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Volume 9 Number 4 2003
ISBN 0-86176-899-X
ISSN 1355-2511
Journal of
Quality in Maintenance Engineering Maintenance management and modelling: The IFRIM conference, May 2002, Växjö University, Sweden Guest Editor: Basim Al-Najjar
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Journal of Quality in Maintenance Engineering
ISSN 1355-2511 Volume 9 Number 4 2003
Maintenance management and modelling: the IFRIM conference May 2002, Va¨xjo¨ University, Sweden Guest Editor Basim Al-Najjar
Access this journal online __________________________ 327 Editorial advisory board ___________________________ 328 Abstracts and keywords ___________________________ 329 Editorial __________________________________________ 331 Towards a value-based view on operations and maintenance performance management Jayantha P. Liyanage and Uday Kumar _____________________________
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Adaptive model for vibration monitoring of rotating machinery subject to random deterioration Y. Zhan, V. Makis and A.K.S. Jardine ______________________________
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Design and development of product support and maintenance concepts for industrial systems Tore Markeset and Uday Kumar __________________________________
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Integration of RAMS and risk analysis in product design and development work processes: a case study Tore Markeset and Uday Kumar __________________________________
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CONTENTS
CONTENTS continued
An analysis of economics of investing in IT in the maintenance department: an empirical study in a cement factory in Tanzania E.A.M. Mjema and A.M. Mweta ___________________________________
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Application and implementation issues of a framework for costing planned maintenance Mohamed Ali Mirghani __________________________________________
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Note from the publisher ____________________________ 450 Call for papers ____________________________________ 452 Index to Volume 9, 2003 ___________________________ 453
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EDITORIAL ADVISORY BOARD Professor Daoud Ait-Kadi Director, Graduate Industrial Engineering Program, Laval University, Quebec, Canada Dr Khaled S. Al-Sultan Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia Professor A.H. Christer University of Salford, Salford, UK Dr Ir Patrick De Groote Vice-President, ABB/DGS Maintenance Engineering, Antwerp, Belgium Professor B.S. Dhillon Director of Engineering Management Program, University of Ottawa, Ottawa, Canada Professor V. Makis Department of Industrial Engineering, University of Toronto, Toronto, Canada Professor L. Mann Jr Department of Industrial Engineering, Louisiana State University, Louisiana, USA Professor F.G. Miller Department of Mechanical Engineering, University of Illinois at Chicago, Illinois, USA
Journal of Quality in Maintenance Engineering Vol. 9 No. 4, 2003 p. 328. # MCB UP Limited 1355-2511
Professor D.N.P. Murthy Department of Mechanical Engineering, The University of Queensland, Brisbane, Australia Professor Dr Liliane Pintelon K.U. Leuven, Centre for Industrial Management, Leuven, Belgium Professor A. Rahim Faculty of Administration, University of New Brunswick, Fredericton, New Brunswick, Canada Professor Haritha Saranga Indian Institute of Management, Calcutta, India Professor D. Sherwin Department of Industrial Engineering, Lund University, Lund, Sweden Dr Abdel Rahman N. Shuaib Mechanical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia Dr Albert H.C. Tsang Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China Professor Hajime Yamashina Department of Precision Mechanics, Kyoto University, Kyoto, Japan
Towards a value-based view on operations and maintenance performance management Jayantha P. Liyanage and Uday Kumar Keywords Oil industry, Gas industry, Operations management, Maintenance programmes, Values, Balanced scorecard, Performance levels Most of the North Sea oil companies have recognized the need to adjust their management processes, including those concerned with operations and maintenance, to the changed and changing business conditions in industry at large, particularly due to the volatile oil price. This has been a rationale to review organizational operations and maintenance policies by many. This paper describes findings from a research study on operations and maintenance performance conducted in the emerging operating environment with close cooperation of leading oil and gas organizations in the Norwegian continental shelf. An attempt has been made to develop an architecture for effective management of operations and maintenance performance linking results to performance drivers. This has further been extended to apply the balanced scorecard concept. The paper emphasizes the value rather than the cost of operations and maintenance in the emerging business environment, and stress that there is a need to move from a plant-based policy to a more or less long-term business-oriented approach. Adaptive model for vibration monitoring of rotating machinery subject to random deterioration Y. Zhan, V. Makis and A.K.S. Jardine Keywords Vibration measurement, Autoregressive processes Due to the non-stationarity of vibration signals resulting from either varying operating conditions or natural deterioration of machinery, both the frequency components and their magnitudes vary with time. However, little research has been done on the parameter estimation of time-varying multivariate time series models based on adaptive filtering theory for condition-based maintenance purposes.
This paper proposes a state-space model of non-stationary multivariate vibration signals for the online estimation of the state of rotating machinery using a modified extended Kalman filtering algorithm and spectral analysis in the time-frequency domain. Adaptability and spectral resolution capability of the model have been tested by using simulated vibration signal with abrupt changes and time-varying spectral content. The implementation of this model to detect machinery deterioration under varying operating conditions for condition-based maintenance purposes has been conducted by using real gearbox vibration monitoring signals. Experimental results demonstrate that the proposed model is able to quickly detect the actual state of the rotating machinery even under highly non-stationary conditions with abrupt changes and yield accurate spectral information for an early warning of incipient fault in rotating machinery diagnosis. This is achieved through combination with a change detection statistic in bi-spectral domain. Design and development of product support and maintenance concepts for industrial systems Tore Markeset and Uday Kumar Keywords Maintenance programmes, Product management, Reliability management, Failure (mechanical), Life cycle costs, Service delivery systems Product design and service delivery both affect service performance, and therefore a product support strategy must be defined during design stage, in terms of these two dimensions, to ensure the delivery of “promised product performance” to customers. Furthermore, product support strategy should not only be focused around product, or its operating characteristics, but also on assisting customers with services that enhance product use and add additional value to their business processes. This paper examines various issues such as reliability, availability, maintainability, and supportability (RAMS), etc., which directly or indirectly affect product support, maintenance needs and related costs on the basis of a case study conducted in a manufacturing company. The main purpose of the study was to analyse
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the critical issues related to the product support and service delivery strategy as being practised by the company, and to suggest means for improvements. On the basis of the case study, the paper presents an approach for design and development of product support and maintenance concepts for industrial systems in a multinational environment. The paper emphasizes that the strategy for product support should not be centred only on “product”, but should also take into account important issues such as the service delivery capability of the manufacturers, service suppliers, the capability of users’ maintenance organization, etc.
Integration of RAMS and risk analysis in product design and development work processes: a case study Tore Markeset and Uday Kumar Keywords Reliability management, Life cycle costs, Risk analysis, Customer requirements, Dissemination of information Most industrial customers are looking for products that meet the functional performance needs and have predictable life cycle cost (LCC). Due to design problems and poor product support, these systems are not able to meet the customers’ requirements. Major causes of customer dissatisfaction are often traced back to unexpected failures, leading to unexpected costs. However, with proper consideration of reliability, availability, maintainability and supportability (RAMS) in the design, manufacturing, and installation phases, the number of failures can be reduced and their consequences minimized. Based on a case study in a manufacturing company, an approach for integration of RAMS and risk analysis in design, development and manufacturing is presented. The importance of LCC analysis, use of feedback information, and integration of various information sources to facilitate easy RAMS implementation, in combination with risk analysis in the design phase, is discussed. An approach is suggested for integration of RAMS in the Stage Gate model for project and work process management, coordination and
control, to reduce risk. A training program, developed and implemented during the study to create awareness and to improve learning and understanding of RAMS’ aspects of existing and future products and processes, is also presented.
An analysis of economics of investing in IT in the maintenance department: an empirical study in a cement factory in Tanzania E.A.M. Mjema and A.M. Mweta Keywords Maintenance, Computers, Quality The main objective of this study was to analyse the economics of introducing IT in the maintenance department. The economics in this case was determined by conducting a quantitative analysis on the reduction of operational costs, on increase in productivity and on quality improvement. A comparison was made to analyse company performance in the maintenance before and after the introduction of IT in the maintenance department. The analysis shows that there were reductions of operational and inventory holding costs. Likewise, it was shown that there was also improvement in product quality and productivity.
Application and implementation issues of a framework for costing planned maintenance Mohamed Ali Mirghani Keywords Preventive maintenance, Cost effectiveness, Maintenance costs This paper develops a case study on the application and implementation issues of a framework for costing planned maintenance. It outlines the methodology for the development of the case study and presents the major findings of the existing maintenance-costing system of the organization under study. It presents the results of a pilot study of the application of the proposed costing framework to a sample of planned maintenance jobs. It provides recommendations and identifies critical issues for a successful implementation.
Editorial
Editorial
About the Guest Editor Basim Al-Najjar is a Professor of Terotechnology and Department Head of Terotechnology (Systemekonomi) at the School of Industrial Engineering, Va¨xjo¨, Sweden.
The concepts of the available maintenance strategies focus mainly on reducing failures and their consequences. But, maintaining the condition of machinery to fulfil production requirements demands an efficient maintenance policy that can participate in the continuous enhancement of a company’s profitability and competitiveness. In order to achieve an effective integration of relevant working areas it is necessary for maintenance management to select the most cost-effective maintenance policies, models, performance measures, life-cycle cost and assess maintenance technical and financial impact on the company’s profitability and competitiveness. This special issue of the Journal of Quality in Maintenance Engineering is devoted to the advances, developments and applications of maintenance management, mathematical modelling, performance measure, life-cycle cost and maintenance technical and financial impact on the company’s profitability and competitiveness. The papers included in this issue are some of the papers presented at the Conference IFRIM Maintenance Management and Modelling, May 2002, Va¨xjo¨ University, Sweden. These selected four papers cover the following topics: . Describing findings from a research study on operations and maintenance performance conducted in the emerging operating environment with close cooperation of leading oil and gas organizations in the Norwegian continental shelf. We have made an attempt to develop an architecture for effective management of operations and maintenance performance linking results to performance drivers, which has further been extended to apply the balanced scorecard concept. . Modelling a state-space model of non-stationary multivariate vibration signals for the online estimation of the state of rotating machinery using a modified extended Kalman filtering algorithm and spectral analysis in the time-frequency domain. In addition, testing adaptability and spectral resolution capability of the model by using simulated vibration signal with abrupt changes and time-varying spectral content. . Examination of various issues such as reliability, availability, maintainability, and supportability (RAMS), etc., which directly or indirectly affect product support, maintenance needs and related costs on the basis of a case study conducted in a manufacturing company. The main purpose of the study was to analyse the critical issues related to the product support and service delivery strategy as being practised by the company, and to suggest means for improvements.
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An approach for integration of RAMS and risk analysis in design, development and manufacturing is presented. The importance of life-cycle cost (LCC) analysis, use of feedback information, and integration of various information sources to facilitate easy RAMS implementation, in combination with risk analysis in the design phase, is discussed.
The Guest Editor would like to acknowledge the efforts made by Professor David Sherwin in planning this special issue. The authors’ and the referees’ contributions to this issue are highly appreciated. Basim Al-Najjar Note from the Editor The special issue was planned to be exclusively from papers presented at IFRIM conference. The Guest Editor managed to accept four papers from IFRIM for the special issue. Four papers are not sufficient for the special issue and I have added two papers to complete the issue. Papers 1-4 in this issue are from the IFRIM conference and papers number five and six from the regular accepted pool of papers. Paper number five quantifies the economic benefits of introducing information technology (IT) in the maintenance department. The economic benefits have been quantified through quantitative data analysis prior and after introducing IT. The sixth paper presents, through a case study, the application and the implementation issues of a framework for costing planned maintenance. It outlines the methodology for development of the case study and presents the major findings as a result of adopting such a costing system. The Editor acknowledges the authors for their valuable contributions to Volume 9. He is also grateful to all the referees who graciously participated in the review process. In many situations they made improvements to the papers. The skill and the follow-up made by the Managing Editor of JQME are instrumental in preparing the volume. The Rector of King Fahd University of Petroleum and Minerals Dhahran, Saudi Arabia, and his administration are acknowledged for the continuous support provided and the excellent facilities made available. Salih O. Duffuaa
The Emerald Research Register for this journal is available at http://www.emeraldinsight.com/researchregister
The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/1355-2511.htm
Towards a Towards a value-based view on value-based view operations and maintenance performance management 333
Jayantha P. Liyanage School of Science and Technology, Stavanger University College, Stavanger, Norway, and
Uday Kumar Division of Operations and Maintenance Engineering, Lulea University of Technology, Lulea, Sweden Keywords Oil industry, Gas industry, Operations management, Maintenance programmes, Values, Balanced scorecard, Performance levels Abstract Most of the North Sea oil companies have recognized the need to adjust their management processes, including those concerned with operations and maintenance, to the changed and changing business conditions in industry at large, particularly due to the volatile oil price. This has been a rationale to review organizational operations and maintenance policies by many. This paper describes findings from a research study on operations and maintenance performance conducted in the emerging operating environment with close cooperation of leading oil and gas organizations in the Norwegian continental shelf. An attempt has been made to develop an architecture for effective management of operations and maintenance performance linking results to performance drivers. This has further been extended to apply the balanced scorecard concept. The papers emphasize on the value rather than the cost of operations and maintenance in the emerging business environment, and stresses that there is a need to move from a plant-based policy to a more or less long-term business-oriented approach.
Practical implications How operations and maintenance performance (O&M) makes good business sense has become an important issue lately, and has drawn the attention from various corners of oil and gas (O&G) production business in particular. This calls for a more holistic view of O&M and an appropriate basis to show its link to the core business. Furthermore, a comprehensive performancfe assessment system has to accommodate a balanced view on overall performance involving not only results but also drivers of those results, and also should be able to provide some understanding about the causal relationships between them. A notable interest in this regard is to seek ways whereby the popular balance scorecard concept can be applied within O&M process. This paper looks into these aspects in respect of emerging O&G business environment and elaborate how O&M becomes a value-added process to the core business, extending our understanding beyond its pure financial implications.
Journal of Quality in Maintenance Engineering Vol. 9 No. 4, 2003 pp. 333-350 q MCB UP Limited 1355-2511 DOI 10.1108/13552510310503213
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Introduction At the current pace of advancement, both in engineering and business, management disciplines coupled with tighter regulatory regimes, performance management of O&M process has gained considerable momentum, particularly in high risk and capital intensive industries (see, for example, Dwight, 1999; Liyanage and Kumar, 2000a; Tsang, 1999). The petroleum industry, in particular, is keen on the assurance of proper control of production assets through application of asset-wide performance measurement systems. Not only operating companies, but also regulatory authorities (e.g. Norwegian Petroleum Directorate, Minerals Management Service (USA), etc.) have taken interesting initiatives to direct O&G producers’ attention to adapt performance-based reporting mechanisms for their day-to-day operations. As the classical financially-oriented measurement techniques are subjected to wider critics in the contemporary business context (Kaplan and Norton, 1996; Sveiby, 1997), we observed that some of the operating companies have already implemented business-wide O&M performance measurement systems (e.g. Statoil, Norsk Hydro). Many others (e.g. Philips, BP, Shell) have already initiated internal projects to deal with the problem that best suits their business conditions. However, owing to inherent limiting conditions within individual organizational settings these, in general, are relatively far from being full-blown managerial practices yet. Furthermore, as O&M in offshore O&G production assets is subjected to a period of transition, potential opportunities are enormous for novel and innovative approaches that capture O&M performance that makes good business sense. O&G exploration and production by nature is known to be an economically and technologically intensive business. In addition, its social and ecological sensitivity is much discussed and debated lately, resulting in an adaptation of very cautious operational strategies by O&G producers. Subsequently, current practices render adherence to more complex risk-based decision-making processes throughout the O&G production process. As much as risk remains an inherent element in decision criteria that effectively deals with potential threats, asset managers are also seen paying more attention to capitalize on every single opportunity available to them to get the maximum throughput from the asset portfolio for business advantage. For instance, as one of the offshore platform managers expressed: . . . in general we rely on drilling technology and reservoir management to get the best from the existing reserves. But we are aware about confrontations with economical and technological limitations. In order to show that we are competitive in the business and to keep our assets commercially attractive we have to resort to many other potential opportunities that are still left fully un-exploited. One of such disciplines is O&M. We should realise how an effective asset O&M policy can in fact make a difference in terms of delivery of operating results.
The total-value concept that we introduce in this paper explores this Towards a opportunistic phenomenon and elaborates how O&M can be heightened as a value-based view value-added process to the petroleum business. Our postulations in this regard are grounded on the emerging sustainable O&G business context. This sustainable move is seemingly pivotal to redefining the business role of O&M process from a different perspective, yet numerous opportunities it has brought 335 still remains largely un-exploited. Our underlying assertions in this endeavour stem from the fact that commercial competitivity of O&G business is a product of the extent of threat mitigation and opportunity realization in the emerging uncertain, complex, and dynamic environment for O&G business. Background and methodology A joint industry project on the development and implementation of O&M performance indicators for the petroleum industry was initiated by the Centre for Asset and Maintenance Management of Stavanger University College, Norway, in 1999 (see Kumar and Ellingsen, 2000; Ellingsen et al., 2002). Despite that, this project resulted in a comprehensive application of the balance scorecard concept to measure O&M performance of O&G producers, certain limitations were inevitable, particularly owing to practical problems pertinent to availability and quality of data in prevailing organizational enterprise resource planning (ERP) systems. This situation created a need for an independent and an extended research study to develop a more universal and generic theoretical architecture to provide a basis for ongoing efforts within this discipline. This paper is based on inferences drawn from an exploratory study conducted with the aforementioned scope in the Norwegian petroleum sector during the period of 2000-2002. The study adopted a qualitative methodology through interviews, discussions, informal conversations, analysis of three industrial cases and various forms of performance-related business documentations. The magnitude of coverage is 72 formal interviews, exclusive of informal discussions and conversations, that included voluminous and a veracity of information from a total of 65 different personnel and study of three cases, covering a total number of 16 distinctive organizations/institutions. By virtue of the extent of coverage, the entire study is more comprehensive and can be characterized as: . Cross-business. It constitutes views, opinions, and practices from different business sectors of the petroleum industry. For instance, oil and gas production, engineering contractors and suppliers, consultants, certification and verification bodies, and authorities. . Cross-organizational. Iconstitutes views, opinions, and practices from different organizations within each of the business sectors. For instance, it covered six major operators (BP, Shell, Statoil, Norsk Hydro, Exxonmobil, Philips) involved in O&G production in the Norwegian continental shelf.
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Cross-disciplinary. It constitutes views and opinions of peers having professional expertise on different petro-disciplines with a long-term exposure to a spectrum of practices adopted by industry. For instance, operations and maintenance, financial, production/asset management, health/safety/environment, engineering design/modifications, advisory/ consultancy, technology. Cross-hierarchical. It constitutes views and opinions of peers having different roles and responsibilities in organizations, varying from company directors, offshore platform managers to maintenance engineers, who have a direct exposure to numerous practices adopted by organizations.
Premises for the value-based concept Today, the language of the petroleum industry clearly signals a managerial transition to adapt a new decision-making criteria and a course of action; namely, “corporate sustainability” (see, for example, Agbon, 2000; Bradley and Hartog, 2000; Hargis, 2000). For instance, Wolff et al. (2000) reveal that the currently adopted criteria for investment decisions are not exclusively economic in nature, but also take into account social and environmental considerations in appraisal of the security of investments. They also contend, for instance, that the indicator called “consideration of environmental and social criteria in business decisions” captures management programmes and processes aimed at describing the management system’s capability to link sustainability issues to business decision-making criteria for operations and planning, and that green accounting, eco-efficiency measures, total cost assessment, and so on, illustrate further examples. Although the term “corporate sustainability” may convey a difference in meaning to many, prevailing myths around sustainability in general advocates quite a blend of economy and technology; ecology and demography; and governance and equity. In O&G business context today this mainly revolves around: . economical values that rest on the degree of financial accountabilities displayed; . social values that rest on the degree of social equity displayed; and . environmental values that rest on the degree of environmental care displayed. The degree to which O&G operators are opted to this new business norm that, in turn, re-defines delivery obligations, is largely reflected in the current business reporting process. It has explicitly adopted a “triple-bottomline” concept (see Elkington, 1997) over the last few years. For instance, in 1996, a project consortium comprising Statoil, BP, Conoco, and Shell developed a benchmarking portal to review how companies in the O&G business deal
with the issue of sustainable development (Wolff et al., 2000). This portal Towards a primarily constituted five target areas; namely, ethics/corporate core values, value-based view community capacity building, stakeholder relations, environmental management, and economics, that have to be achieved through various internal business drivers. The current trend can be seen as a genuine response to an exposure to a 337 complex profile of risks, and the organizational adaptation to the new world order. This world order is notably generated by: . globalization, liberalization, and technology; in conjunction with . uprising people power; and . concerns on changes in the global eco-system. As such, the definition of management by far has evolved as the process of value creation and risk mitigation in the emerging sustainable O&G business context. The prevailing business environment seemingly is relatively more fertile to much of this transition. Despite the absence of consistent economical theories to directly account business impact of social and environment-related deliveries, there remains a large body of corroborative evidence from various corners of the O&G industry at large about the existing forces that are strong enough to sustain the current momentum. Some of the notable contributions include: . global compact concept initiated by UN; . Dow Jones Sustainability Group Index (DJSGI); . double decade sustainability road map developed by UK Offshore Operators Association; . value reporting technique advocated by PricewaterhouseCoopers; and . sustainable development management framework adopted by Royal Dutch Shell. Our new concept, termed “value-based management of O&M performance”, discussed in this paper, is developed on the basis of empirical evidence from this emerging operating environment for the O&G industry. At the core of expositions there remains the theoretical value configuration of the O&M process as the point of departure with respect to these changing industrial demographics. First, we assert that many recent initiatives and incidents within the O&G industry or the organizational behaviour at large, unveil that the formula for commercial success in the current business economy constitutes a delicate balance of: . delivery of short-term results – concerns profitability prospects; and . consolidation of long-term opportunities – concerns growth potential.
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Second, we argue that the notion of values that are critical to the O&G business in general to arrive at such a commercial success today can in fact be said to be two-fold: (1) Accountable values. The tools for financial managers or accountants to report performance in monetary terms, e.g. cost savings, production volume, cycle time, proved reserves, etc. (2) Non-accountable values. These cannot be presented in monetary terms yet posses a finite value in terms of meeting business prospects and profit margins, e.g. cross-trained labour, intellectual capital, increased work morale, enhanced job satisfaction, customer loyalty, reputation, etc. These values presumably are combined in complex patterns to deliver end results and subsequently to business prosperity. The corroborative facts gathered and insights of informants captured during the study were substantial to unfold this complexity to a considerable degree. The resulting theoretical causal configuration that underlie the value-based concept of O&M performance is illustrated in Figure 1. The working algorithm illustrated here displays a top-down flow that incorporates a particular logic, where neighbouring levels are knitted using specific causal presumptions. This causal algorithm results in the development of the steering model that constitutes four key areas, each with a unique value proposition of its own. These value propositions form the corner-stones of the value-based concept, and are placed in the particular order as illustrated in Figure 1, so that it provides a clear view about the important components of the value-added O&M performance.
Figure 1. Theoretical configuration of the value based O&M performance concept
Moreover, this brings the term value into a broader perspective in comparison Towards a to its relatively stringent application within financial expressions (see, for value-based view example, Porter, 1985; Knight, 1998; Perry and Starr, 2001). Figure 2 illustrates such an application. Thus, we use the term “value” in this article in a different perspective, indicating a clear departure from this classical application of the term in 339 current economical schools. How it applies to an O&G production asset Unfolding the inherent complexity of O&M performance further, and any elaboration on the constituents of the steering model for a more universal architecture call for a better insight into the O&M process and into the environment within which it exists. It implies that we need to develop an adequate level of prior knowledge regarding the role and characteristics of the O&M process and the nature of its interface with the operating environment and the core business. This calls for more detailed analysis that can be accomplished through, what we term, concurrent maintenance assessment. Such assessment is aimed at ensuring: . Vertical alignment. The degree to which the O&M process is aligned with both business policies and asset condition in a given operating environment. Here we follow through a vertical assessment. . Lateral integration. The degree to which the O&M process is sensitive to changes in its environment and to work management policies in other parallel processes. Here we follow through a lateral assessment. . Self-assessment and improvement. The degree to which the O&M process has identified its role and has defined resource, competence, and capability requirements according to their criticality on the process performance and thus on plant health. Here we follow through a self-assessment.
Figure 2. Value-based management in economical perspective
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In principle, this is meant to portray the level of interactivity and dependence of the O&M process in an O&G production environment. The understanding of these dependencies are important insofar as they contribute to our knowledge to unfold inherent complexities of O&M performance, and then to define its causal performance model within a given setting. In general, this relational environment within an offshore O&G production facility can be classified into four classes with respect to the nature and the potential influence (see Figure 3). Administrative services here refer to finance and accounts, secretarial, office equipment, accommodation facilities, catering, etc., where finance and accounts, in principle, concerns salaries and wages, bonuses, insurance and compensation schemes and the like. Typical human resource services encapsulate, for instance, career/employee development, stress management, counselling, training provisions, recruitment, rewards and incentives, provision of necessary access to health, medical and other fringe benefits, etc. The rest of the content in Figure 3, is presumably self-explanatory. Despite that the nature, mechanism and the magnitude of impact of these sources on the O&M process can, in fact, take many facets and can ramify across various corners and in different forms, they in principle, are meant to nurture three important domains that contribute to the quality and standard of O&M performance: (1) operations/work management process to institutionalise green activity, operational intelligence, and supply integrity with the purpose of building an effective operational interface; (2) technology management process to establish technical worthiness of the asset with the purpose of building an effective technological interface; and (3) human resource management process to develop human capital with the purpose of building an effective human interface. Green activity in general concerns whether all specifications pertaining to the set of scheduled activities have adequately been met, and thus qualify for immediate execution in offshore installations. The term intelligence here
Figure 3. The level of interactivity and dependence of the O&M process in an O&G production asset contribute to its performance complexity
implies the ability to understand, learn, and make judgments or have opinions Towards a that are based on facts from the interactive environment, and worthiness value-based view implies suitability to be used, operated or put into function in accordance with pre-defined specifications. They seemingly are considered to be increasingly critical to sustain an efficient and effective O&M support in the Norwegian O&G sector. They remain centrally focussed as it is known that they directly 341 contribute to the health of those offshore assets. Health here implies the inherent condition of an offshore installation and the degree to which it is free of faults and failures, or the state of being well to ascertain safe and sound operations. There are two core aspects that elucidate this health issue from O&M point of view: (1) quality and standard of O&M activities; and (2) safe and sound technical functions of technical items compatible with operational specifications. In fact, the competence that O&G producers develop within these areas is advantageous insofar as they make a difference in terms of end results from the asset portfolio. The current offshore production environment insists that the following results are contingent on the quality and standard of O&M support and the subsequent health of offshore installations: . CAPEX and OPEX: display excellent control of costs and investments; . regularity: assure smooth and uninterrupted production; . occupational health and safety: assure safety to plant and people; and . zero environmental releases: assure environmentally benign operations. Hence, O&M process owners constantly emphasize the need of better understanding and knowledge on O&M performance to pool necessary resources and to develop core competences central to drive those results. Regardless that different organizations attempt to deploy different strategies to build an adequate level of proficiency in this endeavour in accordance with individual business conditions, a review of underlying matters in focus and more recent initiatives unveiled that those strategies constitute quite common elements. Some of the notable ones are illustrated in Table I. On the basis of these elaborations the generic theoretical O&M performance architecture for an O&G production asset can be illustrated as in Figure 4. Obviously, O&M processes do not possess full control over all events in any production asset, as they could occur in a random and abrupt manner. Hence, there are notable hands-out events or occurrences that remain beyond O&M control, yet has some considerable impact on its decisions and activity level. Technical worthiness of plant items can be changed due to process variations; for example, depending on the variations in characteristics of the handling agent (e.g. produced hydrocarbons), pressure and temperature variations, variations in sand, water or gas production, etc. One of the primary forms of
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Premise
Focus/initiatives
Human
Administrative and organizational proficiency
Creating a stimulating work culture Creating a strong social environment to build healthy relationships and teamwork Establishing a support pool of disciplinary experts Promotion of employee physiological and psychological health
Operational
Operations/work management proficiency
Systematic employee competence assessment complying with task specifications Mastering IT platforms for effective information management Developing intellectual capital by all necessary means Sustaining process integrity and pursuit of internal discipline Promoting strategic partnerships
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Technological Technical and EPCICa proficiency
Table I. The most recent initiatives by O&G producers to strengthen triple-interfaces
Figure 4. The theoretical architecture of value-based O&M performance management concept applied to an O&G production asset
Building systematic means for qualifying application technology Assuring quality of technical support process and quality of products Being innovative in developing technological solutions Extracting the best technical knowledge from repositories and experience transfer to substantiate engineering projects
Note: a The term EPCIC here stands for engineering, procurement, construction, installation and commissioning process
degradation due to such variations encompass corrosion in pipes that may Towards a remain undetected over an extended period of time, and this is reportedly said value-based view to occur even under thick insulation. In addition, there can be some operational impediments such as extreme weather conditions, industrial disputes, terrorists threats, etc., that directly impact installation health affecting, for instance, activity carrying level or increasing backlog. Those mostly remain 343 non-amenable to generic O&M policies and may sometimes carry surprises for day-to-day performance and, importantly, successful confrontation of them calls for adequate contingency planning. Regarding “lags” and “leads” or “outcome measures” and “performance drivers”, there are still notable ambiguities as to what in fact they embody in O&M management context. As the proponents of the popular concept “balanced scorecard” advocate (Kaplan and Norton, 1996), outcome measures are to reflect common goals of a multiplicity of strategies, while performance drivers tend to own a sense of uniqueness for the process in question by provision of some opportunities to arrive at desired outcomes. Therefore, they in combination define the path for delivery of results. In Figure 4, performance lags imply what O&M process is accountable to deliver, and performance leads imply the core constituents in the pathway to meet those delivery responsibilities efficiently and effectively. Notably, both social and environmental aspects further generate economical consequences. Value-based concept in global view In general, we emphasize that the value-based concept elaborated here compliments four popular movements today: (1) Total quality school. This recognizes that meeting delivery expectations is a function of developing core technical and organizational capabilities, and systematic approaches to planning and management of activities. Contemporarily, the need for pursuit of quality ramifies across economical, social, and environmental imperatives (e.g. Bank, 1992; Faure and Faure, 1992; Beckford, 1998). (2) Systems school. The systems school in one avenue recognizes that performance is a function of the joint operation of social and technical systems, and in another recognizes continuous interaction of a system with its environment as a basis for evolution. It further advocates integrity and universality of performance within defined boundaries (e.g. Herbst, 1974; Checkland, 2000; Jambekar, 2000; Pheng and Wee, 2001). (3) Process school. This recognizes the need for accommodating horizontal workflows, and strengthening internal interactions and interfacing, and avoidance of sub-optimization for business advantage (e.g. Garvin, 1995; Ljungberg, 1998).
