, Kent, ME4 4TB, United Kingdom

Abstract The study aim was to identify references to knowledge in conversation to inform personal expertise skill profiles. Objectives were to notate instances of issues or claims that arise during the discussion meetings; and to locate any supporting evidence of knowledge that has impacted on the profitability of a product. The volunteer participant was an employee from BAE Systems. A video from face-to-face (F2F) meetings uncovered 140 instances identified as either an issue or claim. Indexing the path to existing content or identifying gaps has mapped the infrastructure in use. Insight is also provided into commercial success in the Defence industry. Keywords: Product Development Knowledge; Review Meeting; Defence Industry

1

INTRODUCTION

The Plan-Do-Check-Act (PDCA) cycle which is similar to the learning cycle and could be likened to Nonaka’s dynamic spiral for knowledge creation [1] is popular and widely used in engineering as a method of continuous improvement. A Dynamic Knowledge Management Framework has been presented by the authors in an earlier paper to explain the relationship between cultural factors (motivation, people, human to human interface) and technological factors (human to machine interface, content and infrastructure) to support organisational learning [2]. Knowledge is a currency of value in its own right and businesses need the development of their products (including services) to be a success in terms of profitability. This means that people must continuously improve their own skills to develop products that are profitable. Formal standard processes in industry like the Performance Development Review (PDR) for people to reflect on and set personal learning objectives and the Product Lifecycle Management (PLM) process are designed to link the actions and decisions people make to the success of product development and the profitability of the company. PLM is a systematic method whereby only products that have met the prearranged project criteria may progress with appropriate funding. This is discussed and decided at face-to-face (F2F) review meetings. The PDR process is where the people in the company are motivated to achieve set goals which is also often discussed F2F. Knowledge alone can not achieve business results, people need to make decisions and take action in applying knowledge to develop products and keep a business profitable. Performance analysis of the actions that people take is more commonplace in Sport where notated key performance indicator ratios are computed for comparison [3, 4]. Expertise level of people in product development could perhaps be determined by how competent they are in performing their chosen capabilities. There has been some work from Bredin to identify the groups of capability [5] and Bhatnagar has provided a diagrammatic tool which can be used to assess talent within a pipeline for succession planning [6] but research is limited that actually attempts to quantify performance in product development other than self reporting award submissions [7, 8].

The relationship between knowledge and performance could be the expertise skill level (capability and competency) of people. Individual capability in an engineering business context has been presented in four main points. These are strategic, functional and project capabilities which all influence the fourth point of overall people capability [5]. It is obvious that there is not enough time for one person to master the application of all knowledge in the world within all capability categories. This means that people tend to focus their attention into a domain that they prefer and in which they have enjoyed most success. Therefore individuals must discuss how to achieve common goals collaboratively. 2

FACE-TO-FACE MEETINGS

Video capture is emerging in product development with visual symbols in a map being used to represent items discussed like issue status, answers to questions and arguments [9, 10]. There has been some evaluation of the contributions people make in a F2F meeting and how these discussions shape the development of a product but so far this has not been associated to profitability. Analysis of F2F meetings requires a tremendous effort in codifying the content. Aspects of these techniques have been applied to meeting content [9-11] but no researcher has attempted to link the references to knowledge in conversation from F2F meetings to the skill of the person and profitability. Codified people skill profiles therefore made available in the company infrastructure interoperable with existing Performance Development Review (PDR) and Product Lifecycle Management (PLM) enterprise software applications is a research challenge yet to be explored [2]. Establishing what people know, what they have done to develop a product and how successful that was will have general appeal in industry. Notating instances of issues or claims that arise during discussion in F2F meetings will uncover opportunities for improvement in the organisation. Also, finding references to knowledge from the analysis could provide an index of language terminology including keywords which may be clustered into a theme or themes. This initial exploratory work then will be of use to web developers

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_98, © Springer-Verlag Berlin Heidelberg 2011

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Aim and Objectives

The aim of this industrial case-study is to identify references to knowledge in conversation to inform the development of a personal skill (capability and competency) profile. The objectives are to notate instances of issues or claims that arise during relevant discussions and to locate any supporting evidence of knowledge that has impacted on the profitability of a product. The case-study is part of the three year project funded by BAE Systems and UK Engineering and Physical Science Research Council (EPSRC) in ‘Knowledge Management for Integrated Product Development’. 3 3.1

METHODS Case-study Selection

BAE Systems is organised around a combination of the different products and services they provide, and the geographical area in which they operate. The BAE Systems Rochester facility in the United Kingdom is a product innovation and development centre and its people have a range of expertise in electro-optics, electromechanical systems, safety-critical software, and control and computing systems (Bartlett, 2002). Also, Rochester provides a gateway to markets in Europe and the Middle East for its parent organisation BAE Systems Inc. based in the United States of America. Rochester has relevant employees who possess the knowledge to provide product design and development, business development, sales and product support in these regions. Three BAE Systems employees self-selected themselves as volunteer participants for the study. All volunteers were male and had over 30 years experience in the Defence industry. The role that the participants had at the time was defined as a ‘Principal Technologist’, ‘Chief Technologist’ and ‘Manufacturing Engineering Manager’. The ‘Principal Technologist’ retired from employment before the research could be completed so this left two of which the ‘Chief Technologist’ was chosen for further investigation because the duration of video captured was approximately 30 minutes shorter in length. Participants gave informed consent to participate in the study that was approved by the Institutional Ethics Committee. The participant in this case-study manages the ‘core technology’ element of the R&D programme in BAE Systems, Rochester and he is the main point of contact with external research and technology providers. Before joining BAE Systems in 2004 the participant was a Technical Director at Thales and before that a Research Laboratory Manager in the field of microwave and laser radar. Possessing real practical industrial experience in developing products spanning a career of nearly 30 years in different organisations, plus his involvement in engaging with academics and technical specialists from small to medium size enterprises makes the volunteer participant an interesting case-study. 3.2

Data Collection and Analysis

Due to the nature of the collaborating company, rules are imposed which meant that care needed to be taken by the investigator and the participant not to speak on camera about anything product specific or anything classified above “Restricted”. Video data was acquired through one Polycom® CX5000 table mounted threehundred and sixty degree web camera (Polycom, Slough UK) with PC and software. This commercial off the shelf camera with microphone is the main component to be developed by the research group into a prototype face-to-face (F2F) meeting capture and indexing tool. The video capture frequency was 15 Hz and audio microphone range 150 Hz - 3.4 kHz within the maximum room size 7.62 m x 4.57 m x 3.05 m. The Microsoft® Live Meeting (Microsoft

565 Corporation, Reading UK) software and Polycom® PVXTM (Polycom, Slough UK) software provided a Panoramic video resolution of 1056 x 144 pixels and audio. The output .avi file from the camera played with a YUV codec and was compressed to .mp4 format. Semi-structured interview questions were designed to get the participant to speak of their experiences throughout their career. Particular interest was in identifying the participant’s functional, project and strategic skill level (capability and competency). Further questions were to uncover evidence of knowledge generation, attempted knowledge re-use and transfer. The questions and also points to note were printed on cue-cards which were spoken by the investigator directed to the participant. The participant was asked to respond verbally or with the aid of drawing on a Whiteboard. Verbatim transcripts were produced by a professional typist post data collection. These were uploaded into the NVivo8 (QSR International, Victoria, Australia) software where key events were time-coded by the investigator for each instance where a question was asked, when an issue was raised or a claim made during the discussion. Post data collection, the respondent participant was asked to provide supplementary evidence links to documents or websites. 4 4.1

RESULTS AND DISCUSSION Verbatim Transcript

The face-to-face (F2F) meeting provided a rich source of data for analysis. A total of 108 questions were asked by the investigator over two separate sessions which resulted in a total of 3 hrs, 32 mins and 45 secs of meeting data. This was held in two .avi files 15.6 GB and 20.3 GB in size which when converted to .mp4 format reduced the size to 112 MB and 147 MB respectively. The verbatim transcript generated by the professional typists from the two .mp4 files contained some minor errors which were smoothed by the investigator. Instances of “Noise” were defined by the investigator where no analysis was needed to be performed. There were 140 instances which were coded by the investigator as either an “Issue or Claim” that was raised or made by the respondent (R). This generated a further 362 instances where the investigator (I) asked for supplementary evidence such as links to documents or websites. A selected extract can be seen in Table 1. The verbatim transcript in the extract (Table 1.) gives insight into some of the challenges from the point of view of the participant responding to the questions about commercial success. The participant spoke of how the Defence industry has evolved after numerous re-assessments. A recent re-assement has just been welcomed by BAE Systems following the publication of the UK Government’s Strategic Defence and Security Review (SDSR). In an official response issued by BAE Systems they state that they “have been fully aware of the challenges facing the new [UK] Government in addressing the public spending deficit and throughout the SDSR consultation period we [BAE Systems] have cooperated with the Ministry of Defence (MOD) to identify areas in which efficiencies could be delivered and key industrial capabilities are maintained.” There seems to be a reduced demand for large scale Defence programmes which may be due to the collapse of the former Soviet Union and other significant political events. Transferable skills which can be used to develop profitable products in commercial adjacent markets therefore now and in the future need to be identified. For example, Cyber crime is now one of the UK’s greatest threats and therefore the announcement in the SDSR that the new Government is committed to improve cyber security in the UK is welcomed by Detica and BAE Systems (Detica is a BAE Systems company and was acquired in September 2008). Detica, by partnering with the UK Government will be able to share capabilities

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and critical information to ensure that the UK can protect its critical national infrastructure and drive exports.

I:

Tell me about generating profit in the industry for this company

R:

Okay. [*] [That] is a broad question isn’t it? [*]. It’s driven by numerous things. There are external parameters, [as] you [*] [appreciate, such as] what’s happening in the economy and the markets (2) but there’s also the fact that this industry, and I don’t just mean this company, I mean the whole [Defence] industry, has changed its shape quite dramatically in the last 20 years or so and typically in large organisations, there tends to be [requirements dictating] a culture and a process which is quite [*] [demanding] in terms of the amount of [*] [procedures] that need to be gone through and followed to [*] [execute projects] (3). [*]…Now clearly if that front-end [of the Product Life-cycle Management] process is very [*] [onerous], that immediately starts to impact profit margins because typically if you’re not funded to do the [Defence product] development, which is often the case, or at least not fully funded (4), then you need to recoup the non-recurring costs over the production run (5). With production runs getting smaller (6) then [*] it’s harder to amortise [costly] [*] non-recurring [*] [activities]. [Also,] with the market being ever more cost sensitive (7) it’s hard to [*] [apply] large margins [*] [to] jobs. So all of that works against generating profit when you get to the [traditionally more] profitable part of the [*] [life cycle, for example] during the production phase and then the through-life [service] phase (8). [*] …

Further Evidence Requested: (2) What can be done to reduce the negative effects of these external factors? (3) Is end-to-end process performance data visible? (4) Why are the product development projects not fully funded? (5) Is the volume of the production run part of the product development project selection criteria? (6) Is this a fact [about product runs getting smaller]? Why is this? (7) What would the market consider to be value for money? (8) Can you lock customers into an agreement after a certain point in the PLM? I:

What about making sales in this industry. How’s that?

R:

The whole process is also, in my opinion, you know, a lengthy and challenging one. The lifecycle of these [Defence product development] programmes is enormous. In terms of trying to win orders, I guess for a big programme, you expect that [bid] phase of the life-cycle to go on for quite a few years (9) [*] [ideally] for a bid to be [*] [efficient] you want to be quite fast moving (10) [*]. You want to have your best people (11) working on it and you want them to have the freedom (12) to actually [*] be generating innovative ideas as that bid comes together, be that new designs (13) or novel ways of getting the message across (14) and so on. An awful lot (15) of effort goes into producing data for internal review (16) and for actually going through that review process (17) [*]…

Further Evidence Requested: (9) Is it desirable for the bid winning phase to be slow? Are there any examples where it has been faster than normal? (10) How fast? (11) Who are the best people? (12) How could this freedom be granted? (13) Have any new designs been established as a result of a bid? If so where are they stored? Who owns them? (14) Have there been any novel ways of getting the message across as a result of a bid and if so where are they stored? Who owns them? (15) How many hours per bid? (16) What data? Review with whom? (17) Please provide a link to further details of this process * N.B. company sensitive content removed from publication. Table 1: Selected Extract of the Video Profile Interview. The participant spoke of processes that he feels slow people down in getting things done but helps to ensure quality. It was indicated that he wanted the “best people” to have freedom to innovate. These and other points were marked for further evidence to be requested by the investigator (Table 1.). In a large global corporation plus the extended organisation of academics, suppliers and specialists there will undoubtedly be varying levels of expertise. Each person has their own experiences in developing complex products. Each has their own interpretation of the market and its demands. Attempting to build a dynamic web based profile of a person based on content gathered through a F2F meeting will be difficult due to the time and effort needed in post-processing. Furthermore, semantically linking this profile to the profitability of an organisation will be challenging.

4.2

Factors Effecting Profitability

From the methodology used in the project the factors affecting profitability have been formalised by the investigators for critique. It is thought that greater demand and maximizing revenue improves the opportunity for profit in an organisation. Less complexity and minimizing overhead improves the opportunity for profit. The expertise skill level of people involved may influence the profitability depending on their performance in reducing operating costs and making sales.

Information and Knowledge Management

567 Operational framework is cited for the Product Life-cycle Management (PLM) process. The unique identifier for each knowledge (issue or claim) asset verified with evidence is so that knowledge transfer between participants and performance improvement for the organisation may be tracked as a result of an intervention. A collection of superimposed grid maps (Figure 2) layers could be implemented for industrial use as part of the Performance Development Review (PDR) process showing where people are in the pipeline for each knowledge asset. This will support the organisation in maintaining a flow of expertise which is ratified by performance results during the product lifecycle management (PLM) process.

Figure 1: Factors Effecting Profit in an Organisation. Demand is the market need for a product and the plus sign shows that as demand increases there should be more revenue which would be through a combination of units sold at a price the customer is willing to pay. Greater volume means more opportunity to make profit depending on the costs incurred during organisational activity. Overheads therefore need to be kept to a minimum (as the minus sign depicts) and this can be achieved by keeping things simple and focusing on value delivered to the customer. This poses a paradox because products need to be sold at a price the customer can afford but also at a price that can generate profit. Therefore the expertise skill of workers in simultaneously balancing sales generation with the cost of product development is of paramount importance. Capturing further meeting content from more people involved in product development will provide a larger sample to analyse the language terminology used in making claims or raising issues. Particular interest would be in profiling people’s expertise skill and how that influences profit (Figure 1). This will uncover more stories of how expertise skill and associated knowledge is used to increase revenue or reduce overhead. 4.3

Personal Expertise Skill Profile

A unique identifier assigned to the evidence gathered informs a personal skill profile for the participant. A grid map with three levels was used to plot knowledge assets. The User level competency means that the participant has accessed and applied the stated knowledge. The Innovator level is where the participant has found a gap in the existing knowledge and has reported findings from further investigations to improve understanding. In being inventive the participant has refreshed the knowledge available for re-use to be attempted by others in the organisation. The top Expert level is where the knowledge has been re-used and improved but also the participant actively engages in attempting to transfer the knowledge by supporting and mentoring others. The participants learn at all levels in the grid pipeline. The answers to the questions in the selected extract (Table 1) were about commercial success in the Defence industry numbered 2-17. This could inform a unique identifier for each knowledge asset verified with evidence to plot onto a map for display purposes (Figure 2). For example if the participant was known as Participant X then item 7 could be listed as X2010-7. This unique identifier which is the reason why the participant thinks that the market is being more cost sensitive can then be plotted on the map in the Strategic knowledge transfer section. This is because the participant is actively engaged in communicating this to his team. Item X2010-13 is an example of Functional knowledge innovation and item X2010-16 an example of Project knowledge re-use where the BAE Systems

Figure 2: Grid Profile Map. For the participant to move the knowledge asset X2010-16 up the pipeline (Figure 2) evidence would need to be provided to show, for example, that the PLM process, or its means of implementation, has been improved. For the participant to be recognised as an expert for asset reference X2010-13 then evidence would need to be shown of how they have attempted to transfer the innovation to another product or person. Evidence has been provided for reference X2010-7 where the participant has been successful in winning new product development bids. The participant has transferred knowledge from one bid proposal to another and also shared the importance of cost sensitivity with others. This paper gives an example of how one person with expertise skill who is motivated to create profit for the company can interface with other people and also technology to support organisational learning. PLM and PDR data can provide a measurable to plan to improve on. A methodology is presented that may be used to quantify performance in product development which is an alternative to self reporting award submissions [7, 8]. Some of the answers to the questions were vague and required further investigation. The extra effort required is beneficial for both the organisation and the participant because real live capture during an F2F meeting means that there could be less hindsight bias. Video capturing a F2F meeting gives an opportunity to reflect on the original plan afterward. Tradeoffs can then be evaluated or eliminated and is available to be checked with others. For example there was a trade-off highlighted by the participant with quality processes and profitability margins. If this and other meeting content was published online within the company then people who may not have attended the original meeting can comment on the current issues and claims made. Codified content can then be made searchable within the organisational infrastructure by tagging it with meta-data. For example unique identifier X2010-13 may be tagged with keywords such as

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Information and Knowledge Management

those itemised in the patent publication like the name of the inventor and the domain expertise. Other keywords might be the name of the projects and products that are associated with that intellectual property. On the occasions where there is no need to check, and there has been authority granted at the review meeting to progress and act on the proposed change then there should be some visible performance outcome improvements to follow. These may be an improvement of the profitability of the product and or people having learnt something on reflection during the PDCA cycle. It is important that PLM and PDR systems are interoperable so that further continuous improvements can be planned on reflection and there is no electronic double handling and waste. An example of this could be where the participant has identified an opportunity where the PLM process can be improved to allow greater flexibility in the front-end of the product lifecycle. When the participant has made a change to this process and there has been some visible performance improvements as an outcome then this should be spoken about during their PDR so that reference X2010-16 can be moved up a level.

[7] Ranta, D. (2008): Conoco Phillips - Our Edge in Knowledge Sharing. KIN Winter Workshop - Informality and Serendipity: Creating an Innovation Environment, Audleys Wood Hotel, Basingstoke, UK. [8] Cummings, J.N. (2004): Work Groups, Structural Diversity, and Knowledge Sharing in a Global Organization. Management Science Vol. 50, No. 3, pp.352–364. [9] Bracewell, R., Wallace, K., Moss, M., Knott, D. (2009): Capturing Design Rationale. Computer-Aided Design Vol. 41, No. 3, pp.173-186. [10] Bracewell, R.H., Ahmed, S., Wallace, K.M. (2004): DRed and Design Folders: a way of Capturing, Storing and Passing on Knowledge Generated during Design Projects, in: Proceedings of the 2004 ASME International Design Engineering Technical Conferences (DETC'04), pp. Salt Lake City, Utah, USA. [11] Buckingham Shum, S., Slack, R., Daw, M., Juby, B., Rowley,

5

CONCLUSION

This project has identified the references to knowledge in conversation to inform the development of a personal skill (capability and competency) profile. The instances of issues or claims that arose during the discussion were notated and supporting evidence that the knowledge impacted on the profitability of a product was located. The case-study has proved the research methodology since references to valuable knowledge were unearthed during the investigation, some of which was sensitive and could not be published. More work is to be done to refine the prototype F2F meeting capture and indexing tool. 6

ACKNOWLEDGMENTS

This document is based on work funded by EPSRC through BAE Systems. The researchers are deeply grateful to Nick Martin, Clive Simmonds and all others for the support in making this study possible. Any opinions, findings, and conclusions or recommendations expressed in this document are those of the authors and do not necessarily reflect those of EPSRC or BAE Systems. 7

REFERENCES

[1] Nonaka, I. (1994): A Dynamic Theory of Organizational Knowledge Creation. Organization Science Vol. 5, No. 1, pp.14-37. [2] Piorkowski, B.A., Gao, J. (2010): A Dynamic Knowledge Management Framework, in: Proceedings of the International Conference on Interoperability for Enterprise Software and Applications: Doctoral Symposium (IESA 2010), pp. University of Coventry, Coventry UK. [3] Hughes, M.D., Franks, I.M. (2004): Notation Analysis of Sport: Systems for better coaching and performance in sport. Routledge, London. [4] Hughes, M.D., Bartlett, R. (2002): The use of performance indicators in performance analysis. Journal of Sports Sciences Vol. 20, No. pp.739-754. [5] Bredin, K. (2008): People Capability of Project-based Organisations: A Conceptual Framework. International Journal of Project Management Vol. 26, No. pp.566-576. [6] Bhatnagar, J. (2008): Managing capabilities for talent engagement and pipeline development. Industrial and commercial training Vol. 40, No. 1, pp.19-28.

A., Bachler, M., Mancini, C., Michaelides, D., Procter, R., Roure, D.d., Chown, T., Hewitt, T. (2006): Memetic: An Infrastructure for Meeting Memory, in: Proceedings of the 7th International Conference on the Design of Cooperative Systems. Carry-le-Rouet, France.

CAD-Integrated LCA Tool: Comparison with dedicated LCA Software and Guidelines for the Improvement 1

1

Alessandro Morbidoni , Claudio Favi , Michele Germani 1

1

Design Tool and Method Group, Polytechnic University of Marche, Ancona, Italy

Abstract CAD-integrated LCA tools are developed in order to support SLCA (Simplified Life Cycle Assessment) method and they could be used as eco-design tools in the design phase. Nevertheless they are still a long way from being accurate and properly usable. The present work aims at demonstrating this assumption in concrete terms by focusing the attention on the mechanical field. A comparison analysis between CAD-integrated LCA tools and dedicated LCA tools has been proposed in order to determine the main causes of error and to propose guidelines for improvement. An approach based on these guidelines is presented and preliminarily evaluated. Keywords: Life Cycle Assessment; Eco-design; CAD

1

INTRODUCTION

Nowadays eco-design has become an important and useful topic in engineering design, in fact human sensibility and market factor promote the environmental aspect. Life Cycle Assessment (LCA) is an environmental accounting and management approach that considers all aspects of resource use and environmental releases associated with an industrial system “from cradle to grave”. Specifically, it is a holistic view of environmental interactions that covers a range of activities, from the extraction of raw materials from the Earth to the production and distribution of energy through the use, reuse and final disposal of a product. LCA is a relative tool intended for comparison and not absolute evaluation, thereby helping decision makers to compare all major environmental impacts in the choice of alternative courses of action [1]. LCA analysis is both time and resource consuming, due to the collection of the product data needed to perform it (Life Cycle Inventory phase LCI). For this reason complete LCA can be carried out mainly to assess the environmental impact of an existing product, where manufacturing, use and dismantling can be estimated with accuracy. Simplified Life Cycle Assessment (SLCA) approaches try to increase LCA usability in the early design stages. They adopt dedicated tools to estimate the environmental impacts of product alternatives and to predict environmental costs or burdens for manufacturers [2]. A large number of simplified LCA methods has been developed to overcome this drawback and make it possible to perform and be used more easily. Many of these methods have been developed for a specific group of products and are not well documented. In the engineering design phase it is not easy to perform an environmental consideration for the complete life cycle when not all product data is available and fixed. Therefore, it is important to evaluate simplified methods and to study what type of information they require and what kind of results they can produce. New emerging Computer Aided Design (CAD) tools are trying to support the integration of SLCA methods within the traditional flow of product design activities. Their scope is to provide a concurrent analysis of product design solutions from a functional and

environmental point of view. Such technologies can be called CADSLCA. However, even if the approach can be considered valid, it still requires wide improvements from a performance point of view. This work is focused on the mechanical product design field. In order to demonstrate the inaccuracy of current CAD-SLCA solutions, this paper evaluates and compares them with a complete LCA software tools. In particular the analysis has been based on a wide number of different components. SolidWorks Sustainability (by Dassault Systems) and GaBi (by PE International) have been considered as references since they represent the advanced state of art of this kind of technologies. The second objective is the definition of a more accurate and highly usable CAD-SLCA tools to estimate the environmental impact of mechanical products. A simplified LCA not only has to be simple and easy to use but it also has to come up with reliable results. This can be possible by considering the most important aspects of the product under investigation. A classification of necessary data which can be extracted from the CAD model has been realized. Through the analysis of priorities the best compromise between the CAD -based information and the LCA analysis accuracy has been evaluated. Thus it has been possible to define a CAD-SLCA tool able to propose meaningful results without weighting on product design time. 2

RESEARCH BACKGROUND

A lot of research and tools exist regarding the eco-design topic since environmental interest in the product engineering has become so widespread. Eco-design literature shows that many existing tools fail because they do not focus on design, but they aim at strategic management or retrospective analysis of existing products instead [3]. In particular in this paper the attention is focused on the Life Cycle Assessment Simplification method (SLCA) and ComputerAided LCA. Eco-design tools help the designer evaluate environmental aspects during the product design phase. Several approaches to eco-design have been studied. These tools are based on different techniques and characterized by different

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_99, © Springer-Verlag Berlin Heidelberg 2011

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570 levels of difficulty related to their implementation [4]. These approaches vary from simple checklists and guidelines as presented in Wimmer et al. and Stevels’ works [5,6], to complex methodologies, which require the designer to have a high level of personal knowledge in order to apply them correctly. Actually, many proposed approaches represent an “ecological” extension of traditional and well known design methods. This is the case of the different environmental versions of the Quality Function Deployment (QFD) [7], such as the quality function deployment for the environment proposed by Masui et al. [8] and the green QFD proposed by Zhang et al. [9]. An extension of the functional analysis method, which takes product life-cycle aspects during the design stages into consideration, was presented by Prudhomme et al. [10]. Recent efforts in developing holistic eco-design tools for industrial designers, as described in Lofthouse’s work [11], underline the importance of combining guidance, education and information with well considered content. In practice the current situation is unfortunately far from ideal. Designers still highlight a lack of coordination in the design activities and this obstacles putting the indications provided by eco-design tools and application guidelines into practice. Furthermore, it is often not so evident how to perform the comparative evaluation of the environmental impact of alternative eco-design solutions. For this reason CAD-integrated LCA tools could be useful and easily coordinated with the normal design activity. LCA represents an assessment and comparison tool for existing products. The idea to use it as eco-design method has been evaluated by many researchers [12]. In recent years, some of the debates regarding the methodology of LCA have focused on the development of SLCA methods. The main goal of SLCA is to reduce the complexity of several of the tasks involved, while maintaining the main features and soundness of a complete LCA. One projection for the development of such simplified methods has been the possibility to employ them during the early design stages of a product, when the data available is incomplete and lacking in details. Perhaps it should be underlined that a complete LCA can only be correctly used for completely defined products and services. It means that products and services and their components, materials and processes are precisely defined before the assessment. Different simplification methods have been proposed, though most of them are related in some way to the reduction of the amount of data required to perform the analysis. This data reduction is usually achieved by excluding some life cycle stages in the assessment as reported by Hochschorner et al. and Hur et al [13, 14]. Although the soundness of such simplified methods is still a matter of debate, some agreement seems to have been reached regarding the employment of SLCA to obtain qualitative results which can be used to evaluate alternative design solutions. A complementary approach, aimed at reducing the complexity of the compilation of the life cycle inventory required to perform LCA, is represented by the integration of LCA tools with product life cycle management (PLM) systems [15-19]. A PLM system is an Information Technology (IT) platform implemented within an enterprise, whose aim is to store and manage technical and administrative data related to the life cycle of the goods produced or services provided [20,21]. From a technical point of view, a PLM system is based on a central database, enabling integration of data produced by the different IT systems used by the different departments within the enterprise. Some examples of IT systems, which are part of a PLM solution, are: computer-aided design, manufacturing and engineering systems (CAD, CAM, CAE), material requirement planning, advanced production, manufacturing execution, enterprise resource planning systems (MRP, APS, MES, ERP), supply chain management and customer relationship

Life Cycle Assessment - Methods and Tools management systems (SCM, CRM). This approach which integrates LCA analysis and CAD software has even come up in the market in SolidWorks 2010 suite. The included eco-design tool is called Sustainability. It makes it possible to evaluate the product being designed from an environmental impact point of view. Therefore it is possible to compare different design solutions concerning the material and the transformation process selection. This last method seems to be promising in terms of rapidity and usability but needs to be verified in terms of accuracy. 3

LCA TOOL COMPARISON: TEST CASE ANALYSIS

Eco-design approach is becoming increasingly important in mechanical design, with the need for “green” products playing a key role in the current scenario. A CAD-integrated LCA approach is a powerful tool to compare different design solutions and to establish a real ecological benefit. There are some advantages of using CADintegrated LCA tools, in particular regarding the time necessary to conduct and elaborate the analysis. This aspect is a direct consequence of the simplification of the LCA analysis (SLCA) as well as of an easier use of tools integrated in the CAD system. This aspect increases the possibility for designers to estimate sustainability in the early design stages. The scenario in which the CAD-integrated LCA tool is focused is product design and in particular eco-design. Geometrical and dimensional aspects, material selection, shape definition and structural aspects must be evaluated only in the first design stages and these have a direct consequence on product sustainability. It is important to correctly estimate the effective value of environmental impact in order to compare different design solutions and choose the best one. In this paper the CAD-integrated LCA approach has been analyzed, with particular reference to SolidWorks Sustainability software included in the 2010 suite. The selected test cases for this work are generic mechanical parts: a plastic injection moulding part (Plastic cap), a machine tool product (Pinion shaft) and a sheet metal part (Carter). These parts have been selected as they represent the most common mechanical components and some important observations can be made regarding them. LCA analysis for these components has been performed with SolidWorks Sustainability and then compared with a complete LCA conducted with dedicated software (GaBi). The analysis for this work has been limited to the manufacturing phase. The analysis conducted with GaBi contains real process data and energy consumption referred to the company. Figure 1 represents the comparison of LCA results and the relative graphs which have been drawn according to quantitative values of the main CML 2001 impact categories [22]. In particular the four environmental indicators provided by SolidWorks Sustainability are: 

Carbon Footprint or Global Warming Potential [CO2];



Total Energy Consumed [MJ];



Air Acidification [SO2];



Water Eutrophication [PO4].

The first test case is the “Plastic cap”, made of Polypropylene (PP) by injection moulding process. The second test case is a “Pinion shaft”, made of common construction steel and manufactured by machining process (turning and grinding) and finished by bonding treatment (galvanizing). The last test case is a sheet metal part known as “Carter”; the final shape has been obtained from a stainless steel sheet, cut with laser machine and finished with bending process. Table 1 shows the LCA indicator results which have come up from the comparison between the analysis performed in GaBi and in SolidWorks Sustainability (SW).

Life Cycle Assessment - Methods and Tools

Plastic cap

571 limitation is in the material library available in the software, but this is not relevant in the count of total value of LCA indicators. Regarding the manufacturing phase in some cases relevant inaccuracies of LCA indicator values emerge. In particular it is not possible to assign different processes to a single component but only the main manufacturing process can be selected.

Pinion shaft

Table 1: LCA comparison between SW Sustainability and GaBi. Another relevant difference is the impossibility to modify the existent process available in the database. This can be the cause of significant errors. Each process has some input (such as energy, fuel, etc) and output (such as waste material) that can change from one factory to another, due to machinery and methods used. The errors in the results for the material depend on the amount considered, which corresponds to the weight of the finished CAD model. However, the amount of material that should be considered is the weight of the starting stock material. The error in the material impact referred to sheet metal and machining parts is more evident compared to injection moulding components where material waste is less significant. Due to these considerations the next paragraph describes an approach aimed at improving the robustness of a simplified CAD- integrated LCA analysis. 4

Carter

PROPOSED APPROACH

Starting from the positive aspects of the CAD-integrated LCA tools, it is possible to overcome the above identified drawbacks and to obtain an efficient tool for product eco-design. The following proposed approach aims at improving the result accuracy of LCA indicators, and, at the same time, to leave intact the benefits such as user friendliness, rapid visualization of LCA results and preliminary evaluation of sustainability at early design stages. 4.1

System architecture

The logical framework of the proposed CAD-LCA integration system is shown in Figure 2. Data flow can be managed and modified by a dedicated user interface which allows interaction with CAD and LCA systems. Product geometrical and non-geometrical data can be retrieved from the CAD structure and the connected PLM database.

Figure 1: different value of environmental impact quantities for the test cases (CML 2001). Looking at the results summarized in Table 1, it is possible to highlight that the simplified analysis developed with SolidWorks Sustainability is affected by relevant errors. The error in the material selection is due to the fact that SolidWorks Sustainability considers the weight of the finished component whereas GaBi takes into consideration the start weight of the raw material. If considering the same amount of material, the results would be coincident. The only

Figure 2: proposed CAD-LCA integration approach framework.

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Life Cycle Assessment - Methods and Tools

The geometrical CAD model implicitly contains different data about the component, referred to its shape and dimensions. These values are useful to determine the production process characteristics. The data can be extracted from the CAD software by analysing the CAD model data structure by the use of a specific software tool based on the Application Protocol Interface of CAD system. In this case the specific application has been developed in Microsoft .NET. Users can refine data and add others more if necessary. Manufacturing processes and component materials can be chosen from the LCA database. The user interface also allows connection with the machine process database. It contains all the information (energy consumption, utilization range, manufacturing process type, etc) of the different machines available in the company. According to the selected manufacturing process, a list of machines is shown in the user interface and the system proposes the most suitable by using decisional rules related to the specific geometrical product data. An important feature of the proposed approach is the possibility to modify the manufacturing processes selected from LCA database with the selected machine information (e.g. energy consumption). Therefore real process data can be computed. All the information from CAD and LCA software can be merged by the user and a “mass-material-process” link is created and sent back to LCA software to calculate the environmental impact of the product. The designer can select more than one process for each component in order to recreate the complete manufacturing cycle. The results are automatically presented in the user interface as data and graphs, allowing a rapid comparison between different solutions to be made. 4.2

user has the possibility to modify the starting sheet metal and specify the value of sheet scrap. The scrap for “Carter” is 38% of the starting sheet metal mass. Figure 3 shows the starting sheet metal proposed by the CAD software.

Figure 3: starting sheet metal for “Carter” proposed by CAD. This represents an important improvement in terms of accuracy of the LCA analysis. In the current commercial CAD-integrated LCA tool, the mass considered for the environmental impact calculation is the final component mass and it is not possible to set other information. Figure 4 illustrates an example of the sheet metal form containing all the required information for the analysis of “Carter”.

Product data analysis

The proposed approach distinguishes the different types of mechanical components according to the manufacturing processes that they undergo. As cited in section 3, main product components used in mechanics can be classified in three families, according to the manufacturing process: moulded components; machined components, and sheet metal components. These types of families and the related manufacturing parameters have been analyzed in order to reach the right compromise between LCA result accuracy and easy as well as rapid product data retrieval. Through the analysis of different manufacturing process characteristics, a list of parameters has been determined for each family. The main parameters related to the moulded family part are: material type, amount of scrap, percentage of recyclable scrap and the type of machine used. In the case of machined family part the parameters to be considered are: material type, starting stock material, the main machining processes, amount of scrap and the type of machines used. Finally, the parameters for sheet metal family part are: type of material, the starting dimension of sheet metal, amount of scrap, the type of machines used and the quantity of scrap which can be recycled. There are fundamentally three basic steps in order to perform the life cycle assessment analysis: to define the used material, to analyze the properties of component and, finally, to define the main manufacturing processes to transform the component from raw material to finished product. In order to exemplify the proposed approach the data analysis of “Carter” test case (see section 3) is reported. The first step is the material selection from the LCA database; in this case stainless steel (AISI 316) is selected. This step is exactly the same as SLCA with SolidWorks Sustainability. The second step is the mass calculation based on the component 3 volume and material density (8027 kg/m ). In this case the volume considered is the starting sheet metal used to obtain “Carter”. The

Figure 4: example of sheet metal form for “Carter”. The impossibility to consider the material scrap implies a different calculated mass for the analysis and a consequent error in the environmental impact calculation. The third step is the manufacturing process selection. According to the geometric properties of the component and the utilization range, the software automatically proposes a specific machine for this process regarding the machine database. Designers can select the proposed machine or a different one on the basis of their experience and needs. The machine consumption must be referred to the specific manufacturing operations. For example, in the case of “Carter” the manufacturing cycle is composed of both sheet metal “laser-cutting” and “stamping and bending” operations. For the “laser-cutting” operations, the length of the cutting path is extracted from the CAD model by a specific developed algorithm. The machine consumption is calculated with reference to this value. The laser-cutting machine power consumption is 0,66 kW/m for “Carter”, the total energy needed for this operation is calculated on the length of the cutting path. From the CAD model the extracted cutting path length is 3,325 m, the power consumption for this process is 2,21 kW. The same calculation has been made for the other machine parameters (cutting gas, lubrification, etc). Similar steps can be applied for “stamping and bending” operations. In this context the consumption considers the number of bends, extracting this value

Life Cycle Assessment - Methods and Tools

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automatically from the CAD model. As regard Carter the machine power consumption is 0,004 kW/bend and the bend number is 5, so power consumption for this operation is 0,021 kW. The same calculation has been made for the other machine parameters (compressed air, lubrification oil, etc). The selected LCA manufacturing processes are modified according to the machine properties and therefore the real environmental impact is computed. 5

APPROACH VALIDATION AND DISCUSSION

In order to validate the proposed approach in a more general context the three components reported in section 3 have been analyzed. The achieved results have been compared to the complete LCA analysis conducted with a dedicated LCA software (GaBi), in order to verify the approach in terms of accuracy. 5.1

Experimental case studies

Figure 6: comparison result between Proposed approach and GaBi analysis for the “Pinion shaft” (CML 2001).

The following tables (tables 2-4) report the use of the manufacturing cycle for each component by adopting the three different systems (our proposed system, GaBi and SW Sustainability).

Table 2: “Plastic cap” manufacturing cycle.

Figure 7: comparison result between Proposed approach and GaBi analysis for the “Carter” (CML 2001). 5.2 Table 3: “Pinion shaft” manufacturing cycle.

Table 4: “Carter” manufacturing cycle. In all cases the analysis only takes the main manufacturing processes into consideration; for example the washing-degreasing and galvanizing processes have not been taken into account for the Pinion shaft. The other parameters (product model and manufacturing machines) have been fixed by adopting the functionalities provided by the three tools. The obtained environmental results for the components are reported in Figures 5, 6 and 7.

Figure 5: comparison result between Proposed approach and GaBi analysis for the “Plastic Cap” (CML 2001).

Result discussion

As it is possible to see in tables 1 and 5 the comparison of results gives the opportunity to discuss the three different approaches. Regarding the material environmental impact, the error is attributed to the different amount of material computed for the analysis. SW Sustainability considers the weight of the finished part, so the impact result is underestimated, whereas with the proposed approach the amount of the material considered is the weight of the starting stock material used to obtain the finished product. In the proposed approach the information about the stock material is extracted from the CAD model using specific algorithms for each product family, and the users can modify this information selecting a specific stock material on the basis of their knowledge of the specific company process. Thanks to this approach, the error for the material selection has been completely deleted (Table 5). Regarding the manufacturing process, the error derived from the SW Sustainability approach is attributed to both the simplification of the process cycle and to the lack of data on machines used. It is important to note that only the principal process could be selected and no machine data could be specified, so the choice is forced by the specific approach. The proposed approach allows the choice of different processes which can concur in production cycle and the modification of the process data input according to the component being analyzed by extracting information from the CAD model. Thanks to these modifications we are able to consider the real manufacturing process therefore the environmental impact result depends on the user’s choices and not on the approach limitations. According to the standard settings only the main processes are calculated, and the result error is minimal compared to the complete analysis. Most of the information required for the analysis is extracted from the CAD model. The user has to insert some easily available information, so the time to obtain an environmental impact value for the product is comparable with the available commercial

574

Life Cycle Assessment - Methods and Tools

CAD-integrated LCA tools. The user knowledge is essential to obtain a complete and accurate analysis. The proposed approach guides and speeds the user process up thanks to the automatic process and machine selection. For specific manufacturing cycles and high result precision, the user inputs based on experience and knowledge are certainly necessary. Using the proposed approach, the result error has been drastically reduced to less than 7% (Table 5).

Table 5: LCA comparison between Proposed approach and GaBi. Considering the material and the manufacturing process the overall error is less than 3% for the Plastic Cap, 2% for the Pinion shaft while less than 1% for the Carter (Table 5). 6

CONCLUSIONS

This paper shows how the current SLCA systems based on the integration of CAD tools with LCA databases are still deeply inaccurate. Firstly they neglect the whole life cycle (in particular use and dismantling), secondly the estimation of material used and manufacturing cycle impact are treated with too little detail. This paper proposes an approach where the same system structure (CAD, machine and LCA databases) are more efficiently integrated by extracting the right amount of geometrical and non-geometrical data from the CAD data structure and PLM databases. This approach is able to set a good LCA estimation and achieve a high usability in the early product design phases. The experimental results obtained from the analysis of different components in the mechanical production field show the high potential accuracy. The future developments of this research work will be dedicated to the formalization of all main manufacturing processes in the mechanical field in order to extract the needed data/parameters for SLCA. The sensitivity analysis on these parameters will allow the right order of priorities between parameters to be established in order to further simplify the approach. Finally, this approach will be implemented in a software tool to support the product designer’s day-to-day work. 7

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Hur T. et al. (2005): Simplified LCA and Matrix Methods in Identifying the Environmental Aspects of a Product System, Journal of Environmental Management, vol. 75, issue 75, pp. 22 –237.

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Hochschorner E., Finnveden G. (2003): Evaluation of Two Simplified Life Cycle Assessment Methods, International Journal of LCA, vol. 8, issue 3, pp. 119–128.

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Otto H. E. et al. (2003): Integration of CAD Models with LCA, Proceedings of 3rd International Symposium on Environmentally Conscious Design and Inverse Manufacturing - EcoDesign, Tokyo, Japan.

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Morbidoni A., Recchioni M., Otto H. E., Mandorli F. (2010): Enabling an efficient SLCA by interfacing selected PLM LCI parameters, Proceedings of TMCE 2010 Ancona, Italy.

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Stark J. (2006): A PLM Handbook Has Finally Arrived, Product Lifecycle Management: 21st Century Paradigm for Product Realization, Springer, London, U.K.

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Guinée J., Heijungs R. (1992): Environmental life cycle assessment of products: Guide, CML, Leiden, The Netherlands, NOH report 9266.

Comparison of two LCA Methodologies in the Machine-Tools Environmental Performance Improvement Process 1

1

1

Mariana Azevedo , Marta Oliveira , João P. Pereira , Ana Reis 1 2

2

Instituto de Engenharia Mecânica e Gestão Industrial, Campus FEUP, Porto, Portugal

DEMec, Faculdade de Engenharia, Universidade do Porto, Campus FEUP, Porto, Portugal

Abstract This paper presents the results of a comparison between a simplified LCA analysis and a detailed LCA carried out under a Ecodesign project of a machine-tool, a commercial CNC press-brake. The aim was to assess to what degree, the most detailed information resulting from a detailed LCA, allows decisions qualitatively superior in terms of environmental efficiency of the equipment to redesign. This work was also intended to initiate a process of establishing guidelines to support these studies, particularly in the case of its application to complex mechanical and electromechanical systems such as machine-tools. Keywords: Ecodesign; LCA Methods; Machine-tools.

1

INTRODUCTION

Life Cycle Assessment (LCA) refers to an evaluation of the environmental profile of a product taken along its entire life cycle, i.e., from raw-material extraction to its final disposal. Thus, any LCA study is supposed to refer to all life cycle stages, even if just qualitatively, and a different term should be adopted for ‘partial’ LCA studies, although this has been not always considered [1-4]. In what concerns the LCA methodology, guidelines have been established by different groups working worldwide (such as ISO, SETAC, EPA and CSA). For Europe, a LCA study has to comply with ISO 1404X standards to be publically accepted. The methodologies standardized by these guidelines are generally recognized has ‘full’ LCA methods, and any simplification from this gives rise to simplified LCA methods. Every LCA methods might use qualitative, quantitative or semi-quantitative analysis, although the quantitative form is considered more suitable for detailed LCA studies [1, 3]. In order to overcome the significant effort in time and resources typically associated to a detailed LCA, several simplified techniques have been proposed either from the scientific community or consultancy from several economical sectors. A list of comparative studies between LCA tools and methods was compiled and analyzed by Bala [5], concluding that the most common simplification strategies are based on reducing categorization scope, such as limiting inventory or impact categories, or on simplifying procedures, by using qualitative information, data from previous studies and/or threshold levels for specific inputs. This obviously deviates from the referred standards, making more difficult the methodological standardization of simplified LCA, and limiting its application to internal studies. On the other hand, the strong potential of simplification techniques for studies of specific product systems or sectors, adapting ‘customized’ or ‘tailor-made’ perspectives, has been pointed out, as these enable to include sector-specific principles and practices more relevant and appropriate to the interested LCA end-user, while still producing valid and robust results [1,5,6]. This is particularly important in product system (re)design studies, where sector-specific values are

determinant to the new product specification to be built. In this perspective, Hochschorner et al [3] highlighted the importance of the method applicability to the field of application as the most important selection criteria of the proper LCA method to adopt, in order to deliver the required information. The potential of a particular simplified LCA method designed to fit the needs of a specific product or sector, while keeping the LCA basic conditions regarding scope and methodology, is indeed to emphasize, as several common conditions existing between products and companies would simplify the LCA process by itself. Particularly for complex multi-components product systems, such as a machine-tool, the use of data from previous studies is just one of the evident benefits: as many product parts are common, this would enable a standardized part classification and even the creation of LCI sets for product sub-systems, as suggested in the Black Box concept proposed by the present authors [7]. Another opportunity would be to limit the environmental impact categories to analyze, as the main reasons for the environmental impact are maintained from product to product of a similar technology [1]. Moreover, special care should be taken with the process inventory formats and quality, but also here common methods for search and acquiring of similar data could be established, assuming most companies of a specific sector work with analogous internal ERP languages and systems, and/or have access to common external data sources, like suppliers or sector associations. The result of the interesting survey conducted by Junnila [8] indicates the urgency of such common methods to be adapted to companies’ organizations. The results clearly showed that the relatively long overall time of LCA studies was mostly related to excessive waiting time during inventory, and not to the difficulty on finding the required information. Instead, the dispersion of information throughout the company sectors and persons, and the extra work that this represents to the persons involved, have been referred as the main reasons between net and gross times for LCA inventorying. In any case, the overall time for the detailed LCA projects typically exceeded 2 months, which is far above the maximum of 20 days suggested by Guinée [9] for an execution of a simplified LCA study.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_100, © Springer-Verlag Berlin Heidelberg 2011

575

576 The most appropriate conditions to obtain the required level of detail and quality of the LCA inventory is another controversial point, to which advantages and disadvantages of simplified vs detailed LCA methods have been discussed, and several hybrid or iterative processes for data fine-tuning have been suggested [3,5,7,9]. On the practical side, particularly on preliminary product evaluations, it seems realistic to start focusing on main material and energy inflows, as this is easier to obtain than emissions data. In any case, as detailed in the procedure of Lewansdoka et al [10], for implementation of the guidelines previewed in the Ecodesign Directive 14062, the inventory compiled by the LCA method should be detailed ‘enough’ to reveal the weaknesses of the product under study, in the form of the following parameters: (1) the overall environmental effect generated throughout its entire life cycle, (2) the relative contribution of each particular life cycle stage to the total environment impact, (3) the mostly affected environmental impact categories, and (4) the main inputs and outputs responsible for those impacts, indirectly revealing the main design changes to focus for an improved environmental profile of the product system. The case of machine-tools The present case-study is a metal-sheet forming machine-tool. Machine-tools appeared in third position in the ranking of energyusing products (EuP) with significant environmental impact, and currently a large discussion is being held by several stakeholders regarding the LCA approach to adopt for this sector. The product categorization to adopt and the LCA methods to use are still controversial, mostly due to the innumerous types of machine-tools and respective plurality of environmental profiles. As highlighted by Junnila [8], even the European Commission has used different methods in different situations. In the elaboration of the EuP directive, by using the MEEuP methodology, the report focused on the dominant contribution of the energy consumption during use to the overall environmental impact of the energy-using products. Similar methods and statements are being presented by the working group dedicated to the machine-tools assessment. However, as advanced in a previous report of the present work [11], the first detailed LCA of a standard press-brake has shown that, when compared to the contribution of energy consumption during use, materials and energy resources integrated during machine-tool manufacturing presented a similar contribution to the total potential environmental impact. Moreover, the particular system technology and utilization mode also play important roles on the accounting of energy consumption during use, although this has been neglected on the common LCI databases, and considered only in extensive sensitivity analysis complementary to the standardized LCA methods. Other studies about the environmental performance of machine-tools are supporting these evidences in other equipment types [7, 12-14]. As an example, when evaluating a welding equipment, Junnila [8] confirmed material and processing resources as main contributors to the majority of the impact categories, while, the operating energy of the equipment during use dominated only moderately in climate warming and acidification categories. Moreover, the strong influence of the utilization mode on the contribution of the use phase to the environmental profile of such EuPs was also emphasized, and the need for more methodological and practical studies focused on the behavior of users was suggested. The work here proposed intends to contribute for selecting the most appropriate LCA method to be used for the Ecodesign of a machine-tool. The objective is to understand to what extent an extremely detailed LCA method involving relative high part detail level and relatively complex modeling and accounting methods contributes to qualitatively superior results and Ecodesign decisions. A standard commercial press-brake was used as case-

Life Cycle Assessment - Methods and Tools study and the LCA result of 2 methods, differing mostly on the type and sources of the process inventory data, is compared regarding the 4 parameters indicated above for the identification of the weaknesses of the product system to redesign. 2 2.1

METHODS AND EXPERIMENTS Product system characteristics and available inventory

For product systems of high complexity, such as a machine-tool, often integrating a huge quantity of parts, the manufacturing inventory required for a reliable LCA is a major task. The bill-ofmaterials (BoM), when available, typically includes different detail levels for manufactured or purchased finished items. While for manufactured parts, materials and processes data are available inhouse, in the later case a similar detail level is almost unfeasible, particularly for multi-components items with high complexity, as motors or pumps, considered as black-boxes. For such cases, parameterization techniques have been proposed [6, 15], based on a combination of eco-relevant functional and/or design parameters pre-defined in order to maximize the LCI parameters’ reliability. The machine-tool to redesign was a commercial hydraulic pressbrake of standard construction from 2006, made in Portugal. This equipment is specified to operate at a maximum bending capacity of 110 t and a maximum bending length of 3 m, with a main motor rated at 7.5 kW, with a total weight of about 6.6 t. For the purposes of this study, an inventory list of the integrated components was provided by the manufacturer, which consisted on a list of part references grouped by levels corresponding to the product tree of the machine, structured according to the internal assembly logic of the manufacturer. The cost per piece was indicated for all parts, and additional technical information about materials and manufacturing processes was included. The available information per part differed according to the part category adopted in this framework [6]: manufactured parts (materials and manufacturing processes details), standard parts (materials details only) and black boxes (reference and model details). 2.2

LCA methods under evaluation

A cradle-to-grave LCA of the press-brake was followed, by applying the two LCA methods to be compared, named as Direct method and Detailed method. The Direct method refers to a simplified approach explained ahead. These methods differed mostly on the complexity of the inventory content and accounting methods, with direct impact on the time effort needed to complete the analysis, of about 1-2 weeks on the Direct method and 2-2.5 months on the Detailed method. The main inventory differences involved the inputs related to the Assembly and Use life cycle stages of the equipment, while fixed scenarios were used for Transport and End-of-life stages. The specific inventory conditions adopted for each method are compiled on Table 1, and the differences are additionally described as follows: 

Direct Method: This method consisted on the direct application of data selection techniques to the technical data available. As Assembly stage’ inputs, the analysis focused on 8 main level groups and no part detail level analysis was followed. For each main group, the part inventory list was filtered by material type (steel-based, aluminum and nylon) and the respective cumulative mass values were taken. The total raw material mass value was used as material input, while the total part mass value was used as process input. Standard parts were ignored and the electric motor was the only black box accounted, based on estimations presented on a specific report [7]. The electricity consumption during use was estimated from theoretical calculations based on a schema of the electro-

Life Cycle Assessment - Methods and Tools

577

hydraulic driving system of the equipment, provided by the manufacturer. 

Detailed Method: This method consisted in an intensive utilization of the part individual data provided. All material types and quantities involved, as well as all individual manufacturing processes, have been considered per part, for a total of 368 components. The in-house manufactured parts were modeled in 3D CAD software and the related assembly-phase data were collected through a process similar to the CAD Add-in developed in-house, as described previously [7]. All functional components of the electro-hydraulic driving system, such as the main electric motor, the hydraulic pump and all valves, have been included. These components were treated as black boxes and all related inventory was modeled in separate. Despite the higher number of components considered, the different mass accounting methods applied resulted on similar total weight values. The electricity input value considered for the energy consumption during use was accounted assuming a manualintensive mode, according to categorization of bending operation mode proposed in a parallel report.

Finally, all environmental analysis generated was followed by application of the Eco-Indicator 99 (H,A) method, using SimaPro 7.0 with Ecoinvent 2.0 unit processes as LCI database [17-19]. LCI

Life cycle Stage

Type/Scenario

1. ASSEMBLY (Acc. part categorization [x])

Mat.

Hydraulic Oil 4. END-OF-LIFE (Disposal: Reuse [x])

Source Value

Electricity

Export (second-hand)

Overall environmental impact

Figure 1(a) shows the LCA result obtained with both methods, in terms of the global environmental potential impact of the machine. The Detailed method resulted on an impact indicator value about 45% higher than that obtained with the Direct Method. The higher complexity on manufacturing processes considered for machine production and the higher energy consumption during use considered in the Detailed method are understood to be the main contributors to this result (Figure 1(b)), besides the higher number of components, particularly black boxes, introduced.

Method DIRECT Cumulative mass value per mat. (initial raw material weight), per sub-system. Electric cabinet: Total mass value

Proc.

3. USE (Yearly consumptions, lifetime: 15 yrs)

3.1

Mat.

Value Export

RESULTS AND DISCUSSION

The results achieved throughout the application of the two inventory methods were compared relatively to the 4 LCA outputs referred, giving rise to a top-down perspective where the bottom detail level is expected to enable the identification of the main Ecodesign changes to apply.

343 components / 6.571,7 kg

Proc.

2. TRANSPORT

3

Qty.

Manufactured

Black Boxes

datasets of secondary metals were used whenever applicable. The main inputs related to the use phase, electricity and hydraulic oil, were distinguished as different use phases, to assist their individual impact during the analysis. The LCA outcome results from Single Score analysis.

Source

Value Source Value Source

DETAILED 368 components / 6585.4 kg

type Individual mass value per part (raw material weight of manufacturing block automatically selected per 3D CAD model) Relevant specific LCI parameter (waste Cumulative mass value per material type mass, length, area or processing time) automatically calculated per processing step (final part weight value) from the 3D CAD model Electric motor only: Total mass values per material Electric motor, Hydraulic pump and Valves, type, estimated acc. [x] modeled acc. [x]. Not considered 260 km road transportation + 9000 km water transportation - Avg. from manufacturer internal sales records Jan/2000-Apr/2009, - Worst case-scenario considered: sale to a non-european country ( 30% of the sales). 3516 kWh

5475 kWh

- According to theoretical estimations based on actual driving system - Usage: 2000 h (8 h*250 days), 12.5% in working mode [x] - Load worst-case scenario, 110 t (max)

Real consumption measurements - Usage: 2000 h - Ref. case-scenario, manual-intensive production mode (n=80 cycles/h) [x]

120 L/yr - Acc. Preventive Maintenance Plan provided by the Manufacturer [16] 400 km road transportation + 9700 km water transportation - Estimation, avg. distance to Asia, Africa or South America far countries

Table 1: Inventory conditions considered in the execution of the LCA methods under evaluation.

Life Cycle Assessment - Methods and Tools 7000

6000

6000

5000

5000

4000 3000

100%

Others Use_Elect.

90%

Assembly

80%

Contribution to EI'99

7000

EI'99 [mPt]

EI'99 [mPt]

578

4000 3000

2000

2000

1000

1000

0

0

70% Reuse

60%

Use_Oil

50%

Use_Electricity

40%

Transport

30%

Assembly

20%

(a)

DIRECT DETAILED

(b)

10% 0%

DIRECT

DIRECT DETAILED

DETAILED

Figure 2: Comparison of the different LCA methods tested, regarding the relative contributions of life cycle phases to the global environmental impact of the press-brake under redesign.

3.2

Contribution of each life cycle stage to the overall environment impact

determined as a function of the utilization mode, which should be validated for each case.

Figure 2 shows the relative contributions of each life cycle phase to the global environmental impact of the machine. Assembly inputs and electricity consumption during machine use have major impacts on the environmental performance of the current equipment. The assembly phase appears with a significant contribution of about 40%, independently on the method applied, which is sustained by the parallel increase of inputs associated to the assembly and non-assembly phases. In the later case, the single and significant increase on the energy consumption value, estimated for the use phase in the Detail method, resulted on the reduction of the potential impact of all other life-cycle phases which inventory inputs were kept constant. Although their major contributions become clear at this point, assembly and energy consumption during use appear in switched top positions of impact when different inventorying methods are applied. It must be noted that, in the Detailed method, the energy consumption value was

Figure 3 presents the distribution of the global environmental impact shown in the previous figures by the standard environmental impact categories (middle-points), revealing those to which the current machine is potentially more detrimental. The profile showed that the main impacts are related to the depletion of minerals and non-renewable resources, such as fossil fuels, and to the release of respiratory inorganic emissions involved in these processes. This is understood to result from the potential impacts typically associated to the raw materials and manufacturing processes integrated in and with the assembly components, as well as to the electricity source and supply impacts considered in the energy inputs required during the machine use. These were consistent results obtained from both methods, as expected from the contributions of the different life cycle phases shown in Figure 2.

3.3

Most affected environmental impact categories

3000

3000

2500

2500

2000

2000

EI'99 [mPt]

EI'99 [mPt]

Figure 1: Comparison of the (a) global environmental impact and (b) contribution of main LC stages, for the press-brake under redesign, and obtained from the different LCA methods tested.

1500 1000

1500 1000

500

500

0

0

Assembly

Transport

(a)

Use_Electricity

Use_Oil

DIRECT Method.

Reuse

Assembly

Transport

(b)

Use_Electricity

Use_Oil

Reuse

DETAILED Method.

Figure 3: Environmental profile of the current machine by middle-point impact category, as obtained from the different LCA methods tested. The life cycle stages’ contributions is also shown.

Life Cycle Assessment - Methods and Tools 3.4

579

Main inputs and outputs responsible for the impacts identified

While the electricity consumption of the machine during use corresponds to one single input, a deeper analysis is required to the Assembly phase contributors, in order to reveal the main unit process contributors to the previous environmental impacts identified. Figure 4 presents the relative contributions of the main machine sub-systems to the environmental impact of the current machine in the Assembly stage (sub-systems original references and deeper breakdown analysis to component level were omitted due to confidentiality restrictions with the manufacturer). The major impact introduced by sub-system A, responsible for about 65-69% of the environmental impact associated to the assembly phase, is highlighted. The Direct method points out a second main contributor (sub-system H), while the application of the Detailed method revealed that similar secondary contributions could result from sub-systems C, E and H.

Contribution to EI'99

100% 90%

H

80%

G

70%

F

60%

E

50%

D

40% 30%

C

20%

B

10%

A

0%

DIRECT

DETAILED

Figure 4: Comparison of the different LCA methods tested, regarding the relative contributions of the main machine systems to the environmental impact of the current machine during the Assembly stage. From this point onwards, the prossecussion of the analysis to deeper detail levels differs significantly between the methods under evaluation. In the Direct Method, the next and final step linked directly to the unit processes associated to the main systems, without any identification of the origin component. Similar results were obtained with the Detailed Method, although additional 2 system breakdown levels had to be analysed. In this case, as subsystem A groups the external massive structural components of one same material type, it was clear that the material input and the associated manufacturing processes dominate the overall impact attributed to the assembly phase, and the missing identification of the responsible unit components, associated to the Direct method, was not a critical point. However, in case the dominant contributor could not be changed as a whole and, in alternative, an approach to a component level on sub-system A or to other second-priority subsystems would be feasible, the methods would give rise to completely different redesign approaches. At this point, the advantages associated to the component level analysis inherent to the Detailed Method might play an important role, on the identification of relevant components to be redesign, either according to their individual impact or, in a more integrated

approach, according to their interaction with the driving system of the machine, which is responsible for its energy consumption. 3.5

Discussion

In the present case-study, both LCA methods guided to similar conclusions regarding the identification of main contributors to the majority of the environmental impact accounted, namely the steelbased machine structure and related manufacturing processes, and the electricity consumed during machine utilization. From both methods, it was possible to conclude that, although the product system integrates completely different sub-systems and a huge number of components, only a small number of these is in fact responsible for the main impacts attributed to the Assembly stage, which was expected since they comprise about 80% of the total weight incorporated. This was determinant for the global result, as this overlapped the significant differences of the energy consumption values introduced by the accounting methods and/or utilization mode considered. The relative low-energy consuming character of the bending process, when compared to other standard machining processes, is understood to be the main reason for this dual contribution. From this, the Ecodesign recommended changes to focus are clear: (1) the reduction of dimensions, quantities or alternative materials of lower impact for the main structural components and (2) alternative driving systems targeting energy consumption savings during use. However, and although, for this particular Ecodesign study, the application of both methods provided similar results, which by itself would justify the adoption of the resourceless and capable Direct Method in future similar cases, the differences found for the overall environmental impact parameter are considered significant and points to the need for case-by-case evaluation. As the result of the Direct Method depends mostly on the structuring (product-tree), quality and sourcing of the inventory provided by the LCA customer, in case of comparative studies (typical for rankings or go-no-go decisions), the application of this method might be of low usefulness. In alternative, as long as similar LCI data detail level and accounting methods are guaranteed, the Detailed method provides for comparable and reliable LCA results. Furthermore, particularly for redesign projects, as the new machine or part of its sub-systems have to be specified from scratch, the Detailed method allows comparative analysis on a component or sub-system level between the current and new alternative systems. In what concerns the estimation of the energy consumption of the new machine, and thus the improvement of the energy efficiency of the machine during use, it must however be guaranteed that the alternative technologies are included in the real consumption measurements study followed for the inventory of the Detailed method, and that similar utilization modes were considered. 4

SUMMARY

This paper summarizes the comparative study of two LCA methods, a simplified Direct Method and a Detailed Method, when applied for the analysis of the environmental profile of a highly complex energy-using product system (a machine-tool), in the framework of an Ecodesign project. Both methods made use of the product-tree and manufacturing data provided by the manufacturer, but differed on the sub-systems detail level, data quality and accounting methods considered. The application of both methods revealed the same priorities for reduction of the environmental impact of the product, indicating that the simplified Direct Method is capable to identify the main Ecodesign strategies to optimize the overall environmental impact of a complex product system. The identified strategies were tied to the points with largest contribution to the overall impact, which, in

580

Life Cycle Assessment - Methods and Tools

the case of the machine-tool analyzed, correspond to the structural components of high dimensions and to the electricity consumption during utilization along the relative long lifetime of the machine.

[10]

Lewandowska, A., Kurczewski, P., (2010) ISO 14062 in theory and practice – ecodesign procedure. Part 1: structure and theory. Int J Life Cycle Assess 15:769-776.

On the other hand, when compared to this simplified approach, the Detailed Method accounted for an environmental impact 45% higher, showing that the simplifications made in the Direct method inhibit to account for the real contribution of the main environmental detractors on the system, such as the estimation of electricity consumption during the use of the machine and the simplification in the manufacturing processes identified. In other systems, with no predominant detractors, this might be particularly critical, as the error introduced by the simplified approach might lead to different prioritization for design changes.

[11]

Santos, J. P., Oliveira, M. I., Almeida, F. G., Pereira, J.P., Reis A., (2010) Improving the environmental performance of machine-tools: influence of technology and throughput on the electrical energy consumption of a press-brake, paper in press on J Clean Prod (DOI: 10.1016/j.jclepro.2010.10.009).

