maintenance management and modelling: the ifrim conference, may 2002, v¤xj¶ university, sweden

ISBN 0-86176-899-X ISSN 1355-2511

Journal of

Quality inMaintenanceEngineeringMaintenance management and modelling: The IFRIM conference, May 2002, Växjö University, SwedenGuest Editor: Basim Al-Najjar

Volume 9 Number 4 2003

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Access this journal online __________________________ 327

Editorial advisory board ___________________________ 328

Abstracts and keywords ___________________________ 329

Editorial __________________________________________ 331

Towards a value-based view on operations andmaintenance performance managementJayantha P. Liyanage and Uday Kumar _____________________________ 333

Adaptive model for vibration monitoring of rotatingmachinery subject to random deteriorationY. Zhan, V. Makis and A.K.S. Jardine ______________________________ 351

Design and development of product support andmaintenance concepts for industrial systemsTore Markeset and Uday Kumar __________________________________ 376

Integration of RAMS and risk analysis in productdesign and development work processes: a case studyTore Markeset and Uday Kumar __________________________________ 393

Journal of Quality inMaintenance Engineering

Maintenance management and modelling: the IFRIM conferenceMay 2002, Vaxjo University, Sweden

Guest EditorBasim Al-Najjar

ISSN 1355-2511

Volume 9Number 42003

CONTENTS

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An analysis of economics of investing in IT in themaintenance department: an empirical study in acement factory in TanzaniaE.A.M. Mjema and A.M. Mweta ___________________________________ 411

Application and implementation issues of aframework for costing planned maintenanceMohamed Ali Mirghani __________________________________________ 436

Note from the publisher____________________________ 450

Call for papers ____________________________________ 452

Index to Volume 9, 2003 ___________________________ 453

CONTENTScontinued

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Journal of Quality in MaintenanceEngineeringVol. 9 No. 4, 2003p. 328.# MCB UP Limited1355-2511

EDITORIAL ADVISORY BOARD

Professor Daoud Ait-KadiDirector, Graduate Industrial Engineering Program,Laval University, Quebec, Canada

Dr Khaled S. Al-SultanSystems Engineering Department, King FahdUniversity of Petroleum and Minerals, Dhahran,Saudi Arabia

Professor A.H. ChristerUniversity of Salford, Salford, UK

Dr Ir Patrick De GrooteVice-President, ABB/DGS MaintenanceEngineering, Antwerp, Belgium

Professor B.S. DhillonDirector of Engineering Management Program,University of Ottawa, Ottawa, Canada

Professor V. MakisDepartment of Industrial Engineering, University ofToronto, Toronto, Canada

Professor L. Mann JrDepartment of Industrial Engineering, LouisianaState University, Louisiana, USA

Professor F.G. MillerDepartment of Mechanical Engineering, Universityof Illinois at Chicago, Illinois, USA

Professor D.N.P. MurthyDepartment of Mechanical Engineering, TheUniversity of Queensland, Brisbane, Australia

Professor Dr Liliane PintelonK.U. Leuven, Centre for Industrial Management,Leuven, Belgium

Professor A. RahimFaculty of Administration, University of NewBrunswick, Fredericton, New Brunswick, Canada

Professor Haritha SarangaIndian Institute of Management, Calcutta, India

Professor D. SherwinDepartment of Industrial Engineering,Lund University, Lund, Sweden

Dr Abdel Rahman N. ShuaibMechanical Engineering Department, King FahdUniversity of Petroleum and Minerals, Dhahran,Saudi Arabia

Dr Albert H.C. TsangDepartment of Industrial and Systems Engineering,The Hong Kong Polytechnic University, Kowloon,Hong Kong, China

Professor Hajime YamashinaDepartment of Precision Mechanics, KyotoUniversity, Kyoto, Japan

Towards a value-based view onoperations and maintenanceperformance 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 haverecognized the need to adjust theirmanagement processes, including thoseconcerned with operations and maintenance,to the changed and changing businessconditions in industry at large, particularlydue to the volatile oil price. This has been arationale to review organizational operationsand maintenance policies by many. This paperdescribes findings from a research study onoperations and maintenance performanceconducted in the emerging operatingenvironment with close cooperation ofleading oil and gas organizations in theNorwegian continental shelf. An attempt hasbeen made to develop an architecture foreffective management of operations andmaintenance performance linking results toperformance drivers. This has further beenextended to apply the balanced scorecardconcept. The paper emphasizes the valuerather than the cost of operations andmaintenance in the emerging businessenvironment, and stress that there is a needto move from a plant-based policy to a more orless long-term business-oriented approach.

Adaptive model for vibrationmonitoring of rotating machinerysubject to random deterioration

Y. Zhan, V. Makis and A.K.S. Jardine

Keywords Vibration measurement,Autoregressive processes

Due to the non-stationarity of vibration signalsresulting from either varying operatingconditions or natural deterioration ofmachinery, both the frequency componentsand their magnitudes vary with time. However,little research has been done on the parameterestimation of time-varying multivariate timeseries models based on adaptive filtering theoryfor condition-based maintenance purposes.

This paper proposes a state-space model ofnon-stationary multivariate vibration signalsfor the online estimation of the state of rotatingmachinery using a modified extended Kalmanfiltering algorithm and spectral analysis in thetime-frequency domain. Adaptability andspectral resolution capability of the modelhave been tested by using simulated vibrationsignal with abrupt changes and time-varyingspectral content. The implementation of thismodel to detect machinery deterioration undervarying operating conditions forcondition-based maintenance purposes hasbeen conducted by using real gearboxvibration monitoring signals. Experimentalresults demonstrate that the proposed modelis able to quickly detect the actual state of therotating machinery even under highlynon-stationary conditions with abruptchanges and yield accurate spectralinformation for an early warning of incipientfault in rotating machinery diagnosis. This isachieved through combination with a changedetection statistic in bi-spectral domain.

Design and development of productsupport and maintenance concepts forindustrial 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 affectservice performance, and therefore a productsupport strategy must be defined during designstage, in terms of these two dimensions, toensure the delivery of “promised productperformance” to customers. Furthermore,product support strategy should not only befocused around product, or its operatingcharacteristics, but also on assisting customerswith services that enhance product use and addadditional value to their business processes.This paper examines various issues such asreliability, availability, maintainability, andsupportability (RAMS), etc., which directly orindirectly affect product support, maintenanceneeds and related costs on the basis of a casestudy conducted in a manufacturing company.The main purpose of the study was to analyse

Abstracts andkeywords

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Journal of Quality in MaintenanceEngineering

Vol. 9 No. 4, 2003Abstracts and keywords

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the critical issues related to the product supportand service delivery strategy as being practisedby the company, and to suggest means forimprovements. On the basis of the case study,the paper presents an approach for design anddevelopment of product support andmaintenance concepts for industrial systems ina multinational environment. The paperemphasizes that the strategy for productsupport should not be centred only on“product”, but should also take into accountimportant issues such as the service deliverycapability of the manufacturers, servicesuppliers, the capability of users’ maintenanceorganization, etc.

Integration of RAMS and risk analysisin product design and developmentwork 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 forproducts that meet the functional performanceneeds and have predictable life cycle cost (LCC).Due to design problems and poor productsupport, these systems are not able to meet thecustomers’ requirements. Major causes ofcustomer dissatisfaction are often traced backto unexpected failures, leading to unexpectedcosts. However, with proper consideration ofreliability, availability, maintainability andsupportability (RAMS) in the design,manufacturing, and installation phases, thenumber of failures can be reduced and theirconsequences minimized. Based on a case studyin a manufacturing company, an approach forintegration of RAMS and risk analysis indesign, development and manufacturing ispresented. The importance of LCC analysis,use of feedback information, and integration ofvarious information sources to facilitate easyRAMS implementation, in combination withrisk analysis in the design phase, is discussed.An approach is suggested for integration ofRAMS in the Stage Gate model for project andwork process management, coordination and

control, to reduce risk. A training program,developed and implemented during the study tocreate awareness and to improve learning andunderstanding of RAMS’ aspects of existingand future products and processes, is alsopresented.

An analysis of economics of investing inIT in the maintenance department: anempirical study in a cement factory inTanzania

E.A.M. Mjema and A.M. Mweta

Keywords Maintenance, Computers, Quality

The main objective of this study was to analysethe economics of introducing IT in themaintenance department. The economics inthis case was determined by conducting aquantitative analysis on the reduction ofoperational costs, on increase in productivityand on quality improvement. A comparison wasmade to analyse company performance in themaintenance before and after the introduction ofIT in the maintenance department. The analysisshows that there were reductions of operationaland inventory holding costs. Likewise, it wasshown that there was also improvement inproduct quality and productivity.

Application and implementation issuesof a framework for costing plannedmaintenance

Mohamed Ali Mirghani

Keywords Preventive maintenance,Cost effectiveness, Maintenance costs

This paper develops a case study on theapplication and implementation issues of aframework for costing planned maintenance. Itoutlines the methodology for the developmentof the case study and presents the majorfindings of the existing maintenance-costingsystem of the organization under study. Itpresents the results of a pilot study of theapplication of the proposed costing frameworkto a sample of planned maintenance jobs. Itprovides recommendations and identifiescritical issues for a successful implementation.

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EditorialAbout the Guest Editor Basim Al-Najjar is a Professor of Terotechnology and DepartmentHead of Terotechnology (Systemekonomi) at the School of Industrial Engineering, Vaxjo, Sweden.

The concepts of the available maintenance strategies focus mainly on reducingfailures and their consequences. But, maintaining the condition of machinery tofulfil production requirements demands an efficient maintenance policy thatcan participate in the continuous enhancement of a company’s profitability andcompetitiveness. In order to achieve an effective integration of relevantworking areas it is necessary for maintenance management to select the mostcost-effective maintenance policies, models, performance measures, life-cyclecost and assess maintenance technical and financial impact on the company’sprofitability and competitiveness.

This special issue of the Journal of Quality in Maintenance Engineering isdevoted to the advances, developments and applications of maintenancemanagement, mathematical modelling, performance measure, life-cycle costand maintenance technical and financial impact on the company’s profitabilityand competitiveness. The papers included in this issue are some of the paperspresented at the Conference IFRIM Maintenance Management and Modelling,May 2002, Vaxjo University, Sweden. These selected four papers cover thefollowing topics:

. Describing findings from a research study on operations and maintenanceperformance conducted in the emerging operating environment with closecooperation of leading oil and gas organizations in the Norwegiancontinental shelf. We have made an attempt to develop an architecture foreffective management of operations and maintenance performancelinking results to performance drivers, which has further been extendedto apply the balanced scorecard concept.

. Modelling a state-space model of non-stationary multivariate vibrationsignals for the online estimation of the state of rotating machinery using amodified extended Kalman filtering algorithm and spectral analysis in thetime-frequency domain. In addition, testing adaptability and spectralresolution capability of the model by using simulated vibration signalwith abrupt changes and time-varying spectral content.

. Examination of various issues such as reliability, availability,maintainability, and supportability (RAMS), etc., which directly orindirectly affect product support, maintenance needs and related costs onthe basis of a case study conducted in a manufacturing company. Themain purpose of the study was to analyse the critical issues related to theproduct support and service delivery strategy as being practised by thecompany, and to suggest means for improvements.