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(4) Balanced assessment school. This recognizes adverse impacts of total reliance on pure financial or result-based measures, and hence the need for assessing overall performance in a financially and non-financially balanced perspective. Another contemporary avenue is the significance of intangible assets (Kaplan and Norton, 1992; Sveiby, 1997). However, importantly, a full-scale application of the value-based concept calls for a rich infrastructure, and an organizational culture that promotes the absorption of the subject matter and its reception as an effective tool to manage performance. Two issues in particular are vital in this regard: (1) Responsibility, i.e. given that all processes in the asset embark on common goals on economics (CAPEX, OPEX, and production or revenue) and health, safety and environment, and that O&M has limited accountability on overall asset performance, it is a requisite to analyse the system in its entirety and pre-define what responsibilities are assigned to O&M process owners and the scope and scale of such an assignment. (2) Authority, i.e. whether necessary and essential authority has been delegated to those O&M process owners to make decisions and take actions in respect of the responsibilities assigned, and that any limitations imposed in this respect is clearly defined. For instance, as revealed by a chief maintenance engineer for a core production area that comprises three major offshore oil production platforms, and who has hands-on experience as a principle co-ordinator for development and implementation of a performance management and review system for one of the O&G producers: . . . a major hurdle we had to jump over was regarding the responsibility and authority. By developing the performance measurement system we have clearly defined what our responsibilities are. To make sure that we deliver what we are bound, we stressed that we need authority. What we said was “if we have these responsibilities and if someone else will have the authority then we are not accountable for any failure to meet our targets and objectives. If you want us to take responsibilities to deliver results that we are bound to deliver we have to be clear about our authority, and for that matter you have to delegate necessary authority effective for our results” . . . Achieving this status has not been so smooth. We continued to attempt through loads of information, defining responsibilities, and setting of ground rules to follow. For instance, we had to remind asset managers whenever he take technical issues to discuss with production people. In fact we had to “arrest” him in a number of times on this matter . . .
For further illustrations of this value-based concept refer Liyanage and Kumar (2001, 2002a) and Liyanage et al. (2001). Value-based concept in balanced scorecard (BSC) perspective The concept of balanced BSC was introduced by Kaplan and Norton (1992). There are two other contemporary concepts that were readily embraced as part
of the same wave; namely, intangible asset monitor (Sveiby, 1997), and Towards a intellectual capital (Edvinson and Malone, 1997). The central theme of this value-based view popular wave, which re-engineered and revitalised long-lasted performance theories is the necessity to see beyond mere financial performance owing to inadequacy of financial measures alone to help guide business success in emerging highly competitive conditions. Seemingly, the application of the BSC 345 concept that has earned the respect of performance theorists comprises two genuine attributes: (1) The framework, that constitutes the proposed four-perspectives; namely: . financial; . customer; . internal; and . learning and growth. (2) The logic, that insist on complementing financial performance with a view on non-financial performance, identifying outcome measures and performance drivers, and building causal relationships. With its increasing popularity, some have attempted to devise BSCs for O&M in the recent past (see, for example, Tsang and Brown, 1998; Ahlmann, 1999; Liyanage and Kumar, 2000b; Ellingsen et al., 2002). Despite that BSC has created many success stories encompassing the organization’s corporate vision, certain ambiguities come to the forefront pertinent to the extent of coverage in the framework. The accompanying ambiguities relevant to O&G business and O&M of O&G production assets have been discussed by authors elsewhere (see Liyanage and Kumar, 2001). Furthermore, Neely and Adams (2001) contend that BSC describes a causal model for enhancing financial returns alone (more importantly, pure shareholder value) disregarding the rest of the stakeholders who matter for commercial success of the business. Ellingsen et al. (2002) have set an example as to how this framework should be refined by adopting a different set of perspectives; namely, cost, operations, organization, and health and safety environment, paying proper attention on the most predominant conditions within the O&G business. Perhaps this ambiguity may largely be attributed to semantics, or rather to the fact that the ideology that the proponents intended to convey may have been subsumed in the entire terminology that underpins the concept but have some genuine social meanings, less in context relative to implications within BSC. However, it is worth noting that the petroleum sector is seemingly attracted to embrace tempting arguments promoted in the BSC concept. Owing to the above, we insist that the application of BSC to O&M process is worthwhile seeing it as a matter of more than just finding “who the customer for O&M is” that often point the finger to production. The message in principle is to look beyond pure financial orientation of performance management
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systems to the other dimensions and also on areas that has potential impact on end results, and thus on the bulk of stakeholders of O&G business activity. This is to entail a fundamental change in the underlying assumptions about O&M performance for the better. Figure 5 illustrates how we make use of the logic of the BSC and an adopted version of its original framework to build the value-based concept for O&M performance highlighted in Figure 4. Notably, we here insist on the overall results rather than cost cutting or controlling operational expenses that in one way has led to demark O&M as a mere cost centre. Such pure cost-based views also led to cutting corners that, in fact, can be a multi-billion dollar deal; for instance, as exemplified by the sunk P-36 offshore oil production platform in deep Brazilian waters recently. Moreover, we assert the fact that sustainable conduct appeals to adapting an optimal criterion for the co-existence of business and its wider stakeholders, and, in the same note, opportunities for O&M in this emerging business conditions are wide open, yet still remains largely unexploited. We are hopeful that the time and circumstances will get us there. Implementation As mentioned previously, the background for this research study was set by the joint industry project on development and implementation of O&M performance indicators for the petroleum industry. The overall results from this project were based on custom practices from individual O&G producers, that captured experience from some of the performance measurement systems already being initiated, and learned through discussions and sharing of information by major players in the Norwegian continental shelf to lay the
Figure 5. How balanced scorecard is applied within the value-based concept
foundation for a standard practice. Even though a consensus was reached by Towards a the members of the project consortium about the framework and the content value-based view therein, some practical difficulties emerged once the implementation phase was reached. The organizations targeted for implementation were not adequately prepared to absorb the change and for immediate implementation of project results. These bottlenecks mainly related to the infrastructure required. Some 347 of the major ones included: . Data. Data available in ERP systems were not quality assured, and many of the data required for computation of indicators were not part of the formal reporting practices. Furthermore, even mining for some of the available data require extensive time and energy in most cases. Moreover, searching through various sources makes it a more tedious task. This also brought in the issue of insufficient configuration of IT systems to facilitate systematic means for data storage, retrieval, sharing, and decision support. . Competence and business setting. It was clear that the offshore O&M crews require some training and education on the subject and on the technical content of measures. Such a commitment was not forthcoming nor feasible due to business situations (e.g. many had not fully recovered from economical impact of low oil price) and, subsequently, priorities were seen lying elsewhere. . Buying-in and culture. Owing to the above reasons, in conjunction with attitude and prevailing scepticism on the actual internal use of measures to support asset decisions, there were difficulties to buying-in offshore leaders and O&M crews to run a pilot study. It appears that various changes, which bombard offshore facilities as innovative solutions, or favourites of the week, from time to time without yielding appreciable results, have contributed to a culture that is mostly cautious and non-appreciative of novel products. For instance, as Ellingsen et al. (2002) note, the more closely a project of this nature approaches implementation phase it becomes more difficult to reach common consensus among several participants. Each end user at the end prefers to adopt his own unique approach that is most compatible with internal strategies and work practices. However, the story does not end there. Process owners still keep the momentum, awaiting opportunities to launch the measurement framework fully or partially depending on internal requirements and in consultation with offshore teams. This obviously requires time and patience. Along with such organizational initiatives, we look forward to launching the next phase of the project aimed at a standardized reporting structure for O&M performance and a Web-based benchmarking portal. Yet, it is a matter of time and circumstances.
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Conclusion Emerging O&G business conditions are seemingly more promising to heighten O&M as a critical constituent of the core business process, yet the recognition of its full-blown potential calls for novel concepts that are more appealing to the management, and promotional campaigns to change the mindset in general. In this paper, we elaborated that the changing conditions in the O&G business can be seen more inclined to adapt a new course for decision making and action taking along corporate sustainability that emphasises wider economical, social, and environmental imperatives of business conduct. In this paper, we introduced the value-based concept of O&M performance providing a basis to redefine the business role of O&M process in production assets in this emerging business environment. We also discussed how the popular BSC concept can be meaningfully used to develop an architecture for O&M performance management process. Overall, our continuous attempt is to explore the subject matter and promote O&M as a value-added process in the emerging O&G business environment. References Agbon, I.S. (2000), “Social responsibility and the sustainable economic development of oil and gas producing communities in Nigeria”, paper presented at the SPE International Conference on Health, Safety, and the Environment in Oil and Gas Exploration and Production, paper SPE, 61102, available at: www.spe.org Ahlmann, H. (1999), “The economic significance of maintenance in industrial enterprises”, paper presented at the UTEK seminar. Bank, J. (1992), The Essence of Total Quality Management, Prentice-Hall, London. Beckford, J. (1998), Quality: A Critical Introduction, Routledge, London. Bradley, A.S. and Hartog, J.J. (2000), “Susutainable development – implementation strategy for a global exploration and production business”, paper presented at the SPE International Conference on Health, Safety, and the Environment in Oil and Gas Exploration and Production, paper SPE, 61106, available at: www.spe.org Checkland, P. (2000), Systems Thinking, Systems Perspective, John Wiley & Sons, Chichester. Dwight, R. (1999), “Frameworks for measuring the performance of the maintenance system in a capital intensive organisation”, PhD thesis, Department of Mechanical Engineering, University of Wollongong, Wollongong. Edvinson, L. and Malone, M.S. (1997), Intellectual Capital: The Proven Way to Establish your Company’s Real Value by Measuring Its Hidden Brain Power, Harper Collins, Philadelphia, PA. Elkington, J. (1997), Cannibals with Forks: The Triple Bottom-line of 21st Century Business, Capstone, Mankato, MN. Ellingsen, H.P. et al. (2002), “Management of assets, resources and maintenance by using a balanced scorecard based performance framework”, Proceedings of the 16th International Maintenance Conference: Euromaintenance-2002, pp. 203-11. Faure, L.M. and Faure, M.M. (1992), Implementing Total Quality Management, Pitman Publishing, London.
Garvin, D.A. (1995), “Leveraging processes for strategic advantage: a roundtable with Xerox’s Allaire, USAA’s Herres, Smithkline Beecham’s Leschly, and Pepsi’s Weatherup”, Harvard Business Review, September-October, pp. 76-92. Hargis, P.D. (2000), “Balancing sustainable offshore production with onshore social and environmental issues in Central California”, paper presented at the SPE International Conference on Health, Safety, and the Environment in Oil and Gas Exploration and Production, paper SPE, 61109, available at: www.spe.org Herbst, P.G. (1974), Socio-technical Design: Strategies in Multidisciplinary Research, Tavistock Publications, London. Jambekar, A.B. (2000), “A systems thinking perspective of maintenance, operations, and process quality”, Journal of Quality in Maintenance Engineering, Vol. 6 No. 2, pp. 123-30. Kaplan, R.S. and Norton, D.P. (1992), “The balanced scorecard: measures that drive performance”, Harvard Business Review, January-February, pp. 71-9. Kaplan, R.S. and Norton, D.P. (1996), Translating Strategy into Action: Balanced Scorecard, Harvard Business School Press, Boston, MA. Knight, J.A. (1998), Value Based Management: Developing a Systematic Approach to Creating Shareholder Value, McGraw-Hill, New York, NY. Kumar, U. and Ellingsen, H.P. (2000), “Development and implementation of maintenance performance indicators for the Norwegian oil and gas industry”, Proceedings of the Euromaintenance-2000 Conference, pp. 221-6. Liyanage, J.P. and Kumar, U. (2000a), “Utility of maintenance performance indicators in consolidating technical and operational health beyond the regulatory compliance”, in Doerr, W.W. (Ed.), Safety Engineering and Risk Analysis: The International Mechanical Engineering Congress and Exposition-2000, pp. 153-60. Liyanage, J.P. and Kumar, U. (2000b), “Measuring maintenance process performance using the balanced scorecard”, Proceedings of the 15th International Maintenance Conference: Euromaintenance-2000, pp. 25-32. Liyanage, J.P. and Kumar, U. (2001), “Value based maintenance performance diagnostics: an architecture to measure maintenance performance in petroleum assets”, Proceedings of the International Conference of Maintenance Societies – 2001, paper 050. Liyanage, J.P. and Kumar, U. (2002a), “Value based maintenance performance management for the petroleum industry”, Proceedings of the 4th International Conference on Quality, Reliability, Maintenance (QRM-2002), pp. 113-6. Liyanage, J.P. and Kumar, U. (2002b), “Value based management of maintenance performance: the best practice for the 21st century maintenance based on experiences and learning from oil and gas industry”, Proceedings of the 16th International Maintenance Conference: Euromaintenance 2002, pp. 29-36. Liyanage, J.P. et al. (2001b), “Risk and value: a basis for balancing maintenance performance in offshore engineering constructions”, Proceedings of the 11th International Offshore & Polar Engineering Conference 2001, Vol. IV, pp. 529-36. Ljungberg, A. (1998), “Measurement systems and process orientation”, PhD thesis, Department of Engineering Logistics, Lund University, Lund. Neely, A. and Adams, C. (2001), “Perspectives on performance: the performance prism”, Focus Magazine, available at: www.focusmag.com Perry, D. and Starr, A.G. (2001), “Introducing value based maintenance”, in Starr, A.G. and Rao, R.B.K.N. (Eds), Condition Monitoring and Diagnostic Engineering Management, Elsevier Science, Amsterdam.
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Pheng, L.S. and Wee, D. (2001), “Improving maintenance and reducing building defects through ISO 9000”, Journal of Quality in Maintenance Engineering, Vol. 7 No. 1, pp. 6-24. Porter, M. (1985), Competitive Advantage: Creating and Sustaining Superior Performance, The Free Press, New York, NY. Sveiby, K.E. (1997), “The intangible asset monitor”, Journal of Human Resource Costing and Accounting, Vol. 2 No. 1, pp. 73-97. Tsang, A.H.C. (1999), “Maintenance performance management in capital intensive organisations”, PhD thesis, Department of Manufacturing Engineering, The Hong Kong Polytechnic University, Hong, Kong. Tsang, A.H.C. and Brown, W.L. (1998), “Managing the maintenance performance of an electric utility through use of balanced scorecard”, Proceedings of the 3rd International Conference on Maintenance Societies, paper 022. Wolff, R. and Zaring, O. et al. (2000), “Indicators for sustainable development”, paper presented at the SPE International Conference on Health, Safety, and the Environment in Oil and Gas Exploration and Production, paper SPE, 61320, available at: www.spe.org
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Adaptive model for vibration monitoring of rotating machinery subject to random deterioration
Model for vibration monitoring 351
Y. Zhan, V. Makis and A.K.S. Jardine Department of Mechanical and Industrial Engineering, University of Toronto, Ontario, Canada Keywords Vibration measurement, Autoregressive processes Abstract Due to the non-stationarity of vibration signals resulting from either varying operating conditions or natural deterioration of machinery, both the frequency components and their magnitudes vary with time. However, little research has been done on the parameter estimation of time-varying multivariate time series models based on adaptive filtering theory for condition-based maintenance purposes. This paper proposes a state-space model of non-stationary multivariate vibration signals for the online estimation of the state of rotating machinery using a modified extended Kalman filtering algorithm and spectral analysis in the time-frequency domain. Adaptability and spectral resolution capability of the model have been tested by using simulated vibration signal with abrupt changes and time-varying spectral content. The implementation of this model to detect machinery deterioration under varying operating conditions for condition-based maintenance purposes has been conducted by using real gearbox vibration monitoring signals. Experimental results demonstrate that the proposed model is able to quickly detect the actual state of the rotating machinery even under highly non-stationary conditions with abrupt changes and yield accurate spectral information for an early warning of incipient fault in rotating machinery diagnosis. This is achieved through combination with a change detection statistic in bi-spectral domain.
Practical implications This paper presents an online diagnostic technique for evaluating the state of gearbox systems under varying operating conditions. The proposed technique will be useful for practitioners working in the area of vibration monitoring to make more accurate state analysis in comparison with conventional techniques since it, above all, takes advantage of spectral information from time-frequency representations yielded by high-resolution parametric modeling with the aid of advanced adaptive filtering algorithm and then provides a robust approach which is exempt from the influence of varying operating conditions. The authors are most grateful to the Applied Research Laboratory at Penn State University and the Department of the Navy, Office of the Chief of Naval Research (ONR) for providing the data used to develop this work. They also thank Bob Luby at PricewaterhouseCoopers and Murray Wiseman in the CBM Lab at the University of Toronto for their support. This work has been supported by the Natural Science and Engineering Research Council of Canada. The authors wish to thank NSERC for their financial support.
Journal of Quality in Maintenance Engineering Vol. 9 No. 4, 2003 pp. 351-375 q MCB UP Limited 1355-2511 DOI 10.1108/13552510310503222
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1. Introduction The objective of any manufacturing process is the efficient production of a part with specific shape, with acceptable dimensional accuracy and surface quality. Deviation of the machine conditions from a prescribed plan may influence the final part quality and must be examined in detail by the experienced operator. Global competition and the current economic conditions have forced many manufacturing organizations to improve product quality and cut production costs at the same time. The requirements for increased plant productivity, safety, and reduced maintenance costs, have led to a growth in popularity of methods for condition monitoring to aid the planning of plant preventive maintenance and operational policies (Christer et al., 1997). Increased use of automation, although reduces the burden on machine operators and the risk of human error, renders the production process more vulnerable to various kinds of faults. The unscheduled breakdown may trigger substantial economic loss due to the high cost of restoring equipment to an operable condition under a crisis situation, the secondary damage and safety/health hazards inflicted by the failure and the penalty associated with lost production (Tsang, 1995). Therefore, an effective condition-based maintenance system should be capable of monitoring the operating conditions of machinery, issuing advanced warnings of possible faults, predicting the life span of a defective machine component prior to a fatal breakdown, and thus reducing unscheduled production shutdowns. However, in the applications of condition monitoring and fault diagnosis techniques to many mechanical systems, the component of interest is often inaccessible and cannot be observed or measured directly. Therefore, to determine the condition of inaccessible components of an operating machine, the only possible course of action is to measure at a remote station some related signal, say vibration signals, which carry a great deal of information describing the condition of the component. Hence, vibration monitoring presents a unique and appealing means to conduct condition monitoring and offers significant rewards due to economic benefits that accrue from its effectiveness. It has been investigated extensively in a wide variety of engineering maintenance literature (Koo and Kim, 2000; McFadden and Toozhy, 2000; Jardine et al., 1999). The purpose of vibration signal processing is to perform transformations on signals to make some aspects of them easier to detect and quantify to assist in diagnosis. The fast Fourier spectral analysis based on the assumption of stationary property of vibration signals conceals the time-domain information, which, however, is especially relevant to the time-varying vibration signals of rotating machinery. Machine vibration signals often demonstrate a highly non-stationary and transient nature and carry small yet informative components embedded in larger repetitive signals due to external varying operating conditions and internal natural deterioration characteristics of machinery. The time-frequency representation, which describes how the spectral content of a signal changes over time, has received considerable
attention for analysing time-varying vibration signals. Recently, the techniques of time series modelling (AR, MA and ARMA, etc.), known as high resolution parametric spectrum analysis methods, have been applied to vibration signals analysis of rotating machinery by using time-invariant coefficients (Dron et al., 1998; Baillie and Mathew, 1996; Mechefske and Mathew, 1992). Taking into account the reality that a multiple sensor-based machine vibration monitoring system, which leads to the multivariate feature of vibration signals, is usually desired for reliability purposes, a multivariate model is more realistic and demanded. The vector autoregressive model (VAR) is usually preferred since it is the best compromise between temporal representation and speed, efficiency and simplicity of algorithms enabling the estimation of model parameters. In practice, the spectrum of ARMA process could even be represented purely in terms of the AR coefficients without resort to compute the MA coefficients. In view of the time-varying frequency components and magnitudes of non-stationary multivariate vibration signals, it is therefore natural to assume the coefficient matrices of the VAR model to be time-varying. Up to now, only little attention has been focused on time-varying VAR models where the evolution law of time-varying coefficients is assumed to be stochastic (Arnold et al., 1998), whereas the parameter estimation of time-varying multivariate time series models based on adaptive filtering theory for timely making maintenance decisions is rarely investigated. A few articles presented relevant work conducted in this issue, but confined to conventional filtering theory or scalar cases (Christer et al., 1997; Arnold et al., 1998; etc.). In the last decades, it has seen a surge in the development of advanced adaptive filtering algorithms (Chui et al., 1990; Kung and Hwang, 1991; Ahmed and Radaideh, 1994; Wall and Gaston, 1997; Noriega and Pasupathy, 1997; etc.). Our previous study addressed in detail the applications of a multivariate noise-adaptive Kalman filter to condition monitoring (Zhan et al., 2002a, b). However, little research has been conducted on the implementation of advanced adaptive filtering algorithms to condition monitoring. In particular, when further assumptions that result in unknown system parameters of state space models are made, an adaptive filtering scheme that is able to yield simultaneous estimation of both state vector and system parameters must be employed. For this regard, this paper is concerned with a state space representation of time-varying VAR modelling of non-stationary multivariate vibration signals where the system parameters adaptively estimated from vibration data with the aid of a modified extended Kalman filter (MEKF) proposed by Chui et al., (1990) since it provides the most suitable algorithmic structure to yield estimates of state vector and system parameters simultaneously. Consequently, the adaptive estimation of power spectra in time-frequency domain can be conveniently obtained. The model is evaluated by applying to a simulated trivariate vibration signal with abrupt changes and implemented to real gearbox vibration signals for detecting deterioration purposes by means of a
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hybrid system combining the proposed MEKF-based time-varying VAR model and a statistical fault detection approach in bispectral domain. The remainder of this paper is organized as follows. Section 2 presents the model formulation with all related algorithms, where section 2.1 illustrates the state space model and modified extended Kalman filtering recursions, section 2.2 is devoted to the introduction to an innovation-based model check for the proposed model, and the adaptive spectral analysis in time-frequency domain is addressed in section 2.3. In section 3, the proposed model is validated in two aspects: fast adaptation capability and high time-frequency resolution by using a simulated signal. A condition-based maintenance study of the gearbox by using full lifetime vibration data is presented in section 4. Some concluding remarks are finally given in section 5. 2. Description of model In this section we present a state space model transferred from the VAR model with time-dependent coefficients and provide its corresponding recursion algorithms with the aid of a Kalman filter. 2.1 State space model and Kalman filter A VAR process is a discrete-time multivariate linear stochastic process given by: yi ¼
p X
Ak yik þ 1i
ð1Þ
k¼1
for i ¼ 1; 2; . . .; N , that is, the time series can be considered as the output of a linear all-poles filter driven by a white-noise signal with a flat spectrum, where N is the sample size, p the order of VAR model, yi the ith measurement vector of dimension d £ 1, Ak the kth d £ d coefficient matrix of the measurement yi-k, and ei an d £ 1 sequence of zero-mean white Gaussian measurement noise. Since the non-stationary property of vibration signatures that takes place frequently due to the maintenance actions imposed on and/or the natural deterioration of machinery and that in turn results in the time varying spectral properties of vibration signatures, taking this into consideration we assume the coefficient matrices of the above VAR model to be time-varying: yi ¼
p X
Ak ðiÞyik þ 1i :
ð2Þ
k¼1
To make use of the Kalman filtering algorithm, it is necessary to develop a state space representation of the model (2). This can be achieved by rearranging the elements of the matrices of coefficients in vector form using the vec-operator, which stacks the columns of a matrix on top of each other from the left to right side. Then, with the following notation:
ai ¼ vecð½A1 ðiÞ; A2 ðiÞ. . .; Ap ðiÞT Þ
ð3Þ
Y i ¼ ðyTi ; yTi1 ; . . .; yTipþ1 Þ
ð4Þ
C i ¼ I d ^Y Ti
ð5Þ
an appropriate state space representation of the VAR model with stochastic coefficients can be given by aiþ1 ¼ f i ðai Þ þ ni
ð6Þ
yi ¼ C Ti1 ai þ 1i
ð7Þ
where ai is the pd 2 £ 1 state vector, ni is an pd 2 £ 1 sequence of zero-mean white Gaussian state noise, uncorrelated with a1 and 1i, 1i is the same as in (1) and uncorrelated with a1 and ni, f(†) in the state equation (6) can be of nonlinear forms of the state elements, which can then be processed by the extended Kalman filter (EKF), or of some specific form for convenient calculation, e.g. Miai, by which EKF is reduced to the linear Kalman filter, and the measurement equation (7) has an adaptive time-varying coefficient C Ti1 of dimension d£pd 2. We also have a^ 0 ð¼ Eða0 ÞÞ, the Gaussian pd 2 £ 1 initial state vector with covariance matrix P 0j0 ð¼ Covða0 ÞÞ, and the noise covariance matrices: E{nk nTi } ¼ Qk dki
ð8Þ
E{1k 1Ti } ¼ Rk dki
ð9Þ
where T denotes transposition, and d denotes the Kronecker delta sequence. Suppose that a linear system with state space description below instead of (6) and (7): aiþ1 ¼ M i ai þ ni
ð10Þ
yi ¼ C Ti1 ai þ 1i
ð11Þ
is being considered, where, assuming n ¼ pd 2 for simplicity, M i ¼ diag½m1 ; · · ·; mn and, as before, ai 2Rn , ni 2Rn , 1i 2Rd , and ni and 1i are uncorrelated Gaussian white noise sequences. Let us assume a vector u to represent the unknown constant elements mi for i ¼ 1; . . .; n; namely u ¼ ðm1 ; . . .; mn ÞT . The objective is to identify u, which must be treated as a random vector such as:
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uiþ1 ¼ ui þ zi ;
ð12Þ
where zi is any zero-mean Gaussian white noise sequence uncorrelated with ei and with pre-assigned positive definite covariances Covðzi Þ ¼ Wi . In applications, we may choose W i ¼ W for all i. The MEKF introduces a very efficient parallel computational scheme for system parameters identification (Chui et al., 1990). The modification is achieved by an improved linearization procedure, which results in that the MEKF algorithm can be applied to real-time system parameter identification even for time-varying stochastic systems. The MEKF algorithm consists of two sub-systems. Algorithm I, which deals with model (13) and (14) below, is a modification of the extended Kalman filter, where the real-time linear Taylor approximation is not taken at the previous estimate. Instead, in order to improve the performance, it is taken at the optimal estimate of state vector ai given by a standard Kalman filtering algorithm called Algorithm II, which deals with model (15) and (16) below. Therefore, the system (10) and (11) together with the assumption (12) can be reformulated as the nonlinear stochastic system: " # " # " # aiþ1 ni M i ðui Þai ¼ þ ð13Þ uiþ1 ui zi T
yi ¼ ½ C i1 "
ai
ui
0
ð14Þ
# þ 1i ;
to which the Algorithm I can be applied, and subsystem (15) and (16): aiþ1 ¼ M i ðu~ i Þai þ ni
ð15Þ
yi ¼ C Ti1 ai þ 1i ;
ð16Þ
to which the Algorithm II can be applied. The two algorithms are applied in parallel starting with the same initial estimate, where Algorithm I is used for yielding the estimate ½ a~ i u^ i T with input a^ i1 obtained from Algorithm II, which is used for yielding the estimate a^ i with the input ½ a~ i1 u^ i1 T obtained from Algorithm I. The two-algorithm procedure listed below is called the parallel algorithm.