[12]

Devoldere, Tom, Dewulf, Wim, Deprez, Wim and Duflou, Joost R. Energy Related Life Cycle Impact and Cost Reduction Opportunities in Machine Design: The Laser Cutting Case [online]. In: CIRP International Conference on Life Cycle Engineering (15th : 2008 : Sydney, N.S.W.). LCE 2008: 15th CIRP International Conference on Life Cycle Engineering: Conference Proceedings. Sydney, N.S.W.: CIRP, 2008: 412-419.

[13]

Dietmair, A., Verl, A., 2010, ‘Energy consumption assessment and optimization in the design and Use phase of machine tools’, Proceedings of the 17th CIRP International Conference on Life Cycle Engineering, Anhui-China, May 19-21, 116121.

[14]

Dietmair, A., Zulaika, J., Sulitka, M., Bustillo, A., Verl, A., 2010, ‘Lifecycle impact reduction and energy savings through light weight eco-design of machine tools, Proceedings of the th CIRP International Conference on Life Cycle 17 Engineering, Anhui-China, May 19-21, 105-110.

[15]

Dick, M., Dewulf, W., Birkhofer, H., Duflou, J., (2004) Estimating the environmental impacts of similar products, International Design Conference – Design 2004, Dubrovnik, May 18-21, 1-6.

[16]

Manufacturer preventive maintenance plan, www.adira.pt, Last visited: October 2010.

Considering these capabilities, the application of the Direct method is recommended when screening a product for prioritization of Ecodesign changes, particularly when this is dominated by a few number of sub-systems. For other purposes, such as comparative studies between products, the adoption of the Direct Method should be carefully considered, as the result is highly dependent on the quality and structuring of the inventory provided by the manufacturer. In any case, the Detailed Method was shown to be a highly accurate and reliable LCA method, particularly when huge amount of data need to be integrated. 5

ACKNOWLEDGMENTS

This work was developed in the frame of the Co-Promotion Project 3406, from the Program of Incentives to Technological Research & Development, supported by the Portuguese Agency of Innovation, to whom the financial support is to be acknowledged. 6

REFERENCES

[1]

Curran, M. A., Young, S., (1996) Report from the EPA conference on Streamlining LCA, Int J Life Cycle Assess 1 (1):57-60.

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Todd, J. A., Curran, M. A., (1999) Streamlined Life cycle assessment: A final report from the SETAC North America Streamlined LCA workgroup, SETAC Report

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Bala, A., Raugei, M., Benveniste, G., Gazulla, C., Fullana-iPalmer P., (2010) Simplified tools for global warming potential evaluation: when ‘good enough’ is best, Int J Life Cycle Assess 15:489-498.

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database,

Developing Impact Assessment Methods: an Approach for addressing inherent Problems 1

1

Marten Toxopeus , Vincent Kickert , Eric Lutters

1

1

Laboratory of Design, Production and Management, Faculty of Engineering Technology, University of Twente, Enschede, The Netherlands

Abstract In developing new impact assessment methods (IAMs), for environmental applications, as well as for non-environmental disciplines, many inherent and underlying problems are encountered. Such problems hamper the development of IAMs and their adequate use, because it is difficult to assess which problem plays the most important role. Moreover, circumstances and the influence of the problem on the method and its development are uncertain. This publication describes the foundation of a framework that integrates methods, context and circumstances, and denotes problems and directions for possible solutions. A scenario describes the possible employment of the framework in developing a new impact assessment method. Keywords: Impact Assessment Method; Non-environmental LCA; Method Development

1

INTRODUCTION

For future development cycles of sustainable and rational products, the consideration of the entire life-cycle with respect to different subjects is of the utmost importance. The subjects not only include environmental impact, but also encompass many other subjects, ranging from employability via safety to life cycle costing. Underlying this consideration is the analysis of impacts of actions, products or available services. Given the increasing attention for especially the non-environmental impacts, there is an increasing need for the development of impact assessment methods on these subjects. Historically, many methods have been developed to facilitate the different perspectives on environmental impact indicators. However, many of these methods have been built upon previous initiatives, leading to a collection of interrelated methods (see figure 1), with the accompanying accumulation of assumptions on application area, circumstances and context. Next to the ‘family’ of methods, a number of other methods have been developed for more specific situations, and from more specific perspectives. In preparing the future engineers for their careers, the students at the University of Twente are trained in understanding existing

methods. Moreover, they are challenged to develop impact assessment methods for different subjects, stressing the importance of the non-environmental application of LCAs. Both from experiences in industry and the findings from the many students working with IAMs, a number of issues emerged that seem to indicate a number of problems that show considerable similarities with the well-known problems in existing environmental impact methods. These problems may have the same background, being the fact that during impact method development the choices that have to be made are not clearly defined, or are implicit to the developer. Moreover, the consequences of these choices on the remainder of the development cycle cannot be overseen. This gave rise to the assumption that these problem types are inherent to the process of developing impact assessment methods. Therefore, a different approach for the development of impact assessment methods is required. 2

AIM

In order to address the common problems in the development of impact assessment methods, an approach is required that is capable of integrating multiple perspectives, and takes into account the requirements of different types of users. Moreover, the consequences of specific circumstances or context need to be addressed in an explicit manner, thus avoiding to overlook choices that should have been made. In general terms, this implies that the developer of an impact assessment method is confronted with the vast complexity of the solutions space he or she is working in. Especially inexperienced developers, or people that are occasionally involved in the development of assessment methods lack the skills, experience and knowledge to quickly address the complex and interrelated set of decisions that defines the IAM. As the decisions are interrelated, the initial decisions might strongly influence the overall development process. This often causes iterations in that process.

Figure 1: Overview of different impact assessment methods.

This implies that a framework is required that facilitates developers of IAMs in overcoming the complexities that are involved in the

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_101, © Springer-Verlag Berlin Heidelberg 2011

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developing process. The framework will not render the method in itself, it will aid the developer to rationalize and underpin the decisions that are made, but it will also help to focus on which decisions have to be made. To obtain an overview of the complexities the developer is confronted with, there are a number of requirements that can be imposed on the framework: 

Provide a well-structured and transparent depiction of the interrelations between the inputs, outputs and controls of the method under development.



Provide a support in identifying and recognizing analogous problems in IAMs.



Provide solution paths that help the developer to come up with a well-founded strategy.



Provide an overview that tracks which choices have been made, and lists consequences for other choices.



Provide a developer with support in assessing the accuracy of the method under development.

This publication describes the development of the framework for facilitating IAM developers. It gives an overview of the process steps in developing impact assessments methods and the inherent decisions to be made. 3

ASPECTS IN IAM DEVELOPMENT

With the introduction of the CML ’92 [1], environmental impact assessments were given a structured framework, clarifying environmental impact assessment methods (EIAM) and providing a guideline for calculating the life cycle assessments on the subject, of environmental impact in this case. Although impact assessment methods had been used for years, the structure and approach from the CML ’92 provided a base that was often followed in other environmental assessments. With this framework for determining interventions, classification and effects, new methods followed with the intent of delivering result sets that were more appropriate for the context and the intended users. While the CML’92 was aimed at an academic audience that intended to gain insight in the environmental impact of their

products or processes, its successors developed in different directions. Simultaneously, aims shifted towards more precise results and extended effect sets on the one hand and more business aimed result sets on the other hand. In figure 1, the relative position to the CML '92 method is depicted for a selection of methods. Consequently, subsequent methods engendered a diversity of result sets. As elements of the original approach had a continued effect in successive methods, certain obstructions that presently influence the process and results can be traced back to the basis of CML '92. In order to address these influences, each subsequent step and its impact on the method requires clarification. 3.1

Approach

Whereas the result of each method is different by design, the structure of the method is not. Each element in the framework demands careful attention and understanding in order to coincide with the other parts of the framework. In order to develop an assessment method that performs, not only as expected but with pre-chosen precision and solutions, this attention needs to focus on the archetypical obstructions from the original method. To instigate the development, a clear overview of the structure of an IAM is needed. As figure 2 illustrates, IAM’s can contain several phases where each are linked by specific transformation mechanisms, as represented in the lower half. A phases of a LCA, such as inventory, impact on effects, damage assessments and the construction of indicators, hold specific actions and interrelations. Depending on the preference for the type of IAM, different elements of the depicted general phases in figure 2 have to be constructed. To preserve the coherence of the method, the correct transformation mechanisms between elements have to be constructed. Some of these transformations, although often present in IAM's, are discouraged by the ISO standards [2, 3]. 3.2

Subject and Results

The first and perhaps foremost step in developing a new IAM is to formulate the subject of the assessment in a clear, structured and transparent manner. Since subjects can range from safety, health to even employability, defining the subject requires careful attention. Developing a new IAM for a specific subject may contain elements

Figure 2: An overview of the different aspects of impact assessment methods and their relative position within the framework.

Life Cycle Assessment - Methods and Tools from other methods as these may provide solutions for the chosen subject or its effects. Additionally, the order level of the subject, meaning the diversity of issues addressed, has a direct influence on the accuracy of the result set and the subsequent obstructions. Simultaneously, IAM developers should be supported (and stimulated) in accurately defining the appropriate result set of the method. Understanding the relations between an Impact Assessment (IA) and a Life Cycle Assessment (LCA) [4] emphasizes the relevance of establishing a clear subject and welldefined desired set of results. As an example, the usage of “human health impairment” as a damage group, from the Eco-Indicator ’99 [5], is now commonly used as the subject itself in Health Impact Assessments (HIA). With HIA’s only the damages towards humans have remained. The desire to calculate all effects towards the original environmental subject has been altered and resulted in an impact assessment aiming at a specific set of issues and results. 3.3

Procedural Steps

After the initial step, the framework has to allow for a considerable freedom in choosing the subsequent steps. Although the subject and the desired results give a clear indication, the actual decision on where to start filling in the framework depends on the focus of the developers. Although the different routes contain similar obstructions, choosing an approach determines in which order the elements of the IAM should be developed. Based on the analyses of several methods, two commonly used approaches were distinguished, being the linear approach and the top-down approach respectively (See figures 3 & 4). From determining the subject and set of results, one approach aims at working from the interventions towards the single result score in a linear sequence, where the alternative approach uses a “backwards” or top-down approach from subject to intervention. If the interventions are the point of departure, each subsequent step encompasses a more convergent transformation in the method. This renders a close correlation between the interventions and effects. An obstruction is encountered when the transformations reach a high order level because the specified impact needs to address the constructed results while the correlation between its roots and the pre-chosen set of results should be maintained. Contrariantly, when working top-down, little problems are encountered in determining the equivalent units for the damages as they only yield a correlation with the set of results. In a later stage of the IAM development, in one of the remaining transformations, the correlation between the equivalents in the effects and actual interventions delivers a similar problem. Choosing either approach will not prevent the obstruction caused by keeping a clear correlation in the final steps of transformations. The compromise determines if one rather argues on chosen equivalents in the steps of damages or effects. In more academic audience aimed methods, the linear approach is often chosen as it leaves room to stop within the boundaries of ISO standards and contain correlated values for each equivalent impact. The top-down approach will fuel a more presentable result where insightful damage groups and correlated effects will support the set of results, normalised and weighted, for a business LCA. 3.4

Interventions

Within the phase that addresses the interventions, the different approaches share similar obstructions. Describing the interventions themselves requires an elaboration on their construction and usage. In this development phase of the approach, a process is performed that transforms aspects of product lifecycles such as substances, emissions and other relevant elements into interventions. To

583 adequately address these transformation, formalisation is required of preceding choices on the order level of the interventions, the sources for these interventions and the order level on which the interventions will be available for the user to assign in their LCA. Defining these levels of detail are choices stemming from the desired set of results, subject and the aim of the IAM. In comparing relatively complex products, the desire to have interventions at a lower level may be less suitable, leading to the use of more compounded interventions. An example could be the MEEUP's interventions [6], where entire part solutions such as electronic boards can be selected as an intervention. Here, the desired high order level, outperforms a more detailed level of interventions, because users can quickly compare complete elements of their products. This emphasizes the difference in aim of the IAM and subject. A secondary part of the construction is the use of databases [7-10]. For the EIAM's, several databases are already available and it has been accepted to use interventions from these databases. New IAM's on non-environmental subjects often lack predetermined interventions. In these situations also a new database needs to be created and linked to these interventions. Resulting in the possibility that the order level may become higher than the effects order level when working with a top-down approach. For both approaches it is advantageous to construct the list of interventions in advance, whether or not that is merely choosing from available lists or completely constructing new sets. This will create a more objective collection of interventions suiting the subject, aim of the IAM and desired set of results. 3.5

Characterisation towards an Effect

When applying an IAM, each intervention as determined in the inventory phase of the LCA, is characterized in relation with an effect in the profiling phase. The interventions with similar impacts are grouped together (classified) based on their contribution to a certain effect. The downside of this approach is the lack of correlation between the different effects while each effect consists of more correlated interventions. These are transformed in order to give the effect only a single equivalent and presentable intervention. With EIA, the usage of CO2 as an equivalent substance for all elements contributing to the Greenhouse effect, as also used in the Eco-Indicator 95 [11], a clear example can be given. The immediate problem, however, lies in the accuracy of the characterisation and the choices for the expressed unit. The choice of the equivalent unit should be based upon the interventions characterized, the name of the effect and the best suited intervention representative for that effect. The choice should be realistic, evidence- and non-political based, as argumented by Pawson [12] and recently elaborated by Matthew Cashmore et al. [13]. The suggestions given deliver an insight in preventing the usage of popular and politically emphasized choices. An example is the “carbon footprint”, known for disagreements [14] due to definitions alone, while the effect 'Global Warming' has already established a name and comprehensible impact among most readers. The top-down approach will sustain a large obstruction in this phase when pre-determined effects, or rather their names, hold correlation to future steps but may lack correlation to the interventions related to the subject. Assigning interventions to effects demands proper involvement and will take considerable effort to compensate for the missing correlation. As the structure and level of interventions demand considerable care and detail, it is advised to construct them separately or in advance of naming the effects. 3.6

Effects

The importance of proper transformation mechanisms such as classification and characterisation towards the effects, in both

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approaches, is obvious. However, the impact of both the names and magnitude of effects is a different obstruction for the result. As a large collection of effects may stem from the linear approach, defining effects’ names from interventions and classifying accordingly, the subsequent influence of a collection of effects brings back the problem of correlation. With specific effects, the need for accurate naming while remaining comprehensible to the less involved reader, increases and requires equivalent interventions chosen specifically to avoid confusion. Obviously, it would be wise to avoid using the same equivalent intervention for multiple effects. While on a parallel line enforcing the ambition to remain appropriate for the subject chosen, this can cause a conflict in something as simple as naming effects that classify a group of interventions. The described controversy cannot be solved in a single transformation. In essence, the choice boils down to keep focussing on the appropriate target audience. Where a more academic, involved or experienced audience will understand specific effects and their equivalent interventions, a solution is required that delivers meaningful explanations for less involved readers to understand the transformations. The structure of the initial method ReCiPe [15] delivers a possible solution, adding an intermediate step to serve both audiences. As shown in the final ReCiPe method [16], a selection of initial effects is used in an “Environmental mechanism part I” to classify different areas, where a secondary transformation mechanism is used to calculate the final damages. The IAM overview in figure 2 depicts a similarly broad scope of different transformations, however with the additional time consumption for these calculations, expanding the IAM needs to be considered in advance. 3.7

Between Damages and Effects

Where in the linear development approach the initial classification and characterisation of interventions for effects, already proved a difficult task, transformation of the interventions into the damages is an even more sensitive step in the development. As the results stray further away from the lower order levels and classify impacts to higher order levels through characterisation, an increasing distance between the factual interventions and the transformed result is created. Each repetition will therefore require precise handling of the original interventions and the aim of the IAM. Simply classifying the effects for “logical” damage categories should be prevented, as this common approach leaves the question why a certain effect is considered not to influence other categories. It cannot be stated that an effect is without influence towards the other damage categories. For instance, the effects in “Damage to the Ecosystem Quality” are considered to not influence [17] the “Damage to Human Health” group in the Eco-Indicator 99. The idea that a destroyed ecosystem would not influence the human health has been maintained, although the ReCiPe method does show a single interrelated effect [18]. It can, however, be stated that the interrelation has already been encountered in the initial transformation. However, just as is the case for the explanation of the interventions, each effect should be considered to influence several targets of damage categories. By capturing these interrelations under the more generic name of ‘transformation mechanisms’ as in figure 2, it emphasizes the repetition and therefore possible multiple targets. Although both approaches have a sensitive phase to solve, the top-down approach will present itself with more correlation when defining sub-elements. The correlation may be more straightforward, however, the omission of multiple targets, or origins for the damages that depend on the view, has a higher probability.

3.8

Damage Groups

With less correlation remaining after the initial formulation of effects, the damage groups towards which these effects have been transformed, demand defining. This however demands two additional steps to be taken into account. The damage groups need to be linked to the results and need to be able to be normalised. After normalisation a weighting factor could be applied to transform the impacts to weighted scores. They can even be succeeded by an aggregation resulting into a single indicator score. To achieve this, the damage groups need to be correlated between the subject, the effects and yield a normalisation that fits the desired set of results. The top-down approach lacks the required correlation with effects as they have not been defined. Finding a norm applicable to the damage groups while remaining correlated to the subject, should not be problematic. 3.9

Normalisation

In the linear approach, the groups of damages are separated and incomparable, as each represent values of impacts of different origins, in comparison to a correlated set of damages when defining these top-down. With the general accepted and understood benchmark of normalisation, these damages can share a common denominator. To determine this set it’s important to consider the target group to substantiate the chosen values. The scale on which to do this should be considered important, not to mention to select a relevant scale to begin with. The usage of a geographical based norm brings the danger of using an inappropriate scale [19]. Elsa João [20] has demonstrated that a correct scale can alter results considerably. Using any scale to normalize too needs to be precise enough and representing the IAMs’ targeted set of results. 3.10 Weighting The value of weighting comes forth from desiring to put emphasis on a specific damage group or end-points. The usage is debatable and not accepted under the ISO standards, however does provide a strong tool to interpret the results. Not only to emphasize the results, they can also clarify results when certain, less focussed effects, obscure other results in the graphs. This element however no longer forms any obstruction as the arbitrarily set of weighting factors is subjective and open for the personal alteration when the method is used. In practise most IAM’s are supplied with default sets of weighting factors to aid the user in expressing the results into a single indicator score. However it should be considered to supply the user with a method to determine and underpin the specific set of weighting factors appropriate for the actual LCA on the products under consideration. When considering to provide a weighting set, the approach that has been used in the Eco-Indicator 99 [21] could be considered. By means of a survey under a panel of scientist, several views and according sets of weighting factors were delivered. This approach can be very useful, however the actual basis requires a substantial amount of returns. This was encountered in the low return for the Eco-Indicator 99 when a mere 22% formed the weighting set. 4

IDENTIFYING

With the described steps and examples of obstruction an overview on these obstructions can now be formed per element and build towards the framework. Using figure 2 as a framework reference both approaches are schematically represented.

Life Cycle Assessment - Methods and Tools 4.1

Top-Down Approach

585 4.2

Linear Approach

Figure 4: Linear Approach.

Figure 3: Top-Down Approach. Starting the approach at the level of the subject, it's desired to make a clear and well defined subject as the central focal point of the intended IAM and set of results to meet the expectations of the users. Having the subject remained narrow and in line with well correlated results, encloses the level of divergence following in the approach. Indirectly the set of results already deliver a hint towards the single score, damage groups and what is expected to be deducted from the set of results. The focus should be on determining the damage groups and how they should be normalized. After this the damage groups can be expanded into effects. Deducting the mid-points and/or effects from each damage group consists of a straightforward work where related equivalent units can be determined. Using this deduction allows clear definitions for the transformation mechanisms. Expanding the set of effects, from the selected damage group, contains a compromise between a large set to please a scientific audience and the subsequent additional effort needed to remain coherent, correlated and have each effect characterized based on scientific facts. For each lower step and implied increased precision, the transformation process will increase in effort. Depicted in figure 3 however, the amount of transformation mechanisms have been simplified to merely express the transformations between the main phases in the IAM as depicted in figure 2. Each characterisation contains an equal approach on determining an equivalent unit, however in the top-down approach the necessity to keep track of the coherence with the lower level of interventions is subservient as they have not been determined. Determining the characterisation factors, once these lower order steps have been defined and are given equivalents, does provide a tougher challenge especially when reaching the effects or lowest points in the effects phase. In the effects phase, the final stage remaining, is linking the relations with the interventions. This transformation no longer contains finding equivalents and determining correlated dependencies but actual intervention classification and characterisation. This phase in the top-down approach requires a lot of effort to correlate the large sum of interventions towards the effects, as both sides connect for the first time.

The usage of the linear approach has in its overview a clear converging proceeding. As each step contains more converged results of the previous steps, they remain correlated until the final stages. With this linear approach, the method can be defined after the set of necessary interventions has been completed. This prevents parallel development of the IAM and the supporting database on one hand, while it avoids the consumed time for the correlation in the final stage, as with the top-down approach, on the other hand. Setting up the list of effects, mid-points and end-points comes forth from grouping elements together. For a more public audience, the usage of common names, as the illustrated "Greenhouse effect" for an EIAM, shares instant recognition versus the probability of grouping less accurately understood interventions when creating a new method. A shared denominator that expresses the grouped elements and its most common effect name, formulates the common approach but forms no prescript. As long as the chosen combination represents the reason for the grouping, the new named effect can be used. Each intervention however needs to be reconsidered in the next grouping to avoid omission. The transformation of the contribution of each intervention to the used equivalent unit, in each further step, can be defined. After all convergences the final stage will hold the normalisation. In this step the constructed damage groups are backwards influenced by the intended audience of the IAM and their understanding of equivalent units. Combined with the fact that these groups need to be normalised, in the linear approach the main obstruction is encountered in this phase. The decision can be made to disregard this particular problem and to continue with the converging naming of the damage groups. This may still result in very usable names and normalisation values. 5

CONCLUDING REMARKS & RECOMMENDATIONS

It will be clear that, for developers of IAM’s, there are quite a number of pitfalls. They are -in general- related to the subjects, the rules for result set interpretation and aggregation level (of the target audience). Most important, however, the applicability of any developed method heavily depends on the way in which a trade-off between these aspects is achieved. This immediately implies that no single nor context-independent remedy can exist. Since the interventions are the pivot point between the model of a product lifecycle and the transformations in the IAM, the development and determination of the relevant interventions play an important role. In order to avoid omissions in determining interventions and possible compartmentalisation, this process

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should be considered to be executed separately from the construction of the method. This can be done concurrently in the case of using the top-down approach, although it delivers a daunting challenge when correlating the interventions and the effects. While creating new IAM’s, obstructions will always be encountered; a solution free of compromises can therefore not be found. Developers can consider the possible obstructions and anticipate the possible consequences on the results. The presented framework and main obstructions provide insights for the compromises that need to be considered and while giving developers a base on which to found decisions. The development of new methods will benefit from documented development and will offer increased insight and result in possible new approaches. Together these may yield solutions for obstructions inherited from predecessors. 6 [1]

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assessment: available from: www.elsevier.com/locate/eiar. [21] Goedkoop, M.; Spriensma, R. (2001): The Eco-Indicator 99 A damage oriented method for Life Cycle Impact Assessment, by:

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Consultants:

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http://www.pre.nl/eco-indicator99/ei99-reports.htm.

from:

Developing a Conceptual Framework for UT based LCA 1

Jae-Min Cha , Suk-Hwan Suh 1

2

Dept. of Industrial Management and Engineering, POSTECH, Pohang, S. Korea 2

Center for Ubiquitous Manufacturing, Pohang, S. Korea

Abstract LCA is a methodology for evaluating and improving environmental impacts; it is well established in a theoretical way, however, has some practical problems such as 1) difficulties of transparent information acquisition from real-fields, 2) difficulty of transparent information exchange in value-chain, 3) difficulty of LCA methodology itself. Therefore, it is hard to get reliable LCI database reflecting the real situation, and derive the reliable LCA results. In this study, we propose the u-LCA concept for solving problems using ubiquitous computing technologies. To specify this, we develop the u-LCA conceptual framework by considering practical LCA problems as well as UbiDMR paradigm. Keywords: Life Cycle Assessment (LCA); Ubiquitous Computing Technology (UT); UT based LCA

1

INTRODUCTION

With the enforcement of global environmental regulations such as EuP (Energy using Product), WEEE (Waste Electrical and Electronic Equipment), and RoHS (Restriction of Hazardous Substances), and increasing customer focus on environmentally conscious products and companies, companies are necessary to cope with these environmental changes by mitigating the environmental changes of product and services. Life Cycle Assessment (LCA) is a methodology for evaluating and improving environmental impacts; it is regarded as a major tool for environmental improvements [1]. Particularly, LCA was proposed as a specific methodology for realizing green ICT (Information Communication in a high-level OECD meeting in 2009 with the theme of “ICTs, the Environment and Climate Change” [2]. In order to evaluate the environmental impacts of products in LCA, several kinds of information with respect to products, processes, and product usage are required; further, it is imperative to acquire high-quality data from the real-field to obtain reliable results from LCA [3]. Practically, however, LCA requires massive time, labor, and cost; thus, small organizations such as SMEs (small and medium-sized enterprises) and NGOs (Non-governmental organizations), as opposed to large enterprises that have adequate infrastructure, have used inventory data via indirect methods such as public/private LCI (Life Cycle Inventory) databases, literature surveys, assumptions, and estimation. These data manifest temporal and geographical differences with accurate data that LCA practitioners require, which is regarded as a major reason for the degradation of the reliability of the results of LCA. Also, the limitations of measurement technology and inappropriate measurement techniques, which manifest in measurement inconsistencies between LCA practitioners and improper measurement periods, are a reason for unreliable LCA results [4]. To overcome the above mentioned problems, one good technical approach is ubiquitous computing technology (UT), which is an emerging technology for supporting real-time information

throughout the product lifecycle anytime and anywhere. Since the introduction of the ubiquitous paradigm in the early 1980s [6], related hardware and software technologies have been rapidly developed for its realization. This study aims to propose a UT-based LCA (u-LCA) that supports the acquisition of seamless information from the real-field regarding product lifecycle and the procurement of more reliable LCA results through the application of ubiquitous computing technology (UT) to LCA. For this, the current problems are analyzed from a practical view point in section 2. Section 3 derives the design consideration for u-LCA concept, and section 4 shows the u-LCA conceptual model from the derived design considerations and illustrates it in detail. Usage scenario is illustrated to shows the effectiveness of the proposed the conceptual model in section 5. The paper concludes in section 6. 2

PROBLEM ANALYSIS

LCA has been developed by many experts from academia to industry since it was introduced in the early 1970s. Particularly, there have been many studies to improve LCA theory such as a theoretical methodology to compensate for LCI data uncertainty, the development of indicators for impact assessment, and so forth. Additionally, researchers have sought to disseminate their results to industry through several LCA case studies of diverse products and processes. In LCA, however, the means to acquire more reliable information is totally left to the LCA practitioner’s subjective knowledge and opinions, and there are hardly any efforts to address this issue. Given that the reliability of LCA results is fully dependent on the reliability of LCI data, it is necessary to investigate this matter. To make the new concept proposed in this paper more realistic, one should consider practical LCA problems. Some main problems derived from LCA case studies, literatures [3][4][5][7], and interviews with LCA experts are as follows: 

[Problem (PR) #1] Data are acquired from the real world through inaccurate methods such as manual input, surveys, etc.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_102, © Springer-Verlag Berlin Heidelberg 2011

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Life Cycle Assessment - Methods and Tools Therefore, LCI data are easily affected by the practitioner’s subjective opinions, and apt to be inaccurate.



[PR #2] The shop-floor has not been integrated with information systems so that information synchronization between them is not achieved.



[PR #3] Some lifecycle phases such as product usage or transportation for which it is hard to collect information are often not considered or dependent on assumptions and scenarios.

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[PR #4] Even though LCI databases including products, processes, materials, etc., are built up by many LCI database vendors, it is still not enough.



[PR #5] The LCI databases provided by various vendors are still not fully interoperable. ISO 14048 provides a standard data model for LCI data; however, some LCI vendors have retained their own data model.



[PR #6] LCI databases are not updated often or never even updated for several decades; thus, they cannot reflect current situations.



[PR #7] Heterogeneous information systems in a company manifest a lack of interoperability; therefore, it is difficult to share the information required for LCA on various products, processes, etc.



[PR #8] Interoperability amongst companies in the course of the product lifecycle is insufficient; therefore, it is difficult to acquire the information required for LCA from diverse real-fields throughout the product lifecycle.



[PR #9] Although ISO 1404x provides a standard procedure for LCA, it is theoretical and complicated for LCA non-experts.



[PR #10] In order to carry out LCA, a variety of knowledge relating to products, materials, processes, the environment, etc., as well as LCA procedures are needed; this makes LCA more difficult.



[PR #11] The standard LCA procedure is well defined in ISO 1404x. However, it does not provide a systematic guide for the contents (what-to) and the means (how-to) of information acquisition; thus, LCA practitioners face difficulties in information acquisition in practice.

3

DESIGN CONSIDERATIONS FOR U-LCA

In order for a framework to be more practical, practical problems should be considered. In this section, the design considerations are derived to solve the practical problems identified in the previous section. 



[Design Consideration (DC) #1] Real-time information acquisition: information generated in real time from real fields should be supportable. Especially, real-time information acquisition is essential in the case of LCA-based environmentally-friendly process planning (refers to PR #1, #2, #3, and #4). [DC #2] Wireless network environment: Wireless technologies such as WSN (Wireless Sensor Network), RFID (Radio Frequency Identification), and RTLS (Real Time Location System) are able to support the remote acquisition of information from the real field. In addition, PDAs (Personal Digital Assistants) and Smart phones can enhance operational efficiency by helping remote practitioners to manually input. To achieve this, a wireless network environment should be supported (refers to PR #1, #2, #3, and #4).



[DC #3] Interoperability of heterogeneous information systems: To carry out LCA, a variety of information relating to products, design, processes, the environment, and regulation is required from other information systems. To achieve this, interoperability between heterogeneous information systems in a company should be secured (refers to PR #5, #6, and #7).



[DC #4] Inter-company interoperability: To evaluate the environmental impacts over the entire product lifecycle, it is necessary to exchange information with other companies in the entire product lifecycle from material extraction to product disposal as well as exchange information with the product itself. To do this, interoperability should be secured between companies (refers to PR #5, #6, and #8).



[DC #5] Reliability of information: To assure the quality of information in LCA amidst considerable information exchange between real fields, systems, and companies through wired/wireless communication technologies, the reliability of information exchange should be secured from a system viewpoint (refers to PR #1, #2, #7, and #8).



[DC #6] Security of information: Information from the real field that is acquired by wireless technologies generally tends to be weak in terms of security. Information that is relevant to LCA concerning products, processes, and the environment is regarded as a company secret that involves company knowledge. Thus, information security must be secured with high-level encryption (refers to PR #1, #2, #7, and #8).



[DC #7] Distributed databases: To manage databases that are scattered across many stages in the product lifecycle, distributed database management techniques are required (refers to PR #4, #5, and #6).



[DC #8] Huge scale of databases: The amount of data acquired from real fields is significant. Especially, data acquisition over a long period requires management techniques that are able to treat masses of data (refers to PR #4 and #6).



[DC #9] Interoperability of heterogeneous LCI databases: At the time of using the LCI databases, it is important to interoperate with other LCI databases provided by several database vendors. This interoperability must be ensured by supporting interfaces that are compatible with the data model that each vendor provides (refers to PR #4, #6 and #9).



[DC #10] Intelligent LCA methods for contexts: The required information for carrying out LCA can be changed according to certain contexts with relevant to LCA such as the LCA stakeholder, LCA purpose and target product, etc. Based on such a characteristic, fundamental, required information reflecting the contexts of LCA practitioners should be provided in advance to help them work efficiently (refers to PR #10 and #11).



[DC #11] Systematic information acquisition methodology: Through a systematic information acquisition methodology regarding where, how, and which information should be acquired in the LCI data acquisition step, the efficiency for carrying out LCA will be improved for not only LCA experts but also LCA non-experts (refers to PR #10 and #11).

4

A CONCEPTUAL FRAMEWORK FOR U-LCA

This section shows the conceptual u-LCA framework that reflects the design considerations of the previous section. To specify this, the conceptual model, definition, and reference architecture are explained.

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Figure 1: Conceptual model for u-LCA. 4.1

The u-LCA concept

The u-LCA is not just a methodology for environmental impact evaluation but also a service for enabling progressive environmental impact evaluation based on ubiquitous computing technologies. To be specific, it can be defined as “a service that enables accurate, sustainable, and intelligent life cycle assessment by transparently acquiring, exchanging, and using environmental and lifecycle information generated in the entire product lifecycle based on ubiquitous computing technology and ubiquitous information engineering”. In order to systematically configure the framework, this new concept not only considers the practical problems of current LCA approaches, but also is based on our previously developed paradigm, called UbiDMR [8], meaning product design, manufacturing, and recycling via ubiquitous computing technology. Based on these requirements, we derive the conceptual model to show the u-LCA concept as shown in Figure 1. As figure illustrates, three main features are highlighted as follows: 1) transparent information exchange, 2) intelligent information acquisition support, 3) seamless information acquisition from real-world. 4.2

the layer where the information is transparently transmitted, exchanged, and retrieved by various stakeholders. The UPLI (Ubiquitous Product Lifecycle Information highway) belongs to this layer. Next, the Application system layer is the key layer that evaluates the environmental impacts based on the information acquired from D2U and UPLI. Finally, the Life cycle layer means the application systems of other stakeholders regarding the BOL (Beginning-Of-Life), MOL (Middle-Of-Life), and EOL (End-Of-Life) phases. In each layer, several modules that perform certain functions are located. The details of each module are as follows. 

Inventory database module: A module that is composed of several LCI databases for environmental impact evaluation. It stores the information or provides the required information to other modules through the information search and store functions (refers to DC #7 and #8).



Environment assessment module: A module that carries out environmental impact evaluation in practice. If the order is given by the LCA practitioner through HCI, the module then carries out the environmental impact evaluation based on information from the inventory database module. In this module, the core engine supporting inventory analysis, impact assessment, interpretation, and documentation are included (refers to DC #10 and #11).



Context reasoning module: A module that infers the required information level and contents according to several conditions such as the LCA stakeholder, LCA purpose, target product, etc. It provides the proper information template including the contents and acquisition methods to LCA practitioners for their own purposes (refers to DC #10 and #11).



Information engineering module: A module that supports decisions in terms of the appropriate information contents (what-to) and information acquisition methods (how-to) in order to effectively achieve the LCA objectives. This can enable LCA practitioners to acquire the information in a more effective way (refers to DC #10 and #11).

Reference architecture

In order to materialize the proposed u-LCA concept, design architecture to be referred is required. In this section, we derive the reference architecture for u-LCA by reflecting the design considerations and UbiDMR paradigm as shown in Figure 2. The reference architecture is composed of four layers: (1) Real-world layer, (2) Information infrastructure layer, (3) Application system layer, and (4) Life cycle layer, as shown in Figure 2. The Real-world layer means the layer wherein several information sources relating to products, processes, resources, the environment, user, and operator for LCI databases are included. In this layer, D2U (Device to u-System), which supports information acquisition, and several sensors are used to acquire information from several information sources. Then, the acquired information is transmitted to the information infrastructure layer via ubiquitous communication technologies. The Information infrastructure layer is

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Figure 2: Reference architecture for u-LCA. 

HCI (Human Computer Interface) module: A module that directly interfaces with the LCA practitioner. It supports an easy and intuitive user interface for the four main functions of the environmental assessment module, namely, inventory analysis, impact assessment, interpretation, and documentation (refers to DC #10 and #11).

the environmental impacts through the entire product lifecycle are converted. Many companies in Europe, the US, and Japan voluntarily carry out this process. This system is currently on the way to being enacted in the international standard 14067 and will be one of the main trade barriers thereafter. Hence, it is imperative to prepare a countermeasure to the system.



D2U (Device to UPLI) module: A hardware and middleware system for transmitting real-field data to the application system layer through UPLI. D2U has functions for refining data through the data cleaning, data transformation, and data aggregation phases (refers to DC #1 and #2).

In order to acquire the carbon footprint label, Company A should acquire transparent LCI information from the real field through the product lifecycle of mobile phones as soon as possible.



5

UPLI (Ubiquitous Product Lifecycle Highway): An information infrastructure for transparent information exchange between various stakeholders through the product lifecycle. To overcome the challenge of transparent information exchange owing to different information models, expressions, system interfaces, etc., among stakeholders, it supports the standard information model and an SOA (Service Oriented Architecture)based system architecture. More details can be found in Lee et al. [9] (refers to DC #3, #4, #5, #6, and #9). USAGE SCENARIO: RAPID RESPONSE ON CARBON FOOTPRINT LABEL

This section illustrates a simple usage scenario to show the effectiveness of the proposed concept, and analyzes the expected impacts via As-Is vs. To-Be analysis in Figure 3. Background scenario The following scenario is about a mobile phone company, Company A, which does product planning, marketing, and assembly of mobile phones. This company has decided to acquire the carbon footprint label for each product model in order to cope with the increasing customer focus on environmentally conscious products and companies, and trade barriers. The carbon footprint label is a system that helps the consumer select more environmentally conscious products through an attached label that shows the amount of CO2 emissions into which

As-Is scenario (the conventional LCA approach) The LCA practitioner who is in charge of the carbon footprint label in Company A (1) selects a target product to acquire information and (2) decides the LCA purpose and scope. Next, she sets up the system boundary (Step 3), followed by collection of the LCI data from real fields. The LCI database from the real field in the assembly process mostly has not been established; even some of the acquired information is too outdated to reflect the current situation of the real field. Thus, the LCA practitioner asks each process manager for real-field data for the LCI database. But, the process managers also do not have enough real-field data. Therefore, the LCA practitioner interviews process managers or surveys the processes. In the case of the mobile phone, there are a variety of processes such as PCB injection, parts installation, glue hardening, PCB inspection and case assembly, etc., in an assembly process. And, the LCA practitioner asks each process manager for real-field data for LCI database (4~6). Besides, a mobile phone consists of many parts such as the PCB, exterior case, LCD (Liquid Crystal Display), batteries, etc. Therefore, LCA practitioners ask several parts suppliers for realfield LCI data (7~9). But, acquiring information from other companies is much more difficult than from one’s own company because, from the point of view of subcontractors, the LCI data that they provide is knowledge that is relevant to their design and manufacturing; hence, they are unwilling to offer it. Also,

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Figure 3: (a) As-Is scenario vs. (b) To-Be scenario. interoperability between systems cannot be guaranteed because of many heterogeneous process terminologies with different information systems that are used between businesses. For these reasons, it takes approximately 6~24 months and entails considerable cost to build up the LCI database from many companies that are related to the product value-chain. The LCA practitioner evaluates the CO2 environmental impacts based on the real-field data (10) and then, applies for the carbon footprint label to KEITI (Korea Environmental Industry and Technology Institute), which is the certification institute of carbon footprint labels in Korea (11). KEITI investigates the credibility of the data, undertakes document review and auditing, and finally issues the label (12). Under this current situation, the certification of carbon footprint labels is delayed by a huge amount of time due to LCI data acquisition, especially in the case of products such as mobile phones, which have short product release data ranging from two to

three months. Hence, the acquisition of the carbon footprint label could delay product launch. To-be scenario (UT-based LCA approach) The LCA practitioner who is in charge of the carbon footprint label in Company A (1) selects a target product to acquire information and (2) decides the LCA purpose and scope. Next, she sets up the system boundary (Step 3), followed by collection of the LCI data from real fields. Not only the assembly process but also each parts process of the supplier has several kinds of sensors that are used to acquire process information and environmental information in real time. Then, the integrated LCI database is updated with the information thus acquired (4~5). To achieve this, D2U (Device to u-System) technology that helps to gather information from each process transparently and transmit it, sensor-related technologies to sense information, and some other technologies are used. Moreover,

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As-Is. (current LCA approach)

To-Be. (u-LCA)

Inaccurate data acquisition from real-field such as manual input, survey, interview, etc.

Automatic and accurate data input supported by computing technologies

ubiquitous

One time updated or never updated LCI database

Continuous updated LCI database from real-field throughout the lifecycle

Difficulties of information acquisition among in-company information systems owing to insufficiency of interoperability

Transparent information acquisition based on interoperability among in-company information systems

Difficulties of information acquisition between companies owing to insufficiency of interoperability

Transparent information acquisition based on interoperability between companies

Carried out by only LCA expert owing to complicated methodology

Carried out by LCA non-expert as well as expert based on intelligent system support

Inaccurate information acquisition with trial-and-error based on practitioner’s subjective on information acquisition means

Accurate information acquisition without trial-and-error with systematic methodology on information acquisition methodology

Table 1: Expected impacts. information exchange between companies in the product value chain is transparently supported through the SOA (Service-oriented architecture)-based system architecture and standard information data model development. The LCA practitioner acquires the LCI data for the target product from the integrated LCI database (6~7), evaluates the CO2 environmental impacts based on the data (9), and then applies for the carbon footprint label to KEITI (Korea Environmental Industry and Technology Institute), which is the certification institute of carbon footprint labels in Korea (9). KEITI investigates the credibility of the data, undertakes document review and auditing, and finally issues the label (10). With the u-LCA approach, as a result of the decreased time spent for LCI data acquisition from days to hours, more prompt action for the carbon footprint labels for products such as mobile phones, which have short product release cycles, can be possible.

7

This work was financially supported by Korea Ministry of Environment (MOE) as “Project of a School of Ecodesign.” also, this research was supported by the International Research & Development Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (MEST) of Korea (K2001001621-10B1300-02910). 8

ISO 14040 (1997): Environmental management – Life cycle assessment – Principles and framework.

[2]

OECD (2009): ICTs, the Environment and Climate Change, High-level OECD conference, Helsingør, Denmark.

[3]

Huijbregts, M.; Norris, G.; Bretz, R.; Ciroth, A.; Maurice, B., Bahr, B.; Weidema, B; Beaufort, A. (2001): Framework for modelling data uncertainty in Life Cycle Inventories, International Journal of Life Cycle Assessment, Vol. 6, No. 3, pp. 127-132.

[4]

Weidema, B.; Wesnæs, M. (1996): Data quality management for life cycle inventories-an example of using data quality indicators, Journal of Cleaner Production, Vol. 4, NO. 3-4, pp.167-174.

[5]

Finnveden, G. (2000): On the limitations of life cycle assessment and environmental systems analysis tools in general, International Journal of Life Cycle Assessment, Vol. 5, No. 4, pp. 229-238.

[6]

Weiser, M. (1999): The computer for the twenty-first century, Scientific American, Vol. 265, No. 3, pp. 94-104.

[7]

Eun, J.-H; Son, J.-H.; Monn, J.-M; Chung, J.-S.: Integration of life cycle assessment in the environmental information system, International Journal of Life Cycle Assessment, Vol. 14, No. 4, pp. 364-373.

[8]

Suh, S.; Shin, S.; Yoon, J.; Um, J. (2008): UbiDM: A new paradigm for product design and manufacturing via ubiquitous computing technology, International Journal of Computer Integrated Manufacturing, Vol. 21, No. 5, pp. 540-549.

[9]

Lee, B.; Suh, S. (2008): An architecture for ubiquitous product life cycle support system and its extension to machine tools with product data model, The International Journal of Advanced Manufacturing Technology, Vol. 42, No. 5-6, pp. 606-620.

The usage scenario shown above has a limitation in terms of showing all the effects of the proposed framework. Thus, further research will derive more usage scenarios to show the impacts. 6

CONCLUDING REMARKS

In this study, we propose a u-LCA conceptual framework that adopts emerging ubiquitous computing technologies to solve practical problems when LCA practitioners carry out an LCA. This framework not only considers the practical problems but also is based on the UbiDMR paradigm that our research team proposed earlier. To specify this, we illustrate the conceptual framework by introducing the definition, purpose, and reference architecture, and show the effectiveness of the proposed concept via a simple usage scenario. This study is an initial step towards fuller research in applying ubiquitous computing technologies in the LCA field. Further research will elaborate and materialize the proposed concept by deriving diverse usage scenarios for showing the effectiveness of the concept and developing a prototype.

REFERENCES

[1]

Expected impacts Through the usage scenario shown above, how the proposed framework improves the LCA approach in relation to the current LCA approach is summarized in six aspects in Table 1

ACKNOWLEDGEMENT

Towards the Integration of Local and Global Environmental Assessment Methods: Application to Computer System Power Management 1

1

1

Valentine Moreau , Natacha Gondran , Valérie Laforest 1

Institut Henri Fayol, UR SEPIT, Ecole Nationale Supérieure des Mines de Saint-Etienne, Saint-Etienne, France

Abstract The 21st century is characterized by the increase of information technologies, whose environmental impacts are now well documented. The consequences of these impacts, their nature but also the difficulty for the users to identify them make IT services to be an interesting case study for environmental assessments. The proposed methodology aims at retrieving both local and global effects of a given IT activity, taking into account both the direct and indirect impacts. The final objective is to establish an environmental dashboard based on a set of indicators, in order to assess environmental impacts of a service-based activity at different scales. Keywords: Energy Environmental Impact; Environmental Assessment; Information Technology

1

INTRODUCTION

The dramatic growth of energy consumption worldwide is clear. Since the early 1970s, world consumption almost doubled from 4676 Mtoe (Million tons of oil equivalent) in 1973 to 8428 Mtoe in 2008 [1]. Knowing that the share of energy produced from fossil fuel remains constant at about 85% [1], this trend will inevitably lead to the depletion of non-renewable resources. The role of information technology (IT) in this situation should not be overlooked. In 2008, the U.S. Congress [2] evaluated that the IT sector consumed 61 billion kilowatt-hours (61 000 TWh) in 2006, representing 1.5% of the total US electricity use. In France, the Ministry of Ecology and Sustainable Development [3] estimated a consumption of 55-60 TWh in 2008, which corresponds to 13.5% of the French electrical utilization. Between 2000 and 2006, the performance of IT hardware has been multiplied by 25, while their energy efficiency only increased by a factor of 8 [4]. Similarly to the automobile industry during “The Thirty Glorious Years" (1945-1973), the IT industry grew with performance as the main development criterion. Energy efficiency (i.e. reducing consumption for an equal power) was then only considered a minor concern. However, in the late 1980s, Harris [5] published a study on the electricity needed by a personal computer, while other studied the total power used by office equipment [6] [7]. Also, in the early 1990s, a strong interest in the electricity used by IT hardware surfaced with the first Energy Star specification for personal computers [8]. Knowing the recent growth in the IT industry and that its equipments generate an important energy demand, a real race after energy efficiency is beginning. This paper details the results of the monitoring and assessment of the environmental impacts of an IT service operating within a mass retail company.

2 2.1

CONTEXT OF THE STUDY From IT to Green IT

From 1995 to 2007, total energy savings, despite very substantial efforts by the IT manufacturers, have been neutralized by the increasing number of devices and their high levels of power consumption [9]. However, the future will no longer allow such a scenario: the gains in electricity consumption that could be expected by the evolution of technologies are now achieved. Most of the electricity savings were realized, and it is unrealistic to expect they will offset the continuing strong growth in electricity consumption of the IT sector. Recently, the concept of “Green IT” was defined as taking “into account an environmental dimension to the life cycle, hardware, software and services related to IT services” [10]. The general objective of Green IT, which consists mainly of respecting the environment during all the manufacturing steps, can be achieved in different ways: reducing energy consumption, reducing dependence on non-renewable resources, conserving natural resources, choosing recyclable components, using nontoxic and biodegradable substances, etc. At the outset, Green IT was wrongly interpreted, particularly due to marketing practices of some companies (e.g. use of green colors in ads, use of terms related to the environment as “ecologic”, etc.). Now, after a period of discovery and awareness-raising, Green IT can be considered, when well-managed, as a tool to comply with legal requirements and expectations of stakeholders and customers. 2.2

Energy and environment

The actual massive consumption of electricity generates numerous impacts, notably air pollution linked to the combustion of fossil fuels. Indeed, in 2008, 81.3% of the electricity in the world was produced from the combustion of oil (33.2%), coal or peat (27%) and gas (21.1%) [11]. Also, local wastewater releases and accidents like oil spills lead to water and soil pollution, while radioactive wastes and pollution can be related to the production of electricity by nuclear power plants. To these common impacts, one can add the

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_103, © Springer-Verlag Berlin Heidelberg 2011

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disruption of rivers and deforestation. Finally, a distinction needs to be drawn between local pollution (emissions of particulates, ozone, nitrogen oxides, sulfur or volatile organic compounds) and global pollution on a larger scale (climate change, caused by emissions of greenhouse gases, depletion of stratospheric ozone layer, etc.). Despite their differences, with the important growth of energy consumption, both the small and large-scale impacts are accentuated. 3 3.1

METHODOLOGY Context and objective of the study

The information technology department of a company already involved in a sustainable development strategy wanted to reduce the environmental impacts of the activities of their centralized and diffused computers. Moreover, results obtained by this study will support their decision between the extension of their data-center or the creation of a more eco-efficient one. In this mindset, a new method was proposed and applied in order to take into account direct and indirect consequences, as well as local and global impacts. This method consisted in three steps:   

Data collection; Calculation methods; Expression of environmental impacts.

This study seeks to express the environmental impacts of the IT hardware of an organization, identify which parts have the most important environmental impacts, detect the possible improvements and finally, with a simulation, assess the potential benefits. 3.2

Data collection

Data collection is a key step in any environmental assessment and was achieved here through three phases: An inventory, which aimed to collect the necessary information, such as a list of the devices models (quantity, year, etc.), the physical distribution of the device, the person in charge of maintenance, etc.

These three phases were carried out in parallel and feedback was needed to validate and supplement the information gathered at each level. 3.3

Calculation methods

There lies a difference between the power indicated by the manufacturer and the one actually observed. Therefore, to have a more reliable estimate of the consumption of the devices, some energy meters were used. The instantaneous power of the devices and their total consumption were measured for one week. Crossing with answers to the questionnaires, the instantaneous power yielded three device states: online, offline and standby. This separation into three statuses helps to link the environmental impacts to the use of device and identify possibilities of improvement. Calculations of consumptions in these three states are described in Figure 1. Total consumption measured (CM) and calculated consumption (CC) should always be equal.

Energy meter

MEASURES CALCULATIONS





Surveys with operators, which enabled the validation of the information gathered during the inventory, the observation of the behavior of operators and the assessment of whether or not the service had been delivered. For this study, a questionnaire was established and carried out by a dozen unit and logistic managers and users, through onehour personal interviews. Questions were notably related to the power of the device, the duration of use and the device lifetime. Measures to validate and/or complete all information previously collected. Here, the energy consumption of the IT hardware of the study site was measured with energy meters (econometrics with USB interface, Standby-Energy-Monitor Log 16, NZR) [12], retrieving real consumption of each equipment (in kWh/year), real time of use in each status (off, standby, on), etc. Results were then interpreted by analyzing the measures and the answers to the questionnaire.

Total consumption = CM

Intantaneous power

Power equipment Offline = POff

Power equipment Online = POn

Power equipment Standby = PSb

x

x

x

Time spent on POff = TOff

Time spent on POn = TOn

Time spent on PSb = TSb

Consumption on POff = COff

+

Consumption on POn = COn

+

Consumption on PSb = CSb

=

Calculated consumption = CC

Figure 1: Calculations possible with the energy meter results.

Life Cycle Assessment - Methods and Tools The data collection and calculations involve the creation of the company’s utilization profile. A series of monitoring indicators were thus created to account for different parameters:      

Average power consumption per year for each device; Average power consumption per year per category of device (desktops computer, laptops computer, servers, etc.); Annual usage rate of device; Utilization time relative to the opening span of the company; Lifetime of devices; Amount of produced waste.

Finally, based on these monitoring indicators, a series of environmental indicators were added to allow expression in terms of impacts on the environment of this company. 3.4

Characterization of environmental impacts

An environmental dashboard allows the characterization of the environmental impacts of a given system. It consists of a set of indicators, portraying the state of the environment, the environmental pressures (natural resources consumption, greenhouse gas emissions, etc.) or the possible mitigation of those impacts. It represents the evolution of a given phenomenon and relies on observable or calculable quantities of materials, activities or services that may affect the environment. The importance of each activity within a specific impact can be derived from the data concerning IT activity (consumption, device, releases, etc.) [13]. This derivation requires the use of conversion factors, which can be found in the literature and through databases. In this study, the Ecoinvent [14] and Bilan Carbone® ADEME [15] conversion factors were used. Consequently, the emissions of greenhouse gases related to power consumption of IT activity (expressed in kg CO2eq.) were estimated by multiplying the annual electricity consumption by a conversion factor corresponding to the European electricity mix (kg CO2-eq./ kWh). For IT hardware, the Ecoinvent database factors include the infrastructure (factory), the electricity needed for the manufacturing, the water consumption and industrial waste water, the required ship, rail and ground transport for input materials, the packaging, and the disposal [16]. Various methods can be used to express environmental impacts: the Ecoinvent database contains fifteen, but amongst them only CML 2001 and Impact 2002+ cover IT hardware. The CML method has been developed by the Center of Environmental Science of Leiden University in the Netherlands [17]. It is characterized by the use of impact indicators to model the potential power of polluting substances created by a reference substance. On the other hand, the Impact 2002+ method, developed by the Swiss Federal Institute of Technology in Lausanne (EPFL), uses normalization factors to express the impacts in a common unit [18]. In this study, the CML 2001 method was chosen, but only the following indicators were selected for the study:  Climate change (kg CO2-eq.);  Stratospheric ozone depletion (kg CFC-11-eq.);  Depletion of abiotic resources (kg Sb-eq.);  Acidification (kg SO2-eq.);  Ecotoxicity (kg 1,4-DCB-eq.);  Human toxicity (kg 1,4-DCB -eq.);  Ionizing radiation (DALYs.). These indicators correspond to the environmental stakes that were considered as the most relevant for the activity under study. Linking environmental impacts with monitoring indicators helped the identification of the company’s weaknesses and the suggestion of possible improvements, while also highlighting the strong points to advertise in order to encourage staff and management.

595 4

RESULTS

4.1

Consumption results

The environmental dashboard illustrates results in different forms. Table 1 illustrates results obtained for a desktop computer, which was never offline. 46% of the electricity consumption was from the standby phase, which consisted of 62.5% of the measured time. If this device would be turned off for half the time spent on standby, the total electricity consumption could be reduced by 20%. Figure 2 displays allocations of time spent in the three statuses identified previously. With these results, it is possible to know the utilization profile of each category of device. In this case, two important points should be highlighted: three of the five devices under study are offline 50% of the time and only printers are never offline. The major consequence of the utilization profile of each IT hardware and the number of devices in each category is the unequal distribution of consumptions. Percentages of consumption are presented in Figure 3. It is important to note that printers, which are never offline as shown in Figure 2, represent 4% of the total consumption of IT hardware. Another important issue is the repartition of consumption relatively to the time spent in the online and standby states. Desktops, laptops and Multi-Function Printers (MFP) have approximately the same repartition (being offline for around half of the time), but they do not consume the same amount of energy. Different explanations can be found. First, there are two times more desktops than notebooks and ten times more laptops than MFPs. Then, different devices have different powers: on average, desktop computers, laptops and MFPs consume respectively 264, 130 and 600 kWh/year. Note that it is very important to know which information and hypotheses are used to establish the graphs in order to understand the global situation depicted in an environmental dashboard of the company. 4.2

Environmental impacts

In the dashboard, different impacts are expressed with the use of factors coming from the Ecoinvent database, using the CML 2001 method. Conversion factors and the inventory of devices allow the estimation of the environmental impacts of the device, by compiling data such as the electricity for the assembly of the IT hardware, the water consumption and industrial waste water, the required ship, rail and road transport for input materials, the packaging and the disposal. Figures 4 and 5 display results obtained for ecotoxicity and stratospheric ozone depletion. While these two impacts cannot be compared directly because they do not use the same reference unit, it is possible to discuss their order of magnitude. For the ecotoxicity, the device with the biggest impact is the multi-function printer. This can be related to its weight: it averages about 150 kg, which is ten times the weight of a desktop computer. On the other hand, the device most involved in stratospheric ozone depletion is the laptop computer. Its impact is eight times more important than a desktop computer, even though a desktop computer is ten times heavier than a laptop. This difference may come from the role and impact of batteries, as retrieved from the laptop’s LCA. Status of the

Time allocation

device

(%)

Share in total consumption (%)

Offline

0

0

Online

37.5

54

Standby

62.5

46

Table 1: Allocations in time and consumption of a desktop computer

596

Life Cycle Assessment - Methods and Tools Allocation of time spent Online / Standby / Offline by device

% of consumption by device relative to the total IT consumption

100%

Multi Function Printer 10%

Printer 4%

50%

Notebook 1%

Offline Standby Online

Laptop computer 23%

Desktop computer 62%

0% Desktop computer

Laptop computer

Notebook

Printer

Multi Function Printer

Figure 2: Allocations of time spent in the three statuses (Online, Standby and Offline) (in %)

Figure 3: Allocations of energy consumption by device relative to the total IT energy consumption of the company (in %) Stratospheric ozone depletion

Expression of ecotoxicity for the manufacturing and disposal of device

4,0E-04

30000

3,5E-04 3,0E-04

[kg CFC-11 éq.]

[kg 1,4-DCB-eq.]

25000

Terrestrial ecotoxicity

20000

Marine sediment ecotoxicity 15000

Marine aquatic ecotoxicity Freshwater sediment ecotoxicity

10000

Freshwater aquatic ecotoxicity

2,5E-04 2,0E-04 1,5E-04 1,0E-04

5000

5,0E-05 0

0,0E+00

Desktop Laptop Printer computer computer

MFP

Server

Desktop computer

Figure 4: Ecotoxicity impact of manufacturing and disposal device (in kg 1,4-DCB-eq.) Electricity consumption is mainly used to estimate impacts during the use phase. A conversion factor helped convert 1 kWh of electricity energy into environmental impacts: the one chosen comes from the Bilan Carbone® method (i.e. 1kWh emits 0.083 kg C-eq, emissions for the European electricity mix) [15]. It is then possible to compare the environmental impacts of the use and manufacturing phases, while making sure the same period of time is considered: here, energy consumption is calculated for one year of standard use of device. In a similar way, the impacts associated to the production of the material are distributed over the estimated useful life of the device. In the example shown in Figure 6, the material is kept three years in the company: the impacts associated with production are thus divided by three. Figure 6 also shows that climate change impacts are more important in the production phase than the use phase. The end user has limited power over these parameters, but with the recent inclusion of environmental and social clauses within the criteria for purchase [19], it is possible for buyers to pressure the manufacturers to recognize the environmental impacts of their processes.

Laptop computer

Printer

MFP

Server

Figure 5: Stratospheric ozone depletion of manufacturing and disposal device (in kg CFC-11-eq.) 5 5.1

DISCUSSION Assessing benefits

With the help of the quantification of environmental impacts, the priority of actions of improvement can be identified. Based on international literature as the Code of Conduct [20], opportunities for improvement were studied. The possible environmental benefits of various actions can be estimated. Initially, through the environmental dashboard, an overview of the situation has been established. Next, the improvement scenarios were also quantified. Then the costs of implementation of these scenarios within the company were approximated. Finally, the benefits (positive or negative) could be estimated with respect to the difference between the environmental impacts of the initial state and those of the potential actions of improvement. Benefits may be both environmental and economical. Environmental benefits can vary from the extension of the lifespan of the device (which reduces impacts related to the manufacturing of new device) to better IT stock management (reduced utilization of energy). Then, those actions may also have a financial impact on the company by reducing the costs of energy use and of acquisition of new material. In the context of this study, a reduction of about 20% in CO2 emissions compared to the baseline value is considered.

Life Cycle Assessment - Methods and Tools

597

Expression of the impact on climate change (in t CO2-eq) 450

Also, the dataset used within the Ecoinvent database is applicable to describe the production of a common desktop computer in the last three years before the reference year of 2005 (Pentium 4, processor speed 2000 MHz, 40 GB RAM HDD, 512 MB working memory, total weight without screen and cardboard packaging 11.3 kg). This study was made in 2009, and while this was the last data available on Ecoinvent, the manufacturing process and capacities of IT hardware evolve so quickly that it can be questioned whether this data is still valuable.

400 350

[t CO₂-eq.]

300 250 200 150 100 50 0 Desktop computer

Printer

MFP

Use of equipment (by year) Manufacturing equipment (by year - Lifespan = 3 years)

Figure 6: Expression of the indicators for contribution to climate change (in t CO2-eq), using the Bilan Carbone® coefficients. 5.2

them can be compared with CML 2001 (climate change and ecotoxicity), because the other two do not use the same units.

Conversion factors in different methods

The influence of the variability of the different conversion factors that can be found in the various assessment methods was studied. The objective is twofold: the variability existing between different assessment methods for the same type of conversion factor was studied and the potential causes of this variability were looked for. Four methods used in the Ecoinvent database (v2.2 2010) were compared: CML 2001, EDIP, IPCC and TRACI. This paper does not aim at explaining the differences between these four methods, but mostly at highlighting some points on which it was necessary to be cautious to ensure the coherence of the environmental dashboard, based on the data and scientific knowledge available. In each method, seven impacts commonly used in environmental assessment (particularly in LCA) have been studied: climate change, stratospheric ozone depletion, depletion of abiotic resources, acidification, ecotoxicity, human toxicity and ionizing radiation. By analyzing the various conversion factors used for each category in each method, the variability of these factors was estimated. The first observation is that for IT hardware (e.g. electronics), only the CML 2001 method allows expressing all the seven impacts mentioned previously. The second important point is that there is only one theme where there is a consensus on the expression of impacts: climate change (GWP 100a). Figure 7 shows the conversion factors used for CO2 emissions of a desktop computer. The four conversion factors are very similar: they vary from 270.31 to 271.04 kg CO2-eq. This comparison leads to the conclusion that the choice of the method used for the climate change indicator for production and end of life phase of a desktop computer does not influence significantly the final value of the impact. However, the French Bilan Carbone® method quantifies the CO2 emissions for the manufacturing of a desktop computer (without a screen like in the other methods) at 609.77 kg CO2-eq., which is more than twice the previous results. The huge difference forced to a detailed study on the calculation methods and the perimeters of studies considered in each method. Another important point concerns the EDIP method, which renders four conversion factors: climate change, stratospheric ozone depletion, depletion of abiotic resources and ecotoxicity. Only two of

In view of these differences on the conversion factors of diverse methods, the calculations of the environmental impacts are mentioned by a range of values in which the environmental impact may vary. Moreover, it is useful to present the method chosen with results obtained. 5.3

Local and global, direct and indirect impacts

With conversion factors, it is possible to calculate potential environmental impacts of an activity. Many environmental assessment methods allow the assessment of global and direct environmental impacts like emissions of greenhouse gases, but few studies consider local and indirect impacts like acidification. This methodology tries to solve this problem by establishing monitoring indicators. Moreover, the use of conversion factors from databases implies the use of generic data. In this methodology, we tried to include an accurate impact assessment by acquiring specific data. For example, measures on electricity consumption of IT hardware were conducted, so they are not generic data used to calculate consumption. These impacts are significant and deserve to be taken into account in the environmental assessment methods. We are thus currently working to identify them clearly. 6

CONCLUSION

Information technologies are omnipresent in the consumer goods market and more largely in today’s consumption society through individual computers, internet, communication, automation, etc. Their importance is growing every day and, in this race of performance and speed of calculation, the environmental consequences have usually been forgotten. Today, there are many environmental assessment methods that can explore this area of study, but many unknowns remain (quick evolution of the manufacturing processes, many subcontractors, confidentiality of the IT sector linked to the strong competition, etc). During the past years, many studies reflected on the subject of environmental impacts of IT. While they may have different objectives, scopes and subjects, they all contribute to awareness-raising of environmental impacts of the “IT society”. The main limitation to the application of these environmental studies is the lack of available data. While databases exist where main results on the subject are centralized, information is generally not updated regularly. This applies to the Ecoinvent database, which is an international reference in the field of life cycle analysis (LCA), as well as to the French Bilan Carbone®, considered as a reference in France regarding the estimation of greenhouse gases emissions. Information about the electronic device, which we used in this study, dates from 2005. Five years later, process and efficiency of the IT industry changed considerably and these factors of conversion are probably outdated. However, because of the great competition on this market, LCAs that may be conducted currently in this sector remain confidential.