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Vol. 9 No. 4, 2003pp. 331-332


. An approach for integration of RAMS and risk analysis in design,development and manufacturing is presented. The importance oflife-cycle cost (LCC) analysis, use of feedback information, andintegration of various information sources to facilitate easy RAMSimplementation, in combination with risk analysis in the design phase, isdiscussed.

The Guest Editor would like to acknowledge the efforts made by ProfessorDavid Sherwin in planning this special issue. The authors’ and the referees’contributions to this issue are highly appreciated.

Basim Al-Najjar

Note from the EditorThe special issue was planned to be exclusively from papers presented atIFRIM conference. The Guest Editor managed to accept four papers fromIFRIM for the special issue. Four papers are not sufficient for the special issueand I have added two papers to complete the issue. Papers 1-4 in this issue arefrom the IFRIM conference and papers number five and six from the regularaccepted pool of papers. Paper number five quantifies the economic benefits ofintroducing information technology (IT) in the maintenance department. Theeconomic benefits have been quantified through quantitative data analysisprior and after introducing IT. The sixth paper presents, through a case study,the application and the implementation issues of a framework for costingplanned maintenance. It outlines the methodology for development of the casestudy and presents the major findings as a result of adopting such a costingsystem.

The Editor acknowledges the authors for their valuable contributions toVolume 9. He is also grateful to all the referees who graciously participated inthe review process. In many situations they made improvements to the papers.The skill and the follow-up made by the Managing Editor of JQME areinstrumental in preparing the volume.

The Rector of King Fahd University of Petroleum and Minerals Dhahran,Saudi Arabia, and his administration are acknowledged for the continuoussupport provided and the excellent facilities made available.

Salih O. Duffuaa

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Towards a value-based view onoperations and maintenanceperformance management

Jayantha P. LiyanageSchool of Science and Technology, Stavanger University College,

Stavanger, Norway, andUday 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 theirmanagement processes, including those concerned with operations and maintenance, to thechanged and changing business conditions in industry at large, particularly due to the volatileoil price. This has been a rationale to review organizational operations and maintenancepolicies by many. This paper describes findings from a research study on operations andmaintenance performance conducted in the emerging operating environment with closecooperation of leading oil and gas organizations in the Norwegian continental shelf. An attempthas been made to develop an architecture for effective management of operations andmaintenance performance linking results to performance drivers. This has further beenextended to apply the balanced scorecard concept. The papers emphasize on the value ratherthan the cost of operations and maintenance in the emerging business environment, andstresses that there is a need to move from a plant-based policy to a more or less long-termbusiness-oriented approach.

Practical implicationsHow operations and maintenance performance (O&M) makes good businesssense has become an important issue lately, and has drawn the attention fromvarious corners of oil and gas (O&G) production business in particular. Thiscalls for a more holistic view of O&M and an appropriate basis to show its linkto the core business. Furthermore, a comprehensive performancfe assessmentsystem has to accommodate a balanced view on overall performance involvingnot only results but also drivers of those results, and also should be able toprovide some understanding about the causal relationships between them. Anotable interest in this regard is to seek ways whereby the popular balancescorecard concept can be applied within O&M process. This paper looks intothese aspects in respect of emerging O&G business environment and elaboratehow O&M becomes a value-added process to the core business, extending ourunderstanding beyond its pure financial implications.

The Emerald Research Register for this journal is available at The current issue and full text archive of this journal is available at

http://www.emeraldinsight.com/researchregister http://www.emeraldinsight.com/1355-2511.htm

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Vol. 9 No. 4, 2003pp. 333-350


DOI 10.1108/13552510310503213

IntroductionAt the current pace of advancement, both in engineering and business,management disciplines coupled with tighter regulatory regimes, performancemanagement 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 petroleumindustry, in particular, is keen on the assurance of proper control of productionassets through application of asset-wide performance measurement systems.Not only operating companies, but also regulatory authorities (e.g. NorwegianPetroleum Directorate, Minerals Management Service (USA), etc.) have takeninteresting initiatives to direct O&G producers’ attention to adaptperformance-based reporting mechanisms for their day-to-day operations. Asthe classical financially-oriented measurement techniques are subjected towider critics in the contemporary business context (Kaplan and Norton, 1996;Sveiby, 1997), we observed that some of the operating companies have alreadyimplemented business-wide O&M performance measurement systems (e.g.Statoil, Norsk Hydro). Many others (e.g. Philips, BP, Shell) have alreadyinitiated internal projects to deal with the problem that best suits their businessconditions. However, owing to inherent limiting conditions within individualorganizational settings these, in general, are relatively far from beingfull-blown managerial practices yet. Furthermore, as O&M in offshore O&Gproduction assets is subjected to a period of transition, potential opportunitiesare enormous for novel and innovative approaches that capture O&Mperformance that makes good business sense.

O&G exploration and production by nature is known to be an economicallyand technologically intensive business. In addition, its social and ecologicalsensitivity is much discussed and debated lately, resulting in an adaptation ofvery cautious operational strategies by O&G producers. Subsequently, currentpractices render adherence to more complex risk-based decision-makingprocesses throughout the O&G production process. As much as risk remainsan inherent element in decision criteria that effectively deals with potentialthreats, asset managers are also seen paying more attention to capitalize onevery single opportunity available to them to get the maximum throughputfrom the asset portfolio for business advantage. For instance, as one of theoffshore platform managers expressed:

. . . in general we rely on drilling technology and reservoir management to get the best fromthe existing reserves. But we are aware about confrontations with economical andtechnological limitations. In order to show that we are competitive in the business and to keepour assets commercially attractive we have to resort to many other potential opportunitiesthat are still left fully un-exploited. One of such disciplines is O&M. We should realise how aneffective asset O&M policy can in fact make a difference in terms of delivery of operatingresults.

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The total-value concept that we introduce in this paper explores thisopportunistic phenomenon and elaborates how O&M can be heightened as avalue-added process to the petroleum business. Our postulations in this regardare grounded on the emerging sustainable O&G business context. Thissustainable move is seemingly pivotal to redefining the business role of O&Mprocess from a different perspective, yet numerous opportunities it has broughtstill remains largely un-exploited. Our underlying assertions in this endeavourstem from the fact that commercial competitivity of O&G business is a productof the extent of threat mitigation and opportunity realization in the emerginguncertain, complex, and dynamic environment for O&G business.

Background and methodologyA joint industry project on the development and implementation of O&Mperformance indicators for the petroleum industry was initiated by the Centrefor Asset and Maintenance Management of Stavanger University College,Norway, in 1999 (see Kumar and Ellingsen, 2000; Ellingsen et al., 2002). Despitethat, this project resulted in a comprehensive application of the balancescorecard concept to measure O&M performance of O&G producers, certainlimitations were inevitable, particularly owing to practical problems pertinentto availability and quality of data in prevailing organizational enterpriseresource planning (ERP) systems. This situation created a need for anindependent and an extended research study to develop a more universal andgeneric theoretical architecture to provide a basis for ongoing efforts withinthis discipline. This paper is based on inferences drawn from an exploratorystudy conducted with the aforementioned scope in the Norwegian petroleumsector during the period of 2000-2002. The study adopted a qualitativemethodology through interviews, discussions, informal conversations, analysisof three industrial cases and various forms of performance-related businessdocumentations. The magnitude of coverage is 72 formal interviews, exclusiveof informal discussions and conversations, that included voluminous and averacity of information from a total of 65 different personnel and study of threecases, covering a total number of 16 distinctive organizations/institutions. Byvirtue of the extent of coverage, the entire study is more comprehensive andcan be characterized as:

. Cross-business. It constitutes views, opinions, and practices from differentbusiness sectors of the petroleum industry. For instance, oil and gasproduction, engineering contractors and suppliers, consultants,certification and verification bodies, and authorities.

. Cross-organizational. Iconstitutes views, opinions, and practices fromdifferent organizations within each of the business sectors. For instance, itcovered 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 havingprofessional expertise on different petro-disciplines with a long-termexposure 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 havingdifferent roles and responsibilities in organizations, varying fromcompany directors, offshore platform managers to maintenanceengineers, who have a direct exposure to numerous practices adoptedby organizations.

Premises for the value-based conceptToday, the language of the petroleum industry clearly signals a managerialtransition to adapt a new decision-making criteria and a course of action;namely, “corporate sustainability” (see, for example, Agbon, 2000; Bradley andHartog, 2000; Hargis, 2000). For instance, Wolff et al. (2000) reveal that thecurrently adopted criteria for investment decisions are not exclusivelyeconomic in nature, but also take into account social and environmentalconsiderations in appraisal of the security of investments. They also contend,for instance, that the indicator called “consideration of environmental andsocial criteria in business decisions” captures management programmes andprocesses aimed at describing the management system’s capability to linksustainability issues to business decision-making criteria for operations andplanning, and that green accounting, eco-efficiency measures, total costassessment, and so on, illustrate further examples.

Although the term “corporate sustainability” may convey a difference inmeaning to many, prevailing myths around sustainability in general advocatesquite a blend of economy and technology; ecology and demography; andgovernance and equity. In O&G business context today this mainly revolvesaround:

. economical values that rest on the degree of financial accountabilitiesdisplayed;

. social values that rest on the degree of social equity displayed; and

. environmental values that rest on the degree of environmental caredisplayed.

The degree to which O&G operators are opted to this new business normthat, in turn, re-defines delivery obligations, is largely reflected in the currentbusiness reporting process. It has explicitly adopted a “triple-bottomline”concept (see Elkington, 1997) over the last few years. For instance, in 1996, aproject consortium comprising Statoil, BP, Conoco, and Shell developed abenchmarking portal to review how companies in the O&G business deal

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with the issue of sustainable development (Wolff et al., 2000). This portalprimarily constituted five target areas; namely, ethics/corporate core values,community capacity building, stakeholder relations, environmentalmanagement, and economics, that have to be achieved through variousinternal business drivers.

The current trend can be seen as a genuine response to an exposure to acomplex profile of risks, and the organizational adaptation to the new worldorder. 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 ofvalue creation and risk mitigation in the emerging sustainable O&G businesscontext. The prevailing business environment seemingly is relatively morefertile to much of this transition. Despite the absence of consistent economicaltheories to directly account business impact of social and environment-relateddeliveries, there remains a large body of corroborative evidence from variouscorners of the O&G industry at large about the existing forces that are strongenough to sustain the current momentum. Some of the notable contributionsinclude:

. global compact concept initiated by UN;

. Dow Jones Sustainability Group Index (DJSGI);

. double decade sustainability road map developed by UK OffshoreOperators Association;

. value reporting technique advocated by PricewaterhouseCoopers; and

. sustainable development management framework adopted by RoyalDutch Shell.

Our new concept, termed “value-based management of O&M performance”,discussed in this paper, is developed on the basis of empirical evidence fromthis emerging operating environment for the O&G industry. At the core ofexpositions there remains the theoretical value configuration of the O&Mprocess as the point of departure with respect to these changing industrialdemographics.