Algorithm I. Set: "
a~ 0 u~ 0
#
" ¼
Eða0 Þ
"
#
Eðu0 Þ
and P 0 ¼ Cov
a0
#! ð17Þ
u0
For i ¼ 1; . . .; N, compute the recursive prediction equations: 3 2 2 P iji1
357 3T
6 6 2 37 2 37 6 6 M i1 ðu~ i1 Þa^ i1 7 M i1 ðu~ i1 Þa^ i1 7 7 7 6 6 › › 4 57P i1 6 2 57 34 ¼6 7 7 6 2 ai1 3 6 u~ i1 u~ i1 7 7 6 6 ai1 5 5 4›4 4›4 5 5 ui1 ui1 þ Qi1 ð18Þ "
a~ iji1 u~ iji1
#
" ¼
M i1 ðu~ i1 Þa^ i1 u~ i1
and the updating equations: h T iT h T Gi ¼ P iji1 C i1 0 ½ C i1
h T P iji ¼ I Gi ½ C i1 "
ð19Þ
0 T þ R^ i
i 0 P iji1
i1
ð20Þ ð21Þ
# a~ iji1 ¼ ~ þ Gi ðyi C Ti1 a~ iji1 Þ; ð22Þ uiji1 " #! ni ; R^ i ¼ Covð1i Þ; and a^ i1 is obtained by the where Qi ¼ Q1 ¼ Cov zi a~ i u~ i
#
#
0 P iji1 ½ C Ti1
"
following Algorithm II. Algorithm II. Set: a^ 0 ¼ Eða0 Þ and P 0 ¼ Covða0 Þ For i ¼ 1; . . .; N, compute the recursive prediction equations: T P iji1 ¼ M i1 ðu~ i1 Þ P i1ji1 M i1 ðu~ i1 Þ þQi1
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ð23Þ
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a^ iji1 ¼ M i1 ðu~ i1 Þa^ i1
ð24Þ
and the updating equations: h i1 Gi ¼ P iji1 C i1 C Ti1 P iji1 C i1 þ R^ i
ð25Þ
h i P iji ¼ I Gi C Ti1 P iji1
ð26Þ
a^ i ¼ a^ iji1 þ Gi yi C Ti1 a^ iji1 ;
ð27Þ
358
where Qi ¼ Q2 ¼ Covðvi Þ; R^ i ¼ Cov(1i), and u~ i1 is obtained from Algorithm I. However, in order to apply the above MEKF process, we still need an initial estimate u^ 0 :¼ u^ 0j0 , which in fact can be chosen arbitrarily (Chui and Chen, 1999). Evidently, the parallelism we have considered here is fundamentally motivated by the need for an evaluation of the Jacobian matrix of the (nonlinear) function M i1 ðui1 Þai1 and the prediction term h ivector-valued T a~ iji1 u~ iji1 at the optimal position a^ i1 at each time instant. The reader of interest is referred to Chui and Chen (1999) for the discussion of convergence of this parallel filtering scheme. A detailed study of array-processor designs for Kalman filter can be found (Kung and Hwang, 1991), which proposed an efficient systolic implementation for Kalman filter. Since the measurement series {yi ; i ¼ 1; 2; . . .; N } are usually not independent, the likelihood can be decomposed into the product of the conditional distributions of each yi on all its predecessors, if the function f(†) takes some linear form, e.g. Miai, that is: L¼
N Y
pðyi j y1 ; y2 ; . . .; yi1
ð28Þ
i¼1
and the joint distribution of {yi ; i ¼ 1; 2; . . .; N } is multivariate normal since it can be shown that each observation yi is a linear function of normal random noise items. Based on the multivariate normal distribution it follows that the log-likelihood function for {yi ; i ¼ 1; 2; . . .; N } is given by: log L ¼
1X N N 1 N 1X logS^ i zT S^ zi : logð2pÞ 2 2 i¼1 2 i¼1 i i
ð29Þ
The maximum likelihood method can be used to estimate the values of parameters. However, it cannot be used to compare different models without some corrections. Therefore, the Akaike Information Criterion (AIC) is applied to determine the appropriate order value p off-line for VAR models by
minimizing the information theoretical function of p, AIC( p), which is defined as: AICðpÞ ¼
N X lnR^ i þ 2pd 2 :
ð30Þ
i¼1
For nonlinear forms of f(†) the log-likelihood estimation (21) cannot be applied since the observation yi is no longer a linear function of normal random noises. Therefore, we will have to compare the global performance of models with different order value p based on trial and error in order to determine the optimal one. 2.2 Test for optimality The model having been identified and the parameters estimated, diagnostic checks are then applied to the fitted model. The test to determine whether the innovations series zi is a white sequence, thus indicating optimum filter behavior, is based on an estimate V^ k of the autocorrelation sequence Vk (Noriega and Pasupathy, 1997). Data is processed in batches of N samples. For a given batch, Ns samples of V^ k given by: N 1 1X V^ k ¼ zi zT N i¼k ik
ð31Þ
for k¼0, 1, . . ., Ns2 1 are calculated (Ns , N). The above is an asymptotically unbiased estimate with mean and (approximate) covariance given by: E{V^ k } ¼ ð1
k ÞV k N
1 1 X Covð½V^ k i;j ; ½V^ l m;n Þ ø ð½V t i;m ½V tþlk j;n þ ½V tþl i;n ½V tk j;m Þ; N t¼1
ð32Þ
ð33Þ
where Cov(a, b) ¼ E{[a 2 E{a}] · [b 2 E{b}]}, and [·]i,j denotes the element in row i and column j of the matrix. The estimate can also be shown to be consistent because the summation in (33) is finite and asymptotically normal. It is the Gaussian property of V^ k that we use to test for whiteness of the innovations sequence zi. From the 95 per cent confidence limit test for a random variable X with Gaussian distribution: P{ X 0 # X # X 0 } ¼ 0:95; for X 0 ø 1:96sx :
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ð34Þ
This can be applied to, for example, elements in the main diagonal of V^ k . For zi a white sequence, from (33) it follows that:
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1 Covð½V^ k i; j ; ½V^ l m;n Þ ¼ ½V 0 i;m ½V 0 j;n ; for k ¼ l . 0: N
ð35Þ
The variance of a diagonal element ½V^ k i;i is then given by
360
varð½V^ k i;i Þ ¼
1 ^ 2 ½V0 i;i ; k . 0 N
ð36Þ
and substituting (36) into (34) results in the limit(s) for the test: 1:96 h i X 0 ¼ pffiffiffiffi V^ 0 : i;i N
ð37Þ
The actual test is performed by determining the percentage of values of ½V^ k i;i for k¼1, 2, . . ., Ns2 1, which fall outside of the range X0. If this is less than 5 per cent, then zi is considered white. The test can be done on several of the main diagonal elements of V^ k and simulations have shown good results using the two extreme elements (Noriega and Pasupathy, 1997). However, the whiteness of innovations sequence is a sufficient condition only under the assumption that transition matrix Mi in (10) is known. When Mi is unknown, an additional condition for filter optimality; namely, that the innovations have zero mean, i.e.: E{zi } ¼ 0
ð38Þ
for i ¼ 0; 1; . . .; N must be imposed on the model so as to suffice for optimality testing (Noriega and Pasupathy, 1997). 2.3 Parametric spectral analysis in time-frequency domain It can be shown that the parametric spectrum of the signal depends on the estimated parameters of time series models. In fact, the relationship is given by: Pðf Þ ¼
P N ðf Þ jHðf Þj2
;
ð39Þ
that is, the signal power density spectrum (PDS) depends on what can be expressed as the product of PN( f), PDS of the white noise (PN( f)¼PNO), and H( f), frequency response of the linear filter. After estimating the coefficient matrices of the VAR model, an instantaneous estimating of the spectral density function, which in the multivariate case is a matrix valued function of frequency, can be given in terms of the VAR coefficient matrices: 1 * ^ P i ðf Þ ¼ ½H 1 i ðf ÞRi ½H i ðf Þ ;
where the asterisk mark denotes the conjugate complex and:
ð40Þ
H i ðf Þ ¼ I d
p X
^ k ðiÞe j2pfT s k : A
ð41Þ
k¼1
Autoregressive models sare less dependent on the time window and have often been used in the estimation of stationary or weakly non-stationary signals. In order to use the VAR model for time-frequency analysis, the coefficient matrices of the model have, therefore, to be adapted to the time-varying characteristics of the signal. The PDS function (41) is adaptive because each ^ k is considered to be subject to a stochastic process coefficient matrix A expressed by (6) in order to fit the time-varying spectral characteristics of the vibration signals. In this way, the model can, in principle, follow rapidly varying spectra because it has an inherently non-stationary structure. Accordingly, the PDS function, expressing the spectrum by using the time-varying VAR parameters, becomes a function of two variables, time i and frequency f in the same way as for all time-frequency distributions (Conforto and D’Alessio, 1999). 3. Model evaluation by using simulated vibration data This section investigates the performance of the proposed model and demonstrates the fast adaptation and high spectral resolution capabilities by filtering one highly non-stationary trivariate vibration signal with abrupt changes and time-varying spectral contents. We assume that there is presence of abrupt changes in the state of a motor outboard bearing and therefore a synthetic trivariate bearing vibration signal is made up of three 341-point signal segments. The motor rotor of these three segments has a 3,600rpm (60Hz) rotational speed. The sampling frequency and observed frequency range are 12.821kHz and [0, 5000] Hz, respectively. In order to show the presence of abrupt changes, the artificially connected trivariate signal is exhibited in Figure 1, which clearly shows two abrupt changes at sampling points 342 and 683 in each of axial, horizontal and vertical variate signals, respectively. Our further investigation by means of non-parametric time-frequency techniques, i.e. short-time Fourier transform, reveals that these three signal segments contain rather different dominant frequency components and energy distribution, respectively, although they were selected from the same bearing. Therefore, the simulated signal sets very harsh conditions for evaluating the performance of the proposed model. Figure 2 displays the FFT spectra of the original 1,024-point trivariate vibration signals from which the third segment [683, 1023] shown in Figure 1 was taken. Extensive tests were conducted in order to select the most appropriate order value based on the AIC and the optimality criterion. Order p ¼ 21 is finally determined. Figure 3 demonstrates that the outlier percentages are less than 5 per cent for the first and second variates (the outlier percentage of the third variate just slightly
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Figure 1. Simulated trivariate vibration data
Figure 2. FFT spectra of the original 1,024-point signal from which the third segment [683,1,023] is taken
exceeds 5 per cent limit). Further inspection reveals that in each subplot of Figure 3; namely, the outliers trace by using each diagonal element of V^ k , most outliers are present only at the initial period of filtering. With the progress of filtering, the presence of outliers exceeding the upper and lower 5 per cent limits in each subplot of Figure 3 is very quickly ameliorated, although very few outliers are present around the sample points of abrupt changes; for instance, sample point 683 in the horizontal subplot of Figure 3. Evidently, all three variates present fairly stable behavior within the third signal segment [683, 1023] as shown in each subplot of Figure 3. The findings from the zero mean check of innovations sequence as shown in Figure 4 show consistent results
Model for vibration monitoring 363
Figure 3. Optimality test for whitenes assumption of innovations sequence
with the findings from Figure 3. Similarly, the most unstable fluctuation of the mean of innovations is also present at the initial filtering stage as shown in each subplot of Figure 4, where the mean trace of innovations sequence of each variate shows a very efficient and rapid tendency to zero with the progress of filtering. The only notable jump taking place at sample point 342 in the axial subplot of Figure 4 actually does not imply an inferior behavior in comparison with the horizontal and vertical subplots of Figure 4, since, by examining its leftmost scale values, it has the least variation range [20.02, 0.03]. Thus, the optimality criterion of zero mean innovations sequence is effectively ensured for each of the axial, horizontal and vertical variates, respectively. In conclusion, the optimum behavior of filter is guaranteed as defined in section 2.2. In Figure 5, the adaptive estimation procedures of ten randomly selected variates of the state vector ai are plotted. Abrupt changes and corresponding rapid adaptation of the state estimate can obviously be observed around the sampling points 342 and 683, respectively. Estimation errors may exist in the filtering process within the first segment [1, 341], e.g. Figure 5(j) or the second segment [342, 682], e.g. Figure 5(b). Examinations on other variates of the state vector ai were also conducted and show that most variates of ai converge to their steady state immediately after the first or second segments. Most importantly, the time-averaged parametric autospectra of the third signal segment [683, 1023] as shown in Figure 6 computed by using the proposed MEKF-based time-varying VAR model are strongly consistent with the spectra
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Figure 4. Optimality test for the zero mean of innovations sequence
calculated via FFT as shown in Figure 2, by using the original 1,024-point vibration data. The correct spectral information proves that the proposed model is able to conduct accurate condition analysis of machinery even under highly non-stationary conditions. Furthermore, in practice, state variations of machine components, especially defects of machine components which are critical to the CBM, usually have a relatively slow onset and would not be present and gone in such a sudden manner. As such, the simulated vibration signal in this section sets much harsher conditions for evaluating the performance of the proposed model. However, the artificially introduced non-stationary conditions are, to a great extent, similar to the gear fault-induced non-stationary effects since the damaged teeth of a faulty gear will also introduce abrupt changes into the spectral contents of the vibration signals when they get involved in meshing motion with another gear over each revolution. Therefore, this simulation test implies a highly desirable applicability of the proposed model to deal with gear vibration signals. 4. Application to gearbox vibration monitoring 4.1 The object of interest In order to investigate the performance of the proposed model on real vibration monitoring signals, a mechanical diagnostics test-bed (MDTB, see Figure 7) was utilized in this study to provide data on a commercial transmission as its health progresses from new to faulted and, finally, to failure. The MDTB is functionally a motor-drive-train-generator test stand (Byington and Kozlowski,
Model for vibration monitoring 365
Figure 5. Randomly selected dimensions of the state vector ai estimated from the simulated data
1997). The gearbox is driven at a set input speed using a 30Hp, 1750rpm AC drive motor, and the torque is applied by a 75Hp, 1,750rpm AC absorption motor. The maximum speed and torque are 3,500rpm and 225ft-lbs, respectively. The speed variation can be accomplished by varying the frequency to the motor with a digital vector drive unit. However, in this test run, the shaft speed is kept constant at 1,750rpm. The variation of the torque is accomplished by a similar vector unit capable of controlling the current output of the absorption motor. The system speed and torque set points are produced by analog input signals (0-10VDC) supplied by the data acquisition (DAQ) computer and a D/A board. The MDTB is highly efficient because the electrical
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Figure 6. Parametric spectra via the proposed MEKF-based model
Figure 7. Mechanical diagnostic test bed
power that is generated by the absorber is fed back to the driver motor. The mechanical and electrical losses are sustained by a small fraction of wall power. The MDTB has the capability of testing single and double reduction industrial gearboxes with ratios from about 1.2:1 to 6:1. The gearboxes are nominally in the 5-20Hp range. The system is sized to provide the maximum versatility to speed and torque settings. The motors provide about two to five times the rated torque of the selected gearboxes, and thus the system can provide good overload capability. The use of different reduction ratios and gearboxes than listed is possible if appropriate consideration to system operation is given. The motors and gearbox are hard-mounted and aligned on a bedplate. The bedplate is mounted using isolation feet to prevent vibration transmission to the floor.
The shafts are connected with both flexible and rigid couplings. Torque-limiting clutches are used on both sides of the gearbox to prevent the transmission of excessive torque as could occur with gear jam or bearing seizure. In addition, torque cells are used on both sides of the gearbox to directly monitor the efficiency and the loads transmitted (Byington and Kozlowski, 1997). The general gearbox information is shown in Table I. This test run was conducted with a single reduction helical 1:1.5 ratio gearbox which was run at 100 per cent output torque and Hp for 96 hours then increased to 300 per cent torque and Hp until failure. Data were collected in ten-second windows at set times and triggered by accelerometer RMS thresholds. Table II presents the brief description of the two operating conditions. The following data are contained in this test run: single axis accelerometer sensor (A02-A07), triaxial accelerometer (A10: axial; A11: jj floor; A12: perp floor), external microphone sensor (M01), where the triaxial accelerometer (A10: axial; A11: jj floor; A12: perp floor) is selected to construct a trivariate time series for filtering. Figure 8 shows the location of the triaxial accelerometer. There is a total of 83 trivariate data sets for the triaxial accelerometer, of which 12 were collected under condition No. 1 and 71 under condition No. 2. The data sets were sampled synchronously, where each data set contains 200,000 sample points for ten seconds in all. The triaxial accelerometer is included to determine whether triaxial data can provide significantly better sensor fusion for gearbox health assessment than the single-axis accelerometers. However, the measurement trade-off is that the triaxial accelerometer possesses a lower frequency bandwidth (8kHz) than single-axis accelerometers (20kHz). Gearbox ID# Make Model Rated input speed (rpm) Maximum rated output torque (in-lbs) Maximum rated input (Hp) Gear ratio Contact ratio Gear mesh frequency of drive gear (Hz) Gear mesh frequency of pinion gear (Hz)
Condition No. 1 No. 2
DS3S015005 Dodge APG R86001 1,750 528 10.0 1.533 2.388 875.53 874.99
Input speed (rpm)
Output torque (in-lbs)
Power (Hp)
Duration (hours)
1,750 1,750
540 1,620
9.8 30
96.0 31.4
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Table I. General gearbox information
Table II. Two operating conditions
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Figure 8. Location of triaxial accelerometer (A10, A11 and A12)
4.2 Detection of gearbox deterioration In this section, the proposed MEKF-based model is combined with a bispectrum-based robust fault detection statistic proposed by Parker et al. (2000) for investigating the deterioration of the gearbox. The objective is to verify whether the proposed model is able to provide accurate spectral information in time-frequency domain to machinery fault diagnose via higher-order spectral analysis. The most commonly used higher-order spectra is the complex-valued bispectrum associated with the third-order cumulant and defined as: Bðf 1 ; f 2 Þ ¼ E½Xðf 1 ÞXðf 2 ÞX ðf 1 þ f 2 Þ:
ð42Þ
where asterisk denotes complex conjugation and X( f) is the Fourier transform of X(n). The bispectrum can be viewed as a decomposition of the third moment (skewness) of a signal over frequency. It must be noted that in this study X( f) is replaced with the time-varying power spectra generated by the proposed MEKF-based time-varying VAR model. The expectation operator E signifies an average over sufficient ensembles. To address the detection statistic, the magnitude-squared bicoherence function obtained by normalization of bispectrum:
bðf 1 ; f 2 Þ ¼
1Bðf 1 ; f 2 Þ1 2
2
E½jXðf 1 ÞXðf 2 Þj E½jXðf 1 þ f 2 Þj
ð43Þ
must be quoted. It has been shown in equation (16) that the bicoherence function, which is restricted to the range jBðf 1; f 2Þj, is less sensitive to changes in vibration amplitude across varying operating regimes (e.g. torque levels). This is a very important property of bicoherence since it furnishes a robust locally optimum detection statistic Tlo expressed by:
Model for vibration monitoring 369
T lo ¼ max
k X
1#l#k m¼l
ðbm b0 Þ
ð44Þ
which is sensitive to faulty conditions but insensitive to the changes of operating regimes, where b0 denotes the pre-change values of b( f1, f2) reflecting the behavior of the machine under normal operating conditions and can be interpreted as a known quantity that can be readily estimated (Parker et al., 2000). Therefore, the two techniques specifically effective for processing a non-stationary vibration signal, MEKF-based time-varying VAR model in time-frequency domain and fault detection statistic in bispectral domain, are integrated in this section for detecting machine deterioration. The principle of gearbox fault diagnose on which the detection statistic Tlo is based is that the large deviation from baseline indicates a fault (Parker et al., 2000). There is a total of 83 Tlo’s generated from 83 data sets, corresponding to different life stages from new to breakdown, where the first 12 data sets under operating condition No. 1 are used to compute b0. To reduce computational requirements, an equally-spaced 3,000-point sample block in each data set is selected for processing and only the low-frequency vibrations (e.g. gear meshing fundamental and associated lower sidebands) are used to produce the bicoherence estimates, where f2 is held fixed at f gearmesh ¼ 875Hz and f1 is swept from 20Hz to fgearmesh. Thus, the maximum frequency to be considered is 2 £ f gearmesh which is equal to 1,750Hz. In order to ensure the applicability and effectiveness of the proposed hybrid diagnostic system, a number of assumptions are required: (1) the maximum frequency of interest is lower than the half bandwidth of accelerometers whose signals are to be analyzed according to Nyquist theory; (2) the geometric imperfections or assembly errors of gears in meshing motion have much less effect on the non-stationarity of vibration signals, comparing to fault-induced effects; (3) the driven gear of interest is constantly in its healthy state under condition No. 1; and (4) the considered frequency range for computing time-frequency representations contains sufficient spectral information for evaluating the deterioration of the gear of interest.
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As mentioned in section 4.1, the frequency bandwidth of the triaxial accelerometer is 8kHz. According to the Nyquist theory, the effective frequency bandwidth is 4kHz for eliminating aliasing, which is large enough for the following analysis, since it is larger than 1,750Hz as required by the above assumption (1). Furthermore, according to the notations in the original data CD of test-run TR No. 5, the tested gearbox did not show any abnormal symptom during its initial lifetime. As such, it is believed that the inevitable geometric imperfections or assembly errors of meshing gears do not have notable negative effects on the sampled vibration signals. This is consistent with the requirement of assumption (2). In addition, based on the analysis of Miller (1999) who investigated the state evolution of TR No. 5, the gearbox is constantly in its healthy state under condition No. 2. Therefore, it is eligible to compute b0 using the first 12 data sets under condition No. 1. This is also consistent with the requirement of assumption (3). Since only the gear meshing fundamental and associated lower sidebands that result in the maximum frequency of interest 1,750Hz are considered in order to reduce computational requirements, it is therefore mandatory to obtain sufficient spectral information regarding the state evolution of the driven gear of interest. This condition can be satisfied, since gear meshing fundamental and its lower sidebands are typically characteristic defect frequencies and also the most dominant spectral area which contains most energy of gear meshing motion, although partial spectral information beyond 1,750Hz is ignored. Thus, assumption (4) is valid. The normalized contour plots of Tlo of the trivariate time series with order p ¼ 21 are illustrated in Figure 9(a) and (b) for A10 and A11 only, which show the Tlo progressions evaluated over 83 data sets. It can be seen that in both Figure 9(a) and (b) there is no visible demarcation line at data set 13 where the change of operating condition takes place. This, to some extent justifies the insensitiveness of the detection statistic Tlo to variation of operating conditions. Though, the Tlo plot of A11 is unlikely to represent true evolution of the gearbox’s state since it is against the findings of post-failure checkup (Byington and Kozlowski, 1997). The abnormal Tlo plot of A11 may be due to the poor quality of the collected vibration signal as denoted in the original data CD. Notwithstanding, the Tlo plot of A10 presents a very satisfactory illustration of the deterioration process. As a matter of fact, this finding is consistent with the finding of our previous study (Zhan et al., 2002a, b) which also showed that the single axial accelerometer A03 presents the most desirable results in describing the state evolution of the gear of interest. Furthermore, Miller (1999) indicated in his research thesis that accelerometers mounted in axial direction are able to give signals with best quality. This further confirms our finding in the present study. By checking the intensity level of the shaded area in Figure 9(a), detectable symptom of incipient fault of the gearbox can be observed around data sets 25/26. A notable jump is present
Model for vibration monitoring 371
Figure 9. Tlo Contour plots of accelerometers A10 and A11, respectively (MEKF-based model)
between data sets 40 and 50. This is consistent with the RMS trace of A04 as shown in Figure 10(b), while RMS trace of A02 shown in Figure 10(a) presents a gradual increment around data set 40 which is slightly earlier than that of RMS trace of A04. Thereafter, this infantile faulty state develops gradually and continuously until data sets 61/62 approximately, becomes more serious after data set 68 and remains the faulty state until data set 83, where the RMS levels of two accelerometers (A02 and A04) passes 150 per cent of nominal levels, engendering the shutdown of the test bed. In order to confirm the analysis of A10’s Tlo plot, the Tlo plots of A02 and A03 obtained by making use of the NAKF model proposed in our previous studies (Zhan et al., 2002a, b) are quoted in Figures 11(a) and (b), respectively. Both Figures 11(a) and (b) suggest that the gear tooth defect initiates around data set 28 approximately, shows a notable jump between data sets 40 and 50 and keeps a slow developing
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Figure 10. RMS signal strength of accelerometers A02 and A04 vs datasets
tendency till data set 62 and thereafter, there is a rapid degradation period from data set 62 to 68, which gives a five-hour earlier warning than the RMS method as shown in Figure 10 which presents a quite fast growing duration of faulty state within data set range [73, 83] in both Figure 10(a) and (b). After data set 68, the gearbox goes quickly to breakdown. Evidently, the result of A10 is well consistent with the findings of A02 and A03. Comparing Figure 9(a) with Figure 10, it is evident that the Tlo method, by making use of the accurate spectral information provided by the proposed MEKF-based model, is superior to the conventional RMS method with respect to two regards. First, the RMS method is very sensitive to the alternating of operating conditions, but the Tlo method is not. Second, the Tlo method is able to yield an earlier warning for incipient fault of rotating machinery. This is very significant for industrial
Model for vibration monitoring 373
Figure 11. Tlo Contour plots of accelerometers A02 and A03, respectively (NAKF-based model)
practices, in that it provides sufficient warning for timely scheduling necessary maintenance activities and, therefore, avoiding catastrophic failures. 5. Conclusions In this paper, a modified extended Kalman filter is applied to process non-stationary multivariate vibration monitoring signals fitted by a state space representation of time-varying VAR model. The performance of the proposed model has been evaluated by using simulated and true online vibration signals in two aspects: adaptation capability and spectral resolution capability in time-frequency domain. Results show that the proposed model is able to quickly converge to the steady state and generate precise spectral information even under highly non-stationary conditions with abrupt changes, as well as providing an adaptive fashion for on-line vibration monitoring. It is noteworthy
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that the simulated signal is characterized by highly non-stationary property, since it contains abrupt changes in its spectral contents within very short duration and, thus, furnishes very harsh conditions for evaluating the performance of the proposed MEKF-based time-varying VAR model. This artificially introduced non-stationary property is to a great extent similar to the gear fault-induced non-stationary effects, since the damaged teeth of a faulty gear will also introduce abrupt changes into the spectral contents of vibration signals when they get involved in meshing motion with another gear over each revolution. The simulation results show highly desirable properties of the proposed model with respect to the adaptability and accuracy of the resulting spectra. The proposed model was then implemented to provide online time-averaged spectral domain information to make CBM decisions of the gearbox. The implementation demonstrates that it is capable of yielding accurate frequency-domain information for scheduling correct online maintenance decisions. References Ahmed, N.U. and Radaideh, S.M. (1994), “Modified extended Kalman filtering”, IEEE Transactions on Automatic Control, Vol. 39 No. 6, pp. 1322-6. Arnold, M., Milner, X.H.R., Witte, H., Bauer, R. and Braun, C. (1998), “Adaptive AR modeling of nonstationary time series by means of Kalman filtering”, IEEE Transactions on Biomedical Engineering, Vol. 45 No. 5, pp. 553-62. Baillie, D.C. and Mathew, J. (1996), “A comparison of autoregressive modeling techniques for fault diagnosis of rolling element bearings”, Mechanical Systems and Signal Processing, Vol. 10 No. 1, pp. 1-17. Byington, C.S. and Kozlowski, J.D. (1997), “Transitional data for estimation of gearbox remaining useful life”, Mechanical Diagnostic Test Bed (MDTB) Data (CD-ROMs: Test Run TR#5), Condition-Based Maintenance Department, Applied Research Laboratory, The Pennsylvania State University. Christer, A.H., Wang, W. and Sharp, J.M. (1997), “A state space condition monitoring model for furnace erosion prediction and replacement”, European Journal of Operational Research, Vol. 101, pp. 1-14. Chui, C.K. and Chen, G. (1999), Kalman Filtering: with Real-Time Applications, Springer-Verlag, New York, NY and Berlin. Chui, C.K., Chen, G. and Chui, H.C. (1990), “Modified extended Kalman filtering and a real-time parallel algorithm for system parameter identification”, IEEE Transactions on Automatic Control, Vol. 35, pp. 100-4. Conforto, S. and D’Alessio, T. (1999), “Spectral analysis for non-stationary signals from mechanical measurements: a parametric approach”, Mechanical Systems and Signal Processing, Vol. 13 No. 3, pp. 395-411. Dron, J.P., Rasolofondraibe, L., Couet, C. and Pavan, A. (1998), “Fault detection and monitoring of a ball bearing benchtest and a production machine via autoregressive spectrum analysis”, Journal of Sound and Vibration, Vol. 218 No. 3, pp. 501-25. Jardine, A.K.S., Joseph, T. and Banjevic, D. (1999), “Optimizing condition-based maintenance decisions for equipment subject to vibration monitoring”, Journal of Quality in Maintenance Engineering, Vol. 5 No. 3, pp. 192-202.