598

Life Cycle Assessment - Methods and Tools [3]

Breuil H., Burette D., Flüry-Hérard B. (2008) : Rapport TIC et Développement durable, Conseil général des Technologies de l’Information. 96p.

[4]

Schulz G. (2007) Analysis of EPA Report to Congress (Law 109-431) in: The storageIO Group – Information Technology Analysis and Caonsultants. 12p.

[5]

Harris, J., Roturier J., Norford L.K., Rabl A. (1988): Technology Assessment: Electronic Office Equipment. Lawrence Berkeley Laboratory. LBL-25558.

[6]

Norford L., Hatcher A., Harris J., Roturier J., Yu O. (1990): Electricity Use in Information Technologies. in: Annual Review of Energy. pp. 423-53.

[7]

Moreover, in the IT sector, the issue of globalization is very present. How can one impose environmental rules when products are manufactured on a global scale and the laws hardly cross national borders?

Koomey J., Piette M.A., Cramer M., Eto J. (1996): Efficiency Improvements in U.S. Office Equipment: Expected Policy Impacts and Uncertainties. In: Energy Policy. Vol. 24, No. 12. pp. 1101-1110.

[8]

Johnson B.J., Zoi C.R. (1992): EPA energy star computers: the next generation of office equipment in: Proceedings of the American Council for an Energy Efficient Economy, Summer Study on Energy Efficiency in Buildings, Vol. 6. pp. 107-114

7

[9]

ADEME, EDF, Union Européenne (2008) : Mesure de la consommation des usages domestiques de l’audiovisuel et de l’informatique in: Projet REMODECE. 80p.

[10]

Corne C., Porcheron A., Guy P., Pavia J. (2009): Green IT. Dunod edition. 223p.

[11]

International Energy Agency (2010): Key world energy statistics. 82p.

[12]

Standby-Energy-Monitor Log 16, distributed by NZR

[13]

Jasch, C. (2000): Environmental performance evaluation and indicators in Journal of Cleaner Production, Vol. 8. No. 1, pp. 79-88.

[14]

Swiss centre for Life cycle inventories. (2010): Ecoinvent database v2.2.

[15]

ADEME. (2010): Calcul des facteurs d’émissions et sources bibliographiques utilisées, in: Guide des facteurs d’émissions.

[16]

Hischier R., Classen M., Lehmann M., Scharnhorst W. (2007): Life cycle inventories of electric and electronic equipment: production, use and disposal. Empa / Technology & Society Lab, swiss Center for Life Cycle Inventories, Dübendorf, Ecoinvent report No 18. 179p.

[17]

Guinee J.B., (final editor), Gorée M., Heijungs R., Huppes G., Kleijn R., de Koning A., van Oers L., Wegener Sleeswijk A., Suh S., Udo de Haes H.A., de Bruijn H., van Duin R., Huijbregts M.A.J., Lindeijer E., Roorda A.A.H. and Weidema B.P. (2002): Handbook on Life Cycle Assessment; An operational guide to the ISO standards; in: The international Journal of Life Cycle Assessment, Vol. 7, No. 5, pp. 311-313.

We extend our sincere thanks to the company which financed and allowed the application of this methodology. We also thank all the employees who filled out the questionnaire, facilitating the implementation of the project within their walls. Finally, we would like to thank our language reviewer, Charles David Mathieu-Poulin.

[18]

Jolliet O., Margni M., Charles R., Humbert S., Payet J., Rebitzer G., Rosenbaum R. (2003): Impact 2002+: a new life cycle impact assessment methodology, in: International Journal of Life Cycle Assessment, Vol. 8, No 6, pp. 324-330.

[19]

France legislation (2006) : Code des marchés publics. Available on line on http://www.legifrance.gouv.fr

9

[20]

European Commission. (2008): Best practices for the EU Code of Conduct on Data Centers. 27p.

CO2 emissions for a desktop computer 609,77 600

kg CO2-eq

500 400 300

270,31

271,21

270,87

270,12

271,59

270,13

200 100 0 CML 2001 EDIP 1997 EDIP 2003 IPCC 2001 IPCC 2007

TRACI

Bilan Carbone®

Figure 7: Comparison of CO2 emissions for a desktop computer.

SUMMARY

The 21st century is characterized by the constant evolution of IT technologies. Their major impacts on the environment are now well documented and are unequally distributed geographically and along the full life cycle of the device. While environmental impacts are significant, they also are invisible to the end user. The consequences of these impacts, their nature but also the difficulty for the users to identify them, leads to IT services being an interesting case study. The proposed methodology aims to retrieve both local and global effects of a given activity, taking into account both direct and indirect impacts. The final objective is to establish an environmental dashboard based on a set of indicators, in order to assess environmental impacts of a service-based activity at different scales. The originality of this study is to assess the service provided by part of a business activity: for example, activities necessary to its internal operations. This methodology has been applied through a partnership with a mass retail company, regarding the assessment of the environmental impacts of its IT services. The main results highlighted weak and strong points of these services, from which opportunities for improvement have been advocated. Each of these opportunities has subsequently been analyzed in order to express the benefits expected in terms of reducing the environmental impact. A suggested scenario thus considers a reduction of about 20% in CO2 emissions compared to the baseline value. 8

ACKNOWLEDGMENTS

REFERENCES

[1]

International Energy Agency. (2010): Key World Energy Statistics. 78p.

[2]

U.S Environmental Protection Agency (2007): Report to congress on server and data center energy efficiency – Public Law 109-431. 130p.

Cradle to Cradle and LCA – is there a Conflict? Anders Bjørn, Michael Z. Hauschild Section of Quantitative Sustainability Assessment, DTU Management Engineering, Technical University of Denmark, Denmark

Abstract: The Cradle to Cradle (C2C) approach to ecodesign has been gaining increasing interest among industries, authorities and consumers over the last years. With its focus on resource conservation through closing loops, use of solar-based energy sources, avoidance of certain chemicals and the stated aim to create good rather than just avoid doing too much evil, it appeals more to industry than traditional LCA-based ecodesign. What are the real differences between the two approaches, and is there a conflict? Potential points of divergence between C2C and LCA are identified and the ability of C2C to support a sustainable development is discussed. Keywords: Cradle to Cradle; Life Cycle Assessment; Sustainable Product Design

1

INTRODUCTION

As a new approach to sustainable product and system design Cradle to Cradle has gained wide popularity in the non-academic environment. It has attracted new companies and revitalized some of the dormant actors. It is however regarded with a high degree of scepticism in the academic environment. LCA practitioners have claimed that it does not include all life cycle stages and therefore cannot be considered a serious concept for sustainable design. This attitude gap is problematic because it inhibits communication between the two groups. This communication is crucial if Cradle to Cradle is to grow from being buzz to a concept that leaves a solid, positive and constructive impact in the world of sustainable design. Few in-depth studies have so far been conducted to identify where the conflicts between Cradle to Cradle and LCA arise and how these conflicts may be solved. This paper analyses the two approaches to identify differences and serve as a basis for a discussion on the conflicts and on how Cradle to Cradle and LCA may complement each other providing guidance in the process of sustainable design. 2 2.1

BACKGROUND Eco-efficiency and LCA

The concept of eco-efficiency has been defined as “adding maximum value with minimum resource use and minimum pollution” [1]. It has during the last couple of decades gained wide acceptance as a mean to ensure sustainability and is realized through technological innovation that may be supported by regulatory frameworks such as taxing non-eco-efficient goods, eco-labelling eco-efficient products and promoting green public purchase. The relationship between environmental impacts (I), population (P), affluence per capita (A) and eco-efficiency (1/T) is commonly expressed through the I = PAT equation [2]. Since P and A are on the rise globally, I may exceed (or have already exceeded) the global carrying capacity, which leads to depletion of the natural stock.

It has been debated how much eco-efficiency must increase for I to remain (or get) below the carrying capacity. Factors between 4, 10 and even 50 in improvement have been proposed [3], [4]. The variation reflects different projections of economic and population growth, different understandings of “carrying capacity”, different situations for different types of impact, and different time perspectives. This means that in the worst case scenario we may need to improve products and systems to the point where they in the future provide the same services as today, but at 2% resource use and emission rate of current levels. The most complete and widespread method to measure ecoefficiency is Life Cycle Assessment (LCA). It keeps track of all types of relevant resource uses and emissions throughout the entire life cycle of a product or a system, from cradle (raw materials) to grave (waste management). These are then translated quantitatively into different environmental impacts, such as Global Warming, Acidification and Nutrient Enrichment using characterization factors [5]. While still a young discipline, LCA has been standardised (ISO 14040 and 14044) and is widely used by businesses to identify improvement potentials of their products, by third parties as a basis for awarding environmental labels and by authorities as a decision support tool. 2.2

Cradle to Cradle

While LCA is an assessment method, Cradle to Cradle is a different approach aiming at sustainable design. Although others have used the term before, the concept fist became thoroughly defined in 2002 in the book ‘Cradle to Cradle – Remaking the way we make things’ by William McDonough and Michael Braungart (hereafter referred to as “the authors”) [6]. The concept has been translated into detailed criteria that serve as basis for a certification, and producers can apply for a Cradle to Cradle label according to different levels of compliance with these criteria. The Cradle to cradle concept and the underlying criteria are based on 3 fundamental principles: Waste Equals Food, Use Current Solar Income and Celebrate Diversity.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_104, © Springer-Verlag Berlin Heidelberg 2011

599

600 Waste Equals Food Waste Equals Food represents the idea of eliminating the very concept of waste and instead be inspired by nature’s endless nutrient cycles. Instead of the eco-efficient approach of trying to reduce the amount of waste, the focus should be to design systems with outputs that can be taken up as nutrient by other processes. This goes both for emissions during the production stage of a product and for the product itself once it reaches the disposal stage. The authors use the cherry tree as an example of how nature is usually not very eco-efficient, but still sustains itself through its nutrient cycles: “Thousands of blossoms create fruit for birds, humans, and other animals, in order that one pit might eventually fall to the ground, take root, and grow…although the tree actually makes more of its “product” than it needs for its own success in an ecosystem, this abundance has evolved…to serve rich and varied purposes. In fact, the tree’s fecundity nourishes just about everything around it.” [6] The very interconnectedness of nature’s organisms in ecosystems is used to illustrate how industries should expand their focus from single products to whole systems: “Just about every process has side effects. But they can be deliberate and sustaining instead of unintended and pernicious…Eco-effective designers expand their vision from the primary purpose of a product to the whole.” [6] This line of thought is comparable with the concept of industrial symbiosis, of which the most well known case is located in the Danish city of Kalundborg [7]. It is stressed that products should either be designed as biological nutrients or technical nutrients. Biological nutrients are defined as: “A material used by living organisms or cells to carry on life processes such as growth, cell division, synthesis of carbohydrates and other complex functions. Biological Nutrients are materials that can biodegrade safely and return to the soil to feed environmental processes.” [8] Technical nutrients are defined as: “A material that remains in a closed-loop system of manufacture, reuse, and recovery called the technical metabolism, maintaining its value through infinite product life cycles.” [8] The concept of the two nutrient cycles is illustrated in Figure 1.

Life Cycle Assessment - Methods and Tools which they may cause harm. Downcycling only slows this degrading process down. Other than the closed loop focus Cradle to Cradle also has a strong emphasis on using non-toxic (or ‘healthy’ as they are termed) materials. This has a dual purpose since it both prevents humanand eco-toxic effects from occurring and prevents complications in the recycling process (whether that be in the technical or biological metabolism). Use Current Solar Income The energy required for fuelling a closed loop Cradle to Cradle society must all come from what is termed ”current solar income”, defined as photovoltaic, geothermal, wind, hydro and biomass. These sources correspond with the general understanding of renewable energy sources. Due to the vision of being entirely supplied by energy from the sun, Cradle to Cradle design is not limited by any constraints on the energy use during the life cycle of a product. As long as the energy quality meets the requirements (current solar income) the energy quantity is irrelevant. Celebrate Diversity The main point of this last key principle is to avoid one-size-fits-all solutions and instead design products and systems with local environments, economies and cultures in mind: “Industries that respect diversity engage with local material and energy flows, and with local social, cultural, and economic forces, instead of viewing themselves as autonomous entities, unconnected to the culture or landscape around them.” [6] Eco-efficiency according to Cradle to Cradle The authors stress that Cradle to Cradle is a fundamentally different approach to sustainable design than eco-efficiency, of which they claim to be: …a reactionary approach that does not address the need for fundamental redesign of industrial material flows… principally a strategy for damage management and guilt reduction. It begins with an assumption that industry is 100% bad, and proceeds with the goal of attempting to make it less bad. [6] Downcycling is perceived by the authors as a symptom of ecoefficiency. Making small changes to a system that is fundamentally wrong can never achieve anything ‘good’, but only slow the ‘bad things’ down somewhat. Eco-efficiency’s focus on ‘being less bad’ also means that it is incompatible with economic growth: “Innovation is impossible because the priority for dematerialization suffocates creative approaches to the use of materials while simultaneously directing funding towards the generation of decreasingly beneficial incremental improvements. Growth becomes a problem because it threatens to result in increased resource use and waste.” [6] Instead of trying to be less bad Cradle to Cradle strives to ‘be more good’ in the sense that emissions should not be reduced, but instead be redesigned to become nutritious to the technical or biological metabolism. This relationship is illustrated in Figure 2.

Figure 1: The technical and biological nutrients cycle after [9]. Biological and technical nutrients should not be mixed beyond easy separability. Otherwise a product is created which neither fits into the biological nor the technical metabolism. Such a product can never be truly recycled, but merely downcycled into a product of lower quality and value. Alternatively virgin materials are necessary as inputs in the recycling process in order for the value and quality of the new product not to be lowered. In both cases a truly sustainable system is not possible, because the linear model of cradle to grave is maintained: Resources are being extracted and end up as materials with no value to humans or the environment to

Figure 2: Eco-efficiency and Cradle to Cradle after [10].

Life Cycle Assessment - Methods and Tools 3

601

POTENTIAL CONFLICTS BETWEEN CRADLE TO CRADLE AND LCA

definition of a technical nutrient and when composted it fits into the definition of a biological nutrient.

LCA aims to be value neutral and does not set absolute goals for eco-designers. It provides guidance in terms of the most environmentally sustainable way to reach the goal for each case. Cradle to Cradle on the other hand sets a number of absolute and universal criteria (e.g. dual closed loop recycling and the use of current solar income). These two fundamentally different approaches lead to a number of critical points where LCA and Cradle to Cradle are in disagreement.

So what disposal option should be chosen? Cradle to Cradle does not offer any guidance on that issue. According to the concept all products and emissions should be designed to become technical or biological nutrients and none of the two corresponding metabolisms has higher priority than the other.

3.1

Based on different environmental ethics

The basis of eco-efficiency is that all human activities have a more or less significant negative impact on the environment and that the task is to reduce that impact per unit of service. According to the Cradle to Cradle concept impacts can be ‘good, healthy and nourishing’. This calls for an analysis of what environmental ethics the two different approaches are based on and how that influences the applicability of the two, individually or in combination. LCA can be characterized as utilitarian up to and including the point of normalization in the sense that it attempts to show the path to minimizing negative utility (environmental impacts in this case) [11]. This is no longer the case when performing the weighting step, where the LCA can apply different ethics by emphasizing impacts prioritized by politicians, in the public debate, on human health, uncertain impacts or others. For that reason LCA practitioners often exclude the weighting step. The results may be perceived more valid when sticking to the utilitarian approach and often still gives clear results that are relatively robust towards choice of weighting principle. Cradle to Cradle is at first sight based upon the radical ethic theory of Deep Ecology since it recognizes that everything has the same and equal right to flourish and that humans have no special rights [11]. However, where this has lead traditional proponents of deep ecology to reject economic growth and consumerism, Cradle to Cradle embraces consumerism and claim to be compatible with economic growth. Due to this ‘win-win’ assertion Cradle to Cradle rejects the utilitarian approach of LCA. Why try to reduce overall negative utility when it is possible for all of nature and humans to flourish at the same time without compromising each other? These conflicting ethical points of reference may result in Cradle to Cradle being attractive to decision makers with different ethical mindsets than those who find LCA attractive. Moreover it may pose difficulties if trying to combine the two approaches. 3.2

Characterising technical and biological nutrients

According to Cradle to Cradle literature and certification criteria [6],[12],materials and products should either be designed as technical or biological nutrients. If products are easily separable they may contain both technical and biological nutrients. However the definitions are not mutually excluding as such. Some materials qualify to be both technical and biological nutrients. An example of this is polylactic acid (PLA), a polymer consisting of lactic acid monomers and based on sugar, commonly derived from corn. It is widely used as a biobased and biodegradable plastic material for e.g. food and beverage packaging. The largest worldwide supplier of PLA is Nebraska based NatureWorks LLC. Although not Cradle to Cradle certified, they claim to work by the Cradle to Cradle principles and their PLA is also used as example of a Cradle to Cradle material by Cradle to Cradle proponents [13], [14]. According to NatureWorks, their PLA has several disposal options, including recycling into lactic acid monomers through chemical hydrolysis and composting. When recycled PLA fits into the

According to the eco-efficiency concept it is possible to assess the most sustainable disposal option using LCA. This has in fact been done in two studies [15], [16]. The results of these studies will not be commented here, but this example illustrates another point of conflict between Cradle to Cradle and LCA 3.3

Energy use

When trying to fit Cradle to Cradle into the framework of life cycle assessment it is evident that some aspects of life cycle stages and impact categories are not considered. One of the strongest points of criticism of Cradle to Cradle is that it does not assess the amount of energy use. As long as the energy source qualifies as current solar income, the quantities used are irrelevant. This approach may be appropriate in a world that is fuelled entirely by current solar income and where available energy is abundant and without undesired environmental or resource impacts. However a fossil free economy is very unlikely to be realized within the foreseeable future. Therefore there might be a trade-off, in terms of sustainability, between the benefits of closing the material loop and the disadvantages from closing it as a result of e.g. increasing energy needs for transportation and recycling processes. More generally speaking it could be pointed out that imitating nature might not be such as good idea after all if it is not done with thoughtfulness. This is because the limiting factor for growth in most ecosystems is nutrients and not energy. Nature has therefore largely evolved to become very efficient in terms of nutrient recycling but equally inefficient in terms of energy use (hence the cherry tree metaphor). When comparing the natural system with the present human economy it can be said that both nutrients (e.g. metals and minerals) and energy (e.g. oil, gas and capacity for renewables) are limiting factors for our technical systems. Therefore, while nature can afford to be inefficient when it comes to energy use, the human economy at its present stage can not. Thermodynamically it has been shown that the last percentages of a separation process are far more energy-demanding than the first percentages [17]. Cradle to Cradle closed loop recycling implies 100% pure outputs of recycling processes (otherwise it results in downcycling). Therefore substantial energy demands may occur in the disposal stage when following the Cradle to Cradle principle. This may in some cases offset the environmental gains from closing the material loop, but this will not be revealed by the Cradle to Cradle methodology. Another related issue is that Cradle to Cradle’s strong focus on closed loop recycling may direct the attention away from optimising energy efficiency in the use stage of (directly or indirectly) active products. LCAs show that for most such products the highest energy use takes place in the use stage, and being an important source of several environmental impacts, this is normally one of the main focus points for ecodesign in the whole life cycle. For clothes it has been found that up to 80% of the total energy consumption occurs in the use stage due to laundering [18]. For laundry detergents 70-80% of the primary energy use takes place in the use stage [19]. For televisions (using picture tube technology) 70-80% of the total CO2 emissions have been found to take place in the use stage [20]. A Japanese LCA study shows that for refrigerators also around 80% of the CO2 emissions take place in the use stage [21]. Finally for automobiles LCAs were carried out on a number of Ford

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cars (all 2.0litre engines). They showed that 75-80% of all Global Warming Potential takes place in the use stage, with more or less similar results for Photochemical Ozone Creation Potential [22]. The last issues of this point relates to the certification program, which acknowledges that only a small fraction of the world’s energy demands is currently covered by current solar income [12]. Therefore it is possible to fulfil the requirements for use of current solar income in the production process by purchasing Green-e certified renewable energy certificates to offset the energy used to in the production stage of the product. As with most other green electricity certification programs, purchased certificates do not guarantee that the electricity you receive is physically produced by renewable sources. Instead it attributes a certain fraction of the renewable electricity produced to the purchaser. Demand for sustainable electricity thus theoretically provides utilities with an economic incentive to supply more renewable energy through the installation of more renewable energy generation capacity. In reality, however, there is no guarantee that this actually happens. In Denmark the supply of green certificates is so high that the demand for certificates has only served to increase the profits of the utility companies, not the size of the installed renewable energy generation capacity [23]. Since coal is considered the short term marginal electricity resource in Denmark (and in many other countries), an increased demand in electricity will be supplied with electricity from coal. This is compatible with the approach used when carrying out a consequential LCA. 3.4

studies could indicate for each case which disposal option would present the most sustainable solution. This has been partly investigated in the two PLA studies [15], [16], where composting in the second study causes higher overall environmental impacts than incineration with energy recovery (in the first study composting was not assessed). In response to the fact that biological nutrients in many cases do not contain any macro- or micronutrients the authors suggest that these should be integrated into products on purpose. This is exemplified in the idea of including a seed in an ice cream wrapper to support growth of plan life when the wrapper is discarded on the ground [10]. However there is lag of logic here. If the plant life should be supported because it would otherwise decline, then what is the use of extracting scarce seeds from the eco system and then return them again at a later point? This does not represent a nutrient addition, but a nutrient transportation. The same point could be made about integrating macro- and micronutrients into biological nutrient products. Finally it must be stressed that ecosystems are complex. The concentration of a nutrient that is optimal in one ecosystem could be toxic in others. Also within an ecosystem different niches have different needs of nutrients. Distribution of biological nutrients is therefore a key issue as illustrated in Figure 3.

Effect of adding biological nutrients to the environment

According to the Cradle to Cradle concept adding biological nutrients to the environment is a good thing. This statement is based on the fact that many parts of the environment are in shortage of nutrients due to human activities and therefore need the addition of biological nutrients to recover their natural balance. However the authors are not very clear on exactly to which parts of the environment the biological nutrients should be added (e.g. unspoiled ecosystems, watersheds, agricultural lands or gardens?). Also they do not elaborate on whether it matters what kind of nutrients are added where and in which amounts. It is a well established fact that everything is toxic if the dose is sufficiently large, so the simplified message of Cradle to Cradle that biological nutrients are good and more biological nutrients are better is problematic. The concept of biological nutrients and biological metabolisms needs to be elaborated on. Macronutrients such as nitrogen, phosphorus and potassium are necessary in rather large quantities for most species. Micronutrients, such as zinc, manganese and selenium, are less abundant, but nevertheless needed in small amounts for many biological processes. The examples used by the authors as biological nutrient include carpet trimmings, clothing and packaging materials. Such products would most likely be based on polymers of carbohydrates, as in the case of PLA. These polymers only contain carbon, hydrogen and oxygen and therefore no macro or micronutrients. Carbon is usually not considered a nutrient, since it in biodegradable form is degraded into CO2 and water, neither of which nourishes species and increases their growth (other than that of the degrading microorganisms). When added to soil, the small fraction of carbon that is not degraded stays in the soil in the form of humus, that limits erosion, buffers against fluctuations of soil pH, retains water, is important for soil fertility and may mitigate climate change due to its function as a carbon sink [24], [25]. However since only a small fraction (around 2%) of the carbon is retained in humus and since it may not be irreversibly retained, the benefits of this disposal option may be limited. For this reason the Danish EPA has stated that biodegradable plastics should generally rather be incinerated with energy recovery than composted [26]. Again LCA

Figure 3: Generalized picture of the relation between dose of biological nutrient and effect on an organism after [24]. An example where biological nutrients will lead to adverse rather than positive effects is the addition of bio available nitrogen and phosphorous compounds (such as ammonia and phosphate) into receiving water bodies. Such compounds are concentrated in waste water, mainly due to human waste and ends up in aqueous ecosystems along with similar compounds from agricultural runoffs. This nutrient enrichment causes eutrophication, which leads to excess production of algae, loss of oxygen and biodiversity in surface water ecosystems. Also when increased concentrations of bio available nitrogen occurs in ground water aquifers, the use of the water for drinking water supply is linked to increasing incidences of diseases such as stomatitis and methemoglobinemia (‘blue baby sickness’) [24]. When applying the Cradle to Cradle concept of biological nutrients into design of products issues such as nutrient type, distribution and alternative disposal options should therefore be carefully considered. This can be done by the use of LCA. It should, however, be mentioned that since LCA considers all impacts from emissions to cause adverse effects, then additions of nutrients that will in fact cause degraded environments to recover, are not attributed positively, unless it is defined as an intention and included in the functional unit of the study.

Life Cycle Assessment - Methods and Tools 3.5

The use of composite materials

According to the Cradle to Cradle concept, materials should be uniform to guarantee maximum recyclability. This should be understood in the sense that technical and biological nutrients should not be mixed, but also in the sense that mixing of technical nutrients should at least be limited so that one product does not contain too many different types of compounds that would complicate recycling. Thus uniform materials are preferred over composite materials. Here, a trade-off may arise in the fact that the use of composite materials could lead to lower environmental impacts in other life cycle stages than disposal when compared to uniform materials. An example can be found in the automobile industry. As mentioned, 75-80% of the global warming impact is caused by emissions occurring in the use stage [22]. Obviously, the weight of the car has a significant influence on the fuel consumption and thereby the total global warming impact. Cars are usually composed of hundreds of components that are made from different steel and aluminium alloys due to different needs in e.g. strength and flexibility. If they were to become homogenized according to the Cradle to Cradle concept, it would inevitably lead to a less practical design. More importantly a study has found that legislation imposing strict recycling quotas, such as the EU Directive on end-of-life vehicles, may inhibit the development of future light weight car designs. This is because such designs rely on parts made from non-metals (primarily glass, plastic and composites) that are problematic to recycle [27]. Using the same argument, the development of sustainable light weight cars may be inhibited in a Cradle to Cradle design paradigm. This trade-off between recyclability and impacts in the use stage can be investigated using LCA. 3.6

Sustainability and economic growth

Perhaps the most radical message of Cradle to Cradle is that economic growth and thereby growing rates of material consumptions are compatible with a sustainable Cradle to Cradle society. The authors justify this message by stating that as long as all materials circulate in the technical or biological closed nutrient loop, then economic growth can happen at a high rate without any harm to the environment (provided that there is an unlimited access to solar-based energy with a negligible environmental impact). However at some point economic growth will result in a situation where 100% of an available resource is present in the use stage of the technical or biological metabolism. Using the allegory of the cherry tree, this corresponds to a situation where all the nutrients in the cherry tree ecosystem are in the tree, mainly in the form of cherries hanging on the trees because the tree doesn’t shed the fruits. The lack of nutrients in the other parts of the cycle causes the tree’s surrounding environment to degrade. In the case of a Cradle to Cradle society with unlimited economic growth the parallel is a situation where further production is limited by the rate at which products are being disposed of, so their technical nutrients can become available to new products, and where environmental degradation is significant. In response to this, the authors encourage products to be designed with a short lifetime in mind. This will enable the nutrients to move quickly around in the closed loops to fuel the economy. However the authors do not address the issue of stockpiling. It is a fact that the demand for different resources in a given region by far exceeds the waste generation rates of the same resource for that region. E.g. the demand for iron in the EU is much higher than the generation rate of iron waste. This is partly due to the fact that metals such as iron are commonly applied in physical infrastructure, such as railroads and street lights, where their function often demands high durability. Design for short lifetime is thus not always a feasible solution and may not, by itself,

603 solve the problem of resource shortage as a result of continued economic growth in a Cradle to Cradle society. According to eco-efficiency thinking, the response to increasing economic growth would be to design products that, in addition to being recyclable, also are dematerialised. However a decrease of down to 2% material to meet the worst case requirements derived from the IPAT equation seems unrealistic. Therefore, neither the eco-efficiency nor the Cradle to Cradle approach has a solid solution to a sustainable future where economic growth continues at today’s rates. 4

OUTLOOK

It is clear that Cradle to Cradle has a very different approach to sustainability than eco-efficiency and LCA. From the presentation of the critical points it is also clear that the Cradle to Cradle approach alone could lead into sub-optimisation and thereby unsustainable products. This is especially the case in a world that is very far from only relying on current solar income. Tradeoffs between closing the material loop and the associated energy use is the main reason for critical points 3.2, 3.3 and 3.5. However Cradle to Cradle also has some advantages over eco-efficiency in that it provides some absolute guidelines. These have been found to inspire product designers to rethink their perception of sustainability and to fundamentally redesign products. Cradle to Cradle as a generative method can inspire designers to different product design solutions. LCA as an analytical tool may be used to assess the sustainability of these different design solutions and keep track of it as the design process proceeds [28]. By using both tools a producer could benefit from the positive image of a Cradle to Cradle product and still be certain that the product does not perform worse than products of eco-efficient competitors who don’t follow a Cradle to Cradle approach. Generally it should be investigated for which types of products Cradle to Cradle design results in non-eco-efficient products. This would allow producers to know, before investing time and effort into the Cradle to Cradle concept, whether it is something they would want to engage in. However, hardcore proponents of Cradle to Cradle may argue: “It does not matter if Cradle to Cradle products today perform worse than eco-efficient products. What matters is that the products are driving the development towards a Cradle to Cradle society.” Such an argument is valid when it comes to waste management infrastructure. If large volumes of closed-loop recyclables are introduced to the market, recyclers will be provided with an economic incentive to recycle these materials. Therefore, where an LCA may discredit a product designed for closed loop recycling, because such recycling is not taking place, then in time, these products would in fact drive the development towards a more sustainable waste management system based on more specialized recycling processes. When it comes to energy supply there is however no reason to believe that Cradle to Cradle products would act as a driver for the installation of more renewable energy capacity. That is unless producers choose to follow the advice of the authors: get off the grid and rely on own locally produced power through e.g. windmills or solar panels on factory roofs. This leads on to the discussion of what part of society should act as drivers of a Cradle to Cradle development (if such a development is to be pursued). The authors themselves have a rather liberal view and state that regulatory instruments should not be applied and that private initiatives will drive the development once producers see the benefits. Other than a clean consciousness, incentives are stated as reduced fees for disposal of toxic waste, increased income from the right to use the Cradle to Cradle brand and increased income

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from the change in business model that may be necessary [6]. However 8 years after the book was published relatively few products (less than 400 worldwide) have been certified [29]. Of these few of the producers are known to have completely changed their business model the way the authors propose it (e.g. technical nutrient products should be leased through product service systems and not sold). Therefore regulatory environmental measures such as increased taxes on raw materials and land filled waste and higher subsidies to the installation of renewable energy capacity, may be needed to seriously promote the Cradle to Cradle development. 5 [1]

REFERENCES Huesemann, M. H. (2004): The failure of eco-efficiency to guarantee sustainability: Future challenges for industrial ecology. Environmental Progress, Vol. 23, No. 4, pp. 264270.

journey/~/media/news%20and%20events/natureworks_th eingeojourney_pdf.ashx [14]

Slideshow presentation (2010): Cradle to Cradle Seminar, Copenhagen Business School, 24/11-10

[15]

Madival, S.; Auras, R; Singh, S. P.; Narayan, R. (2009): Assessment of the environmental profile of PLA, PET and PS clamshell containers using LCA methodology. Journal of Cleaner Production, Vol. 17, No. 13, pp. 1183-1194.

[16]

Vink, E. T. H.; Davies, S.; Kolstad, J. J. (2010): ORIGINAL RESEARCH: The eco-profile for current Ingeo® polylactide production. Industrial Biotechnology, Vol. 6, No. 4, pp. 212224.

[17]

Gutowski, T. G. (2008): Thermodynamics and recycling, A review. IEEE International Symposium on Electronics and the Environment, pp. 1-5.

[18]

De Clercq, S. (2008): Towards sustainable business uniforms. Thesis (master). Delft University of Technology.

[19]

Van Hoof, G.; Schowanek, D.; Feijtel T. C. J.; Boeijie, G.; Masscheleyn, P. H. (2003): Comparative Life-Cycle Assessment of Laundry Detergent Formulations in the UK. Tenside, Surfactants, Detergents, Vol. 40, No. 5, pp. 276-287.

[2]

Huesemann, M. H.; Huesemann, J. A. (2008): Will progress in science and technology avert or accelerate global collapse? A critical analysis and policy recommendations. Environment, Development and Sustainability, Vol. 10, No. 6, pp. 787-825.

[3]

Chertow, M. R. (2001): The IPAT Equation and Its Variants: Changing Views of Technology and Environmental Impact. Journal of Industrial Ecology. Vol. 4, No. 4, pp. 13-29.

[20]

[4]

Wenzel, H.; Alting, L. (2004): Architecture of Environmental Engineering. Conference proceeding from "Global Conference on Sustainable Product Development and Life Cycle Engineering" Berlin, September 29th - October 1st 2004.

Andrae, A. S. G.; Andersen, O.; (2010): Life cycle assessments of consumer electronics — are they consistent? The International Journal of Life Cycle Assessment, Vol. 15, No. 8, pp. 827-836.

[21]

Wenzel, H.; Hauschild, M.; Alting, L. (1997): Environmental Assessment of Products. Volume 1: Methodology, tools and case studies in product development. Kluwer Academic Publishers

Morioka, T.; Morioka, T.; Yamamoto, Y.; Yabar, H.; Tsunemi, K.; Yoshida, N. (2005): Eco-efficiency of advanced loopclosing systems for vehicles and household appliances in Hyogo Eco-town. Journal of Industrial Ecology, Vol. 9, No. 4, pp. 205-221.

[22]

Schmidt, W. (2006): Life Cycle Tools within Ford of Europe's Product Sustainability Index. Case Study Ford S-MAX & Ford Galaxy. The International Journal of Life Cycle Assessment, Vol. 11, No. 5, pp. 315-322.

[23]

The Ecological Council. (2010): Strøm med klimavalg (note only available in Danish): http://www.ecocouncil.dk/index.php?option= com_content&view=article&id=166:strom-medklimavalg&catid=10:artikler-energi-og-klima&Itemid=89'

[24]

Reijnders, L. (2008): Are emissions or wastes consisting of biological nutrients good or healthy? Journal of Cleaner Production, Vol. 16, No. 10, pp. 1138-1141.

[25]

Lal, R.; Follett, F.; Stewart, B. A.; Kimble, J. M. (2007): Soil carbon sequestration to mitigate climate change and advance food security. Soil Science, Vol. 172, No. 12, pp. 943-956.

[26]

Nielsen, A. M.; Weidema, B. P. (2002): Miljøvurdering af alternative bortskaffelsesveje for bionedbrydelig emballage. Miljøprojekt Nr. 680 2002. Miljøstyrelsen: http://www.mst.dk/udgiv/publikationer/2002/87-7972-0706/pdf/87-7972-071-4.pdf

[27]

Reuter, M. A.; van Schaik, A.; Ignatenko, O.; de Haan, G. J. (2006): Fundamental limits for the recycling of end-of-life vehicles. Minerals Engineering, Vol. 19, No. 5, pp. 433-449.

[28]

Bakker, C. A.; Wever, R.; Teoh, C.; de Clercq, S. (2010): Designing cradle-to-cradle products: A reality check. International Journal of Sustainable Engineering. Vol 3, No. 1, pp. 2-8.

[29]

McDonough Braungart Design Chemistry. (2010): Cradle to Cradle certification. Certified Products. View by certification rating: http://c2c.mbdc.com/c2c/list.php?order=type

[5]

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McDonough, W.; Braungart, M. (2002): Cradle to Cradle – Remaking the way we make things. North Point Press. New York.

[7]

Kalundborgsymbiosys. (2008): New technologies and innovation through Industrial Symbiosis. Industrial Symbiosis Institute:http://www.symbiosis.dk/media/7940/symbiosis% 20paper%20presentation.pdf

[8]

McDonough Braungart Design Chemistry (2010). Cradle to Cradle Resources: http://www.mbdc.com/detail.aspx?linkid=1&sublink=26

[9]

Voorthuis, J.; Gijbels, C.; A Fair Accord (2010): Cradle to Cradle as a Design Theory Measured against John Rawls’ Theory of Justice and Immanuel Kant’s Categorical Imperative. Sustainability, Vol. 2, No. 1, pp. 371-382.

[10]

Braungart, M.; McDonough, W.; Bollinger, A. (2007): Cradleto-cradle design: creating healthy emissions - a strategy for eco-effective product and system design. Journal of Cleaner Production, Vol ;15, No. 13-14, pp. 1337-1348.

[11]

Sessions, G. (1995): Deep ecology for the 21st century: Readings on the philosophy and practice of the new environmentalism. Shambhala Publications, London, England, UK. ISBN: 1570620490

[12]

[13]

McDonough Braungart Design Chemistry. (2008): Cradle to CradleSM Certification Program - Version 2.1.1. 2.: http://www.mbdc.com/images/Outline_CertificationV2_1_ 1.pdf NatureWorks. The Ingeo™ Journey. http://www.natureworksllc.com/the-ingeo-

(2009):

Environmental Assessment of Printed Circuit Boards from Biobased Materials 1

2

3

Yelin Deng , Karel Van Acker , Wim Dewulf , Joost R. Duflou 1 2

1

Center for Industrial Management, Katholieke Universiteit Leuven, Belgium

Department of Material Engineering, Katholieke Universiteit Leuven, Belgium 3

Groep T – Leuven Engineering College, Leuven, Belgium

Abstract This paper performs a cradle-to-gate LCA (Life Cycle Assessment) to compare the environmental impact between conventional PCB substrate (epoxy resins reinforced with glass fiber) and biobased PCB substrate, in case epoxidized linseed oil and flax fiber. The study reveals that the overall weighted environmental scores of substrate from biobased materials are significantly lower than the traditional materials, especially in impact categories of climate change, human toxicity and fossil resources depletion. Since previous results showed satisfactory technical properties of the biobased materials as PCB substrate, they offer promising perspectives for final replacement of the conventional materials. Keywords: Printed Circuit Board; Life Cycle Assessment; Biobased Materials

1

INTRODUCTION

Printed Circuit Boards(PCBs) substrate refers to the most fundamental part of PCB on which circuits, devices, and chips can build. In general, substrate is a laminated composite consisting of three components: the resin system, the reinforcement, and the copper foil [1]. By far, the most commonly used materials for resin system and reinforcement are epoxy resin or epoxy resin blends and woven glass fiber fabric. PCB substrate is manufactured through prepregs and lamination process. Firstly glass fiber fabric is coated with partially cured epoxy resin to form prepreg, and then multiple layers of prepregs are stacked between two layers of copper foil. Finally copper foil and prepregs are laminated into intact composite under high pressure and high temperature [2]. Within substrate, epoxy resin is derived from crude oil, a nonrenewable resource, glass fibers are manufactured through energy intensive processes, and its laminated structure made PCBs very difficult to recycle. Dominant disposal technology of PCBs today is pyrometallurgical process [3], which is to incinerate PCB scraps and then extracts metals from ash. Epoxy resin acts as fuel for incineration while glass fibers are transferred into slag in this process. Although pyrometallurgical process demonstrates a high economic feasibility since it can recover most precious metasl used in PCBs, this proccess, like any other process involving incineration of petroleumbased materials, contributes to CO2 emissions and the resulting global warming. From materials viewpoint, one approach to reduce environmental concerns of PCB would be to try biobased materials. Biobased polymer and natural fibers are possible alternatives to epoxy resin and glass fibers respectively. Advantages of biobased materials includes that they are obtained from renewable resources and they contribute to balancing the CO2 cycle. Biobased materials take up CO2 during growth and release CO2 to the atmosphere after incineration. In addition, natural fibers, unlike glass fibers, that burden the incineration, can also be considered as fuel during pyrometallurgical process, and additionally reduce the amount of slag.

An early contribution regarding biobased alternatives in PCB substrate production was published by Kosbar and Gelorme [2]. In their study a biopolymer named lignin was incorporated into traditional composite (glass fiber reinforced epoxy resin) as PCB substrate. Key properties for PCB applications, such as the glass transition temperature, the coefficient of thermal expansion(CTE), the dielectric constant, the dissipation factor, and flame retardancy were found to be comparable to traditional materials. They also carried out a very simple environmental analysis and argued that lignin based materials had lower energy requirements. Another work in this topic was contributed by J.D.Lincoln et.al [4]. Unlike Kosbar and Gelorme, who still used glass fibers as reinforcement, J.D.Lincoln et,al. adopted almost fully biobased materials. They used epoxidized linseed oil(ELO) and flax fibers to replace epoxy resin and glass fiber respectively. The only synthetic material in their combination was melamine polyphosphate(MPP), a non-halogen flame retardant regarded as environmentally friendly flame retardant [4]. J.D Lincoln et al implemented a full range of tests according to IPC4101A/20, an international standard for multilayered printed circuit board laminates. Their results show that substrate from flax fiber/ELO plus MPP meets most requirement categories in IPC4101A/20. J.D.Lincoln et al.’s results are promising. However, in their study, the authors did not present a comprehensive environmental impact assessment to compare the biobased alternatives with conventional materials. Generally speaking, biobased materials can be expected to correspond to a lower environmental impact since they are renewable, but a quantitative environmental analysis is indispensable to confirm this anticipated conclusion. Therefore, in this study, a comparative LCA was carried out between biobased and conventional PCB substrate materials. 2

GOAL AND SCOPE DEFINITION

The aim of this LCA is to compare the environmental impact of PCB substrate from two composites: glass fiber reinforced conventional epoxy resin(glass fiber/epoxy) and flax fiber reinforced ELO plus

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_105, © Springer-Verlag Berlin Heidelberg 2011

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MPP(flax fiber/ELO(MPP)). Copper foil is not included because copper foil remains unchanged in both cases and hence can be omitted in a comparative LCA study. 2.1

Functional unit

The glass fiber content in uncladed PCB substrate varies from 58% to 66% by weight. In this study, an average fraction of 62wt% of glass fiber content is assumed. The flax fiber content is 52.6wt% as implemented in [4]. Since PCBs are sold by their dimension, not by 2 weight [5], the functional unit is set at 1 m of laminate composite from these two types of materials system with thickness of 1.60mm, a standard thickness of PCB substrate [1]. Functional equivalence is thought to be achieved due to the final testing results in [4]. 2.2

3

LIFE CYCLE INVENTORY

3.1 Flax fiber reinforced epoxidized linseed oil composite The general production steps of flax fiber reinforced ELO composites, as shown in Figure 1, start from flax plant cultivation. Flax cultivation generates two products: straws and seeds. Flax fibers can then be extracted from straws. Flax seeds, on the other hand, are used to produce linseed oil, which can be converted to epoxidized linseed oil through epoxidization. Detail information on these steps will be discussed in the following sections. Flax seeds

System boundaries

This study analyzes stages from raw materials extraction and production until composite fabrication. Applied data represents current situation in Europe. Environmental impacts during usage and disposal phases are not discussed in this paper. Flax fiber and Epoxidized linseed oil production France, Belgium, and Nederland accounted for almost 94% of total flax production within EU-27 in 2008 [6] , flax plant cultivation mainly refers to data from these three countries. The flax yarn production and fabric manufacturing are applied as LCI modules in Ecoinvent 2.2 database from the Swiss center for Life Cycle Inventories. These LCI modules address the general techniques for textile fabrication of bast fibers in the world.

Cultivation

Flax straw

MPP

Epoxidization

Flax fiber

Moulding

ELO

Flax fiber composite

Glass fiber and Epoxy resin production

Equipments and Infrastructures Impacts of equipments used for cultivation, fiber processing, yarn and fabric production and oil squeezing are considered in this study, including machines production, delivery, and depreciation. Impacts of agricultural buildings, oil mill, and chemical plants are included in the applied LCI modules from Ecoinvent 2.2 Transport Transport distances are extremely difficult to identify for each specific operation. Standard distances for commodities consumed in Europe [7] are applied. 2.3

Allocation principle

In this LCA study, an economic allocation is implemented when multiple products are generated. Other common allocation methods such as mass allocation or energy allocation, however, may lead to unreasonable results. For example, flax fiber only constitutes about 25 wt% [7] of the whole flax plant , but it is the main incentive for people to grow flax plants. 2.4

Data sources

For every production system under study, the inventory data, including inputs of materials, energy, and processes and outputs of emissions and waste materials, were retrieved by literature study. The data sources are listed in the inventory table of a specific production system. LCI data for these sublayer units, e.g. inputs of materials energy, are referred to the same or highly related modules in Ecoinvent 2.2

Linseed oil

Fiber processing

Flax seeds produced can be used to extract linseed oil. There is no detailed data on environmental impact of linseed oil production, therefore the LCI of rapeseed oil production in Ecoinvent2.2 is selected. Data on glass fiber and epoxy production are exclusively obtained from Ecoinvent 2.2. LCI module of glass fiber is based on a report for European glass manufacturing, while LCI module of epoxy is obtained from Eco-profiles of the European plastics industry.

Pressing Extraction

Flax seed

Figure 1: Overview of production processes of flax fiber composite. Flax cultivation Flax is cultivated through six consecutive steps: soil preparation, fertilization, sowing, pesticide and herbicide spraying, desiccation, and harvesting (pulling) [8]. Inputs of Seeds, fertilizer and pesticide input are calculated through averaging values from different publications [8-11]. In order to generate maximum length of fibers, flax plants are commonly harvested by pulling Yields of flax straws and seeds are calculated based on information from statistics of agriculture and rural development of European Commission [6]. The average yield of flax straws from 2005 to 2008 is 6.17 ton/hectare and average yield of seeds is 457 kg/hectare in France, Belgium, and Nederland. Direct field emissions are calculated through formulae obtained from the publications listed in the reference column in Table 1. Wheat straw and rape seeds are applied as proxies of flax straw and seeds respectively for calculation of emissions of heavy metals to soil because data on heavy metal absorption of flax are not available. Indirect emissions from agricultural machines are included in the applied LCI module for that specific agricultural process. Flax cultivation

Value

Reference

Flax straw

6170kg

[6]

Flax seed

457kg

[6]

75kg

average, [8-11]

Products

Materials input Seeds for sowing

…table continued on the next page

Life Cycle Assessment - Selected Applications

607

…continued from the previous page

Flax retting

Nitrate

40kg

average, [8-11]

Product

Phosphorus

32kg

average, [8-11]

Flax straw, retted

Potassium

60kg

average, [8-11]

Material input

Lime

666kg

[8]

Flax straw

6170kg

Pesticide

1.36kg

[8, 9]

Tractor

6.35kg

[8]

Carbon Dioxide

9211kg

[12]

Other machines

3.27kg

[8]

Diesel

1049.8MJ

[8]

Herbicide

7.88kg

[8]

Agricultural machinery processing Use of plough, cultivator, roller, sowing, fertilizing ,harvesting

1 ha

[8]

Transport Train, railway

57.72tkm

[7]

Lorry, road

9.62tkm

[7]

Energy consuming of agricultural machines is included in the applied LCI module from ecoinvent2.2. Emission Emission Types

Value

Reference

to Air

0.971kg

[13]

to Air

1.14kg

[13]

Nitric oxide

to Air

0.239kg

[13]

Nitrate

to groundwater

40kg

[13]

to groundwater

0.07kg

[13]

Ammonia Dinitrogen noxide

mo-

Phosphorus

to river, run-off

0.189kg

[13]

to river by erosion

0.087kg

[13, 14]

to soil

Reference

Heavy metal emissions to river by erosion

Cadmium

42.27mg

18.68mg

2.12g

[13, 14]

Chromium

20.87g

2.18g

200.9g

[13, 14]

Nickel

~

1.51g

8.93g

[13, 14]

Lead

102.7mg

307.3mg

2.75g

[13, 14]

Mercury

0.17mg

0.44mg

1.46mg

[13, 14]

Zinc

10.4g

1.44g

12.29g

[13, 14]

Copper

2.73g

1.40g

-8.4g

[13, 14]

Table 1: Inventory of flax plant cultivation per hectare. Negative value of copper in emissions to soil represents that copper content decreases in the soil. Copper may transfer into water body and/or flax plant according to [13]. Flax straws and flax seeds share almost the same price in market [8], therefore, economic allocation and mass allocation deliver the same results. Flax fiber processing After being pulled, flax straws are left in the field for retting process [15]. Field retting is main retting methods in Europe today [15]. During field retting, flax straws expose to dew, rain, and sunshine for several weeks. Retting benefits subsequent flax fiber extraction because it decomposes pectin, a binder among fiber bundles, through microbial process. Materials loss after retting is 13% of total weight according to [16]. When retting process is finished, flax straws are baled for storage or proceed to the scutching process.

Reference

5121kg

[16]

Transport Train, railway

4.73tkm

Lorry, road

0.788tkm

Table 2: Inventory of flax fiber processing: Retting. Flax fibers are finally obtained from the scutching process. Retted flax straws firstly go through between a pair of fluted rollers so that they would be crushed into small pieces. Then the broken straws are beaten by rotating blades forcing inner woody tissue of the stem (called shives) falling apart and separated from flax fibers. Scutching process generates long fibers, short fibers, and shives. Yield of flax fibers (long fiber and short fiber) is 1756 kg/ha [6]. This value represents the average yield of flax fibers in France, Belgium, and Nederland during 2005-2008. Average ratio of long flax fibers over short flax fibers is 4:1 [17]. Yield of flax shives is found to be at 50% weight of input biomass [18]. The inventory data can be seen in Table 3 Flax fiber scutching Products Long fiber

to groundwater

Value

1404kg

[6, 17]

Short fiber

351kg

[6, 17]

Shive

2561kg

[18]

Materials/Energy input Flax straw, retted

5121kg

Machines

16.1kg

[8]

Electricity

2707MJ

[8]

Transport Train, railway

512tkm

Lorry, road

256tkm

Waste treatment Dust and Residual

805kg

Table 3: Inventory of flax fiber processing: Scutching. Following economic principles, the allocation factors for multiple products are calculated, as shown in Table 4 Products

Yield (kg)

Price (Euro/kg)

Allocation factor

Long fiber

1404

1.80

93%

Short fiber

351

0.35

5%

Shive

2561

0.02

2%

Table 4: Allocation factors for multiple products of flax (Products prices from [8]).

608

Life Cycle Assessment - Selected Applications

Yarn production and fabric manufacturing To be used as reinforcement for PCB substrate, flax fibers need to be incorporated and woven into fabrics [5]. Flax yarns are base materials for any fabric production. ‘Yarn production, bast fibres’, an LCI record in Ecoinvent2.2, was selected to evaluate the environmental impact of this process. ‘Weaving, bast fibres’, also in Ecoinvent2.2 is applied to assess the process from yarn to fabric. Materials loss during production of flax fabrics is 18% in total: 16% loss due to yarn production, 2% due to subsequent loss. [19] Natural fibers suffer from high moisture absorption [4]. Chemical treatment of flax fabrics is essential to lower the moisture absorption. Surface treatment, as practiced in [4], Alkali(sodium hydroxide) plus silane, is assumed to be a standard step for flax fabric in case of future PCB substrate application. Detail information on flax fabric manufacturing can be found at Table 5 Flax fabric

Value

Reference

1155kg

[19]

Products Flax fabric, chemical treatment Materials input Long flax fiber

1404kg

Ecoinvent 2.2 is used as proxy for linseed oil extraction. However, a few adjustments were made according to [21]: 

Flax seeds input for producing 1 kg of linseed oil is 3.14 kg



co-product linseed meal is 2 kg



Transport is adjusted to 0.314 tkm by train and 0.156 tkm by road.

Allocation factors for linseed oil and linseed meal is 72% and 28% respectively , as listed in Table 6, based on economic principle. Products

Yield (kg)

Price (Euro/kg)

Allocation factor

Linseed oil

1

0.94

72%

Linseed meal

2

0.185

28%

Table 6: Allocation factors of linseed oil and linseed meal (Price source: tradingcharts.com). The last step is epoxidization of linseed oil. Synthetic methods have already been discussed by researchers [22]. To epoxidize 1 kg of linseed oil requires 200g 50% peroxide aqueous solution. Related Energy consumption and emissions of epoxidization are omitted due to lack of data. Biobased composite manufacturing

Processing Yarn production

1404kg

‘Yarn production, bast fibres’ (Ecoinvent 2.2)

Weaving

1179kg

‘Weaving, bast fibres’ (Ecoinvent 2.2)

Surface treatment of flax fiber

1155kg

[4]

Transport, energy and emissions are included in the yarn production and weaving process Table 5: Inventory of flax fabric production. Epoxidized linseed oil production Both linseed oil and flaxseed oil are extracted from seeds of flax. Their difference lies in different extraction method. Flaxseed oil is produced by a cold-pressing for edible use [20] while Linseed oil is obtained from depress solvent extraction of flax seeds and mainly used in industrial applications [21].

Flax fiber/ELO(MPP) composite is fabricated through traditional prepregs and lamination process [4]. Energy intensity of this process is 53.1MJ/kg [23]. Materials loss during manufacturing is 5% according to the assumption in [24]. Units for producing one functional unit of PCB substrate are calculated and listed in Table 7 Units

Value

ELO

0.44kg

Flax fabric

1.22kg

MPP

0.65kg

Energy consumption

123 MJ

Transport railway

1.3tkm

Transport road

0.23tkm 2

Table 7: Unit processes for production of 1m PCB substrate. 3.2

Glass fiber reinforced epoxy resin composite

Glass fiber fabric As depicted in Figure 3, glass fiber is manufactured by melting a mixture of different materials: sands, limestone, soda, etc. Detail information concerning the manufacturing of glass fiber can be found in [25]. The ‘glass fiber, at plant’ module in Ecoinvent2.2 is applied for assessment. This module covers processes for continuous filament glass fiber, which subsequently can be twisted or plied into yarns, and then woven into fabrics. ‘1080’, ‘2116’, and ‘7628’ are three most common types of glass fiber fabrics for PCB substrate. All of them are woven by yarns from continuous filament glass fibers. Other types of glass fiber fabrics may be manufactured from staple filament or texturized continuous filaments [1].

Figure 2: Processes flow of production of epoxidized linseed oil. Figure 2 shows the processes flow for producing epoxidized linseed oil. In North America, linseed is produced in the same way of producing rapeseed oil [21]. It is assumed in the study that this is also true in Europe. The LCI module, ‘Rape oil, at oil mill/RER U’ in

Electricity and Thermal energy consumption in weaving process can be found at [26]. Electricity consumption is 5.06 kWh/kg woven fabric, and heating(coal) is 9.85 kJ/kg woven fabric. Materials loss from glass yarn production and weaving is assume to be at 18% same as in flax fiber fabric production, 16% in yarn production, and 2% in weaving.

Life Cycle Assessment - Selected Applications

609 4.1

Characterization

In total 17 impact categories were selected for this life cycle assessment. Figure 4 presents the environmental profiles of the two 2 composites for 1m PCB substrate production. As mentioned before, in this LCA study, environmental impacts during the use and disposal phases are not included. The environmental profiles for both variants only account for the raw material extraction/production and composite manufacturing.

Figure 3: Processes flow of glass fiber/epoxy composite production. Yarn production of glass fiber is modified from yarn production of bast fibres module in ecoinvent 2.2. The following inventory table provides data for production of 1 kg glass fabric. Units

Value

Reference

1.21 kg

Processing of weaving

1.02kg

[26]

Processing production

1.21kg

‘Yarn production, bast fibres’ modified

of

yarn

120 110 100 90 80 70 60 50 40 30 20 10 0

Fossil depletion

IMPACT ASSESSMENT

The environmental impact of the two studied types of composites is calculated and evaluated by means of Simapro 7.2.4. The assessment method is ReCiPe 1.04/ Europe ReCiPe H/A.

Metal depletion

4

Urban land occupation

2

Table 9: Unit processes for production of 1m PCB substrate.

Natural land occupation

0.29tkm

Agricultural land occupation

Transport road

Freshwater ecotoxicity

1.7tkm

Marine ecotoxicity

151MJ

Transport railway

Terrestrial ecotoxicity

Energy consumption

Freshwater eutrophication

1.77kg

Terrestrial acidification

Glass fiber fabric

Ionising radiation

1.09kg

Climate change ecosystems

value

Brominated epoxy

Particulate matter formation

5% weight loss is also assumed during lamination. Table 9 refers to the inventory for one function unit of glass fiber/epoxy substrate.

Photochemical oxidant formation

Composite manufacturing

Ozone depletion

The most common type of epoxy resin for PCB is synthesized from epichlorohydrin and bisphenol-A. Generally bisphonol-A are brominated in order to increase flame retardancy for epoxy resin. Tetrabromobisphenol-A(TBBPA) is the most widely used brominated bisphonol-A. It can react with epoxy and incorporates its structure into the molecular chain of epoxy. Hence TBBPA will not leach to environment during use phase [1].

Human toxicity

Table 8: Unit processes for 1kg of glass fiber fabric. Epoxy resin

Climate change human health

Transport is included in the above LCI module but adjusted to 0.71tkm by railway and 0.12 tkm by road

Units

Flax fiber/ELO(MPP)

Glass fiber/Epoxy

%

Glass fiber

From Figure 4 it is clear that for most impact categories the flax fiber/ELO(MPP) alternative offers a reduced environmental burden except for agricultural and natural land occupation. The higher impact of flax fiber/ELO(MPP) composite on higher land occupation is self-evident. However, the high level of land occupation raises the concern that flax may compete with human food production. With regard to the climate change, both from human health and ecosystem perspective, the flax fiber/ELO(MPP) composite shows a significantly better environmental score. This is primary due to the fact the flax plant can absorb CO2 during growth and flax/ELO composite consumes much less fossil fuel compared to glass/epoxy composites. Epoxy/glass composite also have much higher impact in human toxicity. The main sources of its high human toxicity are from their more electricity consumption during production and from brominated epoxy resin itself.

Figure 4: Characterization of the two composites. 4.2

Evaluation

Although aggregation poses a risk for obscuring the specificity of the environmental impact effects caused by the studied composite alternatives, at this stage of the comparative study it was considered useful to obtain a conclusion that could provide an overall conclusion towards PCB producers and designers of electric/electronic equipment. For this purpose the normalization and weighting steps are used. Normalization and weighting performed by Europe ReCiPe H/A, which is default set in Simapro.7.2.4, referring to normalization value of Europe with average weighting set. As it can be seen from Figure 5, the main factors contributing to total weighted environmental impact of glass fiber/epoxy is fossil depletion and climate change both in human health and in ecosystem. Agricultural land occupation, fossil depletion, climate change are major constituents of overall weighted environmental impact of flax fiber/ELO(MPP) composite. In general, the single points of two composites definitely demonstrate that flax fiber/ELO(MPP) has much lower environmental impact.

610

Life Cycle Assessment - Selected Applications processing scenarios and a flax scenario, National Institute from Agronomy Research (INRA). France.

4.01Pt 2.78Pt

[9]

Schmidt, A., Jensen, A., Clausen, A., Kamstrup, O., Postlethwaite, D., (2004): A comparative life cycle assessment of building insulation products made of stone wool, paper wool and flax. The International Journal of Life Cycle Assessment, Vol. 9, No. 1, pp. 53-66.

[10]

Guidelines for growing flax, (2004): Flax and Hemp Project, Henfaes Research Centre, University of Wales, online at: www.flaxandhemp.bangor.ac.uk

[11]

Smith, M. and Carlson, S., (2006): Flax Production Guideline for Iowa, Iowa State University Extension, online at: www.extension.iastate.edu

[12]

De Vegt, O. and Haije, W., (1997): Comparative environmental life cycle assessment of composite materials, Netherlands Energy Research Foundation.ECN.

[13]

Nemecek, T. and Kagi, T., (2007): Life cycle inventories of agricultural production systems, in Ecoinvent report, No.15, Swiss Centre for Life Cycle Inventories.

[14]

Van der Knijff, J., Jones, R., and Montanarella, L., (2000): Soil erosion risk assessment in Europe, European Soil Bureau, European Commission.

Pt

4 3.5 3 2.5 2 1.5 1 0.5 0

Glass fiber/Epoxy Climate change human health Particulate matter formation Freshwater eutrophication Agricultural land formation Fossil depletion Ozone depletion Ionising radiation Terrestrial ecotoxicity Urban land occupation

Flax fiber/ELO(MPP) Human toxicity Climate change Ecosystems Freshwater ecotoxicity Natural land transformation Photochemical oxidant formation Terrestrial acidification Marine ecotoxicity Metal depletion

Figure 5: Single score of the two composites. 5

SUMMARY

This comparative LCA study shows that the flax fiber and epoxidized linseed oil alternatives show a clear impact reduction compared to glass fiber and epoxy resin. For the production stage the overall weighted environmental impact of flax fiber/ELO(MPP) is only approximately 69% of the environmental load of the epoxy/glass fiber combination. Since the technical properties of flax fiber/ELO(MPP) almost entirely comply to the international standard specifications for PCB substrates, a clear perspective exists for further investigation of the properties of flax fiber and ELO. Ultimately this may lead to a replacement of conventional materials for printed circuit board substrate production. For the biobased materials alternative major concern in this context relates to its high agricultural land occupation. This may imply competition with human food production. Therefore, further research towards biobased materials with minimal requirements for arable land use is recommendable. 6

[15] Ehrensing, D.T., (2008): Oilseed Crops: Flax, Extension and Experiment Station Communications, Oregon State University [16]

Mikhailouskaya, N., (2006): The effect of flax seed inoculation by Azospirillum brasilense on flax yield and its quality, plant soil and environment, Vol. 52, No. 9, pp. 402.

[17]

Records for crop reports 2009, (2009) : Saneco Group, online at: www.saneco.com.

[18]

Khazma, M., Goullieux, A., Dheilly, R., Laidoudi, B., Queneudec, M., (2010): Impact of aggregate coating with a PEC elastomer on properties of lightweight flax shive concrete, Industrial Crops and Products.

[19]

Althaus, H.-J., Werner F., Settler, C., Dinkel, F., (2008): Life Cycle Inventories of Renewable Materials, in Ecoinvent report, No. 21, Swiss Centre for Life Cycle Inventories.

[20]

Zheng, Y., Wiesenborn, D., Tostenson, K., Kangas, N., (2003): Screw pressing of whole and dehulled flaxseed for organic oil. Journal of the American Oil Chemists' Society, Vol. 80, No. 10, pp. 1039-1045. Flax situation and outlook, (2007): Bi-weekly bulletin, Vol. 20, No. 1, pp. 5-10, Agriculture and agri-food, Canada.

REFERENCE

[1]

Coombs, C., (2007): Printed circuits handbook: McGraw-Hill Professional.

[2]

Kosbar, L., Gelorme, J.D., Japp, R.M., Fotorny, W.T., (2000): Introducing biobased materials into the electronics industry, Journal of Industrial Ecology, Vol. 4, No. 3, pp. 93-105.

[21]

[3]

Yu, J., Williams, E., and M. Ju., (2009): Review and prospects of recycling methods for waste printed circuit boards, IEEE international symposium on sustainable systems and technology, pp.1-5.

[22] Téllez, G., Vigueras-Santiago, E. and Hernández-López, S., (2009): Characterization of linseed oil epoxidized at different percentages, Superficies y Vacio, Vol. 22, No. 1, pp. 5-10.

[4]

Lincoln, J., Shapiro, A., Earthman, J., Saphores, J., Ogunseitan O., (2008) Design and evaluation of bioepoxy-flax composites for printed circuit boards, Electronics Packaging Manufacturing, IEEE Transactions on, Vol. 31, No. 3, pp. 211-220.

[23]

Suzuki, T. and Takahashi, J., (2005): Prediction of energy intensity of carbon fiber reinforced plastics for mass-produced passenger cars, the Ninth Japan International SAMPE system, pp. 14-19.

[5]

LEE, K. and PARK, P., (2001): Application of life-cycle assessment to type III environmental declarations, Environmental Management, Vol. 28, No. 4, pp. 533-546.