First, we assert that many recent initiatives and incidents within the O&Gindustry or the organizational behaviour at large, unveil that the formula forcommercial success in the current business economy constitutes a delicatebalance 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 businessin general to arrive at such a commercial success today can in fact be said to betwo-fold:

(1) Accountable values. The tools for financial managers or accountants toreport performance in monetary terms, e.g. cost savings, productionvolume, cycle time, proved reserves, etc.

(2) Non-accountable values. These cannot be presented in monetary termsyet posses a finite value in terms of meeting business prospects andprofit margins, e.g. cross-trained labour, intellectual capital, increasedwork morale, enhanced job satisfaction, customer loyalty, reputation, etc.

These values presumably are combined in complex patterns to deliver end resultsand subsequently to business prosperity. The corroborative facts gathered andinsights of informants captured during the study were substantial to unfold thiscomplexity to a considerable degree. The resulting theoretical causal configurationthat underlie the value-based concept of O&Mperformance is illustrated in Figure 1.

The working algorithm illustrated here displays a top-down flow thatincorporates a particular logic, where neighbouring levels are knitted usingspecific causal presumptions. This causal algorithm results in the developmentof the steering model that constitutes four key areas, each with a unique valueproposition of its own. These value propositions form the corner-stones of thevalue-based concept, and are placed in the particular order as illustrated inFigure 1, so that it provides a clear view about the important components of thevalue-added O&M performance.

Figure 1.Theoreticalconfiguration of thevalue based O&Mperformance concept

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Moreover, this brings the term value into a broader perspective in comparisonto its relatively stringent application within financial expressions (see, forexample, Porter, 1985; Knight, 1998; Perry and Starr, 2001). Figure 2 illustratessuch 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 incurrent economical schools.

How it applies to an O&G production assetUnfolding the inherent complexity of O&M performance further, and anyelaboration on the constituents of the steering model for a more universalarchitecture call for a better insight into the O&M process and into theenvironment within which it exists. It implies that we need to develop anadequate level of prior knowledge regarding the role and characteristics of theO&M process and the nature of its interface with the operating environmentand the core business. This calls for more detailed analysis that can beaccomplished 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 withboth business policies and asset condition in a given operatingenvironment. Here we follow through a vertical assessment.

. Lateral integration. The degree to which the O&M process is sensitive tochanges in its environment and to work management policies in otherparallel processes. Here we follow through a lateral assessment.

. Self-assessment and improvement. The degree to which the O&M processhas identified its role and has defined resource, competence, andcapability requirements according to their criticality on the processperformance and thus on plant health. Here we follow through aself-assessment.

Figure 2.Value-based

management ineconomical perspective


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In principle, this is meant to portray the level of interactivity and dependence ofthe O&M process in an O&G production environment. The understanding ofthese dependencies are important insofar as they contribute to our knowledgeto unfold inherent complexities of O&M performance, and then to define itscausal performance model within a given setting. In general, this relationalenvironment within an offshore O&G production facility can be classified intofour classes with respect to the nature and the potential influence (see Figure 3).

Administrative services here refer to finance and accounts, secretarial, officeequipment, accommodation facilities, catering, etc., where finance andaccounts, in principle, concerns salaries and wages, bonuses, insurance andcompensation schemes and the like. Typical human resource servicesencapsulate, 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 thesesources on the O&M process can, in fact, take many facets and can ramifyacross various corners and in different forms, they in principle, are meant tonurture three important domains that contribute to the quality and standard ofO&M performance:

(1) operations/work management process to institutionalise green activity,operational intelligence, and supply integrity with the purpose ofbuilding an effective operational interface;

(2) technology management process to establish technical worthiness of theasset with the purpose of building an effective technological interface;and

(3) human resource management process to develop human capital with thepurpose of building an effective human interface.

Green activity in general concerns whether all specifications pertaining to theset of scheduled activities have adequately been met, and thus qualify forimmediate execution in offshore installations. The term intelligence here

Figure 3.The level of interactivityand dependence of theO&M process in an O&Gproduction assetcontribute to itsperformance complexity

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implies the ability to understand, learn, and make judgments or have opinionsthat are based on facts from the interactive environment, and worthinessimplies suitability to be used, operated or put into function in accordance withpre-defined specifications. They seemingly are considered to be increasinglycritical to sustain an efficient and effective O&M support in the NorwegianO&G sector. They remain centrally focussed as it is known that they directlycontribute to the health of those offshore assets. Health here implies theinherent condition of an offshore installation and the degree to which it is freeof faults and failures, or the state of being well to ascertain safe and soundoperations. There are two core aspects that elucidate this health issue fromO&M point of view:

(1) quality and standard of O&M activities; and

(2) safe and sound technical functions of technical items compatible withoperational specifications.

In fact, the competence that O&G producers develop within these areas isadvantageous insofar as they make a difference in terms of end results from theasset portfolio. The current offshore production environment insists that thefollowing results are contingent on the quality and standard of O&M supportand 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 betterunderstanding and knowledge on O&M performance to pool necessaryresources and to develop core competences central to drive those results.Regardless that different organizations attempt to deploy different strategies tobuild an adequate level of proficiency in this endeavour in accordance withindividual business conditions, a review of underlying matters in focus andmore recent initiatives unveiled that those strategies constitute quite commonelements. Some of the notable ones are illustrated in Table I.

On the basis of these elaborations the generic theoretical O&M performancearchitecture 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 anyproduction asset, as they could occur in a random and abrupt manner. Hence,there are notable hands-out events or occurrences that remain beyond O&Mcontrol, 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 handlingagent (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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Interface Premise Focus/initiatives

Human Administrative andorganizational proficiency

Creating a stimulating work cultureCreating a strong social environment to buildhealthy relationships and teamworkEstablishing a support pool of disciplinaryexpertsPromotion of employee physiological andpsychological health

Operational Operations/work managementproficiency

Systematic employee competence assessmentcomplying with task specificationsMastering IT platforms for effectiveinformation managementDeveloping intellectual capital by allnecessary meansSustaining process integrity and pursuit ofinternal disciplinePromoting strategic partnerships

Technological Technical and EPCICa

proficiencyBuilding systematic means for qualifyingapplication technologyAssuring quality of technical support processand quality of productsBeing innovative in developing technologicalsolutionsExtracting the best technical knowledge fromrepositories and experience transfer tosubstantiate engineering projects

Note: a The term EPCIC here stands for engineering, procurement, construction, installation andcommissioning process

Table I.The most recentinitiatives by O&Gproducers to strengthentriple-interfaces

Figure 4.The theoreticalarchitecture ofvalue-based O&Mperformancemanagement conceptapplied to an O&Gproduction asset

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degradation due to such variations encompass corrosion in pipes that mayremain undetected over an extended period of time, and this is reportedly saidto occur even under thick insulation. In addition, there can be some operationalimpediments such as extreme weather conditions, industrial disputes,terrorists threats, etc., that directly impact installation health affecting, forinstance, activity carrying level or increasing backlog. Those mostly remainnon-amenable to generic O&M policies and may sometimes carry surprises forday-to-day performance and, importantly, successful confrontation of themcalls for adequate contingency planning.

Regarding “lags” and “leads” or “outcome measures” and “performancedrivers”, there are still notable ambiguities as to what in fact they embody inO&M management context. As the proponents of the popular concept“balanced scorecard” advocate (Kaplan and Norton, 1996), outcome measuresare to reflect common goals of a multiplicity of strategies, while performancedrivers tend to own a sense of uniqueness for the process in question byprovision of some opportunities to arrive at desired outcomes. Therefore, theyin combination define the path for delivery of results. In Figure 4, performancelags imply what O&M process is accountable to deliver, and performance leadsimply the core constituents in the pathway to meet those deliveryresponsibilities efficiently and effectively.

Notably, both social and environmental aspects further generate economicalconsequences.

Value-based concept in global viewIn general, we emphasize that the value-based concept elaborated herecompliments four popular movements today:

(1) Total quality school. This recognizes that meeting delivery expectationsis 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 acrosseconomical, social, and environmental imperatives (e.g. Bank, 1992;Faure and Faure, 1992; Beckford, 1998).

(2) Systems school. The systems school in one avenue recognizes thatperformance is a function of the joint operation of social and technicalsystems, and in another recognizes continuous interaction of a systemwith its environment as a basis for evolution. It further advocatesintegrity 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 horizontalworkflows, and strengthening internal interactions and interfacing, andavoidance 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 totalreliance on pure financial or result-based measures, and hence the needfor assessing overall performance in a financially and non-financiallybalanced perspective. Another contemporary avenue is the significanceof intangible assets (Kaplan and Norton, 1992; Sveiby, 1997).

However, importantly, a full-scale application of the value-based concept callsfor a rich infrastructure, and an organizational culture that promotes theabsorption of the subject matter and its reception as an effective tool to manageperformance. Two issues in particular are vital in this regard:

(1) Responsibility, i.e. given that all processes in the asset embark oncommon goals on economics (CAPEX, OPEX, and production orrevenue) and health, safety and environment, and that O&M has limitedaccountability on overall asset performance, it is a requisite to analysethe system in its entirety and pre-define what responsibilities areassigned to O&M process owners and the scope and scale of such anassignment.

(2) Authority, i.e. whether necessary and essential authority has beendelegated to those O&M process owners to make decisions and takeactions in respect of the responsibilities assigned, and that anylimitations imposed in this respect is clearly defined.

For instance, as revealed by a chief maintenance engineer for a core productionarea that comprises three major offshore oil production platforms, and who hashands-on experience as a principle co-ordinator for development andimplementation of a performance management and review system for one ofthe O&G producers:

. . . a major hurdle we had to jump over was regarding the responsibility and authority. Bydeveloping the performance measurement system we have clearly defined what ourresponsibilities are. To make sure that we deliver what we are bound, we stressed that weneed authority. What we said was “if we have these responsibilities and if someone else willhave the authority then we are not accountable for any failure to meet our targets andobjectives. If you want us to take responsibilities to deliver results that we are bound todeliver we have to be clear about our authority, and for that matter you have to delegatenecessary authority effective for our results” . . . Achieving this status has not been sosmooth. We continued to attempt through loads of information, defining responsibilities, andsetting of ground rules to follow. For instance, we had to remind asset managers whenever hetake technical issues to discuss with production people. In fact we had to “arrest” him in anumber 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) perspectiveThe concept of balanced BSC was introduced by Kaplan and Norton (1992).There are two other contemporary concepts that were readily embraced as part

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of the same wave; namely, intangible asset monitor (Sveiby, 1997), andintellectual capital (Edvinson and Malone, 1997). The central theme of thispopular wave, which re-engineered and revitalised long-lasted performancetheories is the necessity to see beyond mere financial performance owing toinadequacy of financial measures alone to help guide business success inemerging highly competitive conditions. Seemingly, the application of the BSCconcept that has earned the respect of performance theorists comprises twogenuine 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 aview on non-financial performance, identifying outcome measures andperformance drivers, and building causal relationships.