Koo, I.S. and Kim, W.W. (2000), “The development of reactor coolant pump vibration monitoring and a diagnostic system in the nuclear power plant”, ISA Transactions, Vol. 39, pp. 309-16. Kung, S.Y. and Hwang, J.N. (1991), “Systolic array designs for Kalman filtering”, IEEE Transactions on Signal Processing, Vol. 39 No. 1, pp. 171-82. McFadden, P.D. and Toozhy, M.M. (2000), “Application of synchronous averaging to vibration monitoring of rolling element bearings”, Mechanical Systems and Signal Processing, Vol. 14 No. 6, pp. 891-906. Mechefske, C.K. and Mathew, J. (1992), “Fault detection and diagnosis in low speed rolling element bearing. Part I: The use of parametric spectra”, Mechanical Systems and Signal Processing, Vol. 6, pp. 297-307. Miller, A.J. (1999), “A new wavelet basis for the decomposition of gear motion error signals and its application to gearbox diagnostics”, Master of Science thesis, The Graduate School, The Pennsylvania State University. Noriega, G. and Pasupathy, S. (1997), “Adaptive estimation of noise covariance matrices in real-time preprocessing of geophysical data”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 35 No. 5, pp. 1146-59. Parker, B.E. Jr, Ware, H.A., Wipf, D.P., Tompkins, W.R., Clark, B.R., Larson, E.C. and Poor, H.V. (2000), “Fault diagnostics using statistical change detection in the bispectral domain”, Mechanical Systems and Signal Processing, Vol. 14 No. 4, pp. 561-750. Tsang, A.H.C. (1995), “Condition-based maintenance: tools and decision making”, Journal of Quality in Maintenance Engineering, Vol. 1 No. 3, pp. 3-17. Wall, D.S. and Gaston, F.M.F. (1997), “Modified extended Kalman filtering”, IEEE 13th International Conference on Digital Signal Processing Proceedings, Vol. 2, pp. 703-6. Zhan, Y., Makis, V. and Jardine, A.K.S. (2002a), “An adaptive model of rotating machinery subject to vibration monitoring”, IIE Annual Research Conference Proceedings 2002, Paper No. 2066, Orlando, FL. Zhan, Y., Makis, V. and Jardine, A.K.S. (2002b), “Adaptive state analysis of machinery subject to vibration monitoring”, paper presented at the 30th International Conference on Computers & Industrial Engineering, Tinos Island.
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Design and development of product support and maintenance concepts for industrial systems Tore Markeset Stavanger University College, Stavanger, Norway, and
Uday Kumar Lulea˚ University of Technology, Lulea˚, Sweden Keywords Maintenance programmes, Product management, Reliability management, Failure (mechanical), Life cycle costs, Service delivery systems Abstract Product design and service delivery both affect service performance, and therefore a product support strategy must be defined during design stage, in terms of these two dimensions, to ensure the delivery of “promised product performance” to customers. Furthermore, product support strategy should not only be focused around product, or its operating characteristics, but also on assisting customers with services that enhance product use and add additional value to their business processes. This paper examines various issues such as reliability, availability, maintainability, and supportability (RAMS), etc., which directly or indirectly affect product support, maintenance needs and related costs on the basis of a case study conducted in a manufacturing company. The main purpose of the study was to analyse the critical issues related to the product support and service delivery strategy as being practised by the company, and to suggest means for improvements. On the basis of the case study, the paper presents an approach for design and development of product support and maintenance concepts for industrial systems in a multinational environment. The paper emphasizes that the strategy for product support should not be centred only on “product”, but should also take into account important issues such as the service delivery capability of the manufacturers, service suppliers, the capability of users’ maintenance organization, etc.
Journal of Quality in Maintenance Engineering Vol. 9 No. 4, 2003 pp. 376-392 q MCB UP Limited 1355-2511 DOI 10.1108/13552510310503231
Practical implications If a product is designed with due consideration for product support and maintenance, factors influencing service delivery performance, and the competence and capability of users, it can be a major source of revenue for the manufacturer, distributors (agents) and users. It can also provide a sustainable competitive advantage in the market for all parties involved. Especially, in industries where operations are often located in remote areas, a serious consideration of maintenance and product support can play a key role in ensuring customer loyalty. The authors are thankful to the RAMS Coordinator and the Technical Director in the company for sponsoring the project and for support throughout the study. They further would like to thank the anonymous reviewers for valuable feedback.
Basic and fundamental concepts related to maintenance and product support are discussed in the paper on the basis of a case study in a company delivering advanced industrial products. The paper discusses the issues related to designing out of the maintenance need of system/product versus designing for easy maintenance. This will help the design engineers in picking out the best possible alternatives from product support point of view. Introduction Most physical products and systems wear, tear, and deteriorate with age and use. In general, due to cost and technological considerations, it is almost impossible to design a system that is maintenance free. In fact, maintenance requirements come into consideration mainly due to a lack of proper designed reliability and quality for the tasks or functions to be performed. Thus the role of maintenance and product support can be perceived as the process that compensates for deficiencies in design, in terms of unreliability and quality of the output generated by the product. Other factors such as human error, statutory requirements, accidents, etc., also influence the design and development of product support and maintenance concept. Product support and maintenance needs of systems, are more or less decided during the design and manufacturing phase (see, e.g. Blanchard, 2001; Blanchard and Fabrycky, 1998; Goffin, 2000; Markeset and Kumar, 2001; Smith and Knezevic, 1996). Often the reasons for product failures can be traced back to design engineers’ and management’s inability to foresee problems. Furthermore, the strategies adopted by owners/users concerning systems operation and maintenance, also considerably affect maintenance and product support needs. Hence, we can assert that product design and service delivery both affect service performance, and therefore product support strategy for customers must be defined in terms of these two dimensions (see Cohen and Lee (1990) for further discussion). Service delivery performance in the operational phase can be enhanced through better service delivery of spare parts and improvement of the technical support system. However, to ensure the desired product performance at a reasonable cost, we have to design and develop maintenance and product support concepts right from the design phase. The existing literature appears to have paid little attention on the influence of product design characteristics in dimensioning product support. Product support: some basic concepts Traditionally, support merely constituted maintenance, service and repair. However, as the scope of product support has broadened over the past decade, it has also included such aspects as installation, commissioning, training, maintenance and repair services, documentation, spare parts supply and logistics, product upgrading and modifications, software, and warranty
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schemes, telephone support, etc. (Blanchard and Fabrycky, 1998; Goffin, 1999; Wilson et al., 1999). Product support, in respect to maintenance needs, can be classified as tangible and intangible, as well as planned (proactive) and unplanned (reactive). It is tangible if there is an exchange of physical parts (e.g. spare parts, tools, printed documentation, training manuals, etc.) involved. If the rendered service involves only intangible support (e.g. expert advice, training, online support, etc.) pricing is more complicated. Planned support is often related to preventive maintenance, training, installation, commissioning, etc., while unplanned support is often connected to unplanned corrective maintenance activities where the product fails unpredictably (we exclude here planned corrective failures of non-critical parts, components, and sub-systems). Unplanned support can also be the assistance needed to resolve problems related to planned maintenance and service, but where the documentation is inadequate, the recommended spare parts or tools are unavailable, etc. Common for unplanned support and maintenance is that it is often very inconvenient, costly and time consuming for all parties involved. As customer satisfaction is crucial to business success, product and service strategies should be aligned to customers’ needs. Staying close to customers and providing superior services create more loyal customers and increased customer satisfaction (Fites, 1996). Improved customers satisfaction and increased repeat sales can be achieved by matching service and product support delivery strategy to the urgency of the customer’s needs (see Cohen et al., 2000). How the quality of these service delivery processes improves customer satisfaction and loyalty, has been discussed in depth by many researchers (see, e.g. Berry et al., 1988; Gro¨nroos, 2000; Kasper and Lemmink, 1989; Parasuraman et al., 1985). A distinction between services supporting the products, and services that support the customer’s actions in relation to products is essential for developing an optimal maintenance and product support strategy (Mathieu, 2001). The main goal of a service intended to support a product, is to ensure the expected function and/or to facilitate the client’s access to its function. Services intended to support the customer, are related to improving the customer’s accessibility to product function, efficient and effective use of it, and retrieval of performance attributes. Implementation of effective and efficient service strategies requires a thorough understanding of product characteristics, product application, etc., during use. However, the kind of services delivered by manufacturers of industrial products, which are closely connected to the product reliability and performance characteristics, have not been researched extensively (Goffin, 1998; Goffin and New, 2001). Case study observations and analysis The company studied is a part of a larger industrial group of companies with regional offices located all over the world. It produces various types of
customized integrated and advanced production systems. More formally, the regional offices purchase required systems from the manufacturer and integrate it into the customer’s production system. The company has observed an increased trend in product support needs. It is not clear if this is caused by more products being sold, increased product complexity, reduced product reliability compared to an earlier model, by changed or more intensive product use, or by changed customer needs and conditions. The product will be more attractive if it is designed for low life-cycle costs (LCC), minimal required support, and optimal support delivery. The study can be characterized as an action research methodology where the researcher participates in the processes and operations (see, e.g. Westbrooke, 1995). Various forms of data and information were collected through employee surveys, interviews and conversations, study of company literature, participation in meetings and projects, and analysis of work processes. Strengths, weaknesses, opportunities, threats (SWOT) analysis methodology was used to organize and systematize the observations and information. Recommended maintenance practices, predicted LCC and performance Customers are increasingly focused on reliability and cost. For the company to stay competitive it is necessary to deliver products with documented and predictable quality, reliability, supportability, and maintainability. The customers are also demanding an estimate for LCCs. The company has developed a software tool to assist in making sure that RAMS issues are considered throughout the product design, manufacturing, and delivery phases. The tool is based on failure mode effects and criticality analysis (FMECA) methodology and is integrated in product development project management. An LCC analysis is dependent on good reliability and maintainability data input. Much of this data can be estimated using experience, service reports, spare and warranty parts data, comparison with similar products, product databases, etc. However, quantitative input from product owners and users would be valuable to reduce uncertainty in these estimates (see Markeset and Kumar, 2002). The design tool developed in the company will provide a basis for recommended maintenance strategies (including preventive maintenance), training, documentation, spare part logistics, product support, etc. Documentation Product documentation has gone through a tremendous development during the last five to six years and is now considered to be excellent, employing the latest software developments to make it more accessible and easy to use. For complex products, there is a problem in making the available information accessible and understandable to the user. Documentation also usually ends up being quite extensive. Excellent documentation can be of immense use in dimensioning of product support during the design phase, as well as in
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maintenance, service, diagnostics, and repairs/restorations after failure. Furthermore, documentation is important for the company in respect of warranty and support. Recent developments in information technology make it easier to make digital documentation. Spare part and warranty issues The sale of spare parts is an important source of income for the company, but, at the same time, warranty costs are substantial. Corrective maintenance often involves warranty considerations during part of the product’s service life. The company want the market to have the impression that they provide high-quality products that are reliable, durable, dependable, and come with no negative surprises. As a result, they are continuously trying to improve their products and to remove the need for spare parts. However, it often proves impossible to design out maintenance, and as a result the products have to be designed for effective and efficient maintenance and support. Even if the product is designed for maintenance free life-cycle, random and unforeseen failures can still occur. It is negative for both customers and manufacturer that warranty parts are needed. However, both warranty and service provision is a way of reducing the risk for the customer. Training The company offers various training programs for their customers. However, there may be a need for the instructors to acquire hands-on experience from a customized product application as seen from the customers’ viewpoint. Lack of user understanding of product capabilities, and a difficult user interface, reduces the user’s capability to utilize the product fully. The result can be a very dissatisfied customer. Incorrect use can also lead to increased maintenance, faster degradation, wear and tear, increased warranty costs for the manufacturer. In the worst case, it can lead to accidents, reduced safety, and damage to health and environment. Training of users and operators improves their ability to correctly apply/use and maintain the products and, not least, increase user satisfaction. The ability to take full advantage of product capabilities and capacities, and to obtain maximum product value, also increases. Customer complaints resolution process: online service and assistance The company uses many databases and information systems to manage customer feedback, complaints and product problem resolution, quality assurance and control, field service reporting, information provision to customer with respect to product problem solutions, etc. They also have in place telephone helplines and online/Internet support for fast problem resolution. We observed that employees were often disturbed in their planned regular work to resolve customer problems requiring expert assistance. This kind of
product support work they call “fire-fighting activities” and often have high priority. This kind of “work process disturbances” will exist as long as unplanned and unpredictable product failures can occur and the customers (or any intermediaries) do not have the required competence to resolve the problem themselves. A more “proactive” approach would be to try to reduce the consequences of such disturbances for both the customer and manufacturer, by planning and accommodating for such activities (inserting contingencies in experts’ time schedules, implementing possibilities for remote product surveillance, improved communication, etc.). To remove the need for this kind of assistance may prove impossible, as the failure has to be designed-out, but the consequences can be reduced by increasing diagnostic capabilities, improving documentation, diagnostic and corrective routines, etc. Figure 1 depicts examples of different kinds of product support observed in this study.
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Development of product support and maintenance concept: dimensioning of product support Based on the discussions in the previous section, we find that product support and maintenance concept is decided and affected by issues both during the design and operation phase. We will now discuss design and development of product support during design phases of product development. Product support and service delivery strategy Product support needs are dependent on product characteristics such as reliability and maintainability, the customer’s skills and capabilities, and the
Figure 1. An overview of product support and service types observed in the company
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Figure 2. Integration of customer needs and product attributes
environment in which the product is going to be used. Therefore, product support specifications should be based on design specifications and conditions faced by the customer. The idea is to be proactive in the design phase, not reactive in the exploitation phase. After-sales services are often in response to a customer problem, e.g. product failure restoration, problem diagnosis, expert assistance to resolve a problem, problem with using the product, etc. Therefore, after-sales service is a recovery process that attempts to resolve a customer problem, which, if not resolved, causes dissatisfaction and a less satisfied customer. The service function therefore attempts to recover the customer satisfaction to the level it was before the occurrences of problems (Gro¨nroos, 2000). In the long-term, a manufacturer will benefit from supplying a product that needs as little maintenance as possible. It is important to understand operators’ requirements, performance targets, system attributes, and the competence level of operators and maintenance personnel before the design process is initiated. It is essential that customer needs and organization culture are integrated with system attributes and product support strategy. Companies developing products and services need to understand what consequences and benefits product attributes have on customer needs and values, and how they affect customer expectation and satisfaction. Product attributes related to customer satisfaction can be divided into “must be” attributes (basic requirements), “one-dimensional” attributes (performance requirements) and “attractive” attributes (surprise and delight requirements) (Kano et al., 1984; Matzler and Hinterhuber, 1998). These are captured in the information pyramid depicted in Figure 2. The bi-directional arrows show two concepts; namely, the concept of abstraction where concrete
product and service attributes provide consequences and benefits which fulfil the customer’s needs and values, and the concept of translation where information about customer’s needs and values are translated into concrete products and services (Johnson, 1998). System engineering is an effective approach to incorporate customer’s specifications into the design process. It is a top-down approach to product development, viewing the system as a whole, focusing on customer’s needs, wants, preferences, and requirements – starting with the functional requirements and the functional performance of the product. Figure 3. illustrates the relationship between product/system characteristics (reliability and maintainability), product exploitation (type of application), and product support. Designed product functional and RAMS characteristics influence how the product is operated and maintained, as well as what kind of, how much, and when support is needed. Furthermore, product use and maintenance, customer’s skills and competencies, operational environment, etc., also influence what kind of product support needed. The continuous lines indicate primary influences, whereas broken lines indicate secondary influences. The box containing product characteristics and product support forms the functional product. To avoid blocking capital the customer can choose to buy only the function, and not the product (Markeset and Kumar, 2002). Of late, this has become increasingly popular and a more attractive approach. With functional products, the user company focuses on core business processes (e.g. production) and need not worry about service/maintenance. In such an approach, both parties (supplier and customer) share the business risks.
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Flaws and errors: root causes of product support and maintenance requirements As a product becomes increasingly complex, integrating advanced mechanical, electrical, software, and electronic subsystems and technical solutions, it becomes increasingly difficult to foresee all the possible ways that the final
Figure 3. Relationships between “product characteristics”, “product exploitation”, and “product support”
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Figure 4. Failures and errors leading to product support and maintenance requirement
product can fail. As the components and sub-systems become more technically advanced and the number of components increases, the possibilities of failure also increase. Through exhaustive testing of prototypes before product release and use, many potential failures can be eliminated. In evolutionary design, there is the opportunity to improve the functional performance by designing-out weaknesses (physical, functional performance, etc.) found during exploitation. By adding something new or changing a standard product, by customizing it to fit a customer’s demands, wants, and desires, one also introduces various new possibilities of product failure. Product failures can be attributed to failure in the design and delivery processes, operational environment, or how the product is used. A design failure can be defined as an inability of an engineering solution to perform its intended function(s), while errors can be defined as the underlying cause for design failure (Voland, 1999). Both the specification process and the implementation processes of the product creation process contribute to design failures. The specification process is often a result of interaction between the manufacturer and the industrial customer, while the design specification implementation process is the responsibility of the manufacturer. The underlying causes of failures can be attributed to physical flaws (e.g. overload, fatigue, corrosion, electrical hazards, etc.), error in work processes (design, analysis, manufacturing, assembly, maintenance, operation), and errors in user perspectives and attitudes as shown in Figure 4. Errors in work processes can cause physical flaws and typically include incorrect calculations, faulty assumptions, miscommunications, failure to follow established procedures and routines, performing tasks out of order, etc. Flaws in the perspective or attitude of the employees participating in a specific work process can lead to errors in work processes. Reason (1990) defines human error as “the failure of planned actions to achieve their desired ends – without the intervention of some unforeseeable event”. Typical examples are error in judgment, error in moral perspective, over-confidence, under-confidence, indifference, arrogance, selfishness, and other forms of focusing on oneself rather than on others. Training and awareness-creating
activities are therefore necessary to avoid such errors. The manufacturer should therefore carefully design the work processes for design, manufacturing, assembly, etc., and, not least, for supporting product use, to avoid errors in use and reduced reliability and quality, and, finally, for better service delivery performance. Quality and reliability issues Customer satisfaction is related to both product characteristics and product support quality. Customer perception of product quality is affected by how well the product conforms to specification and fits to its intended use, and also by product reliability over time (Juran and Blanton, 1999). Customer satisfaction is also affected by product characteristics such as maintainability, supportability, and product support, as well as by the processes involved in providing product support. Customer satisfaction is, in other words, not only decided by value and performance of hardware purchased, but by the total value received, and by the quality of the interaction and relationship experience throughout the service life of the product.
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“Design out maintenance” and “design for maintenance” While considering maintenance in design, there are generally two options: either one can try to design out maintenance (Figure 5) or try to optimise the design with respect to maintenance issues (Figure 6). After having identified maintenance characteristics one has the possibility to try to eliminate those characteristics that would cause maintenance costs. However, if maintenance is to be designed out, one has to consider the cost of reliability throughout the product’s life-cycle. Furthermore, one has to consider costs and available state of the art technology. There are also other considerations such as product capacity, design alternatives, and payback of development cost, etc., to evaluate. There will always be trade-offs between these considerations. LCC analysis can be used to compare design alternatives and its results have to be balanced against market needs, customer willingness to pay, customer preferences, etc. In designing out maintenance, one can use the RAMS tools like FMECA, fault tree analysis (FTA), event tree analysis (ETA), and risk analysis to arrive at the best LCC alternative. If the LCC of the design out maintenance approach
Figure 5. “Design out” maintenance
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Figure 6. “Design for” maintenance and product support
are higher compared to the alternative design for maintenance, one naturally prefers the latter. As long as the failure or degradation mechanism is known, one can design a compensating maintenance and support strategy to reduce risk, and to make the product easy to maintain and support. The presence of wear mechanisms causing maintenance does not mean that the system is unreliable – it may, however, become unreliable if the compensating mechanisms are unreliable or fail. If the reliability is too low, maintainability issues such as accessibility to parts that need to be maintained, serviceability and interchangeability of parts and systems, use of modular design have to be considered (Blanchard et al., 1995; Dhillon, 1999; Ericsson and Erixon, 1999; Thompson, 1999). Warranty and life span are also issues to be evaluated. The objective of such analysis is to reduce product maintenance time and cost, and to determine labour and other related costs by using maintainability data to estimate item availability. Other ways to reduce future maintenance needs, is to reduce capacity, to substitute/eliminate the weak functions, or to replace weak components by ones that are more robust. If we allow the system/component to fail due to various limitations, then we need to have a provision for easy and quick repair/replacement. Thus, when designing for maintenance, one will first have to examine the reliability characteristics, and thereafter decide the maintainability characteristics. Both reliability and maintainability are traded off to meet the design requirement. LCC analysis, in combination with
risk analysis methods, could be a viable tool for evaluating these issues (Blanchard and Fabrycky, 1998; Moss, 1985). Furthermore, the maintenance procedures need to be correct, precise, as well as easy to follow and technical methods need to be safe enough. Operating environment Operating environment should be seriously considered while dimensioning product support and service delivery performance strategies. More often than not, the recommended maintenance program for systems and components are based on their age without any consideration of operating environment. This, in turn, leads to many unexpected system and components failures. This creates poor system performance and a higher LCC due to unplanned repairs and/or restoration as well as support. The environmental conditions in which the equipment is to be operated, such as temperature, humidity, dust, maintenance facilities, maintenance and operation personnel training, etc., often have considerable influence on the product reliability characteristics and thereby on the maintenance need and product support requirement (Kumar and Kumar, 1992; Kumar et al., 1992). Furthermore, the distance of user from manufacturer, distributor/supplier can bring additional influence. Design for data collection, diagnostics, prognostics, Internet applications, etc. During operation phase, manufacturers can benefit from obtaining information about the product’s technical health as well as conformance and deviations from the expected performance targets. The collected data can be effectively used for the development of new generation of products, but, most importantly, it can be used for changing design to remove or reduce any critical weaknesses in design that lead to higher demands on service and maintenance. The data can also be used to make prognoses about future maintenance and support needs, and to predict when to upgrade, modify or replace the equipment. See Markeset and Kumar (2003) for further discussion. The designer’s goal, in respect to design for diagnosability, is to create a process of determining the parameters that can signal product ill-health. Automated sensor-based diagnostics systems have been the focus in work conducted towards diagnostics in mechanical systems (Paasch and Ruff, 1997). Remote and real-time assessment of performance, which often is a must for automated and complex systems, requires integration of various technologies such as sensory devices, reasoning agents, wireless communication, virtual integration and interface platforms. In the near future, Internet and advanced communication technology can be used to facilitate easier assessment of product performance, maintenance, and support system. Furthermore, advancements in information technology provide a better interface and thus largely facilitate communications between users and the support system (Lee, 2001).
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The capabilities of manufacturer’s service organization and customer’s maintenance organization In general, manufacturers/suppliers, besides being a manufacturer, also need to maintain a service organization delivering services to their customers in the same way as any other service organizations such as a hotel, travel agency, bank, etc. Therefore, most manufacturers usually have a service department responsible for delivering services such as assistance in fault finding, failure diagnostics, supplying expert assistance, spare part delivery, spare part storage, etc. However, many manufacturing companies are uncomfortable with the intense service expectations of their customers. The service department usually functions in a different way than other internal departments, since its relationship with the customers is often of a much longer duration. The service department needs to stay in contact with the customers for the rest of the product life span. While designing and dimensioning a product support and service delivery strategy, designers have to analyse the company’s own service delivery capabilities and to align them with customer’s needs. It is important to analyse owners’ maintenance organization, location, level of competence, culture, etc., to arrive at the best service and maintenance alternative. If the supplier is delivering a total functional system (i.e. including operation, maintenance, and support), the customer’s user environment, operation and maintenance goals and strategies, and so on, need to be understood to assure optimal and sustaining functional performance and customer satisfaction. This will help the designer to design an appropriate service delivery system that will satisfy the customer. As mentioned in the preceding section, this necessitates that manufacturing companies should analyse and understand its “customer” before adopting any strategy for service delivery. If not, the outcome can be poor product support and a dissatisfied customer. This is mainly due to work culture gaps, separating service environments from manufacturing environments.
Interactive problem resolution Some influential aspects of future product performance and failure are contended to be fundamentally unpredictable and unknowable at the design stage (Bea, 2001). When such problems occur in the exploitation phase, an interactive and improvised approach is often needed for fast, effective and cost-efficient problem resolution. Furthermore, the manufacturer, distributors, customer, and suppliers should design in contingencies, risk reduction activities, active intervention training, etc., in product support for making the problem resolution process, for this kind of problem, as painless and cost efficient as possible. By being proactive in the design stage, the consequences are less in the product exploitation stage for this kind of problem.
Development of maintenance concept: operation phase Once a system or product is commissioned for use, the maintenance concept is more or less fully governed by the type of maintenance strategy adopted by the user for the system. Establishing maintenance strategy requires understanding the technical characteristics of the product, and functions to be performed. Of course, one has to examine the types of resources (organization and level of competence) available. Often an interactive approach is needed to deal with maintenance problems in unpredictable environments such as mining, offshore oil exploration and production, etc. Furthermore, measures need to be started for implementing world-class maintenance practices evolving from manufacturing and process industries; namely, total productive maintenance (TPM) and reliability centred maintenance (RCM). TPM (see Nakajima, 1986) was developed in Japan and has many successes in manufacturing sectors. On the other hand, RCM (see Moubray, 1997) was developed in the USA and is popular among aerospace and process industry for optimising maintenance processes. In fact, TPM and RCM have been major themes in the development of maintenance strategies for the last ten years. Many companies have followed this route and have demonstrated considerable improvements in plant and process performance (Dawson, 1996). Many industrial companies are also adopting these philosophies and practices in their operations and maintenance strategies. The type of maintenance strategy decided on should be developed taking into account internal resources (facilities, tools, competence, knowledge and manpower, etc.) available to deal with maintenance and repair problems and issues. If there is a lack of competence or manpower to deal with maintenance/service work, one has to rely on external resources. The use of external resources and outsourcing of maintenance Contractors, distributors, and consultants who provide competence, knowledge or manpower to operations and are not directly employed by the product owners, are termed as external resources. Of late, many users’ companies are focusing on their core processes and competencies while outsourcing other areas. With the advent of this trend, outsourcing of maintenance is becoming a popular way to deal with maintenance and support requirements. Recently, many manufacturers and suppliers are offering total performance guarantee for their products or are supplying a functional product as mentioned earlier. In such cases, the manufacturer and suppliers are taking the full responsibility for the operation, maintenance, and support of the system. The customers only pay the supplier for the function they provide. This has revolutionised the product support issues from the designers’ point of view, forcing them to look for the best available solution that will lead to the lowest LCC. The past practice of making profit by the sale of spare parts and services to customers is no longer valid in case of functional products.