[24]

[6]

Statistical and economic information 2009, (2009): Agriculture and Rural Development, European Commission, online at: http://ec.europa.eu/agriculture/agrista/index_en.htm

Hischier, R., Classen, M., Lehmann, M., Scharnhorst, W., (2007): Life Cycle inventories of Electric and Electronic Equipment: Production, Use and Disposal, in Ecoinvent report. No. 18, Swiss Centre for Life Cycle Inventories.

[25]

Kellenberger, D., Althaus, H.-J., Jungbluth, N., Kunniger T., Lehmann, M., Thalmann, P., (2007): Life Cycle Inventories of Buidling Products, in Ecoinvent report, No. 7, Swiss Centre for Life Cycle Inventories.

[26]

Koç, E. and Çinçik, E., (2010): Analysis of Energy Consumption in Woven Fabric Production. FIBRES & TEXTILES in Eastern Europe, Vol. 18, No. 2, pp. 14-20

[7]

[8]

Frischknecht, R., and Jungbluth, N., (2007) Overview and methodology, in Ecoinvent report, No. 1, Swiss Centre for Life Cycle Inventories. Van der Werf, H. and Turunen, L., (2006): Life cycle analysis of hemp textile yarn. Comparison of three hemp fibre

Application of Life Cycle Engineering for the Comparison of Biodegradable Polymers Injection Moulding Performance 1

1

1

2

Duarte Almeida , Paulo Peças , Inês Ribeiro , Pedro Teixeira , Elsa Henriques 1

1

IDMEC, Instituto Superior Técnico, TULisbon, Portugal 2

Fapil S.A., Malveira, Portugal.

Abstract The use of biodegradable and compostable polymers (BDP) has a rising concern derived from its particular characteristics. Currently, various BDPs are combined to improve technical performance, to open up new applications or to reduce costs. In this paper a Life-Cycle-Engineering model is developed to compare the economical, environmental and technical dimensions of performance for 4 different types of BDPs when processed through injection moulding technology. The proposed model allows for comprehensive alternative comparison, supporting informed material selection decisions in a product-design context. The use of a ternary decision space supports materials comparison and the identification of their ‘‘best alternative domains’’. Keywords: Life Cycle Engineering; Biodegradable and Compostable Polymers; Injection Moulding

1

INTRODUCTION

The increasing environmental awareness of nowadays society has affected most of industrial processes and products, especially plastic, which is one of the most versatile materials in the modern age. Plastic is widely used in many products throughout the world. However, its dramatic production increasing has focused public attention on a potentially huge environmental accumulation and pollution problem that could persist for centuries, due to their lack of degradability, to the closing of landfill sites and to the growing water and land pollution [1,2]. Furthermore, as over 99% of plastics are of fossil fuel origin, their rapid increase will put further pressure on the already limited non-renewable resources on Earth. This new context of an environmentally conscious society has fostered the development of new solutions for plastics, with lower environmental impacts [3]. In fact, biodegradable and compostable plastics may serve as a promising solution to the overloaded landfills by diverting part of the volume of plastics to other means of waste management and, in most of the cases, by preserving non-renewable resources [4]. Starch (STA) has been seen as a possible substitute for petroleum based plastics as it is both renewable and degradable. However, due to its water sensitivity and low mechanical properties, it’s not suitable for many plastic products. One solution developed to overcome these limitations was to combine plasticized starch with another biodegradable polymer [5]. PolyLactidAcid (PLA) is currently one of the most promising biopolymers, as some studies have found that PLA has comparable mechanical and physical properties to that of Polytethyleneterephtalate (PET) and Polystyrene (PS) [6,7], therefore being able to fulfil very different commercial applications [5]. Following this research area, this study aims to compare four different types of biodegradable polymers (BDP) with different amounts of starch and PLA, considering a final product produced by injection moulding. The comparison, unlike most studies in the area regarding only environmental impacts, comprises also economical and functional performance analyses. Hence, it allows having an integrated view of the advantages and disadvantages of using these new materials regarding several dimensions of analysis. This comprehensive

analysis is within the Life Cycle Engineering [LCE] scope, as this label concerns areas where environmental concerns overlap with Design Engineering and Production Engineering [8]. Jeswiet [9] defined LCE as “Engineering activities which include: the application of technological and scientific principles to the design and manufacture of products, with the goal of protecting the environment and conserving resources, while encouraging economic progress, keeping in mind the need for sustainability, and at the same time optimizing the product life cycle and minimizing pollution and waste”. Moreover, material selection is an important application area of LCE. As material selection is part of product design, decisions taken during this stage largely influence the product’s costs and environmental impacts for its entire life. As environmental impacts of products are directly influenced by the materials environmental properties, the material selection assumes a strategic importance [10, 11]. Being a general methodology connecting several areas, it is necessary to use different methods to evaluate the dimensions of analysis. As the aim is to analyse different materials of a generic product produced by injection moulding, it was considered the life cycle of the product comprising the stages from material production till the product end-of-life. The life cycle stages were analysed both in terms of economical performance, through Life Cycle Cost (LCC) method, and in terms of environmental evaluation, using Life Cycle Assessment (LCA). LCC objective is to cover the assessments of costs in all steps of the product’s life cycle, including the costs that are not normally expressed in the product market price [12], such as costs incurred during the usage and disposal. LCC is essentially an evaluation tool in the sense that it gets on important metrics for choosing the most cost-effective solution from a series of alternatives [13]. Regarding LCA, it is a structured method to quantify potential environmental impacts of products or services over their full life cycle [14, 15], being therefore a valuable tool to provide designers with information on inputs, outputs and associated environmental impacts of a defined system [16]. Regarding the functional dimension of analysis, the proposed materials are compared taking into consideration its intrinsic characteristics and its correlations with the

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_106, © Springer-Verlag Berlin Heidelberg 2011

611

612

Life Cycle Assessment - Selected Applications

most important characteristics of a plastic part. Finally, instead of following the traditional approach of analysing the dimensions separately, the three dimensions of analysis are aggregated in a single analysis framework. The result is a more comprehensive view of the possible choices. The framework is a ternary diagram, in which the dimensions of analysis are represented in each axis. With this approach, the difficult task related to the materialization of the relative importance of the three dimensions into a set of weights is overcome. The use of ternary diagrams to support decisions is an innovative approach, which has been applied in other industrial frameworks [17]. 2

METHODOLOGY

Raw Material Acquisition Plastics Processing

Mould Production

Plastic Parts Manufacturing Parts Use

End of Life

Economic evaluation – LCC

Mould material processing

Environmental Evaluation – LCA

The first stage of the LCE model proposed in this study (Figure 1) is to define the boundaries of the problem under analysis and to collect specific data for material application and product life cycle. The next step is to evaluate individually the product from an economic, environmental and functional point of view. These evaluations use distinctive methods. Economical and environmental evaluations are performed from a life cycle perspective, using LCC and LCA respectively. Functional Assessment is performed using a conventional approach based on decision matrices, with the materials analysed based on their properties. For each material and for each dimension of evaluation a single indicator is obtained, allowing the direct incorporation of the functional, economical and environmental performances into a multi-criteria decision problem. The final result is a global evaluation, presented in a ternary diagram, which make available a clear view of the possible choices according to the importance given to the three dimensions of analysis (functional, economic, and environmental) – criteria weights.

3 3.1

APPLICATION OF LCE FOR THE COMPARISON OF POLYMERS Case study

The aim of this study is to compare four different biodegradable polymers (BDPs), not only environmentally, but also in terms of economical and functional performances. The BDPs are all mixtures of PLA and STA, differing on the amount used of these two components, as shown in Table 1. Although both components are compostable, the environmental burdens during the production of PLA are higher than in the STA case. However, as already mentioned, STA lacks in mechanical properties. Therefore, by analysing a product life cycle using these different materials it is important to evaluate them based on a comprehensive approach. Material Manufacturer Trade name 10/90 Cabopol Biomind C004 40/60 Rodenburg Biopol. Solanyl 35F 80/20 Cabopol Biomind R006 90/10 Biotec Bioplast GS 2189

Composition 10%PLA+90%STA 40%PLA+60%STA 80%PLA+20%STA 90%PLA+10%STA

Table 1: BDPs description.

3.2

Plastic parts life cycle

In this section it is presented the life cycle of plastic parts, with all the data and important processes of each life cycle phase. Figure 2 represents the life cycle of a generic plastic part and it’s divided in 5 main stages, from raw material acquisition to end of life. Mould material production

Injection Materials Production

Mould manufacturing

Injection moulding

Injected parts (samples)

Injection wastes

Parts use

Composting

EOL Ideal scenario

Functional Assessment

Composting Selection Diagram

Figure 1: Overview of the Life Cycle Engineering Model. These ternary materials selection diagrams illustrate the “best materials” for different criteria weights. In fact the ternary diagrams identify not only the best materials according to a set of weights attributed to functional, economic, and environmental dimensions, but also the domain (range of weights) of each best material. Within this approach the design engineer overcomes the difficult task related to the materialization of the relative importance of the three dimensions into a set of weights.

Alternative scenario

Landfill

Figure 2: Plastic parts life cycle. Once this study is only concerned with the plastic materials and not with a particular product, the use phase won’t be analyzed. Moreover, the final disposal phase regards several scenarios; composting and landfill. Although landfill is still a real scenario for plastic products nowadays, this study aims to compare the BDPs impacts in an ideal scenario – Composting. Regarding the plastic parts manufacturing stage, the process chosen is a very common one, injection moulding. All parts were injected using the same injection mould; therefore in terms of polymers comparison it won’t

Life Cycle Assessment - Selected Applications

613

Life Cycle Cost

The global approach of the LCC model to each material life cycle phase is illustrated in Figure 3. For each life cycle phase, the LCC model uses the parameters to perform a simplified life cycle inventory, with only the relevant streams considered, cross this information with costs databases and retrieve a total phase cost. Gathering all stages it’s possible to obtain the entire life cycle cost.

Process information Mass streams

50

Cycle time [sec]

3.3

and energy costs decrease with the cycle time decreasing. It means that these costs increase with the increase of the PLA content.

44

42

40

100 75

20

50

10

25

0

Production facilities

Energetic streams

Energy consumed

125

30

0 10/90

Resources consumed

Cycle time [sec] Raw material costs [€] Injection costs [€] 39 36

Cost [k€]

produce any changes. Still, its incorporation will be reflected on the parts’ final costs and environmental impacts.

40/60

BDPs

80/20

90/10

Figure 5: Injection cycle time Vs. Injection and Raw material costs for 200,000 parts.

Labour

Machines and Tools

Infrastructures and Overheads

Setup

120

Labour

Energy

Equipment

100 Cost [k€]

Costs Database

TOTAL COST Figure 3: LCC Model.

80

56.4%

40 20

The LCC model was applied to an annual average production volume of 200,000 units, distributed in batches of 25,000 units. (The reader should note that is this study, a unit equals to a sample). The results are present in Figure 4. It’s possible to conclude that there is trend of LCC reduction with the increasing of the PLA content.

56.4%

56.4%

56.4%

15.4%

15.4%

15.4%

15.4%

28.1%

28.1%

28.1%

28.1%

10/90

40/60

80/20

90/10

60

0 BDPs

Figure 6: Injection phase costs distribution.

120

0.3%

0.3 %

Cost [k€]

100 80 60

84.4%

Mould production End of Life 0.3% 80.5%

84.5%

0.3% 76.9%

40 20 0

12.3% 10/90

3.0%

12.1% 40/60

3.2%

BDPs

16.0% 80/20

3.2%

Exploring the potential of the LCC model developed, is possible to produce several sensitivity analysis. One of these analyses is presented in Figure 7, which illustrates the influence of the annual production volume on the cost per part (based on the LCC). With the annual production increasing the cost per part decrease and the cost hierarchy is not altered since all the cost as a similar dependence on the number of parts produced.

3.3%

0,75

19.5% 90/10

Figure 4: LCC results and costs distribution for a production volume of 200,000 parts. As can be confirmed in Figure 5, the cause of this behaviour is the cycle time required to inject the part. The better injection characteristics of PLA compared with STA ones, allow the BDPs with higher PLA (90/10 and 80/20) content to be injected with lower cycle times. The reduction in the production time costs compensates the higher costs for the BDPs with higher PLA content. It must be referred that for different part geometry the relation between the required material and cycle time might be different, so a distinct behaviour can be observed. As regards the type of production costs involved, the ones related with the injection equipment causes more than 50% of the total, followed by the labour costs (Figure 6). As expected, equipment

10/90

0,70 Cost per part [€]

140

Materials acquisition Injection moulding

40/60

80/20

90/10

0,65 0,60 0,55 0,50 0,45 0

250000

500000

750000

1000000

Production volume

Figure 7: Evolution of the LCC with the annual production increasing. 3.4

Life Cycle Assessment

At this stage, a cradle to grave approach is performed to assess the environmental impacts of the several candidate BDPs, using all

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data previously collected for the injected parts/samples and considering an annual average production of 200,000 parts. The proposed LCA model, schematized on Figure 8, considers 11 environmental impact categories, in the following three areas: Human Health (HH), Ecosystem Quality (EQ) and Resources (R). The methodology aggregates all the emissions and resources consumption from the life cycle into these impact categories and, afterwards, weights the scores into a single value, called the “ecoindicator 99” (EI 99) [18].

impact of injection moulding has a higher volume the overall environmental impact tends to reduce with the increasing of the PLA content. It can also be mentioned that even though the production of materials with high STA content have a lower environmental impact, the differences in injection cycle time are high enough to cause a higher environmental impact of these materials. Nevertheless, for different geometries it might occur a small difference in injection cycle times that can promote the lower PLA materials as the ones with lower impact.

The first step is to define the system boundaries. The materials impact in the life cycle stages of the plastic material are considered, from the raw materials extraction to the plastic production. The use phase was disregarded since it was assumed to be equivalent to the four materials. The injection moulding process and the mould production where analysed separately, as more accurate results could be obtained with the data gathered from the processes. Finally, it was considered as the end of life strategy that the BDP go to composting.

3.5

LCI – Life Cycle Inventory Process Information Mass Streams

Energetic Streams Emissions Data base

Resources Consumed

Emissions Produced

Energy Consumed

Impact Value System Human health Ecosystem Resources Environmental Impact Calculation

Impact categories

TOTAL ENVIRONMENTAL IMPACT

EI ‘99

Functional assessment

The functional performance of a product, tool or other equipment can be evaluated using several decision-making methods, usually made on a comparison base, such as graphic theory and matrix approach (GTMA) and fuzzy Multiple Attribute Decision-Making (MADM) methods [18]. In common, all of them rely on the knowhow and expertise of professionals and users to determine the relevant functional requirements for the application. In the LCE model developed for this study, the functional assessment refers to functional requirements and their contribution to the functional performance of a typical application for the polymers in comparison, over its life. Possible applications to biodegradable polymers are: daily use and disposable type of products, such as food or liquid containers, plastic bags or even hygiene products like tooth brushes. Therefore, the selection of the requirements for the polymers comparison should rely on the polymers’ physical properties but also on product users’ demands and expectations. At the time of this study execution, physical tests were still being made; hence, there is a lack of polymers’ physical data to perform an elaborated functional assessment of these polymers. For this reason, it was adopted a simple functional assessment analysis, yet capable of being used with the LCE approach to the polymers comparison.

LCIA – Life Cycle Impact Assessement

Figure 8: LCA Model.

12000

EI'99 points

10000

End of Life Injection materials Mould material 9971.7

Injection moulding Mould manufacturing 10012.3

9934.4

9525.6

8000 6000 4000 2000 0 10/90

40/60

BDPs

80/20

90/10

Figure 9: LCA final results. The results of the application of the LCA model are presented in Figure 9. The impact of mould material, mould manufacturing and material composting are not significant. As the PLA content increases the impact of material production increases, and simultaneously, the impact of part production decreases. Since the

Figure 10: Functional Assessment methodology. The first stage of this analysis is, as indicated in Figure 10, to select the requirements to analyse. Having in mind the type of products in which these polymers are intended to be used, the following requirements to assess were selected: Lightness, Mechanical Strength, Biodegradability and also Appearance. Lightness can be easily evaluated by polymers density and Mechanical Strength by the knowledge of the Tensile Strength property for the polymers 40/60 and 90/10. For the remaining BDPs, that property may be qualitatively evaluated by the concentration of STA (Table 2). If PLA is the substance responsible for the STA “plasticization” and improvement of its limitations such as mechanical and water sensitivity, one may assume BDPs with lower percentages having also lower values of Tensile Strength. Consequently it is valid to positioning 10/90 having lowest Mechanical Strength among BDPs, being 80/20 positioned between 40/60 and 90/10.

Life Cycle Assessment - Selected Applications Physical properties PLA concentration [%] STA concentration [%] Density [kg/m3] Tensile Strength [Mpa]

10/90 10 90 1200 -

40/60 40 60 1280 13-15

615 80/20 80 20 1250 -

90/10 90 10 1300 30 - 45

Table 2: Polymers’ physical properties. As far as Biodegradability goes, it can also be evaluated by the presence of STA. The larger the percentage of STA, faster should be the polymers degradability at equal conditions of temperature and humidity. Finally, Appearance may obviously be evaluated by visually inspection of the injected samples but also by knowing that greater concentrations of PLA are expected to deliver a more synthetically-like appearance to the final products and consequently better outlook.

The global evaluation for this case study is presented in the ternary diagram in Figure 11. Only two materials appear in the triangle meaning that 10/90 and 40/60 don’t have performance, relatively, good enough in any of the three dimensions. In fact, these two materials are the more economic ones and cause the lower environmental impact in its production. Nevertheless, considering the overall life cycle analysis they have lower performance in the cost and environmental dimensions than the other two materials. Since their functional performance is lower, they don’t “show up” as alternatives in the final decision diagram.

Table 3 shows the ratings given to the materials on each requirement, assuming equal weighting to all of them. Material properties Lightness Strength Biodegradibility Appearance Total Ranking

10/90 10 1 10 1 5.5 2

40/60 3 4 7 4 4.5 3

80/20 5 7 3 8 5.75 1

80%PLA + 20% STA

90/10 1 10 1 10 5.5 2

90% PLA + 10% STA

Table 3: Functional assessment evaluation. Total results from Table 3 shows little functionality differences for the 4 materials. The material with lower STA (10/90) presents the best results for Lightness and Biodegradability, but is also the weaker and one with lower ranking on Appearance. The 40/60 has the lowest average ratings, despite of having a good degradability. The 90/10 appears as the stronger and better in appearance but also the worst when it comes to Lightness and Biodegradability. Finally, 80/20 presents the best overall ranking due to its better average ratings. In despite of being simple, this Functional Assessment allows comparing the BDPs in terms of functionality and permits the application of the LCE approach to materials comparison. However, further developments in this dimension of comparison are being made and should be included in future studies. 3.6

Global evaluation

The assessment of the results achieved allows the development of a global evaluation of the alternatives. The outcomes of each individual dimension of analysis (technical, economical and environmental performance) are adimensionalized to allow the attribution of importance weights (dimension weights). The sum of the three dimensions weights must be 100% and different combinations of weights might result in a different “best alternatives”. The difficulty to attribute importance weights to the dimensions of analysis that closely reflect a corporation strategy, and the sensibility of the results achieved to such weights are the major drawbacks normally pointed to a global evaluation based on weights attribution. To overcome this disadvantage and have a clear view of the possible “best moulds” correlated to its domain of weights, the global evaluation is performed through a ternary diagram, where each axis represents one dimension of analysis. The diagram illustrates not only the “best alternative” for a particular set of importance weights but also the domain of weights for each “best alternative”.

10%

20%

30% 40%

50%

60% 70% 80%

90%

Economical Performance Figure 11: Global Evaluation of the 4 materials. The 80/20 polymer is the best choice if in the decision making process is given an importance to functional performance higher than 47% and to environmental importance lower than 51%. The better performance of 90/10 on cost dimension and environmental dimensions are the cause for this behaviour. 4

CONCLUSIONS

This research focused on comparing biodegradable polymers (BDPs) with different compositions regarding the amount of starch (STA) and PolyLactidAcid (PLA). Most studies analyse these materials in terms of environmental impacts, as BDPs are seen as possible fossil-based polymers substitutes. However, nowadays decisions are multi-attribute, based also on economical and technical performances. Additionally, a decision based only on price or environmental differential between materials is not enough. In an industrial context, materials are used to manufacture a part or a product and different materials mean different operating conditions or even different processes during production. Moreover, materials may even imply changes in design in order to meet technical requirements. In fact, this study enhances the need to go beyond material properties and to analyse the whole product life cycle. And as previously stated, the life cycle evaluation of a product using different materials is not sufficient by only looking at environmental impacts, being necessary to evaluate the materials in terms of life cycle cost and technical performance. In this paper four different BDPs are analysed, differing in the amount of PLA and STA. Whilst STA means lower environmental impacts to produce, PLA performs better during injection moulding, leading to lower pressure

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requirements, lower cycle time and consequently, lower energy consumption. Actually, results from the application of the methodology based on LCE principles show that both economically and environmentally, the 90/10 PLA-based material is the one with higher life cycle scores. As regards to the technical analysis, also a PLA-based material, the 80/20, is the one with higher score. This was expectable due to the poor mechanical performance of STA.

[11]

Giudice, F., La Rosa, G., Risitano, A. (2005): Materials selection in the Life-Cycle Design process: a method to integrate mechanical and environmental performances in optimal choice in: Materials and Design, vol. 26, pp. 9-20.

[12]

Krozer, Y. (2006): Life cycle costing for innovations in product chains in: Journal of Cleaner Production, vol. 16, no. 3, pp. 310-321.

Considering the decision diagram integrating all dimensions of analysis, only these two materials, the 80/20 and the 90/10, appeared as the best choices. This is because other materials, STA-based, performed worst in all dimensions of analysis considering the product life cycle. If approximately more than 50% of importance is given to the technical performance, the “best material” is the 80/20 PLA-based polymer. Otherwise, the best choice is the 90/10 polymer. Notice that this analysis considered a particular manufacturing process, injection moulding, and this may not be truth for other processes. As STA-based polymers have lower acquisition costs and lower environmental impacts regarding the material production phase, their performance in the subsequent processes define their suitability for a particular product.

[13]

Shtub, A.; Bard, J. F.; Globerson, S. (2005): Project Management - Processes, Methodologies and Economics, Pearson Prentice Hall.

[14]

Johansson, K.; Perzon, M.; Fröling, M.; Mossakowska, A. (2007): Sewage sludge handling with phosphorus utilization e life cycle assessment of four alternatives In: Journal of Cleaner Production, vol. 16 no. 1, pp. 135-151.

[15]

Udo de Haes, H. A.; Heijungs, R. (2007): Life-cycle assessment for energy analysis and management in: Applied Energy, vol. 84, no. 7-8, pp. 817-827.

[16]

Warren, J. L.; Weitz, K. A. (1994): Development of an Integrated Life-Cycle Cost Assessment Model in: Proceedings of the IEEE International Symposium on Electronics and the Environment; IEEE, San Francisco, CA, pp 155-163.

[17]

Ribeiro, I., Peças, P., Silva, A., Henriques, E., (2008): Life cycle engineering methodology applied to material selection, a fender case study in: Journal of Cleaner Production, vol. 16: p. 1887-1899.

[18]

Ribeiro, I., Peças, P., Henriques, E. (2009): Life Cycle Engineering applied to design decisions, a case study in: Proceedings of the 16th CIRP International Conference on Life Cycle Engineering, Cairo, Egypt.

Finally, the main conclusion is the importance of analysing the whole life cycle of a product. As results show, even materials labelled as eco-friendly, as STA, may behave poorly during the product manufacturing and turn out to have high environmental and economical impacts. 5

REFERENCES

[1]

Mok, C.K., Chin, K.S., Lan, H. (2008): An Internet-based intelligent design system for injection moulds In: Robotics and Computer-Integrated Manufacturing, vol. 24, pp. 1-15.

[2]

Shah, A.A., Hasan, F., Hameed, A., Ahmed, S. (2008): Biological degradation of plastics in: A comprehensive review. Biotechnology Advances, vol. 26, no. 3, pp. 246-265.

[3]

Stripple, H., Westman, R., Holm, D. (2008): Development and environmental improvements of plastics for hydrophilic catheters in medical care: an environmental evaluation in: Journal of Cleaner Production, vol. 16, no. 16, pp. 1764-1776

[4]

Ren, X. (2003): Biodegradable plastics: a solution or a challenge? in: Journal of Cleaner Production, vol. 11, pp. 2740.

[5]

Schwach, E., Six, J-L., Avérous, L. (2008): Biodegradable Blends Based on Starch and Poly (Lactic Acid): Comparison of Different Strategies and Estimate of Compatibilization in: Journal of Polymers and Environment, vol. 16, pp. 286-297.

[6]

Auras R, Singh J, Singh S. (2006): Performance evaluation of PLA existing PET and PS containers in: Journal of Testing and Evaluation, vol. 34, no.6, pp.530–6.

[7]

Auras R., Singh S., Singh J. (2005): Evaluation of oriented poly(lactide) polymers vs. existing PET and oriented PS for fresh food service containers. Packaging Technology and Science, vol. 18, pp. 207–16.

[8]

Jeswiet, J., Duflou, J., Dewulf, W., Luttrop, C., Hauschild, M. (2005): A Curriculum for Life Cycle Engineering Design for the Environment in: 1st Annual CDIO Conference, Ontario, Canada.

[9]

Jeswiet, J. (2003), A definition for life cycle engineering in: Proceedings of the 36th international seminar on manufacturing systems. pp. 17–20. Saarbrucken, Germany.

[10]

Kurk, F.; Eagan, P. (2008): The value of adding design-forthe-environment to pollution prevention assistance options in: Journal of Cleaner Production, vol. 16, no. 6, pp. 722-726.

6

CONTACT

Paulo Peças IDMEC, Instituto Superior Técnico, TULisbon, Av. Rovisco Pais, 1049-001 Lisbon, Portugal [email protected]

Using Ecological Assessment during the Conceptual Design Phase of Chemical Processes – a Case Study 1

1

2

Laura Grundemann , Jan C. Kuschnerow , Tobias Brinkmann , Stephan Scholl 1

1

Institute for Chemical and Thermal Process Engineering, Technische Universität Braunschweig, Braunschweig, Germany 2

ifu Hamburg GmbH, Hamburg, Germany

Abstract During the conceptual design phase the performance of a chemical process is fixed by defining the sequence of unit operations and choosing suitable equipment. A tool box supports a consistent data management and a quantitative assessment of process alternatives. From the viewpoint of sustainable development, the integration of ecological and social assessment methods remains fragmental whereas economic methods are fully developed. In this case study, three ecological assessment methods have been applied in order to explore their applicability within the conceptual design phase. Conclusions are drawn concerning the methods` usability, transferability and integration into the early process development stages. Keywords: Ecological Assessment; Batch to Conti Transfer; Ionic Liquids

1

INTRODUCTION

The development of new processes and the optimisation of existing systems regarding resource efficiency as well as profitability are challenges in modern engineering. Having chosen a synthesis route, the constituting elements of a process are then mostly fixed in the early stages of conceptual process design [1], [2]. During this stage, the sequence of unit operations and all relevant process parameters are defined and suitable equipment for production scale is chosen. The methods for process design are already well established and subject of continuous improvement. A tool box in the framework of Computer Aided Process Engineering supports a consistent data management and a quantitative assessment of process alternatives. Especially the economic assessment is fully developed and integrated into the engineering workflow. This contributes to the design period’s acceleration, quality management and know-how protection. However, from the viewpoint of a sustainable development the integration of ecological and social assessment methods in the stage of early process development remains fragmental. In contrast to economic assessment, standardised procedures are still lacking [3]. This is caused by the difficulty of evaluating a measure e.g. in regard to social factors such as the potential for innovation, the concerns of employees, customers and neighbouring habitants. Based on an enquiry amongst stakeholders a system of social values has been set up for the biotechnology sector for instance [4]. Due to the immatureness of social assessment methods, the focus of this paper lies on ecological factors. The ecological assessment is based on scientific models, causeand-effect relationships, threshold values and other models since goods are not linked to an ´ecological market price` [3]. Ecological indicators (e.g. yield) and design approaches like the pinch point method [5] are already applied during the design phase. However, further studies concerning impact categories like the global warming potential, the ecotoxicity or resource consumption are mostly not included. Also, little benefit is drawn from the information gained on

lab scale experiments on process and/or equipment performance. Typical tasks in the conceptual design phase are e.g.: 

Selecting the operating mode: continuous, semi-continuous or batchwise.



Selecting and designing unit operations, e.g. selective vs. nonselective separation of an undesired medium.



Selecting a separation process for product capture, e.g. crystallization (requires a heat sink at low temperatures) vs. extraction (requires a suitable extracting agent).



Selecting a suitable catalyst in regard to e.g. the disposal effort, recyclability and substitution.

In principle, all aspects can be treated by a quantitative ecological assessment. Several commercial and public domain tools are available to support this process step, e.g. the software Umberto [6], GaBi [7] and GEMIS [8]. This paper aims to give some insight as to how different ecological assessment methods help an engineer in the conceptual process design phase to develop a more sustainable process. The comparative results of the two case studies are discussed and conclusions are drawn concerning the methods` usability, transferability and integration into the early process development stages. 2

ECOLOGICAL ASSESSMENT METHODS

The Life Cycle Assessment (LCA) method is the only internationally accepted, standardised method for analysing environmental aspects and potential impacts of products or processes. According to Klöpffer and Grahl [9] the LCA method is based on a simplified system analysis. Herein the simplification mainly consists of a linearization. Cross-linking existing parts of a product cycle may lead to very complex relationships. Collecting the required data is one of the most time consuming parts during a LCA study. Depending on complexity and scope LCA studies according to DIN EN ISO 14040 [10] and 14044 [11] take often several months of substantial effort.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_107, © Springer-Verlag Berlin Heidelberg 2011

617

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Life Cycle Assessment - Selected Applications

In the context of conceptual process design this time demand is regarded too high. Other, shorter evaluation methods which require less data and are easier to handle have thus been developed in the past. However, they provide a lower level of information than a complete LCA. For this paper we chose the methods Eco-indicator`99, an EHS assessment tool (Sabento) and the cumulated energy demand (CED) and applied them for two case studies. All of these methods deliver only a single indicator as a result which is easy to interpret. These methods differ in their system boundaries and the required data. Generally, the broader the system boundaries are, the more data is required and the longer a study takes. Thus, it is of interest that the method with the smallest system boundary delivers comparatively good results. The three mentioned methods are introduced in the following. 2.1

Eco-indicator 99

The Eco-indicator 99 was developed especially for process designers by PRé Consultants in the Netherlands [12]. In contrast to the two other methods, the impact categories are calculated according to DIN EN ISO 14040 [10] and 14044 [11] and normalised applying the average European environmental impact potential. The calculated damage score is either given as an individual value for the three main categories ´human health`, ´ecosystem quality` and ´fossil resources` or as an aggregated indicator. According to DIN EN ISO 14044, comparative studies based on methods that allow a high aggregation should be handled with care. The system boundaries follow the ´cradle-to-grave` approach and cover the complete life cycle of a product: pre chains, production, use and disposal/recovery. 2.2

Cumulated energy demand

The cumulated energy demand (CED) is a key indicator for the comparative assessment of the primary energy requirement for technical processes and systems. According to Fritsche [13] the multiplicity of impact categories in LCAs leads to a high effort for data collection and to very complex assessment methods. In case where the environmental impact is dominated by energy consumption, the CED indicator can be used as a rough estimation. It provides at least an informative basis for an environmental assessment [13]. Except for the human and ecotoxicity index, it can be used as an indicator for the shifting of all other LCA impact categories during process design [14]. The calculation of the cumulated energy demand is described in the VDI guideline 4600 [15]. As for the Eco-indicator 99 the system boundaries cover the complete life cycle of a product but the CED is only focusing on the primary energy requirements.

2.3

EHS method according to Heinzle

The EHS (Environment, Health and Safety) assessment method was developed by Heinzle and his co-workers at the University of Saarland [16], [17]. In this method techniques from the classical LCA method are combined with those common in risk assessment [18], [19]. It was especially designed for application in the early phases of process development in which the knowledge and data availability is limited. In contrast to the other methods mentioned this analysis focuses on a “gate to gate” approach which means that the boundaries of the assessed system match the boundaries of the production site. Thus, ecological drawbacks caused by the preceding processes, e.g. the production of the reagents, are only roughly estimated. A rough ABC classification is an essential part of the method. According to defined criteria low, medium or strong effects in the impact categories are assigned to the classified substances. Aggregating all impact categories then delivers a key indicator, the potential environmental impact (PEI) [20]. Since the environmental impact of the energy supply is not taken into account in this method, the PEI always has to be considered in combination with the energy index. The ecological indicators presented are applied for the evaluation of two processes which were modeled using the software tools Umberto and Sabento. The data bank ecoinvent 2.2 [21] was used as a data source for the two indicators Eco-indicator`99 and CED. 3 3.1

INTRODUCTION OF A NEW CATALYST IN THE HOMOGENEOUS CATALYSED TRANSESTERIFICATION Description of the process alternatives

The homogeneous catalysed transesterification is a standard reaction with large scale industrial applications. It is of importance for the production of solvents or bio fuels. The reaction is reversible and has an equilibrium constant of nearly one. Thus, an equimolar mixture of educts and products is obtained after the reaction has reached its equilibrium. This reaction can be catalysed either by acids or bases. Today, sulphuric acid and alkali hydroxides are used as catalysts. After the reaction, they are neutralized and washed out as salt [22], [23], [24]. Acid Ionic Liquids (“IL”), e.g. 1-butyl-3-ethylimidazoliumhydrogensulfate (BEIM-HSO4), are suitable alternative catalysts for the transesterification [23]. Due to their technically negligible vapour pressure, Ionic Liquids are easily recyclable by evaporation of the reactants. The catalytic activity of the above mentioned IL is lower than of sulphuric acid due to its lower acidity and slow solubility [25]. An IL catalyst is currently designed and optimized so that it

Figure 1: Flow sheet of the desired process.

Life Cycle Assessment - Selected Applications

619

Figure 2: Mass and energy flows of the H2SO4 catalysed process (top) and the IL catalysed process (bottom). can be recycled by evaporation, see Figure 1. Based on experimental data and the Ecoinvent database Vol.2.1, an ecological assessment has been performed to compare both technologies described above. The processes with the corresponding mass and energy flows are shown in Figure 2. Here, the existing process catalysed by sulphuric acid has been compared with a newly designed IL catalysed process. The acid IL BEIM-HSO4 has been used as catalyst with a concentration of 2.5 molar % in the reaction mixture. Calculations are based on a production of 40.6 t of butylacetate per year which is the theoretical production capacity of the miniplant test rig. The results obtained are suited for scale-up. The reactor is equipped with an external thermosyphon reboiler. Reaction temperature is 80 °C, heating temperature in the reboiler is 110 °C. System boundaries were chosen as tight as possible in this comparative assessment to keep the analysis simple and still wide enough to cover the main differences like the reaction step and the recycling step of the catalyst. In both processes, the material flows from the synthesis of educts and catalyst to the product of the transesterification are considered. 3.2

Results of the ecological assessment of the two processes

The results of the process comparison are listed in table 1. Low impact numbers indicate eco-friendly processes. At first glance the H2SO4 catalysed process seems to be more eco-friendly, especially while focusing on the differences between both processes, as shown in table 1. For all compared assessment methods the IL scenario is inferior and it seems that the tighter the system boundaries, the bigger the differences between the results. At a second glance it becomes obvious that the differences should not be overestimated. For both alternatives the PEI value is very small. The differences can be explained by uncertainties and the rough evaluation method.

The energy index of the IL catalysed process calculated in Sabento is 25 % higher than in case of an acid catalysed process. This is due to a high energy demand during IL synthesis on lab scale and evaporation of all reactants during recycling. However, the energy index for the reaction itself is lower for the IL catalysed process. The efficiency of the IL catalysed process increases with the number of possible recycles of the IL. Further calculations showed that the energy index of the IL catalysed process is lower than the benchmark process if the IL was recycled and used at least 170 times. Even though there is an energy advantage on the process level, the CED values draw near. The analysis of the cumulative energy demand indicates that by far most of the energy demand is caused by the production of the educts and only around 5 % is needed for the process itself. Also the damage score of the Eco-indicator 99 shows comparable results. 3.3

Discussion of the results

All applied methods indicate similar differences between the two process alternatives. Due to the uncertainties and data quality, these differences should be interpreted carefully. It can be concluded that the IL catalysed process is more energy intensive but produces less waste. Yet, it has to be mentioned that an existing process is compared with a newly designed but not fully optimized process. The IL catalysed process therefore still offers a large potential for improvement. Generally, the results strongly depend on the assumptions. In the assistant based software Sabento the impacts on the environment may only be classified very roughly. Toxicities of unknown substances, for example, have been estimated by comparing the substances with similar molecules considering especially the different functional groups.

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Life Cycle Assessment - Selected Applications H2SO4 catalysed process

IL catalysed process

Damage score in points (Eco-indicator 99) [Points/kg product] 0.86 0.95 Potential environmental impact (Sabento) [PEI/kg product] 6.18 8.66 Energy index (Sabento) [kJ/kg product] 1281 1607 Cumulative energy demand Total value 255816 288680 (CED ) [kJ/kg product] CED renewable 3435 3911 CED non-renewable 252381 284769 Table 1: Results of ecobalances for transesterification in key figures [26]. Here, in case of an unknown effect, it is advised to choose the worst category which shifts the results systematically to less advantageous values. Due to the small percentage of catalyst in the streams, the reduction of waste by using a recyclable catalyst does not have a strong impact on the final result. Process modifications have to reduce the amounts of required educts or waste significantly in order to improve the impact number PEI. The IL synthesis is still performed on laboratory scale which is economically and energetically inefficient compared to technical production scale. Until now, the market volume of IL is small because they are mainly used in R&D. Significant uncertainties are introduced by calculating the energy demand for heating, cooling and vacuum generation based on miniplant data. The values for the new process may however improve if the market for IL grows and if IL thus are produced on technical scale. The results of the CED analysis correspond well to those of the EHS model. The newly designed process is linked to an energy consumption which is around one third higher than the H2SO4 catalysed process. Due to less process chains being considered the values obtained by the EHS model are lower than for the CED analysis. In conclusion, all three applied methods give similar evidences. However the method’s application differs significantly. The Ecoindicator and CED are much more comprehensive than the EHSmethod but require more data. While the educts´ synthesis is implemented in the Eco-indicator model, it is just roughly estimated in the analysis using the EHS method. 4

4.1

Change compared to H2SO4 catalysed process [%] +10 +40 +25 +13 +14 +13

order to form the colour complex the mixture is then heated up to reaction temperature and held at that temperature for a defined amount of time. After cooling down to ambient conditions a final conditioning step is applied before the ink is filled into drums. After each batch both vessels are cleaned with 1,5 m³ water and are scrubbed manually with 1 l of ethanol and soda. Based on the pilot plant described in [28] a production plant with a capacity of 30 kg/h was designed. In contrast to the traditional batch process at least two batch vessels are needed for the colour premixes. One premix is used as a feed for the currently produced ink whereas another is produced or stocked in the remaining vessel(s). After the production of 1000 l ink one premix vessel as well as the micro plant itself is cleaned. An increased mixing efficiency allowed to omit several stabilizers and additives and to replace deionised water by tap water. A low amount of cleaning agents results from the low hold-up of the micro equipment itself. In order to investigate their influence on the assessment, the amount and type of cleaning agent used for the continuous flow through the micro plant were varied. Less fouling occurs at the vessel walls due to increased educt qualities required for a longer stocking of the colour premixes. Thus, cleaning the premix vessel also takes up less purging water.

CONVERSION OF A BATCH INK PRODUCTION PROCESS TO A SEMI CONTINUOUS PRODUCTION LINE USING MICRO PROCESS ENGINEERING Introduction and description of the process alternatives

Due to their flexibility and low production costs batch production schemes are commonly used in the pharmaceutical and specialty chemistry sector [27]. Multi product batch plants are however linked to a high cleaning effort representing a significant ecological disadvantage. Applying micro process equipment the conversion from macro batch to continuous processes becomes profitable even for low and medium production capacities. A campaign manufacturing scheme allows for the production of several products on the same plant. Such a micro conti process has been developed for the model system of writing ink [28]. In order to quantify the environmental impact, an ecological assessment was conducted. The two process alternatives were modelled in Umberto based on a production capacity of 30 t/a. A sensitivity analysis showed no influence of the ink colour on the results. Thus, the analysis was conducted for one specific ink colour out of the respective production group. The two alternatives are described in the following. The data used for the batch process are based on measurements and balancing for a batch size of 1000 l. During the production two premixes are prepared in separate vessels and are then mixed. In

Figure 3: System boundary for the ecological assessment based on CED and EI´99 for both process alternatives (included process steps are shaded in grey; B stands for batch process, C for micro conti process).

Life Cycle Assessment - Selected Applications

621 Batch process

Micro conti process

0.073 1.14 437.5 20.99 0.81 20.18

0.055 1.09 63.82 15.03 0.59 14.44

Damage score in points (Eco-indicator 99) [Points/kg product] Potential environmental impact (Sabento) [PEI/kg product] [29] Energy index (Sabento) [kJ/kg product] [29] Cumulative energy demand Total value (CED ) [kJ/kg product] CED renewable CED non-renewable

Change compared to batch process [%] -25 -4 -85 -28 -28 -28

Table 2: Results of ecological assessment for batch to conti transfer in key figures. The ecological assessment was first limited to the processes themselves. In order to further investigate the changes in recipe, the plant set-up and the design of the cleaning cycle, the upstream and disposal stages were added to the process model, see Fig. 3. In contrast to a complete life cycle assessment, most upstream stages of the educts could not be considered due to insufficient information on the exact ingredients. The same applies for the production of the plant itself. The lifespan of both plants was set to 20 years. No change at transport frequency nor distance was assumed. 4.2

Results of the ecological assessment of the two processes

It first has to be noted that – in contrast to the EHS tool - for the methods Eco-indicator 99 and CED not all processes inside the system boundaries could be assessed due to insufficient data availability, especially for the energy intensive production of educts like colour dyes and pigments. Including those processes would increase the values significantly. It was then chosen to rather analyse only the differing positions of the two production systems. The results are therefore only valid for a comparative analysis between the two process alternatives. The analysis reveals that the micro conti process has advantages in all applied methods as shown in Table 2. Whereas the damage score of the Eco-indicator´99 and the total value of the CED are on a similar level (-25 to –28 %), the PEI (-4 %) and the energy index (-85 %) from the EHS method differ in the percental change. Omitting harmful additives during micro conti production would potentially lead to even lower environmental impact indicators compared to the batch process. This effect is however cancelled out by the impact of the large amounts of ethylene glycol used for cleaning of the continuous flow through micro plant. The substitution of the amount of ethylene glycol by the same amount of water results in a slightly lower PEI in comparison to the batch process. Yet, it has almost no effect on the other two indicators since the amounts are small compared to other material streams on the upstream and disposal stages. Due to a very coarse material classification method implemented in Sabento deionised water and tap water are assigned to the same category. Thus, using utilities at a lower quality is not influencing the PEI results. The different qualities are taken into account for the Eco-indicator and CED. 4.3

Discussion of the results

From the viewpoint of the EHS method, the PEI and the energy index indicate an ecological advantage for the micro conti process. The values of the CED and the Eco-indicator confirm the results. Overall, the micro conti process is more energy efficient and produces less waste during the cleaning cycles than the batch process. In comparison to the batch process the energy index of the micro conti process is 85 % lower. The material streams either remain unchanged or their changes level each other out as the PEI indicates. Thus, this is mainly due to a decrease in energy demand on process level enabled by heat integration with a micro heat

exchanger. The ideal case of total heat integration was assumed based on measurements of the heat transfer efficiency on pilot plant scale [28]. Other experiments have shown that several ink colours can be produced consecutively without any in between cleaning cycles for the continuous plant at optimal production sequence [30]. This would lead to an even lower amount of cleaning agents. However, the largest share of cleaning agents is required for cleaning of the premix vessel. So far the powdery educts still need to be dissolved in order to be fed into the process. The currently available micro equipment does not allow handling and mixing of powdery educts. On the other hand, the batch process could also be further improved. It should be investigated whether a heat reservoir for heat integration is economically viable. 5

SUMMARY

During the process design phase a discrepancy exists between effort and accurateness respectively extensiveness of an ecological assessment. Difficulties may appear if LCA data is not available. By modeling only the differing stages between two or more systems and using the cut-off rule, the number of processes and thus the modeling effort can be reduced to a manageable size. All applied methods delivered within the area of validity. Even miniplant data, relevant area research objectives leading to be quantified.

good results for the case studies though the analyses were based on of research was highlighted and more eco-friendly processes could

The two applied methods considering the whole life cycle, the CED and the Eco-indicator, require a similar effort (same software, modeling, data source) and lead to very similar conclusions. Being easier and quicker, the EHS method from Heinzle shows the same tendency as the other methods in both case studies. However, since the EHS method features smaller system boundaries and different impact categories, relevant information for process or supply chain optimization may be lacking. In both studies the percental differences of the energy indices outrange the CED values which emphasizes the impact of the upstream stages. From the viewpoint of a sustainable development it is therefore consequent to choose an ecological assessment method which considers the total life cycle of a product. In case of process modifications connected to small changes in upstream and disposal stages, the EHS method is however suitable. Choosing the most valid and practical method for a given problem is thus a crucial task for the process engineer. For most precise results during the conceptual process design phase, the studies were consequently updated with data taken from experiments. Vice versa, an optimal benefit could be drawn from the studies`results by using sensitivity analysis in order to identify promising research routes and potential for improvement. However, this interlacing could be further supported by integrating the LCA software into the usual working platforms and material flow analysis tools like flow sheet simulations. The multiple usage of experimental data thus reduces the overall data collection effort.

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Life Cycle Assessment - Selected Applications

The ecological assessment could then also be linked to and be complemented by methods like pinch point analysis helping to detect possible causes for energy inefficiency. 6

REFERENCES

[1]

Azapagic, A., Millington, A., Collett, A. (2004), Process Design for Sustainability: the Case of Vinyl Chloride Monomer, in: Sustainable Development in Practice: Case studies for Engineers and Scientists (Eds.: A.Azapagic, S.Perdan, R.Clift), Wiley-VCH, Chichester.

[2]

Heinzle, E., Hungerbühler, K. (1997): Integrated Process Development: the Key to Future Production of Chemicals, Chimia, Vol. 51, pp. 176-183.

[3]

Heinzle, E. (2006): Abschlussbericht Projekt AZ0312752A; BMBF, Berlin.

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Koller, G., Fischer, U., Hungerbühler, K. (2000): Assessing Safety, Health, and Environmental Impact Early during Process Development, Ind. Eng. Chem., Vol. 39, No.4, pp. 960-972.

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Smola, T. (2009): Das Spaltenmodell – Eine Hilfestellung zur Substitutionsprüfung nach Gefahrstoffverordnung, (Hrsg.: BGIA – Institut für Arbeitsschutz der Deutschen Gesetzlichen Unfallversicherung), St. Augustin, www.dguv.de/ifa/de/pra/spaltenmodell/index.jsp#.

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Brinkmann, T., Rubbeling, H., Fröhlich, P., Katzberg, M., Bertau, M. (2010): Application of Material and Energy Flow Analysis in the Early Stages of Biotechnical Process Development – A Case Study, Chem. Eng. Technol., Vol. 33, No.4, pp. 618-628.

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Swiss Centre for Life Cycle Inventories, ecoinvent, Vol. 2.1 and 2.2., Switzerland.

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Lotero, E., Liu, Y, Lopez, D. E., Suwannakarn, K., Bruce, D. A., Goodwin, J. G. (2005): Synthesis of Biodiesel vie Acid Catalysis, Ind. Eng. Chem. Res., Vol. 44, No. 14, pp. 53535363.

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Sivasamy, A., Cheah, K. Y., Fornasiero, P., Kemausuor, F., Zinoviev, S., Miertus, S. (2009): Catalytic Applications in the Production of-o Biodiesel from Vegetable Oils, ChemSusChem, Vol. 2 No.4, pp. 278-300.

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Schmidt, J., Reusch, D., Elgeti, K., Schomäcker, R. (1999): Kinetik der Umesterung von Ethanol und Butylacetat- Ein Modellsystem für die Reaktivrektifikation, Chem. Ing. Tech., Vol. 71, No. 7, pp. 704-708.

[25]

W. Korth (2003): Zur Veresterung und Umesterung mit Ionischen Flüssigkeiten, Diss., RWTH Aachen, Aachen.

[26]

M. Wesche (2009):, Ökobilanzierung am Beispiel der Katalysatorumstellung für eine Umesterung, Bachelor Thesis, Techn. Univ. Braunschweig, Braunschweig.

ACKNOWLEDGMENTS

The financial support of the Deutsche Bundesstiftung Umwelt (DBU), Osnabrück, Germany (Ref. No. 25833 and 27370) is gratefully acknowledged. We would also like to thank Mrs. Mandy Wesche for the support during the ecological assessment. 7

[17]

Schmidt, M., Keil, R. (2002): Stoffstromnetze und ihre Nutzung für mehr Kostentransparenz sowie die Analyse der Umweltwirkungen betrieblicher Stoffströme. Beiträge der Hochschule Pforzheim Nr. 103.

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Wuppertal Institut und Trifolium-Beratungsgesellschaft (2005): Soziale Bewertung der Nachhaltigkeit biotechnologischer Produktion, BMBF Projekt FKZ 0312752E.

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Linnhoff, B., Flower, J.R. (1978): Synthesis of Heat Exchanger Networks: I. Systematic Generation of Energy Optimal Networks, AlChE J. Vol. 24, No.4, pp. 633-641.

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ifu Hamburg GmbH, Umberto, www.umberto.de.

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PE International, GaBi, www.gabi-software.com.

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Fritsche, U., et al. (1997): Gemis, GEMIS Österreich, www.umweltbundesamt.at.

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Klöpffer, W., Grahl, B. (2009): Ökobilanz (LCA) – Ein Leitfaden für Ausbildung und Beruf, WILEY-VCH, Weinheim.

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[10] DIN EN ISO 14040 (2006): Umweltmanagement- ÖkobilanzGrundsätze und Rahmenbedingungen, Deutsches Institut für Normung e.V., Berlin.

Rauch, J. (Ed.) (1998): Mehrproduktanlagen, Wiley-VCH, Weinheim.

[28]

Grundemann, L., Fischer, N., Scholl, S. (2009): From Macro Batch to Micro Conti Manufacturing: A New Eco-Friendly Production Process for Writing Ink Employing Micro-process Engineering, Chem. Eng. Technol., Vol. 32, No.11, pp. 1748– 1756.

[29]

Sass, R. (2009): Bewertung der ökologischen und ökonomischen Potentiale bei der Umstellung eines Farbherstellungsprozesses, Diploma Thesis, Techn. Univ. Braunschweig, Braunschweig.

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Grundemann, L., Fischer, N., Scholl, S. (2010), in: Proceedings of the 11 th Int. Conf. on Microreaction Technology (IMRET 11), Kyoto, Japan, March 8-10, 2010.

[11] DIN EN ISO 14044 (2006): Umweltmanagement- ÖkobilanzAnforderungen und Anleitungen, Deutsches Institut für Normung e.V., Berlin. [12]

Goedkoop, M., Spriensma, M.: The Eco-indicator 99 – A damaged oriented method for Lifecycle Impact Assessment, Methodology Report. Ministerie van Volkshuisvesting, Ruimtelijke Ordening en Milieubeheer, Nr. 1999/36A.

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Fritsche, U. R. (1999): KEA: mehr als eine Zahl Basisdaten und Methoden zum Kumulierten Energieaufwand (KEA). Broschüre im Rahmen des UBA-F&E-Vorhabens Erarbeitung von Basisdaten zum Energieaufwand und der Umweltbelastung von energieintensiven Produkten und Dienstleistungen für Ökobilanzen und Öko-Audits, Berlin.

[14]

Kralisch, D. (2006): Ökologische Nachhaltigkeit im Fokus der chemischen Forschung und Entwicklung, Diss., Univ. Jena, Jena.

[15]

Richtlinie VDI 4600 (1997): Kumulierter Energieaufwand – Begriffe, Definitionen, Berechnungsmethoden. VDI Verlag, Düsseldorf.

[16]

Biwer, A. (2003): Modellbildung, Simulation und ökologische Bewertung in der Entwicklung biotechnologischer Prozesse, Diss., Univ. Saarbrücken, Saarbrücken.

Environmental Footprint of Single-Use Surgical Instruments in Comparison with Multi-Use Surgical Instruments 1

1

2

2

2

2

Joachim Schulz , Juergen Pschorn , Sami Kara , Christoph Herrmann , Suphunnika Ibbotson , Tina Dettmer and 2 Tobias Luger 1 2

AESCULAP AG, Germany

Joint German-Australian Research Group in Sustainable Manufacturing and Life Cycle Management, Germany Australia

Abstract Manufacturers have been driven towards sustainable manufacturing due to various external and internal forces. Life Cycle Assessment (LCA) is widely used to assess a product’s environmental performance in order to meet arising challenges. This research presents the environmental footprint assessment of single-use and multi-use surgical scissors which are manufactured by AESCULAP AG and a single-use surgical scissors produced by a comparable manufacturer. The cradle-to-gate and the cradle-to-grave assessments were conducted to compare the three surgical scissors using the IPCC GWP100 and Eco-indicator 99 methods. A break-even analysis estimates the preference between single-use and multi-use scissors depending on the use scenario. Keywords: Environmental Footprint; Life Cycle Assessment; Sustainable Manufacturing

1

BACKGROUND

Global trends such as increasing energy and raw material consumption, increasing environmental pollution, shortage of natural resources etc. pose an evident challenge to companies and societies. Industrial manufacturing is one major source of energy and resource consumption today. Thereby, manufacturing entails per definition the use of energy and resources for value creation. The cumulative energy and resource demand of industry is taking up a high share in relation to other sectors. For example, European statistical data shows that the energy consumption of the industry is more than one fourth of the overall energy consumption [1]. The worldwide demand for resources, such as oil and many metals (e.g. Platinum and Indium) is already projected to exceed raw material production in the near future [2]. Moreover, as production today is carried out in global supply chains, transport of raw materials, semifinished goods and final products add up to the overall energy demand and the associated environmental impact. Furthermore, environmental legislations and environmentally conscious customers extend a producer’s responsibility after manufacturing to the entire life cycle of a product comprising material sourcing, manufacturing processes, usage and end-of-life. Enterprises are in a challenging position where they have to satisfy these demands as well as sustain their economic viability and their product’s integrity. Thus, life cycle thinking is necessary as a design criterion to assist manufacturers in improving the environmental performance of their entire product life cycles. More and more it becomes crucial for a company to understand and influence the environmental impacts of their products throughout the whole life cycle. Thereby, the design of products is of major relevance. The decisions made in this phase determine not only an economic challenge but also the ecological performance of a product in all life cycle stages. Furthermore, life cycle thinking has to evaluate possible design solutions that are optimised only for a single life cycle stage whether they may lead to problem shifting instead of solving the problem. At the same time, not only product design but also

process design in the manufacturing supply chain and beyond is in the focus to optimise a product’s environmental performance. In this regards, a Screening Life Cycle Assessment (LCA) is a method which is widely used to provide initial results on the environmental impact of products throughout their life cycle [3][4][5]. AESCULAP AG, based in Tuttlingen, Germany, is a globally leading manufacturer of surgical instruments. The exemplary products of this study are surgical scissors used in a medical environment. The products are manufactured in a global supply chain of raw material sourcing and manufacturing operations until the distribution from Germany to worldwide customers. In general, two types of scissors can be distinguished. Reusable scissors are sterilised after each usage and periodically sharpened. This allows for multiple-use cycles over more than 10 years. Single-use instruments are shipped in a sterile packaging. They are meant for one-time usage, especially in environments, where re-sterilisation is unavailable, e.g. emergency ambulance, military and disaster aid. Due to a significant price difference, there is also a competition between single-use and multi-use products for regular hospital applications. Furthermore, brand products of surgical instruments are also challenged by competitor’s products from manufacturers in the Sialkot area in Pakistan. Most manufacturing steps are carried out there under often poor working conditions. Only the final steps are then carried out in Germany and the products are then marketed as “Made in Germany” at significantly lower costs despite their lower quality often [6]. Therefore, this paper presents the environmental impact assessment of the selected surgical scissors in a cradle-to-gate and cradle-to-grave screening LCA. The environmental preference of the three product alternatives was evaluated and identified environmental hot spots. Thus, the methodological approach is presented in the next section, followed by initial results of the study that follows the procedure of DIN ISO 14040 methodology. An environmental break even analysis of the three scissor types is also performed in relation to the functional unit in terms of use cycles. The assessments are concluded in the last section of the paper.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_108, © Springer-Verlag Berlin Heidelberg 2011

623

624 2

Life Cycle Assessment - Selected Applications METHODOLOGY

The Life Cycle Assessment (LCA) method is widely used to assess the environmental impact of a product life cycle. A Life Cycle Assessment according to ISO 14040:2006 is carried out in four basic steps, which are [7]: (1) Goal and scope definition; (2) Inventory analysis; (3) Life Cycle Impact Assessment (LCIA); (4) Interpretation. 

(1) Goal and scope definition: First, systems boundaries and intended application are set. Furthermore, the functional unit of the assessment is defined.



(2) Inventory analysis: In the second step, all material and energy flows along the processes of the product system are collected and quantified.



(3) Life Cycle Impact Assessment (LCIA): In the stage of the impact assessment, the contribution of the analysed material and energy flows to impact categories is calculated,



(4) Interpretation: This step contains the interpretation of the results and the derivation of decisions.

LCA result can be produced in different environmental impact categories which depend on the selection of the LCIA methods. Notably, the mid-point (problem-oriented) LCIA methods are distinguished from the end-point (damage-oriented) LCIA methods. The former assessment methods, such as the IPCC methods [8] quantify the environmental impacts in a number of impact categories, such as global warming potential and acidification etc. The contributions of different substances to the environmental impacts are converted to equivalents of a reference substance (e.g. CO2 equivalents for the greenhouse effect). The latter methods, such as the Eco-indicator 99 method, comprise a weighting of the different impact categories and aggregation to a single score indicator based on a damage model. Eco-indicator method presents a single score indicator which encompasses the full range of most established environmental impact categories, that estimated damage to resources, ecosystem quality and human health [9]. It is a practicable method and widely used, but it also bears the risk of concealing goal conflicts. IPCC method assesses the environmental impact in terms of greenhouse gas (GHG) emissions in a unit of kilogram of carbon dioxide equivalent (kg CO2eq). This method represents the quantities of GHG emissions which are well-known to a public audience including government sector such as the carbon related schemes. A screening LCA in accordance with the ISO 14040 methodology is used as an assessment tool. Screening LCAs substitute missing process data with assumptions derived from: existing databases; similar processes; and expert interviews etc. Thereby, the assumptions are used to provide initial results on the environmental impact of products throughout their life cycle.

The three selected competitive products are: 

a pair of single-use surgical scissors with model A1 from AESCULAP AG,



a pair of multi-use surgical scissors with model A2 from AESCULAP AG,



a pair of single-use surgical scissors with model B from competitor.

The cradle-to-gate assessment analysed the material provision, associated transportation and manufacturing process stages until the finished product was ready to be delivered to the customer from AESCULAP AG plant in Germany. The cradle-to-grave analysis additionally included distribution of the finished product to the customer, use phase and end-of-life processes. Therefore, a functional unit of the cradle-to-gate analysis for the three selected products was the manufacturing of one pair of surgical scissors, which includes raw material extraction, transportation and manufacturing to the finished product ready to be delivered to the customer. The cradle-to-grave analysis that was selected to present in this paper had a functional unit of 3,000 use cycles of surgical scissors used by a German customer during a service life of 12 years. Additionally, the influence of the customer location on the total results was analysed by calculating a second scenario for a customer located in the United States. In the full study, a functional unit of 4,500 use cycle of surgical scissors during a service life of 18 years was also assessed.

Raw material production

Raw material production

Transport of raw materials to a manufacturing plant

Transport of raw materials to a manufacturing plant

Making of 3,000 pairs of scissors incl. packaging

Making of 1 pair of scissors incl. packaging

Transport of scissors to AESCULAP AG

Transport of scissors to AESCULAP AG

Distribution of the scissors to a customer

Distribution of the scissors to a customer Repair (every 750 use cycles)

Use of the 3,000 scissors in 12 years

The procedure of the study in the next section follows the ISO 14040 methodology. Hence, the data and results are presented in four basics steps. 3 3.1

DATA AND RESULTS Goal and scope

Goal of this study is to compare the environmental impact of the selected surgical scissors in a cradle-to-gate and cradle-to-grave screening LCA.

Washing, disinfection and sterilisation

Use of the scissors (3,000 times in 12 years )

Transport of used scissors to a disposal / recycling site

Transport of used scissors to a recycling site

Disposal / recycling process of the used scissors

Recycling process of the used scissors

Single-use product

Multi-use product

Figure 1: Life cycles of the single-use and multi-use scissors.

Life Cycle Assessment - Selected Applications

625

Life Cycle stages

Model A1

Model A2

Model B

Surgical scissor types

Single-use

Multi-use

Single-use

Manufacturer

AESCULAP AG

AESCULAP AG

Competitor

Raw material: Types of core materials and supplier locations

Plastic

Steel

Steel

Europe and Asia 1

Europe and Asia 1

Europe and Pakistan

Road and water

Air, road and water

Air, road and water

Asia 1

Asia 1

Pakistan

Road and water

Air, road and water

Air, road and water

Cradle-to-gate of one pair

Cradle-to-gate of 3,000 pairs

Cradle-to-gate

Transportation: for moving raw materials from suppliers to the manufacturing plant Manufacturing process: Electricity consumption at the plant in different location Transportation: for moving the finished product back to AESCULAP AG

Cradle-to-grave Cradle-to-gate of 3,000 pairs

Material and manufacturing process: Transportation: for moving the purchased product from AESCULAP AG to a customer

Road transportation within Germany in a distance of 500 km  for 3,000 washing, disinfection, and sterilisation cycles;

Usage: Electricity and transportation involved until the product is disposed

End-of life: Road transportation and different disposal processes

 for 3 repair and service cycles 100% recycling for steel production scrap and 100% incineration for other materials

Most of steel is recycled and 100% incineration for other materials

100% recycling for steel and 100% incineration for other materials

Table 1: Input data summary of the three scissors. Inventory analysis

The life cycle of the three products are presented in Figure 1 and a summary of the input data for the analyses is listed in Table 1. The input was modified from AESCULAP AG data and literature. The life cycle inventory (LCI) data was gathered from different data sources from which the assumptions made for the study were derived. Sources comprised personal communications, data provided by AESCULAP AG and literature data. Ecoinvent 2.2 and Australian data 2007 databases [10] were employed for all processes as the main LCI databases. Process cases of the Ecoinvent 2.2 database can accommodate most of the activities involved in the life cycle of the three scissors. A number of new and modified process cases were created for unavailable process cases such as different sterilisation processes and electricity mixes. Therefore, the energy sources of the modified electricity cases were obtained from the IEA data source [11]. The steel recycling process was based on the Australian data 2007 database [10] which may not reflect an actual situation in those customer locations. However, the Australian 2007 database incorporates a better reflection on the benefits gained from material recovery, which was the reason for deriving the two steel recycling processes from it. 3.3

Impact assessment

The Life cycle Impact Assessment was carried out for analyses using the IPCC GWP100a version 1.07 (GWP) [8] and the Ecoindicator 99 H/A version 2.07 (EI’99) [9] methods from SimaPro 7.2.4 software [10]. These methods produced the GWP and the EI’99 single score results in units of kg CO2eq and points

respectively. In this section, the impact assessment results for the cradle-to-gate and the cradle-to-grave analyses are presented. Result representation is mostly normalised to the highest score to keep AESCULAP’s data confidential. The cradle-to-gate analysis compared one pair of each of the three scissor types. In this case, model A2 produces the highest GWP and EI’99 results which are more than one third higher than those of model B as depicted in Figure 2. While, model A1 has the lowest impacts which are approximately 90% less than model A2 results.