With its increasing popularity, some have attempted to devise BSCs for O&Min the recent past (see, for example, Tsang and Brown, 1998; Ahlmann, 1999;Liyanage and Kumar, 2000b; Ellingsen et al., 2002). Despite that BSC hascreated many success stories encompassing the organization’s corporatevision, certain ambiguities come to the forefront pertinent to the extent ofcoverage in the framework. The accompanying ambiguities relevant to O&Gbusiness and O&M of O&G production assets have been discussed by authorselsewhere (see Liyanage and Kumar, 2001). Furthermore, Neely and Adams(2001) contend that BSC describes a causal model for enhancing financialreturns alone (more importantly, pure shareholder value) disregarding the restof the stakeholders who matter for commercial success of the business.Ellingsen et al. (2002) have set an example as to how this framework should berefined by adopting a different set of perspectives; namely, cost, operations,organization, and health and safety environment, paying proper attention onthe most predominant conditions within the O&G business. Perhaps thisambiguity may largely be attributed to semantics, or rather to the fact that theideology that the proponents intended to convey may have been subsumed inthe entire terminology that underpins the concept but have some genuine socialmeanings, less in context relative to implications within BSC. However, it isworth noting that the petroleum sector is seemingly attracted to embracetempting arguments promoted in the BSC concept.

Owing to the above, we insist that the application of BSC to O&M process isworthwhile seeing it as a matter of more than just finding “who the customerfor O&M is” that often point the finger to production. The message in principleis 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 onend results, and thus on the bulk of stakeholders of O&G business activity.This is to entail a fundamental change in the underlying assumptions aboutO&M performance for the better. Figure 5 illustrates how we make use of thelogic of the BSC and an adopted version of its original framework to build thevalue-based concept for O&M performance highlighted in Figure 4.

Notably, we here insist on the overall results rather than cost cutting orcontrolling operational expenses that in one way has led to demark O&M as amere cost centre. Such pure cost-based views also led to cutting corners that, infact, can be a multi-billion dollar deal; for instance, as exemplified by the sunkP-36 offshore oil production platform in deep Brazilian waters recently.

Moreover, we assert the fact that sustainable conduct appeals to adapting anoptimal criterion for the co-existence of business and its wider stakeholders,and, in the same note, opportunities for O&M in this emerging businessconditions are wide open, yet still remains largely unexploited. We are hopefulthat the time and circumstances will get us there.

ImplementationAs mentioned previously, the background for this research study was set bythe joint industry project on development and implementation of O&Mperformance indicators for the petroleum industry. The overall results fromthis project were based on custom practices from individual O&G producers,that captured experience from some of the performance measurement systemsalready being initiated, and learned through discussions and sharing ofinformation by major players in the Norwegian continental shelf to lay the

Figure 5.How balanced scorecardis applied within thevalue-based concept

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foundation for a standard practice. Even though a consensus was reached bythe members of the project consortium about the framework and the contenttherein, some practical difficulties emerged once the implementation phase wasreached. The organizations targeted for implementation were not adequatelyprepared to absorb the change and for immediate implementation of projectresults. These bottlenecks mainly related to the infrastructure required. Someof the major ones included:

. Data. Data available in ERP systems were not quality assured, and manyof the data required for computation of indicators were not part of theformal reporting practices. Furthermore, even mining for some of theavailable data require extensive time and energy in most cases. Moreover,searching through various sources makes it a more tedious task. This alsobrought in the issue of insufficient configuration of IT systems tofacilitate systematic means for data storage, retrieval, sharing, anddecision support.

. Competence and business setting. It was clear that the offshore O&Mcrews require some training and education on the subject and on thetechnical content of measures. Such a commitment was not forthcomingnor feasible due to business situations (e.g. many had not fully recoveredfrom economical impact of low oil price) and, subsequently, prioritieswere seen lying elsewhere.

. Buying-in and culture. Owing to the above reasons, in conjunction withattitude and prevailing scepticism on the actual internal use of measuresto support asset decisions, there were difficulties to buying-in offshoreleaders and O&M crews to run a pilot study. It appears that variouschanges, which bombard offshore facilities as innovative solutions, orfavourites of the week, from time to time without yielding appreciableresults, have contributed to a culture that is mostly cautious andnon-appreciative of novel products.

For instance, as Ellingsen et al. (2002) note, the more closely a project of thisnature approaches implementation phase it becomes more difficult to reachcommon consensus among several participants. Each end user at the endprefers to adopt his own unique approach that is most compatible with internalstrategies and work practices. However, the story does not end there. Processowners still keep the momentum, awaiting opportunities to launch themeasurement framework fully or partially depending on internal requirementsand in consultation with offshore teams. This obviously requires time andpatience. Along with such organizational initiatives, we look forward tolaunching the next phase of the project aimed at a standardized reportingstructure for O&M performance and a Web-based benchmarking portal. Yet, itis a matter of time and circumstances.


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ConclusionEmerging O&G business conditions are seemingly more promising to heightenO&M as a critical constituent of the core business process, yet the recognitionof its full-blown potential calls for novel concepts that are more appealing to themanagement, and promotional campaigns to change the mindset in general. Inthis paper, we elaborated that the changing conditions in the O&G businesscan be seen more inclined to adapt a new course for decision making and actiontaking along corporate sustainability that emphasises wider economical, social,and environmental imperatives of business conduct. In this paper, weintroduced the value-based concept of O&M performance providing a basis toredefine the business role of O&M process in production assets in thisemerging business environment. We also discussed how the popular BSCconcept can be meaningfully used to develop an architecture for O&Mperformance management process. Overall, our continuous attempt is toexplore the subject matter and promote O&M as a value-added process in theemerging O&G business environment.

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Garvin, D.A. (1995), “Leveraging processes for strategic advantage: a roundtable with Xerox’sAllaire, USAA’s Herres, Smithkline Beecham’s Leschly, and Pepsi’s Weatherup”, HarvardBusiness Review, September-October, pp. 76-92.

Hargis, P.D. (2000), “Balancing sustainable offshore production with onshore social andenvironmental issues in Central California”, paper presented at the SPE InternationalConference on Health, Safety, and the Environment in Oil and Gas Exploration andProduction, paper SPE, 61109, available at: www.spe.org

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Kumar, U. and Ellingsen, H.P. (2000), “Development and implementation of maintenanceperformance indicators for the Norwegian oil and gas industry”, Proceedings of theEuromaintenance-2000 Conference, pp. 221-6.

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Adaptive model for vibrationmonitoring of rotating

machinery subject to randomdeterioration

Y. Zhan, V. Makis and A.K.S. JardineDepartment 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 operatingconditions or natural deterioration of machinery, both the frequency components and theirmagnitudes vary with time. However, little research has been done on the parameter estimation oftime-varying multivariate time series models based on adaptive filtering theory for condition-basedmaintenance purposes. This paper proposes a state-space model of non-stationary multivariatevibration signals for the online estimation of the state of rotating machinery using a modifiedextended Kalman filtering algorithm and spectral analysis in the time-frequency domain.Adaptability and spectral resolution capability of the model have been tested by using simulatedvibration signal with abrupt changes and time-varying spectral content. The implementation of thismodel to detect machinery deterioration under varying operating conditions for condition-basedmaintenance 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 ofthe rotating machinery even under highly non-stationary conditions with abrupt changes and yieldaccurate 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 implicationsThis paper presents an online diagnostic technique for evaluating the state ofgearbox systems under varying operating conditions. The proposed techniquewill be useful for practitioners working in the area of vibration monitoring tomake more accurate state analysis in comparison with conventional techniquessince it, above all, takes advantage of spectral information from time-frequencyrepresentations yielded by high-resolution parametric modeling with the aid ofadvanced adaptive filtering algorithm and then provides a robust approachwhich is exempt from the influence of varying operating conditions.



The authors are most grateful to the Applied Research Laboratory at Penn State University andthe Department of the Navy, Office of the Chief of Naval Research (ONR) for providing the dataused to develop this work. They also thank Bob Luby at PricewaterhouseCoopers and MurrayWiseman in the CBM Lab at the University of Toronto for their support. This work has beensupported by the Natural Science and Engineering Research Council of Canada. The authorswish to thank NSERC for their financial support.

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Vol. 9 No. 4, 2003pp. 351-375


DOI 10.1108/13552510310503222

1. IntroductionThe objective of any manufacturing process is the efficient production of a partwith specific shape, with acceptable dimensional accuracy and surface quality.Deviation of the machine conditions from a prescribed plan may influence thefinal part quality and must be examined in detail by the experienced operator.Global competition and the current economic conditions have forced manymanufacturing organizations to improve product quality and cut productioncosts at the same time. The requirements for increased plant productivity, safety,and reduced maintenance costs, have led to a growth in popularity of methodsfor condition monitoring to aid the planning of plant preventive maintenance andoperational policies (Christer et al., 1997). Increased use of automation, althoughreduces the burden on machine operators and the risk of human error, rendersthe production process more vulnerable to various kinds of faults. Theunscheduled breakdown may trigger substantial economic loss due to the highcost of restoring equipment to an operable condition under a crisis situation, thesecondary damage and safety/health hazards inflicted by the failure and thepenalty associated with lost production (Tsang, 1995). Therefore, an effectivecondition-based maintenance system should be capable of monitoring theoperating conditions of machinery, issuing advanced warnings of possible faults,predicting the life span of a defective machine component prior to a fatalbreakdown, and thus reducing unscheduled production shutdowns. However, inthe applications of condition monitoring and fault diagnosis techniques to manymechanical systems, the component of interest is often inaccessible and cannotbe observed or measured directly. Therefore, to determine the condition ofinaccessible components of an operating machine, the only possible course ofaction is to measure at a remote station some related signal, say vibrationsignals, which carry a great deal of information describing the condition of thecomponent. Hence, vibration monitoring presents a unique and appealing meansto conduct condition monitoring and offers significant rewards due to economicbenefits that accrue from its effectiveness. It has been investigated extensively ina 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 onsignals to make some aspects of them easier to detect and quantify to assist indiagnosis. The fast Fourier spectral analysis based on the assumption ofstationary property of vibration signals conceals the time-domain information,which, however, is especially relevant to the time-varying vibration signals ofrotating machinery. Machine vibration signals often demonstrate a highlynon-stationary and transient nature and carry small yet informativecomponents embedded in larger repetitive signals due to external varyingoperating conditions and internal natural deterioration characteristics ofmachinery. The time-frequency representation, which describes how thespectral content of a signal changes over time, has received considerable