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Concluding remarks The ultimate goal of the product, or service, is to facilitate or fulfil the customers’ goals. These goals therefore need to be designed into the product or service. Furthermore, a performance indicator system should be used to monitor the effectiveness and efficiency of the implemented operation, maintenance and support strategies (ee Kumar and Ellingsen (2000) for further details). In this paper, we have discussed a general approach for the dimensioning of product support by taking into account product design characteristics, information technology applications, capability of service delivery organizations, client service needs and expectations, the manufacturer’s delivery capabilities, etc. It is clear that maintenance is more or less dependent on the designer’s perception of function to be performed, manufacturer’s service delivery capability and user’s competence, and capability of any third party involved. Products and services have to be designed from a holistic perspective benefiting and adding value for all participants. It is believed that if designed properly, product support and support strategy can be a major source of revenue and profit for the manufacturers, product owners, and intermediaries. Furthermore, during the operational phase of systems, a considerable amount of savings can be made from service and maintenance cost by establishing an effective and efficient service and maintenance strategy.
References Bea, R.G. (2001), “Risk assessment and management of offshore structures”, Prog. Struct. Engng. Mater., Vol. 3, pp. 180-7. Berry, L.L., Parasuraman, A. and Zeithaml, V.A. (1988), “The service-quality puzzle”, Business Horizons, Vol. 31 September-October, pp. 35-43. Blanchard, B.S. (2001), “Maintenance and support: a critical element in the system life cycle”, Proceedings of the International Conference of Maintenance Societies, May, Melbourne, Paper 003. Blanchard, B.S. and Fabrycky, W.J. (1998), Systems Engineering and Analysis, 3rd ed., Prentice-Hall, Upper Saddle River, NJ. Blanchard, B.S., Verma, D. and Peterson, E.L. (1995), Maintainability: A Key to Effective Serviceability and Maintenance Management, Wiley, New York, NY. Cohen, M.A. and Lee, H.L. (1990), “Out of touch with customer needs? Spare parts and after sales service”, Sloan Management Review, Winter, pp. 55-66. Cohen, M.A., Cull, C., Lee, H.L. and Willen, D. (2000), “Saturn’s supply chain innovation: high value in after sales service”, Sloan Management Review, Summer, pp. 93-101. Dawson, A. (1996), “Reliability centred maintenance and its implications for asset management systems”, Maintenance, Vol. 11 No. 1, pp. 15-18. Dhillon, B.S. (1999), Engineering Maintainability: How to Design for Reliability and Easy Maintenance, Gulf, Houston, TX.
Ericsson, A. and Erixon, G. (1999), Controlling Design Variants: Modular Product Platforms, Society of Manufacturing Engineers, Dearborn, MI. Fites, D.V. (1996), “Make your dealers your partners”, Harvard Business Review, March-April, pp. 40-51. Goffin, K. (1998), “Evaluating customer support during new product development: an explorative study”, J Prod Innov Manag, Vol. 15, pp. 42-56. Goffin, K. (1999), “Customer support: a cross industry study of distribution channels and strategies”, International Journal of Distribution and Logistics, Vol. 29 No. 6, pp. 374-97. Goffin, K. (2000), “Design for supportability: essential component of new product development”, Research-Technology Management, Vol. 43 No. 2, March/April, pp. 40-7. Goffin, K. and New, C. (2001), “Customer support and new product development: an explorative study”, International Journal of Operation & Production Management, Vol. 21 No. 3, pp. 275-301. Gro¨nroos, C. (2000), Service Management and Marketing: A Customer Relationship Management Approach, 2nd ed., Wiley, Chichester. Johnson, M.D. (1998), Customer Orientation and Market Action, Prentice-Hall, Upper Saddle River, NJ. Juran, J.P. and Blanton, G.A. (Eds) (1999), Juran’s Quality Handbook, 5th ed., McGraw-Hill, New York, NY. Kano, N., Seraku, N., Takahashi, F. and Tsjuij, S. (1984), “Attractive quality and must-be quality”, Hinshitsu: The Journal of the Japanese Society for Quality Control, April, pp. 39-48. Kasper, H. and Lemmink, J. (1989), “After sales service quality: views between industrial customers and service managers”, Industrial Marketing Management, Vol. 18, pp. 199-208. Kumar, U. and Ellingsen, H.P. (2000), “Development and implementation of maintenance performance indicators for the Norwegian oil and gas industry”, Proceedings of EUROMAINT 2000, Gothenburg, 7-9 March, pp. 221-8. Kumar, D. and Kumar, U. (1992), “Proportional hazard model: a useful tool for the analysis of a mining system”, Proceedings of the 2nd APCOM Symposium, Tucson, Arizona, 6-9 April, pp. 717-24. Kumar, D., Klefsjo¨, B. and Kumar, U. (1992), “Reliability analysis of power cables of electric loader using proportional hazard model”, Reliability Engineering and System Safety, Vol. 37, pp. 217-22. Lee, J. (2001), “E-manufacturing systems for e-business transformation”, College of Engineering and Applied Science, Center for Intelligent Maintenance Systems, University of Wisconsin, Madison, WI, pp. 1-8, available at: www.uwm.edu/ceas/ims Markeset, T. and Kumar, U. (2001), “R&M and risk analysis tools in product design to reduce life-cycle cost and improve product attractiveness”, Proceedings of The Annual Reliability and Maintainability Symposium, 22-25 January, Philadelphia, pp. 116-22. Markeset, T. and Kumar, U. (2002), “Integration of RAMS and risk analysis in product design and development work processes”, paper presented at the IFRIMmmm 2002, Maintenance, Management and Modelling Conference, Va¨xjo¨, 6-8 May. Markeset, T. and Kumar, U. (2003), “Integration of RAMS information in design processes – a case study”, paper presented at the 2003 Annual Reliability and Maintainability Symposium, Tampa, FL, 20-24 January. Mathieu, V. (2001), “Product services: from a service supporting the product to a service supporting the client”, Journal of Business & Industrial Marketing, Vol. 16 No. 1, pp. 39-58.
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Matzler, K. and Hinterhuber, H.H. (1998), “How to make product development projects more successful by integrating Kano’s model of customer satisfaction into quality function deployment”, Tecnovation, Vol. 18 No. 1, pp. 25-38. Moss, M.A. (1985), Designing for Minimal Maintenance Expense, Marcel Dekker, New York, NY. Moubray, J.M. (1997), Reliability Centred Maintenance: RCM II, 2nd ed., Butterworth Heinemann, Oxford. Nakajima, S. (1986), “TPM: challenge to the improvement of productivity by small group activities”, Maintenance Management International, Vol. 6, pp. 73-83. Paasch, R. and Ruff, D.N. (1997), “Evaluation of failure diagnosis in conceptual design of mechanical systems”, Journal of Mechanical Design, March, Vol. 119, pp. 57-64. Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1985), “A conceptual model of service quality and its implications for future research”, Journal of Marketing, Vol. 49, pp. 33-46. Reason, J. (1990), Human Error, Cambridge University Press, New York, NY. Smith, C. and Knezevic, J. (1996), “Achieving quality through supportability: part 1: concepts and principles”, Journal of Quality in Maintenance Engineering, Vol. 2 No. 2, pp. 21-9. Thompson, G. (1999), Improving Maintainability and Reliability through Design, Professional Engineering Publishing, Bury St Edmunds. Voland, G. (1999), Engineering by Design, Addison-Wesley, Reading, MA. Westbrooke, R. (1995), “Action research: a new paradigm for research in production and operations management”, International Journal of Operations & Production Management, Vol. 15 No. 12, pp. 6-20. Wilson, T.L., Bostro¨m, U. and Lundin, R. (1999), “Communications and expectations in after-sales service provision: experiences of an international Swedish firm”, Industrial Marketing Management, Vol. 28, pp. 381-94.
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Integration of RAMS and risk analysis in product design and development work processes
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A case study Tore Markeset Stavanger University College, Stavanger, Norway, and
Uday Kumar Lulea˚ University of Technology, Lulea˚, Sweden Keywords Reliability management, Life cycle costs, Risk analysis, Customer requirements, Dissemination of information Abstract Most industrial customers are looking for products that meet the functional performance needs and have predictable life cycle cost (LCC). Due to design problems and poor product support, these systems are not able to meet the customers’ requirements. Major causes of customer dissatisfaction are often traced back to unexpected failures, leading to unexpected costs. However, with proper consideration of reliability, availability, maintainability and supportability (RAMS) in the design, manufacturing, and installation phases, the number of failures can be reduced and their consequences minimized. Based on a case study in a manufacturing company, an approach for integration of RAMS and risk analysis in design, development and manufacturing is presented. The importance of LCC analysis, use of feedback information, and integration of various information sources to facilitate easy RAMS implementation, in combination with risk analysis in the design phase, is discussed. An approach is suggested for integration of RAMS in the Stage Gate model for project and work process management, coordination and control, to reduce risk. A training program, developed and implemented during the study to create awareness and to improve learning and understanding of RAMS’ aspects of existing and future products and processes, is also presented.
Practical implications The paper emphasises the importance of reliability, availability, maintainability and supportability (RAMS) characteristics for ensuring failure-free operations of industrial products. It is argued that RAMS characteristics must be considered during the design phase to facilitate competitive advantage for the product and to reduce the business risk associated with non-performance of products and systems. A need for effective and efficient control of the information flow and the work processes involved in the design, manufacturing, delivery, commissioning, and after-sales support The authors are thankful to the company for assisting in sponsoring and financing this research study. They are also thankful to all the employees of the company who helped us to perform this study. Furthermore, they would like to thank anonymous reviewers for their valuable input and feedback.
Journal of Quality in Maintenance Engineering Vol. 9 No. 4, 2003 pp. 393-410 q MCB UP Limited 1355-2511 DOI 10.1108/13552510310503240
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Figure 1. Functional product
was identified as critical to successful integration of RAMS and risk analysis in the work processes. The paper demonstrates the application of RAMS tools and methods on the basis of a case study performed in a manufacturing company. Introduction and background Manufacturers of industrial systems/machines experience increased pressure from customers to deliver customized products with documented RAMS characteristics and LCC, with improved quality, at a lower price, and in a shorter timeframe. The customers demand products that meet the functional performance needs and have predictable performance and cost throughout the service life cycle. However, due to design problems, these systems are not able to meet customer requirements in terms of system performance, effectiveness and efficiency. This is often due to poorly designed RAMS characteristics combined with a poor maintenance strategy. This has given a new dimension to the problem of effective and efficient service and maintenance management of industrial systems/machines. To avoid the complexities of maintenance management, many customers/users prefer to purchase only the required function, not the machines or systems. Thus, the responsibility of maintenance and product support lies with the organization delivering the required function. With the advent of this trend, focus has shifted to the design of functional products. The definition of a functional product is that the user is not buying a machine/system but the function it delivers. Figure 1 illustrates the definition of a functional product and depicts the relationships between product characteristics, exploitation, and support. The continuous and broken lines indicate primary and secondary relationships, respectively. Designed product characteristics (hardware and software) define the types of exploitation the product can be subjected to and the type of product support needed to achieve the expected function and performance. Furthermore, the users and operating environment can also influence the degree of support needed to achieve the expected performance level (Markeset and Kumar, 2002). Major causes of customer dissatisfaction are often traced back to unexpected failures, leading to unexpected costs. In general, product failures are often caused by the design engineers’ and manufacturers’ inability to predict
problems that may occur later in the product application phase. However, with proper consideration of RAMS in design, manufacturing, assembly, testing, and installation, the number of failures can be reduced and their consequences minimized considerably. It is argued that if due attention is paid during the design phase to the “maintenance needs” of the system; considerable savings can be made in the operation phase. Manufacturing companies can gain much from improving the work processes involved in design, manufacturing, assembly, and delivery processes by integrating “the maintenance needs analysis” at the design board stage. Design is a process of balancing needs and functional requirements against various constraints such as material, technological, economical, physical, functional, operational, environmental, legal, and human/ergonomical factors (Pahl and Beitz, 1996; Voland, 1999; etc.). It is a decision-making process where engineers have to make decisions concerning the translation of customer needs, desires, and wants into a product that can fulfill the functional requirements in a reliable and consistent way over time. This process should ensure a product of satisfactory quality in an effective and efficient way. Product complexity caused by integration of electronics, data processing, processing controls, aspects of product acceptance and environmental concerns is steadily increasing, resulting in an ever-increasing number of questions and problems to be considered in the design phase. This necessitates interdisciplinary cooperation and creativity among specialists, creating new demands on organizations and individuals (see, e.g. Pahl and Grote, 1996; Thompson, 1999; Voland, 1999). The discussions in this paper are based on a case study performed for a manufacturer and supplier of industrial systems with customers and distributors worldwide. The company has recently experienced that customers increasingly emphasise demands on product reliability, maintainability, support, and life-cycle costs, and has realized that documented and predictable reliability, quality, maintainability, and LCC for the product could be a competitive advantage. In addition, customers demand the products be delivered with a shorter lead-time, with a shorter commissioning phase, and improved after-sales support. As a result, the company sees the need to implement and integrate systematic and formalized RAMS synthesis and analysis, by incorporating RAMS data analysis together with risk analysis into their design approach. With this background, we will discuss fundamental issues related to implementation of RAMS in product design and development, and related to integration of reliability, maintainability and risk analysis tools and methods to enhance performance efficiency, to reduce product LCC and delivery time, and to increase customer satisfaction and product attractiveness. This approach is expected to create a win-win situation for both manufacturers and customers.
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Figure 2. Integrated product development facilitating interactive information flow
Integration of product performance requirements into the design process A product exists because there is a customer who is willing to pay for and use the product. A manufacturer exists because the product needs to be made and because there is a market and customers for his product. In order to deliver the product or the required function, the manufacturer has to design the product, manufacture it, and provide any required support to meet expected performance demands. These work processes need to be managed and organized. Suitable organizational systems and leadership therefore have to be in place to manage the work processes. This can be referred to as “customer pull” of the product development process. In this case the product and the product delivery system is created and formed on the customers’ terms (see Figure 2). Customer needs, wants, and preferences are, in this case, integrated into the products and serve as the drivers of product and organizational development. In the other extreme, the manufacturer can “push” products on the customers, based on what is technologically possible, and, moreover, form the organization without taking customer’s needs, wants, and preferences into consideration. This reverse relationship is what we refer to as “technological and organizational push”. However, whether the driver for product and organizational development is a pull or a push process, the increased market
pressure in respect of cost, time and performance forces a need for effective and efficient distribution of, and access to, product and work process-related information, and for more proactive, reactive, and interactive information use. It is important to integrate customer needs, wants, and preferences into the design as early as possible, as during this stage it is easier to influence product LCC and customer satisfaction. We argue that integration of RAMS and LCC in combination with risk analysis in the design and manufacturing process is fundamental in accomplishing and ensuring the success of new product development and for reaching the goals set at the outset. There exists a large volume of literature discussing RAMS analysis for different types of products and applications under varying conditions (e.g. Barlow and Proschan, 1981, Blanchard et al., 1995; Dhillon, 1999; Kumar, 1990; Kumar et al., 1992; etc.). However, to our surprise, we did not come across any literature where the issues related to implementation of RAMS and risk analysis in design are discussed. Some of the notable exceptions are Blanchard and Fabrycky (1998), Dhillon (1999), Markeset and Kumar (2001), Sandberg and Stro¨mberg (1999), Van Baaren and Smit (1998), Warburton et al. (1998). For a mechanical system, Warburton et al. (1998) demonstrate a methodology for providing the design engineer with the tools to understand and model mechanical failure characteristics and thereby simulate product behaviour in terms of design, operational, environmental and material parameters based on mathematical models expressing underlying failure processes and parameters. Moss (1985) describes how to design for minimal maintenance expense through the use of LCC analysis. However, this is difficult due to uncertainties and lack of data. Furthermore, product support is often not considered early enough in the design process. If it is, there usually is a lack of quantitative design goals. Often the cost of support is not fully understood at the design stage of developing new products (Goffin, 1998). It seems little research has been reported on how to integrate product support in design (Goffin and New, 2001). Support is needed to compensate for product unreliability, loss of product performance quality and effectiveness, reduced product output quality, lack of usability, etc. Tools, methods and models in RAMS and risk analysis There are many tools and methods available to assess RAMS, LCC and to apply risk analysis during product development (see, e.g. Blanchard et al., 1995). RAMS tools like failure mode effects and criticality analysis (FMECA), fault tree analysis (FTA), and event tree analysis (ETA) are useful in the dimensioning of product characteristics and product support. As the demand for shorter delivery cycles increases, more effective and efficient work processes are more important than ever to examine factors affecting product performance, maintenance, and support. We believe that routines for integrating such assessment in the earlier phases of product development
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processes is important to gain better control of product LCC. To be able to sustain competition, to deliver a superior product, and to continue growing, companies need to focus on making the design process as effective and efficient as possible. The Gate Model introduced by Cooper (1990) is one method used to define routines and procedures, to control product development, to reduce risks in complex processes, and thus help create focus on the value creating activities in a value chain. In the Gate Model, a set of gates is assigned to various phases of a project. In each phase, a number of checkpoints and tasks are evaluated and approved before the project is allowed to enter the next phase. The idea is that by going through the checks, and by making sure the tasks are evaluated, the project risks should be better controlled and reduced. During design there are many interrelated processes and activities that are implemented for a purpose and lead to a common goal. The inputs to the work process are customer needs, wants and desires, and the output is the product and services produced. Sometimes companies experience problems with integrating design concepts and output from various groups, disciplines and work processes into the product to fit the customer requirements. If the different groups are focusing only on their own functions and do not try to integrate their solution into the solutions from other disciplines, the end result could be less than optimal. Integration of solutions needs to be done as early as possible in the design process. The overall product delivery process is composed of many sub-processes. If these sub-processes are considered as functions (or disciplines/groups), and there is competition between them because of result requirements to justify their existence, each of the functions will often attempt to optimise themselves to look the best in the eyes of the business management. However, it is important to realize that it is the overall goal that is important, and which everybody should work on to reach and to optimise together. This is a direct parallel to “systems thinking” in which the focus is not on optimising the pieces, but rather on the fit between the pieces of the system (Liker et al., 1995). We believe that “systems thinking” is important and valid both for work processes and for the product itself. It does not if a component/subsystem is designed to perfection if the rest of the system/product is not. After all, what the customer is primarily interested in is the functional performance of the product and the total product offered and delivered, not the individual components. Research methodology and approach The study was conducted in two phases; namely, a preliminary study and a main project phase. In the preliminary study we aimed to become acquainted with the employees, to understand the work processes involved in design and manufacturing, and to identify factors and areas that affect product design characteristics and service life performance. In the main project phase we selected some areas and work processes for a more detailed study.
The main goal and purpose of the study was to identify areas where the company should focus for improvements in respect to the products and work processes involved in product design, development, delivery, and support. One of the goals was to evaluate information sources and to identify information needs not covered in the company’s existing databases. Furthermore, we wanted to evaluate how RAMS and risk analysis can be integrated in work processes. The study also aimed to motivate and provoke a discussion within the company about the design process and related problem areas, and to make the employees involved aware of the issues and complexities involved. The project goals were accomplished by the use of interviews, surveys in the form of questionnaires, data collection and analysis, discussions, participation in projects and meetings, etc. To get a holistic view of the company we selected employees from all departments and groups to participate in the surveys. Strengths, weaknesses, opportunities, and threats (SWOT) analysis methodology was applied in both the preliminary and main study to organize and categorize information. The study can be characterized as action research methodology, where the researcher participates in the processes and operations under investigation (Westbrooke, 1995). Case study: study and analysis of design and manufacturing process The company observed in the study produces various types of flexible, advanced, integrated, and automated production systems based on advanced technology. The systems are powered by electrical motors and are controlled by advanced software solutions, electronics and sensors. Their customers are using the products in high-performance production lines where uptime is critical. Even though the company has not been able to design out all needs for maintenance, the products are very reliable, dependable and durable. Through an excellent supply and support network, their customers trust the company to provide necessary support when needed. However, if a production system fails unpredictably, the consequences can be very costly for the customer. Many of the customers therefore demand products which have documented and predictable service life performance, a high technical performance and reliability, are durable and dependable, comply with health, safety and environmental standards, and are cost effective. Normally the customer purchases a production system to fit into their production line from the industrial group’s closest regional office. If the regional office is not able to assist and resolve problems, the customer communicates with the manufacturing company directly. Products are categorized as standard products, customized products, and development products. The products are designed to last for 50,000 hours of continuous use. The owner will need spare parts and may also need to upgrade the product due to any weaknesses discovered and/or technological developments that increase product performance or maintenance effectiveness and efficiency.
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Work processes in design and manufacturing The employees are organized in functional departments and sub-groups according to specialization. Both the products and the work processes necessary to produce the products have evolved in advancement and complexity resulting in a higher demand on employee specialization. One of the results of this evolution is that fewer employees than before have a full understanding and overview of the complexity of the products and the work processes. As the customer’s demand improved products in respect to quality, reliability and performance, delivered with shorter lead-time and at lower costs, work process effectiveness and efficiency is becoming increasingly important. Standard product orders are handled directly by the production department, while projects involving customisation, new technical development or product improvements, are handled by the research and development department. The study indicates that some work processes are not properly defined, or have procedures, routines or checklists that are not followed or are not easy to follow. Even if many of the required procedures, routines and checklists are in place, time-pressure occasionally makes them difficult to follow. Procedures, routines, and checklists are used to coordinate and control the work process to ensure that the actual output meets the expectations (or is according to specifications and quality). The work processes need to be understood and formalized to maximize the output. It is important to consider the coordination among work processes to be able to achieve optimal results. Product reliability and maintainability characteristics are designed into the manufacturing and assembly specifications in the form of drawings, manufacturing and assembly procedures and methods, choice of materials, etc. The output from the engineering design stage is therefore the foundation for product reliability and quality. If too tight tolerances are given, or if the component is difficult to manufacture and assemble, errors may be introduced in manufacturing and assembly, causing reduction of the designed-in reliability and increased quality problems. However, to produce the drawing, the engineer may need input from the manufacturing department about critical inputs that may make the component difficult to make, which further down the line can influence quality and product RAMS. Many work process and product problems are caused by a lack of understanding and awareness of why things are done in the way they are done. Often, when people communicate, they talk about the same thing but use different terminology/language, or discuss different things using the same terminology. To avoid confusion and misunderstanding there must be focus on having the same understanding and on using the same and agreed-on terminology. There must be a common understanding of why things are done the way they are, and of the purpose of the activities. In this study, there are several indications of anomalies in perception between department managers and employees, and also between different departments. Focused training and
follow-up are important for understanding and awareness, and also affect motivation, attitudes and teamwork abilities. The training undertaken in this project has given positive responses with respect to this. In the training sessions given, the seminar started with a general introduction from one of the company managers, followed by a presentation of general theory explaining the background, foundation and basic philosophy of RAMS integration, which was followed by a relevant application. Throughout the seminars the participants were encouraged to comment on the issues presented and to participate in discussions. The result was a better understanding of the topic and, hopefully, more motivated employees.
Software systems, databases, and information sources The company uses advanced software systems for product design and analysis, for administration and management of related documentation and analysis, and for the production of their products. They also have in place many databases and information systems to manage customer feedback, complaints and resolution of customer product problems, quality assurance and control, field service reports, and information provision to customers with respect to product problem solutions, etc. Some of the employees complain that there are too many information sources and no easy accessible overviews and explanations of where to find and how to use the different kinds of information. Although there is an abundance of information available, it is often difficult to obtain useful, relevant information when needed. It was observed that many of the information systems were used for reactive and not proactive improvement purposes. As data and information accumulates, the data should be identified and trended to identify weaknesses and opportunities for improvement, and to avoid repeating mistakes. The databases can also be used as a source of information when solving similar problems, or during design and development of new products and models. There seems to be a lack of information system integration and holistic perspective of possible use. Some of the information systems are difficult to use and are error prone. Sometimes it is also difficult to access the databases. Common to many of them is that the information in them is of a qualitative format, which makes it difficult to search, filter and find information if needed. It also makes statistical analysis and trending in the worst cases impossible, and at best difficult, cumbersome and work intensive. More quantitative information is needed for producing better LCC analysis and availability estimates for standard products. Many of the information sources, and the information therein, are intended for product improvements and not so much for improvement of work processes. Improvement of products and work processes are intertwined and complementary activities, not mutually exclusive.
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Product development and testing The company develops products in an iterative and evolutionary process, partly as a result of attempts to remove or design out product weaknesses, partly as a consequence of advancements in technology, partly as a result of comparison with competitors, and partly as a result of customer and market demands. Many product development efforts are a result of product customisation efforts toward special user needs evolving from cooperation with customers and suppliers. The customer demands reliable, durable, and dependable products. As products become increasingly advanced, complex, and integrated, the number of ways they can fail increases as well. As changes or new technology are introduced to existing products and new products are developed, new possibilities for weaknesses, failures and errors are also introduced. It was observed that many projects had insufficient time to test all new changes and to optimise the design by designing prototypes using laboratory testing-facilities to improve maintainability, etc., before being completed and introduced to the customers. Training The company offers training programs for their employees and customers. All the company employees need to be trained in respect to design for maintenance issues and in utilization of new RAMS tools and methods. There was also observed a need for training of manufacturing and assembly personnel with respect to implementing new design solutions. Integration of RAMS and risk analysis in design work processes RAMS activity coordination and integration The company has realized that both their products and work processes involved in designing, manufacturing, installing and supporting the products, and the products themselves in parallel, have become increasingly advanced, complex and integrated. To stay competitive it is necessary to deliver products with documented quality, reliability, maintainability and competitive LCC. Therefore, a RAMS coordinator position was created in the company. Since a RAMS coordinator deals with product and work process improvement with respect to RAMS issues, it is a cross-functional and partly independent position. This reduces the focus on interdepartmental optimisation, and instead creates a holistic view on product and work process improvements. The coordinator is responsible for coordinating efforts focused on integrating RAMS into design work processes, development and use of RAMS tools and methods, utilization of information sources, data, and experience which can be used to improve product reliability and, not least, training of employees in respect to these issues. The goal is to systematize and formalize the design methodology in respect to RAMS, to focus on product and work process improvements, and to make the product performance more
predictable. When a product problem is identified, the goal is to find the root cause and prevent it from reoccurring. At least it should be possible to reduce the problem consequences by making the problem predictable and by including maintenance and support compensation activities. Efficient and effective use of the testing laboratory is also part of the RAMS coordinator’s responsibility. The goal is to be able to use the facility more proactively and interactively during design, to reduce design iterations and rework, to reduce cost and lead-time, to improve both reliability and maintainability, and hence downtime and costs for the customer. By creating the RAMS coordinator position, the company has managed to bring focus on the integration of RAMS and risk analysis in the work processes. RAMS tools and methods Central in the efforts of integrating RAMS into work processes is the development of a computerized design tool based on the FMECA methodology. FMECA is a powerful analysis method involving two elements of risk; namely, failure frequency and consequence. Sometimes the possibility for detecting the failure also is included. FMECA analysis concentrates on identification of the events and frequency resulting in failures and analysing their effects on the components and systems. Information about possible ways the product can fail and product weaknesses originate from experience, feedback from customers and suppliers, testing, analysis, spare part and warranty data, and project review reports, etc. If a failure mode is identified, its risk is predicted by estimation of failure frequency, consequence, and detectability. If the risk proves too high, efforts are initiated either to reduce frequency and/or consequence, or by increasing the detectability to make it possible to avoid the event, or at least to reduce the severity of the consequences. The analysis and design-out of the failure cause, or corrective action, has to be done in product design (Carter, 1997). The intention of the FMECA tool is to formalize and standardize design processes with respect to RAMS, to meet demands from customers in respect to documented reliability analysis, and to make it easier to identify product improvement opportunities. The computerized tool is now starting to be used actively in the design process. Although FMECA analysis has been performed in the company for many years, only recently have efforts been initiated to formalize and systematize the analysis process. The results from the analysis are gradually becoming popular and used more frequently. Such results provide a basis for decision making such as recommendations for preventive maintenance, spare parts and maintenance tools (both for commissioning and exploitation phase), documentation (including procedures, routines, and checklists for installation, failure diagnosis, maintenance, etc.), and LCC predictions. The analysis also serves as a basis to evaluate warranty considerations, maintenance programs, modifications and upgrading of existing products, customer training, and
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feedback to involved parties, etc. The vision is to be able to design out all product characteristics leading to unplanned corrective failures and warranty costs. Corrective or unplanned maintenance is needed when the product fails either intentionally, as sometimes is the chosen strategy for components that can fail but which are not critical, or unintentionally as a result of overload, wrong use, design errors, etc. The whole point is to improve product performance, reliability and predictability, reduce costs, increase profit margins, and thereby to increase product-related performance and customer satisfaction. RAMS information sources As mentioned above, there exist many possible sources of information that can be related to product and work process improvements. The problem is to identify and route the interesting information to RAMS improvement activities, and to the RAMS tools and methods. To make efficient and effective use of the information sources, demands must be specified with respect to use and needs, information type and format, how it is to be accessed and by whom, how the information is to be routed to fulfill the various purposes, etc. In this study, several new ways to use databases and information sources to improve products and work processes were identified. For example, many concrete information system improvement possibilities are identified in the mapping of the RAMS information flow. The service reports have been improved somewhat as a result of suggestions from the employees and new information uses. This can be considered an added benefit of the RAMS coordinator’s efforts of identifying information sources with information relevant to product improvement. Even though much of the information is focused on the products, often the root cause of a product problem recorded can be traced back to work processes, activities, procedures, routines, or checklists in use during delivery of the products. This information must therefore be used and discussed with improvement of both processes and product in mind. The company has used an intranet for some years for providing easy access to information sources, and has recently also started to use the Internet to facilitate easy access to information and distribution of information. It is believed that integration of the Internet and intranet applications with the Stage Gate model can support and accelerate new product development (see Howe et al., 2000). Work process management and control: the Stage Gate model Recently, the company has started to use a modified Stage Gate model to improve project management and control, in parallel with traditional project tools and methods. In this model, projects are divided into sequential stages, or phases, with go/no-go gates at the end of the phase. The purpose of the gates is to avoid a project entering the next phase before the goals of the first phase are accomplished. The gates provide an opportunity to review what has been done
to date and to adjust performance gaps, or to stop the project if the results are not as anticipated and too much money has been spent. In this way the project can become easier to control and business risks reduced. Recent developments in information and communication systems has made it possible to perform design and manufacturing processes simultaneously, and hence more effective and efficient, resulting in reduced lead-time and costs (Yazdani and Holmes, 1999). To improve products, RAMS-related activities need to be performed and evaluated as early as possible, preferably already in the specification phase. As mentioned previously, the foundation for a reliable product is laid in the design phase. Product reliability cannot be improved in the later stages of production. In these design implementation (manufacturing, assembly, etc.) stages there are many opportunities to reduce the inherent and designed-in reliability by not conforming to specifications given. The introduction of the Stage Gate model results in that representatives of later stage functions, or work processes, have the possibility to influence the design at a much earlier stage through the gate reviews. This also forces, and gives an opportunity for, inter-disciplinary cooperation and coordination, which is both recommended and, in many cases, required. As Pahl and Grote (1996) point out “teamwork and individual work are complementary in an integrated and interdisciplinary development process”. Furthermore, a risk analysis based on various factors such as economical, environmental, support, planning, etc., thought to influence project feasibility, success and results, is performed at the beginning of the project. This analysis is updated before the gate reviews and functions as a basis for decision making. To ensure that RAMS issues are considered at various design and manufacturing stages, the company has started to use a RAMS activity template to define activities and tasks to be performed at each project stage.