Eco-indicator 99 [%]

3.2

100 90 80 70 60 50 40 30 20 10 0

100 64 10 A1

A2

B

Surgical scissor model Figure 2: Overall Eco-indicator 99 results for the cradle-to-gate assessment of a pair of the three surgical scissors.

Life Cycle Assessment - Selected Applications

The differences of the results are largely due to the different environmental impacts from raw material acquisition and manufacturing per product as shown in Figure 3. The figure demonstrates the contribution to the overall environmental impact of 1) raw material extraction, 2) associated transportation and 3) manufacturing processes. For the metal products, transportation plays an inferior role, while raw material extraction shows considerable impact but it is clearly exceeded by the manufacturing processes such as metal forming. This pattern recurs for both observed indicators. In contrast, the contribution of the different life cycle stages is more evenly distributed in the case of the plastic product (A1). As its upstream chains and manufacturing processes are not that energy intensive, the ecological impact of transportation takes more effect.

GWP

100 90 80 70 60 50 40 30 20 10 0

100

21 A1

1.75 A2

B

Surgical scissor model

Figure 4: GWP results for the cradle-to-grave assessment of 3,000 pairs of models A1 and B, and 3,000 use cycles of a pair of model A2.

EI'99

100% 90%

Eco-indicator 99 [%]

Process chain analysis of cradle-to-gate results for one pair of scissors

Global Warming Potential [%]

626

80% 70% 60% 50% 40% 30%

100 90 80 70 60 50 40 30 20 10 0

100

17

0.95

A1

A2

B

Surgical scissor model

20%

Figure 5: Eco-indicator 99 results for the cradle-to-grave assessment of 3,000 pairs of models A1 and B, and 3,000 use cycles of a pair of model A2.

10% 0% A1

A2

B

A1

A2

B

Raw material extraction Associated transportation Manufacturing process

Figure 3: Cradle-to-gate process chain analysis for a pair of the three scissors. Consequently, the cradle-to-gate results are used as materials and manufacturing life cycle stages for the cradle-to-grave analysis as elaborated in Table 1. Cradle-to-grave results in units of kg CO2eq and points are illustrated in a series of bar charts as plotted in Figures 4 and 5. The results show the comparison between: 3,000 pairs of scissors model A1; one pair of scissors model A2 that is used for 3,000 cycles; and 3,000 pairs of scissors model B. Location of the customer is Germany for a service period of 12 years. A clear conclusion can be drawn from the results presented in Figures 4 and 5. The overall cradle-to-grave environmental impact of the scissors model B is the highest followed by model A1 and model A2. This conclusion is valid throughout both considered evaluation methods, GWP and EI’99. The results of the Pakistani scissors, model B are significantly higher than those of the scissors model A1 and A2 in a range of 5 to 6 and 57 to 105 times respectively.

The dominant contributions to the environmental impacts of the single use scissors, A1 and B, are caused by the high consumption of plastics and steel. Moreover, the high energy consumption during the raw material extraction and the manufacturing processes also influence those results. Whereby, a pair of multi-use scissors, model A2 has the highest contributor at the usage stage as illustrated in Figure 6. At this stage, scissors model A2 need to be washed, disinfected and sterilised for 3,000 times and they also require to be repaired three times. As shown in Table 1, the first three processes consume electricity, whereas the repairing process involves with transportation and electricity consumption. In the end-of-life stage, the environmental impact is caused by different disposal options. According to Table 1, the predominant disposal options are the assumptions of 100% recycling for steel and 100% incineration for other materials including plastics. As a result, the cradle-to-grave results of 3,000 pairs of scissors model A1 in Figure 6 have high contributions in the end-of-life stage. This is due to the fact that the scissors are mainly made of plastics which are mainly incinerated. On the other hand, a pair of the scissors model A2 and 3,000 pairs of scissors model B are mainly made from steel. Therefore, their environmental impacts at the end-of-life stage are significantly less than the scissors model A1 results. This is because of the benefits of material recovery are gained from the 100% steel recycling assumption.

Life Cycle Assessment - Selected Applications

GWP

100%

3.4

EI'99

To analyse the robustness of the study, Eco-indicator 99 mid-point results have been checked for goal conflicts of the different impact categories. None could be detected. Additionally, sensitivity analyses of probable influential assumptions and choices showed that, the overall results and the ranking of the three scissors are reliable.

90% 80% 70%

To derive recommendations, an environmental break-even analysis was conducted which is represented in Figure 8 on the example of EI’99 results. Y-axis intercepts show again that the supply of one pair of reusable scissors model A2 has the highest impact on the environment among the three investigated scissor models. In general, lines A1 and B have much steeper slope than that of the line A2 as can be observed in Figure 8. These differences of the slope level indicate that the environmental impact of those two single-use products per use cycle is explicitly higher than that of the model A2 scissors.

60% 50% 40% 30% 20% 10% 0% A1

A2

B

Cradle-to-Gate

A1 Usage

A2

B

End-of-Life

Figure 6: Process chain analysis of the cradle-to-grave results for 3,000 use cycles. The question arises, whether the location of the final customer impacts the cradle-to-grave environmental impacts of the surgical scissors. Figure 7 presents the GWP results of the cradle-to-grave analysis for a pair of the multi-use scissors, model A2 that are used by a customer in Germany and the United States. As it can be seen, the amount of the GHG emissions for the scissors, model A2 are 8 % higher when they are used in the United States. This is largely due to the fact that the distribution of the product for the American customer requires air freight over approximately 10,000 km, whereas road transportation is used in the German customer case as stated in Table 1.

Global Warming Potential [%]

Moreover, although both countries use similar percentage of coal to generate their electricity, German electricity is produced from higher wind power and less percentage of natural gas. 110 100 90 80 70 60 50 40 30 20 10 0

Interpretation

Intersections indicate the break-even points. From this number of cycles onwards, the initially higher environmental impact of the reusable product (A2) is compensated by the continuous environmental impact for the supply of single use scissors. Its multiple usage means an advantage for the environment compared to the use of multiple single-use products. Figure 8 shows that A2 is environmentally advantageous in comparison with the competitor product manufactured in Pakistan (B) as soon as it is used for a second time.

Eco-indicator 99

Process chain analysis of cradle-to-grave results for 3,000 use cycles

627

1

2

3

4

5

6

7

8

9

10

11

12

Number of use cycles A1

A2

B

Figure 8: Environmental break-even analysis of the Eco-Indicator 99 results and the number of use cycles for the three scissors. 100

108

Germany

United States

Customer location

Figure 7: GWP results for the cradle-to-grave assessment of the 3,000 use cycles of a pair of model A2 that used in different customer locations.

When the reusable product is used more than 11 times, its environmental performance also exceeds those of AESCULAP’s plastic product A1. The impact of repair cycles and end-of-life processes of the reusable product is of minor influence. It just causes minimal steps in the A2 line and does not affect the breakeven results at all. Based on the assumption of 250 use cycles per year, this means that right after three weeks of use, the scissors model A2 outclasses the single-use products from an environmental point of view. Therefore, the assumption of 3,000 use cycles until the endof-life for the scissors model A2 has no effect on the main results of the LCA study. It highlights only the possible magnitude of the environmental benefits from using the scissors model A2.

628

4

Life Cycle Assessment - Selected Applications

CONCLUSION

In this paper, the environmental assessment of one multi-use, one single-use model of surgical scissors from AESCULAP AG and a single-use competitor product made in Sialkot area, Pakistan was presented. IPCC GWP 100 and EI’99 methods were chosen for the cradle-to-gate and cradle-to-grave analyses. The cradle-to-gate analysis referred to one pair of scissors as functional unit, while the cradle-to-grave analysis related to the life cycles of according numbers of scissors for 3,000 use cycle during a 12 year service period. Key findings of the assessments have been drawn as follows. The screening LCA revealed that the multi-use scissors (model A2) produce far less environmental impact than the single-use scissors. The single-use plastic scissors from AESCULAP AG can reduce the environmental impact by approximately 80% in lieu of the singleuse metal scissors (model B). High contributions of the cradle-tograve results for the single-use scissors (models A1 and B) are constituted predominantly by the material and manufacturing stages. Consequently, a hot spot analysis should indicate improvement potentials of energy and resource consumption to lower the associated environmental impacts. Whereas, contributions of the cradle-to-grave results for the multiple-use scissors (A2) are mainly governed by the electricity consumption associated with the sterilisation process during the usage stage. Environmental breakeven analysis revealed that after 2 and 11 use cycles, the higher cradle-to-gate environmental impact of the reusable product (model A2) is compensated when compared with the Pakistani product (model B) and the plastic scissors (model A1) respectively. Despite the fact that single-use scissors are especially intended for usage under special conditions (e.g. disaster aid, military etc.), they also represent a competitor product for regular hospital applications due to their significantly lower price. Further work can be continued for this research by focusing on the optimisation between the Life Cycle Cost and delivery time involve with the environmental performance of the products. 5

ACKNOWLEDGMENTS

The study was carried out by the Joint German-Australian Research Group “Sustainable Manufacturing and Life Cycle Management” in collaboration with AESCULAP AG. The authors would like to thank all colleagues from AESCULAP AG who contributed to this study. 6

REFERENCES

[1]

Eurostat (2009): Final Energy Consumption, by Sector, online source, http://epp.eurostat.ec.europa.eu/tgm/refreshTableAction. do?tab=table&plugin=1&init=1&pcode=tsdpc320&langua ge=en, access date: 10/11/2010.

[2]

Angerer, G., Marscheider-Weidemann, F., Lüllmann, A., Erdmann, L. et al. (2009): Rohstoffe für Zukunftstechnologien - Einfluss des Branchenspezifischen Rohstoffbedarfs in Rohstoffintensiven Zukunftstechnologien auf die Zukünftige Rohstoffnachfrage. 2. ed., Stuttgart: Fraunhofer IRB Verlag.

[3]

Christiansen K, de Beaufort-Langeveld A, van den Berg N, Haydock R, ten Houten M, Kotaji S, Oerlemans, E., Schmidt, W.-P., Weidenhaupt, A., White, R. (1997): Simplifying LCA: Just a Cut? Final report SETAC-Europe LCA Screening and Streamlining Working Group, SETAC-Europe, Brussels.

[4]

Bretz, R., Frankhauser, P. (1996): Screening LCA for Large Numbers of Products Estimation Tools to Fill Data Gaps,

International Journal of Life Cycle Assessment, Vol. 1, No. 3, pp. 139-146. [5]

Rebitzera, G., Buxmannb, K. (2005): The Role and Implementation of LCA within Life Cycle Management at Alcan, Journal of Cleaner Production, Vol. 13, Iss. 13-14, pp. 1327-1335.

[6]

Bhutta, M. F. (2006): Fair Trade for Surgical Instruments BMJ,.

[7]

ISO 14040:2006 (2006): Environmental Management -- Life Cycle Assessment -- Principles and Framework.

[8]

Houghton, J., T., Ding, Y., Griggs, D., J., Noguer, M., van der Linden, P., J., Dai, X., Maskell, K., Johnson, C., A. (2001): Climate Change 2001: The Scientific Basis, Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom.

[9]

Goedkoop, M.; Spriensma, R. (2001): The Eco-indicator 99 A damage oriented method for Life Cycle Impact Assessment, 3. ed., Publikatiereeks Produktenbeleid 1999/36A, Ministerie van Volkshuisvesting, Ruimtelijke Ordening en Milieubeheer; PRé Consultants B.V., Amersfoort.

[10] PRe Consultants BV. (2008): SimaPro 7 User's Manual, the Netherlands. [11] www.iea.org/stats/index.asp, access date: 10/11/2010.

Comparative Carbon Footprint Assessment of Door made from Recycled Wood Waste versus Virgin Hardwood: Case Study of a Singapore Wood Waste Recycling Plant 1

1

1

1

1

Ruisheng Ng , Chee Wai Patrick Shi , Jonathan Sze Choong Low , Hui Mien Lee , Bin Song 1

Singapore Institute of Manufacturing Technology

Abstract Recycling of wood waste has the benefits of reducing waste stream and avoiding the need (avoided impact) of harvesting virgin wood. To justify these benefits, a carbon footprint assessment methodology is proposed to compare the carbon emissions of a door made from recycled wood waste (technical wood) versus virgin hardwood. Results show that technical wood door has lower carbon emissions of 12.8 kg-CO2eq compared to virgin hardwood door (16.2 kgCO2eq). When avoided impact is taken into account, technical wood door carbon emissions may even be lower (-2.9 kgCO2eq). This assessment also identifies the ‘hotspots’ for future carbon emissions improvement. Keywords: Carbon Footprint Assessment; Recycled Wood Waste; Avoided Impact

1

INTRODUCTION

According to Singapore Key Environmental Statistics in 2009, the generation of wood and timber waste is approximately 0.27 million tonnes per annum. There are several wood waste treatment options. Landfilling of wood waste is not the best option for a landscarce country like Singapore. Incineration is one of the most effective ways of treating wood waste but combustion of wood waste releases about 1.28 tonnes of carbon dioxide per tonne of wood waste [1]. A better option may be to recycle wood waste, especially for a resource-poor country like Singapore. This will allow Singapore to be less reliant on foreign import of wood resource. Another benefit of recycling wood waste is that it avoids the need (avoided impact) of harvesting trees for virgin wood. If trees are not felled, they can continue to sequester and store carbon dioxide from the atmosphere through photosynthesis. Furthermore, recycling wood waste delays the release of carbon dioxide stored within the wood. To justify the benefits of recycling wood waste, a case study is carried out on a Singapore wood waste recycling plant (LHT Holdings Limited) to compare the carbon footprint of a door made from two different materials: recycled wood waste (technical wood) and virgin hardwood. Technical wood refers to the end-product from the recycling of wood waste and virgin hardwood refers to Kapur or Nyatoh, tree types commonly found in Southeast Asia. To carry out the comparative assessment, carbon footprint is chosen as the metric for comparison due to its relevance in quantifying the carbon storage and also its importance in global warming impact. Here, carbon footprint refers to the six greenhouse gas (GHG) emissions consisting of CO2, CH4, N2O, SF6, HFC and PFC and is expressed in weight of carbon dioxide equivalents (CO2eq), e.g. kg-CO2eq. Carbon footprint has also been commonly referred to as carbon emissions. In this paper, carbon footprint assessment refers to the quantification of carbon emissions. The results from the assessment are expressed in term of carbon emissions (kg-CO2eq).

2

METHODOLOGY FOR FOOTPRINT ASSESSMENT

COMPARATIVE

CARBON

The carbon footprint assessment methodology follows closely the principles and framework set out by two standards: ISO14040/44 [2] and PAS 2050 [3]. The ISO 14040/44 is a de facto standard for carrying out Life Cycle Assessment (LCA) that quantifies the environmental impacts. On the other hand, PAS 2050 focuses on carbon emissions quantification. Both standards share great similarities but distinct differences still exist. To best fit the case study, specific elements from both standards and also literatures [4, 5, 6] such as carbon storage quantification and avoided emissions are modified and adapted. 2.1

Goal Definition and Scope

Purpose To assess, quantify and compare the carbon emissions of recycled wood waste (technical wood) with virgin hardwood in the application of wooden door using comparative carbon footprint assessment methodology. Functional Unit The functional unit for the comparative study of the door is: One unit of standard size (2200 mm by 830 mm) door that has a product lifespan of 10 years System Boundaries for Comparative Study of the Door System boundary covers the activities included in the assessment. For a comparative carbon footprint assessment, both system boundaries cover the same life cycle stages that span from cradle to end-of-use. The life cycle stages include raw material acquisition and processing (cradle), door production and usage. The difference within the two system boundaries lies in the specific process activities shown in the boxes. Door knob, hinges, laminate and paint on door are excluded from the study. Figures 1 and 2 show the system boundaries for a virgin hardwood door and technical wood door respectively.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_109, © Springer-Verlag Berlin Heidelberg 2011

629

630

Life Cycle Assessment - Selected Applications Cradle

Production

Usage

Door Manufacturing

Door Usage

carbon emissions due to carbon storage. Equations 2 and 3 show the carbon storage quantification method.

Kiln-drying

Harvesting and Milling

Impregnation Transportation of Lumber

CEcs  ADcs  WFcs  EFcs 

(2)

Where:

Heat Treatment

CECS is the Carbon Emissions of carbon storage

Figure 1: System boundary for virgin hardwood door.

ADCS is the Activity Data of carbon storage EFCS is the Emission Factor of carbon storage

Cradle Collection of Wood Waste

Drying of Wood Chips

Shredding of Wood Waste

Pressing of Wood Chips and Resin

Metal Separation and Hammering

Production of Resin

Production

Usage

Door Manufacturing

Door Usage

WFCS is the weighting factor due to carbon storage and it is defined as:

WFcs =

0.76 × t o 100

(3)

Where: to is the number of years the full carbon storage benefit of a product exists following the formation of the product.

Figure 2: System boundary for technical wood door.

Avoided Impact

Data Collection and Data Quality Data collection involves surveys and questionnaires, site visits to LHT production plants, interviews with LHT representatives and domain experts. Data collected this way are considered to be primary data as they are case-specific. In the absence of primary data, secondary data and derived data are used instead [3]. Secondary data include databases from commercial LCA software (e.g. GaBi 4.3 and SimaPro 7.1), publicly available databases and literatures. The derived data are obtained from calculations and modelling from a combination of data sources. The sources include primary and secondary data. Reasonable estimates and assumptions based on engineering principles are made in the calculations. As far as possible, the data used in the carbon footprint assessment are geographically, temporally and technologically relevant. 2.2

Carbon Footprint Calculation

There are two types of variables, namely activity data and emission factors, used in carbon footprint calculation [3]. Activity data refer to a quantitative measure of an activity. This includes the amount of material produced, energy required for processing, fuel consumed during transportation etc. Emission factor refers to a coefficient that quantifies the carbon emissions or removal of a gas per unit activity. Emission factors are often based on a sample of measurement data, averaged to develop a representative rate of emission for a given activity level under a given set of operating conditions. Equation 1 shows the carbon footprint calculation.

CE=

∑(AD

i

× EFi )

(1)

Where: CE is Carbon Emissions

There is general consensus that recycling wood waste displaces the activities and associated emissions that otherwise would have occurred [4, 5, 6]. This avoidance is termed as avoided emissions. There is some degree of uncertainty in this concept. Also, there is currently no widely accepted standard approach to include forest carbon impacts in the carbon footprints of forest products, as pointed out in a critical review statement in [6]. As such, quantifying avoided emissions in such manner is only scenario-based and not to be taken as absolute avoided emissions that will occur. Hence, it is proposed in this paper to quantify the avoided emissions in a reasonable and conservative manner. The terminology used in the proposed approach is avoided impact instead of avoided emissions. This distinction is because the avoided impact considers only the amount of carbon stored in non-harvested trees that would have occurred as a result of recycling. Unlike the cases in [4, 5, 6], the proposed approach did not include all activities and associated emissions that would have been displaced by recycling. Furthermore, the effect of avoided impact is reduced when the amount of carbon stored is multiplied by a weighting factor (Equation 4) that will always be equal or less than one. This approach is reasonable and conservative because only the benefit of delayed emissions due to carbon stored in non-harvested trees is reported instead of “full benefits”. To quantify the avoided impact, Equation 2 is used except that the weighting factor is changed to Equation 4. Although the weighting factor in Equation 4 refers to the calculation of the weighted average impact of carbon storage in products [3], it is assumed that this weighting factor applies to carbon storage in tree as well. The rationale for assigning a heavier weighting factor is because a tree that is not felled can store carbon as well as absorb carbon dioxide from the atmosphere. This delays the release of stored carbon and reduces carbon emissions from the atmosphere at the same time. 100

ADi is Activity Data for ith activity EFi is Emission Factor for ith activity

∑X

2.3

i 1

Carbon Storage and Avoided Impact Quantification

Carbon Storage The benefit of carbon storage can be attributed to a product that exists for between 2 and 25 years after its formation [3]. The rationale of giving credit to storing carbon in product is because carbon emissions are delayed from emitting to the atmosphere. To quantify the benefit of storing carbon, a weighting factor from [3] is used to multiply the emission factor and a negative sign is assigned to the emission factor. The negative sign indicates a reduction in

WFAI 

i

100

(4)

Where: i is each year in which carbon storage occurs X is the proportion of total storage remaining in any year i WFAI is the weighting factor due to avoided impact It could be argued that the same amount of carbon stored in nonharvested tree would eventually be transferred to virgin hardwood

Life Cycle Assessment - Selected Applications

631

Activity Data

Unit

Harvesting and Milling

800

kg/m

Transportation of Lumber Kiln-Drying Total

440 4

ton-km kWh

Activity

Emission Factor (kg-CO2eq/ unit of activity data)

Emissions (kg-CO2eq/ 3 m of timber)

0.087

69.924

Primary; [7, 8]

0.134 0.576

58.953 2.304 131.181

Primary; Calculations Primary

3

Data Sources Activity Data

Emission Factor [9, 10, 11, 12, 13]; Calculations ELCD/PE-Gabi [14]

Table 1: Life cycle inventory per cubic metre of virgin hardwood timber. Activity Virgin Hardwood

Activity Data

Unit

0.053

m

3

Emission Factor (kg-CO2eq/ unit of activity data) 131.181

Emissions (kg-CO2eq/ 3 m of door) 6.904

Data Sources Activity Data

Emission Factor

Primary

Table 1 IDEMAT, Ecoinvent/SimaPro [14] [14] [14] [17]; Calculations

Fire Retardant

0.158

kg

0.048

0.008

[15, 16]

Impregnation Heat Treatment Door Manufacturing Carbon Storage Total

0.532 0.211 20 0.026

kWh kWh kWh 3 m

0.576 0.576 0.576 -99.527

0.306 0.121 11.519 -2.619 16.239

Ecoinvent/SimaPro [15, 16] Primary Primary

Table 2: Life cycle inventory per functional unit of virgin hardwood door. product, hence creating a double-counting effect. However, this double-counting effect is eliminated if business-as-usual scenario is assumed. Business-as-usual scenario refers to the case where the same amount of raw material (either virgin hardwood or wood waste) is used to produce the same volume of output. 3

RESULTS OF ASSESSMENT

COMPARATIVE

CARBON

FOOTPRINT

The results of the comparative carbon footprint are shown in the Life Cycle Inventory (LCI). The LCI catalogues the activities, activity data, emission factors and computed carbon emissions per functional unit. 3.1

Life Cycle Inventory for Virgin Hardwood Door

Virgin Hardwood Timber The types of virgin hardwood used and operational data are estimated by LHT and domain experts based on previous experiences in production of virgin hardwood and technical wood door. Typically, hardwood (Kapur and Nyatoh) [7, 8] is used to make virgin hardwood door. The virgin hardwood is harvested and milled in Pahang, Malaysia and transported to LHT in Singapore. 3 The average density of Kapur is 800 kg/m at a moisture content of 12% [7] whereas the density for Nyatoh ranges from 400 to 1075 3 kg/m (air dry) [8]. To be comparable with technical hardwood door, it is assumed that the average density of virgin hardwood to be 800 3 kg/m (moisture content of 12%). The average moisture content of the virgin hardwood lumber upon arrival is 40% and is kiln-dried in LHT to an average moisture content of 15%. Table 1 shows the LCI of processing one cubic metre of virgin hardwood timber prior to door production. The amount of carbon emissions for processing one cubic metre of virgin hardwood timber is 131.2 kg-CO2eq. Virgin Hardwood Door The required amount of wood required based on the dimensions of 3 the standard size (2200 mm by 830 mm) door is 0.026 m . A fire retardant chemical is used in the impregnation process to infuse fire retardant properties into the virgin hardwood timber. Information about the chemical composition is limited, however it is known that boric acid is the main active ingredient. Therefore, the emissions from the production of fire retardant will be based on the production of boric acid. Heat treatment follows after impregnation process to dry the virgin hardwood timber. The heat-treated virgin hardwood timber is then manufactured into virgin hardwood door. The amount

of waste generated from the door manufacturing is 50% which is due to engineering scrap. As such, 50% more virgin hardwood timber, fire retardant and energy consumption for impregnation and heat-treatment processes are required. The benefit of carbon storage is credited to the virgin hardwood door based on the computation method in section 2.3. The lifespan of the door is assumed to be 10 years during usage phase as stated in the functional unit. Table 2 shows the LCI of virgin hardwood door. The amount of carbon emissions for one functional unit of virgin hardwood door is 16.2 kg-CO2eq. 3.2

Life Cycle Inventory for Technical Wood Door

Technical Wood Timber Technical wood timber is made from wood waste collected by LHT in Singapore. Wood waste is shredded, hammered and dried to produce wood chips. The amount of wood chips determines the density of the technical wood timber. To produce a technical wood door of desired mechanical strength and property, a density of is 3 840 kg/m with a final moisture content of 8% is required. Approximately 90% of the volume of technical wood consists of wood chips while the resin makes up the rest of the 10%. The resin is a mixture of melamine-urea-formaldehyde (65% by volume) and water. The wood chips are mixed with resin before they are pressed to mould into technical wood. High pressure and temperature steaming process follows next to make technical wood resistant to pest and fungus. Table 3 lists the LCI of processing one cubic metre of technical wood timber prior to door production. The amount of carbon emissions for processing one cubic metre of 3 technical wood timber (of density 840 kg/m ) is 143.3 kg-CO2eq. Technical Wood Door Technical wood is resistant to water, fire, pest and fungus. Hence it does not require impregnation and post-heat treatment processes. Another advantage of Technical wood is that it can be moulded into the near-net shape segments required for door manufacturing. As a result, the amount of waste is greatly reduced to 3% and the 3 required amount of technical wood timber is 0.027 m . The consideration of carbon storage is also credited to the technical wood door, similar to the case in virgin hardwood door. Further to that, there is also benefit of avoided impact as stated in section 2.3. The LCI of technical wood is listed in Table 4. The total amount of carbon emissions for one functional unit of technical wood door

632

Life Cycle Assessment - Selected Applications

Activity Collection of Wood Waste Shredding, Metal Separation and Hammering, Drying, Pressing, and Steaming Production of Resin Total

Data Sources Emission Activity Data Factor Primary, ELCD/PECalculations Gabi

Activity Data

Unit

Emission Factor (kg-CO2eq/ unit of activity data)

Emissions (kg-CO2eq/ 3 m of timber)

14.743

ton-km

0.134

1.976

240

kWh

0.274

65.798

Primary

[18, 19]; Calculations

46.8

kg

1.614

75.521 143.294

Primary

[20]

Table 3: Life cycle inventory per cubic metre of technical wood timber. Activity

Activity Data

Technical Wood Door Manufacturing Carbon Storage Avoided Impact Total

0.027 20 0.026 0.120

Emissions Emission Factor Data Sources (kg-CO2eq/ (kg-CO2eq/ Activity Data Emission Factor 3 unit of activity data) m of door) 3 m 143.294 3.888 Primary Table 3 kWh 0.576 11.519 Primary [14] 3 m -97.821 -2.574 Primary [17]; Calculations 3 m -130.957 -15.772 Calculations [17]; Calculations -2.940 Unit

Table 4: Life cycle inventory per functional unit of technical wood door. is -2.9 kg-CO2eq. Reader should note that the production of technical wood door does not result in reduction of emissions by 2.9 kg-CO2eq. The negative emissions is the potential reduction of emissions by technical wood door that is relative to the scenario of producing virgin hardwood door after taking the avoided impact into account. Without making comparison with the virgin hardwood door, the emissions due to the production of technical wood door will be 12.8 kg-CO2eq. Figure 3 compares the carbon emissions of virgin hardwood door and technical wood door, with and without avoided impact. kg-CO2eq 20.0

amount of upstream milling waste, engineering scrap etc. A benefit of conducting carbon footprint assessment is that it can carry out “hotspots” analysis to understand the significance of contributing factors. The carbon emissions contributing factors for both virgin hardwood and technical wood doors are shown in Figures 4 and 5. 60%

40%

10%

16.2 12.8

1.43%

0.04%

0.56%

0%

10.0

-10%

5.0

-20%

-12.20% Virgin Fire Door Impregnation Heat Hardwood Retardant Manuf acturing Treatment Timber

0.0 -5.0

-2.9 Virgin Hardwood Door Technical Wood Door Technical Wood Door (No Avoided Impact) (with Avoided Impact)

Figure 3: Carbon emissions of virgin hardwood door and technical wood door, with and without avoided impact. DISCUSSIONS

Carbon Storage Benef it

Figure 4: Carbon emissions distribution per functional unit of virgin hardwood door. 40%

34.13%

30% 20% 10%

11.52%

0%

Hotspots Analysis for Virgin Hardwood and Technical Wood Doors

-10%

The amount of carbon emissions for producing one cubic metre of technical wood timber is 143.3 kg-CO2eq. This is approximately 9.2% higher than one cubic metre of virgin hardwood timber (131.2 kg-CO2eq). Although technical wood timber has relatively higher emissions compared to virgin hardwood timber, the cradle to endof-use carbon emissions of technical wood door (-2.9 kg-CO2eq) are about 1.2 times lower than virgin hardwood door (16.2 kgCO2eq), after taking the avoided impact into account. Without considering avoided impact, the carbon emissions of technical wood are 12.8 kg-CO2eq which are still about 21% lower than virgin hardwood door. Care should be taken when interpreting the negative emissions of technical wood door. The avoided impact can only be attributed to the technical wood door as it is making a relative comparison with virgin hardwood door in the current study. If the technical wood door is compared to other types of wood, the avoided impact will be different due to various factors, such as the

-30%

4.1

32.15%

30% 20%

15.0

4

53.63%

50%

-7.63%

-20% -40% -50%

-46.73%

-60% Technical Wood Timber

Door Manuf acturing

Carbon Storage Benef it

Avoided Impact

Figure 5: Carbon emissions distribution per functional unit of technical wood door. From Figure 5, avoided impact contributes 46.73% of the total emissions. It is assigned as negative emissions because it reduces carbon emissions of technical wood door when compared to virgin hardwood door. Since technical wood door makes use of wood waste to make door, it avoids harvesting virgin hardwood (avoided 3 impact), in this case 0.12 m of Kapur/Nyatoh Tree. This volume 3 (0.12 m ) of Kapur/Nyatoh tree, if not harvested, will absorb carbon

Life Cycle Assessment - Selected Applications

633

dioxide and store it as carbon for 10 years. There are two factors that result in virgin hardwood door using greater amount of wood 3 volume (0.12 m ). Firstly, a large amount of waste is generated during the upstream milling of harvested logs into planed timber. According to [12], only 43.7% of log is converted into planed timber. 3 For that reason, approximately 2.3 m of logs is required to produce one cubic metre of planed timber. Secondly, about 50% engineering scrap is created during door production unlike the case of technical wood door which is only 3%. As a result, 50% more virgin hardwood timber, fire retardant, energy consumption for impregnation and heat-treatment processes are required. This 50% of additional virgin hardwood timber contributes to the 32.15% of carbon emissions for virgin hardwood door. It partly explains why virgin hardwood door has higher carbon emissions than technical wood door although virgin hardwood timber carbon emissions are 8.4% lower than technical wood timber on a per cubic metre basis. Another major contributor of carbon emissions in both cases is the energy required in door manufacturing. The energy required for the door production contributes 53.63% of carbon emissions for virgin hardwood door and 34.13% of carbon emissions for technical wood door. In absolute terms, both cases require the same amount of energy. However, virgin hardwood door actually requires higher amount of energy as there are more trimming and sawing processes compared to technical wood door manufacturing. Due to limited data and on a conservative side, it is assumed that virgin hardwood door manufacturing consumes the same energy as technical wood door manufacturing. This area can be further explored in future work. 4.2

Hotspots Analysis for Virgin Hardwood and Technical Wood Timber

Figure 6 reveals that 44.94% of carbon emissions per cubic metre of virgin hardwood timber are contributed by transportation of lumber (virgin hardwood) from Pahang, Malaysia to LHT, Singapore. On the other hand, the transportation (collection) of wood waste merely contributes less than 2% (Figure 6) of carbon emissions per cubic metre of technical wood timber. In absolute terms, the transportation carbon emissions for technical wood timber are 1.9 kg-CO2eq whereas virgin hardwood timber has 58.9 kg-CO2eq. Hence, recycling wood waste actually reduces reliance of resource imports and cuts down carbon emissions of resource imports due to long haul transportation. 60%

53.30%

50%

44.40%

40% 30%

60%

52.70% 45.92%

50% 40% 30% 20% 10% 1.38%

0% Resin

Collection of Wood Waste

Recycling

Figure 7: Carbon emissions distribution per cubic metre of technical wood timber. Although technical wood door has lower carbon emissions than virgin hardwood door, there may be still rooms for improvement. As shown in Figure 7, the main contributors of carbon emission for technical wood timber are resin and recycling process (including shredding, metal separation and hammering, drying, pressing and steaming). Table 5 shows a list of resin alternatives and the respective potential reductions in carbon emissions.

Types of Resin MUF (Baseline) MUF-1241 UF-1205 UF-1206

Emissions (kg3 CO2eq/m )

% Change

Emissions (kgCO2eq/door)

143.294

Base

12.832

Base

134.416 133.504 135.142

-6.20% -6.83% -5.69%

12.591 12.567 12.611

-1.88% -2.07% -1.72%

% Change

Table 5: Potential reductions in carbon emissions of technical wood door by choosing resin alternatives. The types of resin shown in Table 5 are Casco Products from Sweden and their emission factors are from [21, 22]. Resin UF1205 shows the biggest reduction potential of 6.83% per cubic metre of technical wood timber but only 2.07% in the door. However, an in-depth study will be required to assess whether there are technical feasibility issues of bonding strength by replacing the current resin with alternatives. For the case of recycling energy consumption, LHT was not able to give a detailed breakdown of the energy used in sub-processes. Nevertheless, a sensitivity analysis (Table 6) is carried out to show the potential reduction of carbon emissions by reducing the energy consumption in recycling process. From Table 6, it shows that for every 5% reduction in energy consumption, there is a potential of 2.3% reduction in carbon emissions per cubic metre of technical wood timber and 0.7% reduction in door.

20% 10%

1.76%

Energy Reduction

Kiln-drying

Baseline 5% 10% 15% 20%

0% Harvesting and Milling Wood

Transportation of Lumber

Figure 6: Carbon emissions distribution per cubic metre of virgin hardwood timber. Another major contributor of carbon emissions in virgin hardwood timber is harvesting and milling. Carbon emissions are calculated by modifying activity data in [9, 12] and emission factors in [10, 11, 13]. It is assumed that the operational data in [9, 12] are similar to the harvesting and milling operations in Malaysia. As explained earlier in section 4.1, a large amount of waste is generated during the upstream milling of harvested logs into planed timber.

Emissions (kg-CO2eq/ 3 m) 143.294 140.004 136.714 133.425 130.135

% Change Base -2.30% -4.59% -6.89% -9.18%

Emissions (kg-CO2eq/ door) 12.832 12.743 12.654 12.564 12.475

% Change Base -0.70% -1.39% -2.09% -2.78%

Table 6: Potential reductions in carbon emissions of technical wood door by reducing energy in recycling process. In both cases, choosing resin alternatives and reducing energy consumption reduce carbon emissions of technical wood timber by a much bigger margin than technical wood door. This is because the contribution of technical wood timber to the door is only 11.52% (Figure 5). However, there may be higher reduction potential for

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other technical wood-based products that have higher percentage of carbon emissions due to technical wood timber.

[3]

British Standard (2008): Publicly Available Specification – Specification for the assessment of the life cycle greenhouse gas emissions of goods and services.

5

[4]

U.S. Environmental Protection Agency (2007): Forest Carbon Storage in EPA’s Waste Reduction Model.

[5]

Eriksson, E., Karlsson, P-E., Hallberg, L., Jelse, K. (2010): Carbon Footprint of Cartons in Europe – Carbon Footprint methodology and biogenic carbon sequestration.

[6]

Miner, R. (2010): Impact of the global forest industry on atmospheric greenhouse gases, in Food and Agriculture Organisation of the United Nations, Rome, Italy.

[7]

Hopewell, G. (2010): Information of Kapur, available in http://www.dpi.qld.gov.au/26_5423.htm. Last accessed 10 November 2010.

[8]

Gan, K. S., Choo, K. T., Lim S. C. (1999): Timber Notes – Light Hardwoods (Mersawa, Nyatoh, Pelajau, Penarahan, Perupok), Timber Technology Bulletin, No. 15.

Hotspots analysis reveals that the main contributing factors of virgin hardwood door having higher carbon emissions are the following:

[9]

McCallum, D (2009): Report on Carbon Footprint Project Nelson Forest.



High engineering scrap (50% waste) during door manufacturing

[10]



High energy consumption required for door manufacturing



Low harvested log to planed timber conversion rate (43.7%) in the upstream harvesting and milling

Ministry for the Environment New Zealand (2006): Fuel combustion emission factors (transport fuels), available in http://www.mfe.govt.nz/publications/climate/guidancegreenhouse-gas-reporting-apr08/html/page3.html. Last accessed 10 November 2009.



Long distance transportation of virgin hardwood lumber from Pahang, Malaysia to Singapore

[11]

U.S. Department of Energy, Energy Information Administration (2009): Fuel Emission Factors from Appendix H of the instructions to Form EIA-1605.

[12]

Bergman, R. D., (2008): Environmental Impact of Producing Hardwood Lumber using Life-Cycle Inventory, Wood and Fiber Science, 40 (3), pp 448-458.

CONCLUSIONS AND FUTURE WORK

To justify the benefits of recycling wood waste, a case study was carried out on a Singapore wood waste recycling plant (LHT) to compare the carbon footprint of a door made from two different materials: recycled wood waste (technical wood) and virgin hardwood. A carbon footprint assessment methodology is proposed to compare the carbon emissions of a door made from recycled wood waste (technical wood) versus virgin hardwood. Results show that technical wood door carbon emissions of 12.8 kg-CO2eq are 21% lower than virgin hardwood door (16.2 kg-CO2eq). When avoided impact is taken into account, technical wood door carbon emissions may even be lower (-2.9 kg-CO2eq) by 1.2 times. Avoided impact is credited to technical wood door as recycling wood waste avoids the need (avoided impact) of harvesting trees for virgin hardwood and delays the release of carbon emissions.

Although technical wood door has lower carbon emissions than virgin hardwood door, hotspots analysis may identify rooms for improvement. The main contributing factors of technical wood door carbon emissions are the following: 

High energy consumption required for door manufacturing

[13]

Malaysian Grid Emission Factor Calculation (2008).



High energy consumption required for wood waste recycling to technical wood

[14]



High emission factor of production of resin for bonding wood chips

National Environment Agency (2009): Information on Emission Factors (For CDM projects in Singapore) in http://www.nccc.gov.sg/informationOnEmissionFactors.p df. Last assessed 10 November 2010.

[15]

Arch Timber Protection (2008): Fire Retardant Coating for Timber Based Product, Specifier’s Guide.

[16]

Arch Timber Protection (2002): Dricon Fire Retardant Treated Wood and Lumber, Material Datasheet.

Sensitivity analysis shows that choosing resin alternatives and reducing energy consumption will reduce carbon emissions of technical wood timber by a much bigger margin than technical wood door. This is because the contribution of technical wood timber to the door is only 11.52% (Figure 5). However, there may be higher reduction potential for other technical wood-based products that have higher percentage of carbon emissions due to technical wood timber. Hence, future works can explore the technical feasibility of replacing current resin with alternatives and energy efficiency study of the recycling process.

[17] Nebel, B., Alcorn, A., Wittstock, B. (2009): Life Cycle Assessment: Adopting and adapting overseas LCA data and methodologies for building materials in New Zealand, The Ministry of Agriculture and Forestry Publications. [18]

Kannan, R., Leong, K. C., Osman, R., Ho, H. K., Tso, C. P. (2005): Gas fired combined cycle plant in Singapore: energy use, GWP and cost—a life cycle approach, Energy Conversion and Management 46, pp: 2145–2157.

We like to acknowledge LHT for providing data required for the study and all those who have contributed, especially DavidJonathan Chan for valuable inputs.

[19]

International Panel on Climate Change (2010): Emission Factor ID: 12090 in Emission Factor Database.

7

[21]

Nilsson, B., Flemström, K. (2003): SPINE@CPM, Chalmers University of Technology, Sweden.

[22]

Nilsson, N., Pålsson, A. C. (2001): SPINE@CPM, Chalmers University of Technology, Sweden.

6

[1]

[2]

ACKNOWLEDGEMENTS

REFERENCES Khoo, H. H., Tan, R. B. H., Sagisaka, M. (2008): Utilisation of woody biomass in Singapore: technological options for carbonisation and economic comparison with incineration, International Journal of LCA, 13:312–318. ISO 14040/44 (2006): Environmental Management – Life Cycle Assessment – Principles and Framework/Requirements and Guidelines.

[20] National Renewable Energy Laboratory (2010): U.S. LifeCycle Inventory database.

A Target Costing-Based Approach for Design to Energy Efficiency 1

Annett Bierer , Uwe Götze 1

1

Faculty of Economics and Business Administration, Chair of Management Accounting and Control, Chemnitz University of Technology, Germany

Abstract For some years an additional target – design to energy efficiency – comes into the focus of machine tool designers. Mechanical engineering companies are now facing the challenge to develop and manufacture cost efficient and energy efficient machine tools. Due to methodological support for the development of energy and cost efficient machine tools is needed, but remains unmet in theory and practice, the paper discusses target costing for energy- and cost-related planning and controlling of design specifications. Two approaches are introduced: an adjusted target costing that integrates energy efficiency via corresponding cost budgets and a target energy management focusing on energy consumption. Keywords: Design to Energy Efficiency; Target Costing; Target Energy Management

1

DESIGN TO ENERGY EFFICIENCY – AN INTRODUCTION

Today, mechanical engineering companies are facing the challenge that their customers require environmentally acceptable and/or energy efficient machine tools and technologies – and are often not willing to accept corresponding high prices. Historically, the development of machinery and equipment had to meet more and more targets. To address these challenges, various DfX/DtX tools (design to cost, design to quality, design for manufacturability, and design for assembly) have been developed [1]. As society and with it the customers of the mechanical engineering industry became more conscious of the effects of exhaustible materials and energies and environmental pollution, a further design concept – design for environment (DfE) or ecodesign – emerged. DfE is a strategy for the development of sustainable products that covers various design activities which aim at improving the environmental performance of a product throughout its entire life cycle [1] [2]. The implementation of a DfE strategy in a mechanical engineering company can help i. a. to reduce negative environmental impacts of the machine tools and their manufacturing (e. g., minimizing toxic chemicals releases), optimize raw material consumption and energy use in the manufacturing processes, reduce (life cycle) cost, and meet “user needs/ wants by exceeding current expectations for price, performance and quality” [1]. This demonstrates that DfE should attain environmental as well as economic targets. For some years now attention focuses on design to energy efficiency (DtEE). DtEE can be interpreted as part of a DfE strategy. It aims at ensuring that machine tools meet customers’ needs for energy efficient products [3] [4] and/or at improving the productivity of a manufacturer’s production processes [5]. The relevance of this strategy arises from the fact that machine tools and the processes to manufacture them take energy inputs to transform material inputs into products and wastes and therefore predominantly influence the manufacturer’s (but also the customer’s) environmental outcome and the industrial energy consumption. In theory and practice, energy efficiency is normally defined as the ratio of a useful output to an energy input:

useful output  energy efficiency energy input

(1)

The numerator and denominator of this ratio can be expressed by thermodynamic, physical and/or economic units (e. g., [6] [7]). Thus, a design engineer has the option to improve the energy efficiency of a machine tool by increasing the useful output while keeping the energy input constant, to reduce the energy input while keeping the output at a constant level or to optimize both. The focus of this paper is on improving energy efficiency by minimizing energy use. On one hand, passed opportunities to optimize the energy efficiency of a machine tool during product development would increase the machine’s energy use and energy cost as well as the energy wastes and waste disposal cost incurred during the manufacturing and the use of the machine tool. On the other hand, efforts for improving energy efficiency will also have positive or negative effects on the machine’s manufacturing, operation, maintenance and recycling cost and thus will influence a company’s earnings in different ways [5]. As a result, following a DtEE approach design engineers have to pay attention to both energy conservation measures and the effects of reducing energy consumption on various types of cost (and other aspects such as functionality and quality which are not covered here). Therefore, the need for methodological support for the development of energy and cost efficient products is evident. However, a review of literature shows that there are many publications dealing with the assessment of environmental (and energy) aspects. One of the most prominent approaches to compile and evaluate the inputs and outputs as well as the potential environmental impacts (also including impacts caused by energy use) of a machine tool throughout its life cycle is life cycle assessment [8]. But, like other environmental methods LCA does not include economic effects of environmental and energy impacts and does not support an integrated and continuous management and controlling of product development with respect to energy and cost. Thus, the need for methodological support stated above, still remains unmet. To address this deficit, the paper proposes the transfer of the

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_110, © Springer-Verlag Berlin Heidelberg 2011

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well‐known target costing approach to the field of DtEE. The approach can be modified and applied in different ways. First, it can support the controlling of various types of costs, up to a machine’s life cycle cost, resulting from energy‐related design decisions. Second, it can also be used to control energy-related (nonmonetary) targets like energy consumption or emission reduction. The remainder of this paper is organized as follows. First, based on a description of target costing fundamentals (section 2), reasonable combinations of target costing options for DtEE are presented (section 3). Thereafter, different approaches for using target costing to support DtEE are described (section 4). The summary and conclusions of the paper are presented in the fifth section.

uct target cost (CT) are allocated to the product properties or the respective functions (for means of simplification, here we abandon the distinction between properties and functions) and product components, subassemblies and parts. One usual procedure begins with weighting the product properties (m with m = 1, …, M) with their relative importance as perceived by the customers (vm). Afterwards, the contribution of each of the defined product components (k with k = 1, …, K) to product properties fulfillment (bkm) is estimated. Based on this, it is possible to compute “benefit ratios” for the components (nk) by summarizing the products of the components contribution to property fulfillment and the properties weights: nk 

2

THE TARGET COSTING CONCEPT

Target costing is defined as “a cost management tool for reducing the overall cost of a product over its entire life cycle with the help of the production, engineering, R&D, marketing, and accounting departments” [9]. It is used for effective market- and cost-oriented controlling of design specifications and production techniques. Due to industry (automotive engineering and supplier, mechanical engineering, consumer goods industry with serial production, smallscale production and even individual production) and product specifics (cars, machine tools, machine elements, consumer goods, etc.), the use of and procedures for target costing differ from company to company. Despite these differences in detail, it is possible to identify four common basic steps (Figure 1).

target cost for the product target cost decomposition (determining the target cost for the product functions/properties and components and parts) and target cost achievement within product development  design concept  detail design  production planning  production preparation product and production requirements

target cost determination for product  properties/functions  components  assemblies and parts detailed target cost

target cost achievement and continuous improvement during the market and the after market stage

Figure 1: Target costing process [10]. The procedure starts with basic product planning. The preparation of the basic product plan takes the company’s product and business strategy, market trends and the needs of potential customers into account. This plan includes the positioning of the product in the market and the main product properties. Target cost determination for the new product usually begins with establishing a market-oriented target price (p). After that, the product target cost is computed by subtracting a target profit margin from the target price. It is important to note that the starting point for target cost determination must not need to be a target price [9]. Instead, a current cost level of similar existing products (out of standard cost) or of competitive products (out of competitor) can be used as well. Then, the target cost is calculated by subtracting a required cost savings from the current or competitor cost level.

The next step consists of two sub-steps, target cost decomposition and achievement. During target cost decomposition the set prod-

M m 1

bkm  v m ; k  1, ..., K

(2)

Then, the component target cost (CkT) is calculated by multiplying the product target cost with the respective component benefit ratios:

C kT  n k  CT ; k  1,..., K

(3)

In further decomposition levels the target costs for subassemblies and parts are computed in a similar way by determining benefit ratios for the subassemblies and parts and multiplying them with the respective target cost. Please note that the described target cost decomposition is only one method among several alternatives. The literature describes further allocation methods. The most common are the 

function-oriented method where the decomposition starts with the identification and weighting of product functions and the calculation of functions target costs, and



component-allocation method where the product target cost is directly allocated to product components, usually on the basis of comparisons to already existing products.

basic product planning setting the target cost for the product target price – target profit = allowable cost



Other options include the allocation to cost items (material costs, conversion costs, distribution costs), to departments (marketing, manufacturing, assembly) or to design teams. To ensure that design specifications achieve target cost and fulfill the customer requirements, a target cost index (TCI; benefit ratio to cost share) [10] can be calculated for the components, subassemblies and parts. The ratio can be used to assess whether a component’s design is “too complex” (TCI < 1), or “too simple” (TCI > 1), because its cost share is too high/low with respect to the benefit the customer would assign to it. The target cost achievement process in the development phase is completed when the product meets the properties expected by the customers and the costs are within the target cost limit for the product. With the last step, target cost achievement and continuous improvement, the cardinal rule of target costing “the target cost must never be exceeded” [11] [12] is extended to the phases following the development phase. Now, efforts should aim at continuous improvement activities throughout the whole product life cycle to guarantee that the target cost are always kept during the market and after market stage. 3

OPTIONS FOR USING TARGET COSTING IN DESIGN TO ENERGY EFFICIENCY

In line with the design of energy efficient machine tools, target costing can be applied to prevent design faults that result in high priced machine tools which have undesired functions and are energy inefficient. In search of methodological support to address this challenge, various general target costing approaches have been identified considering different options. Some of these options are

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637

options

company‘s perspective

customer

manufacturer

supplier

cost/energy object

basic machine tool

machine tool variants

machine tool elements

level of decomposition

requireproperty functional compoments level level level nent level

part level

type(s) of targets

manufacturing cost

energy cost

life cycle phase(s)

development

…

life cycle energy concost sumption manufacturing

operation and maint.

...

Life cycle phase(s). Costs and aspects of energy efficiency can be considered throughout the whole life cycle of a machine tool, ranging from the initiation of a development project to recycling and disposal of the machine tool (Figure 3).

As Figure 3 shows, target costing can not only be applied from different company’s perspectives (manufacturer, customer, supplier) and using different types of targets (e.g., cost, energy consumption), but also for different phases of the machine tool life cycle, e.g., product emergence process, operation and maintenance. initia- plan- developm./ tion ning manufact. manufacturer

recycling

Figure 2: Relevant options for energy-related adaptations of target costing.

Cost objects represent entities for which separate measurements of cost are needed [15]. Cost objects in target costing can be products and product elements, but also services, customers, processes or activities. Additionally, in DtEE energy objects are considered that comprise all entities for which separate – physical and/or thermodynamic – measurements are differentiated. Within the context of the considered mechanical engineering three main cost and energy objects can be distinguished: 

Basic machine tools are shared sets of common design, engineering and production efforts only featured with major elements. They provide a platform for a number of distinct variants and types of machine tools.



Machine tool variants are fully equipped types of machine tools and customized machines, ready to be sold to the customers.



Machine tool elements can be mechanical components, subassemblies, and parts as well as electronic devices.

Level of target decomposition. As mentioned above, cost targets can be decomposed at different levels. Energy efficiency or surrogate aspects like energy consumption or energy conservation can also be integrated at various allocation levels, e. g., at the properties level, component level. Types of targets. An early survey of TANAKA showed that companies mostly include the production costs in the target cost, but also costs of R&D, distribution, conversion, and user cost [16]. The literature discusses further cost items that can be used as target cost with or instead of the production costs: i. a. operations and maintenance costs, recycling/recovery costs [17], life cycle cost [18] [19], ecological costs [20], environmental life cycle cost [19], and the net present value on the basis of discounted cash in- and outflows [21]. The listed targets are all monetary targets. But beyond that, in DtEE also non-monetary targets should be applied, because planning and controlling energy efficient design specifications initially aim at energy consumption, conservation, recycling and/or emis-

operating costs

transfer

target price

maintenance manufacturing costs developm. costs

product creation process

customer/user of the machine tool operation and maintenance

recycling

Figure 3: Graphic representation of the life cycle (according to [22]). In conclusion, the described options can be variably combined to pursue different energy-related design goals in product development. With respect to DtEE, some of the combinations are more relevant than others. life cycle phases operation and maintenance energy efficiency in energy efficiency in target costing with a target costing with a manufacturing cost cost of use target target (section 4.1) manufacturing

types of targets

Company’s perspective. A mechanical engineering company can act as manufacturer, customer or supplier [12] [13] [14]. With respect to DtEE, a manufacturer as well as a supplier aims at achieving i. a. its own energy-related manufacturing costs or energy conservation in the production process and/or the user’s energy-related costs or energy consumption of a machine tool during its operation and maintenance phase. If a company does not manufacture all product components by itself, it acts as a customer for the component suppliers and may apply target costing to identify target prices for purchase components, but also to determine their energyrelated requirements (minimum energy consumption, maximum energy efficiency, etc.).

waste disposal

Life Cycle Costs

dimension

sion reduction. These targets are usually expressed in thermodynamic and physical units.

invesment sum

categorized (Figure 2) and described in order to be able to derive useful starting points for the adaptation of target costing for DtEE.

cost target

target energy manaconsumpgement for machine tion target tool manufacturing

target energy management for machine tool use (section 4.2)

Figure 4: Scenario placement within the considered scope. Figure 4 visualizes four selected scenarios for a mechanical engineering company in the role of a manufacturer. This company, developing and manufacturing custom-made machine tools, orients itself to the customers’ needs. Beside functionality and cost, these needs nowadays often also include high energy efficiency. In this situation, the company can use target costing with a focus on cost or consumption targets on the one hand, and on the manufacturing or the operation and maintenance phase on the other hand. Two of the resulting four scenarios are selected and discussed in the next section: 

the particular consideration of energy-efficiency (in the use phase of the machine tool, seen as one of its properties from the point of view of a customer) in the conventional target costing approach, i.e. with a manufacturing cost target (resp. product cost target), and



a target energy concept (called “target energy management”) aiming at the reduction of energy consumption in the operations and maintenance phase of the machine tool.

638 4 4.1

Life Cycle Costing SELECTED SCENARIOS FOR USING TARGET COSTING IN DESIGN TO ENERGY EFFICIENCY Energy efficiency in an adjusted target costing approach

Common aspects A particular consideration of energy efficiency requires a specification of some of the common basic steps of the conventional target costing approach (see section 2). In the step of basic machine tool planning this refers to focusing (beside other aspects) on energy efficiency as a part of the manufacturer’s product and business strategy, energy-related market trends and energy efficiency as a specific need of potential customers. The second step of the target costing approach, target cost determination, has not to be specified. The most conceptual refinements are needed for the sub-step of target cost decomposition. Here, the mechanical engineering company can integrate energy efficiency aspects (and within target cost achievement) in multiple ways, especially, either by setting an energy efficiency budget that is part of the target manufacturing costs or by determining an energy cost budget. The choice between these options should be made according to the relevance of the energy cost in the manufacturing phase and in the operations and maintenance phase. Determining an energy efficiency budget At the first level of decomposition, energy efficiency is considered to be a relevant product property of a machine tool (e) because customers will assign positive perceptions with it (e. g., reduced energy consumption in the operations and maintenance phase). According to the conventional target costing, it is assumed that the costs should be proportional to the customer benefit. On the basis of market research (e. g., by means of conjoint analyses), the relevance of the energy efficiency property (ve) and of the other properties (vm) as perceived by the customers are estimated. Taking the relevance of the energy efficiency property as a basis, now a so called energy efficiency budget (CET) can be determined. This budget comprises financial measures that are available for efforts of the manufacturer during product development and manufacturing to improve the energy efficiency of the machine tool with respect to its operation and maintenance phase: CeT  v e  CT

(4)

After the machine tool components (k with k = 1, …, K) are defined, their contribution to property fulfillment (except the energy efficiency property) is estimated. Using these data, the benefit ratio of each component (nk) can be computed by equation (2). Then, the component target costs (CkT) are calculated by multiplying the machine’s overall target cost with each component benefit ratio: C kT  n k  (CT  C eT ); k  1, ..., K

(5)

Calculated this way, the target cost of a component should be extended by a share of the energy efficiency budget (CkeT) if the component is a main energy consumer and an object of energyconservation efforts. The component´s share of the energy efficiency budget can be estimated on the basis of expected energy conservation potentials (bke) in the machine tool’s use phase. Some approaches to determine these potentials are described in section 4.2. The total target cost of the component (CtotalkT) then amount to: total CkT  CkT  bke  CeT

(6)

The components are subdivided into subassemblies/ and parts. Their contributions to properties fulfillment and respective target costs can be calculated analog to the component target costs.

In the step of target cost achievement within product development, the estimated energy efficiency budget establishes the development and/or manufacturing costs limit for the improvement of the energy efficiency of existing components, subassemblies and parts as well as the development and realization of new low-energy components etc. The corresponding efforts comprise measures and methods 

for energy conservation of existing machine elements like the options NEUGEBAUER ET AL. proposed for machine tools (elimination of energy usage, adjusted-to-needs energy usage, general improvement of energy efficiency, energy recovery) [23],



and to support the design of new low-energy machine elements like optimization calculations or simulations on the basis of physical and thermodynamic characteristics that could be used to determine the components’, subassemblies’, and parts’ energy consumption.

Within the last step of the target costing procedure, target cost achievement and continuous improvement in the market and after market stage, not only the product costs, but also the energy efficiency of the product at its use at the customer should be managed and controlled. In general, the described energy efficiency budgets have the potential to support an effective use of financial measures to improve energy efficiency. Determining an energy cost budget A quite different option of integrating energy efficiency into target costing focuses on energy cost targets. Energy costs can be a subject in target costing in different ways, especially using energy cost budgets for the components’ (or subassemblies’ and parts’) manufacturing processes. Taking the conventional procedure, the overall target cost are estimated and allocated to the machine tool properties on the basis of their respective relevance for the customers. Then, the target cost is decomposed to the components and subdivided into cost budgets for the different items of the producer’s manufacturing costs, such as the energy costs, material costs, direct labor costs, purchased parts costs, etc. [24]. This enables the design engineers to select manufacturing technologies and configure manufacturing process chains wherewith the given energy cost budget for the manufacturing of the machine tool can be achieved. 4.2

Target energy management

Common aspects The described option in section 4.1 is directed to the manufacturer’s aims to develop energy-efficient machine tools and to manufacture them in an energy-efficient way at a competitive cost level. However, what to do when the focus is on energy consumption, e.g., a machine tool is required to have a certain energy consumption or a consumption that will be lower than that of already manufactured or competitive machine tools? To plan and control the development and manufacturing of a machine tool consuming “less energy”, neither its manufacturing cost or life cycle cost nor any other monetary target, especially the energy costs the machine causes during its use, would be exclusively appropriate types of targets. This is due to the fact that design decisions which are directed towards energy conservation affect different cost items in different ways. Additionally, the energy costs of the user often cannot be assigned to single machine tools. In many cases, the manufacturing of machine elements consuming less energy in its operation phase cause higher manufacturing cost than comparable ones. Therefore, costs are not good indicators when trying to develop products that spend less energy. Other ways must be found to deal with that specialty. One of them is the introduction of energy consumption or conservation targets instead of “target cost”. Since the term “costing” is closely connected to cost

Life Cycle Costing

639

accounting and management, the term “target energy management” is used here to point to a new approach that considers energyrelated targets like energy consumption or conservation instead of cost targets. In the following, such a target energy management approach is presented assuming that the “energy consumption of the machine tool during its use at the customer” is the overall target. Figure 5 gives a general idea of the respective procedure.

contributions to property fulfillment are determined. The components’ benefit ratios (nk) are again computed using equation (2). Then, the target energy consumption of every component (EkT) is calculated by multiplying the respective benefit ratio with the total target energy consumption:

E kT  n k  ET ; k  1,..., K with

basic machine tool planning setting the target energy consumption for the machine reference value for energy consumption – target energy conservation target energy = allowable energy consumption consumption for the machine tool target decomposition (determining the target energy consumption for machine tool properties, components and parts) and target achievement in the development phase  design concept  detail design  production planning  production preparation

target consumption determination for product  properties/functions  components  assemblies/parts

product and production requirements

detailed target energy consumption

target achievement and continuous improvement during the market and the after market stage

Figure 5: Process of a target energy management. Step 1: basic machine tool planning As in conventional target costing (see section 2), in the first phase the mechanical engineering company (the manufacturer) determines a basic plan for the new machine tool on the basis of the company’s product and corporate strategy and with a specific focus on energy consumption. Step 2: Determination of target energy consumption After a basic plan of the machine tool has been defined, the energy consumption target is established. Similar to target costing, this target can be derived from the market. In fact, a mechanical engineering company may be confronted with a conservation requirement or an allowable level for energy consumption that is required by the customers. In other cases, such market targets are not available. As shown in Figure 5, in such cases alternatively a reference value for energy consumption can be identified using an 

out of standard consumption strategy when the energy consumption of an already existing and comparable machine tool is taken as a basis, or



out of competitor strategy when the energy consumption of competitive machine tools represents the starting point.

To compute the allowable target energy consumption (ET) of the new machine tool on the basis of these strategies, a target energy conservation potential has to be subtracted from the reference value. Information to determine the conservation potential can again come from the company itself or from competitors. Step 3a: Target decomposition In the next step, the established target energy consumption is decomposed up to the component and the subassembly and part level. Following the conventional target costing procedure, the target energy consumption is allocated on the basis of components’ benefit ratios (and other, depending on the level of decomposition). The process starts with the identification of the machine tool properties and their relevance as perceived by the customers. After that, the components of the machine tool (k with k = 1, …, K) and their



K k 1

nk  1

(7)

This market-oriented approach is based on the assumption that the energy consumption rates should be proportional to the customer benefit. The corresponding cost-related assumption is a basic problem in conventional target costing [25] and similar to the fact that a proportionality of energy consumption and customer benefit will not be given in many cases. For instance, a machine tool could have components that require a minimum energy consumption to generate a certain output with a certain quality level. In some cases, the customer will not appreciate this basic energy consumption requirement in an appropriate way. However, if the consumption falls below this minimum, the component is no longer able to produce any output at all. In such cases the market-driven energy consumption budget will not be a good controlling measure. To prove or to improve the results of the market-oriented target decomposition, in particular with respect to the described effect, the component-allocation method may be used additionally or instead. Then, the target energy consumption will be directly allocated at the components, subassemblies, and parts taking the current consumption of similar components of comparable existing machine tools into account. This requires that authoritative information is available from already manufactured and used components and machine tools of the company, of component suppliers or of competitors. Step 3b: Target achievement During target achievement, the methods for energy conservation of existing components and the design of new low-energy components mentioned in section 4.1 can be applied. To control the design specifications in order to fulfill the customer requirements as well as the consumption targets, a target energy consumption index, analog to the target cost index in section 2, could be calculated and taken as basis for comparisons between planned/targeted energy consumption and actual attainable consumption. Step 4: Target achievement and continuous improvement The target energy management process should not stop after the consumption target has been achieved in product development. A machine tool has an expected useful life of 8 to 15 years. Without systematic maintenance of the energy consuming components, ranging from inspections and repair to the replacement of components, subassemblies and parts by ones with improved energy efficiency, its consumption would increase with time. So, target energy consumption achievement and continuous improvement during the market and after market stage should be an integral part of a target energy management concept. The described target energy management can contribute to DtEE by supporting the development of machine tools that simultaneously fulfill the customer requirements and achieve a certain energy consumption target. So far, the costs incurred by an energy efficient designed machine tool are ignored in this approach. Because of this and with respect to the initially mentioned targets in DtEE, the target energy management approach should be adjusted by setting cost constraints or by using a two-dimensional – cost and consumption – top level target.

640 5

Life Cycle Costing SUMMARY

In summary, the paper raised the problem of inadequate methodological support for the planning and controlling of design processes in DtEE with respect to energy and cost. To address this problem, target costing has been recommended as a potential method for resolution. Out of the analysis of existing approaches, two concepts for using target costing in the context of DtEE are proposed: an adjusted target costing approach with either energy efficiency or energy cost budgets and a target energy management approach directed to the controlling and management of energy consumption. Further research activities are necessary in at least two fields: First, more detailed methodological elaboration of the described concepts is needed. Second, as already denoted at the end of section 4.2 a combined approach that allows it to pursue energy- and costrelated targets simultaneously has to be developed. 6

ACKNOWLEDGMENTS

Our work is part of research in the Cluster of Excellence „EnergyEfficient Product and Process Innovation in Production Engineering“ (eniPROD®). The Cluster of Excellence „Energy-Efficient Product and Process Innovation in Production Engineering“ (eniPROD®) is funded by the European Union (European Regional Development Fund) and the Free State of Saxony.