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attention for analysing time-varying vibration signals. Recently, the techniquesof time series modelling (AR, MA and ARMA, etc.), known as high resolutionparametric spectrum analysis methods, have been applied to vibration signalsanalysis of rotating machinery by using time-invariant coefficients (Dron et al.,1998; Baillie and Mathew, 1996; Mechefske and Mathew, 1992). Taking intoaccount the reality that a multiple sensor-based machine vibration monitoringsystem, which leads to the multivariate feature of vibration signals, is usuallydesired for reliability purposes, a multivariate model is more realistic anddemanded. The vector autoregressive model (VAR) is usually preferred since itis the best compromise between temporal representation and speed, efficiencyand simplicity of algorithms enabling the estimation of model parameters. Inpractice, the spectrum of ARMA process could even be represented purely interms of the AR coefficients without resort to compute the MA coefficients. Inview of the time-varying frequency components and magnitudes ofnon-stationary multivariate vibration signals, it is therefore natural toassume the coefficient matrices of the VAR model to be time-varying. Up tonow, only little attention has been focused on time-varying VAR models wherethe evolution law of time-varying coefficients is assumed to be stochastic(Arnold et al., 1998), whereas the parameter estimation of time-varyingmultivariate time series models based on adaptive filtering theory for timelymaking maintenance decisions is rarely investigated. A few articles presentedrelevant work conducted in this issue, but confined to conventional filteringtheory or scalar cases (Christer et al., 1997; Arnold et al., 1998; etc.). In the lastdecades, it has seen a surge in the development of advanced adaptive filteringalgorithms (Chui et al., 1990; Kung and Hwang, 1991; Ahmed and Radaideh,1994; Wall and Gaston, 1997; Noriega and Pasupathy, 1997; etc.). Our previousstudy addressed in detail the applications of a multivariate noise-adaptiveKalman filter to condition monitoring (Zhan et al., 2002a, b). However, littleresearch has been conducted on the implementation of advanced adaptivefiltering algorithms to condition monitoring. In particular, when furtherassumptions that result in unknown system parameters of state space modelsare made, an adaptive filtering scheme that is able to yield simultaneousestimation of both state vector and system parameters must be employed. Forthis regard, this paper is concerned with a state space representation oftime-varying VAR modelling of non-stationary multivariate vibration signalswhere the system parameters adaptively estimated from vibration data withthe aid of a modified extended Kalman filter (MEKF) proposed by Chui et al.,(1990) since it provides the most suitable algorithmic structure to yieldestimates of state vector and system parameters simultaneously. Consequently,the adaptive estimation of power spectra in time-frequency domain can beconveniently obtained. The model is evaluated by applying to a simulatedtrivariate vibration signal with abrupt changes and implemented to realgearbox vibration signals for detecting deterioration purposes by means of a

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hybrid system combining the proposed MEKF-based time-varying VAR modeland a statistical fault detection approach in bispectral domain.

The remainder of this paper is organized as follows. Section 2 presents the modelformulation with all related algorithms, where section 2.1 illustrates the state spacemodel and modified extended Kalman filtering recursions, section 2.2 is devoted tothe introduction to an innovation-basedmodel check for the proposedmodel, and theadaptive spectral analysis in time-frequency domain is addressed in section 2.3. Insection 3, the proposed model is validated in two aspects: fast adaptation capabilityand high time-frequency resolution by using a simulated signal. A condition-basedmaintenance study of the gearbox by using full lifetime vibration data is presentedin section 4. Some concluding remarks are finally given in section 5.

2. Description of modelIn this section we present a state space model transferred from the VAR modelwith time-dependent coefficients and provide its corresponding recursionalgorithms with the aid of a Kalman filter.

2.1 State space model and Kalman filterA VAR process is a discrete-time multivariate linear stochastic process givenby:

yi ¼Xp

k¼1

Akyi�k þ 1i ð1Þ

for i ¼ 1; 2; . . .;N , that is, the time series can be considered as the output of alinear all-poles filter driven by a white-noise signal with a flat spectrum, whereN is the sample size, p the order of VARmodel, yi the ith measurement vector ofdimension 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 placefrequently due to the maintenance actions imposed on and/or the naturaldeterioration of machinery and that in turn results in the time varying spectralproperties of vibration signatures, taking this into consideration we assume thecoefficient matrices of the above VAR model to be time-varying:

yi ¼Xp

k¼1

AkðiÞyi�k þ 1i: ð2Þ

To make use of the Kalman filtering algorithm, it is necessary to develop astate space representation of the model (2). This can be achieved byrearranging the elements of the matrices of coefficients in vector form using thevec-operator, which stacks the columns of a matrix on top of each other fromthe left to right side. Then, with the following notation:

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ai ¼ vecð½A1ðiÞ;A2ðiÞ. . .;ApðiÞ�TÞ ð3Þ

Yi ¼ ðyTi ; y

Ti�1; . . .; y

Ti�pþ1Þ ð4Þ

Ci ¼ I d^YTi ð5Þ

an appropriate state space representation of the VAR model with stochasticcoefficients can be given by

aiþ1 ¼ f iðaiÞ þ ni ð6Þ

yi ¼ CTi�1ai þ 1i ð7Þ

where ai is the pd 2 £ 1 state vector, ni is an pd 2 £ 1 sequence of zero-meanwhite 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 ofnonlinear forms of the state elements, which can then be processed by theextended Kalman filter (EKF), or of some specific form for convenientcalculation, e.g. Miai, by which EKF is reduced to the linear Kalman filter,and the measurement equation (7) has an adaptive time-varying coefficientCT

i�1 of dimension d£pd 2. We also have a0ð¼ Eða0ÞÞ, the Gaussian pd 2 £ 1initial state vector with covariance matrix P0j0ð¼ Covða0ÞÞ, and the noisecovariance matrices:

E{nknTi } ¼ Qkdk�i ð8Þ

E{1k1Ti } ¼ Rkdk�i 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 Miai þ ni ð10Þ

yi ¼ CTi�1ai þ 1i ð11Þ

is being considered, where, assuming n ¼ pd 2 for simplicity, Mi ¼diag½m1; · · ·;mn� and, as before, ai2R

n, ni2Rn, 1i2R

d , and ni and 1i areuncorrelated Gaussian white noise sequences. Let us assume a vector u torepresent the unknown constant elements mi for i ¼ 1; . . .; n; namelyu ¼ ðm1; . . .;mnÞ

T . The objective is to identify u, which must be treated as arandom vector such as:

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uiþ1 ¼ ui þ zi; ð12Þ

where zi is any zero-mean Gaussian white noise sequence uncorrelated withei and with pre-assigned positive definite covariances CovðziÞ ¼ Wi. Inapplications, we may choose Wi ¼ W for all i. The MEKF introduces avery efficient parallel computational scheme for system parametersidentification (Chui et al., 1990). The modification is achieved by animproved linearization procedure, which results in that the MEKFalgorithm can be applied to real-time system parameter identificationeven for time-varying stochastic systems. The MEKF algorithm consists oftwo sub-systems. Algorithm I, which deals with model (13) and (14) below,is a modification of the extended Kalman filter, where the real-time linearTaylor approximation is not taken at the previous estimate. Instead, inorder to improve the performance, it is taken at the optimal estimate ofstate vector ai given by a standard Kalman filtering algorithm calledAlgorithm II, which deals with model (15) and (16) below. Therefore, thesystem (10) and (11) together with the assumption (12) can be reformulatedas the nonlinear stochastic system:

aiþ1

uiþ1

" #¼

MiðuiÞai

ui

" #þ

ni

zi

" #ð13Þ

yi ¼ ½CTi�1 0 � ð14Þ

ai

ui

" #þ 1i;

to which the Algorithm I can be applied, and subsystem (15) and (16):

aiþ1 ¼ Mið~uiÞai þ ni ð15Þ

yi ¼ CTi�1ai þ 1i; ð16Þ

to which the Algorithm II can be applied. The two algorithms are applied inparallel starting with the same initial estimate, where Algorithm I is used foryielding the estimate ½ ~ai ui �T with input ai�1 obtained from Algorithm II,which is used for yielding the estimate ai with the input ½ ~ai�1 ui�1 �T obtainedfrom Algorithm I. The two-algorithm procedure listed below is called theparallel algorithm.

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Algorithm I. Set:

~a0

~u0

" #¼

Eða0Þ

Eðu0Þ

" #and P0 ¼ Cov

a0

u0

" # !ð17Þ

For i ¼ 1; . . .;N , compute the recursive prediction equations:

Piji�1 ¼›

›

ai�1

ui�1

24

35

Mi�1ð~ui�1Þai�1

~ui�1

24

35

26666664

37777775

Pi�1›

›

ai�1

ui�1

24

35


~ui�1

24

35

26666664

37777775

T

þ Qi�1

ð18Þ

~aiji�1

~uiji�1

" #¼


~ui�1

" #ð19Þ

and the updating equations:

Gi ¼ Piji�1CT

i�1 0h iT

½CTi�1 0 �Piji�1½CT

i�1 0 �T þ Ri�h i�1

ð20Þ

Piji ¼ I � Gi½CTi�1 0 �

h iPiji�1 ð21Þ

~ai

~ui

" #¼

~aiji�1

~uiji�1

" #þ Giðyi � CT

i�1 ~aiji�1Þ; ð22Þ

where Qi ¼ Q1 ¼ Covni

zi

" # !; Ri ¼ Covð1iÞ; and ai�1 is obtained by the

following Algorithm II.

Algorithm II. Set:

a0 ¼ Eða0Þ and P0 ¼ Covða0Þ

For i ¼ 1; . . .;N , compute the recursive prediction equations:

Piji�1 ¼ Mi�1ð~ui�1Þ� �

Pi�1ji�1 Mi�1ð~ui�1Þ� �T

þQi�1 ð23Þ

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aiji�1 ¼ Mi�1ð~ui�1Þai�1 ð24Þ

and the updating equations:

Gi ¼ Piji�1Ci�1 CTi�1Piji�1Ci�1 þ Ri

h i�1ð25Þ

Piji ¼ I � GiCTi�1

h iPiji�1 ð26Þ

ai ¼ aiji�1 þ Gi yi � CTi�1aiji�1

� �; ð27Þ

where Qi ¼ Q2 ¼ CovðviÞ; Ri ¼ Cov(1i), and ~ui�1 is obtained from Algorithm I.However, in order to apply the above MEKF process, we still need an initial

estimate u0 :¼ u0j0, which in fact can be chosen arbitrarily (Chui and Chen,1999). Evidently, the parallelism we have considered here is fundamentallymotivated by the need for an evaluation of the Jacobian matrix of the(nonlinear) vector-valued function Mi�1ðui�1Þai�1 and the prediction term

~aiji�1~uiji�1

h iT

at the optimal position ai�1 at each time instant. The reader of

interest is referred to Chui and Chen (1999) for the discussion of convergence ofthis parallel filtering scheme. A detailed study of array-processor designs forKalman filter can be found (Kung and Hwang, 1991), which proposed anefficient systolic implementation for Kalman filter.

Since the measurement series {yi ; i ¼ 1; 2; . . .;N} are usually notindependent, the likelihood can be decomposed into the product of theconditional distributions of each yi on all its predecessors, if the function f(†)takes some linear form, e.g. Miai, that is:

L ¼YNi¼1

pðyi y1; y2; . . .; yi�1j�

ð28Þ

and the joint distribution of {yi ; i ¼ 1; 2; . . .;N} is multivariate normal since itcan be shown that each observation yi is a linear function of normal randomnoise items. Based on the multivariate normal distribution it follows that thelog-likelihood function for {yi ; i ¼ 1; 2; . . .;N} is given by:

log L ¼ �N

2logð2pÞ �

1

2

XN

i¼1

log Si

�� 1

2

XN

i¼1

zTi S

�1

i zi: ð29Þ

The maximum likelihood method can be used to estimate the values ofparameters. However, it cannot be used to compare different models withoutsome corrections. Therefore, the Akaike Information Criterion (AIC) is appliedto determine the appropriate order value p off-line for VAR models by

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minimizing the information theoretical function of p, AIC( p), which is definedas:

AICðpÞ ¼XN

i¼1

ln Ri

�� þ 2pd 2: ð30Þ

For nonlinear forms of f(†) the log-likelihood estimation (21) cannot be appliedsince the observation yi is no longer a linear function of normal random noises.Therefore, we will have to compare the global performance of models withdifferent order value p based on trial and error in order to determine the optimalone.