RAMS activity template The template is meant to include RAMS gate activities to check and control if the goals have been reached at the various project stages. RAMS goals must reflect real customer needs, available technology, and customer willingness to pay. They also have to reflect what is necessary with respect to market competitiveness. It is important to consider the coordination between work processes to be able to get an optimal result. The FMECA tool is used in all project meetings and is used as a checklist to ensure that identified improvement actions identified are implemented and followed up. The end result is that the design process becomes even more concurrent and dynamic, involving increased informal and formal information exchange. This has a positive effect on employee motivation and increases the understanding of how their contribution fits into the big picture. The holistic view should be that all activities contribute to customer satisfaction.
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RAMS training Many work process and product problems are caused by unawareness and a lack of understanding of purpose and goals. Part of the RAMS coordinator’s job is to motivate the various employees to take part in improving the products and to use the tools available. As such, focused training and awareness-creation efforts and coordination are of the utmost importance and can have a tremendous impact – both with respect to improving understanding and knowledge of the issues involved, to improve motivation, attitude, teamwork abilities, and to create a holistic view of the products and work processes. Part of this is the effect of gaining a common understanding of goals, focus areas, work processes, problems and, finally, but perhaps most importantly, customer satisfaction. With better training, the employees should be able to design for RAMS at an earlier design phase and reduce the number of design iterations necessary to produce a final and acceptable design. Project risk may also be reduced. To improve the design in respect to reliability and maintainability, the employees need to be trained in RAMS tools, methods and terminology. All employees need a similar understanding of what design for RAMS means and to use the same terminology. During the study, several courses were arranged for the employees to create awareness. Figure 3 depicts a general dynamic product development process controlled by the Stage Gate model, together with support activities to integrate RAMS in the design process. As shown in the figure, the product development processes are started simultaneously. To be able to include results and information from later stage work processes early in the product development process, information sources and support activities must be available and facilitated. Furthermore, facilities like Internet, intranet, video conferencing, etc., need to be in place for continuous communication with customers, regional offices and suppliers. In simultaneous processes like these, the use of cross-functional and multi-skilled integrated teams and facilitation for intensive communication between work processes involved (depicted by many short, vertical, and bi-directional arrows in Figure 3) are of the utmost importance to coordinate and control the process. The participants also require an understanding and knowledge of the work process and a holistic view of the goals. Discussion Customer feedback is important for having good input data for reliability, maintainability, LCC calculations, for product improvements, customer satisfaction measurements, and for sales of new products and services. Normally, it is difficult to get systematic feedback from customers. However, since many of the customers come back to buy new products, they also have an interest in the manufacturer improving the product’s characteristics. Manufacturers and customers are mutually dependent on each other – the manufacturer needs feedback from customers on product behaviour to improve
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Figure 3. Dynamic product development process including Stage Gate work process control and proactive, reactive and interactive partner communication
the next product generation or version, while the product user may need spare parts, expert advice and help in maintaining the product, training, and documentation, etc. Somehow the manufacturer and customer have to create a relationship to take advantage of each other’s information, knowledge and intelligence (Liyanage et al., 2001). The recent development of communication and information systems has made it much easier, quicker, and simpler to retrieve information directly from customers and products, to provide remote monitoring and support, to interact with customers, suppliers, and service personnel at remote locations, and to increase the speed of product development and delivery. Product design characteristics and built-in reliability are dependent on how the products are to be manufactured, assembled and installed. If, for example, a component is difficult to design and manufacture, there is a higher chance of making mistakes, which may result in the component being weaker than intended or having a damaging/detrimental effect on other components, etc. It is, therefore, important to consider how the product design is to be implemented in manufacturing and assembly to avoid errors caused by unnecessarily complicated operations and tasks. Therefore, the manufacturer needs to have in place effective and efficient routines for integrating RAMS in the design and manufacturing processes, for obtaining data and information from the customers throughout the product service life, and to cooperate with the customers in maintenance and support planning from the early concept phase to the end of the product service life (see also Markeset and Kumar (2003)).
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Figure 4. An illustration of components of RAMS integration process
Some of the pieces of the puzzle related to integration of RAMS and risk analysis discussed in this paper are shown in Figure 4. Concluding remarks The company studied is still in an early phase of integration of RAMS in its work processes related to design. This is being implemented gradually and phase-wise with feedback to monitor the effects. By integrating RAMS in the work processes involved in delivering, installing, and supporting products, it is believed that business risk will be reduced. The company sees the need for implementing training programs with focus on integration of RAMS considerations in the design phase in combination with risk and LCC analysis. A need for effective and efficient control of the information flow and the work processes involved in the design, manufacture, delivery, commissioning, and after-sales support was identified as critical to successful integration of RAMS and risk analysis in work processes. The company also has initiated measures to coordinate RAMS activities being implemented in different sections and departments. We believe that successful integration of RAMS will provide the company with a competitive edge and the successful implementation will mainly depend on the company’s ability to create awareness and understanding of the issues
involved. The employees need to be trained to use the appropriate tools and methods, and an infrastructure needs to be in place to make these tools and information sources available when needed. It is important to consider the coordination between work processes, tools, and information sources to be able to get an optimal result. Procedures, routines, and checklists need to be in place where they are needed; they need to be clear, concise, concrete, and precise to be efficient and effective. They also need to be updated regularly to reflect changes in needs and uses. However, one must be careful not to introduce too much bureaucracy into the organization, as it tends to kill creativity and innovation. References Barlow, R.E. and Proschan, F. (1981), Statistical Theory of Reliability and Life Testing, To Begin With, Silver Spring, MD. Blanchard, B.S. and Fabrycky, W.J. (1998), Systems Engineering and Analysis, 3rd ed., Prentice-Hall, Upper Saddle River, NJ. Blanchard, B.S., Verma, D. and Peterson, E.L. (1995), Maintainability: A Key to Effective Serviceability and Maintenance Management, John Wiley & Sons, New York, NY. Carter, A.D.S. (1997), Mechanical Reliability and Design, Macmillian, Basingstoke. Cooper, R.G. (1990), “Stage Gate systems: a new tool for managing new products”, Business Horizons, May-June, pp. 44-54. Dhillon, B.S. (1999), Engineering Maintainability: How to Design for Reliability and Easy Maintenance, Gulf Publishing, Houston, TX. Goffin, K. (1998), “Evaluating customer support during new product development: an explorative study”, J Prod Innov Manag, Vol. 15, pp. 42-56. Goffin, K. and New, C. (2001), “Customer support and new product development – an explorative study”, International Journal of Operation & Production Management, Vol. 21 No. 3, pp. 275-301. Howe, V., Mathieu, R.G. and Parker, J. (2000), “Supporting new product development with the Internet”, Industrial Management & Data Systems, Vol. 100 No. 6, pp. 277-84. Kumar, D., Klefsjo¨, B. and Kumar, U. (1992), “Reliability analysis of power transmission cables of electric loaders using the proportional hazard model”, Reliability Engineering and System Safety, Vol. 37, pp. 217-22. Kumar, U. (1990), “Reliability analysis of load-haul-dump machines”, PhD thesis, 1990:88D, Lulea˚ University of Technology, Lulea˚. Liker, J.K., Ettlie, J.E. and Ward, A.C. (1995), “Managing technology systematically: common themes”, in Liker, J.K., Ettlie, J.E. and Campbell, J.C. (Eds), Engineered in Japan: Japanese Technology Management Practices, Oxford University Press, New York, NY. Liyanage, J.P., Markeset, T. and Kumar, U. (2001), “On the knowledge driven performance management grounded in process intelligence: with applications to asset maintenance and product development”, paper presented at IMSIO2: 2nd Conference on Intelligent Management System in Operations, Salford, 3-4 July. Markeset, T. and Kumar, U. (2001), “R&M and risk analysis tools in product design to reduce life-cycle cost and improve product attractiveness”, in Proceedings of The Annual Reliability and Maintainability Symposium, 22-25 January, Philadelphia, PA, pp. 116-122.
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Markeset, T. and Kumar, U. (2002), “Design and development of product support and maintenance concepts for industrial systems”, paper presented at the IFRIMmmm 2002, Maintenance, Management and Modelling Conference, Va¨xjo¨, 6-8 May. Markeset, T. and Kumar, U. (2003), “Integration of RAMS information in design processes – a case study”, paper presented at the 2003 Annual Reliability and Maintainability Symposium, 20-24 January, Tampa, FL. Moss, M.A. (1985), Designing for Minimal Maintenance Expense, Marcel Dekker Inc., New York, NY. Pahl, G. and Beitz, W. (1996), in Wallace, K. (Ed.), Engineering Design: A Systematic Approach, 2nd ed., Springer, Berlin. Pahl, G. and Grote, K.H. (1996), “Interdisciplinary design: knowledge and ability needed”, Interdisciplinary Science Reviews, Vol. 21 No. 4, pp. 292-303. Sandberg, A. and Stro¨mberg, U. (1999), “Gripen: with focus on availability performance and life support cost over the product life cycle”, Journal of Quality in Maintenance Engineering, Vol. 5 No. 4, pp. 325-34. Thompson, G. (1999), Improving Maintainability and Reliability through Design, Professional Engineering Publishing, Bury St Edmunds. Van Baaren, R.J. and Smit, K. (1998), “A systems approach towards design for RAMS/LCC: lessons learned from cases within aerospace, chemical processes, and automotive industry”, Proceedings of the 8th Annual International Cost Engineering Congress, April, Vancouver, pp. 49-55. Voland, G. (1999), Engineering by Design, Addison-Wesley, Reading, MA. Warburton, D., Strutt, J.E. and Allsopp, K. (1998), “Reliability prediction procedures for mechanical components at the design stage”, Proc Instn Mech Engrs, Vol. 212 Part E, pp. 213-24. Westbrooke, R. (1995), “Action research: a new paradigm for research in production and operations management”, International Journal of Operations & Production Management, Vol. 15 No. 12, pp. 6-20. Yazdani, B. and Holmes, C. (1999), “Four models of design definition: sequential, design centred, concurrent and dynamic”, Journal of Engineering Design, Vol. 10 No. 1, pp. 25-37.
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An analysis of economics of investing in IT in the maintenance department
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An empirical study in a cement factory in Tanzania E.A.M. Mjema and A.M. Mweta Department of Engineering Management and Entrepreneurship, University of Dar es Salaam, Dar es Salaam, Tanzania Keywords Maintenance, Computers, Quality Abstract The main objective of this study was to analyse the economics of introducing IT in the maintenance department. The economics in this case was determined by conducting a quantitative analysis on the reduction of operational costs, on increase in productivity and on quality improvement. A comparison was made to analyse company performance in the maintenance before and after the introduction of IT in the maintenance department. The analysis shows that there were reductions of operational and inventory holding costs. Likewise, it was shown that there was also improvement in product quality and productivity.
Practical implication There are very few researches, which are aimed at showing the economics of investing in information technology (IT) in the maintenance department. Many companies introduced IT in the maintenance department from a technological point of view on aspiration of increasing the efficiency of job performance. In addition, several empirical researches established that there does not exist a positive relationship between the size of the investment in IT and the productivity or profitability of the company. In some companies it was even noted a negative correlation between the volume of investment in IT and the productivity of the enterprise. This situation is termed as “productivity paradox of the information technology” (Stickel, 1997). The result of this research work has shown a contrary, that there has been an increase in productivity, reduction of downtime and reduction of the overall maintenance cost by introducing IT in the maintenance department. Introduction Economic and social development of any society depends on the performance of the production and infrastructure facilities invested within the society. The facilities can be a manufacturing enterprise (e.g. a textile mill, cement factory, etc.); an infrastructure facility (e.g. road, a highway, airport, etc.); a public utility (e.g. sewage system, telecommunication
Journal of Quality in Maintenance Engineering Vol. 9 No. 4, 2003 pp. 411-435 q MCB UP Limited 1355-2511 DOI 10.1108/13552510310503259
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systems, etc.) or any other structures like dispensaries, health care centres, hospitals, schools, etc. These facilities cannot provide the intended services to the expected level if they are not taken care of. In other words, the performance of these facilities will depend on the level and efficiency of maintenance provided by the concerned authority. In the production sector, poor maintenance management of production equipment is one of the key factors which resulted in low capacity utilisation in many Tanzanian industries. A study conducted in the late 1990s shows that there is a general lack of awareness of the economic benefits resulting from well-maintained equipment and facilities (Bavu et al., 1997). In the effort to improve the capacity utilisation and realise the benefits of sound maintenance, some few industries in Tanzania have decided to introduce IT in their maintenance departments. Among such industries, which so far have introduced IT in maintenance departments, are Tanzania Portland Cement Company Limited (TPCC) and Coca-Cola Kwanza Bottlers Limited. It is anticipated that applying computers in a maintenance department will improve the maintenance system and hence increase the capacity utilisation. In order to meet the challenges of global economy and improve the chronic problem of low capacity utilisation, the Tanzanian industries are required to reduce operational and maintenance costs, to improve productivity, and to improve products quality. The production of high-quality products is normally supported by a well-managed maintenance system (Mjema and Kundi, 1996). The question to be asked is: “Has the introduction of IT in a maintenance department helped the companies to achieve better competitiveness?”. A difficult hurdle for answering this question is that this type of investment yields results over time, and seldom in the short-run. Likewise, it is difficult to quantify and calculate the tangible benefits of IT when it is used for strategic purposes (Connolly, 1999). IT provides competitive advantage if it enables a firm to either reduce its cost structure or differentiate its products and services. Competitive advantage results if a firm gains an advantage, such as increased market share or information asymmetries, over its competitors (Ohmae, 1992). The competitive advantage is a function of the ability of a firm’s workforce to exploit the capabilities of IT creatively to develop new products or services. IT must create structural differences if it is to provide sustainable competitive advantage (Porter, 1985). Competitive advantage derived from IT will occur only when IT improves an organisation’s primary business functions, creates value-adding experience that enhances customer services and focuses on changing demand patterns and use (Adcock et al., 1993). Regarding the concept of quality, for a company to achieve successes in the quality management it needs a better information system for reporting the changes in the production parameters in the shortest possible time. Therefore,
IT contributes greatly in the success of the quality programs. The quality of the product can be looked at from two perspectives: first is the producer’s perspective, and second is the customer’s perspective. From the producer’s perspective quality is achieved if there is conformance to specifications. Conformance to the specification is influenced by the quality of production processes, which is influenced by maintenance. A solution to meet the producer’s perspective of quality is to have an efficient preventive maintenance system, which can minimise equipment breakdown and avoid product defects. But with the rapid increase of industrial automation, this has stimulated the search for a more effective preventive maintenance program. To achieve this, introduction of IT in the maintenance department seems to be a clear solution. It is therefore expected that the use of IT in the maintenance department can help in quality improvement programs. However, there are some prerequisites for an economical introduction of an IT system into a maintenance management system. The prerequisites were identified as: defining precisely the objectives of an enterprise which can specify the needs of an enterprise and the requirements for an IT system for the concerned enterprise (Mjema and Kundi, 1996). Likewise, IT employs an automatic data processing system to schedule maintenance work and report maintenance data for management information and control. With automatically scheduled preventive maintenance activities, there is a great reduction in emergency repairs, which increases equipment availability, improves the good working condition of the equipment, and improves the quality of the production process and in totality improves the quality of the products. Pintelon et al. (1999) present some case experiences, whereby IT has been effectively implemented in the areas, such as in the management of work orders, expert systems for failure diagnosis of electronic equipment, and in configuration-based logistic support (CBLS) in a virtual enterprise. The majority of modern computerised maintenance management systems (CMMS) have in-built maintenance material management systems. Materials used and their costs are helpful for keeping inventory up to date and charging materials to each piece of equipment. Having the material identified by its tracking number in the inventory control system is essential for documenting proper part usage and tracking and bill of material building (Winston, 2003). The CMMS can be used to control maintenance tasks such as the addition of fluids, the changing of filters, the tightening of fittings, bearing inspection, lubrication, and plant and equipment inspections can be documented and managed using the system. Another application of CMMS is in periodic inspections. Leaks, fluid contamination, wear, condition of seals, vibration and noise, and the condition of cables, wires, lights, and safety devices can be recorded (Veloz, 1998).
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Gould (1998) commented that the IT, which is the main essence behind today’s CMMS, is truly beyond after-the-fact score keeping. Properly deployed CMMS make information actionable for better maintenance decisions in real-time. Using the CMMS enables the maintenance personnel to pull the failure records of all the motor drives in the factory, for example, and graphically display their operational and failure trends, which leads to dynamic and predictive maintenance management. The most frequently cited benefit of computerisation is lower cost (Mensching and Adams, 1991; Gupta, 1994; Lamendola, 1999). This is due to the fact that either the same work is done with less effort or because the same work is done in less time. Either way, the computer cuts the cost per unit of work accomplished, saving the company money. CMMSs help keep everything up and running as inexpensively as possible where downtime is reflected directly in product costs (Gould, 1998). Lamendola (1999) shows that the modern CMMS have very powerful features. The features include accounting, trending, and predicting functions. The CMMS can be tailored to collect data to what the end user needs. For example, if one wants to know how many minutes of downtime the plant air motors suffer each month due to clogged air filters, one can set the system up to tell you that. Likewise, if one wants to compare that information to what happened in previous months it is possible to do that. That kind of powerful feature paved the way for advanced trending and prediction, based on real data. It also paved the way for making custom reports for up-line management. Pintelon et al. (1999) show the opportunity offered by IT in capturing data such as information on equipment failure and repair characteristics, and on the corresponding costs which can be used in strategic (i.e. long-term) planning, in tactical (i.e. medium-term) planning and on operational (i.e. short-term) planning. Through proper application of IT the maintenance department can get direct information from the manufacturers of the equipment on important maintenance data. For example, PSDI Maximo users have electronic access to maintenance and reliability benchmarking data from HSB Reliability Technologies, a maintenance engineering consulting company. Users can automatically load preventive maintenance tasks directly into their Maximo maintenance management systems. The one-click access to HSB’s exclusive reliability-centred maintenance information is integral to achieving optimal equipment performance and reducing the system’s implementation time (Gould, 1998). Computerisation also beneficially affects maintenance work itself. Using the computer as a job-planning tool improves the efficiency of the planner, reduces errors, and can even streamline the maintenance work itself. Standard job plans can be stored on a computer-desk and easily modified for the specific circumstances of the job. The computer cuts the planner’s time
and, because the standard plan has all the parts and tools identified for successfully performing the maintenance job, ensures that the job is done right and with a minimum backtracking to get forgotten items. Modern CMMS are using open database compliance (ODBC), which allows quantum leaps in maintenance management and performance and file standardization. The file standardisation paved the way for other developments, such as advanced analysis (Lamendola, 1999). The computer can also be used to determine the most cost-effective preventive maintenance interval, to manage inventories of spare parts and to reduce the expense of training new personnel. In short, the objective here is to reduce the following cost elements as far as computerisation of maintenance work is concerned: . inventory control costs; . downtime costs; and . labour costs. Sometimes the machine fails because it is running out of spec during the production run. Such poor performance would not have occurred if proper maintenance was performed on the equipment and equipment utilization was being tracked. The trend in modern maintenance IT systems is to integrate maintenance systems to enterprise resource planning (ERP) and other business systems. This integration creates “synergy” of the whole production system. For instance, the integration lets maintenance users transfer spare part transactions and update work orders with part data and costs contained in the ERP inventory module, or equipment usage data, which is critical for the preventive maintenance (PM) schedules generated by the CMMS, can be automatically updated using the equipment run times in the ERP shop floor control module (Gould, 1998). If computers are properly managed, they substantially increase productivity (Mensching and Adams, 1991). Productivity is generally determined by considering the relationship between input and the output. The inputs to be considered in this context are all the costs and resources utilised in the maintenance of the equipment. These include annual IT costs, labour costs, downtime costs, materials and spare parts costs used in the maintenance of the equipment. However, Pintelon et al. (1999) caution that buying highly-sophisticated IT hardware and software is not the complete answer; IT is only an enabler of changes. Therefore, to benefit from the implementation of IT, the better utilisation of IT resources should be accompanied by positive changes in an organisation. The percentage contribution of the maintenance activities towards total production can be determined as output. Both the input and output data before and after computerisation of a maintenance department have to be collected.
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These data can be used to determine the productivity before and after computerisation of a maintenance department. Now knowing that many industries have taken efforts in introducing IT in their maintenance departments, the problem to be solved is: have they achieved any cost reduction, an improvement in quality or an increase of productivity by introducing IT? Objective The objective of this research is to substantiate quantitatively the impact of introducing IT in the maintenance department with regard to the reduction of operational cost, improvement of the quality of products and improvement of productivity. Research method A quantitative analysis of the data obtained in this research work is done in respect to the amount of downtime of the equipment and an analysis of the maintenance cost before and after the computerisation of the maintenance department. The method used to collect the data for analysis involved the questionnaire (see Appendix) in which the researchers collected quantitative data regarding the downtime, and the cost involved in the introduction of IT in the maintenance department. In addition, the researchers used documentary review, whereby the archival records of the company were visited. Likewise, direct interviews were used to collect the opinions of the interviewees and explanations on some of the information, which was not clear from the data collected. Description of case study area TPCC, is located about 30 kilometres from Dar es Salaam city centre. It has some 30 years’ experience of cement manufacturing and distribution throughout East Africa. Formerly, TPCC was a public company, but now it is owned jointly with Scancem International, being a cement-producing company in Europe. From 1985, a substantial rehabilitation program started to modernise equipment and to upgrade machinery. The modernisation program was not only in the fabric of the plant, but also in such elements as high-calibre management, preventive maintenance, computerisation, effective distribution and quality assurance. Cement production process at TPCC TPCC manufactures cement from limestone and clay that are quarried close to the plant. A fleet of dump trucks transports the raw material to one of the two crushers. It is reduced to the necessary fineness for feeding to one of three kilns by a combination of crushing and milling. Prior to entering a kiln, material passes through a pre-heater consisting of a series of cyclones heated by the
kiln’s hot exhaust gases. The material is dried and partially calcimined before entering the kiln, aiding fuel efficiency. At the final stage of the production process the cement clinker product is mixed with controlled quantities of gypsum and ground into cement. Maintenance department at TPCC The maintenance department at TPCC is under the leadership of a deputy maintenance manager. The maintenance activities of the whole plant fall under three departmental managers; namely, engineering manager, project manager and production manager. The deputy maintenance manager undertakes the maintenance planning and control, prepares and defines the annual maintenance objectives, co-ordinates and controls all the maintenance and production activities of the plant, which fall under the departmental managers, and he prepares the annual maintenance budget. The engineering manager is the head of the three workshops, which are; (1) mechanical; (2) electrical; and (3) instrument.. These three workshops receive work orders from the preventive maintenance unit. The work orders range from preventive to breakdown maintenance. The project manager undertakes every new project introduced in the plant. Since new projects do not occur every day, the project manager is assigned the preventive maintenance unit activities. These activities include preparation of the master maintenance schedule and issuing of work orders to three workshops. Preventive maintenance unit personnel carry out some of the work orders. The production manager has dual activities: apart from leading the production crew and all its activities to meet the production targets, he also leads a small group of maintenance personnel attached to him to meet emergence repair or preventive maintenance detected under regular production without depending on assistance from either of the three workshops or the preventive maintenance unit. In the effort to improve the level of plant’s maintenance activities and to ensure capacity utilisation, the maintenance department introduced a computerised maintenance management system known as SMS in 1991. However, the SMS was not compatible for the year 2000, therefore the management introduced a new computerised maintenance management system known as MP2. The MP2 system is operated and controlled by the preventive maintenance unit (PMU). The PMU is linked through a computer network with the engineering department, computer department, processing department and
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purchase department. The purchase department controls procurements of materials and spare parts for the plant. Benefits of IT in maintenance The benefits of IT can be classified as cost saving or cost avoidance, both of which are usually quantifiable or tangible. Intangible benefits have quality features, which are difficult to quantify. The benefits of IT in the maintenance department can also be expressed in terms of cost-displacement approach. In cost-displacement approach, the savings, in money or time, are accrued by making people more productive. For example, a word-processor can help a secretary type more pages in less time. In some cases, it is possible to actually identify the money that is saved (i.e. hard dollar saving). In addition, the introduction of IT increases efficiency; this efficiency gain is normally associated with cost reduction. Hard dollar savings do not always imply cutbacks; however, “cost avoidance” benefits soccur when the efficiency gains allow one to do more with the same resources. For example, a word-processor may allow a business to grow without hiring more secretaries. Therefore, for the case of maintenance activities, typists can produce more work orders by using maintenance management information system (MMIS), and hence lowering costs. Nowadays MMIS offers more opportunities such as decision-making capabilities (e.g. work order planning), spare parts management, and the management of communication between corporate (e.g. ERP) and shop-floor systems (Pintelon et al., 1999). The research model The model used in this study shows the relationship between the computerised maintenance management system and the achievements in services and the performance (see Figure 1). The parameters associated with the performance are productivity, cost reduction and quality. According to the model, each performance parameter depends on different variables:
Figure 1. A descriptive model for a computerised maintenance management
. .
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the productivity depends on the output/input ratio; quality as far as maintenance is concerned depends on product specifications, availability and quality of the production process; and cost reduction parameter focuses in maintenance costs, downtime costs and inventories costs.
Proper and effective maintenance of the plant and equipment would result in minimising maintenance costs and reduces frequency of equipment breakdowns, thus improving overall plant productivity. Cost reduction implies savings in the cost of production and distribution through the elimination of wastes and inefficiency. In other words, cost reduction means reduction in unit costs and does not necessarily imply reduction in total expenditure, and it may involve increase in expenditure (Gupta, 1994). For example, a firm may spend more on research and development to improve product design so as to reduce unit cost of production. In this context, the TPCC incurred cost to purchase PCs, software and training of staff for the computerisation of the maintenance department with the purpose of reducing cost in the following variables: . maintenance costs (labour, job planning, training, etc.); . inventory costs; and . downtime costs. Reduction of labour costs A reduction in labour costs can be achieved through better machine loading, reduction in batch frequency, work simplification, training and motivation of workers, as well as the provision of better working facilities. Therefore, the computerisation of the maintenance department can be considered as a method for providing better working facilities with the objective of work simplification. The computerisation of the maintenance department simplifies the following types of work: . Job planning. The computer simplifies the process of job planning significantly. First, if a standard job plan already exists, the plan can be retrieved and tailored to the specific task with minimal effort. Such standard plans would identify parts, tools and manpower requirements, as well as define the work to be done, eliminating the guesswork and possible errors of writing a plan from scratch. Second, if a new job plan must be developed, the planner can access all the information she/he needs from the various computer-stored files; equipment parts lists and maintenance histories; parts and tools inventory and location data and personnel records concerning the skills and eligibility. Therefore, using a computer has saved the planner’s time and thus reducing costs.