[10] Götze, U. (2010): Kostenrechnung und Kostenmanagement, Springer Verlag, Berlin, Heidelberg (German). [11] Ax, C., Greve, J., Nilsson, U. (2008): The impact of competition and uncertainty on the adoption of target costing, in: International Journal of Production Economics, Vol. 115, No. 1, pp. 92-103. [12] Cooper, R., Slagmulder, R. (1997): Factors Influencing the Target Costing Process: Lessons From Japanese Practice, working paper 97/30, faculty of economic sciences and applied economics, university of Ghent, pp. 1-28. [13] Yoshikawa, T., Innes, J., Mitchell, F. (1994): Applying functional cost analysis in a manufacturing environment, in: International Journal of Production Economics, Vol. 36, No. 1, pp. 53-64. [14] Dunk, A. S. (2004): Product life cycle cost analysis: the impact of customer profiling, competitive advantage, and quality of IS information, in: Management Accounting Research, Vol. 15, No. 4, pp. 401-414. [15] Horngren, C. T., Srikant, M. D., Foster, G. (2006): Cost accounting: a managerial emphasis. Pearson Prentice Hall, Upper Saddle River, NJ, USA. [16] Tanaka, M. (1984): Substance of Cost Engineering and the Status Quo of Japanese Companies. In: Cost Accounting, February, p. 14. [17] Janz, D., Hornberger, M., Westkämper, E. (2006): Design for environment by target life cycle costing, in: Brissaud, D.: Innovation in life cycle engineering and sustainable development: selection of papers of the 12th CIRP International Conference on Life Cycle Engineering (LCE2005), pp. 337-348, Grenoble, France.

7

REFERENCES

[18] Schmidt, F. R. (2000): Life Cycle Target Costing. Ein Konzept zur Integration der Lebenszyklusorientierung in das Target Costing, Shaker Verlag, Aachen (German).

[1]

XiaoChuan, C. (2004): The relationship between design for environment (DFE) and design for cost (DFC), in: World engineer’s convention, Vol. G, pp. 293-296.

[2]

Hauschild, M. Z., Jeswiet, J., Alting, L. (2004): Design for environment – Do we get the focus right?, in: CIRP Annals – manufacturing technology, Vol. 53, No. 1, pp. 1-4.

[3]

Boardman, B. (2004): Achieving energy efficiency through product policy: the UK experience, in: Environmental Science & Policy, Vol. 7, No. 3, pp. 165-176.

[4]

Graedel, T. (1997): Industrial ecology: definition and implementation, in: Socolow, R., Andrews, C., Burkhout, F., Thomas, V.: Industrial ecoloy and global change. Cambridge University Press, Cambridge, pp. 23-42.

[21] Götze, U., Linke, C. (2008): Interne Unternehmensrechnung als Instrument des marktorientierten Zielkostenmanagements – ausgewählte Probleme und Lösungsansätze, in: Zeitschrift für Planung & Unternehmenssteuerung, Vol. 19, No. 1, pp. 107-132 (German).

[5]

Worrell, E., Laitner, J. A., Ruth, M., Finman, H. (2003): Productivity benefits of industrial energy efficiency measures, in: Energy, Vol. 28, No. 11, pp. 1081-1098.

[22] Deutsches Institut für Normung e.V. (2005): VDI 2884: Purchase, operating and maintenance of production equipment using life cycle costing (LCC), Beuth Verlag, Berlin.

[6]

Patterson, M. G. (1996): What is energy efficiency? Concepts, indicators and methodological issues, in: Energy Policy, Vol. 24, No. 5, pp. 377-390.

[7]

Ayres, R. U., Turton, H., Casten, T. (2007): energy efficiency, sustainability and economic growth, in: Energy, Vol. 32, No. 5, pp. 634-648.

[23] Neugebauer, R., Frieß, U., Paetzold, J., Wabner, M., Richter, M. (2010): Approach for the development of energy-efficient machine tools, in: Knowledge based manufacturing, session 1: knowledge based manufacturing machines design, Wroclaw, Poland, pp. 51-62.

[8]

ISO 14040 (2006): International Standard. Environmental management – Life cycle assessment – Principles and framework, International Organization for Standardization, Geneva, Switzerland.

[9]

Sakurai, M. (1989): Target costing and how to use it, in: Journal of cost management for the manufacturing industry, Vol. 3, No. 2, S. 39-50.

[19] Schild, U. (2006): Lebenszyklusrechnung und lebenszyklusbezogenes Zielkostenmanagement. Deutscher UniversitätsVerlag, Wiesbaden (German). [20] Günther, E., Schill, O., Schuh, H. (2000): Berücksichtigung von Ökologiekosten im Target Costing, in: UmweltWirtschaftsForum, Vol. 8, No. 1, pp. 65-71 (German).

[24] Monden, Y., Hamada, K. (1991): Target Costing and Kaizen Costing in Japanese Automobile Companies, in: Journal of Management Accounting Research, Vol. 3, pp. 16-34. [25] Rösler, F. (1995): Kundenanforderungen als Determinante des Kostenmanagements komplexer Produkte, in: Kostenrechnungspraxis, Vol. 39, No. 4, pp. 214-219 (German).

Life Cycle Costing Assessment with both Internal and External Costs Estimation Sylvain Martinez

1, 2

1

1 2 3

2

, Mehrdad Hassanzadeh , Youcef Bouzidi , Nicolas Antheaume

3

Schneider Electric, Montpellier, France

ICD – CREIDD, Université de Technologie de Troyes, UMR STMR - CNRS

Laboratoire d’Economie et de Management de Nantes-Atlantique, University of Nantes, Nantes, France

Abstract The aim of this article is to study the economic impact of an eco-design-based approach. The product in question is a tie rod fitted to a medium voltage circuit breaker. A new generation of ecologically-designed tie rod, designed by our company, will be compared with the current generation model, using a methodology blending life cycle assessment (LCA), lifecycle costs and external costs. This type of comparison is useful for highlighting companies' attempts to develop environmentally-friendly products, whilst evaluating, wherever possible, the decrease in external costs imposed on the company by such an ecological design-based approach. Keywords: Life Cycle Assessment; External Costs; Eco-Design

1

INTRODUCTION

Numerous European Directives and Regulations (REACH, ROHS, DEEE, EuP, etc.) have been published during the last few years. It is highly likely that new ones will be issued in the years to come. Their aim is, generally, to force producers/manufacturers to take more responsibility for their actions and push them towards adopting new product policies. To meet these directives, and anticipate possible future regulations, companies are developing ecological-design processes for their own products. The advantages expected are multiple: Improving environmental impact, protecting human health (workers, consumers), preserving competitive edges and improving innovative capacity. Beyond there being just a single response to regulatory requirements, certain ecological design approaches can be valorised in themselves, for example, by using specific labelling. However, an ecologically-designed product can lead to costs which do not seem valorisable, notably if the cost analysis does not cover the whole life cycle of the product. One can assume, by working 'from cradle to grave', that ecological design can lead to increased costs during a given stage of the product's life cycle, but that these costs could be clawed back during other stages, both in terms of the costs paid by the enterprise themselves as well as the cost to society in general (external costs). In this article we will be defining the various stages of a product's life cycle. We will, through this example, attempt to show the effects of ecological design, in terms of environmental impact, then translate the latter in terms of potential economies. Our methodology associates cost calculations for the whole life cycle of a product with a full life cycle assessment. 2

PRESENTATION OF THE PRODUCTS BEING STUDIED

The product studied is an insulating tie rod. It has two roles: 

as an electrical insulation barrier between the vacuum interrupter bottle and ground.



as a means to transmit the mechanical movements of the actuator to the mobile contact of the vacuum interrupter.

The insulating shaft/tie rod configured in the shape of a cone has metal inserts moulded at either end. The casting is a silica filled epoxy resin

Figure 1: Epoxy tie rod. A Research and Development project has been carried out with the aim of developing a thermo-plastic tie rod.

Figure 2: Thermoplastic tie rod. The thermoplastic tie rod has the same technical properties (mechanical, thermal, electrical…). The vacuum interrupter is made up of a ceramic casing and copper connections (contacts). One contact is fixed, the other mobile. The latter is spring actuated, with the spring storing a great deal of energy. The high levels of energy required to close or open the vacuum interrupter are because there is a requirement to decrease the contact resistance and to be able to separate the two contacts if they have been 'welded' by an electric arc. The tie rod is a single component within the medium voltage circuit breaker.

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_111, © Springer-Verlag Berlin Heidelberg 2011

641

642

Life Cycle Costing

Copper

Closed

scenarios for the product's end-of-life must be well defined. Materials might be reusable, recyclable, burnable – with or without energy recovery, or simply send to landfill, as shown in Table 1.

Open

Treatment Recovery

Tie rod

Re-use

Recycling

(parts)

(Material)

Recycled mass A medium voltage circuit-breaker used to make, break and guarantee the passage of an electrical current. In this case, the current is broken by a vacuum interrupter.

(material)

Undefined residue (material or part)

Total product mass Table 1: End of life scenario. Re-use: operation by which a product, or a part thereof, having reached the end of one use-phase is used again for the same function for which it was conceived.

Copper

Gas Tank

Energy recovery

Recovered mass

Figure 3: Vacuum interrupter.

Vacuum Interrupter

Disposal

Recycling: processing of waste materials for the original purpose or for other purposes, excluding recovery.

Tie rod

Recovery: process in which a waste product and its constituent material(s) is subjected to material recovery or energy recovery or replacing other materials which would otherwise have been used to fulfill a particular function.

Actuator

Disposal: operation which is not recovery such as incineration, landfill or other permanent storage. Figure 4: Circuit breaker medium voltage. The initial aim of this project was to improve the environmental impact of the tie rod by improving recyclability. In fact, thermoplastics are, in the main, recyclable. This property means that there is less of a drain on natural resources, notably fossil fuels, reserves of which are becoming scarcer and scarcer. 3

PRESENTATION OF THE METHODOLOGY

We have chosen to link a life cycle assessment with a global product costing. The life cycle assessment is a tool capable of integrating all existing product information. The scope of this analysis runs from the extraction of raw materials to the end of the life of the materials making up the product. We have attached particular importance to this end-of-life phase. The various

A great deal of work is currently underway in order to harmonise the various ratios on an international, national and business sector scale. A standard is currently being developed – IEC 62635, covering electrical and electronic equipment. The results of a life-cycle assessment are not always easy to use by personnel who have not studied the LCA methodology. An increase or decrease in the quantities of a pollutant emitted is difficult to exploit. For example, what does an additional emission of 1 kg of CFC11 actually represent? How does one compare that additional CFC emission with a decrease in CO2 emissions? With these types of results, the choice of one scenario over another must be based on a determination of the relative importance attached to each individual environmental impact, as well as consideration into the significance of each of the values obtained.

Figure 5: Impact path.

643

Life Cycle Costing In order to render the contrasting results of the LCA easier to use, various solutions have been proposed, however, as of today, none of them have been entirely satisfactory. They are mainly based on 'standardisation' or 'monetarisation'.

Cost for market research Cost of R&D

Other costs Part cost

The former involves an 'end-point' approach, which is, in turn, based upon the translation of all impacts into individual indicators, as shown in the 'impact path' approach (figure 5).

Cost for manufacturing

Certain methods for the evaluation of environmental impacts (ecoindicators, eco-points, etc.) give a unique indicator score, which can then be linked to the imposed, non-user controllable weighting systems. Another method involves translating the results of the LCA into a 'habitant equivalent'. This means dividing the corresponding environmental impact of the product in question into the total impact on a geographic zone, multiplied by the number of habitants of this zone. This approach can determine which individual environmental effect is the most serious, however, one should avoid mixing the product's contribution to an effect with ones own prejudices. Another limitation of this approach is the fact that the total obtained for all equivalent values, giving a single score, involves weighting all impact at 1, which doesn't make sense.

The method used to calculate internal costs is the Life Cycle Cost (LCC) [1], [2], [3]. Table 2 defines the Life Cycle Cost in a simplified manner. LCC can be used independently of LCA, for the evaluation of private costs over the life cycle of product. In this case the focus is not to link physical flows to monetary values. By combining LCA with LCC we try to establish this link between physical flows and monetary values. Furthermore, we add external costs to the private costs included in the LCC approach. An external cost can be defined as the monetary value assigned to a noxious effect caused by an economic agent, where the cost of this effect is not born by the body responsible for its cause, but by a third party. The evaluation of an external cost involves, firstly, producing an initial expression of an impact in terms of a monetary value [4]. External costs can be determined using two separate approaches: 



The mean approach determines the 'average' effects, that is to say, the total effect of a pollutant over a certain period, divided by the quantity of product produced or consumed during this period which is responsible for the effect. To achieve this, a 'top-down' accounting method is used. This involves evaluating the total effect of a pollutant across a given zone (generally a country, using national databases), which is then divided by the number of units producing the damage in question. The marginal approach determines the 'marginal' effects detected. That is to say, the increase in units of a pollutant responsible for an effect (e.g.: 1 additional kg of CO2 produced). The method used to show the impact, from Figure 5, corresponds to a 'bottom-up' accounting method. The single indicator is then expressed in monetary units.

Material cost Energy cost Other costs

Cost for distribution Life Cycle Cost

Shipping cost Returning cost Other costs Energy cost

Cost during use

Water cost Consumables cost Maintenance/repair cost Other costs Recycling cost

Cost during end-of-life

The second solution involves monetarising the individual environmental impacts. The objective remaining the production of a single unit, covering all impacts, but here it is a monetary unit. Firstly we define the various cost types. There are two cost categories: Internal and External Costs. An enterprise's internal costs are represented by the costs born internally, integrated into the company's own accounts. When environmental taxes are involved they are assumed to be integrated into existing costs (for example, sewage taxes as part of water bills). Internal costs can be used to calculate the 'gate-to-gate' cost of the product.

Cost for product development

Reuse cost Disposal cost Other costs

Other costs

Insurance cost… Other costs

Table 2: Structure of LCC. From both these approaches one can obtain external costs using two different sub-methods: 

Specific studies calculating the value of the external costs created by a pollutant. This methodology can be costly and the time taken to complete the studies can be long. However, the quality and accuracy of the data is excellent, in the sense that they correspond to a precise context (a date, location, product and exact technology).



Use of data taken from literature. This method is simpler to employ and much less expensive. However, the quality and accuracy of the data is not as good, in so far as one is using secondary data which does not necessarily correspond to the actual context as the data gathered from the studies in the previous paragraph.

Certain external costs correspond to clearly identified economic values (healthcare costs, cleaning of buildings, lost harvests, etc.). Others are more difficult to translate economically (the loss of a habitat for example). We have chosen to separate external costs into three categories: Damage prevention costs, the costs of damages themselves and the costs of repairs following damage [5]. Damage prevention costs involve all those costs born in the attempt to stop pollution from causing damage. This is taken in one of two ways, either the costs of protecting against potential damage, or, more commonly, preventive costs the enterprise itself does not wish to internalise. In the second case, as the costs are not due to actual damage, the preventive costs the company would have been required to pay are used as an approximation of the external costs. In summary, in our study, preventive the costs taken into account are those concerning the ecological development of a product. They are internal to the enterprise itself and therefore not counted as protective costs. In fact, the R&D project for the thermoplastic tie rod will lead to a decrease in pollution. We avoid pollution, therefore there is prevention.

Life Cycle Costing

644 The cost of damage represents the cost of pollution. In this case, no pollution is anticipated nor included, corresponding to a 'let do it' type of attitude. This category includes costs such as the effects of climate change (population movement, extreme weather, lost harvests, etc.), reduction in biodiversity, increase in human toxins (ozone depletion, leading to cancers, hospitalisation, health problems, increased mortality, etc.). The costs of repairing damages represent the costs born in an attempt to remedy a problem. The final status should be that before the pollution took place. In this case, as pollution would have already taken place, its traces should be removed by repairing any damage caused to the environment. This may involve water treatment, liming, building façade repairs, and medical bills.

determination of the MF values is a complex affair, which, in the main, requires the production of a model, which itself is based upon modelling hypotheses in addition to geographic and temporal information. The monetary evaluation is used to provide a direct comparison of differing types of effect, given that they are always expressed using the same unit of measurement (in our study this unit is the Euro), expressing the result of the multi-impact evaluation in the form of a single score, thus giving a direct comparison of the results of several systems. The impacts taken into account by the monetarisation process can be diverse in nature: 

Environmental impacts: Through the environment itself, these may involve emissions of pollutants into the air, water and ground, consumption of natural resources, various other problems, etc.

Our approach involves comparing the overall cost of an ecologically designed product (ecological design costs, other internal costs and external costs) with the overall cost of a non-ecologically designed product (internal and external costs).



Social impacts: Involving services and property rendered accessible (or inaccessible) to certain categories of person who would not previously had access (authorised) or the creation of jobs.

Ecological design is justified if:



Economic impacts: Flow of receipts and expenditure

Overall cost of ecologically designed product < overall cost of nonecologically designed product.

In order to complete the monetarisation process a link must be established between the elementary flow or characterisation factor and the effect it causes. This link is known as the monetarisation factor. A monetary value for the damages created by an elementary flow (or characterisation factor) is obtained by multiplying its physical value by the monetarisation factor.

The overall cost of a product is the sum of internal and external costs.

To summarise, the method we propose involves calculating the LCC of a product, carry out a life cycle assessment and calculate the external pollution costs from this LCA. The sum of the costs represents the global cost of a product across its entire life cycle. 4

There are two possible ways of determining the monetarisation factor:

MONETARY DATABASE

With the LCA finished we can see the environmental impacts in the form of aggregated flows. An aggregated flow (or characterisation factor) is the sum of elementary flows. An elementary flow is a flow of material or energy leaving the system being studied and discharged into the environment without later human transformation [6]. Our method involves monetarising characterisation factors as well as elementary flows. To do this we need a database of environmental costs. In the example given in this article, we have based our work on a study carried out by the cabinet RDC Environnement, with the support of the French Ministry for Ecology, Development and Sustainable Living [7]. We have selected this study as it is the most recent available (2007). In addition, the study is a bibliographical review carried out on behalf of the French Ministry, so the data has the status of an accepted reference. In the absolute, without being able to carry out a complete study, one must base ones work on a number of studies in order to obtain a fuller sample value. In the RDC study the monetarisation factors (MF) have been determined in 'Unit of Impact'. These correspond to damages and/or benefits caused by the environmental impacts. The Environmental impact

Approach

Global warming

Damage

Eutrophication

Damage

Human toxicity Human toxicity



The effect is directly due to the elementary flow. Elementary flow

Intermediate effect

Apparent effect

Figure 6: Determination of the effect shown by a damage path. 

The effect is due to preventive or reparative actions undertaken to counter the direct effects of the elementary flow. Elementary flow

Damage prevention or reparation work undertaken

Intermediate effect

Apparent effect

Figure 7: Determination of the effect shown by a damage path or damage repairs. Forecast

Value € 2010

Short term

24,4

Long term

106,2

Unit t eq CO2

1,0

Kg P eq

Damage

1,1

Kg C2H4

Damage

48,9

Kg Cd

Human toxicity

Damage

223,0

Kg dioxines

Human toxicity

Damage

244,3

Kg CrVI

Human toxicity

Damage

1943,7

Kg Pb

Raw material depletion

Damage

Renewable

0,4

Non renewable

0,02

Table 3: External costs used.

MJ

Life Cycle Costing

645

In the RDC Study, the preventive costs, damage reparation costs and damage costs are all listed. There are very few values for preventive and damage reparation costs. The majority of the data covers damage costs. We have thus decided not to use the preventive costs listed above and the damage repair costs. The relative lack of data means we do not have sufficiently reliable information to use. All this data is taken from the study carried out by RDC Environnement. The values were updated in 2010 with an annual update rate of 2.03%. The RDC study contains monetary data for other pollutants. We have chosen to use date from the pollutants in Table 3 only, in accordance with the direction of our Working Group. These choices were guided by the target of fighting against climate change, protecting human health and protecting natural resources.

Impact

Methodology

Value

Unit

GWP

IPCC 2007

2,00

Kg eq CO2

Eutrophication

EDIP 2003

2,74.10-5

Kg P

-4

Human Toxicity

Impact 2002+

8,85.10

Kg C2H4

Human Toxicity

Ecopoint 97

1,21.10-6

Kg Cd

-9

Human Toxicity

Inventory

3,15.10

Human Toxicity

Inventory

1,04.10-5

Kg dioxines Kg CrVI

Human Toxicity

Ecopoint 97

2,06.10-4

Kg Pb

Raw material depletion

Cumulative Energy Demand

40,78

MJ non renewable

0,47

MJ renewable

Table 6: Environmental impact of the epoxy tie rod.

AGAINST

We can see that all values for the thermoplastic tie rod are lower than those for the epoxy tie rod. From a strictly environmental point of view, ecological design has played a role in reducing impacts.

The tie rod system defines the scope of the study. All available data from the extraction of raw materials to end-of-life phases have been covered by this study.

By multiplying the values of each pollutant in Table 5 and table 6 by their monetary value in Table 3, and then by summing the results obtained, we can produce an external cost for each rod:

The Functional Unit for the Tie Rod is: The transmission of mechanical movement from the actuator and vacuum interrupter, whilst providing electrical isolation between the vacuum interrupter and the framework of the equipment during its expected service life of 30 years.

Thermoplastic tie rod:

We have thus carried out a life cycle assessment on two tie rods, using SimaPro Version 7.1.8.



1.46 € / tie rod, short term outlook



1.62 € / tie rod, long term outlook

The data used is all internal data with low levels of incertitude. No data was excluded from the perimeter of our study.

The costs of the damages caused by the thermoplastic tie rod are 4 x less than those caused by the epoxy tie rod.

In terms of the end of life, it seemed useful to define, in Table 4, the data we used, which, we remind you, is still Internal Data.

If we now look at the cost of preventing damage, these correspond to the cost of the project leading us to the development of the thermoplastic tie rod. The R&D project costs include direct costs (materials, labour, equipment: Thermoplastic moulds) and indirect costs (purchasing, accounts, management, etc.) From our study, the damage prevention costs are 4.2 Euros per thermoplastic tie rod over the first three years. By the end of the fourth year the preventive costs have been amortized.

5

APPLICATION: THERMOPLASTIC EPOXY TIE ROD

TIE

ROD

Material name

Recyclability (%)

Recoverability (%)

Waste Disposal (%)

Thermoplastic

70

20

10

Epoxy

0

90

10

Steel

95

0

5

Brass

90

0

10

Table 4: End of life scenario used.



0.37 € / tie rod, short term outlook



0.42 € / tie rod, long term outlook

Epoxy tie rod:

The total sum of these costs is relatively low, especially in terms of damage costs. We can now compare internal costs for both tie rods.

Here are the results obtained: Internal cost (€)

Epoxy tie rod

Thermoplastic tie rod

A

A – 40%

Impact

Methodology

Value

Unit

GWP

IPCC 2007

5,92.10-1

Kg eq CO2

Table 7: Internal costs of the two tie rods.

Eutrophication

EDIP 2003

9,42.10-6

Kg P

Human Toxicity

Impact 2002+

4,29.10-4

Kg C2H4

The thermoplastic tie rod is much less expensive than the epoxy rod. If one adds in the R&D costs (prevention), the cost of the thermoplastic rod is 20% below that of the epoxy rod over the first three years. After those three years, once the R&D costs have been amortized, the cost of the thermoplastic rod is 40% below that of the epoxy tie rod.

-7

Human Toxicity

Ecopoint 97

2,22.10

Kg Cd

Human Toxicity

Inventory

1,69.10-10

Kg dioxines

Human Toxicity

Inventory

5,35.10-6

Kg CrVI

-5

Human Toxicity

Ecopoint 97

1,07.10

Kg Pb

Raw material depletion

Cumulative Energy Demand

14,48

MJ non renewable

0,12

MJ renewable

Table 5: Environmental impact of the thermoplastic tie rod.

If one adds in damage costs, the overall cost of the thermoplastic rod is 24% below the epoxy rod for the first three years then 43% less after this period. The difference between the costs of the two tie rods, including the ecological design costs, remains in favour of the ecologically designed product. For the moment however, the inclusion of a time factor is limited to simply 'pay-back' factors and ignores any inflation updates. These results are given in Figure 8.

646

Life Cycle Costing

Tie rod thermoplastic (< 3years)

Tie rod epoxy (< 3years)

LCC

Tie rod thermoplastic (> 3 years)

Prevention

Tie rod epoxy (> 3 years)

Damages

Figure 8: Comparison of the global cost between the two tie rods. 6

LIMITATIONS OF THE APPROACH

A first limitation of our work is that we lacked space to discuss the assumptions of RDC. We are currently expanding our database of monetary factors to include more sources and provide monetary intervals rather than single values. A second limitation is that, at this stage we have not taken the locality issue into account. Our ongoing research work will address this issue. Throughout our approach we have seen that monetarisation has a notable limitation. During a LCA it is impossible to take into account all possible flows. Monetarisation can only cover a small quantity of the flows taken from the LCA [4], confirming our study. Tie rod thermoplastic

Tie rod epoxy

Number of flux LCA

810

725

Number of flux monetized

125

92

Table 8: Flows of the study. There is thus a major loss of data across the various phases. This is due to the current state of understanding. Work is currently underway to develop Life Cycle Analyses, as well as to improve the monetarisation of environmental impacts (Waste & Society, Monetarisation of External Impacts, ADEME, CASES, etc.), however, the work is currently still in its infancy. It is possible to use equivalent substances, but there is no current proof that there is proportionality between environmental impacts and environmental costs. In addition, the values for environmental costs can never be precise. There is a high level of incertitude for each figure due to the complex nature in which it is arrived at. We would thus propose that it is better to work with cost ranges. The error would to use a single value for each pollutant for each source, as shown in our example. In order to obtain cost ranges [8], and thus improve accuracy, we propose that we put together a database of damage costs, damage repair costs and damage prevention costs. Various studies exist in literature already [9], [10], [11], [12]. No values can be exact, but no values are completely incorrect. By taking various sources, looking at various locations, times, contexts, etc we can provide cost ranges which, in our view, would seem better than a single 'exact' value. 7

CONCLUSION

Our study has shown that there is compatibility between environmental and economic approaches. It shows the necessity, today, of developing global cost methods in order to meet the needs of enterprises, clients and the general population, even if, for the time being, they can only give a partial image of environmental impacts.

The example studies in this article shows that an ecologically designed product can have a lower production cost than that of a non-ecologically designed version. In addition, the costs of damages represent between 3 and 7% of the cost of the product (3% for eco-design, 7% for the non-eco product). This value is relatively high, and the difference between ecologically and nonecologically designed products justifies the cost of ecological design. Currently, the evaluated damage costs is born by society Tomorrow, these costs may be shared between the producer, the client and society in general (total internalisation of external costs is impossible). It is thus of the utmost importance to all parties that transparency be favoured in terms of the connections between product design choices and the consequences of these choices in terms of global costs. 8

REFERENCES

[1]

Jeong, I.-T., Lee, K.-M. (2009): Assessment of the Ecodesign Improvement Options using the Global Warming and Economic Performance Indicators, in: Journal of Cleaner Production, Vol. 17, pp. 1206-1213.

[2]

EPA, (1995): An Introduction to Environmental Accounting As A Business Management Tool: Key Concepts And Terms http://www.p2pays.org/ref/02/01306.pdf (Last access on October 2010)

[3]

Davis Langdon, (2006): Literature review of Life Cycle Costing (LCC) and Life Cycle Assessment (LCA) http://www.tmb.org.tr/arastirma_yayinlar/LCC_Literature_ Review_Report.pdf (Last access on March 2010)

[4]

Antheaume, N. (1999): L’Evaluation des Coûts Externes de la Théorie à la Pratique, doctora thesis, Universtity of Nice.

[5]

Baret, P., Dreveton, B. (2006): L’Evaluation des Impacts Environnementaux : une grille de lecture. http://www. management.free.fr/recherche/contenucongres/AFC/p106 .pdf (Last access on December 2010)

[6]

International Standard ISO, ISO 14044-1 (2006): Management Environnemental Analyse du Cycle de Vie Exigences et Lignes Directrices.

[7]

RDC Environnement, (2007): Environnementaux du Recyclage.

[8]

Antheaume, N. (2004): Valuing External Costs From Theory to Practice: Implications for Full Cost Environmental Accounting, in: European Accounting Review, Vol. 13, No. 3, pp. 443-464.

[9]

Kusiima, J.-M., Powers, S.-E. (2010): Monetary Value of the Environmental and Health Externalities Associated with Production of Ethanol from Biomass Feedstocks, in: Energy Policy, Vol. 38, pp. 2785–2796.

Les

Bénéfices

[10] Bovea, M.-D., Wang, B. (2002): Integration of Customer, Cost and Environmental Requirements in Product Design: an Application of Green QFD. www.gid.uji.es (Last access on September 2010). [11] Noh, J., Itsubo, N. (2004): Data sheet for a life-cycle impact assessment method based on endpoint modeling version. [12] Bickel, P., Friedrich, R. (2005): Externalities of Energy Methodology 2005 Update. http://www.externe.info/ (Last access on June 2010).

Environmental and Economic Evaluation of Solar Thermal Panels using Exergy and Dimensional Analysis 1,2

2

Galina Medyna , Eric Coatanea , Dominique Millet 1 2

1

Eco-design and product optimization Group (EOP), LISMMA – SupMeca Toulon, Toulon, France

Product Development Research Group, Department of Engineering Design and Production, School of Engineering – Aalto University, Helsinki, Finland

Abstract Environmental considerations must now be taken into account more and more during the development of products and processes. As the decisions made during the early phases of development influence a large part of the final structure and cost, a quick and efficient way of evaluating environmental impact is crucial to give solid bases to the decisions. This article presents a framework for an environmental and economic evaluation that uses exergy and dimensional analysis, aimed for these early stages of design. The proposed framework is illustrated through a case study on flat solar thermal panels. Keywords: Environmental Evaluation; Dimensional Analysis; Exergy; Flat Solar Thermal Panels

1

INTRODUCTION

Environmental considerations must now be taken into account more and more during the development of products and processes. As the decisions made during the early phases of development influence a large part of the final structure and cost, a quick and efficient way of evaluating environmental impact is crucial to give solid bases to the decisions. Engineering projects cannot be mounted only studying a single facet such as environmental impacts or expected added value. Each project involves a combination of aspects that must be taken into account, requiring multidisciplinary work and adapted design aid tools. A large number of these tools though only concentrate on one aspect and require the input of data which is not available during the early stages of design. This problem was the motivation behind the development of an adapted tool, fit for the early stages of design and lightweight in terms of data and calculations. In order to evaluate environmental impact in a manner that does not necessitate a large amount of raw data and calculations, a framework based on dimensional analysis and dimensionless numbers has been constructed. The use of dimensionless numbers allows easier comparisons and scaling, reasoning by orders of magnitude and the future expansion of the framework to further fields. The current work presents the developed framework for environmental and economic aspects in Section 2. Its application to the relatively complex system of solar thermal panels is described in Section 3. Section 4 considers the further expansion of the framework and concludes on the results. 2 2.1

checking of physical equations to obtaining the description of the laws of a system through dimensionless numbers. These, as they are dimensionless, are especially useful for scaled models and comparisons, as they do not depend on the units used. Dimensional analysis relies on the notion of dimensions that are commonly defined in physics, chemistry, etc. Buckingham’s theorem [1] is often considered as one of the first and most important formulations of the bases of dimensional analysis. The application of the theorem and its streamlining have been the subject of multiple publications and works by Butterfield [2] among others. Relevant applications of dimensional analysis outside the traditional fields mentioned above are rare but there are, and have been, multiple research efforts. Works can be found in the fields of economics [3], psychophysics [4], operation management [5], etc. The framework proposed in the current work uses the bases provided by dimensional analysis for environmental and economic evaluations. As there are multiple design performances that influence an engineering project, the aim is to expand the work in the future and facilitate a multi-objective optimisation of designs. 2.2

System model for the framework

A system can be studied and modelled for dimensional analysis either through a top-down or bottom-up approach. The top-down approach considers the system as a whole first. The bottom-up approach considers each part of the system separately. For the framework, we consider a bottom-up approach where each part is an organ or a process that can be described through one or several laws following the principles of the General Design Theory [6]. Each organ or process is represented in this work as shown in Figure 1, through relevant inputs and outputs.

A DIMENSIONAL ANALYSIS FRAMEWORK Dimensional analysis

Dimensional analysis is a powerful tool, which has had numerous th applications in physics starting in the 19 century, for example in Fourier’s work on heat flow or to represent fluid dynamics with Reynolds number. Dimensional analysis is used from simple error

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_112, © Springer-Verlag Berlin Heidelberg 2011

647

648

Life Cycle Costing

Elementary organ or process

Inputs

Outputs

Paramaters (variables) Figure 1: Representation of an elementary organ or process. In order to go from elementary organs or processes to a whole system, it is necessary to combine the dimensionless numbers calculated for each part (Eq. 1).

 i total   i1  ...  i n 2.3

(1)

Environmental evaluation through exergy

The development of the dimensional analysis framework began as a search for an alternative to existing environmental assessment tools and software (SimePro, GaBi, etc.) which present such shortcomings as a lack of a uniform metric basis for comparison or expression of the different types of impacts. An approach through dimensional analysis creates such a metric space. The proposed environmental evaluation is based on exergy. The notion of exergy was first introduced as “useful energy” in the 1950s by Rant [7]. Unlike energy, it is both based on the first and second laws of thermodynamics; it can be created and destroyed. The data for exergy is based on reference states and can be found in such works as [8]. Figure 2 depicts the representation of an organ or process through its exergetic inputs and outputs. The inputs include the exergy of raw materials (Exmaterial) and the exergy supply (Exsupply). The outputs include the exergy of the products (Exproduct) and bi-products (Exbi-product), the exergy rejections to the environment calculated through the standard chemical exergy (ExEnvStand) and the exergy of mixing (Exmixing), the waste exergy not directly rejected into the environment (Exrecycling) and the exergy lost (Exlost) due to irreversibility. The explicit presentation and calculations of the notions mentioned in Figure 2 are to be found in [9]. Each organ, as defined in Section 2.2, is represented as shown in Figure 2.

Exmaterial Exsupply

Organ or process

Exproduct Exbi-product ExEnvStand Exmixing Exrecycling Exlost

Figure 2: Exergetic inputs and outputs at the level of an organ or process for environmental analysis. Three dimensionless parameters have been created based on the inputs and outputs indicated for each organ or process. Two of the dimensionless parameters, ΠPECE (Eq. 2) and ΠMRCE (Eq. 3), are efficiency indicators and the aim should be to increase them, while the third parameter, ΠEIE (Eq. 4), is an indicator of emissions and should be decreased.

Π PECE =

Ex product + Ex bi-product

Π MRCE =

Ex materials + Ex supply

Ex product +Ex EnvStand Ex materials +Ex supply -Ex recycling -Ex bi-product

(2)

(3)

Π EIE =

Ex mixing Ex materials + Ex supply - Ex recycling - Ex bi-product

(4)

The proposed dimensionless numbers have been tested against a classic LCA Eco-Indicator 99 (H) approach [9] as well as a Cumulative Exergy Demand (CExD) approach [10] for a simple foundry project. The studies were performed on two manufacturing methods for a part of a pressure regulator composed of stainless steel. The results of the exergetic approach were comparable to those found using the LCA EI99 and CExD approaches in terms of environmental impact but could not be compared number to number as the specific impact categories are different for each indicator. The case study involving flat solar thermal panels in Section 3, and in the long run, photovoltaic panels, is much more complex as a large number of organs is involved and the data is less readily available. 2.4

Economic considerations

Applications of dimensional analysis to economy have been proposed through such works as [3]. There have been a limited number of practical applications using the notion of dimensionless numbers or parameters, restricted mainly to ratios such as debt/GDP. Indeed, most of the economic evaluations done through dimensional analysis generate parameters that rely on a time factor -1 -1 with the final dimension of T , years for example. The proposed application of dimensional analysis is both based on economic and exergetic aspects. A previous effort to link the economic and exergetic aspects through dimensional analysis for the purpose of the framework can be found in [11], the current proposition holds the same spirit of seeking cost drivers, but has been reworked. As shown in Figure 3, the data necessary for the economic evaluation both covers the elementary organ or process as well as the whole system.

Exmaterial Exsupply Cmaterial Csupply

Organ or process

Exproduct Cproduct Gproduct

Exsystem Csystem Gsystem

System

Figure 3 : Input and outputs necessary for the economic evaluation using the dimensional analysis framework. Cmaterial, Csupply, Cproduct and Csystem represent the cost of the investments made for the materials, energy supply, final product and for the whole system, respectively. To simplify calculations, all the costs are converted to euros. Gproduct and Gsystem represent the expected gain from the part considered and from the whole system. For the current calculations, the expected gain is represented in a point system where the expected gain from the whole system is evaluated at 100 points. The exergetic data (Exmaterial, Exsupply, Exproduct, Exsystem) is the same as for the environmental evaluation, Exsystem being the sum of the different Exproduct data. The aim of this economic evaluation is not to give a full overview of every economic aspect of a project but to create and test interactions among dimensionless numbers coming from different fields. In this mind frame, three dimensionless parameters were created to represent the general economic situation of a project. The first parameter, ΠExC (Eq. 5), takes into account both how the material and resources are used to make the product and how

Life Cycle Costing

649

much is invested in them. The closest the parameter is to 1, the fewer the losses can be expected.

Π ExC =

Ex product

Cproduct

 Ex material +Ex supply Cmaterial +Csupply

(5)

Two of the dimensionless parameters represent cost drivers, sections of a system which benefit from high investments, generally justified by a high functional importance. ΠECD (Eq. 6) provides information on the raw material and energy investment whereas ΠGCD (Eq. 7) focuses on the expected gain to come from the product. Looking at the order of magnitude of the cost driver dimensionless parameters for a single part provides information on whether the costs are well sectioned.

Ex product Cproduct Π ECD =  Ex system Csystem

(6)

G product Cproduct  G system Csystem

(7)

Π GCD =

 Exinput     C product 

Ex product



1 Exinput  1 C product

(11)

Given the structure of the proposed dimensionless parameters, an interaction between the exergetic input and the gain is observed through the interactions between ΠECD and ΠGCD (Eq. 12).

 Ex product     G product 

C product

1 Ex product   1 G product

(12)

The aim of the study of interactions among the dimensionless parameters is to provide a simple way of representing the influences one variable has on others. Figure 4 is an example of a possible representation of the interactions through a graph with some major interactions among the parameters.

The current dimensionless parameters do not take into account the costs and expected gain obtained through recycling and bi-product schemes. Should these prove to be important, they can be incorporated into the dimensionless parameters in a similar manner as in the ones for the environmental evaluation. 2.5

Further development interactions

of

the

approach

through

The work of Bashkar and Nigam [12] showed the possible interactions between variables inside a single dimensionless number or in multiple dimensionless numbers. When working with multiple disciplines and fields, the number of variables increases and it can be difficult to understand all the implications when one of them evolves. In the example of an environmental and economic evaluation, the complexity of the variables is limited but the proposed framework is being developed in order to be expanded in future works. The interaction between two dimensionless parameters, given that a common variable exists, is done through partial derivatives (Eq. 8). The evolution can be assessed as the dimensionless parameters are considered constant, a property which also makes similitude studies possible. xc

 yi  yi xc  1  yi xc  y   1 i    y j xc   2  y j xc  2 y j  y j 

y j   j  ( xr  xc 2  ...)

As the number of fields explored through the framework increases, the importance of the representation can be expected to become more complex. The final part of Section 3.3 illustrates the practical application of such a graph. 3

(8)

given that the two dimensionless parameters are written in the form in Eq. 9 and Eq. 10.

yi   i  ( x1  xc 1  ...)

Figure 4: Representation of the interactions among the different dimensionless parameters.

(9)

3.1 (10)

As an example, the interaction between the exergetic resources and the linked costs is then as shown in Eq. 11 (Exinput represents both the material and energy supply). The result of -1 shows that if the final product stays the same but the material and energy resources increase, the final cost of the product should be decreased for the dimensionless parameters to stay the same and therefore for the project to have the same final outcome.

CASE STUDY – SOLAR THERMAL PANELS

The following case study is part of a larger comparative study, using the dimensional analysis framework, of the use of solar thermal panels, photovoltaic panels as well as regular grid electricity in a family home in the Helsinki area. Section 3.1 provides general information on the location of the study and the house considered in the full final study. The information necessary for the present work only concerns the flat solar thermal panels. A family home in the Helsinki area

The considered home is a family home built in the Helsinki area in Finland. The average annual solar radiation in the area is of 940 2 hWh/m but the amount of sunlight greatly varies with the time of year. The months of May, June and July represent the peak of 2 radiation with on average 160 to 170 kWh/m per month whereas the autumn and winter months between October and February only 2 see on average 30 kWh/m per month [13]. 2

2

The home has a usable roof space of 40m , which represents 10m per person for a family of four. Given the size of a single solar thermal panel (1.2m*2.475m) [14], thirteen panels can be installed

650

Life Cycle Costing

on the roof. The case study in this is not comparative but rather illustrative; all the calculations are performed for a single panel. 3.2

Figure 6: Data collected for an environmental evaluation for the casing of a panel.

Solar thermal panels model

The solar panels considered are made of the following organs and processes with the main materials and processes involved indicated in parentheses:

ΠPECE

ΠMRCE

ΠEIE

Glazing

1

1

0



Glazing (low-iron tempered glass)

Tubes

0.93

0.98

~10



Tubes (copper, cut, soldered)

Fins

0.90

1 (0.9998)

~10



Fins (aluminium, cut, glued)

Insulation

0.89

0.99

~10



Insulation (fibreglass, cut, glued)

Casing

0.97

1 (0.999998)

~10



Casing (aluminium, cut, soldered)

The study is limited to the preparation and assembly stage performed by the company selling the final panels. Some components are delivered ready to use, such as the glazing, while others need to be prepared as they are easy to work, such as the insulation or casing. The exergetic study takes into account the raw materials and their extraction but not the different energetic inputs and material losses that take place during the production stages before and after the preparation and assembly. The position of the different parts is shown in Figure 5.

-2 -5 -3 -7

Table 1: Environmental evaluation dimensionless parameters calculated for a flat solar thermal panel. Table 1 contains the processed environmental evaluation data linked to the different organs of a panel. As the glazing was acquired ready to use, its resource uses and environmental impacts are considered to be non-existent as its Exmaterials is the same as its Exproduct. The choice of the stage to study also has an impact on the results of ΠMRCE, the amount of material which is lost as well as the amount of energy provided to obtain the final part are low. In the studies [9] and [10] the results vary much more given the fact that foundry processes utilise large energetic inputs and produce scraps. Similarly to Figure 6, Figure 7 shows the data necessary for an economic evaluation for the same casing. Some of the data is same as for the environmental evaluation.

Exmaterial = 80*106 kJ Exsupply = 190 kJ Cmaterial = 164 € Csupply = 0.121 €

Casing (material, cutting, soldering)

Exproduct = 76*106 kJ Cproduct = 132 € Gproduct = 10 System

Exsystem = 77*106 kJ Csystem = 1125 € Gsystem = 100

Figure 7: Data collected for an economic evaluation of the casing of a panel. Figure 5: Components and their position on a flat solar thermal panel [14]. For the sake of length, the details of the components of each organ are not specified; the author should be contacted to obtain further information. 3.3

Application of the framework to the panels

Each organ is modelled as shown in sections 2.3 and 2.4 and that is all the necessary data for the calculations. Figure 6 represents the example of the casing for an environmental evaluation. The exergetic data was calculated based on a 3mm aluminium sheet that was cut to the appropriate sizes and soldered to form the final casing. The original aluminium sheets can be cut to only have a 5% material loss, of that material 35% can go directly to a bi-product, 45% is recycled otherwise and the rest is considered irrecoverable scraps.

Exmaterial = 80*106 kJ Exsupply = 190 kJ

Casing (material, cutting,soldering)

Exproduct = 76*106 kJ Exbi-product = 2*106 kJ ExEnvStand =8*105 kJ Exmixing = 38 kJ Exrecycling = 1.4*106 kJ Exlost = 0 J

The results of the input of the data collected into the economic evaluation dimensionless numbers are provided in Table 2. Once again, the result of 1 for the ΠExC is due to the fact that the part is considered to be ready to be used. The order of magnitude of the dimensionless parameters ΠECD and ΠGCD are different for all the parts with ΠECD always being lower than ΠGCD except for the casing. The results mean that for all the parts except for the casing the relative exergetic content is lower than the expected gain.

Glazing

ΠExC

ΠECD

1

~10

-5

ΠGCD ~10

-1

~10

-1

Tubes

0.78

~10

-6

Fins

0.72

~10

-4

~10

-2

~10

-7

~10

-3

~10

-1

~10

-2

Insulation Casing

0.74 0.75

Table 2: Economic evaluation dimensionless parameters calculated for a flat solar thermal panel. The interactions presented in Section 2.5 show that if the gain linked to a product is increased, at constant product cost, the total exergetic input will decrease while the exergy of the sole product will increase. The information does not provide further input as to which variable should be increased or decreased in order to modify

Life Cycle Costing the values of the dimensionless numbers. This aspect must be developed as it responds to a need during the development of artefacts, indeed the dimensionless parameters should not be kept constant, as this would mean that the project is frozen in one state. 4

The tool, in its current state, necessitates, as with other tools, an understanding of the different variables linked to the representations. It is essential for both the initial data gathering and the interpretation of the results. No weights have been added to the calculations making the interpretations simple to understand, should there be a requirement for weighted means, the calculations can be easily adapted. The goal for the dimensional analysis framework is to provide a lightweight tool for the early stages of design. Currently the calculations are extremely rapid; the gathering of the necessary data for the calculations represents a large portion of the work. The main difficulty resides in the fact that the chemical composition of many components is not known and needs to be approximated. The data on the exergy of chemical compounds is extremely up to date and often covering multiple regions. Future development of the framework

The next field considered for the expansion of the framework is risk, defined as the “possibility that a requirement is not met”. This field was chosen as risk often plays an important role in engineering projects and there are very few, if any, defined dimensions which are associated with the different aspects. Working with such a notion is expected to provide further material as to the limits of a framework that uses dimensional analysis. Literature on risk and the given definition shows that the main aspect is the mitigation of risk. Mitigation includes cost and investment notions which could provide the link towards the other proposed dimensionless numbers and come expand the interaction graph presented in Figure 4. As pointed out in Section 3.3 there is a need to represent the interactions among variables both for constant and variable dimensionless parameters as both have distinct meanings for a project. The expanding nature of the framework also means that perhaps different representations will be explored later on to fully adapt to the needs to designers to facilitate their work, especially during the crucial first phases of development of an artefact. 5

ACKNOWLEDGMENTS

The author wishes to acknowledge the Product Development Research Group at the Department of Engineering Design and Manufacturing at Aalto University – School of Science and Technology for the contribution to the current work and the thesis. 6 [1]

[2]

Butterfield, R. (2001) Dimensional analysis Revisited, Institute of Mechanical Engineers, 215 (11), pp. 1365-1375.

[3]

De Jong, F.J. (1967) Dimensional Analysis for Economists. North-Holland Publishing Company, Amsterdam.

[4]

Marinov, S.A. (2001) Notes on the use of dimensional analysis in psychophysics, 17th Annual Meeting of the International Society for Psychophysics, Leipzig, Germany.

[5]

Vignaux, G.A. (2001) Some examples of dimensional analysis in operations research and statistics, in: Proceedings of the 4th International Workshop on Similarity Methods, University of Stuttgart, Germany, pp. 247-265.

[6]

Tomiyama, T. (1980) General design theory and its application to design process, University of Tokyo, Japan.

[7]

Rant, Z. (1956) Exergy, a new word for technical available work, Forschungenim Ingenieurwesen (in German), 22(1), pp. 36-37.

[8]

Szagut, J., Morris, D.R. and Steward, F.R. (1988) Exergy Analysis of Thermal, Chemical and Metallurgical Processes, Hemisphere Publishing, New York, NY.

[9]

Medyna, G., Nordlund, H. and Coatanea, E. (2008) Study of an exergy method for environmental evaluation assessment in the early design phase using comparative LCA and exergy approach, International Journal of Design Engineering, 2(3), pp.320-345.

DISCUSSION - CONCLUSION

Section 3 presented the results for an illustrative study of a flat solar thermal panel with indications on the expected and needed developments linked to the proposed framework. A comparative study of a two or more solutions can provide more information, showing which solution is the best, both on single parts and overall. The next case study covering both solar thermal panels and photovoltaic panels will serve as a basis for such a comparative study.

4.1

651

REFERENCES Buckingham, E. (1914) On Physically Similar Systems: Illustrations of the Use of Dimensional Analysis, Physical Review, 4, pp. 345-376.

[10] Medyna, G., Coatanea, E. and Millet, D. (2009) Comparative study of environmental evaluation assessment using exergetic LCA implemented in existing software and a novel exergetic approach during the early design phase, 2009 ICED conference, Stanford, CA, USA. [11]

Medyna, G. and Coatanea, E. (2010) Decision making and value considerations during the early stages of engineering design, 20th CIRP Design Conference, Nantes, France.

[12]

Bashkar, R. And Nigam, A. (1990) Qualitative physics using dimensional analysis, Artificial Intelligence, 45, pp. 73-111.

[13]

Solar radiation energy in Finland http://www.groundenergy.fi/index.php?pid=108&lg=en_au rinko, last retrieved November 2010.

[14]

Thermo-Dynamics – G series solar panels, http://www.thermodynamics.com/technical_specs/G_series_technical.html, last retrieved November 2010.

Implications of Material Flow Cost Accounting for Life Cycle Engineering 1,2

2

3

4

Tobias Viere , Martina Prox , Andreas Möller , Mario Schmidt 1

Centre for Sustainability Management (CSM), Leuphana University Lüneburg, Germany 2

3

ifu Institute for Environmental Informatics Hamburg GmbH, Hamburg, Germany

Institute for Environmental Communication (infu), Leuphana University Lüneburg, Germany 4

Institute for Industrial Ecology, University of Applied Sciences, Pforzheim, Germany

Abstract This paper describes the basic idea of Material Flow Cost Accounting (MFCA) and explores its usefulness for environmental and life cycle engineering. It argues that a better understanding and assessment of costs related to waste flows incentivizes engineers as well as managers to constantly increase resource and energy efficiency. The paper proceeds to explore MFCA beyond its current methodological limitations by highlighting its potential benefits for life cycle and carbon footprint assessments as well as its usefulness for assessing the financial and environmental consequences of material flow loops in production. Keywords: Material Flow Cost Accounting; Life Cycle Engineering; Energy and Resource Efficiency

1

INTRODUCTION

Material flow cost accounting (MFCA) was developed in the German speaking countries in the late 1990s under several denominations such as ‘Reststoffkosten’ (remnant/leftover costs) [1] or ‘Flusskostenrechnung’ (flow cost accounting) [2, 3]. On an international level, MFCA is considered as one specific method of Environmental Management Accounting [4, 5]. Early after its invention the method was popularized in Japan where it is most widely disseminated, standardized and institutionalized [6, 7, 8]. Japan is also the driving force behind the international standardisaton of MFCA within the ISO 14000 group of environmental standards. An ISO 14051 on MFCA is close to its final release [9, 10]. The quantification and visualization of material losses is the overall objective of MFCA and leads to a better consideration of wasteinduced inefficiencies in business decision making. The basic approach is illustrated in Figure 1. Figure 1 a) depicts physical flows of a production process, Figure 1 b) the consequent cost assessment according to MFCA. The crucial difference to conventional cost accounting is that material and other costs of a process are not only allocated to products, but also to material losses, i.e. product-related waste. Other than conventional cost accounting, MFCA treats material loss like a cost object. It assumes physical causalities and a linear relationship of inputs and outputs: a reduction of material loss leads to a reduction of input material demand. The result of the MFCA calculation in Figure 1 can be interpreted as follows: If the material loss was eliminated completely, production costs could be reduced by 150 €. Whether it is actually feasible from a technical perspective to eliminate material loss to zero is not part of MFCA. Thus the MFCA figures indicate a ‘hypothetical inefficiency’. Nevertheless, such figures provide a strong incentive for sound and focused waste minimization measures. In conventional cost accounting wastage is often assessed by disposal costs only or lumped into general overhead [11]. MFCA visualizes the potential consequences of wasteful resource use and thus complements conventional cost, efficiency, and

productivity analysis. A similar approach is followed in quality management by addressing failure cost [12, 13]. The failure cost concept includes only those material losses that are caused by products not fulfilling quality requirements, though. MFCA includes all types of waste, e.g. remnants and even emissions. a)

b)

Figure 1: Basic MFCA approach. 2

MFCA BENEFITS AND LIMITATIONS

MFCA is likely to support the work of environmental engineers and managers by combining environmental goals (waste minimization) and economic consequences in a simple manner. Therefore it serves as starting point for more comprehensive environmental measures and environmental management accounting. Various case studies, e.g. in the ISO 14051 annex, prove the MFCA applicability even in small and medium-sized companies in

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_113, © Springer-Verlag Berlin Heidelberg 2011

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developing countries [9]. However, the simplicity of the approach also implies methodological criticism: 

MFCA is restricted to one (arbitrary) allocation rule, the mass ratio. Neither from an environmental / life cycle engineering perspective nor from an accounting perspective, is such restriction appropriate. In life cycle assessment, for instance, allocation might be based on mass, energy content, exergy, market price etc. while cost accounting requires different allocation keys in order to reflect cause and effect.



A simplistic MFCA approach does not properly treat material and recycling loops within production. Put simply, it does not matter from a MFCA perspective whether a material is processed straight-forward into a product or recycled several times as long as no material loss occurs.



From an environmental point of view, many MFCA examples might be furthermore criticized for its economic focus, i.e. environmental issues have no intrinsic importance within the method. Only material and energy flows with direct economic relevance are taken into account while others, such as air emissions or waste water, are not included. The approach is furthermore analyzing company sites or production lines without including related environmental systems, e.g. life cycles or ecosystems.

The international standardization process on MFCA has started to address these critical issues partially. In the following, MFCA is discussed in the contexts of Life Cycle Assessment (LCA) and of internal material loops. Both fields of application are not within the scope of conventional MFCA, but likely to increase the benefits of the method in a life cycle engineering context. 3

MFCA AND LCA/CARBON FOOTPRINTING

A Life Cycle Assessment (LCA) is defined as ‘the compilation and evaluation of the inputs, outputs and the potential environmental impacts of a product system throughout its life cycle’ [14]. At first glance, material flow cost accounting (MFCA) has nothing in common with LCA. While the latter focuses on products and the whole life cycle, MFCA has been developed to visualize the cost of inefficiencies in production, in particular the costs of wasted materials. On second sight, though, it becomes obvious that LCA and MFCA share some common objectives if applied in a business context. Some surveys suggest that the majority of drivers and applications of LCA in companies are related to internal decision making rather than external information management and that companies’ decision to apply LCA is not purely driven by environmental awareness, but also by cost saving opportunities and cost avoidance in the future [15, 16]. Vice versa, despite the main drive of MFCA is cost reduction, it leads to ecological implications as well. The Sankey diagram in Figure 2 shows an extension of the MFCA assessment depicted in Figure 1. In addition to the monetary valuation of material and energy flows, the assessment shows material and energy flow related carbon footprints (hypothetical figures) and their assignment to product and material loss. For reasons of simplification carbon footprints - expressed as Global Warming Potential (GWP) in kg CO2-equivalents - are considered here as one part of a LCA, despite knowing that the topic is also discussed separately and with great international attention. The MFCA reasoning implies that less material loss will result in less material and energy input and thus a reduced overall carbon footprint.

Figure 2: MFCA-based carbon footprint assessment. The capability of MFCA becomes even more evident if it is used to analyze not just one process, but a whole system of processes, e.g. a production plant, a supply chain or even a whole life cycle model. In many cases, an efficiency increase in a downstream process causes huge financial savings and environmental improvements upstream, a fact that is well known and has for instance inspired concepts like MIPS (Material Input Per Service unit [17]). From a resource efficiency point of view, life cycle inventories do usually not depict an ideal state of a product under examination. Instead, the status quo including waste flows and other potential inefficiencies is examined and analyzed. This might than be followed by a (qualitative) improvement assessment. MFCA can contribute to LCA based improvement assessments by a systematic quantification and visualization of wastage impact on upstream and downstream processes, physical flows, environmental impacts and costs. Basically, using MFCA in LCA improvement assessment means to define material loss as by-product. The system under examination thus becomes a multi-product system and requires allocation rules to distinguish the contribution of each product. There is a crucial difference to ordinary allocation in LCA in terms of usage. In conventional LCA, allocation is used to subtract and exclude the flows and impacts related to a by-product from the system under examination. In an MFCA-based improvement assessment the allocation does not lead to exclusion, but to a breakdown of the overall results into product vs. material loss related impacts within the examined system. The benefit of using MFCA for LCA is constituted by the improved consideration of inefficiencies within the system under examination and the consequent identification of options to reduce these inefficiencies in order to reduce environmental impacts and enhance economic performance. This can be exemplified by looking at LCA studies on coffee conducted by Diers et al. [18] and Salomone [19]. The authors of both papers assessed the life cycle of coffee and mentioned several options for improvement. Besides coffee cultivation, coffee consumption and particularly the energy required to brew coffee plays an important role in both LCA studies. However, another aspect of coffee consumption is not getting much attention: On average, consumers pour away one cup of coffee per can of brewed coffee, which equals wastage of roughly 20% [20]. From a MFCA point of view the poured away coffee is of huge importance. If consumers brew exactly as much coffee as they like to drink, the inputs of coffee brewing such as coffee powder, water and electric energy would be immediately cut by 20%. Even more important, corresponding flows in upstream steps of the life cycle would be reduced, too, e.g. fertilizer and land use in cultivation or fuel consumption in overseas transportation. A MFCA-based improvement assessment in LCA would not only look at this inefficiency in the consumption stage, but also at inefficiencies at other life cycle stages, for instance the commonly occurring overfertilization in coffee cultivation, which leads to unnecessary

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environmental impacts and higher production costs for the whole coffee supply chain [21]. LCA can benefit from integrating MFCA methodology as it reinforces improvement assessment and thereby increases the relevance for business decision making. The consequent consideration, quantification and visualization of wastage and inefficiencies support life cycle engineers and other decision makers in tackling such problems. In an ideal situation diminishing inefficiencies in a product life cycle results in less environmental harm and greater financial benefits at the same time. However, even a highly efficient life cycle might still be a threat to sustainable development. The overall assessment of ecological effectiveness remains a vital task of LCA. In this respect, MFCA is a subordinated methodology to LCA. Möller and Prox [22] took a different approach by placing MFCA at the starting point of all activities in the field of material flow analysis, LCA and related cost accounting approaches. They propose to start on a production improvement level using MFCA. Based on experiential learning their approach subsequently expands the analysis to value chains and finally full life cycle assessments. From a business perspective this might well be a useful “road map” to follow as it increases the complexity and scope of a company’s environmental improvement processes stepwise. Eventually, it does not matter whether MFCA is a subordinate to LCA or vice versa as long as both tools and their combination provide useful information for life cycle engineers and environmental managers to improve the environmental and financial performance of their company and their products’ life cycles. 4

MFCA AND MATERIAL LOOPS

Material loops and recycling processes are eminent in various industries and production systems. In the following, the impacts of material loops on environmental and financial performance and the potential contribution of MFCA for assessing these impacts are elaborated. 4.1 Environmental and financial impacts of material loops In complex and highly integrated chemical production systems the proper assessment of such loops is of uttermost importance for reaching higher levels of resource efficiency and competitiveness [23]. In energy-intensive industries the importance of material loops is very obvious, too. Figure 3 depicts the example of an aluminum rolling plant (the name is not disclosed for confidentiality reasons).

Main material inputs are aluminum ingots from smelteries and aluminum scrap. Purchased ingots as well as ingots from melting external and internal process scrap are processed through sawing and scalping, hot rolling and cold rolling to produce hot and cold aluminum band which is sold to customers for instance from automotive and packaging industries. Given the huge energy demand of the rolling plant, life cycle engineers would certainly assess energy efficiency measures in order to improve the company’s performance as well as its carbon footprint. Another and perhaps even more important aspect is the production system’s material and resource efficiency, though. Almost every process generates aluminum process scrap as a ‘byproduct’. While the maximum annual throughput of aluminum in the system is 1.61 million tons (sawing and scalping process), the total annual generation of aluminum process scrap is 0.45 million tons. Hence, about a quarter of all material is processed several times through the system and requires energy input and other process related effort each time. Assuming that no aluminum scrap was produced, the demand for electric energy would be reduced by 15% and the demand for natural gas by 20% approximately. This would equal annual energy cost savings well above 10 million Euros. Thus, higher levels of energy efficiency can be reached by reducing material wastage and the consequent recycling loops. Furthermore, material costs and reduction of environmental impacts in the supply chain could be realized. If less or no process scrap was generated, less throughput of aluminum would be required within the system. Assuming that the ratio of melted aluminum scrap and ingots into Sawing and Scalping is required to stay constant, the reduced total throughput means less ingots and slightly more external scrap as a substitute for internal scrap. As external scrap is much cheaper than ingots and has a lower environmental footprint, eco-efficiency would be improved further. A reduction of internal scrap to zero is a hypothetical assumption. At the same time it provides strong environmental and financial incentives to strive for a zero waste scenario. The case of the rolling mill highlights the importance of an integrated approach to material and energy efficiency and related costs. Over and above it reveals the crucial impact of material loops on overall efficiency. From a conventional MFCA perspective, the example includes only minor material losses, namely the dross from Melting. How to calculate and assess the additional energy demand and additional material and processing costs caused by internal material loops is not sufficiently described in MFCA guidelines and case studies.

Figure 3: Material and energy flows - aluminum rolling plant.

Life Cycle Costing 4.2 MFCA assessment of material loops

655 a)

A simple case of a material loop within a production system is depicted in Figure 4 a). From a MFCA perspective the system produces exactly one product and no material loss. Hence all costs are assigned to the product analog to conventional cost accounting (Figure 4 b). On a single process level, though, a MFCA analysis reveals a material loss in the production process that is later regained in the recycling process. This material loop causes additional energy demand and other expenses in both, the production and the recycling process. Thus MFCA needs to compute the additional expense caused by the material loop as an indicator for potential efficiency gains without a loop, Two methods to compute the material loop related expense are further discussed: Modeling a zero loss scenario and breaking the loop after recycling. In a zero loss scenario it is assumed that the production process converts all material input into product without any material loss. In this case, no recycling process expenses occur and the production process expenses are reduced in proportion to reduced throughput. Figure 4 c) depicts this approach and reveals a saving potential of 100 €, i.e. 12.5% of total production system expense. Another method is to break the loop after recycling which allows assessing the recycled material by its substitution value (Figure 4 d). The raw material unit price in the given example is 5 €/kg. The recycled material thus has a substituting value of 125 € assuming that there is no quality difference between recycled and raw material. This information is used to conduct a conventional MFCA computation for the production process. Expenses of the production process sums up to 875 € (raw material, recycled material, energy and system cost) and are allocated to product and material loss according to weight (80kg:20kg). The difference of recycling process expense (225 €, including 175 € material loss and 50 € energy and system cost) and recycling process revenue (125 € recycled material value) equal the material loop loss. 5

b)

c)

DISCUSSION AND CONCLUSION

Compared to MFCA, other, more comprehensive tools and concepts are available to analyze material and energy flows within production systems and their financial and ecological consequences. For instance, the material flow network approach of Möller [24, 25] integrates a product and a process view on a material and energy flow basis and enables the use of non-linear process specifications, flexible allocation rules, and different cost accounting approaches. It requires an advanced understanding of underlying methodologies and the application of specialized software, though.

d)

To sustain MFCA as a simple, straightforward tool for environmental engineers and managers, this paper has deliberately focused on facile and feasible enhancements. Such enhancements of conventional MFCA practice are likely to support a more systematic consideration of resource efficiency aspects in product carbon footprints and life cycle assessment and enable an adequate environmental and financial assessment of material loops and internal recycling processes. MFCA is a useful tool for a rough assessment of the potential benefits of reducing, reusing and recycling wasted materials. It helps life cycle engineers and environmental managers to communicate the purpose and benefits of resource efficiency measures. Its applicability to various industries and companies of different sizes makes it a promising tool to support businesses in becoming more sustainable. Figure 4: MFCA assessment of material loops.