2.2 Test for optimalityThe model having been identified and the parameters estimated, diagnosticchecks are then applied to the fitted model. The test to determine whether theinnovations series zi is a white sequence, thus indicating optimum filterbehavior, is based on an estimate Vk of the autocorrelation sequence Vk

(Noriega and Pasupathy, 1997). Data is processed in batches of N samples. Fora given batch, Ns samples of Vk given by:

Vk ¼1

N

XN�1

i¼k

zizTi�k ð31Þ

for k¼0, 1, . . ., Ns21 are calculated (Ns , N). The above is an asymptoticallyunbiased estimate with mean and (approximate) covariance given by:

E{Vk} ¼ ð1 �k

NÞV k ð32Þ

Covð½Vk�i;j; ½Vl�m;nÞ ø1

N

X1t¼�1

ð½V t�i;m½Vtþl�k�j;n þ ½Vtþl�i;n½V t�k�j;mÞ; ð33Þ

where Cov(a, b) ¼ E{[a 2 E{a}] · [b 2 E{b}]}, and [·]i,j denotes the element inrow i and column j of the matrix. The estimate can also be shown to beconsistent because the summation in (33) is finite and asymptotically normal. Itis the Gaussian property of Vk that we use to test for whiteness of theinnovations sequence zi. From the 95 per cent confidence limit test for a randomvariable X with Gaussian distribution:

P{ � X0 # X # X0} ¼ 0:95; for X0 ø 1:96sx: ð34Þ

This can be applied to, for example, elements in the main diagonal of Vk. For zi

a white sequence, from (33) it follows that:

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Covð½Vk�i; j; ½Vl�m;nÞ ¼1

N½V 0�i;m½V 0�j;n; for k ¼ l . 0: ð35Þ

The variance of a diagonal element ½Vk�i;i is then given by

varð½Vk�i;iÞ ¼1

N½V0�

2

i;i; k . 0 ð36Þ

and substituting (36) into (34) results in the limit(s) for the test:

X0 ¼1:96ffiffiffiffi

Np V0

h ii;i: ð37Þ

The actual test is performed by determining the percentage of values of ½Vk�i;ifor k¼1, 2, . . ., Ns21, which fall outside of the range X0. If this is less than 5 percent, then zi is considered white. The test can be done on several of the maindiagonal elements of Vk and simulations have shown good results using thetwo extreme elements (Noriega and Pasupathy, 1997). However, the whitenessof innovations sequence is a sufficient condition only under the assumptionthat transition matrix Mi in (10) is known. When Mi is unknown, an additionalcondition 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 optimalitytesting (Noriega and Pasupathy, 1997).

2.3 Parametric spectral analysis in time-frequency domainIt can be shown that the parametric spectrum of the signal depends on theestimated parameters of time series models. In fact, the relationship is given by:

Pðf Þ ¼PN ðf Þ

jHðf Þj2; ð39Þ

that is, the signal power density spectrum (PDS) depends on what can beexpressed as the product of PN( f), PDS of the white noise (PN( f)¼PNO), andH( f), frequency response of the linear filter. After estimating the coefficientmatrices of the VAR model, an instantaneous estimating of the spectral densityfunction, which in the multivariate case is a matrix valued function offrequency, can be given in terms of the VAR coefficient matrices:

Piðf Þ ¼ ½H�1i ðf Þ�Ri½H

�1i ðf Þ�*; ð40Þ

where the asterisk mark denotes the conjugate complex and:

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Hiðf Þ ¼ I d �Xp

k¼1

AkðiÞe�j2pfTsk: ð41Þ

Autoregressive models sare less dependent on the time window and have oftenbeen used in the estimation of stationary or weakly non-stationary signals. Inorder to use the VAR model for time-frequency analysis, the coefficientmatrices of the model have, therefore, to be adapted to the time-varyingcharacteristics of the signal. The PDS function (41) is adaptive because eachcoefficient matrix Ak is considered to be subject to a stochastic processexpressed by (6) in order to fit the time-varying spectral characteristics of thevibration signals. In this way, the model can, in principle, follow rapidlyvarying spectra because it has an inherently non-stationary structure.Accordingly, the PDS function, expressing the spectrum by using thetime-varying VAR parameters, becomes a function of two variables, time i andfrequency f in the same way as for all time-frequency distributions (Confortoand D’Alessio, 1999).

3. Model evaluation by using simulated vibration dataThis section investigates the performance of the proposed model anddemonstrates the fast adaptation and high spectral resolution capabilities byfiltering one highly non-stationary trivariate vibration signal with abruptchanges and time-varying spectral contents.

We assume that there is presence of abrupt changes in the state of a motoroutboard bearing and therefore a synthetic trivariate bearing vibration signal ismade up of three 341-point signal segments. The motor rotor of these threesegments has a 3,600rpm (60Hz) rotational speed. The sampling frequency andobserved frequency range are 12.821kHz and [0, 5000] Hz, respectively. In orderto show the presence of abrupt changes, the artificially connected trivariatesignal is exhibited in Figure 1, which clearly shows two abrupt changes atsampling points 342 and 683 in each of axial, horizontal and vertical variatesignals, respectively. Our further investigation by means of non-parametrictime-frequency techniques, i.e. short-time Fourier transform, reveals that thesethree signal segments contain rather different dominant frequency componentsand energy distribution, respectively, although they were selected from thesame bearing. Therefore, the simulated signal sets very harsh conditions forevaluating the performance of the proposed model. Figure 2 displays the FFTspectra of the original 1,024-point trivariate vibration signals from which thethird segment [683, 1023] shown in Figure 1 was taken. Extensive tests wereconducted in order to select the most appropriate order value based on the AICand the optimality criterion. Order p ¼ 21 is finally determined. Figure 3demonstrates that the outlier percentages are less than 5 per cent for the firstand second variates (the outlier percentage of the third variate just slightly

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exceeds 5 per cent limit). Further inspection reveals that in each subplot ofFigure 3; namely, the outliers trace by using each diagonal element of Vk, mostoutliers are present only at the initial period of filtering. With the progress offiltering, the presence of outliers exceeding the upper and lower 5 per cent limitsin each subplot of Figure 3 is very quickly ameliorated, although very fewoutliers are present around the sample points of abrupt changes; for instance,sample point 683 in the horizontal subplot of Figure 3. Evidently, all threevariates present fairly stable behavior within the third signal segment [683,1023] as shown in each subplot of Figure 3. The findings from the zero meancheck of innovations sequence as shown in Figure 4 show consistent results

Figure 2.FFT spectra of theoriginal 1,024-pointsignal from which thethird segment [683,1,023]is taken

Figure 1.Simulated trivariatevibration data

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with the findings from Figure 3. Similarly, the most unstable fluctuation of themean of innovations is also present at the initial filtering stage as shown in eachsubplot of Figure 4, where the mean trace of innovations sequence of eachvariate shows a very efficient and rapid tendency to zero with the progress offiltering. The only notable jump taking place at sample point 342 in the axialsubplot of Figure 4 actually does not imply an inferior behavior in comparisonwith the horizontal and vertical subplots of Figure 4, since, by examining itsleftmost scale values, it has the least variation range [20.02, 0.03]. Thus, theoptimality criterion of zero mean innovations sequence is effectively ensured foreach of the axial, horizontal and vertical variates, respectively. In conclusion, theoptimum behavior of filter is guaranteed as defined in section 2.2.

In Figure 5, the adaptive estimation procedures of ten randomly selectedvariates of the state vector ai are plotted. Abrupt changes and correspondingrapid adaptation of the state estimate can obviously be observed around thesampling points 342 and 683, respectively. Estimation errors may exist in thefiltering process within the first segment [1, 341], e.g. Figure 5(j) or the secondsegment [342, 682], e.g. Figure 5(b). Examinations on other variates of the statevector ai were also conducted and show that most variates of ai converge totheir steady state immediately after the first or second segments. Mostimportantly, the time-averaged parametric autospectra of the third signalsegment [683, 1023] as shown in Figure 6 computed by using the proposedMEKF-based time-varying VARmodel are strongly consistent with the spectra

Figure 3.Optimality test for

whitenes assumption ofinnovations sequence

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calculated via FFT as shown in Figure 2, by using the original 1,024-pointvibration data. The correct spectral information proves that the proposedmodel is able to conduct accurate condition analysis of machinery even underhighly non-stationary conditions. Furthermore, in practice, state variations ofmachine components, especially defects of machine components which arecritical to the CBM, usually have a relatively slow onset and would not bepresent and gone in such a sudden manner. As such, the simulated vibrationsignal in this section sets much harsher conditions for evaluating theperformance of the proposed model. However, the artificially introducednon-stationary conditions are, to a great extent, similar to the gearfault-induced non-stationary effects since the damaged teeth of a faulty gearwill also introduce abrupt changes into the spectral contents of the vibrationsignals when they get involved in meshing motion with another gear over eachrevolution. Therefore, this simulation test implies a highly desirableapplicability of the proposed model to deal with gear vibration signals.

4. Application to gearbox vibration monitoring4.1 The object of interestIn order to investigate the performance of the proposed model on real vibrationmonitoring signals, a mechanical diagnostics test-bed (MDTB, see Figure 7)was utilized in this study to provide data on a commercial transmission as itshealth progresses from new to faulted and, finally, to failure. The MDTB isfunctionally a motor-drive-train-generator test stand (Byington and Kozlowski,

Figure 4.Optimality test for thezero mean of innovationssequence

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1997). The gearbox is driven at a set input speed using a 30Hp, 1750rpm ACdrive motor, and the torque is applied by a 75Hp, 1,750rpm AC absorptionmotor. The maximum speed and torque are 3,500rpm and 225ft-lbs,respectively. The speed variation can be accomplished by varying thefrequency to the motor with a digital vector drive unit. However, in this testrun, the shaft speed is kept constant at 1,750rpm. The variation of the torque isaccomplished by a similar vector unit capable of controlling the current outputof the absorption motor. The system speed and torque set points are producedby 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

Figure 5.Randomly selected

dimensions of the statevector ai estimated from

the simulated data

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power that is generated by the absorber is fed back to the driver motor. Themechanical and electrical losses are sustained by a small fraction of wall power.The MDTB has the capability of testing single and double reduction industrialgearboxes with ratios from about 1.2:1 to 6:1. The gearboxes are nominally inthe 5-20Hp range. The system is sized to provide the maximum versatility tospeed and torque settings. The motors provide about two to five times the ratedtorque of the selected gearboxes, and thus the system can provide goodoverload capability. The use of different reduction ratios and gearboxes thanlisted is possible if appropriate consideration to system operation is given. Themotors and gearbox are hard-mounted and aligned on a bedplate. The bedplateis mounted using isolation feet to prevent vibration transmission to the floor.