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Personnel record keeping. Personnel records are easily maintained as a computer database, similar to an inventory system. Up-to-date records on all maintenance staff can quickly be requested by a job planner to determine which employees have certain requisite skills, familiarity with particular equipment or are eligible for overtime. The files can also be expanded to track the time worked by the employee, and, in conjunction with salary data, can provide cost figures for input to a detailed job-cost accounting system. Training. The computer can function as an iterative learning tool, providing detailed maintenance training for new employees, updates and refreshers on new equipment and maintenance techniques for current employees. The training is self-paced, iterative and designed to keep the employee involved and interested. The computer-aided instruction is more efficient than a class with an instructor, because it can be used at any time for any number of students and the information is retained longer than if the employee were merely given a book to read on the subject. The objective of training is to make an employee learn. This learning may be defined as the technological changes that lower cost as a result of experience (Gupta, 1994).
Reduction of inventory costs Inventories of equipment, parts and materials in stores are easily maintained in a computer database. Equipment records can contain all data about machines, including parts lists and even maintenance records, making detailed equipment information readily accessible to authorised computer or terminal devices throughout the facility. Parts and stores inventory system, track volumes on hand, locations, consumption and shrinkage, reorder points and unit costs. The inventory system can even be used to automatically trigger reorder and to maintain parts lists and manufacturers of acceptable substitute items. By computerisation of the inventory system it is expected to reduce the ordering costs and holding costs. Therefore, both questionnaire and data observation approaches were used to find out if, after computerisation of the inventory control system, the ordering and the holding costs have been reduced. Reduction of downtime costs Reduction of downtime cost can be achieved by improving the working condition of the production equipment, which, in return, reduces the number of breakdowns. The lower the rate of breakdowns the lesser is the downtime. Computerisation of the maintenance management activities improves the quality of equipment maintenance, which improves the working condition of the equipment. The work order process flow is the best method to be adopted to
trace out how computerisation of the preventive maintenance schedule could reduce the downtime when compared with the manually-operated preventive maintenance schedule. Productivity improvement Productivity refers to the physical relationship between the quantity produced (output) and the quantity of resources used in the course of production (input). Productivity measures the efficiency of the production system. Higher productivity means producing more from a given amount of inputs or producing a given amount with lesser inputs (Gupta, 1994). Productivity can be either at the level of a plant or at the macro level. In this research the productivity was analysed at the plant level. An increase in productivity means an increase in output that is proportionately greater than an increase in inputs. Productivity may be measured either on aggregate basis or on individual basis. On aggregate basis output is compared with the input factors taken together. This is known as total productivity: Total productivity index ¼ Total output=Total input: On an individual basis, output is compared with any of the input factors and this is called partial productivity or factor productivity. Because productivity is the outcome of many input factors, this study was focused on maintenance productivity. The first consideration was the maintenance management costs with IT-related inputs and the second step considered maintenance management costs without IT inputs. In the first step, the maintenance productivity considered the following input costs: . maintenance costs; . labour costs; and . annual IT maintenance management costs. The costs invested for this purpose, are distributed as annual invested costs under the following formula (Grant et al., 1982): A ¼ PðA=P; i%; nÞ where: A
¼ annual invested costs;
P
¼ total initial costs invested for IT project in maintenance department;
i% ¼ rate of return; n
¼ time in years; and
A/P ¼ capital recovery factor.
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In the second step, the maintenance productivity without IT maintenance management cost was calculated with the following inputs costs: . maintenance costs; . labour costs; and . rehabilitation in annuity costs. In the case study area, rehabilitation investment program started in 1984/1985 for the purpose of rehabilitating the production equipment in order to improve productivity. These rehabilitation costs are also distributed as annual invested costs under the same formula as mentioned above: A ¼ PðA=P; i%; nÞ where: A
¼ annual invested costs;
P
¼ total initial costs invested for rehabilitation program;
i% ¼ rate of return; n
¼ time in years; and
A/P ¼ capital recovery factor. In the effort to find out the influence of maintenance on the productivity of the company, the questionnaire approach was used to collect productivity data from the respondents. This productivity information was compared with the data collected by observation approach. From the input and output data collected, the productivity before and after computerisation were calculated and compared with the results found from the questionnaire approach. Because total production output is affected by many factors, it was agreed among the main stakeholders that maintenance contributes to about 30 per cent of total output. Quality improvement The modern concept of total quality management emphasises that quality control is a responsibility to be shared by all people in an organisation. The maintenance function acts in a supporting role to keep equipment operating effectively to maintain quality standards as well as to maintain the quantitative and cost standards of the output. The traditional definition of quality is the conformance to specifications. The maintenance department has a target of keeping the equipment in good condition to maintain the standard of workmanship which, in turn, conform to specifications which, as a result, improves quality of the product. The product design specifications should be achieved at the end of the production process in order to minimise scraps as well as defective
products. The failure of the equipment generally affects the product specifications. Therefore, the task in this study was to look at quality from this point of view. The quality of the production process is a variable, which is sometimes referred to as producibility or manufacturability. It measures the extent to which the product design can be readily produced with the facilities and processes available to the operating forces (Juran and Gryan, 1998). If the facilities are not properly maintained to achieve the highest working condition level this shall result in: . product faults due to faulted equipment; and . increase in work-in-progress costs, e.g. costs of wasted raw materials and average processing costs. Research results Cost of implementation of IT at TPCC There is no common agreement on what constitute an IT investment, and whether IT investment is a capital investment or an expenditure (Weill, 1991; Bacon, 1992). Weill and Olson (1989) suggest that the definition on IT investment should be as broad as possible to encompass all IT-related expenditures, such as people, training, documentation, consulting, external services, equipment, software, networks and communications. However, in this research work it was only possible to retrieve data for purchase and installation of IT at TPCC. TPCC started the computerization of the maintenance department in the year 1991. From 1991 to 1997, the computer software used was known as SMS, which was found to be not compliant to the millennium bug (Y2K problem). Therefore, in 1998, they installed new software MP2 that was Y2K compliant. The cost for purchase and installation of the SMS system in 1991 was not readily available, since it was installed under the assistance of Scancem International Experts as part of general contract to rehabilitate TPCC. The cost for the purchase and installation of the MP2 system in 1998 was Tshs 33,634,329/= about US$ 50,000 (at that time). Cost reduction after the implementation of IT Regarding the reduction of cost of maintenance, 86 per cent of the respondents agreed that using computers, more work orders could be produced and this reduces cost. Of these respondents, 58 per cent recommended that over 50 per cent of cost reduction have been achieved if compared to manual work orders production. Likewise, 86 per cent of the respondents felt that by using computers the task of job planning has been reduced by 31-50 per cent. After having the responses from the questionnaire, the researchers made a documentary review of the maintenance cost data for the period 1984-1991 before computerisation and between 1994-1999 after computerisation. The results are as depicted in Tables I and II, respectively. The cost of maintenance
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before computerisation are deceiving to be very low compared to costs after computerisation. However, one should note that the Tanzanian currency (Tshs.) is not a stable currency; the increase in the costs, for example, in the year 1995 and 1996 could have been caused by devaluation of the Tanzanian shilling. To avoid this problem the researchers decided to convert the currency to equivalent US dollar value at that period. The next reason in explaining why the cost of maintenance before computerisation seems to be low is the fact that, with computerisation it is possible to track all the maintenance costs in the company and have a proper recording, whereas before computerisation it was almost impossible to track the maintenance costs. As can be seen from Table I, the maintenance costs for the financial year 1986/1987 and those of 1988/1989 were not available due to poor record keeping. This implies also that some of the maintenance costs were not properly recorded during the manual system. Figure 2 summarises the analysis of the maintenance costs after the computerisation. From the data depicted in Figure 2, one can see that the maintenance costs after the computerisation of the maintenance department has shown a decreasing trend. The trend line is showing a negative slope, which is an indication that the maintenance costs were in the decreasing trend. Cost reduction in inventory costs Regarding the inventory levels, 92.9 per cent of respondents believe that computerisation of the inventory system has helped in decreasing the holding
Year Table I. Maintenance costs for the period 1984-1991 at TPCC before computerisation
1984/1985 1985/1986 1987/1988 1990/1991
Year
Table II. Maintenance costs for the period 1994-1999 at TPCC after computerisation
Total annual maintenance cost in Tshs
Average exchange rate with US$
Total annual cost in US$
Percentage increase of maintenance cost
26,770,539 29,027,648 30,920,375 30,965,975
132 156 198 219
202,807 186,075 156,164 141,397
28.25 216.07 29.46
Total annual maintenance cost in Exchange rate with Tshs US$a
Total annual cost in US$
Percentage increase of maintenance cost (using US$)
1994 778,000,000 512 1,519,531 1995 1,009,000,000 581 1,736,661 14.29 1996 1,567,000,000 582 2,692,440 55.04 1997 1,496,000,000 630 2,374,603 211.80 1998 1,008,000,000 660 1,527,273 235.68 1999 926,000,000 750 1,234,667 219.16 Note: a Exchange rate source: Bank of Tanzania Economical Bulletin, Vol. XXIX No. 1
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Figure 2. Maintenance costs after the computerisation of the maintenance department at TPCC
and ordering costs. An amount of Tshs 400 million was saved as holding cost after selling some spare parts, which were kept in storage for many years without being used. Before computerisation, the ordering of spare parts was not scientifically conducted. There was no proper information of the consumption rate of different kinds of spare parts. Consequently, the store was full of different kinds of spare parts, some of which were not readily needed. After computerisation it was possible to identify the spare parts which are frequently needed, and those whose consumption rate was very low. It was also possible to identify some spare parts which are no longer needed by the company. Therefore, the company disposed of those spare parts which were no longer needed by the company and reduced the stock of the low rate consumption spare parts. By doing so the company saved Tshs 400 million. Analysis of the holding and ordering costs are depicted in Table III. If one uses the Tanzanian shilling for analysis it may be concluded that only from 1998 to 1999 both ordering and holding costs are decreasing. However, after converting the costs to a stable currency, it was shown that the inventory holding cost has been decreasing after the introduction of the computer. After introducing the new maintenance software MP2, adequate computer training was given to the purchase department staff and this has allowed them to utilise the software effectively. Consequently, they can use the computer to order only the necessary spare parts needed during a particular period.
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Figure 3 summarises the trend in inventory holding costs. It is clearly depicted by the trend line that the holding cost has been decreasing for the period 1993 to 1999. In 1984, TPCC started a rehabilitation program to improve the plant condition in order to improve the production capacity. The productivity improved from 0.57 in 1984, when rehabilitation started, to 5.50 by 1990. The mean productivity before computerisation was 1.98. The data show that after introducing IT the highest productivity achieved was 6.08 in 1991. The mean productivity achieved after computerisation is 5.08, which is higher than the 1.98 attained before computerisation. If these two means of productivity are compared it can be concluded that productivity has improved above 50 per cent. Through the interview method, the responses on downtime show that 86 per cent of respondents agreed that by introducing IT in the maintenance Item of inventory cost control
1993
Years and amount spent in ordering and holding costs 1994 1995 1996 1997 1998 1999
Ordering costs [mill.] 3.0 3.5 6.0 6.5 7.0 7.6 6.1 Exchange ratea 403 512 581 582 630 660 750 Equivalent cost in US$ 7,444 6,836 10,327 11,168 11,111 11,515 8,133 Holding costs [mill.] 0.5 0.6 0.6 0.7 0.71 0.78 0.60 Table III. 1,172 1,033 1,203 1,127 1,182 800 Inventory costs after the Equivalent cost in US$ 1,241 computerisation Note: a Exchange rate source: Bank of Tanzania Economical Bulletin (1999)
Figure 3. Inventory holding costs after computerisation of maintenance department at TPCC
department, downtime has been reduced by 50 per cent. Regarding the overall cost of maintenance, 79 per cent of respondents agreed that, in totality, the use of IT in the maintenance department has reduced the downtime cost by 50 per cent. However, a quantitative analysis of downtime data showed that the mean downtime before computerisation was 283 hours per month, while after computerisation is 256 hours per month, which is 27 hours saving. This represents an average of 9 per cent decrease of downtime per month after computerisation. This situation is depicted in Tables IV and V. It was not possible to get quality data from TPCC because the company refused to disclose this data for security reasons. Therefore, the method used to indirectly find information about the quality performance at TPCC was determination of availability of the equipment before and after computerisation of the maintenance department. Data on the availability of the equipment are shown in Table VI. The data show that the availability has been fluctuating between 45 per cent and 93 per cent and the mean availability is 65 per cent. The availability before the introduction of CMMS was around 50 per cent. This shows an increase by 15 per cent of the availability before the introduction of CMMS. Availability being a parameter of quality, we can also assume that quality has improved by 15 per cent as far as availability is concerned.
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Conclusion In this research, the main objective was to find out quantitatively, the benefits of introducing CMMS in the maintenance department. The quantitative data shows that there has been a decrease in downtime of the equipment by 9 per cent; the overall maintenance cost has decreased from the highest of US $2.7
Year
Kiln no.
1987
I II III I II III I II III I II III
1988 1989 1990
Uptime (hours)
Down time (hours)
Monthly average down time in hours
4,834 5,885 6,081 4,624 5,472 5,978 4,832 1,145 6,169 6,360 5,844 5,262
3,926 2,875 2,679 4,136 3,288 2,782 3,028 7,615 2,591 2,400 2,916 3,498
327.17 239.58 223.25 344.67 274.00 231.80 252.33 634.58 215.91 200.00 243.00 291.50
Mean total Monthly average monthly average down time for downtime for the the whole plant whole period in hours in hours 26.3 297.6 283.3 367.6 244.8
Table IV. Uptime and downtime before computerisation
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Year
Kiln no.
Uptime (hours)
Down time (hours)
Monthly average down time in hours
1994
I II III I II III I II III I II III I II III I II III
3,970 4,925 5,299 7,796.3 7,599.1 7,627.9 8,188.0 8,146.3 8,083.6 2,870.3 4,461.0 4,516.5 4,523.8 5,139.3 5,364.2 3,576.2 4,866.1 5,414.1
4,790 3,835 3,461 963.74 1,160.86 1,132.13 571.97 613.73 676.36 5,889.7 4,299.0 4,243.5 4,236.2 3,620.7 3,395.8 5,183.8 3,893.9 3,345.9
399.17 319.58 288.42 80.31 96.74 94.34 46.66 51.11 56.36 490.81 358.25 353.63 353.02 301.73 282.98 431.98 324.49 278.83
1995 1996 1997 1998 Table V. Uptime and downtime after computerisation
Table VI. Availability of the machine after the introduction of IT in the maintenance
1999
Mean total Monthly average monthly average down time for downtime for the the whole plant whole period in hours in hours 335.4 90.5 51.7 256 400.9 312.6 345.1
Year
Average uptime (hours)
Average downtime (hours)
Uptime Availability ¼ UptimeþDowntime
1994 1995 1996 1997 1998 1999
4,731.3 7,674.4 8,139.3 3,949.3 5,009.1 4,618.8
4,028.7 1,085.6 620.7 4,810.7 3,750.9 4,141.2
0.54 0.88 0.93 0.45 0.57 0.53
Mean availability
0.65
million per annum in 1996 to about US $1.2 million per annum in 1999. The productivity has increased by 50 per cent and the availability of the equipment has increased by an average of 15 per cent. Therefore, the introduction of CMMS has helped to improve the performance of the company in terms of productivity and reduction of the overall operational unit cost. References Adcock, K., Helms, M.M. and Jih, W.K. (1993), “Information technology: can it provide a sustainable competitive advantage?”, Information Strategy: The Executive’s Journal, Spring, pp. 10-15. Bacon, C.J. (1992), “The use of decision criteria in selecting information system”, MIS Quarterly, Vol. 16 No. 3, pp. 335-54.
Bank of Tanzania Economical Bulletin (1999), Vol. XXIX No. 1. Bavu, E., Sheya, A., Mlawa, H. and Kawambwa, S. (1997), Culture of Maintenance for Sustainable Development in Tanzania, TechMa, Dar es Salaam. Connolly, D.J. (1999), “Understanding information technology investment decision-making in the context of hotel global distribution systems: a multiple-case study”, dissertation, Virginia Polytechnic Institute and State University, Blacksburg, VA. Gould, L.S. (1998), “Keeping up, running and profitable with CMMSs”, Automotive Manufacturing & Production, Vol. 110 No. 8, pp. 68-71. Grant, E.L., Ireson, E.G. and Leavenworth, R.S. (1982), Principles of Engineering Economy, 70th ed., John Wiley & Sons, New York, NY. Gupta, C.B. (1994), Production, Productivity and Cost Effectiveness, Sultan Chand & Sons, New Delhi. Juran, J.M. and Gryan, F. (1998), Juran’s Quality Control Handbook, 4th ed., McGraw Hill Book Company, New York, NY. Lamendola, M. (1999), “CMMS: more than work order system”, CEE News, Vol. 51 No. 8, pp. 24-5. Mensching, J.R. and Adams, D.A. (1991), Managing an Information System, Prentice-Hall, Englewood Cliffs, NJ. Mjema, E. and Kundi, B.A.T. (1996), “Development and introduction of EDP in maintenance management in a Tanzania Institution”, The Tanzania Engineer, Vol. 5 No. 5, pp. 3-11. Ohmae, K. (1992), The Mind of the Strategist: Business Planning for Competitive Advantage, Penguin Books, New York, NY. Pintelon, L., Du Preez, N. and Van Puyvelde, F. (1999), “Information technology: opportunities for maintenance management”, Journal of Quality in Maintenance Engineering, Vol. 5 No. 1, pp. 9-24. Porter, M.E. (1985), Competitive Advantage: Creating and Sustaining Superior Performance, The Free Press, New York, NY. Stickel, E. (1997), “IT-Investitionen zur Informationsbeschaffung und Produktivita¨tsparadox”, Die Betriebswirtschaft, Vol. 57 No. 1, pp. 65-72. Veloz, F. (1998), “Computerized maintenance management systems (CMMS)”, IIE Solutions, Vol. 30 No. 3, pp. 61-4. Weill, P. (1991), “The information technology pay off: implication for investment appraisal”, Australian Accounting Review, pp. 2-11. Weill, P. and Olson, M.H. (1989), “Managing investment in information technology: mini case examples and implications”, MIS Quarterly, Vol. 13 No. 1, pp. 3-18. Winston, C. (2003), “Critical component of the CMMS: the repair work order”, available at: www. mt-online.com/current/0103_cmms_repairorder.html (accessed, 21 February 2003).
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Appendix
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The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/1355-2511.htm
Application and implementation issues of a framework for costing planned maintenance Mohamed Ali Mirghani Department of Accounting and MIS, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia Keywords Preventive maintenance, Cost effectiveness, Maintenance costs Abstract This paper develops a case study on the application and implementation issues of a framework for costing planned maintenance. It outlines the methodology for the development of the case study and presents the major findings of the existing maintenance-costing system of the organization under study. It presents the results of a pilot study of the application of the proposed costing framework to a sample of planned maintenance jobs. It provides recommendations and identifies critical issues for a successful implementation.
Practical implications Proper cost assignment has a major impact on maintenance operations. The framework in this paper provides an effective tool for cost assignment and tracking cost efficiency. Knowledge about major cost derivers will enable organizations to optimize the utilization of resources in their planned maintenance (PM) activities and processes. Also the costing framework will reveal inefficiencies in the maintenance system and will identify the need for updating maintenance time standards and material requirements planning activities. Introduction Planned (preventive) maintenance . . . involves the repair, replacement, and maintenance of equipment in order to avoid unexpected failure during use. The primary objective of planned maintenance is the minimization of total cost of inspection and repair, and equipment downtime (measured in lost production capacity or reduced product quality) (Mann et al., 1995).
It provides a critical service function without which major business interruptions could take place. It is one of the two major components of Journal of Quality in Maintenance Engineering Vol. 9 No. 4, 2003 pp. 436-449 q MCB UP Limited 1355-2511 DOI 10.1108/13552510310503268
The data on the implementation of the proposed framework for costing planned maintenance was collected and reported by Mr Abdullah Al-Rubaian, Mr Sulaiman Al-Namlah, and Mr Turki Al-Rasheed in their term project in ACCT 552 (Managerial Accounting) at King Fahd University of Petroleum & Minerals’ EMBA Program. Their efforts are highly appreciated.
maintenance load. The other component is unplanned (unexpected) Costing planned maintenance (Duffuaa et al., 2000). Planned maintenance could be time- (or maintenance use-based) or could be condition-based (Duffuaa et al., 1998). Over the years the maintenance literature has been replete with research on engineering and planning issues as well as on issues related to the effectiveness of realizing PM schedules. The costing and cost efficiency issues of PM 437 received much less attention. In an attempt to fill this gap, Mirghani (2001) proposed a framework for costing PM. This paper presents a case study on the application and implementation issues of that framework. The case study was developed according to the following methodology. It: (1) Selected a business organization that is heavily dependent on in-house planned (preventive) maintenance in its operations. (2) Gained familiarity with the existing costing system of PM in the business organization under study. This is achieved by a “walk-through” the system to understand its documentary cycle and information support. (3) Documented the understanding of the existing PM costing system. (4) Compared the existing PM costing system with the proposed costing framework and identified the gaps between the two. (5) Tested the practicality of the proposed costing framework through a pilot study of PM jobs. (6) Made recommendations that would enable the organization under study improve its PM costing practices. (7) Identified critical implementation issues of the proposed costing framework. General overview of the framework for costing PM The framework for costing PM proposed by Mirghani (2001) identifies the standard cost elements (direct materials, direct labor, and support services) of a PM job. The documentary support for these cost elements is indicated and they are cross-referenced with the planned maintenance job cost sheet (PMJCS) that represents the core of the proposed costing framework. The framework explains how actual cost data could be captured, the documents that could be used for the data capture, and how they are cross-referenced with the planned maintenance job cost sheet (PMJCS). The framework also explains how the cost-efficiency variances of a PM job could be generated and reported to maintenance management. Direct materials Direct materials represent all materials and component parts that are related to a PM job and traceable to it in an economically feasible manner. Economic feasibility of cost traceability assures the tracing, to a cost object, direct costs
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that are material (significant) in amount only. This assures the cost effectiveness of the costing system. Direct materials requirements should be documented in a bill of materials (BOM). The BOM should allow for normal spoilage of materials if some spoilage is inevitable or related to inherent characteristics of the PM job. The BOM will provide the basis for determining the standard quantities of direct materials that will be reflected in Panel A of the PMJCS. The BOM also provides the necessary data for the direct materials section of a PM work order. Direct labor Direct labor represents all labor skills that directly work on a PM job and their cost is traceable to that job in an economically feasible manner. PM direct labor usually is comprised of a team of several skills needed to assure the quality and cost effectiveness of the maintenance job. Thus, the mix of the labor skills has to be predetermined and should be reflected in the PM job’s work flow sheet (JWFS). The JWFS is a road map for the maintenance job and provides information about processes to be performed the labor skill(s) to be applied, and the amount of labor time to be utilized under normal conditions. The JWFS should indicate if a certain degree of substitution of labor skills is permissible in order to control the quality and cost of the PM job. Furthermore, the JWFS should incorporate any inevitable labor downtime due to some inherent characteristics of the maintenance job. Inevitable labor downtime could be due to waiting time for materials and parts, fatigue, and attendance to personal needs. This is necessary so that the labor time standards are reasonably attainable. The JWFS will provide the basis for determining the standard hours and mix of direct labor that will be reflected in the direct labor section of Panel A of the PMJCS. The JWFS provides the necessary data for the direct labor section of a PM work order. Support activities In addition to direct materials and direct labor, a PM job would require the services of support activities in the areas of: . design; . planning; . work order scheduling; . dispatching; and . follow-up and quality assurance. Support activities costs represent all PM costs other than direct materials and direct labor costs. They can be labeled as PM overhead costs. These costs are common to all PM jobs and are not amenable to traceability in an economically feasible manner. Hence, the only feasible way to reflect them as part of the costs
of a PM job is through allocation. The question is: on what basis? The following Costing planned approaches could be followed: maintenance (1) Look for a single common denominator to serve as a basis for PM overhead costs allocation, like maintenance job labor hours or machine hours. Labor hours could be the relevant allocation basis if the maintenance job is labor-intensive. Machine hours could be a relevant 439 allocation basis if the maintenance job requires the heavy use of machinery, like in a machine shop. However, this approach assumes that all maintenance labor hours or machine hours require the same amount of overhead support. Furthermore, most likely a single basis for overhead allocation may not have any causal relationship with the incurrence of PM overhead costs. Hence, using a single rate for applying (allocating) these overhead costs to PM jobs, could lead to cost cross-subsidization among maintenance jobs, and eventually would lead to the distortion of PM costs making the cost information potentially (if not totally) misleading. In today’s business environment, the tolerable error margin is narrower and organizations can no longer afford such mistakes and remain competitive or get funded (Cokins, 1998). (2) Since there are different support activities within PM, and since maintenance jobs consume the resources of these activities differently, such differentiation has to be captured in building up a PM job cost (Mirghani, 1996). This issue becomes quite critical when the overhead costs are material (significant) in amount in relation to PM total costs. Activity-based costing (ABC) provides the answer. ABC is a system that first accumulates support (overhead) costs of each support area and then assigns the cost of these activities to cost objects (products or services) through the following steps: . identify major support activity areas within PM; . for each activity area, identify a cause-and-effect cost driver(s); . develop total budgeted cost (variable and fixed) and total budgeted demand for each activity under normal conditions; and . calculate a predetermined overhead rate per unit of activity for each activity area by dividing total budgeted costs by total budgeted demand. An ABC system provides the prelude for improving the operations of an organization through activity-based management (ABM). (3) Use the predetermined overhead rates in the last of the four options to apply support overhead costs to PM jobs on the basis of its planned/actual usage of that activity. The predetermined overhead rates for the different support activity areas and the planned quantity of support in each activity area provide the basis for entries in the support services section of Panel A of the PMJCS. ABC provides appropriate
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building blocks for reliable maintenance costing as well as a better understanding of the cost structure of a maintenance operation. (4) Business organizations face significant threats in an increasingly global environment. In this regard, ABC/ABM can support a more strategic approach to cost management and a multitude of other business decisions (Fahy and O’Brien, 2000). ABC can provide more useful information for decision making than traditional costing, but it involves a paradigm change in thinking to make it truly effective (Walker, 1998). The ABC exercise provides information that guides resources management, performance measurement, and more effective utilization of resources. Background of the business organization under study ARASCO is an agricultural services organization working in the Kingdom of Saudi Arabia for the last 20 years. It has a number of facilities and service organizations implementing planned preventive maintenance programs to ensure continuity of operations and maximization of uptime. ARASCO is a just-in-time (JIT) supplier. Its main lines of business include: . feed milling (all types of feeds, vitamin and mineral premixes); . corn milling (starch and glucose production); . chemical industry (dicalcium phosphate production); . port bulk handling and storage operations; . transportation; . cold storage; . agro chemicals and commodities trading; . laboratory services (inspection, analysis, diagnosis, consultation and accreditation); and . meat processing. At ARASCO, PM is basically performed on equipment and facilities with a predetermined frequency. The main goal of performing PM periodically is to extend equipment life and assure its capacity in continuously supporting the company’s goals and targets. ARASCO is heavily dependent on PM for maintaining its ability to serve effectively and efficiently as a JIT supplier to its customers. Planned (preventive) maintenance is very critical to ARASCO’s business strategy because: . one of ARASCO’s critical success factors is its reliability as a supplier; . ARASCO delivers JIT almost all of its products and raw materials which means that any downtime will also have serious implication on its transportation cost and production and delivery schedules; and
.
the cost of unplanned downtime is very high, since the plants are Costing planned processing plants and any breakdown will very likely cause a complete maintenance shutdown.