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REFERENCES

[1]

Fichter, K., Loew, T., Seidel, E. (1997) Betriebliche Umweltkostenrechnung – Methoden und praxisgerechte Weiterentwicklung, Springer, Berlin.

[2]

[3]

Wagner, B., Strobel, M. (1999) Kostenmanagement mit der Flusskostenrechnung, in Freimann, J. (ed) Werkzeuge erfolgreichen Umweltmanagements: Ein Kompendium für die Unternehmenspraxis, Gabler, Wiesbaden, pp. 49-70. Strobel, M., Redmann, C. (2002) Flow cost accounting, an accounting approach based on the actual flows of materials, in Bennett, M., Bouma, J.J., Wolters, T. (eds) Environmental management accounting: informational and institutional developments, Springer, Dordrecht, pp. 67-82.

[4]

Jasch, C. (2009) Environmental and Material Flow Cost Accounting: Principles and Procedures, Springer, Dordrecht.

[5]

IFAC International Federation of Accountants (eds) (2005) International Guidance Document Environmental Management Accounting, IFAC, New York.

[6]

METI Japanese Ministry of Economy, Trade and Industry (eds) (2007) Guide for Material Flow Cost Accounting, METI, Tokyo.

[7]

METI Japanese Ministry of Economy, Trade and Industry (eds) (2010) Material Flow Cost Accounting – MFCA Case Examples, METI, Tokyo.

[8]

Nakajima, M. (2009) Evolution of Accounting (MFCA): Characteristics MFCA Companies and Significance of Kansai University Review of Business 11, pp. 27-46.

[9]

ISO/DIS 14051 - Environmental management - Material flow cost accounting - General framework

Material Flow Cost on Development of Relevance of MFCA, and Commerce, No.

[10] Kokubu, K., Campos, M.K.S., Furukawa, Y., Tachikawa, H (2009) Material flow cost accounting with ISO 14051, ISO Management Systems, Jan-Feb2009, pp. 15-18. [11] Schaltegger, S., Burritt, R.L. (2000) Contemporary Environmental Accounting, Greenleaf, Sheffield. [12] Feigenbaum, A.V. (2005): Total quality control: achieving productivity, market penetration and advantage in the global th economy, 4 ed., McGraw-Hill Higher Education, London, New York. [13] Shank, J. K., Govindarajan, V. (1994) Measuring the "cost of quality": A strategic cost management perspective, Journal of Cost Management, Vol. 8, Summer, pp. 5-17. [14] ISO 14040:2006 - Environmental management - Life cycle assessment - Principles and framework. [15] Frankl, P., Rubik, F. (1999), LCA in Industry and Business Adoption Patterns, Applications and Implications, Springer, Heidelberg. [16] Frankl, P., Rubik, F. (1999), Life-cycle assessment (LCA) in business – an overview of drivers, applications, issues and future perspectives, Global Nest: the International Journal, Vol. 1, No. 3, pp. 185-194. [17] Ritthoff, M., Rott, H., Liedtke, C. (2002) Calculating MIPS – Resource productivity of products and services, Wuppertal Institute, Wuppertal. [18] Diers, A., Langowski, H.C., Pannkoke, K., Hop, R. (1999) Produkt-Ökobilanz vacuumverpackter Röstkaffee, EcoInforma Press, Bayreuth. [19] Salomone, R. (2003) Life cycle assessment applied to coffee production: investigating environmental impacts to aid

decision making for improvements at company level, Food, Agriculture & Environment, Vol. 1, No. 2, pp. 295-300. [20] International Coffee Organization (eds) (2001) Environmental issues relating to the coffee chain within a context of trade liberalization, through a life-cycle approach, ICO, London. [21] Viere, T., Schaltegger, S., von Enden, J. (2007) Using Supply Chain Information for EMA – the Case of a Vietnamese Coffee Exporter, Issues in Social and Environmental Accounting, Vol. 1, No. 2, pp. 296-310. [22] Möller, A., Prox, M. (2008) From Material Flow Cost Accounting to MFA and LCA, Proceedings of the 8th International Conference on EcoBalance, Dec. 10-12, Tokyo. [23] Viere, T., Brünner, H., Hedemann, J. (2010) Verbund Simulation – Strategic Planning and Simulation of Integrated Production Networks, Chemical Engineering & Technology, Vol. 33, No. 4, pp. 582-588. [24] Möller A. (2000) Grundlagen stoffstrombasierter Betrieblicher Umweltinformationssysteme. projekt Verlag, Bochum. [25] Möller, A., Page, B., Rolf, A., Wohlgemuth, V. (2000) Foundations and Applications of computer based Material Flow Networks for Environmental Management, in Rautenstrauch, C., Patig, S. (eds) Environmental Information Systems in Industry and Public Services, Idea Group Publishing, Hershey and London, pp. 379-396.

Aircraft Engine Component Deterioration and Life Cycle Cost Estimation 1

2

1

Yuyang Zhao , Andrew Harrison , Rajkumar Roy , Jorn Mehnen 1

1

Manufacturing Department, SAS, Cranfield University, Cranfield, MK43 0AL, UK 2

Rolls-Royce Plc, PO Box 31, Derby, DE24 8BJ, UK

Abstract Reducing the service elements of Life Cycle Cost (LCC) has become a key issue for aircraft engine manufacturers as TM more of their customers are moving to TotalCare style agreements (fixed cost per operational hour maintenance agreements). This paper makes efforts to build a link between the engine component deterioration (a key driver of LCC) and business led LCC estimation requirements. The techniques of both product and service cost estimation are firstly reviewed, followed by a summary of engine component deterioration life modeling methods. The paper concludes by giving a component deterioration driven cost estimation framework for engine life cycle. Keywords: Engine; Life Cycle Cost; Estimation; Component; Deterioration

1

INTRODUCTION

Traditionally, manufacturing companies were focusing on selling the physical products with provision of basic aftermarket services as a necessary condition of securing the sales. With ever increasing global competition as well as the demand for greater responsibilities of the manufacturer for their products throughout the product life cycle, more and more enterprises are shifting their business focuses from designing and selling physical products only to productservice packages. In addition the services’ proportion of such business models is gaining increased share within the manufacturing industry and the boundary between manufacturing and services is becoming increasingly blurred.

focused mainly on the product operation and support line maintenance, and product disposal phases of the life cycle. Early cross industry sampling showed that amongst the design community there was a general lack of appreciation of the cost of operating and maintaining for a typical long life/complex product in relation to its initial delivery cost. Figure 1 illustrates the direct cost breakdown of a typical large civil engine as seen by the operator over 25 years (excluding fuel and oil costs or inflationary/net present value adjustment).

As products move through design, introduction, growth, maturity, and retirement phases, the Life Cycle Cost (LCC), is increasingly being used when making procurement decisions at each phase of the product lifetime. The LCC is concerned with the overall cost of a product from its conception up to, and including, its disposal. Asiedu and Gu [1] divided the total product cost or LCC into four distinctive phases: (1) research and development costs; (2) production and construction costs; (3) operations and maintenance costs; (4) retirement and disposal costs. Similarly in the context of aircraft engines, a typical engine product life cycle encompasses: 

Infrastructure and Capability Investment: Design, Manufacturing, Assembly, Test, Overhaul, Disposal and so on;

Figure 1: Typical large civil engine-airline acquisition and support cost split over 25-30 years engine life span.



Product Acquisition: Research, Development, Manufacture, Test, Certification, Marketing and Sales and so on;



Product Operation and Support: Line Maintenance, Consumables inc Fuel, Disruption, Overhaul Refurbishment, Regulatory support, and so on;



Product Disposal: Resale, Depreciation, Physical disposal of parts at overhaul and whole engine at end of life.

Component manufacture dominates the initial sales costs and with spares requirements comprising anything from 30% to 50% of an overhaul invoice a focus on component acquisition and replacement cost reduction is essential. However a sole focus on component cost would leave 50% of the total cost picture un-addressed, and in the case of spares fails, it is necessary to consider the options to reduce the cause of component scrap as well as the cost of replacement. A true life cycle approach must therefore balance the costs of acquisition, operation and disposal.

The LCC is concerned with all of these cost elements. However, as extensive processes and practices already existed around the first two elements, the enhancements discussed in this paper have

In the next section, a review of the current cost approaches to cost estimating techniques applicable to whole aircraft engine LCC is

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_114, © Springer-Verlag Berlin Heidelberg 2011

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introduced. The paper then describes the typical engine component deterioration mechanisms with life prediction methods. Using the findings from both sections, the paper proposes an integrative framework for providing LCC estimation as well as maps of the different techniques that may be used at different engine life cycle stages.

generative or detailed and parametric. Evans et al. [5] further break down the cost estimating methods into ten different techniques: parametric, neural network, expert judgment, function-based, feature-based, group technology or analogy-based, generative, casebased reasoning, knowledge-based systems, and activity-based costing. The cost estimating techniques for product can be broadly classified into two major categories as many authors agree [1,3,6]

2

1. Qualitative techniques

COST ESTIMATION TECHNIQUES FOR LCC

Cost estimation is a process of predicting or forecasting the cost of a work activity or output, typically by interpreting historical data. Rush [2] has noted that traditionally there are two main estimates:(1) a first-sight estimate early on in the design process; and (2) a detailed estimate that is associated with precision costing. First-sight estimates are useful for what is often referred to as a rough order magnitude (ROM) estimate and provide useful information at an early stage of product definition but are not suitable for decisions regarding product detail. Product and service can be regarded as locating at the two ends of the engine life cycle, with disposal normally not a major cost issue. Reviewing the cost estimation techniques for both product and service is essential for LCC research, which is introduced in the next two sections. 2.1



Intuitive—estimates are based on the expert estimator’s experience.



Analogical—estimates made on the definition and the analysis of the degree of similarity between the new product and another one for which cost has been estimated in the past.

2. Quantitative techniques 

Parametric—estimates based on an analytical function of a set of parameters characterising the product, without describing it completely. These are known to be top-down applications.



Analytical—based on a detailed analysis of the work required (the elementary tasks that constitute the manufacturing process). This is also termed as bottom up techniques where the cost data are collected from the smallest component levels and aggregated to the total product level. Activity-based costing (ABC) poses an example.

Product cost estimation

There are already a lot of works considering product cost estimation as this is a primary area of interest for the both academic and industry stakeholders in the product design process. Asiedu and Gu [1] contend that there are three quantitative methods: analogybased techniques, parametric, and engineering approaches (detailed). Roy [3] identifies five main methods: traditional, parametric, feature-based, case-based reasoning, and neural networks. Newnes et al. [4] also categorize two basic cost estimating techniques: Technique Advantage

Datta [6] summarises the merits and demerits of the major estimating techniques and also highlights the applicability in terms of the different stages of a product or production lifecycle as shown in Table 1.

Limitations

Parametric

Rapidity of execution Repeatable and objective Less information required than analytic methods Good for budgetary estimates or baseline assessments

Parameters not included can become important Useful in combination with other methods CERs (Cost Estimating Relationship) are too simplistic to predict costs Uncertainties are high as CER specifications are not available Subjective adjustments Accuracy depends on similarity of items Difficult to assess effect of design change Blind to cost drivers More difficult than parametric method as this required cases database, similarity measure, adaptation functions and case indexations

Analogy

Reasonably quick and based on actual data Requires few data User knows the origin of the estimate No requirement of full understanding of problem Accurate for minor difference from analogous case

Analytical

Good for rough order magnitude estimates, in absence of adequate data More accurate than analogy and parametric methods Detailed breakdown useful for negotiation Suitable when all characteristics of product and production process are well defined

Does not handle innovative solutions Slow execution Detailed data may not be available Inappropriate for estimation at design stage

Activitybased costing

Allocates costs according to where they are incurred Improved accuracy and relevance Details the causes of costs and gives a stronger indication of potential profitability

Inaccurate allocation of overheads Time consuming Costly to implement and operate Difficulty in making it the only costing method

Expert judgment

Quick to produce and flexible Few resources in terms of time and costs Can be as accurate as other more expensive methods

Allocation of overhead is complicated Prone to bias and error Inconsistent and unstructured process Nondeterministic as each expert reaches a different estimate

Table 1: Comparison of different product cost estimating techniques [6].

Life Cycle Costing - Modelling In addition to the above techniques some relatively uncommon techniques are also in use particularly in estimating the costs of products. Feature-based costing uses relational drivers of cost, which means a direct relationship, is developed between the associated feature of a product and its cost [6]. However, no consensus is reached on what features are and such methods require large resources to implement [7]. Fuzzy logic is also a relatively new method, which applies highly sophisticated mathematical models to estimate costs, in situations where imprecision and uncertainty are very affective. This method has commonly been applied to represent vague and imprecise knowledge [7]. Harding et al. [8] proposed that, within the construction industry, neural networks offered a useful route for cost estimation at the early stages. As the system receives new information it incorporates it into the decisionmaking process [9]. However, both fuzzy logic and neural network methods are very complex and have found very little practical applications as they are considered as black box [7,9]. 2.2

Service cost estimation

There are not many research papers published in service cost estimating compared with production costing to support design. If the service can be regarded as an activity, a method called ABC (Activity-Based Costing) can be useful, particularly if expenses in indirect and support resources are high and diversity exists in products, customers and processes. But in most occasions companies have difficulty in understanding the full cost of service and this calls for exploring other cost estimation methods, which are introduced below: 1. Top-down costing Top-down costing first calculates the total costs of the service at the organisational, provider or departmental level, then disaggregates the total costs to the department or the units of services (or products) depending on the richness of available data and the homogeneity of services provided. It can be done through multiple steps, e.g., allocate costs to cost centers (e.g., support services workshop, project management), then divide the total costs of the cost centers by the number of units (e.g., spares supplied, etc.) [10]. Top-down approach is less detailed than other methods and so accuracy can suffer. Furthermore, allocation of resources can be more or less arbitrary. 2. Bottom up costing/activity-based costing The bottom up approach records resource utilisation at the individual service level, and aggregates service level utilisation data to identify the type of resources used and to measure resource utilisation in order to calculate the costs of specific services. It is particularly useful when cost data is not available from other reliable sources [11]. The disadvantages of this approach are the huge cost and long time required for costing complex services. 3. Mixed approach Mixed approaches are based partly on bottom up and partly on topdown approaches [11]. The mixed approach could avoid some of the disadvantages of both methods. A mixed method could be cheaper than using only bottom up approach and it could be more accurate than using only top-down approach because it can reflect variation in resource consumptions. Top-down costing can be used where resource variation is reasonably small, and/or when the level of aggregation is relatively high, as well as where bottom up costing would be very expensive and/or would not be worthwhile. On the other hand, bottom up costing can be used where the precision/accuracy of resource measurement is important, and data collection is feasible in an economically sensible way. Alternatively using mixed approach could suffer from the weaknesses of both methods. Local data may not be externally valid, whereas aggre-

659 gate data may not be locally representative and could over or under estimate real resource utilisation [11]. 4. Analogy-based estimates In some cases, when similar services or activities have already been valued and the unit costs calculated, information can be extracted from published reports or analysis. It may be helpful to contact the authors directly to discover more details about the costing exercise in order to assess the quality and reliability of these estimates [10]. However, published studies may suffer from weaknesses such as good internal validity and poor external validity. 5. Extrapolation based on expert opinion Although expert opinion is generally seen as the least reliable source of information about effectiveness and costs, several studies had to rely on multiple sources when assigning monetary value to resources, including expert opinion [11]. Sometimes this helps where the experts are particularly experienced in the service delivery process. 3

ENGINE COMPONENT LIFE ESTIMATION

Arguably all service support costs begin with the phenomena of component and hence system deterioration leading to costs of functionality loss avoidance or recovery. Although the majority of LCC are fixed early on in the design stage, until recently it was not possible for a designer to calculate the LCC of his or her component until after it was designed and in service. As component modeling is introduced, it is possible to predicate the cost of component ownership throughout its life cycle through evaluation in different scenarios. 3.1

Engine component deterioration

The component deterioration is the main driver for engine maintenance activities. At the design stage, the designers are already using life estimation or prediction data not only to do the functional design, but also to provide guide lifetimes for each component, or module (a combination of a lot of components). The engine’s operation and maintenance strategy, i.e. time on wing, inspection intervals, overhaul time, and so on, are largely based on the life predictions of some of the more critical components. In addition, after the engine is in service for some time, component deterioration data, such as cracking, oxidation and wear, will become available to be used to amend the previous life limits calculated at the design stage. It is necessary to point out the significant linkage between engine component deterioration and overall LCC. As the authors have illustrated in section one, the dominant proportion of the LCC occurs in the in-service maintenance stage. When an engine is on wing, only regular inspection works are required with no major issue of cost. When the engine is taken off wing and put into a maintenance workshop, this is when and where the major cost is incurred. The cost of workshop infrastructure, labour, and more importantly, the scrap and repair of the degraded components is statistically the largest proportion of an engines service cost. The maintenance free life expectation of the engine’s key components plays the pivotal role of increasing or decreasing the LCC. The maintenance free life limits are traditionally based on historical data and laboratory empirical data at the design stage. These initial limits may be amended based on developing service experience for reliability, safety or cost reasons. There is a case for developing and maintaining a closed loop life prediction model throughout the design and operational phase of the products lifespan for the benefit of both design and service support communities. The design team can give a more accurate

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initial life limit (based on previous service calibrated models) and when service team demands change, a modified life limit can be acquired quickly in days or hours rather than weeks and months.

support the trade-off of the making the engine component deterioration technical limits. Present

The common life estimation techniques are introduced in the next section. 3.2

Life estimation

Integrated Product Team

The determination of the future capability of a system to perform its function in a given state is a matter of interest, e.g. for safety reasons in critical systems, optimisation of the asset up time by providing adequate maintenance and logistical planning and consequent maximisation of revenue. This interest is also shared in a LCC context for an OEM, for example, to determine the service cost incurred by assets being operated in different scenarios under a service agreement offer.

Trade-off Designer Designer

Service

4.2

Component Model

It has been discussed that life estimation of an engine component for some typical deterioration mechanisms is possible and component models can be built to support the cost estimators. The modern gas turbine engine is a very complex system and contains thousands of components. Each of the components has its own cost of manufacturing, cost of replacement and cost of repair(s) (there may be multiple repair options available).

Model-based methods: based on the physical representation of the system and failure mode in study;



Knowledge-based methods: based on expert judgment of the system and failure mode in study;



Experience-based methods: based on failure-time data of a systems population events record;



Thermal Barrier Coating loss



Data-driven methods: based on extensive data of the system and failure mode in study.



Aerofoil oxidation, creep and fatigue



Shroud oxidation/ wear, cracking

Traditionally, these life estimation results are used to support the engine design and component life expectancy. With the life prediction methods available, it is possible to build a LCC framework based on engine component life estimation.



Sulphidation



Other deterioration mechanisms

4.1

COMPONENT DETERIORATION LCC FRAMEWORK Integrated Product Design

At present, most design processes are involving the form of Integrated Product Team (IPT) and cost engineers are involved from the beginning of a design. The cost estimator provides feedback to the designer on the estimated cost impact of design decisions. However as it has been illustrated earlier in this paper, the inservice costs are predominant in the LCC profile. In most organizations detailed knowledge of the in service cost elements of the product will be held by the service support organisation rather than the traditional cost estimator role (which tends to focus on product acquisition/production costs). The flow of this knowledge to the cost estimator is critical to a balanced LCC assessment. The present and proposed future processes are shown in Figure 2 based on the work of Thokala et al [19] which identifies the past, present and future cost estimation supported design. With the service process providing important data to improve the estimator introduced earlier, the communication between the service and design should be more efficient which enables the functionality of improving the models and generates more accurate outputs to

change

Figure 2: Integrated cost estimation.



4

Estimator

update

Estimator

A diverse number of research fields are concerning the problem of life estimation (e.g. reliability, asset management, maintenance optimisation) even thought subtitle differences can be found in the approaches taken and on the overall goal. Therefore a large suite of tested methods in different contexts for life estimation (and related subjects) is available. Several classification criteria have been used to expose the different techniques for life estimation [12-17]. This classification tends to be made based not only on the distinct characteristics of the different models but also on the model input type (e.g. type of data) representing the system in study and associated degradation mechanism, operational environment and usage conditions. Fernandes, et al [18] have classified them into the following four groups:

Future

For a given component there are still a lot of deterioration mechanisms potentially impacting different parts of the component. Take a high-pressure turbine blade as an example, the typical deterioration mechanisms are:

For each of these deterioration mechanisms, the life predication will mostly be expressed in terms of flight hours or operational cycles. Normally amongst these mechanisms, it is the one with the shortest lifetime determines the overall component life, which may in turn be the determining factor in the overall engine life between maintenance events. However not every component or every deterioration mechanism has the potential to cause the engine maintenance. There are lists of key components and key deterioration mechanisms for each engine, which dominate the statistics of engine maintenance causes. Special focus needs to be paid to those components that cause maintenance events in addition to those cost the most to maintain when the need arises. Introducing the component model, or component deterioration mechanism driven life estimation model is quite useful in the engine life cycle, not only to the design IPTs. The component model driven process interface is shown in Figure 3. In addition to the designers, the repair engineering team, the project team and Whole Engine Model (WEM) team can also use the outputs from component models to support their works.

Life Cycle Costing - Modelling

661 Recomd & Sensi

Design IPT Design Assumptions

Design IPTs

Cost Estimator

Repair Engineer

Repair Engineer

Repair Assumptions Project / WEM Target cost & rest of engine assumptions

Component Model

In-Service Engine History

Requirement Project / WEM

5 Status to target

Figure 3: Component model in LCC 4.3

It can be seen that, while costing product or services, mixing different approaches used for cost estimation is more desirable than relying on a single approach. Most of the techniques however major on retrospective approaches (basing on past historical data, similar service or equipment data) and do not relate to customer requirements for future. Opinions of subject matter experts are of significant importance in estimating costs of services. In the existing inservice costing literatures, the studies do not report the applicability of different estimating techniques at different life-cycle stages of service.

Techniques for component model and cost estimator

The major techniques for life prediction have already been summarised in section 3. Given the extensive use of lifetime data and its availability for different components (as used extensively in product reliability and safety assessments) the use of an experience-base approach should probably be considered as a baseline methodology. However for certain elements of the LCC modeling regime (repair and scrap rates for example) a more data driven approach may be feasible in later parts of the service lifecycle. The existence of an organizational knowledge base spanning multiple products or product lines and documenting various degradation mechanisms, together with their impact on different components/systems, makes a knowledge-based approach appear to be viable. This may limit analysis to a more qualitative rather than quantitative assessment. Model-based approaches are certainly the most attractive. These can provide a “transparent” output, based on the physics of the phenomena being modelled and also, for example, a more accurate quantification of the parameters with the highest impact in service cost. Given the nature of a model-based approach model tailoring or calibration may be needed to capture the complexity, subtleties or interactions of different components and contexts. Computationally demanding modelling techniques may well be needed. In terms of building a cost estimator, the described studies identified LCC research used in product and service cost functions across a spread of industry sectors. The different estimation techniques in service, product and performance-based contract costs are already reviewed. The best practical choice in any situation will be guided by a number of criteria [6]:

DISCUSSION AND FUTURE WORK

Based on both the cost estimation and component life estimation techniques reviewed, this authors make efforts to build a link between the aircraft engine component deterioration and LCC estimation to support both design, service and support, repair, project management, and other relevant departments. The importance of service data feedback to the service cost estimator, in order to improve the estimation is also discussed. As the gas turbine engine is a complicated system with thousands of components and each component has a number of deterioration mechanisms, life prediction could be a massively complex task. However, the engine typically has a subset of components that dominate service cost causes and expenditure. Therefore it will be possible to start from those key components, study their typical deterioration mechanisms, and conduct the necessary life prediction modelling work. For the cost modelling technique, the guide criteria to be referenced when choosing the best practice are identified. The optimum technique chosen may vary based on the nature and context of the work it is going to support. In most case, data availability is the most crucial criterion as it is quite common that the model developers find themselves short of historical data, especially for new engine designs, new components, or new technology applications. Expert’s opinions could be quite important in this scenario. From a long-term view, the combination of the component life estimation and cost estimation has a good potential to contribute to a better LCC calculation and reduction. A more accurate estimation and more efficient cost estimating processes could be approached. 6

ACKNOWLEDGMENTS

This research has been performed within the research project ‘Strategic Investment in LOw-Carbon Engine Technology’, which is jointly funded by Rolls-Royce and Technology Strategy Board UK. The authors would like to extend sincere thanks to all who contributed.



The purpose of costing (feasibility study or bidding for a contract);



The type and complexity of the service (type of offering);

7



The precision required; and

[1]



The data availability.

Asiedu, Y., Gu, P. (1998): Product life cycle cost analysis: state of the art review, International Journal of Production Research, 36/4: 883–908.

[2]

Rush, C., Roy, R. (2000): Analysis of cost estimating processes used within a concurrent engineering environment throughout a product life cycle, CE2000 Conference (Lyon, France, 17–20 July).

[3]

R. Roy (2003): Cost engineering: why, what and how? Decision Engineering Report Series, no. Issue: 1, UK, Cranfield University.

In the context of engine manufacturing industry, the data availability sometimes plays a vital role in choosing the right technique to build a LCC model, although the rest of the list should also be considered. It is a typical scenario that the model developers find themselves short of historical data, especially for a new product, new components, or a new technology. In this case, quantitative approaches are adopted including expert’s opinion. With the data flows in after the product is in service, it will be possible to amend the model to give a more accurate output.

REFERENCES

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[4]

Newnes, L.B., Mileham, A.R., Cheung, W.M., Marsh, R., Lanham, J.D., Saravi, M.E., Bradbery, R.W. (2008): Predicting the whole-life cost of a product at the conceptual design stage, Journal of Engineering Design, 19/2: 99–112.

[5]

Evans, D.K., Lanham, J.D., Marsh, R. (2006): Cost Estimation Method Selection: Matching User Requirements and Knowledge Availability to Methods, University of the West of England, Bristol..

[6]

Datta, P.P., Roy, R. (2010): Cost modelling techniques for availability type service support contracts: A literature review and empirical study. CIRP Journal of Manufacturing Science and Technology, doi:10.1016/j.cirpj.2010.07.003.

[7]

Curran, R., Raghunathan, S., Price, M. (2004): Review of aerospace engineering cost modelling: the genetic causal approach, Progress in Aerospace Sciences, 40:487–534.

[8]

Harding, A., Lowe, D., Emsley, M., Hickson, A., Duff, R. (1999): The role of neural networks in early stage cost estimation in the 21st century, The Quantitative and qualitative cost estimating for engineering design (COBRA).

[9]

Boussabaine, A., Kirkham, R. (2004): Whole Life-cycle Costing: Risk and Risk Responses, 1st edition. Blackwell Publishing, London.

[10]

Beecham, J. (1995): Collecting and estimating costs, in Knapp M, (Ed.) The economic evaluation of mental health care. Arena. Ashgate Publishing Limited,

[11]

Gyldmark, M. (1995): A review of cost studies of intensive care units: problems with the cost concept, Critical Care Medicine, 23/5: 964–972.

[12]

Byington, C. S., Roemer, M. J. and Galie, T. (2002): Prognostic enhancements to diagnostic systems for improved condition-based maintenance, IEEE Aerospace Conference, Vol. 6, Big Sky, Montana, USA, pp. 2815-2824.

[13]

Bagul, Y. G., Zeid, I. and Kamarthi, S. V. (2009): Overview of remaining useful life methodologies, 2008 ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC 2008, Vol. 3, 3 August 2008 through 6 August 2008, New York City, NY, pp. 1391.

[14]

Dragomir, O. E., Gouriveau, R., Dragomir, F., Minca, E. and Zerhouni, N. (2009): Review of Prognostic Problem in Condition-Based Maintenance, European Control Conference 2009 - ECC’09, 2009, Budapest, Hungary,

[15]

Gorjian, N., Ma, L., Mittinty, M., Yarlagadda, P. and Sun, Y. (2009): A review on degradation models in reliability analysis, 4th World Congress on Engineering Asset Management, 2830 September 2009, Athens, Greece,

[16]

Luo, J., Namburu, M., Pattipati, K., Qiao, L., Kawamoto, M. and Chigusa, S. (2003): Model-based Prognostic Techniques, IEEE Systems Readiness Technology Conference (AUTOTESTCON 2003), 22 September 2003 through 25 September 2003, Anaheim, CA, pp. 330.

[17]

Schwabacher, M. A. (2005): A survey of data-driven prognostics, InfoTech at Aerospace: Advancing Contemporary Aerospace Technologies and Their Integration, Vol. 2, 26 September 2005 through 29 September 2005, Arlington, VA, pp. 887

[18]

Pedro Fernandes, Rajkumar Roy, Andrew Harrison (2011): An overview on degradation modelling for service cost prediction. Submitted to 3rd CIRP International Conference on Industrial Product Service Systems, May 5th- 6th, 2011 in Braunschweig, Germany.

[19]

Thokala, P, Scanlan, J, and Chipperfield, A (2009): Life cycle cost modeling as an aircraft design support tool, Proc. ImechE Vol.224 Part G: J. Aerospace Engineering, pp 477 -488.

Life Cycle Cost Estimation using a Modeling Tool for the Design of Control Systems 1

Hitoshi Komoto , Tetsuo Tomiyama 1 2

2

National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan

Intelligent Mechanical Systems Group, Department of BioMechanical Engineering, Faculty of Mechanical, Maritime, Materials Engineering (3mE), Delft University of Technology, Delft, the Netherlands

Abstract Life cycle design requires a good design method to achieve less environmental impacts and life cycle costs. This paper introduces a theory of product life cycle dynamics in analogy of control theory. The paper presents a life cycle model described with a block diagram, which is the standard representation of control systems. The model can simulate the life cycle costs in a market, where service costs are varied regarding the age of products produced at different time points. Keywords: Life Cycle Modeling; Life Cycle Simulation; Life Cycle Costs

1

INTRODUCTION

Life cycle design requires a good design method to achieve less environmental impacts and life cycle costs [1]. For instance, optimization of modular product architecture helps high reusability of modules from a life cycle perspective to reduce environmental impacts [2]. Product-related services and contracts regarding the use of products (e.g., rental and sharing) can also be systematically designed in order to increase the total value of products from a life cycle perspective [3]. In these methods, models of life cycles play a crucial role for the analysis of dynamics of life cycles. One type of these models is differential equations built based on energy and material balance which have been extensively studied in operations research [4-10] and materials engineering [11-13]. On the other hand, so-called life cycle simulation techniques [2, 14-20] use discrete event simulation techniques. While these models facilitate analysis of dynamic behaviors of life cycles, they do not directly support systematic design of life cycles because designers are not provided with useful concepts that allow easy tuning of product life cycles. For instance, a mechanical system and its controller can be easily analyzed and tuned to improve their dynamic behaviors, such as stability and accuracy, by using their control properties including eigenvalues and time constants. Unfortunately, such concepts are missing from dynamics of life cycles and yet to be established. This study aims at the development of a theory of product life cycles as analogy of control theory which is effective for the analysis of dynamic systems [21]. Such a theory of product life cycles should support, for instance, design of accelerated retirement of products from a market [7], which controls the quality of products in a market and life cycle costs of products in the market as a whole. As the first step of the development of a theory of life cycles based on control theory, this paper proposes a life cycle model using a block diagram, which is the standard representation of control systems. A block diagram consists of transfer functions connected one another with input-output signals. The life cycle model is developed on a tool for the design and analysis of control systems [22]. Modeling of life cycles using a block diagram on such a tool

has some benefits. First, graphic user interfaces (GUIs) decrease the effort of designers in building and extending models. Particularly, building blocks that organize transfer functions and input-output signals as groups help designers build models without knowing the technical details hidden in building blocks and reuse them. However, in order to fully enjoy such benefits, life cycle models developed on the tool should express the dynamics of life cycles such as the deterioration behavior of products and the circulation of reusable products. This paper focuses on the development of a life cycle model that can express such dynamics using transfer functions and input-output signals. The proposed model consists of building blocks representing various phases of a life cycle including production and use. The model also includes parameters such as rates of malfunction and reuse, which characterize the dynamics of the life cycle. The life cycle costs are calculated by integrating the costs for production, reuse, and services in the use phase. The model can simulate the life cycle costs in a market, where service costs are varied with respect to the age of products. This paper is structured as follows. Section 2 is a review of two major approaches to the modeling of dynamics of life cycles found in past literature. Section 3 proposes a modeling method of product life cycles using the formalism of control theory. The section describes assumptions and limitations of the modeling method derived from the formalization. Section 4 describes and discusses the simulated behavior of a case study. Section 5 summarizes the paper. 2 2.1

MODELING DYNAMICS OF LIFE CYCLES Modeling mathematical relations among parameters

One approach to model dynamics of life cycles is to represent mathematical relations among parameters of life cycles. This approach employs differential equations built based on energy and material balance and has been extensively studied in operations research [4-10] and material engineering [11-13]. Life cycle models developed in these studies model material and energy flows in end-

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_115, © Springer-Verlag Berlin Heidelberg 2011

663

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of-life (reuse, recycle, and disposal) processes, and the assessment of policies concerning the collection and reuse of products. Life cycle models in this approach consist of mathematical relations among parameters concerning populations of products belonging to specific classes at different time points in a life cycle (e.g., products in use, broken, collected). Differential equations are also used for the representation of such mathematical relations. They also include parameters representing the dynamic properties of life cycles (e.g., reuse rate). For example, Figure 1 describes the population of broken products in a market defined by a proportion of products in the market with a coefficient characterizing physical deterioration. The dynamics of the life cycles is the dynamic populations of products belonging to specific classes calculated with the mathematical relations and initial conditions. Mathematical relations among the populations of products classified from a life cycle perspective can be treated as governing relations of the dynamics of life cycles. However, some of them are simplified forms of the dynamics of lifecycles, which are derived from the behavior of individual products. For instance, physical deterioration of individual products depends on their own state such as age and usage history. Considering physical deterioration of individual products produced at different time points in a life cycle, the populations of products with a certain age class and the mathematical relations regarding the populations vary during a life cycle. This is why the studies of life cycles based on the modeling approach often assume that the state of individual products is not distinguished and they do not model the behavior of individual products. X(t-1) : The population of products in market at t-1 Y(t)=K*X(t-1)

K : Coefficient characterizing physical deterioration

Y(t) : The population of products broken at t Figure 1: A relation between two parameters in a life cycle. 2.2

Modeling with discrete event simulation techniques

Another approach to model dynamics of life cycles is based on discrete even simulation and uses a set of events, which cause transitions of the state of individual products. The approach has been used by the studies of life cycle simulation [2, 14-20]. It is a straightforward approach that purely relies on computational power. Life cycle models based on this approach allow designers to analyze the behavior of life cycles using life cycle simulation such as physical deterioration of machine tools, photocopiers, and refrigerators, and to optimize modular architecture, reuse business and services in life cycles, and resource circulation. Life cycle simulation generates life cycle events that instantiate products (i.e., production) and cause the state transitions of individual product instances (e.g., transportation, failure, and repair) during the life span. The life cycle models can include stochastic variables (e.g., product failure with a random rate). Statistic figures of a life cycle (e.g., the average age of products in a market) are observed from the simulated behavior of a large number of instantiated products in a life cycle. In comparison with life cycle models in Section 2.1, life cycle models based on discrete event simulation techniques do not constrain the populations of products classified from a life cycle perspective with mathematical relations. Such populations are the results of life cycle simulation, and they are obtained by counting individual products that belong to specific classes, which are

defined by intensional representations of products using abstract concepts from a life cycle perspective [23]. For instance, Figure 2 shows some product instances in a life cycle. The product instances possess such attributes as age, location and physical state. The product instances are classified with abstract concepts such as in market, broken, and old. Membership of product instances to abstract concepts is evaluated in terms of the state (a set of the attribute values) of product instances. Since the state of product instances change at the occasions of life cycle events, the populations of product instances belonging to the abstract concepts dynamically change. Old

In market

(age<10 years)

(location=user) Broken (physical state=not functional)

A product instance (age=12years, location=user, physical state=not functional) Figure 2: Classification of products with abstract concepts. 2.3

Comparison of two approaches for life cycle design

Application of the approach in Section 2.1 to life cycle design has a limitation in that mathematical relations concerning populations of products in a life cycle cannot deal with complex life cycle dynamics derived from the behavior of individual products in a life cycle. On the contrary, the approach in Section 2.2 can analyze such behavior with discrete event simulation techniques. However, analysis of life cycles with such simulation techniques has not been based on a theory, which allows systematic tuning of simulation parameters. This is why, life cycle design with the approach in past literature relied on a trial and error exploration of simulation parameters often with help of brute force optimization techniques such as genetic algorithm (e.g., [2]). 3

LIFE CYCLE MODELING WITH A BLOCK DIAGRAM

3.1

Motivation

Control theory has been applied to the control of dynamic systems such as modern mechatronics products [21]. This study assumes that control theory is applicable to the analysis of life cycles and useful to design product life cycles. For instance, life cycle costs can be minimized, while maintaining the quality of products and services in life cycles. For this reason, life cycles should be modeled in analogy to control systems. 3.2

Basic representation and constraints

A block diagram is the standard representation of control systems [21]. It consists of transfer functions with input and output signals (Figure 3 (a)). Transfer functions define mathematical relations between input signals and output signals, which are system variables. These signals and transfer functions can be included in building blocks (Figure 3 (b)), which allow hierarchical representation of control systems and encapsulation of detailed transfer functions and signals. (a) X(t)

Y=f(X)

(b) Y(t) Y(t)

Z=g(Y)

Z(t)

X(t)

Figure 3: A block diagram and the building.

Z(t)

Life Cycle Costing - Modelling

665

The life cycle model proposed here regards a signal as a population of products belonging to a specific class from a life cycle perspective. Such a class is defined by the abstract concepts shown in Figure 2. A population of products in the life cycle model, which belongs to a class i at time t, is a dynamic variable defined as follows.

(1)

n ( Ei , t ) where, Ei is a set of abstract concepts a.

Ei  {a1 , a2 ,}

(2)

Transfer functions define mathematical relations among the populations of products classified from a life cycle perspective. Some transfer functions typically represent the dynamics of life cycles. For example, delays are used to define two signals with a specific delay  . In the life cycle model, they represent processes in life cycles (e.g., transportation) including a delay.

n ( Ei , t )  n ( E i , t   )

(3)

Integrators are used to define the output signals by integration of input signals between 0 and t. In the life cycle model, they are used, for instance, to calculate the accumulated number of life cycle events during a life cycle. t

I [ n( Ei , t )]   n( Ei , ) d

(4)

0

In the life cycle model with a block diagram, a mathematical relation relating input and output signals is constrained by inclusion relations among the classes characterizing the signals. First, Equations 5 and 6 are the necessary condition of the additions of two signals in Equation 7.

E j  Ek  Ei

(5)

E j  Ek  

(6)

n ( Ei , t )  n( E j , t )  n ( Ek , t )

(7)

Production The total number of produced products P(t) is a sum of produced products p(t) with respect to time (Equation 12), which is determined by the actual population of products in the market M(t), the target population (i.e., set point according to the terminology of control systems [21]) Msp(t), and the production capacity pmax. (Equation 13).

P (t )  I [ p (t )]

(12)

p (t )  min( pmax , max( M (t )  M sp (t ),0))

(13)

Market It is assumed that the life cycle model consists of a set of markets, which are classified in terms of the age of products. This assumption is necessary to consider the physical deterioration of individual products with respect to the age of products, which causes the variation of service costs. The number of products in a market i is defined by the number of products, whose age tp is between ti-1 and ti. Figure 4 illustrates the definition of the market in the life cycle model. N

M (t )   mi (t )

(14)

mi (t )  n ( Ei , t )

(15)

i 1

Where, Ei represents a set of products, whose age is between ti-1 and ti. Classification of the products with respect to product age is mutually exclusive, and Equation 14 is thus consistent with the constraint given in Equation 5-7. m1(t)=2 m2(t)=3 mk(t)=1 mN(t)=2 E1 t0=0

E2 t1

Ek t2

tk-1

EN tk

age

tN-1

Figure 4: Multiple markets in the life cycle model.

Second, the value of the coefficient in Equation 8, which defines proportionality of two signals, depends on the inclusion relations between two classes representing the input and output signals as given in Rule 9 and 10.

When no failure (and thus no reuse) is assumed, the number of products in the market i (i.e., mi(t)) is calculated by the superposition of the total number of produced products P(t) with delays ti-1 and ti (Equation 16), which is illustrated in Figure 5.

n ( Ei , t )  K  n( E j , t )

(8)

mi (t )  P (t  ti 1 )  P (t  ti )

Ei  E j  K  1

(9)

Ei  E j  K  1

(10)

The constraints identify invalid mathematical relations among the populations of products in a life cycle. They are thus useful as guidance for the development of life cycle models with a block diagram. 3.3

Dynamics in the life cycle model

Dynamics of life cycles is modeled with the representation of a block diagram considering the constraints in Section 3.2. First, a balance equation regarding the total number of products in a life cycle model is defined. The equation includes the number of the products in the market M(t), the total number of produced products P(t), broken products F(t), and reused products R(t).

M ( t )  P ( t )  R ( t )  F (t )

(11)

(16)

P(t) mi(t) P(t-ti-1) 0

ti-1

P(t-ti) ti

t

Figure 5: The number of products in market i. The total number of broken products F(t) and reused products R(t) is a sum of these products in all markets over time (Equations 17 and 18), in which the number of broken products in market i at t (i.e., fi(t)) is determined by the failure rate FRi and mi(t) (Equation 19), and the number of reused products in market i at t (i.e., ri(t)) is determined by the reuse rate RRi and fi(t) (Equation 20). N

R (t )  I [ r (t )]  I [  ri (t )] i 1

(17)

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Life Cycle Costing - Modelling N

F (t )  I [ f (t )]  I [ f i (t )]

(18)

f i (t )  FRi  mi (t )

(19)

ri (t )  RRi  f i (t )

(20)

i 1

Considering the failure and reuse of products in each market, the population of products in a market i at t is a linear estimation of the population based on Equation 16.

mi (t )  ki 1  P (t  ti 1 )  ki  P (t  ti )  I [ ri (t )  f i (t )]

(21)

Where, i

ki  1 

I [ ( rl (t )  f l (t ))] l 1

P (t )

(1  i  N )

(22)

The feasibility of the estimation is verified with Equation 23, which is the population of products in the entire market M(t) by substituting Equation 21 into Equation 14. N

M (t )  k0  P (t )  k N  P (t  ti )   ( I [ ri (t )  f i (t )])

(23)

k 1

Life cycle costs as a performance indicator Life cycle costs are regarded as performance indicators of the life cycle model. They are measured by collecting signals representing the production costs, repair costs, and the service costs varied with respect to the age of products. Each cost element is a product of the specific coefficient and the production, reuse, and the population of products in individual markets (Equation 24). N

lcc (t )  c p  p (t )   (ci  mi (t ))  cr  r (t )     k 1    reuse costs production costs

(24)

service costs

Building blocks representing life cycle phases

The above formulation is the basis of building blocks in the life cycle model. The building blocks represent production and use phases in a life cycle. The entire life cycle model is built by connecting inputoutput signals among these blocks. The production block calculates the number of products to be produced p(t) and its sum with respect to time P(t). For the calculation, the population of the entire market M(t), the target population Msp(t), and the production capacity pmzx are used as the input signals. The target population and the production capacity can be dynamic variables. The use phase block calculates the population of products in a market mi(t) and the broken and reused products in the market fi(t).and ri(t). The use phase block is designed so that the entire use phase is modeled by a series connection of the use phase blocks. The block takes as input signals the total number of products produced P(t) and with delay P(t-ti-1), a sum of the total number of broken and reused products at the previous use phases I[r1(t)+…+ri-1(t)] and I[f1(t)+…+fi-1(t)]. The block includes a transfer function with a delay, which calculates P (t-ti) from P (t-ti-1). The size of the delay is ti-ti-1. 4 4.1

Assuming that products are not broken before they are used (i.e., k0=0), and the possible maximum life time of products are infinite (i.e., P(t-ti)=0), Equation 23 is as same as Equation 11. This means that the total balance of products in the entire market is valid with the estimation.

(b

3.4

AN EXAMPLE Simulation setting

An illustrative life cycle model was developed based on the formalization in Section 3. The model was implemented on a software tool for the design and analysis of control systems [22]. Figure 6 (a) shows the life cycle model with a production block and four use phase blocks. Figure 6 (b) shows the internal structure of the production block. Figure 7 (a) shows the internal structure of one of the use phase blocks. Figure 7 (b) shows the calculation of broken products corresponding to Equation 19. Graphical notations of the transfer functions in Figures 6 and 7 are explained in the user instruction in [22]. Continuous signals were quantified and discretized with respect to the population of products and simulation time using quantitize and discretize blocks in Figures 6 (b) and 7 (b). The purpose was to guarantee that the population is integer and calculation in the life cycle model is performed step wise. Since such a detail of life cycle models are hidden in the building blocks, designers do not have to deal with it in designing life cycles.

(a

Production block

Use phase blocks in series Figure 6: A life cycle model with a production block and four use phase blocks (a), and the internal structure of the production block (b).

Life Cycle Costing - Modelling

667 (b)

(a)

Figure 7: The internal structure of a use phase block, and the block for the calculation of broken products (b). Table 1 shows the input parameters of the simulation. According to the parameters, the life cycle model has a stepwise increasing failure rate and a stepwise decreasing reuse rate as products in a market become older. The behavior of the life cycle is expected to change at 360, 720, 1080 steps considering the classification of the market in terms of the age of products. i

1

2

3

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0.001

0.002

0.003

0.01

RRi

0.8

0.5

0.3

0

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8

ti-ti-1

360

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360

infinite

The second phase showed approximately linear increases of all costs, because the number of production and reuse events and the distribution of the age of products in the entire market became more stable with the progress of simulation.

Figure 8: Simulated production of products.

Msp(t)=10000; pmax=100; cp=1000; cr=200 m1

Table 1: Input parameters. 4.2

m2

Simulation results

The life cycle model was simulated for 3600 steps. Figure 8 shows the production of products during the simulation. Discrete changes of the number of production were observed around 100, 360, 720, 1080, and 1200 steps, which were interpreted as follows. At the beginning, new products were produced at the rate of the production capacity until the total population of products in the market reaches the target population (around 100 steps). After that new products were produced when the products in the market were broken and not reused. The number of production gradually increased when the products in the market entered new use phases due to aging (around 360, 720, 1080 steps). A steep increase of the number of production between 1080 and 1200 was due to the retirement of products at the final use phase. After that, the number of production deviates following the deviation of the distribution of the age of products in the entire market.

m3

m4

Figure 9: Population of products with respect to age.

reuse costs service costs (m4) service costs (m3) service costs (m2) service costs (m1)

Figure 9 shows the populations of products with respect to the age (use phase) of products. The aging of products was observed through the shifts of the populations of products across use phases at 360, 720, and 1080 steps. The shifts became less visible with the progress of simulation, because the distribution of the age of products in the entire market gradually converged to a stable distribution. However, a simulation with larger time steps is necessary to determine the stable distribution. Figure 10 shows the simulated life cycle costs and the brake down of the costs into the production costs, service costs at each use phase, and reuse costs. The cost structure can be divided into two phases. At the first phase, the production costs were dominative due to the introduction of new products (between 0 and 100 steps).

production costs

Figure 10: Life cycle costs. 4.3

Discussion

The simulation results indicate that the life cycle model using a block diagram could represent the dynamics of life cycles such as physical deterioration of individual products and circulation of

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reused products. The simulation results show that the life cycle model can be used for the analysis of the life cycle costs as a system variable dependent on the parameters like reuse rates and service costs varied with the age of individual products. Further research is necessary to understand the life cycle model as a dynamic system to be controlled. For instance, reuse rates and service costs should be formulated as controllable and controlled variables in a life cycle model. The life cycle model is expandable by additionally defining use phase blocks in series, transfer functions such as delays (representing the delay of the delivery of order information and that of products), and coefficients for the calculation of the performance of life cycles. 5

SUMMARY AND FUTURE WORK

The paper has first analyzed two different approaches to the modeling of life cycles and the applicability of these approaches to life cycle design. In order to develop a theory of product life cycle dynamics in analogy of control theory, it has presented a life cycle model with a block diagram, which is the standard representation of control systems. The model has been built on a modeling tool used for control design. Building blocks representing life cycle phases has been proposed for the effective construction of life cycle models. Life cycle costs have been calculated considering the deterioration behavior of individual products produced at different time points in a life cycle, and circulation of reusable products. In past literature, such complex dynamics of life cycles has been analyzed with discrete event simulation techniques, because mathematical relations concerning populations of products in a life cycle cannot deal with such dynamics. The proposed model is novel in that it could simulate such dynamics with the mathematical relations using the formalism of control systems like superposition of delayed signals. Future work includes the development of a theory and design method of life cycles in analogy of control theory. A library of building blocks based on the proposed model will be published for support of life cycle design based on the theory. 6

[7]

Kim, H.C., Ross, M. H., Keoleian, G.A. (2004): Optimal fleet conversion policy from a life cycle perspective, in: Transportation Research Part D, Vol. 9, pp. 229-249.

[8]

Schwarz, H.G. (2006): Economic materials-product chain models: Current status, further development and an illustrative example, in: Ecological Economics, Vol. 58, pp.373-92.

[9]

Bayindir, Z.P., Dekker, R., Porras, E. (2006): Determination of recovery for a probabilistic recovery system under various inventory control policies, in: Omega, Vol. 34, pp.571-584.

[10]

Chouinard M, D’Amours S, Ait-Kadi D (2008): A stochastic programming approach for designing supply loops, in: International Journals of Production Economics, Vol.113, pp.657-677.

[11]

van Schaik, A., Reuter, M.A., Boin, U.M.J., Dalmijn, W.L. (2002): Dynamic modeling and optimisation of the resource cycle of passenger vehicles, in: Minerals Engineering Vol. 15, pp.1001-1016.

[12]

Ignatenko, O., van Schaik, A., Reuter, M.A. (2008): Recycling system flexibility: the fundamental solution to achieve high energy and material recovery quota, in: Journal of Cleaner Production, Vol.16, pp.432-449.

[13]

Amini, S.H., Remmerswaal, J.A.M., Castro, M.B., Reuter, M.A. (2007): Quantifying the quality loss and resource efficiency of recycling by means of exergy analysis, in: Journal of Cleaner Production, Vol. 15, pp.907-913.

[14]

Shu, L.H., Wallace, D.R., Flowers, W.C. (1996): Probabilistic Methods in Life-Cycle Design, in: Proceedings of IEEE International Symposium on Electronics and the Environment, Dallas, TX, pp. 7-12.

[15]

Johansen, M., Umeda, Y., Tomiyama, T. (1997): Life Cycle Simulation for Verifying Sustainable Model of Products. In: Camarinha-Motos, L. M. (ed.) Re-Engineering for Sustainable Industrial Production, Chapman & Hall, London, pp. 247-258.

[16]

Takata, S., Yamada, A., Kohda, T., Asama, H. (1998): Life Cycle Simulation Applied to a Robot Manipulator - An Example of Aging Simulation of Manufacturing Facilities -, in: Annals of the CIRP Vol.47, No. 1, pp.397-400.

REFERENCES

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Alting, L. (1995): Life Cycle Engineering and Design, Annals of the CIRP Vol.44, No. 2, pp.569-580.

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Umeda, Y., Nonomura, A., Tomiyama, T. (2000): Study on life-cycle design for the post mass production paradigm, in: Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol. 14, pp.149-61.

Hata, T., Kato, S., Sakamoto, H., Kimura, F., Suzuki, H. (2000): Product Life Cycle Simulation with Quality Model, in: Proceeding of 7th CIRP International Seminar on Life Cycle Engineering, pp.60-67.

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Meier, H., Roy, R., Seliger, G. (2010): Industrial Product2 Service Systems-IPS , in: Annals of the CIRP Vol.59, No. 2, pp.607-627.

Fujimoto, J., Umeda, Y., Tamura, T., Tomiyama, T., Kimura, F. (2003): Development of Service-Oriented Products Based on the Inverse Manufacturing Concept, in: Environmental Science & Technology, Vol. 37 No.23, pp.5398-5406.

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Nijkamp, P., van den Bergh, J.C.L.M. (1997): New advances in economic modeling and evaluation of environmental issues, in: European Journals of Operational Research, Vol. 99, pp.180-96.

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Kumazawa, T., Kobayashi, H. (2006): A simulation system to support the establishment of circulated business, in: Advanced Engineering Informatics, Vol. 20, pp.127-36.

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Kandelaars, P.P.A.A.H., van den Bergh, J.C.J.M. (1997): Dynamic analysis of materials-product chains: An application to window frames, in: Ecological Economics, Vol. 22, pp.4161.

Komoto, H., Tomiyama, T. (2008): Integration of a Service CAD and a Life Cycle Simulator, in: Annals of the CIRP, Vol.57, No.1, pp.9-12.

[21]

Ogata, K. (2009) Modern Control Engineering, 5th Edition, Prentice Hall.

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Mathworks (2009): MATLAB and Simulink for Technical Computing Matlab and Simulink, version 7.9.

[23]

Tomiyama, T., ten Hagen, P.J.W. (1990): Representing knowledge in two distinct descriptions: Extensional vs. intensional, in: Artificial Intelligence in Engineering, Vol. 5, No. 1, pp.23-32.

[6]

Fandel, G., Stammen, M. (2004): A general model for extended strategic supply chain management with emphasis on product life cycles including development and recycling, in: International journal of production economics, Vol. 89, pp.293-308.

Assessing the Value of Sub-System Technologies including Life Cycle Alternatives 1

12

1

1

Alessandro Bertoni , Ola Isaksson , Marco Bertoni , Tobias Larsson 1

Division of Functional Product Development, Luleå University of Technology, Luleå, Sweden 2

Volvo Aero Corporations, Trollhättan, Sweden

Abstract Emerging from an industrial case study in the aerospace industry, the paper proposes an approach to evaluate subsystem technology concepts from a life cycle perspective. The approach is composed by 5 main phases that aims to drive product designers towards more value-oriented design decisions. It is shown how different life cycle alternatives, such as the selling of a Product-Service-System instead of a traditional product, deeply impact the value of design alternatives. The described approach has been developed in collaboration with industrial partners and represents a potential instrument to enhance value-driven product design. Keywords: Value Driven Design; Sub-System Technology; Life Cycle Engineering

1

INTRODUCTION

Making the correct choice in the preliminary design phase impacts the entire product life cycle in an order of magnitude that could span from making the product being a big success, to generating, instead, a total business failure [1]. This statement gains more and more relevance when the product is characterized by a long lifecycle, when the technology is highly capital-intensive and when later life cycle modifications imply huge expenditures in terms of money and labor. In the effort of being competitive in the globalized market, a common and intuitive strategy for companies is to cut costs while increasing structure efficiency [2]. However, this approach does not always lead to success. Cost competition does not ensure long-term value added, because of the real risk of engaging in a cost-based fight against market followers [3]. So far, what becomes a real target to any company who wants to lead, or keep on leading, the market, is to provide the highest value to the system in which the company is competing. This concept should be considered not only from the final product seller focusing on end user, but also by all those companies that are relevant business partners in the supply chain. Collopy [4] stated that a product to be successful should maximize the value generated for the customer and for the system; how the profit is then divided between companies is instead decided by the market. To do so it is necessary to adopt a wide vision of the system, understanding how some changes in the sub-system impact on system level. This process is of relevant difficulty, because it implies the acquisition of an enormous knowledge about how the system works, and it needs therefore collaboration from upper-level companies, those could be reluctant to share core information about strategies and future actions with other product stakeholders. Nevertheless, in some business contexts all major companies of the supply chain can be interested in sharing this information. That is the case, for instance, of business deal implying revenue sharing, or concerning products embedding top-level technologies.

2

MOTIVATION AND OBJECTIVES

The main objective of the paper is to propose an approach to evaluate sub-system technology concepts from a life cycle perspective. Emerging from a real example the development of an aircraft engine component, the paper illustrates how the traditional functionality-performance analysis can be complemented by a more value-oriented assessment to enable more lifecycle-oriented decisions in a conceptual phase. The final aim of the paper is to contribute to the ongoing discussion about methods and tools to be used, in the preliminary design phase, to assess the value associated to a design alternative, in order to provide useful instruments to help design teams in choosing the solution that maximizes the value for the system. 3

RESEARCH APPROACH

The approach emerges from the analysis of real industrial problems rather then from a theoretical investigation. The initial problem statement has been defined in collaboration with major European industrial and academic partners in the aerospace sector, and has been further refined by interacting with an aircraft engine subsystem components provider. The approach for value assessment has been defined through workshops, physical meetings, informal interviews and company site visits. Such findings have been further analyzed in view of theory; improvements and implications have been proposed using as a reference the scenario created together with the industrial partner. 4

DESIGN CONCEPTS ASSESSMENT IN A LIFE CYCLE PERSPECTIVE

In an ideal scenario, companies should always select design concepts able to increase the added value for their customers and stakeholders. Being able to calculate a priori, in a transparent and repeatable way, the value of a given solution is, however, not a straightforward process. As stated by Anderson and Narus [5] remarkably few firms have the knowledge and capability to actually

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_116, © Springer-Verlag Berlin Heidelberg 2011

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assess value and, by consequence, gain an equitable economic return for the value delivered to customers. This problem is further exacerbated when the product grows in complexity and when the development activity moves from a “system” to a “sub-system”, or even “component”, perspective. Here the need for a methodology that could help the design team in assessing the lifecycle value contribution of a concept becomes evident. The concept of “value” radically change the way decisions are taken at all the levels of detail the design activity is conducted. The optimal design solution has not to be merely found at the intersection of the “Performance” and “Functionality” axes, rather a third dimension, encompassing the “life cycle option” perspective, as shown in Figure 1, should be considered. The adoption of a life cycle value creation perspective allows designers to judge different alternatives considering a more complete set of information that could lead to a more value-oriented choice.

in a preliminary phase, which technology/component to be further developed. Company A, in fact, needs now not only to think in terms of performances and functionalities but also to consider, for example, how to make the components easier to maintain, or how to make them easier to re-use and recycle. The paper provides guidelines to drive designers toward a more value-oriented choice, allowing a divergent multi-dimension analysis, so to consider lifecycle options as basilar to define and assess the importance of the product main value drivers. 5

LIFE CYCLE OPTIONS ANALYSIS: AN APPROACH

The conceptual approach elaborated for sub-system technologies value assessment is composed by 5 main steps or activities, Figure 2 describes the approach and links each activity to the most relevant actors and stakeholders involved. To define the approach, a large cross-functional network of product stakeholders was established. This allowed the decomposition of the original problem into sub-problems reflecting product needs and requirements.. 5.1

Problem decomposition and requirements identification

The requirements gathering process is usually a very complex affair and can represent a major obstacle to successful system development. It is argued that one reason for development projects poor performance, or even failure, is the mismatch between what expressed by the customers and what specified by the developers in terms of system requirements, a mismatch triggered by the differences in the cultural background of both sides [6].

Figure 1: Choice dimensions. To exemplify this concept, let’s consider a sub-system manufacturer (company A) providing engine components to an aircraft engine manufacturer (company B). Company A is therefore bound by contract agreements to satisfy given functionality and performance requirements. Mean Time Between Failure (MTBF, 20000 flight hours) and weight (70 kilos) represent two main requirements for a component under development. Design A1 has an MTBS of 20,010 hours and weights 69 kilos, while design A2 weighs 50 kilos and has a MTBF of 19,990 hours. The two alternatives are then identical in any other technical aspect. Although Design A2 does not meet the requirements, is really A1 better than A2? Now consider that company B decides to change its selling policy, moving from the traditional selling of a product to providing life cycle commitment, keeping the ownership of the product along the life cycle until disposal. This choice has deep effects also on company A that has now a wider set of information to work on when deciding,

Problem decomposition and requirements identification are the first steps of the methodology. Value assessment represents a big challenge for every design team, and thinking of facing it in a unique solution could lead to the rise of a big set of problems that could affect the results reliability. It is therefore inconvenient to consider it as a “unique box” to be solved; it is instead preferable to adopt a strategy of problem decomposition. [7]. Studies reveal that, analysis–synthesis–evaluation is a design method largely adopted and discussed in literature [8][9]. Analysis refers to the decomposition of the problem into sub problems; synthesis refers to the recomposition of sub problems in different ways; and evaluation refers to the test of the performance of new structures/systems [8]. As described by Simon [9] designers tend to decompose illstructured problems into several sub problems. Additionally stakeholders’ expressed expectation needs to be collected by the design team. Designers should then interpret and reformulate the information acquired, in order to redefine expectations and validate them in a second round with stakeholders. Without losing the focus on expectations and adopting a life cycle perspective, the team should be able to translate the expectations into needs. A needs analysis should then be performed in order to highlight the conflicts between needs.

Figure 2: Value assessment process.