Figure 7.Mechanical diagnostictest bed

Figure 6.Parametric spectra viathe proposedMEKF-based model

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The shafts are connected with both flexible and rigid couplings.Torque-limiting clutches are used on both sides of the gearbox to preventthe transmission of excessive torque as could occur with gear jam or bearingseizure. In addition, torque cells are used on both sides of the gearbox todirectly monitor the efficiency and the loads transmitted (Byington andKozlowski, 1997). The general gearbox information is shown in Table I.

This test run was conducted with a single reduction helical 1:1.5 ratiogearbox which was run at 100 per cent output torque and Hp for 96 hours thenincreased to 300 per cent torque and Hp until failure. Data were collected inten-second windows at set times and triggered by accelerometer RMSthresholds. Table II presents the brief description of the two operatingconditions. The following data are contained in this test run: single axisaccelerometer sensor (A02-A07), triaxial accelerometer (A10: axial; A11: jj floor;A12: perp floor), external microphone sensor (M01), where the triaxialaccelerometer (A10: axial; A11: jj floor; A12: perp floor) is selected to constructa trivariate time series for filtering. Figure 8 shows the location of the triaxialaccelerometer. There is a total of 83 trivariate data sets for the triaxialaccelerometer, of which 12 were collected under condition No. 1 and 71 undercondition No. 2. The data sets were sampled synchronously, where each dataset contains 200,000 sample points for ten seconds in all.

The triaxial accelerometer is included to determine whether triaxial data canprovide significantly better sensor fusion for gearbox health assessment thanthe single-axis accelerometers. However, the measurement trade-off is that thetriaxial accelerometer possesses a lower frequency bandwidth (8kHz) thansingle-axis accelerometers (20kHz).

Gearbox ID# DS3S015005Make Dodge APGModel R86001Rated input speed (rpm) 1,750Maximum rated output torque (in-lbs) 528Maximum rated input (Hp) 10.0Gear ratio 1.533Contact ratio 2.388Gear mesh frequency of drive gear (Hz) 875.53Gear mesh frequency of pinion gear (Hz) 874.99

Table I.General gearbox

information

ConditionInput speed

(rpm)Output torque

(in-lbs)Power(Hp)

Duration(hours)

No. 1 1,750 540 9.8 96.0No. 2 1,750 1,620 30 31.4

Table II.Two operating

conditions

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4.2 Detection of gearbox deteriorationIn this section, the proposed MEKF-based model is combined with abispectrum-based robust fault detection statistic proposed by Parker et al.(2000) for investigating the deterioration of the gearbox. The objective is toverify whether the proposed model is able to provide accurate spectralinformation in time-frequency domain to machinery fault diagnose viahigher-order spectral analysis. The most commonly used higher-order spectrais the complex-valued bispectrum associated with the third-order cumulant anddefined as:

Bðf 1; f 2Þ ¼ E½Xðf 1ÞXðf 2ÞX�ðf 1 þ f 2Þ�: ð42Þ

where asterisk denotes complex conjugation and X( f) is the Fourier transform ofX(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) isreplaced with the time-varying power spectra generated by the proposedMEKF-based time-varying VAR model. The expectation operator E signifies anaverage over sufficient ensembles. To address the detection statistic, themagnitude-squared bicoherence function obtained by normalization of bispectrum:

bðf 1; f 2Þ ¼1Bðf 1; f 2Þ

1

E½jXðf 1ÞXðf 2Þj2�E½jXðf 1 þ f 2Þj

2�

ð43Þ

Figure 8.Location of triaxialaccelerometer (A10, A11and A12)

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must be quoted. It has been shown in equation (16) that the bicoherencefunction, which is restricted to the range jBðf 1; f 2Þj, is less sensitive to changesin vibration amplitude across varying operating regimes (e.g. torque levels).This is a very important property of bicoherence since it furnishes a robustlocally optimum detection statistic Tlo expressed by:

T lo ¼1#l#kmax

Xk

m¼l

ðbm � b0Þ ð44Þ

which is sensitive to faulty conditions but insensitive to the changes ofoperating regimes, where b0 denotes the pre-change values of b( f1, f2)reflecting the behavior of the machine under normal operating conditions andcan be interpreted as a known quantity that can be readily estimated (Parkeret al., 2000). Therefore, the two techniques specifically effective for processing anon-stationary vibration signal, MEKF-based time-varying VAR model intime-frequency domain and fault detection statistic in bispectral domain, areintegrated in this section for detecting machine deterioration. The principle ofgearbox fault diagnose on which the detection statistic Tlo is based is that thelarge deviation from baseline indicates a fault (Parker et al., 2000). There is atotal of 83 Tlo’s generated from 83 data sets, corresponding to different lifestages from new to breakdown, where the first 12 data sets under operatingcondition 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 forprocessing and only the low-frequency vibrations (e.g. gear meshingfundamental and associated lower sidebands) are used to produce thebicoherence estimates, where f2 is held fixed at f gearmesh ¼ 875Hz and f1 isswept from 20Hz to fgearmesh. Thus, the maximum frequency to be considered is2 £ f gearmesh which is equal to 1,750Hz.

In order to ensure the applicability and effectiveness of the proposed hybriddiagnostic system, a number of assumptions are required:

(1) the maximum frequency of interest is lower than the half bandwidth ofaccelerometers whose signals are to be analyzed according to Nyquisttheory;

(2) the geometric imperfections or assembly errors of gears in meshingmotion 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 undercondition No. 1; and

(4) the considered frequency range for computing time-frequencyrepresentations contains sufficient spectral information for evaluatingthe deterioration of the gear of interest.

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As mentioned in section 4.1, the frequency bandwidth of the triaxialaccelerometer is 8kHz. According to the Nyquist theory, the effectivefrequency bandwidth is 4kHz for eliminating aliasing, which is large enoughfor the following analysis, since it is larger than 1,750Hz as required by theabove assumption (1). Furthermore, according to the notations in the originaldata CD of test-run TR No. 5, the tested gearbox did not show any abnormalsymptom during its initial lifetime. As such, it is believed that the inevitablegeometric imperfections or assembly errors of meshing gears do not havenotable negative effects on the sampled vibration signals. This is consistentwith the requirement of assumption (2). In addition, based on the analysis ofMiller (1999) who investigated the state evolution of TR No. 5, the gearboxis constantly in its healthy state under condition No. 2. Therefore, it iseligible to compute b0 using the first 12 data sets under condition No. 1.This is also consistent with the requirement of assumption (3). Since onlythe gear meshing fundamental and associated lower sidebands that result inthe maximum frequency of interest 1,750Hz are considered in order to reducecomputational requirements, it is therefore mandatory to obtain sufficientspectral information regarding the state evolution of the driven gear ofinterest. This condition can be satisfied, since gear meshing fundamentaland its lower sidebands are typically characteristic defect frequencies andalso the most dominant spectral area which contains most energy of gearmeshing motion, although partial spectral information beyond 1,750Hz isignored. Thus, assumption (4) is valid.

The normalized contour plots of Tlo of the trivariate time series with orderp ¼ 21 are illustrated in Figure 9(a) and (b) for A10 and A11 only, which showthe Tlo progressions evaluated over 83 data sets. It can be seen that in bothFigure 9(a) and (b) there is no visible demarcation line at data set 13 where thechange of operating condition takes place. This, to some extent justifies theinsensitiveness of the detection statistic Tlo to variation of operatingconditions. Though, the Tlo plot of A11 is unlikely to represent trueevolution of the gearbox’s state since it is against the findings of post-failurecheckup (Byington and Kozlowski, 1997). The abnormal Tlo plot of A11 may bedue to the poor quality of the collected vibration signal as denoted in theoriginal data CD. Notwithstanding, the Tlo plot of A10 presents a verysatisfactory illustration of the deterioration process. As a matter of fact, thisfinding 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 mostdesirable results in describing the state evolution of the gear of interest.Furthermore, Miller (1999) indicated in his research thesis that accelerometersmounted in axial direction are able to give signals with best quality. Thisfurther confirms our finding in the present study. By checking the intensitylevel of the shaded area in Figure 9(a), detectable symptom of incipient fault ofthe gearbox can be observed around data sets 25/26. A notable jump is present

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between data sets 40 and 50. This is consistent with the RMS trace of A04 asshown in Figure 10(b), while RMS trace of A02 shown in Figure 10(a) presents agradual increment around data set 40 which is slightly earlier than that of RMStrace of A04. Thereafter, this infantile faulty state develops gradually andcontinuously until data sets 61/62 approximately, becomes more serious afterdata set 68 and remains the faulty state until data set 83, where the RMS levelsof 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 ofA10’s Tlo plot, the Tlo plots of A02 and A03 obtained by making use of theNAKF model proposed in our previous studies (Zhan et al., 2002a, b) are quotedin Figures 11(a) and (b), respectively. Both Figures 11(a) and (b) suggest thatthe gear tooth defect initiates around data set 28 approximately, shows anotable jump between data sets 40 and 50 and keeps a slow developing

Figure 9.Tlo Contour plots of

accelerometers A10 andA11, respectively

(MEKF-based model)

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tendency till data set 62 and thereafter, there is a rapid degradation period fromdata set 62 to 68, which gives a five-hour earlier warning than the RMS methodas shown in Figure 10 which presents a quite fast growing duration of faultystate within data set range [73, 83] in both Figure 10(a) and (b). After data set68, the gearbox goes quickly to breakdown. Evidently, the result of A10 is wellconsistent with the findings of A02 and A03. Comparing Figure 9(a) withFigure 10, it is evident that the Tlo method, by making use of the accuratespectral information provided by the proposed MEKF-based model, is superiorto the conventional RMS method with respect to two regards. First, the RMSmethod 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 forincipient fault of rotating machinery. This is very significant for industrial

Figure 10.RMS signal strength ofaccelerometers A02 andA04 vs datasets

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practices, in that it provides sufficient warning for timely scheduling necessarymaintenance activities and, therefore, avoiding catastrophic failures.

5. ConclusionsIn this paper, a modified extended Kalman filter is applied to processnon-stationary multivariate vibration monitoring signals fitted by a state spacerepresentation of time-varying VAR model. The performance of the proposedmodel has been evaluated by using simulated and true online vibration signalsin two aspects: adaptation capability and spectral resolution capability intime-frequency domain. Results show that the proposed model is able toquickly converge to the steady state and generate precise spectral informationeven under highly non-stationary conditions with abrupt changes, as well asproviding an adaptive fashion for on-line vibration monitoring. It is noteworthy

Figure 11.Tlo Contour plots of

accelerometers A02 andA03, respectively

(NAKF-based model)

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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 shortduration and, thus, furnishes very harsh conditions for evaluating theperformance of the proposed MEKF-based time-varying VAR model. Thisartificially introduced non-stationary property is to a great extent similar to thegear fault-induced non-stationary effects, since the damaged teeth of a faultygear will also introduce abrupt changes into the spectral contents of vibrationsignals when they get involved in meshing motion with another gear over eachrevolution. The simulation results show highly desirable properties of theproposed model with respect to the adaptability and accuracy of the resultingspectra. The proposed model was then implemented to provide onlinetime-averaged spectral domain information to make CBM decisions of thegearbox. The implementation demonstrates that it is capable of yieldingaccurate frequency-domain information for scheduling correct onlinemaintenance decisions.