The frequency selected for performing PM tasks takes into consideration the maximum time allowable before failure or extensive and costly breakdown maintenance work is performed. Defining the right tasks and their associated intervals for execution is an important factor for controlling the cost of PM work without sacrificing its value for the business. Implementation of the framework of costing PM at ARASCO ARASCO’s Al-Kharj Feed Mill was selected for the implementation of the PM-costing framework, since its maintenance philosophy and practices were similar to those exercised in other ARASCO facilities. Al-Kharj Feed Mill has a planned preventive maintenance program since its inception in 1987. It has a yearly planned preventive maintenance schedule which provides the details for the planned preventive maintenance work to be executed for the whole year, starting with the first week in January and ending up on week 52 of the calendar year. For every week, the list of all the equipment to be checked and maintained is indicated, with the time needed to perform the job. The planned oiling and greasing program is scheduled separately. At the beginning of every week the planned preventive maintenance schedule covering the mechanical electrical and oiling and greasing for the whole week is issued to the maintenance crew. Preventive maintenance checklists are issued for every job order. The checklist’s upper part describes all the works to be done, and the lower part provides a space for a list of spare parts actually used. During the execution of the maintenance work the maintenance crews write down their remarks on the time it took them to complete the required work. If it is longer than the scheduled time, and also the number of people utilized, it is obvious that recording of the time and manpower was informal and loosely recorded. Weekly maintenance reports summarizing all the maintenance work carried out during that particular week is submitted to the assistant plant manager, operations and maintenance. ARASCO does not have a separate costing system of its PM. It is embedded into its total maintenance costs without any clear distinction between breakdown and PM. It is also clear that the main objective of the PM activity is to ensure the smooth and continuous operations of ARASCO’s plants, and to maintain its image as a reliable supplier to its own customers. The existing PM system in ARASCO’s plants has succeeded in minimizing breakdowns and the unplanned down time to less than 2 percent, but it is inadequate in providing cost information that could contribute to significant
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improvements in its cost competitiveness and efficiency. By reviewing the underlying documentation of the PM system, it has become apparent that the Al-Kharj plant has the ingredients for implementing the proposed costing framework. All the data inputs could become available by adopting the documentations recommended in the proposed costing framework to identify all the proper inputs needed to obtain the standard and actual costs of PM at Al-Kharj plant. Major findings of the existing system in comparison with proposed costing framework By analyzing the existing system, what is available and what is needed to satisfy the requirements of the proposed costing framework were identified. The following are the resultant findings of the analysis: . A PM schedule (yearly and weekly) is available which would facilitate the development of the standard inputs needed to carry out the schedule effectively and efficiently. . There is no available list of material requirements for every PM job, but spare parts were ordered during the job execution. The material requirements should be identified at the planning stage. The plant has enough historical data and manufacturers’ recommended maintenance program for every machine, which could provide the basis for developing a BOM for each PM job. Such information is needed for the standard direct materials section of the PMJCS. The actual direct materials used could be accumulated during the execution of the job through the related materials requisitions to provide the data needed to fill the actual direct materials section of the PMJCS. . The PM schedule provides the total man hours needed to perform the job, but does not provide the breakdown by labor skill, which could be developed on the basis of the PM crew experience, time and motion study, and the knowledge gained during the implementation of the proposed costing framework. There is no separate section for the actual man-hours used in carrying out the job order, but rather a comment by the technician in case the job took longer than expected. Furthermore, the breakdown of the time it took to execute the different jobs is not captured. Hence, labor time tickets are needed to capture the labor utilization in performing a PM job order so as to fill out the actual direct labor section of the PMJCS. . The support activity (design, planning, work order scheduling, dispatching, and follow-up and quality assurance) costs are not allocated to the PM jobs, but rather they appear as part of the total cost of maintenance. Support activity costs could be assigned to PM jobs through ABC.
It is noteworthy that the maintenance department provides maintenance Costing planned services to a number of facilities at Al-Kharj complex, which consume maintenance support services resources differently. This will require an extensive and an elaborate study of the support services activities, costs, and cost drivers with a careful ABC analysis to ensure proper development of multiple overhead rates. If this is not done methodically, the PM-costing system 443 would result in cost cross-subsidization among maintenance jobs and among cost centers. This would make the cost information misleading and would misguide maintenance management efforts. The ABC exercise would result in predetermined overhead rates for the different support activity areas and the planned quantity of support to be reflected in the PMJCS. The actual support activities card described in the proposed costing framework will provide the actual utilization of support services by a specific maintenance job. The pilot study The pilot study included 20 PM jobs. Ten jobs were from week 44 of the year 2002 and ten jobs were from week 16 of the year 2003. The two weeks were selected randomly. Any other two weeks would have given similar results. The data for week 44 were obtained from the historical records of the maintenance department, whereas week 16 data were obtained through the actual implementation of the proposed costing framework during that week. Figure 1 and Tables I and II show sample results of applying the proposed costing framework. The results showed that the variances were generally very high, which underscores the need for better planning and more accurate and up-to-date cost standards. This indicates that the cost standards have to be continuously reviewed to improve the PM program. The results still indicate that the sole motivation behind the PM program is to minimize downtime without considering the cost aspects of it. The pilot study provides evidence of the possibility of adopting the proposed costing framework to assure the cost efficiency of a PM system. It also indicates the need for continuous improvements to the planning side of the PM program to improve reliability while realizing cost efficiencies. What is important is that there are enough indications that the proposed costing framework will contribute to capturing the PM cost elements and provide information that contribute to improving the cost efficiency of the overall PM system. Recommendations . ARASCO has to focus its attention on its PM cost. Its regular PM could be costed according to the proposed costing framework because it has the prerequisites for a successful implementation.
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Figure 1. Planned maintenance job cost sheet
Screw conveyor Hammer mill Elevators
Description
0.00 0.00
0.00
Notes: A = Planned; B = Actual; C = Variance
244.94 37.28 2162.45 458.01
15.00
17.50 30.00
47.50
5.00
7.50 0.00
17.50
30.00
45.60
25.00
40.00
37.50
60.00
20.00 79.40
7.50
14.40
85.00 16.67 85.00 16.67
68.33
68.33
68.33
68.33
68.33
85.00 16.67
85.00 16.67
85.00 16.67
85.00 16.67
85.00 16.67
33.33 68.33 85.00 16.67 19.82 1579.571746.27 166.70
25.00
31.58
30.00 120.00
32.50 27.50 218.75 55.00
68.33 68.33
85.00 16.67
B
Total %
78.33 132.66 98.33 115.00
1.78
9.17
7.44
132.33 156.50
24.17 18.26
352.73 695.80 343.07 97.26
500.17 663.21 163.04 32.60
123.33 132.50
476.41 231.342245.07251.44
21.67
54.33 69.36 16.67 16.95
24.40 410.55 409.94 20.61 0.15 10.55 3684.61 4388.72 704.11 19.11
24.40
24.40
24.40
24.40
24.40
C
296.85 614.52 317.67 107.01
A
1.73 1215.58 1237.25
24.40 24.40
24.40
Support services cost B C %
68.33
A
50.00 964.60 981.27 16.67
75.00 0.00
58.33
Direct labor cost B C %
13.21 60.00 80.00 26.87 400.60 480.00
0.00
130.65
550.80 312.00
0.00
28.60
523.21 116.37
34.00
0.00
0.00
15.00
10.00
10.00 30.00
30.00
A
285.65 120.00 105.00 215.00 212.50
0.00
30.16 #DIV/0! 0.00 0.00
41.34 246.74
240.98
30.16 0.00
142.81
Direct material cost B C %
198.52 482.02 283.50
A
Compressor GA-55 240.98 AV 2 1041 Toyota Camry 98 288.08 HV 2 1001 Forklift # 01 TCM 15.00 HV 2 1003 Forklift # 03 TCM 406.84 HV 2 1011 Wheel Loader # 2 238.80 HV 2 1013 Track Mobile U 2 1400 34.00 WT 2 1038-08 WTP Product Water Pump 282.22 Total 1704.44
FM 2 1069 FM 2 1086 FM 2 1190
FM 2 1072
FM 2 1074
Equipment
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Table I. Week No 16 – 2003 Preventive maintenance planned vs actual cost summary
Elevators 0.00 23.54 23.54 Compressor GA-30 0.00 500.00 500.00 Boiler General 3448.90 3512.22 63.32 Roller Mill # 1 (Ferral Ross) 200.00 231.90 31.90 Chain Conveyor 0.00 0.00 0.00 Service Bus GMC-1994 642.13 642.13 0.00 Forklift # 04 TCM 0.00 38.91 38.91 Forklift # 05 TCM 0.00 10.12 10.12 Total 4291.03 5344.95 1053.92 0.00
12.50
5.00
0.00 68.33
15.63 68.33
25.00 68.33
28.00 233.33 68.33
35.00 25.00 212.50 68.33
20.00
37.50 68.33
10.00 500.00 68.33
7.50
15.00
37.50
22.50 150.00 68.33
85.00
85.00
85.00
85.00
85.00
85.00
85.00
85.00
85.00
Total
97.50
B
16.67 24.40
16.67 24.40
16.67 24.40
16.67 24.40
%
9.17 10.38
C
68.21 84.91
11.67 10.77
48.57 16.85
2.57
83.33 161.41
78.08 93.70
830.46 1012.13 181.67 21.88
108.33 120.00
288.33 336.90
92.49
88.33 610.00 521.67 590.59
80.33 148.54
70.33 483.13 412.80 586.95
88.33
A
16.67 24.40 3597.23 3689.72
16.67 24.40
16.67 24.40
16.67 24.40
16.67 24.40
Support services cost A B C %
120.00 285.00 165.00 137.50 68.33
40.00
20.00
92.50
25.00
40.00
12.00
12.50
Direct labor cost B C %
#DIV/0! 15.00 52.50 37.50 250.00 68.33 85.00 16.67 24.40 83.33 147.62 64.29 77.15 24.56 344.00 612.00 268.00 77.91 683.30 850.00 166.70 24.40 5318.33 6806.95 1488.62 27.99
#DIV/0!
0.00
#DIV/0!
15.95
80.00
20.00
#DIV/0! 1.84
12.00
#DIV/0!
2.00
0.00 386.13 386.13 #DIV/0!
A
20.00
0.00
Direct material cost B C %
0.00 #DIV/0!
0.00
A
Notes: A = Planned; B = Actual; C = Variance
HV 2 1005
HV 2 1004
AV 2 1042
SL 2 1009
FP 2 1004
FM 2 1200
FM 2 1140-1151 FM 2 1189
Hammer mill Union special sewing sachine
FM 2 1072 FM 2 1077 FM 2 1136-2
Table II. Week No. 44 – 2002 preventive maintenance planned vs actual cost summary
Description
446
Equipment
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.
.
.
.
.
.
The direct materials and the man-hour requirements have to be reviewed Costing planned and continuously updated to ensure the proper utilization of input maintenance resources. The actual utilization of these two resources has to be properly captured to ensure that the figures recorded reflect reality, and that the variation between standard and actual costs of PM are within the acceptable control limits. Acceptable control limits could be determined 447 statistically through SPC techniques or through managerial judgment. Significant variances need to be investigated and explained resulting in appropriate corrective action(s). This should enhance further improvement and development of a PM program that achieves the objectives of high reliability and cost efficiency. The support services activities have to be analyzed using an ABC framework. It is important that this should be done methodically because the maintenance department support services are provided to a number of facilities in Al-Kharj complex; namely, the feed mill, the starch wet mill, the glucose refinery, the premix and the aqua feed plants which consume support services differently. An ABC system could be implemented in the entire Al-Kharj complex. A cross-functional ABC implementation team could be formed to engage in activity analysis and identification of causal cost drivers. The results indicated a need continuously to update time standards and the process of planning PM. The spare parts required for the planned preventive maintenance system should be specified in BOM as part of the planning schedule and should not be only identified as the work being executed. This will help in preparing a realistic maintenance budget, and also provide guidance for purchasing and managing the spare parts inventory properly. The availability of spare parts and other materials also require an effective inventory management system. This could be accomplished by utilizing the plant historical data, and manufacturer’s recommended technical data. The planned preventive maintenance man-hour requirement per labor skill should be identified for every job order in detail. This could be obtained through analysis of plant historical data, time-and-motion studies, and experience gained by the preventive maintenance team. The actual man-hour per labor skill used in performance of the job should be properly captured through labor time tickets. In implementing the proposed PM-costing framework, ARASCO can make use of its enterprise resource planning (ERP) system since it has functionalities that support the implementation of such a framework. It can easily accommodate the PMJCS and related forms. ERP systems do
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support ABC systems, integrate operational and cost data, and have a flexible user-friendly reporting structure. Critical implementation issues The proposed PM-costing framework represents a technical framework that would affect information flows and accountability for the utilization of resources in an organization. Furthermore, it involves a new way of thinking. Not only to think about minimizing downtime but also to think of the cost efficiency of achieving that. Hence, the following issues that need to be considered for a successful implementation: . Top management support and commitment. . A culture accepting cost efficiency as a major issue in managing a PM program in addition to the effectiveness of the program. . Formation and effectiveness of ABC teams . Reliability of activity analysis and identification of causal cost drivers. . Development and updating of PM cost standards. . Reengineering of some business processes to realize the full benefits of the proposed costing framework. . The level of cost consciousness in the organization. Concluding remarks and recommendation for future research ARASCO’s top management and maintenance management have decided to adopt the proposed PM costing framework. In fact, they think it would be beneficial to them for evaluating the cost efficiency of both preventive and breakdown maintenance. They indicated that it would provide very valuable information to monitor the cost efficiency of the maintenance operation. It will facilitate the continuous improvement of maintenance and contribute positively to ARASCO’s total quality management (TQM) initiative. For the future, case studies need to be developed for the proposed framework in both planned and breakdown maintenance. References Cokins, G. (1998), “Why is traditional accounting failing managers?”, Hospital Material Management Quarterly, November, pp. 72-80. Duffuaa, S., Raouf, A. and Campbell, J.D. (1998), Maintenance Planning and Control: Modeling and Analysis, John Wiley & Sons, New York, NY. Duffuaa, S., Ben Daya, M., Al-Sultan, K. and Andijani, A. (2000), A Simulation Model for Maintenance Systems in Saudi Arabia, Final Report, KACST Project No. AR-16-85. Fahy, M. and O’Brien, G. (2000), “As easy as ABC? It seems not!”, Accountancy Ireland, Vol. 32 No. 1, February.
Mirghani, M.A. (1996), “Aircraft maintenance budgetary and costing systems at the Saudi Arabian Airlines: an integrated business approach”, Journal of Quality in Maintenance Engineering, Vol. 2 No. 4, pp. 32-47. Mirghani, M.A. (2001), “A framework for costing planned maintenance”, Journal of Quality in Maintenance Engineering, Vol. 7 No. 3, pp. 170-82. Walker, M. (1998), “Attributes or activities? Looking for ABCII”, Australian CPA, Vol. 68 No. 9, pp. 26-8. Further reading Fowler, M. and Yahanpath, N. (2000), “Implementing activity based costing in tertiary institutions”, Chartered Accountants Journal of New Zealand, Vol. 79 No. 11, December, pp. 28-31. Horngren, C., Foster, G. and Datar, S. (2000), Cost Accounting: a Managerial Emphasis, Prentice-Hall, Englewood Cliffs, NJ. Shaw, R. (1998), “ABC and ERP: partners at last?”, Management Accounting, Vol. 80 No. 5, November, pp. 58-60.
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Journal of Quality in Maintenance Engineering Vol. 9 No. 4, 2003 pp. 450-451 q MCB UP Limited 1355-2511
Note from the publisher As managing editor of the Journal of Quality in Maintenance Engineering here at Emerald, I would like explain the benefits available to you when you become an author with Emerald. In addition to achieving wide dissemination of your work by publishing with Emerald, our author relations service – the Literati Club – provides services and support for those authors who publish with an Emerald journal. It is a tangible expression of commitment by a publisher to its authors and editors, and the club offers support and resources for all Emerald contributors worldwide. The Literati Club offers the following benefits: (1) A “thank-you” to outstanding authors and editors. An annual Awards for Excellence, which celebrates outstanding contributors among club members in the following categories: . Best Paper Award for each participating journal; . Editor of the Year; . Leading Editor Awards; and . Research Award. (2) Regular Literati Club Newsline. All major developments occurring within the Literati Club and Emerald as a whole are reported in this newsletter and guidance is given on publishing, writing and editing. (3) Privileged personal subscriptions to home address. Any Literati Club member may at any time take out a personal subscription to an Emerald journal at one-third of the published price for delivery to a home address. (4) Complimentary personal subscription. You will personally receive a complimentary subscription to any Emerald journal in your area of interest if your library takes out a full-price subscription. (5) Calls for papers. All editors’ calls for papers in your areas of interest and previous article keywords will be mailed or e-mailed to you personally. (6) Future publications and new journal ideas. Editors give priority consideration to all articles you submit yourself, or on behalf of colleagues you wish to commend, and to new ideas for journal launches. (7) Photocopying rights. You are authorized to make up to 25 copies of any single article published by Emerald, without seeking prior permission, provided they are not for re-sale. For further information about the Literati Club, please see www. emeraldinsight.com/authors/index.htm For further information about how to submit material to JQME please see www.emeraldinsight.com/jqme.htm
More specifically to JQME, the usage statistics for 2003 to date have been excellent: there have been over 12,700 abstracts viewed in the period January to June 2003 alone. Over 7,700 articles were downloaded as a result of this. The most popular article downloaded during this time was “Strategic maintenance management” by D.N.P. Murthy, A. Atrens and J.A. Eccleston, from issue 4 of volume 8. We look forward to a successful year for JQME in 2004. Rosie Knowles Managing Editor
[email protected]
Note from the publisher
451
Call for papers Journal of Quality in Maintenance Engineering Special Issue on
Costing and budgeting issues in maintenance Journal of Quality in Maintenance Engineering (JQME) is an international refereed Journal published by Emerald, UK. JQME publishes articles in maintenance engineering and related fields. For more information on the editorial scope of JQME, the reviewing process, and article preparation requirements please access its Web site at: www.emeraldinsight.com/journals/jqme/ eabinfo.htm A special issue of the Journal of Quality in Maintenance will be devoted to costing and budgeting issues in maintenance. The issue will cover recent advances, developments, and applications of costing and budgeting techniques in maintenance. The scope of the issue covers allocation and utilization of economic resources by maintenance operations as a critical business activity. Papers for this special issue are solicited in the following areas: .
Cost accumulation and assignment in maintenance.
.
Cost information for evaluating effectiveness and efficiency of maintenance systems.
.
Activity-based-costing (ABC) in maintenance.
.
Activity-based-budgeting (ABB) in maintenance.
.
Cost information for maintenance sourcing decisions.
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Role of maintenance costing and budgeting in continuous improvement.
.
Life-cycle costing in maintenance.
.
Any topic relevant to the issue theme.
Information to authors Authors are requested to submit full papers to one of the issue Guest Editors by October 31, 2003. Authors will be notified of acceptance by March 1, 2004. Final papers for publication must be submitted by April 1, 2004. Submission of an electronic version of the manuscript is required.
Guest editors Dr Mohamed Ali Mirghani, KFUPM Box No. 791, Department of ACCT & MIS, King Fahd University of Petroleum & Minerals, Dhahran – 31261, Saudi Arabia. Tel: (03) 860-2377; Fax: (03) 860-2707; E-mail:
[email protected] Dr Sidney Baxendale, School of Accountancy, University of Louisville, Louisville, Kentucky, USA. Tel: 001 5028524813; Fax: 001 5028526072 E-mail:
[email protected] Dr Mohamed A. El-Haram, Construction Management Research Unit, University of Dundee, Dundee, UK. E-mail:
[email protected]
Index to Journal of Quality in Maintenance Engineering, Volume 9, 2003
Index
453 Authors ABDLSAMAD, M., see AL-BEDOOR, B.O. ABUZEID, O.M., A linear thermo-visco-elastic creep model for the contact of nominal flat surfaces based on fractal geometry: Kelvin-Voigt medium, No. 2, pp. 202-16. ADEWUSI, S.A., see AL-BEDOOR, B.O. AIT-KADI, D., see NOURELFATH, M. AKERSTEN, P.A., see BACKLUND, F. AL-BEDOOR, B.O., GHOUTTI, L., ADEWUSI, S.A., AL-NASSAR, Y. and ABDLSAMAD, M., Experiments on the extraction of blade vibration signature from the shaft torsional vibration signals, No. 2, pp. 144-59. AL-GHANIM, A., A statistical approach linking energy management to maintenance and production factors, No. 1, pp. 25-37. ALHUSEIN, M., see AL-SALAYMEH, A. AL-NASSAR, Y., see AL-BEDOOR, B.O. AL-QAISIA, A., CATANIA, G. and MENEGHETTI, U., Crack localization in non-rotating shafts coupled to elastic foundation using sensitivity analysis techniques, No. 2, pp. 176-201. AL-SALAYMEH, A., ALHUSEIN, M. and DURST, F., Development of a two-wire thermal flow sensor for industrial applications, No. 2, pp. 113-31. BACKLUND, F. and AKERSTEN, P.A., RCM introduction: process and requirements management aspects, No. 3, pp. 250-64. BAMBER, C.J., CASTKA, P., SHARP, J.M. and MOTARA, Y., Cross-functional team working for overall equipment effectiveness (OEE), No. 3, pp. 223-238. BEEBE, R., Condition monitoring of steam turbines by performance analysis, No. 2, pp. 102-12. BOUKAS, E.K., see KENNE, J.P. CASTKA, P., see BAMBER, C.J. CATANIA, G., see AL-QAISIA, A. COOKE, F.L., Plant maintenance strategy: evidence from four British manufacturing firms, No. 3, pp. 239-49. DHILLON, B.S. and KIRMIZI, F., Probabilistic safety analysis of maintainable systems, No. 3, pp. 303-20. DOHI, T., see KIM, J.W. DOHI, T., see NISHIO, Y. DURST, F., see AL-SALAYMEH, A. ˚ G, J. and TONNING, L., Decision support in selecting maintenance organization, EMBLEMSVA No. 1, pp. 11-24. GHOUTTI, L., see AL-BEDOOR, B.O. JARDINE, A.K.S., see ZHAN, Y. KENNE´, J.P. and BOUKAS, E.K., Hierarchical control of production and maintenance rates in manufacturing systems, No. 1, pp. 66-82. KIM, J.W., YUN, W.Y. and DOHI, T., Estimating the mixture of proportional hazards model with incomplete failure data, No. 3, pp. 265-78. KIRMIZI, F., see DHILLON, B.S. KUMAR, U., see LIYANAGE, J.P. KUMAR, U., see MARKESET, T.
Journal of Quality in Maintenance Engineering Vol. 9 No. 4, 2003 pp. 453-455 # MCB UP Limited 1355-2511
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LI, W., SHI, T., LIAO, G. and YANG, S., Feature extraction and classification of gear faults using principal component analysis, No. 2, pp. 132-43. LIAO, G., see LI, W. LIYANAGE, J.P. and KUMAR, U., Towards a value-based view on operations and maintenance performance management, No. 4, pp 333-50. MAKIS, V., see ZHAN, Y.
454
MARKESET, T. and KUMAR, U., Design and development of product support and maintenance concepts for industrial systems, No. 4, pp. 376-92. MARKESET, T. and KUMAR, U., Integration of RAMS and risk analysis in product design and development work process a case study, No. 4, pp. 393-410. MENEGHETTI, U., see AL-QAISIA, A. MERAH, N., Detecting and measuring flaws using electric potential techniques, No. 2, pp. 160-75. MIRGHANI, M.A., Application and implementation issues of a framework for costing planned maintenance, No. 4, pp. 436-49. MJEMA, E.A.M. and MWETA, M., An analysis of economics of investing in IT in the maintenance department: an empirical study in a cement factory in Tanzania, No. 4, pp. 411-35 MOTARA, Y., see BAMBER, C.J. MWETA, M., see MJEMA, E.A.M. NAKAGAWA, T. and YASUI, K., Note on reliability of a system complexity considering entropy, No. 1, pp. 83-91. NISHIO, Y. and DOHI, T., Determination of the optimal software release time based on proportional hazards software reliability growth models, No. 1, pp. 48-65. NOURELFATH, M., AIT-KADI, D. and SORO, W.I., Availability modeling and optimization of reconfigurable manufacturing systems, No. 3, pp. 284-302. PATANKAR, M.S. and TAYLOR, J.C., Posterior probabilities of causal factors leading to unairworthy dispatch after maintenance, No. 1, pp. 38-47. SHARP, J.M., see BAMBER, C.J. SHERIF, J.S., Repair times for systems that have high early failures, No. 3, pp. 279-83. SHI, T., see LI, W. SORO, W.I., see NOURELFATH, M. TAYLOR, J.C., see PATANKAR, M.S. ˚ G, J. TONNING, L., see EMBLEMSVA YANG, S., see LI, W. YASUI, K., see NAKAGAWA, T. YUN, W.Y., see KIM, J.W. ZHAN, Y., MAKIS, V. and JARDINE, A.K.S., Adaptive model for vibation monitoring of rotating machinery subject to random deterioration, No. 4, pp. 351-75. Titles Adaptive model for vibation monitoring of rotating machinery subject to random deterioration, ZHAN, Y., MAKIS, V. and JARDINE, A.K.S., No. 4, pp. 351-75. (An) analysis of economics of investing in IT in the maintenance department: an empirical study in a cement factory in Tanzania, MJEMA, E.A.M. and MWETA, M., No. 4, pp. 411-35.
Application and implementation issues of a framework for costing planned maintenance, MIRGHANI, M.A., No. 4, pp. 436-49. Availability modeling and optimization of reconfigurable manufacturing systems, NOURELFATH, M., AIT-KADI, D. and SORO, W.I., No. 3, pp. 284-302. Condition monitoring of steam turbines by performance analysis, BEEBE, R., No. 2, pp. 102-12. Crack localization in non-rotating shafts coupled to elastic foundation using sensitivity analysis techniques, AL-QAISIA, A., CATANIA, G. and MENEGHETTI, U., No. 2, pp. 176-201. Cross-functional team working for overall equipment effectiveness (OEE), BAMBER, C.J., CASTKA, P., SHARP, J.M. and MOTARA, Y., No. 3, pp. 223-238. ˚ G, J. and TONNING, L., Decision support in selecting maintenance organization, EMBLEMSVA No. 1, pp. 11-24. Design and development of product support and maintenance concepts for industrial systems, MARKESET, T. and KUMAR, U., No. 4, pp. 376-92. Detecting and measuring flaws using electric potential techniques, MERAH, N., No. 2, pp. 160-75. Determination of the optimal software release time based on proportional hazards software reliability growth models, NISHIO, Y. and DOHI, T., No. 1, pp. 48-65. Development of a two-wire thermal flow sensor for industrial applications, AL-SALAYMEH, A., ALHUSEIN, M. and DURST, F., No. 2, pp. 113-31. Estimating the mixture of proportional hazards model with incomplete failure data, KIM, J.W., YUN, W.Y. and DOHI, T., No. 3, pp. 265-78. Experiments on the extraction of blade vibration signature from the shaft torsional vibration signals, AL-BEDOOR, B.O., GHOUTTI, L., ADEWUSI, S.A., AL-NASSAR, Y. and ABDLSAMAD, M., No. 2, pp. 144-59. Feature extraction and classification of gear faults using principal component analysis, LI, W., SHI, T., LIAO, G. and YANG, S., No. 2, pp. 132-43. Hierarchical control of production and maintenance rates in manufacturing systems, KENNE´, J.P. and BOUKAS, E.K., No. 1, pp. 66-82. Integration of RAMS and risk analysis in product design and development work process: a case study, MARKESET, T. and KUMAR, U., No. 4, pp. 393-410. (A) linear thermo-visco-elastic creep model for the contact of nominal flat surfaces based on fractal geometry: Kelvin-Voigt medium, ABUZEID, O.M., No. 2, pp. 202-16. Note on reliability of a system complexity considering entropy, NAKAGAWA, T. and YASUI, K., No. 1, pp. 83-91. Plant maintenance strategy: evidence from four British manufacturing firms, COOKE, F.L., No. 3, pp. 239-49. Posterior probabilities of causal factors leading to unairworthy dispatch after maintenance, PATANKAR, M.S. and TAYLOR, J.C., No. 1, pp. 38-47. Probabilistic safety analysis of maintainable systems, DHILLON, B.S. and KIRMIZI, F., No. 3, pp. 303-20. RCM introduction: process and requirements management aspects, BACKLUND, F. and AKERSTEN, P.A., No. 3, pp. 250-64. Repair times for systems that have high early failures, SHERIF, J.S., No. 3, pp. 279-83. (A) statistical approach linking energy management to maintenance and production factors, AL-GHANIM, A., No. 1, pp. 25-37. Towards a value-based view on operations and maintenance performance management, LIYANAGE, J.P. and KUMAR, U., No. 4, pp 333-50.
Index
455