Life Cycle Costing - Modelling 5.2

Value drivers definition

Once the problem has been decomposed and the relevant innovation topics have been defined, it is necessary to set a number of relevant and measurable value drivers for the value assessment. In order to facilitate both a quantitative and a qualitative evaluation, some value criteria are first defined. These represent the key fields on which the product directly or indirectly impacts. Each criteria clusters the value drivers that refer to the same field so to make easier a comparison between the different alternatives. To define coherent value drivers the team in charge of the activity needs to access to information regarding needs and requirements, defined in the previous step. Moving from high-level value criteria [10], a cross-functional panel of expert is asked to formulate relevant value drivers for a given component under analysis. Value drivers are, in fact, specific instantiations of generic value criteria. The value drivers for a compressor blade, for instance, may significantly differ from those specified for an intermediate case, simply because they differ in terms of geometry, material, expected lifetime, etc., and because of different customer expectations. A large number of stakeholders are involved in this part of the process. Product development and customers still plays a relevant role as in the requirements identification phase, but a wider vision on the system is needed. In order to avoid focusing too narrowly on the performance-functionality axes, members with knowledge from different backgrounds has to take part to the process. Introducing a system view on the future product, including in the decision team a wider set of stakeholders such as top management, marketing and production managers, could help to create a value assessment result more reliable. However team composed by heterogeneous actors with very different background could prove to be difficult to manage, since the members do not have a convergent perspective on their own specialization. Therefore there is the need of a figure that possesses knowledge about how the whole process works on a system level, having a deep understanding of the dynamics and of the knowledge generation sources that involve the product along all his life cycle. Hence the figure of the Value Analyst is introduced with the aim of providing a life cycle oriented perspective to the design team along all the product development process. The process of defining value drivers can vary in different context; however experience and deep requirements analysis are fundamental instruments to help facing this activity, as far as focus groups and interviews are useful methodologies to reach the goal. 5.3

Concepts generation

The aim of conceptual design is to develop promising concepts. This requires generating a wide range of concepts, to prevent overlooking valuable concepts, and evaluating/selecting these soon enough, to restrict their number from getting too large to allow meaningful consideration. [11] The new concepts can imply incremental improvement of existing products or radical innovation. In both case several methodologies are nowadays applied to enhance creativity and innovation in the design team. Some important examples, largely discussed in literature, that can differently be applied basing the choice on the final goal the design team wants to achieve. Brainstorming [12], is a group creativity technique designed to generate a large number of ideas for the solution of a problem, it is a valuable methodology when talking about radical innovation, it has the quality of enhancing creativity promoting the creation of a high number of ideas [13] that, however, could often fall outside the technological or practical constraint of a product. Introducing the Value Analyst in the process as a moderator in the brainstorming session could drive the team toward more value-oriented ideas. Delphi [14], is a

671 structured interactive forecasting method which relies on a panel of experts and is performed anonymously in order to avoid bandwagon effect. It is a methodology oriented more on forecasting the future, and used for marketing and demand forecast analysis [15], so it is more suitable for concepts evaluation than for new concepts generation. TRIZ [16] is a problem solving, analysis and technology forecasting tool derived from the study of patterns of invention in the global patent literature [17]. TRIZ implies a structured approach on the problem providing general guidelines for system evolution but could be weak when focusing on detailed design. It focus on technological evolution not enhance a divergent value-oriented thinking. Focus groups [18] are interactive group setting where participants are free to talk with other group members. Organizing focus group allows the team to focus deeply on the problem, however it could limit creativity and create bandwagon effect among the group [19]. Focus groups are powerful methods if the discussion is well driven by moderator and if a collaborative spirit is spread among the group. The value analyst should play the moderator role keeping the attention of the group focused on the goal. 5.4

Concepts evaluation

The fourth step of the methodology is the concept evaluation. It represents a complex phase that can be structured as a process itself. During this phase is of primary importance the sharing of knowledge from the upper system levels. The project coordinator acts as a link between different stakeholders, both internal and external. Concept evaluation is the most critical phase in the methodology and has been addressed in detail in the ´Life cycle oriented concept evaluation process` chapter. 5.5

Concept selection

Last phase is concept selection, intended as an iterative process that does not always output a dominant concept immediately after the evaluation. A design alternative could prove to be more valuable in a value dimension and show to be weak under another point of view. A multi attribute decision-making problem [20] arises every time we need to decide between different complex design solutions. Nevertheless, it is important that the decision team can access all the data resulting from the evaluation in an easy and readable form, in order to have a complete set of information to base the decision upon. For this reason the concept selection phase is strictly linked to the value visualization. An easy and quick visualization of the value contribution of different alternatives can help decision-making team in choosing the best solution in a limited period of time. The amount of data to be evaluated in fact could be massive, generating therefore confusion, make people unable to judge the different alternatives from a wide value perspective. Current research efforts, in the value-driven design field, tend to focus on the development of a means to quickly visualize and evaluate one or more solutions in a rapid manner. [4] 6

LIFE CYCLE PROCESS

ORIENTED

CONCEPT

EVALUATION

Assessing the value contribution of a solution is an activity that cannot be reduced to the a mere cost and revenue calculation; it is instead a combination of quantitative and often qualitative studies, which results needs to be weighted on the base of qualitative forecast and expectations. In general, there is currently no way to talk about better or worse with respect to an ad hoc aggregate of components. What is required is a process or rule for comparing designs to highlight what is better. Since a relevant part of the parameters cannot be evaluated in a coherent quantitative way, it is often better to recur to a qualitative evaluation based on the comparison between a baseline value, for

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example the minimum value requested by customer requirement, and a target value, that could represent the ideal parameter result. Considering the engine component example mentioned before, we fix a MTBF of 20000 hours and a weight of 70 kg as a baseline, and we fix at 50000 hours the targeted MTBF and 60 kilos the targeted weight we would assign a radically different value to the solutions. Qualitative ranking comparison is therefore necessary to run the value assessment. A second critical aspect in the concept evaluation is the ability of correctly weighing the value drivers, to obtain a reliable final result. Depending, for example, from product nature, market requests, market forecast and company’s objectives, some value drivers need to be considered more relevant than others. The weighting is obtained through the definition of a scale of values, e.g., form one to ten, or through a percentage estimation of the value drivers impact over the total product value. The activity of weighting value drivers is a key step in the approach. It is basilar for a designer to know which characteristics, qualities, or performances, are critical. This is a phase where life cycle options play a crucial role. Different lifecycle perspective can deeply influence the relative importance of a value driver compared to another. Consider for example a traditional product selling structure, meaning that the product is sold in a unique solution, and a product/service system selling architecture, that implies keeping the ownership of the product along all its life, the two different company strategies hugely impact on product life cycle, creating the need to consider new value drivers, as well as different relative importance for the already existing drivers. Figure 3 summarizes the process of concept evaluation highlighting activities, methodologies, actors and outputs. The following paragraphs describe the four activities citing as a case study the evaluation of two different intermediate compressor cases (IMC) for aircraft engine. The evaluation took place considering two different life cycle perspectives, the traditional selling, and the selling of the Product/Service System (PSS) [21]. The case study involved a sub-system technology that needs to be integrated in the aircraft engine structure. Different selling strategies, and therefore different life cycle and ownership alternatives, for the aircraft engine, impact the value assessment in the IMC design phase. 6.1

Costs and revenues analysis

The evaluation of costs and revenues concerns the estimation of the economical performance of an investment. Different methodologies are proposed by literature and broadly applied in

industry. Between the most used it is possible to cite cash flow analysis [22], net present value and adjusted present value [23], internal rate of return calculation [24] and break-even analysis [25]. These activities are almost completely in charge of finance departments and cost managers. Most of the concepts concerning costs and revenues analysis have been stated fifty or more years ago, however these instruments are currently still in use in many companies. Recently more methodology, i.e., the Modified Diatz Method [26], have been introduced in order to weigh individual cash flows by the amount of time that those cash flows are held, or absent, from the portfolio. These analysis, even if still valuable, provides as an output a value related only to the financial performance of the product, ignoring all other aspects related to the value perspective, i.e., the results are calculated in term of money, related to a single product/investment and the phenomena related to the whole value generation for the company are not considered. On a value driven design perspective cost and revenue analysis is still necessary but cannot be considered sufficient for a value assessment. Considering the case study the adoption of a selling + maintenance and service policy implied the consideration of additional variables, such as spare part cost per year, service start-up costs, disassembly costs, recycling costs, remanufacturing cost per unit, service logistic costs, maintenance costs. 6.2

Risk Estimation

Every new product or component implies a certain level of risk. A large number of risk categories and a conspicuous set of methodologies is discussed in literature to estimate risk in new product development. Walker [27] presents a lightweight approach to technical risk estimation through a probability impact analysis. Altman and Saunders [28] propose an approach for credit risk measurement built around a mortality risk framework. Bangia et al. [29] describe a methodology for modeling liquidity risk in correlation with market risk measurement and management. Research is also focusing on regulatory risk measurement, exploring how a change in the regulation impacts the decision of an investment. Manteghini and Scarpa for example [30] describes how regulatory constraints affect a firm's investment choices when the firm has an option to delay investment. William [31] focuses on product development process design and on the response to market, technical and regulation risks, exemplifying with ten company case studies how different processes manage different risks.

Figure 3: Concept evaluation process.

Life Cycle Costing - Modelling Current methodologies used in industry are able to provide a satisfactory risk estimation in this phase of the process, hence no new methodology are proposed, but a combination off a set the techniques that could consider the broadest risk horizon is recommended. Considering the risk analysis from the IMC design point of view, different weights for the risk dimensions needs to be considered. For example a PSS solution has been considered more critical in term of technical risk, since an originally bad design impacts the costs of maintenance and repair until the product disposal; or in terms of market risks, since the company doesn’t know which will be the real response from the customers. In fact, considering the case of an IMC exclusively designed optimizing a PSS engine, the failure of the selling policy could cause big losses to the sub-system technology provider. 6.3

Performance analysis

Performance analysis is the most engineering intensive and technical activity of the process. Performance analysis provides quantitative data related to the in-field usage of the product. In case of a PSS, this category encompass also the value related to all the aspects concerning remanufacturing, maintenance, delivery and discard of the product. Product performances are strictly linked to the requirements set in contracts or needed by the end user. Most of the time requirements fulfillment represents the basilar condition for a product to enter the market, especially in business-to-business situation. Furthermore, performance analysis has to encompass not only performances relevant for the customer, but it is necessary to pay attention to a second performance dimension: the internal company performances. These performances are related to company organization and process structure e.g., process lead-time, process mean time between maintenance, process mean time between failure, machine saturation index, setup time. These aspects are measurable and needs to be taken into consideration when evaluating new design alternatives, in order to avoid indirect impacts on the overall company activity. Different methodologies can be applied for product performance analysis. To test the ´in-field´ performance of a product, physical and virtual testing, such as finite element analysis, are the most common methodologies in use. Instead, considering the internal performances, process simulation methodologies can provide a useful instrument to evaluate the response of the realization of a new product. Interesting examples of application can be found in Abdulmalek and Rajgopal [32] and in Smith et al. [33]. Considering an intermediate compressor case, the “in usage” performances need to be satisfied both for traditional product and PSS, in order to fit safety and customer requirements. However the PSS perspective can allow, in particular situation, the design of cheaper components with shorter life expectation, but that could be substituted more often, instead of choosing life-long and expensive components. 6.4

Intangible Value evaluation

Intangible value is a category that encompasses all those aspects not strictly related to product performances but that impact on the overall system. A various set of characteristics can be defined as providing intangible value. These dimensions are outside the technical horizon of the engineer, they cannot be easily captured [34]. An intangible value could be the relevance of the engineering solution in relation with the flexibility of the environment, in which it operates. Aspects to be taken into consideration are, for example, the degree of compatibility to the external environment and how

673 much an unexpected modification impacts the product function. More undefined, but not less important value is the effect of a choice on brand acknowledgement or in new knowledge acquisition. These aspects cannot be immediately translated into tangible performance, but contribute to the generation of competitive advantage in the long run. In the case study analysis, considering a PSS life cycle, aspect like new knowledge acquisition, continuous improvement enhancement, robustness to external constraint modification or brand acknowledgment, are important, and, by consequence, a big attention has been paid to them during the definition of value drivers weights. 7

CONCLUSION

The described approach represents a potential instrument to increase the awareness about requirements and value embedded in a design alternative. In authors´ belief the adoption of such a process for assessing the value of sub-system technology would help companies to move a step forward a value-driven design, granting good economic performance in the long run. Companies able to correctly assess the value of their sub-technologies, considering the value they provide to the system, would in fact maximize the economic return on their investment. The advantage of the proposed approach is to increase the knowledge about the real value provided to the system by a subsystem technology, and take advantage form this since the preliminary design phase. Traditional cost or performance analysis doesn’t possess such capability of looking to the value of a product from a system perspective. The proposed methodology has been developed in collaboration with an industrial partner, acting as a components provider for aircraft engines. The approach has been validated through discussions and workshops together with other international partners in the aeronautical sector, collecting positive and constructive feedback. It does not pretend to be exhaustive neither to offer a final solution to the problem. It is instead open to discussion, improvement, and future research both inside and outside the aeronautical field. Due to the complexity of the problem and the conspicuous need of data, it is difficult to foresee a large-scale application of the methodology in the short term. However we believe that knowledge sharing and communication are the key words to allow this approach being more and more applied in companies. In addition, the creation of automatic updates form company’s database and models will mark a decisive improvement towards the automation of the process. The authors are currently involved in studies aiming to capture, model and understand customers’ and stakeholders’ needs and expectations. Moreover some methodologies and tools to help teams making decision at a gate, as for example the LIVERY, Light Weight Visualizator, proposed by Bertoni [35], are currently object of research. 8

ACKNOWLEDGMENTS

The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 234344 (www.crescendo-fp7.eu/).

674 9 [1]

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Costing for Avionic Through-Life Availability 1

1

1

Linda Newnes , Antony Mileham , Gwion Rees and Paul Green 1

2

Department of Mechanical Engineering, University of Bath, Claverton Down, Bath, BA2 7AY, UK 2

BAE Systems (Operations Limited) Military Air Solutions, Building P120, Warton Aerodrome, Preston, Lancashire PR4 1AX, UK

Abstract In recent years industries such as defence have moved towards availability contracts, where an agreement is made between the supplier and customer for the provision of a fully functioning product/service for a given period of time. The aim of the research presented in this paper is to propose novel approaches and methods for predicting the through life manufacture and repair cost of avionic availability, providing greater certainty for in-service costs. The initial findings from this pilot study investigated the cost estimating relationships to predict failure rates of products and in turn the cost of providing availability of these products. Keywords: Through Life Costing; Availability; Product Service Systems

1

INTRODUCTION

Traditionally, agreements between suppliers and customers have been based on purchase agreements. This is where the customer will pay a fee for a fully functioning product or service, at which point the ownership and thus the responsibility is passed over to the customer. Here, the supplier would usually only be concerned with the costs incurred over the first four phases of a products lifecycle, shown in Figure 1, and determine the pricing strategy accordingly.

Figure 1: CADMID Life-Cycle Diagram [1].

a 100% increase in business being let under availability type contacts by 2014 when compared to 2009 figures. Increasing business to business service contracting or servitisation [3] and performance based logistics [4] is occurring in both public and private sectors. The MOD is increasingly opening the support of military systems to private companies. An example is ATTAC, a ten-year, whole-aircraft availability contract where BAE Systems take prime responsibility to provide Tornado aircraft with depth support and upgrades, incentivized to achieve defined levels of available aircraft, spares and technical support at a target cost. Previous work has shown that in this environment the service provider manages combinations of their own and client staff at the client’s base in facilities provided by the client, making the provider dependent on actions by the client to fulfill the contract [5]. It also suggests that there are services outside the contract that place additional requirements on both parties if value is to be efficiently co-created. This creates additional risk cost, not previously understood or captured in product based contracting i.e. selling parts and spares.

Suppliers would therefore take precautions to ensure that costs incurred up to and including the manufacturing phase are kept to a minimum, in order to gain maximum return on investment. Although traditionally the majority of the costs incurred by the suppliers can be attributed to the manufacturing phase, up to 80% of a product’s total cost is committed during the first three phases of a products lifecycle [2], this relationship is illustrated in Figure 2. Hence an accurate estimation of future product costs as early as possible in the design stage is desirable. Through life capability management is delivered through availability contracts, such as the aircraft availability contract for Tornado between BAE Systems and the UK Ministry of Defence (MOD). These contracts deliver service by providers working with the client, where the client and provider draw upon each other’s resources to deliver value. Within the electronics sector this shift in business processes is growing. For example, BAE Systems MAS anticipate

Figure 2: Committed vs. Spent Cost (adapted - Clark et al. [6]).

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_117, © Springer-Verlag Berlin Heidelberg 2011

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Unlike with purchase agreements, the responsibility of the product throughout its life cycle remains with the supplier, from the concept stage through to the disposal stage. This can have a major impact within industries where product lifetimes are long, for example the defence industry [6]. In these cases the in-service costs can account for up to 75-85% of the through life costs of the product. Hence, predicting the in-service costs for such long-life low volume products is extremely important. This has led to an increased interest in the field of cost estimation [7] and the techniques which can be used. For the research presented in this paper an example of such a longlife product is introduced, a complex avionic equipment unit. The failure rates of this product are then investigated to ascertain whether Cost Estimating Relationships (CER) can be identified. These CERs can then be used to predict the in-service costs for such products. Although real data has been used to identify the CERs, to protect confidentiality the data used in this paper has been modified to represent typical values that may occur. 2

of a service [16]. This is emphasised by the goal programming approach adopted by Kumar [17], where they attempt to optimize reliability, maintainability and supportability; as current models do not optimize design selection based on cost of ownership through life. However, as part of this optimization there is a need to understand how the product behaves in-service and predict the costs of providing this repair and service. These results can then be used to undertake a trade-off in the early stages where the inservice costs can be predicted. Using the decision support model described by Niazi (2006), the most applicable cost estimating techniques based on the data available should be a Quantitative Parametric approach. This is due to their being detailed information available about the product as it is not in the concept stage. This approach is also very appropriate for the development of a proof of concept model as it based around mathematic algorithms. 2.2



Initial briefings with the industrial liaison were undertaken to determine what was required and the full purpose of the pilot study. This ensured all stake-holders had a common understanding of the expected inputs and outcomes from the pilot study. The first stage in the data collection phase was to identify the product to be investigated. The particular Avionic Equipment was selected as the lifecycle data was available, it had recently entered service and there was a range of data sources for this product.



For the Avionic Equipment spreadsheets of data were obtained from the industrialists, which provided data in terms of failures, including the initial in-service performance. The data also provide information on the partners using the product, the batches produced and the time in-service.



From the spreadsheet data and discussions with the industrialist the data was classified into areas for investigation. The industrial context was important enabling researchers to understand the product and the components the repair and failure data would refer to.



The data was coded in ‘industrial’ speak, i.e. specific codes for use within the company. These were explained enabling the researcher to code the data appropriately.



Once the data had been coded and sorted the researcher then validated the coding approach and the understanding of the data with the industrialists.



As there were different levels of failure, particular product attributes and impact on availability a particular failure was selected for investigation. Failure ‘pilot study’ was selected as it had the highest number of failures and the greatest impact on performance. The researchers were aware that this may not be indicative of the whole system failure but a sub-system within the product.

RESEARCH APPROACH

The aim of this pilot study was to analyse the quality of data available and to identify initial CERs for estimating the cost of avionic through-life availability, answering the following questions: 1. Is the industrial data available for identifying CERs for avionic availability? 2. Do the CERs vary between nations utilizing the avionic equipment? 3. Does the history of the product such as manufacturing/testing failures/process affect in-service failure rates? To address these questions the pilot study was undertaken in four phases. Phase 1, identified and investigated cost estimation techniques for availability cost estimating and phase 2 involved data collection. The third phase was to identify initial cost estimating relationships with the final phase building an excel model to test these relationships. 2.1

Phase 1 – Cost Estimation Techniques for availability

A number of techniques have been developed which range from crude estimations based on cost driving patterns or past experience through to more detailed and accurate mathematical cost models [8]. Although there are many different techniques for product cost estimating (PCE), a comprehensive hierarchical classification of the estimation techniques had not been fully developed until 2006 [9]. Niazi and his colleagues categorised the PCE techniques into qualitative and quantitative. Qualitative which included techniques such as intuitive and analogical. Quantitative including parametric and analytical techniques. For a full review of costing estimating approaches for long-life low volume products please refer to Cheung et al. [10]. Some techniques are well established within certain industries, enabling the optimization of designs and costs in parallel. To enable a provider to cost such a service they need to estimate through life costs including design, initial manufacture and inservice (such as the manufacturing costs for repairs and upgrades). The in-service costs account for up to 75% of the total expenditure through the products life [11]. However, many cost modelling tools and methods are predominantly product based [12, 13] or focus on predicting the obsolescence of e.g. electronic parts [14]. A review of the domain has also found that very few cost estimating tools model in service costs, in particular the link between suppliers in meeting the performance requirements of the service [10, 15]. Research to date has illustrated that products and services have unique properties and new methods are required to model the cost

Phase 2 - Data Collection

To identify the CERs it was necessary to collect appropriate data. For the data collection the following approaches were used;

The data obtained from the industrial parties consisted of full manufacturing, assembly and test failure rates and performance of the products. Initial in-service data was also provided and the host nations of the equipment were given. In summary the following data was analysed: 

Serial Number -This is the unique serial number given to each Avionic Equipment unit produced.



Failure Report Number -This is the unique report number, generated automatically given to every failure reported.



Failure Report Raised Date - This is the date on which the failure was first reported.

Life Cycle Costing - Modelling

677



Failure Origin - The unique aircraft number from which the unit failed or the unique test or build rig identification. From the aircraft number it can be seen which nation the Avionic Equipment was in use with and also whether the aircraft was a single or a twin seat version.

Based on the data, the initial investigation examined the failure rates for the ’pilot sub-system’ failure repairs. The overall aim of the pilot study being, to evaluate the available data in terms of its strengths and weaknesses in ascertaining appropriate CERs.



Nature of Failure - A free text field in which the operator reporting the failure can describe the failure in detail.

3



Environmental Conditions - This is a free text field used to describe the environmental conditions in which the unit was operating before failure.



Corrective Action - This is a free text field used to describe any corrective action taken.



Root Cause - This is a free text field used to describe the root cause of the failure, if known. This is usually filled in at a later date after investigation into the fault is complete.



Preventative Action - A free text field used to describe any preventative action that could be used to avert the failure from occurring. Again this usually filled in at a later date after the investigation into the fault is closed.



Fault Code 1 - A classification system for failures given by BAE Systems, including for example: 

AML crystal display failure;



Backlight driver failure;



Display head assembly failure;



Fan failure;



Key panel failure;

The Fault code 1 failures then sub-divide into greater detail for that particular failure type. 

Module Name - The name of the module which failed within the Avionic Equipment unit, selected in the form of a drop down menu.



Module Serial Number - This is the unique serial number of the module which failed within the Avionic Equipment unit.



Failure Phase - The phase of the products in-service lifecycle in which the failure has occurred, given by one of the following:

To identify initial CERs for future evaluation three batches of Avionic Equipment and their associated failure data were investigated, giving a total of 665. It should be noted that the following CERs represent a particular failure for the unit and are not indicative to all sub-systems/components within the unit. The data was analysed to identify trends in failure, to estimate for example; expected failure rates and whether multiple failure rates would occur and to identify whether different performances were found for different nations. For the rest of this paper the failure type is referred to as ‘pilot sub-system’. 3.1

CER1 – Probability of a first fail

From the 665 units investigated, 154 modules had a ‘pilot subsystem’ fail at least once. It can therefore be said, as an estimate that the failure rate for the pilot sub-system’ is 0. 23. It should be noted that the 665 sub-systems includes units not yet in-service. CER 1

Failure rate for ’pilot sub-system’ = 23.16%.

The avionic equipment has only been in use for eight years. As this CER is based on proportions, the estimate is only valid for an eight year period and further analysis of new data will be required to see whether this applies to further product batches. It will also be important to assess where the failures occured. For example a failure in the early design phases may result in some re-design, which may be more cost efficient. 3.2

CER 2 – Probability of Repeat Failure

In addition to the initial failure rate, there is also a probability of the ’pilot sub-system’ failure happening again in the future. From the 154 modules which failed, 36 failed twice and six modules failed on three separate occasions. From this it can be said that if the Avionic Equipment pilot sub-system were to fail it has a probability of 23.38% to fail twice and 3.4% to fail on a third occasion.



Acceptance test;



Build test;



Flight;



Ground;



Manufacturing;



Stores;



Retest;

3.3

Other;

As the overall aim of the research is to ascertain cost of avionics for throughlife availability, the data to be analysed also includes the impact of failure through-out the lifecycle. The aim of identifying this CER was to ascertain the impact of failure in each lifecycle phase. This can then be ustilised to determine the impact on availability. For example, build and test failures may mean less product are available for use in replacement/exchanges.

 

PHASE 3 – IDENTIFICATION OF INITIAL CERS

ETI (Elapsed Time Indicator) - Every unit manufactured is installed with a microchip which logs the total ‘powered up’ time for the unit. When a failure occurs this figure is logged as the Elapsed Time Indicator (ETI).

The standard process for dealing with an Avionic Equipment failure is that firstly the failure is reported by the BAE Systems representative involved. Following this an investigation is launched, in which an attempt is made to discover the root cause of the fault. This may be done internally within BAE Systems or at the original suppliers, depending on the actual failure. This data can then in turn be transferred into Microsoft Excel for analysis. By liaising with the database operators, the full failure data for the avionic equipment were transferred into a spreadsheet for analysis within this research.

CER 2

If the Avionic Equipment pilot sub-system were to fail it has a probability of 23.38% to fail twice and 3.4% to fail on three occasions.

CER 3 – Probability of Failure in a Lifecycle Phase

The results could also be used to determine the cost of a failure, which will vary within the lifecycle of the product. For example a module failing during flight will involve costs such as aircraft down time, where as a failure which occurs during a build test will not. The results show that there is a considerable variance in the number of failures which occur in each phase, with Build and Test accounting for 60% of the total ’pilot sub-system’ failures.

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This data can therefore be used to calculate the probability of which phase any given failure is likely to occur. The calculated probabilities are shown in Table 1. Phase

Probability

Acceptance Build Test

1.3%

3.4

CER 5 – Weighting for Nations

The aim of this CER was to ascertain whether the Nations had differing failure rates. The interest in this particular CER was to ascertain whether this was the case and if so identify future activities to determine why. Within the industrial data four nations were represented with the total Avionic Equipment and the type of aircraft as shown in table 3.

59.2%

Flight

6.1%

Ground

9.2%

Manufacture

0.4%

NA

5.7%

Other

11.8%

Stores

5.3%

Retest

0.5%

WASMU R2

0.5%

Table 1 - Failure Phase Probability for ‘pilot sub-system’ CER 3:

3.5

If a’pilot sub-system’ were to fail the probability that it will fail in flight is 6.1% (use percentage in table 1 for each phase).

CER 4 – Probability of a Particular Fault Code

Nation

IP



PUC -

-

NYK -

Not Yet Known

SCO -

Defective Soft Keys



SPO -

Defective Potentiometer



NFF -

No Fault Found

IP

B

28

15

43

C

11

8

19

D

19

9

28

94

48

142

Nation A

Number of Avionic Equipments in Use 204

B

174

C

81

D

111

From the failure data spreadsheet, the number of pilot sub-system failures for each nation can be determined, and expressed as a proportion of the total number of Avionic Equipment units in use, shown in Table 5. Total Failures

A

Number of Avionic Equipment in Use 204

B

174

15

8.62%

Probability

C

81

14

17.28%

Nation

Proportion

0.87%

D

111

16

14.41%

31

15.20%

NFF

10.53%

Table 5: Proportion of In-Service Failures.

NYK

5.26%

PUC

63.16%

SCO

9.65%

SPO

10.53%

These results could be misleading as they only account for the total number of Avionic Equipments fitted on the aircraft at any given time, and not the number in spares for example. Therefore the proportion should not be used as a probability for failure for a given nation. However the data is valid for giving a comparison between the failure rates of the four nations.

Table 2: Probability of Fault Code 2 Failure. CER 4:

52

Table 4: Number of Pilot Sub-Systems in Use by Nation.

The aim of this CER was to ascertain the different frequencies for the second level fault codes. For each of these codes ‘should costs’ can then be allocated and the costs of the failures predicted. The most common fault code 2 was found to be due to processing errors during manufacture. From this data the probability of the fault code 2 for any given Avionic Equipment ‘pilot failure’ are summarised in Table 2. Fault Code 2

16

From this data the number of Avionic Equipments currently inservice for each nation was calculated as a single seater aircraft having three Avionic Equipments and a twin six. The results are shown in Table 4.

Process Error During manufacture



36

Table 3: National Aircraft Figures for the Avionic Equipment.

ALS Values Out of Tolerance



Total

Twin

A

Total

Within the industrial data, a secondary fault code was also given under the Fault Code 2 data field. This field enabled analysis and classification of the failures in terms of the type of failure that may occur. For the ‘pilot sub-system’ there were six second level fault codes including for example; 

Aircraft Single

If a ’pilot sub-system’ were to fail the probability that it will be fault code PUC is 63.16% (use percentage in table 2 for each code).

This comparison was used to develop a failure factor for each nation, as shown in Table 6, with the benchmark being set as 1. These failure factors can be used to calculate the failure rate for a given nation by simply multiplying the factor with the standard failure rate calculated under CER 1. Alternatively, for a given

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contract the failure factors can be combined based on the proportion allocated to each nation, and an overall project failure rate calculated

3.6

probability of greater than one failure on an Avionic Equipment,



an indication of the phase in the life-cycle where the failure would be expected to occur,

A

1.09

B

0.62



probability of a failure having a particular fault code, and

C

1.24



a representation of a Nations failure factor.

D

1.04

However, the data was for a period of eight years and did not reflect adequate numbers to make decisions for in-service CERs. The data although expansive needed a greater level of granularity, for example, the time the Avionic Equipment is powered up does not give adequate information on the actual use. Was it in flight, did it just have power? This indicates for validation of the initial CERs and future work, a greater level of detail and breakdown of the data is required to offer a more robust set of CERs. This level of data will enable the user to predict for example, the Mean Time Between Failures, Mean Time To Repair and Mean Time Between Unexpected Removals. These times are sometimes available for particular electronic components, however, they are not always easy to estimate for systems as described by Smith [18]. Data in terms of returns, identified failures and unidentified failures are required to ascertain the expected costs for availability. Understanding the operating conditions will also enable the estimator to ascertain ‘real’ availability and breakdown scenarios within a particular context.

Weighting factors to predict in-service failures per nation

Other CERs investigated – No Relationships Found

Phase to Phase One hypothesis was that failure in phases correlated with failures within particular phases. For example, if the Avionic Equipment was to fail during manufacture it would be more likely to fail during the build and test phase. To test this hypothesis all the data was manually checked to ascertain whether a part failed across different phases of the lifecycle. If this did occur the aim was then to see whether there were any correlations. However, only two of the 154 failures occured in the same product in different phases of the lifecycle. On further investigation it was found that a large proportion of the failed Avionic Equipments had not been re-released for further use. In otherwards if the equipment had failed in the manufacture, build and test phases to date they had not yet been used in service. The impact of this is that the hypothesis still requires further investigation when the in-service data becomes available. The current research is due to be completed by the end of 2014 and data will be provided by the industrialists throughout the research period.. Phase to fault code Another potential relationship discussed was whether a certain type of pilot sub-system failure, i.e. fault code 2 was more likely to occur in one phase than any other. However it again became apparent that due to the low numbers of failures in certain phases and certain fault codes it was not possible to determine a fair cost estimating relationship at this stage of the research for all the fault code 2 possibilities. However, for this pilot study 154 failures were investigated with 63% of these occurring during the manufacturing life cycle phase due to processing errors in manufacturing. This offers utility to the industrialists as it is of practical value illustrating the as-is state of failures. DISCUSSION

The aim of this pilot study was to analyse the quality of data available and to identify initial CERs for estimating the cost of avionic through-life availability, answering the following questions: 4.1

initial failure rates,

 Failure Factor

Although five CERs have been identified other relationships were investigated namely, whether there was a relationship between the history of the part in a particular phase impacting another phase and whether particular fault codes related to phases.

4



Nation

Table 6: Failure Factor for Four Nations. CER 5:

data five initial CERs have been identified for future analysis and validation. These CERs represent;

Is the industrial data available for identifying CERs for avionic availability?

From the data sourced within the industrial partners it was found that there was a reasonable amount of data available. From this

It was also noted in the data analysis that 12% of the failures were classified as ‘other’ under the fault code analysis, which was unhelpful in terms of identifying the reasons for the failure. To provide a robust cost model the actual costs, should costs and estimated costs need to be compared. 4.2

Do the CERs vary between nations utilizing the Avionic Equipment?

The CERs were viewed to be applicable across nations however; the failure factor was different for each nation. Although the data can be used to provide such factors as shown in Table 6, it is important that further work is undertaken to ensure the comparison is sound. For example, the industrial data was not used to classify test sites, particular methods, or particular operators. The test procedures may vary slightly and the threshold levels for pass/fail may be dependant on the sensitivity of the test equipment. The proposed failure factors are an initial start point to ascertain whether there is a clear difference between nations. The data can then be used to determine any correlations between particular operating environments, climate and so on. 4.3

Does the history of the product affect failure rates?

For this particular research question the data reflected that this hypothesis did not hold true. It is the authors’ view that further investigation is worthwhile, as the in-service data did not represent data from the failed modules. 5

SUMMARY

This full research programme for the project Cost of Avionic Through-life Availability (CATA) aims to provide novel approaches to predict the manufacture and repair costs through life for inservice avionic systems. The study presented in this paper summarized the initial findings from the research where cost estimating relationships were identified for use within the cost model. In terms of the industrial data, it was found that there was a large amount of data available, although further data collection/breakdown was required. Assessing the available data

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and determining what future data collection would be required for the full project was a key objective of the pilot study. The positive outcome is that data is available, further data can be accessed and the costs for availability can be estimated. The next stage of the research is to build on the proposed CERs and validate these within the project. The CATA project is multidisciplinary and involves three industrial partners, three UK Universities and two US Universities. These have been selected to provide expertise in the supply chain, through life costing, assessing uncertainty and to represent the supply chain from concept design through to manufacture and disposal. 6

ACKNOWLEDGMENTS

We would like to express our thanks to the Engineering Physical Sciences Research Councils Innovative electronics Manufacturing Research Centre. 7

http://www.dau.mil/pubscats/PubsCats/PM/articles96/man ary.pdf pp. 37-40. [12]

Scanlan, J., Hill, T., Marsh, R., Bru, C., Dunkley, M. and Cleevely, P. (2002): Cost Modeling for Aircraft Design Optimisation. Journal of Engineering Design, 13 ,pp. 261-269.

[13]

S. Castagne, R. Curran, A. Rothwell, M. Price, E. Benard, S. Raghunathan, (2008): A generic tool for cost estimating in aircraft design, Res Eng Des, 18(4), pp. 149-162.

[14]

Sandborn, P.A.; Mauro, F.; Knox, R. (2007): Components and Packaging Technologies, IEEE Transactions on Reliability Management, Volume 30, Issue 3, pp397 - 401.

[15]

Hollick, L. (2009): Achieving shared accountability for operational availability attainment. Proceedings - Annual Reliability and Maintainability Symposium, pp 247-252.

[16]

Huang, X.X., Newnes, L.B and Parry, G (2009): A critique of product and service based systems. Proceedings of ICMRC, 8-10th September 2009, WMG, University of Warwick, England. Paper on CD.

[17]

Kumar, U.D., Nowicki, D., Ramirez-Marquez, J. and Verma D. (2007): A goal programming model for optimizing reliability, maintainability and supportability under performance based logistics International Journal of Reliability, Quality and Safety Engineering, v 14, n 3, pp 251-261.

[18]

Smith, T.C. (2004): Reliability growth planning under performance based logistics, Reliability and Maintainability, 2004 Annual Symposium - RAMS , pp. 418- 423.

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Saravi, M., Newnes, L., Mileham, A. R. and Goh, Y. M. (2008): Estimating Cost at the Conceptual Design Stage to Optimize Design in terms of Performance and Cost. 15th ISPE Int. Conference on Concurrent Engineering. pp. 123130.

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Rogelio Oliva, Robert Kallenberg, (2003): Managing the transition from products to service, International Journal of Service Industry Management, Vol. 14 Iss: 2, pp.160 – 172.

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Richardson, D and Jacopino, A. (2006): Use of R&M measures in Australian defence aerospace performance based contracts. Proceedings - Annual Reliability and Maintainability Symposium, pp. 331-336, IEEE.

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Mills, J. and Crute, V. and Parry, Glenn (2009): Value cocreation in a UK air defence, service availability contract - the problem of multiple customer perspectives and diverse cultures. In: The European institute for advanced studies in management (EIASM) Naples forum on services: servicedominant logic, service science and network theory, 16-19 June 2009, Capri, Italy.

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Clark,G., Piperias,P., Traill, R. (1998): Life-Cycle Cost/ Capability Analysis for Defence Systems. Melbourne: AMRL.

[7]

Newnes, L.B., Mileham, A.R., Cheung, W.M., Marsh, R. and Lanham, J.D., E Saravi, M. Bradbery, R. W., (2008): Predicting the Whole-Life Cost of a Product at the Conceptual Design Stage, Journal of Engineering Design, Vol.19, No.12, pp.99-112.

[8]

Ben-Arieh, D. and Qian, L., (2001): Activity-based cost management for design and development stage. International Journal of Production Economics , 83, pp. 169-183.

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[11]

Manary, J. M. (1996): Cost Analysis Strategy Assessment. Program Manager Magazine,

Eco Global Evaluation: Cross Benefits of Economic and Ecological Evaluation 1

2

3

2

4

Nicolas Perry , Alain Bernard , Magali Bosch-Mauchand , Julien LeDuigou , Yang Xu 1 2 3

Mechanical and Engineering Institute (I2M) – Bordeaux - France

Ecole Centrale de Nantes, IRCCyN UMR CNRS 6597, Nantes, France

Department of Mechanical Systems Engineering, University of Technology of Compiègne, Compiègne, France 4

Department of Information Management, Peking University, Beijing, China

Abstract This paper highlights the complementarities of cost and environmental evaluation in a sustainable approach. Starting with the needs and limits for whole product lifecycle evaluation, this paper begins with the modeling, data capture and performance indicator aspects. In a second step, the information issue, regarding the whole lifecycle of the product is addressed. In order to go further than the economical evaluations/assessment, the value concept (for a product or a service) is discussed. Value could combine functional requirements, cost objectives and environmental impact. Finally, knowledge issues which address the complexity of integrating multi-disciplinary expertise to the whole lifecycle of a product are discussing. Keywords: Costing; Environmental Evaluation; Value Analysis; Product Lifecycle Management; Life Cycle Analysis

1

INTRODUCTION

Sustainable concerns are increasing in the industrial sector. This paradigm has environmental, economic and social aspects (see Figure 1). Most industries have turned “green” due to regulatory constraints or marketing targets. As for quality management, industries have often adopted these evolutions as non-pro-active actors. There has been a shift from ISO 9000 to ISO 14000. However, few of them have clear strategic policies linked to their priorities and on their project’s return on investment potentiality. Product definitions, manufacturing possibilities, logistics strategies and end of life alternatives offer many ways to work toward sustainability.

addition, consumer tutoring has to focus on the way people use the products and resources in their daily lives (like water, light, etc.). Cost and environmentally oriented industry decisions are therefore, linked. Indeed, when engineers have to work in an environmentallyfriendly way, they try to reduce the quantity of materials used and energy consumption, as a natural reflex. In this way, they do not only decrease the product’s incidence on natural resources but they consequently also reduce material and energy costs in the product’s cost. Section 2 of this paper will discuss the latter. Sustainable materials

Ecological value

Sustainable design Economic objectives: lower operating costs Environmental goals: lower consumption & pollution Social goals: increase life quality Figure 1: Sustainable design goals. The social side of the sustainable approach is hard to deal with and is out of the scope of this paper. However, this aspect should be taken into account very quickly in order to develop new services opportunities that meet consumer demand and optimize the products use ratio (real used time versus overall life time) and their environmental affect [1]. Moreover, there is a huge challenge to consider, namely consumer and engineer tutoring. People have to learn to reduce consumption and pollution in order to adapt to the world’s limited natural resources. Solutions have been found in green manufacturing and green alternatives. That means products that create less pollution at all stages of the product life cycle whilst ensuring minimal consumption of non-renewable resources. In

Health & wellness

SUSTAINABLE DESIGN

Transport

Passive strategies

Whole life costs

Figure 2: Sustainable design interests. In most of the cases, it is the life stage of the product that implies the most important impacts or costs. In other words, an overall cost of ownership is now the target of the designer and the marketing departments. It is the same for environmental design and the use of Life Cycle Assessment (LCA called ecobalance or cradle-to-grave analysis) [2]. As illustrated in Figure 2, the whole life cycle costs are included in the sustainable design concerns and evaluations. Section 2 will discuss the needs of an integrated Product Lifecycle Management system to evaluate all the stages impacted efficiently. Product’s information is unclear or unknown in the early phases when decisions are made and 80% of the final costs have been determined. It is the same problem for environmental consequences. Moreover, Product Lifecycle Management (PLM) definition requires product and processes modelling. These models provide the basis

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8_118, © Springer-Verlag Berlin Heidelberg 2011

681

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Life Cycle Costing - Modelling

for different solutions analysis and optimization. The third section will present a value based analysis approach that enables not only cost, on one hand or environmental concerns on the other hand, to be taken into account, but also proposes a value evaluation and value definition. This section will also introduce the links between value analysis and a PLM information system for sustainable analysis. In order to ensure reliable evaluations, the data must reflect the reality. In addition, the aggregations rules must be adapted to the product portfolio, the organization behaviour and the evaluation criteria. .In order to take advantage of previous or similar projects, it is necessary to look for the best practices for project guidelines and to locate the most important knowledge used. The last section will illustrate the use of roadmap methodologies and knowledge value evaluation to enhance and ensure the success of eco-design approaches in parallel to product costs assessment.

2

COST AND ENVIRONMENT COMPLEMENTARITY

SIMILARITY

AND

As for ISO 9000 standards, ISO 14000 standards for environmental management systems are being developed to formalize the LCA method components [3]. Figure 3 presents a classic Product Lifecycle process. Each stage of the loop includes cost, and environment impacts (consumption and pollutions). Product life cycle costing and LCA aims at evaluating performances on an overall cycle and sometimes on multi-cycles. Blanchard emphasized the cost impacts of the early design stages of a product [4][5]. Except for the use phase, the development step (before manufacturing) allows more than 90% of the future global product costs. In the case of environmental impact, there are no similar data available, but we assume that the ratio should be quite similar. For a whole lifecycle evaluation, cost or environmental indicator definition and estimation is equally as difficult. This section emphasizes the need for integrated information models and expert viewpoints to tackle the whole life cycle evaluation of a product or a service. Incineration & disposal Reuse & recycling

Extraction of raw materials Recovery Recycling material/components

Design & production

Reuse Use & maintenance

Packaging & distribution

good basis for extracting and aggregating manufacturing costs. However, in a world where innovation and R&D projects maintain the competitive, these indirect loads are not easy to assess with real data. At the end of the product lifecycle, there is no rule that guides designers in the whole costs impacts on the final estimate. Depending on the alternatives, some financial advantages can be introduced into the loop. For example re-use as second life subsystems or material recycling can generate positive financial flow and reduce the global bill. The same problems arise from environmental indicators. They have to take consumption of resources into account (mainly raw materials and energy), different types of pollution and emissions (solid, liquid, gaseous) and their impacts (human, eco-system, ground, water, atmosphere …). As for cost analysis, some life phases or resource consumption can be monitored easily, such as power supply factories, distribution in a known supply chain, etc. However, in a continuously moving network of enterprise, many measurements depend on the networks dependences. Consequently, the evaluations may be inaccurate during the product development. The real choise of suppliers uses criteria far from the environmental scope. Moreover, the end of life may have a great impact. Depending on the existing recycling paths, or developed technology, this impact could be positive and enhance the global environmental dependence. Burning or landfill solutions will no longer have a future. Industry and designers have to consider this impact in their future designs and developments. Automotive regulations for 2015 will limit the percentage of CO2 emission but also impose a high ratio of recycling for vehicles at the end of life. The use phase of a product is hard to evaluate. In Business-toBusiness relationship this phase is quite well defined and could lead to good evaluations. Whereas Business-to-Consumer products could lead to unusual uses which lead to unexpected costs or environmental consequences. In the case of a LCA, the life phase may be the most noxious. Designers and industry have little impact on it. Here start the limits of designer’s possibilities. Only efficient information and tutoring of the customers lead to reach real sustainable products. Even if it seems impossible to define the whole lifecycle completely, similarities and complementarities arise from the two modelling points of view: cost and environment. In each case, the product evolutions have to be modelled and evaluated. Energy and material consumption are required data for both. Product transformations models are also sources of common rating. Thus, process and product models are used to perform cost analysis and LCA of products through different stages of manufacturing, use, and endof-life options. The system can be analyzed using process flow diagrams. In these representations, the inventory of environmental impacts and resources used is comparable. It provides joint cost and environmental analysis [8][9]. 2.2

Figure 3: Product Lifecycle process. 2.1

Full lifecycle model

Total lifecycle modelling is unachievable. Indeed, specific lifecycle phases have complete definition due to the possible detail of the basis activities (that consume costs or affect the environment). Moreover, costs become shared results for a network of stakeholders [6]. They shift from a productive industry (mainly direct costs linked with manufacturing costs) to a cognitive and world wide networked industry (with major allocations related to indirect costs linked with study and developments stages) [7]. As a result, the product lifecycle phases are already partially formalised. These phases can be more easily populated and monitored. Indeed, the process definitions (required by ISO 9000 standards) provide a

Full lifecycle information

Most of the time, the expected information is only partially defined or not defined at all in the early phases when decisions are made [10]. As a result, it is hard to develop cost or environmental design strategies which could guide designers efficiently, due to these nontrustable values. Specific risks analysis evaluation should be done at the key stage of the product-process development. A contingency analysis would allow the variability of the results to be measured and highlight the main incident factors [11]. These methods are still under validation from an environmental point of view. It seems possible to have detailed information on some stages like manufacturing, packaging and transport or from the recycling

Life Cycle Costing - Modelling processes. Even in these cases, the real data are not so easy to capture [12]. Nowadays, the supply chain is world wide, and the reality of modelled processes and data collection are hard to guarantee [13]. This is the case for cost evaluation and the environmental aspect despite the standard framework imposed to the suppliers. Consequently, calculations must be made using unknown data and have to be interpreted as relative values in most of cases. Thus ranking a new product or product process alternative might be hazardous. 2.3

Multi data aggregation

Another common issue remains regarding the needs for calculation with multiple kinds of data. In the case of LCA, the environmental impacts included are: global warming, acidification, energy use, non-renewable consumption, water eutrophication, gaz and toxic emissions to the environment, etc. This combination of multiple and non-homogeneous data highlights the issue of indicators design and equivalence definition. Some research proposals have started working on unified metrics unities. For instance, they propose decibels as a possibility. This solution has no unity dependence and indicates the contribution or losses of the value (the decibel is calculated as a ratio compared to a nominal value). The energy equivalent calculation is another possibility. This thermodynamic concept suites to measuring material and energy resource consumption for each impact [14][15][16]. In the same way as having a unique cost indicator, Perrin promoted the single value added unit methodology [17][18]. This proposal tries to find an independent cost unit that could facilitate the real representativeness and the final aggregation. In fact, Perrin realised that the analytical accounting system is not adapted to industrial reality. In the same philosophy of cost independence, target costing or activity based costing approaches were developed and adapted to use and integration in design methodologies [19][20][21]. Based on these studies, the concept of value promoted by Porter arises as a global and transitional concept applied to both costs and environmental analysis [22][23]. Indeed, traditionally value includes different factors such as cost, quality, delay, and enables value chain evaluation and optimization to be carried out [24][25]. This notion of value could easily be extended to environmental aspects.

3

LIFECYCLE ENGINEERING AND PRODUCT LIFECYCLE MANAGEMENT BASED ON VALUE EVALUATION

As mentioned in the previous section, whole lifecycle evaluation means formalization and information at all stages of the product development. Nevertheless, the product itself cannot be the only focus. The processes that support product development, manufacturing, using step and end of life dismantling also have to be taken into account. As a result, the information system that supports such approaches must take both product/process into perspective as well as different stakeholder viewpoints [26]. PLM systems rely on a data model composed of business objects that intervene in business processes and in product portfolios. Several modelling methods and languages have been developed to model these objects. Many languages enable the representation of these objects and related activities like SADT or IDEF3, Business Process Modelling Notation (BPMN) [28] or Functional Behaviour Structure (FBS) coupled with Product Process Resources and External effects (PPRE) [29]. The establishment of patterns, based on this language, describes an approach to represent the processes. CIMOSA [30], ARIS [31], GRAI [32], PERA [33] are modelling languages and modelling methodologies that must be adapted for PLM implementation.

683 3.1

The value nutshell for cost and environment analysis

To ensure an efficient twin-eco evaluation (economic and ecological), it is necessary to quantify the alternatives for product and processes. This quantification will be functional, economical and environmental. In order to take into account stakeholders viewpoints, each aspect has to be weighted. The final choice will be made according to the strategy or the enterprise objectives. Value is a concept that enables different factors to be analyzed independently or in combination. Performance and value indicators, presented in Figure 4, come from a reflection on the benefits of product manufacture for each benefiting entity [25][26]. Product performances

Benefiting Entities

Quality

Product Value

Enterprise performances

Shareholders

Cost a

Delay

Cost Quality

Clients Manufacturers

Technical performances

Designers

Environmental performances

Suppliers

Technical performances b

Impact

Processes Value

Delay

Environmental performances

Benefit

Figure 4: Performances that affect value and their interactions with benefiting entities [25]. Process

is a chain of

Value Chain

is realized by

Product

actives constraints is a chain of

Expert knowledge

are defined by

constraints

are defined by

Activity consumes

must realize or realizes

Function Resource

Component

consumes

Figure 5: Structure of the concepts for industrial system modelling. Mauchand proposes a product-process data model focusing on the value chain modelling and evaluation (see Figure 5) [25]. This model needs to integrate lifecycle concepts in order to enrich the value concepts with environmental concerns. For example, the process can be extended to product stages, and will represent all the steps illustrated in figure 3. Labrousse links the Product Process Resources model to the Functional Behaviour Structure view. This solution gives the opportunity to manage both value and value chain evaluation (while using the model in figure 5) and the dynamic aspect of the life cycle evaluation. From a product (set of N functions), different technical solutions meet the needs. In addition, for each solution, the processes alternatives (composed of a set of activities) can lead to the product development and use. For each path, a value chain can be defined as illustrated in Figure 6. Using this method, Mauchand proposes a Value Chain Simulator (VCS) that can compare solutions. Depending on the weights applied related to the benefiting entities interest, the solution will balance high technical performances oriented possibilities, low costs (or adapted market) solutions and environmentally friendly proposals. The structure and basic elements of the VCS are illustrated in Figure 7. Despite all the qualities of this proposal, there is still something missing in terms of lifecycle simulation with such tools. Indeed, the model and data system required for the simulation are hardly complete. Moreover, this tool has mainly been dedicated to the manufacturing phase [25] and must be adapted to the other product lifecycle stages.

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Life Cycle Costing - Modelling

Function

Technical Solution S1

F1

OR

F2 Product

AND

F3

AND

Value Chain

Activity

AND

S2

A1 A2

S3

OR

A3

S4

AND

A4

AND

VC1

AND

VC2

alternative activities of the normal use. This allows evaluating the product and the customers’ impact (depending on its behaviours). This example gives an idea of what a PLM system with evaluations facilities could be.

… Fi … FN

… Sj

… AND

…

SP

Ar

…

Is produced by

AQ Is an element of

Figure 6: Choice process of value chains alternatives.

Figure 7: Value Chains Simulator Architecture [25]. 3.2

PLM system definition

In order to ensure a full product lifecycle evaluation, the life model and life used phases have to be represented and completed with relevant data. LeDuigou proposed a PLM structure adapted to SME’s. Supported by the French Technical Institute of Mechanical Industries (CETIM), this work wants to provide a solution for the SME’s. With this PLM information system, they can get into an extended enterprise structure with measured investments and time [34]. Based on product – activity – resources – organization meta data structure (see Figures 8 and 9), this proposal has to be aligned with the previous value based one, in order to allow its use for assessment of the product lifecycle model. This PLM proposal is based on SME’s needs and requirements analysis [35]. Consequently, it is not completely adapted to the cost and environmental evaluation. Indeed, the different indicators measures can be implemented at all the levels: product, activity, resources and organization. It appears that if these data are available, the activity and the resource views could quickly give pertinent ratings. In the case of the product, the different lifecycle steps are represented by the different activities linked to the product (design, manufacture, use, disassembly…). In the case of the uses phase, alternatives uses (id es non-nominal) are represented by

Figure 8: Product Activity Resource Organization meta-model. 4

KNOWLEDGE MANAGEMENT FOR VIRTUAL ENGINEERING BASED EVALUATIONS DISCUSSIONS

In order to ensure high quality and efficient evaluations, the model should not only be adapted to the whole lifecycle, but the calculated rank should also be proposed with contextual information and the data that reflect reality. Calculation and aggregation rules, data sources reliability and model representations must be available for the contextualisation of results. Consequently, knowledge from different experts must be integrated in knowledge based systems. This system must be interoperable with all the specific tools from the modelling phase and the data capture to the evaluation and results comparison or optimization. Virtual engineering environments allow the integration of all the lifecycle models. Engineers have new media to interact with the different numerical representation and simulation models. They use them for definition and industrialization of complex systems that must integrate more and more perspectives in a short time. The challenge is in the improvement of product development environments and the design of virtual engineering platforms software that take all the phases of product and system lifecycle into account [37]. Consequently, knowledge tracking, identification and formalization, from different expertise, at different levels of detail must be carried out and integrated in knowledge-based engineering platforms. Specific methods ensure the coherence and consistency of these knowledge based system developments [38]. In order to ensure the multiple expertise coherence and interoperability (from the knowledge and software point of view) various integration models exist, and ontology based approaches seem very promising for the future 2.0 technologies [39][40]. For instance, specific ontology definitions of concepts like cost- has already been proposed [41] and can be combined with environmental-, or sustainability ontology [42]. Exchanged documents and previous projects are the information repository areas that can be exploited to enrich the expected knowledge (on costs and on environmental evaluation) [43]. From these documents, key knowledge can be identified. Xu proposes a knowledge value rating system that allows the optimization of the best evaluating models, representative methodologies or efficient software that should be used to quickly and sharply answer the product or systems cross evaluations [44][45]. This proposal gives the potential of pertinent selection for evaluation techniques, depending on the level of product development, information maturity, perspectives and target constraints. Such an operational system is not yet in use. Indeed, the basic compounds of knowledge evaluation have been proposed and offer promising possibilities to browse and select the most efficient and pertinent elements to be integrated into the global knowledge database. The

Life Cycle Costing - Modelling wish to integrate the knowledge of several experts to all phases of the product life cycle leads to a huge system that is unmanageable and unusable. Information reduction coupled with intelligent information technologies (id. es. 2.0) can reduce these risks.

685 capture level for simulation lacks accuracy or sensibility analysis for evaluating the quality of the results in terms of confidence or main factor impact. The performance indicators, cost or environmental impact, can be analyzed separately or shared in a common nutshell such as the value concept. Therefore PLM possibilities, dedicated to data management and information management of product regarding its lifecycle, can be adapted to support the different eco’s calculations (from an economic and/or ecological point of view). Moreover, to ensure a good level of results contextualisation and best practices integration, expert knowledge integration must be included in a knowledge database. These knowledge databases are structured to support the definition and the development of agile virtual engineering platforms. Indeed, the modelling tools might be different from one phase to another. The kind and quality of information will be at different levels. In order to maintain coherence and ensure agility with future software integration in the engineering method, ontology based systems can offer solutions for service oriented architecture for platform development. This type of global approach cannot be addressed in a single project or test case, but results from development strategies of the different identified bricks and their integration in a coherent global proposal.

6

Figure 9: Product – Activity and Resource models [36]. 5

Brissaud D., Lelah A. (2010): A framework for the design of sustainable product-service systems, Conference on Advances in Production Management Systems, APMS 2010 Proc., Italy.

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[12]

Perry N., Bernard A., Delplace J.-C. (2007): Concurrent Cost Engineering for decisional and operational process enhancement in a foundry, International Journal of Production

CONCLUSION

This paper highlights the complementarities of cost and environmental estimate. The same needs and limits for whole lifecycle evaluation appear for cost or environmental application. The modelling level lacks some lifecycle phase’s representation due to absent data or unknown solutions for these phases. The data

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BPMN:

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Index of Authors

A

Clegg, A.

160

Gao, J.

564

Abele, E.

Coatanea, E.

647

Gausemeier, P.

431

Colwill, J.

160

Germani, M.

569

258, 280, 299, 341, 347

Albrecht, M.

90

Almeida, D.

611

Gernuks, M.

Antheaume, N.

641

D

Appel, D.

225

Dagman, A.

Azevedo, M.

575

B

558

395

Goller, S.

519

Deng, Y.

605

Golovatchev, J.

549

Dettmer, T.

623

Gomes, J. O.

407

Gomes, V. E. O.

407

Dewulf, W.

329, 377, 605 219

Gondran, N.

593

263

Götze, U.

635

341, 347

Green, P.

675

235, 401

Grimes-Casey, H.

558

Grundemann, L.

617

Gupta, A.

240

Bähre, D.

287

Dhanik, S.

Barakat, S.

476

Diaz, N.

Barquet, A .P. B.

470

Dietmair, A.

Behmann, B.

225

Dilger, K.

353

Döbbeler, B.

Berger, U.

57

Domingo, L.

148

Bernard, A.

681

Dornfeld, D.

17, 195, 263

Bertoni, A.

669

Dreux-Gerphagnon, B.

Bertoni, M.

669

Duflou, J. R.

Bierer, A.

635

Binder, E.

90

Bellgran, M.

Bittencourt, J. L. Bjørn, A. Bley, H. Bogdanski, G. Böhme, S. Boks, C.

253 599

Eberspächer, P. Egede, P.

389

51

492

Halubek, P.

51

258, 299

Hameyer, K.

531

Evans, R.

564

Hanafi, J.

167, 173

Evrard, D.

148

Hanisch, C.

641

F Fang, K.

305

Fasoli, T.

525

497

Favi, C.

569

Braun, S.

341

Feldhusen, J.

459

Brinkmann, T.

617

Felix, J.

201

Brissaud, D.

124

Föckerer, T.

311

Fracaro de Souza, J.

407

Frauenhofer, M.

401

90 549

Freiberger, S.

C

Friedrich, J.

Cha, J.-M.

323, 587

Frieß, U.

Chen, J. L.

101, 107

Fukushige, S.

Chimienti, M.

240

Christiani, A.

492

Ciacci, L.

Gwee, K. H. K.

347

Braun, M.

Budde, O.

323

Halim, A. V.

Eisele, C.

681

96

90 347 513 118,189

G Gadhia, D.

32

Guzman, A.

Haag, H.

341

1, 323

253

Brückner, C.

Gutowski, T. G.

H

E

501

124

Bouzidi, Y.

130 329, 377, 605

Eigner, M.

Bonvoisin, J. Bosch-Mauchand, M.

45

287

Bonefeld, R.

63

Girata, C.

40

45 492 85

Hans, C.

486

Haoues, N.

130

Harrison, A.

657

Haselrieder, W.

85

Hassanzadeh, M.

641

Hauschild, M. Z.

599

Heinemann, T.

317, 531

Heisel, U.

341

Heller, J. E.

459

Helu, M.

195

Henriques, E.

611

Herold, T. Herrmann, C.

45 51, 268, 274, 317, 323, 335, 531, 623

Hirao, K.

359

Hiraoka, H.

419

Hirosaki, M.

189

Horii, K.

419

J. Hesselbach and C. Herrmann (eds.), Glocalized Solutions for Sustainability in Manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd - 4th, 2011, DOI 10.1007/978-3-642-19692-8, © Springer-Verlag Berlin Heidelberg 2011

687

688 Hoyer, C.

Index of Authors 79

Hribernik, K. A.

486

Hyuga, H.

359

Kwade, A.

L Laforest, V.

I

85

Lanza, G.

Nishida, K.

419

Nohr, R.

531

Nuding, O. 593 195, 225

45

O

Ibbotson, S.

623

Larsson, T.

669

Ocylok, S.

235

Ioannou, K.

213

Laumer, M.

67

Oiko, O. T.

470

Isaksson, O.

669

LeDuigou, J.

681

Oliveira, M.

Ito, K.

419

Lee, H. M.

629

Ometto, A. R.

Lee, J. H.

543

Othmer, J.

J

Lehmann, C.

575 142, 470 531

57

29

Leitner, T.

554

P

525

Lelah, A.

124

Passarini, F.

Jawahir, I. S.

240

Li, B.

437

Peças, P.

611

Jayal, A. D.

240

Li, W.

1, 268, 274

Pechmann, A.

293

Jeong, S.

323

Liu, G.

437

Pehlken, A.

465

Jindal, A.

448

Low, J. S. C.

629

Pereira, F. A.

431

492

Luger, T.

623

Pereira, J. P.

575

Lutters, E.

581

Perez, R.

219

Luttropp, C.

482

Perry, N.

681

Pialot, O.

413

Pigosso, D. C. A.

136

Piorkowski, B.

564

Jäger, H. Jantunen, E.

Jobiliong, E. Johansson, B. Jonsson, C.

201, 395 201

96

K

M

Kara, S.

1, 268, 274, 335, 623

Martinez, S.

641

90

Mathieux, F.

124, 148

Plumeyer, M.

497

454

Pollmanns, J.

459

Käufl, J. Kawachi, E. Y.

407

Maurer, K.

Ke, Q.

437

Mederer, M.

443

Priarone, P. C.

365

235

Medyna, G.

647

Pries, H.

235

329, 377

Mehnen, J.

657

Prox, M.

652

492

Pschorn, J.

623

Puglieri, F. N.

142

Putz, M.

507

Kelbassa, I. Kellens, K. Keloeian, G. A.

558

Melini, E.

Kickert, V.

581

Mennenga, M.

Kieckhäfer, K.

79

Mileham, A.

Kiefer, J.

207

Millet, D.

Kishita, Y.

189

Minhas, S. U. H.

51, 531 675 413, 647 57

45

Klute, S.

537

Mittal, V. K.

383

Rahäuser, R.

Knutson Wedel, M.

395

Mizuno, Y.

189

Rahimifard, S.

Kolbe, C.

537

Moenne-Loccoz, G.

148

Redelsheimer, E.

263

Komoto, H.

663

Möller, A.

652

Rees, G.

675

Kondoh, S.

113, 359

Momberg, W.

67

Refflinghaus, R.

537

Kortelainen, J.

525

Morbidoni, A.

569

Reichel, T.

513

Krebs, P.

179

Moreau, V.

593

Reinhardt, S.

311

Kreling, S.

401

Morselli, L.

96

Reinhart, G.

Krellner, B.

519

Müller, S.

Klocke, F.

Krinke, S.

11

113, 359

R

Mishima, N.

235

Kristina, H. J.

492

N

Kunii, E.

118

Narayanan, A.

Kunz, H.

401

Newnes, L.

Kurdve, M.

353

Ng, R.

389, 629

Kuschnerow, J. C.

617

Niemczyk, M.

Rachuri, S.

543 341 154, 160

179, 311

Reis, A.

575

Renaldi

329, 377

Ribeiro, I.

611

543

Riegel, J.

507

675

Riemer, B.

45

Rizzuti, S.

365

Romvall, K.

353

45

Index of Authors

689

Rotella, G.

365

Stein, N.

Rothenbücher, S.

280

Steinhilper, R.

Roy, R.

657

Stevels, A.

167

Rozenfeld, H.

136

Strömberg, E.

482

Rugrungruang, F. Rühl, J. Rünger, G.

246, 389 195 513, 519

S

Suh, S.-H.

554

Whitefoot, K.

558

90

Wictorsson, J.

353

Winebrake, J. J.

558

Witherell, P.

543

323, 587

Sundelin, A.

201

X

Sutherland, J. W.

305

Xirouchakis, P.

219

Swat, M.

287

Xu, Y.

681

Sääski, J

525

T

Sakai, T.

425

Takata, S.

425

Yang, C. J.

Salhofer, S.

454

Tchertchian, N.

413

Yang, Y.-C.

Salonen, T.

525

Teixeira, P.

611

Yeo, Z.

Sangwan, K. S. Santini, A.

51, 371, 383, 448 96

Terzi, S.

Y

317, 335

492

Thoben, K.-D.

465, 486

Sarkar, P.

543

Tomiyama, T.

663

Schäfer, P. D.

501

Toxopeus, M.

581

Schiffleitner, A.

554

Tracht, K.

443

Schiffler, A.

280

Trapp, K.

287

45

Schindler, S.

179

U

Schlechtendahl, J.

347

Uhan, N.

Schlegel, A.

507

Um, J.

Schlosser, R.

323

Umeda, Y.

118, 189

Schmalz, J.

173

Urbanic, J.

476

Schmidt, K.

73

Schmidt, M.

652

Schmitt, R.

253

Schneider, D.

443

Schöler, I.

293

Scholl, S.

617

Schrems, S.

258, 299, 341, 347

Schubert, A.

519

Schulz, J.

623

Seliger, G.

22, 431

Seow, Y.

154

Settineri, L.

365

Severengiz, S.

431

Shi, C. W. P.

246, 389, 629

V Vassura, I. Verl, A.

605 96 341, 347

Veshagh, A.

213

Viere, T.

652

Volling, T.

73

von Hauff, M.

501

von Stietencron, M.

486

W Wabner, M.

513

419

Wada, H.

189

Sielaff, T.

280

Walla, W.

207

Silgård Casell, S.

229

Warsen, J.

67

558

Weil, M.

185

Weisheit, A.

235

Shigeji, Y.

Skerlos, S. J. Song, B.

246, 389, 629 73, 79

Wenzel, K.

507

Spitzbart, M.

454

Werner, P.

195, 225

Stachura, M.

554

Westkämper, E.

347

Stahre, J.

395

Wever, R.

167

Weyand, L.

287

Spengler, T. S.

Steger, D.

513, 519

Z Zäh, M. F. Zein, A.

311 268, 274, 323

Zhang, H.-C.

437

Zhao, F.

305

Zhao, Y.

657

Zhou, Y.

359

Zimmermann, W. 305

45

Van Acker, K.

101 246, 389

525

Thiede, S.

Santoso, D.

Schindler, B. A.

107

45