References

Ahmed, N.U. and Radaideh, S.M. (1994), “Modified extended Kalman filtering”, IEEETransactions 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 ofnonstationary time series by means of Kalman filtering”, IEEE Transactions onBiomedical Engineering, Vol. 45 No. 5, pp. 553-62.

Baillie, D.C. and Mathew, J. (1996), “A comparison of autoregressive modeling techniques forfault 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 remaininguseful life”, Mechanical Diagnostic Test Bed (MDTB) Data (CD-ROMs: Test Run TR#5),Condition-Based Maintenance Department, Applied Research Laboratory, ThePennsylvania State University.

Christer, A.H., Wang, W. and Sharp, J.M. (1997), “A state space condition monitoring model forfurnace 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-timeparallel algorithm for system parameter identification”, IEEE Transactions on AutomaticControl, Vol. 35, pp. 100-4.

Conforto, S. and D’Alessio, T. (1999), “Spectral analysis for non-stationary signals frommechanical measurements: a parametric approach”, Mechanical Systems and SignalProcessing, Vol. 13 No. 3, pp. 395-411.

Dron, J.P., Rasolofondraibe, L., Couet, C. and Pavan, A. (1998), “Fault detection and monitoring ofa 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 maintenancedecisions for equipment subject to vibration monitoring”, Journal of Quality inMaintenance Engineering, Vol. 5 No. 3, pp. 192-202.

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Koo, I.S. and Kim, W.W. (2000), “The development of reactor coolant pump vibration monitoringand 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”, IEEETransactions on Signal Processing, Vol. 39 No. 1, pp. 171-82.

McFadden, P.D. and Toozhy, M.M. (2000), “Application of synchronous averaging to vibrationmonitoring of rolling element bearings”, Mechanical Systems and Signal Processing, Vol. 14No. 6, pp. 891-906.

Mechefske, C.K. and Mathew, J. (1992), “Fault detection and diagnosis in low speed rollingelement bearing. Part I: The use of parametric spectra”, Mechanical Systems and SignalProcessing, Vol. 6, pp. 297-307.

Miller, A.J. (1999), “A new wavelet basis for the decomposition of gear motion error signals andits 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 inreal-time preprocessing of geophysical data”, IEEE Transactions on Geoscience andRemote 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 ofQuality in Maintenance Engineering, Vol. 1 No. 3, pp. 3-17.

Wall, D.S. and Gaston, F.M.F. (1997), “Modified extended Kalman filtering”, IEEE 13thInternational 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 machinerysubject 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 tovibration monitoring”, paper presented at the 30th International Conference on Computers& Industrial Engineering, Tinos Island.

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Design and development ofproduct support and

maintenance concepts forindustrial systems

Tore MarkesetStavanger University College, Stavanger, Norway, and

Uday KumarLulea 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 aproduct support strategy must be defined during design stage, in terms of these two dimensions, toensure the delivery of “promised product performance” to customers. Furthermore, productsupport strategy should not only be focused around product, or its operating characteristics, butalso on assisting customers with services that enhance product use and add additional value totheir business processes. This paper examines various issues such as reliability, availability,maintainability, and supportability (RAMS), etc., which directly or indirectly affect productsupport, maintenance needs and related costs on the basis of a case study conducted in amanufacturing company. The main purpose of the study was to analyse the critical issues related tothe product support and service delivery strategy as being practised by the company, and to suggestmeans for improvements. On the basis of the case study, the paper presents an approach for designand development of product support and maintenance concepts for industrial systems in amultinational environment. The paper emphasizes that the strategy for product support should notbe centred only on “product”, but should also take into account important issues such as the servicedelivery capability of the manufacturers, service suppliers, the capability of users’ maintenanceorganization, etc.

Practical implicationsIf a product is designed with due consideration for product support andmaintenance, factors influencing service delivery performance, and thecompetence and capability of users, it can be a major source of revenue for themanufacturer, distributors (agents) and users. It can also provide a sustainablecompetitive advantage in the market for all parties involved. Especially, inindustries where operations are often located in remote areas, a seriousconsideration of maintenance and product support can play a key role inensuring customer loyalty.



The authors are thankful to the RAMS Coordinator and the Technical Director in the companyfor sponsoring the project and for support throughout the study. They further would like tothank the anonymous reviewers for valuable feedback.

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Journal of Quality in MaintenanceEngineeringVol. 9 No. 4, 2003pp. 376-392q MCB UP Limited1355-2511DOI 10.1108/13552510310503231

Basic and fundamental concepts related to maintenance and product supportare discussed in the paper on the basis of a case study in a company deliveringadvanced industrial products. The paper discusses the issues related todesigning out of the maintenance need of system/product versus designing foreasy maintenance. This will help the design engineers in picking out the bestpossible alternatives from product support point of view.

IntroductionMost physical products and systems wear, tear, and deteriorate with age anduse. In general, due to cost and technological considerations, it is almostimpossible to design a system that is maintenance free. In fact, maintenancerequirements come into consideration mainly due to a lack of proper designedreliability and quality for the tasks or functions to be performed. Thus the roleof maintenance and product support can be perceived as the process thatcompensates for deficiencies in design, in terms of unreliability and quality ofthe output generated by the product. Other factors such as human error,statutory requirements, accidents, etc., also influence the design anddevelopment of product support and maintenance concept.

Product support and maintenance needs of systems, are more or less decidedduring the design and manufacturing phase (see, e.g. Blanchard, 2001;Blanchard and Fabrycky, 1998; Goffin, 2000; Markeset and Kumar, 2001; Smithand Knezevic, 1996). Often the reasons for product failures can be traced backto design engineers’ and management’s inability to foresee problems.Furthermore, the strategies adopted by owners/users concerning systemsoperation and maintenance, also considerably affect maintenance and productsupport needs. Hence, we can assert that product design and service deliveryboth affect service performance, and therefore product support strategy forcustomers must be defined in terms of these two dimensions (see Cohen andLee (1990) for further discussion).

Service delivery performance in the operational phase can be enhancedthrough better service delivery of spare parts and improvement of the technicalsupport system. However, to ensure the desired product performance at areasonable cost, we have to design and develop maintenance and productsupport concepts right from the design phase. The existing literature appearsto have paid little attention on the influence of product design characteristics indimensioning product support.

Product support: some basic conceptsTraditionally, 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 andlogistics, 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 astangible and intangible, as well as planned (proactive) and unplanned(reactive). It is tangible if there is an exchange of physical parts (e.g. spareparts, tools, printed documentation, training manuals, etc.) involved. If therendered service involves only intangible support (e.g. expert advice, training,online support, etc.) pricing is more complicated. Planned support is oftenrelated to preventive maintenance, training, installation, commissioning, etc.,while unplanned support is often connected to unplanned correctivemaintenance activities where the product fails unpredictably (we excludehere planned corrective failures of non-critical parts, components, andsub-systems). Unplanned support can also be the assistance needed to resolveproblems related to planned maintenance and service, but where thedocumentation is inadequate, the recommended spare parts or tools areunavailable, etc. Common for unplanned support and maintenance is that it isoften very inconvenient, costly and time consuming for all parties involved.

As customer satisfaction is crucial to business success, product and servicestrategies should be aligned to customers’ needs. Staying close to customersand providing superior services create more loyal customers and increasedcustomer satisfaction (Fites, 1996). Improved customers satisfaction andincreased repeat sales can be achieved by matching service and productsupport delivery strategy to the urgency of the customer’s needs (see Cohenet al., 2000). How the quality of these service delivery processes improvescustomer satisfaction and loyalty, has been discussed in depth by manyresearchers (see, e.g. Berry et al., 1988; Gronroos, 2000; Kasper and Lemmink,1989; Parasuraman et al., 1985). A distinction between services supporting theproducts, and services that support the customer’s actions in relation toproducts is essential for developing an optimal maintenance and productsupport strategy (Mathieu, 2001). The main goal of a service intended tosupport a product, is to ensure the expected function and/or to facilitate theclient’s access to its function. Services intended to support the customer, arerelated to improving the customer’s accessibility to product function, efficientand effective use of it, and retrieval of performance attributes. Implementationof effective and efficient service strategies requires a thorough understandingof product characteristics, product application, etc., during use. However, thekind of services delivered by manufacturers of industrial products, which areclosely connected to the product reliability and performance characteristics,have not been researched extensively (Goffin, 1998; Goffin and New, 2001).

Case study observations and analysisThe company studied is a part of a larger industrial group of companies withregional offices located all over the world. It produces various types of

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customized integrated and advanced production systems. More formally, theregional offices purchase required systems from the manufacturer andintegrate it into the customer’s production system. The company has observedan increased trend in product support needs. It is not clear if this is caused bymore products being sold, increased product complexity, reduced productreliability compared to an earlier model, by changed or more intensive productuse, or by changed customer needs and conditions. The product will be moreattractive if it is designed for low life-cycle costs (LCC), minimal requiredsupport, and optimal support delivery.

The study can be characterized as an action research methodology where theresearcher participates in the processes and operations (see, e.g. Westbrooke,1995). Various forms of data and information were collected through employeesurveys, interviews and conversations, study of company literature,participation in meetings and projects, and analysis of work processes.Strengths, weaknesses, opportunities, threats (SWOT) analysis methodologywas used to organize and systematize the observations and information.

Recommended maintenance practices, predicted LCC and performanceCustomers are increasingly focused on reliability and cost. For the company tostay competitive it is necessary to deliver products with documented andpredictable quality, reliability, supportability, and maintainability. Thecustomers are also demanding an estimate for LCCs. The company hasdeveloped a software tool to assist in making sure that RAMS issues areconsidered throughout the product design, manufacturing, and deliveryphases. The tool is based on failure mode effects and criticality analysis(FMECA) methodology and is integrated in product development projectmanagement. An LCC analysis is dependent on good reliability andmaintainability data input. Much of this data can be estimated usingexperience, service reports, spare and warranty parts data, comparison withsimilar products, product databases, etc. However, quantitative input fromproduct owners and users would be valuable to reduce uncertainty in theseestimates (see Markeset and Kumar, 2002). The design tool developed in thecompany will provide a basis for recommended maintenance strategies(including preventive maintenance), training, documentation, spare partlogistics, product support, etc.

DocumentationProduct documentation has gone through a tremendous development duringthe last five to six years and is now considered to be excellent, employing thelatest software developments to make it more accessible and easy to use. Forcomplex products, there is a problem in making the available informationaccessible and understandable to the user. Documentation also usually ends upbeing quite extensive. Excellent documentation can be of immense use indimensioning 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 ofwarranty and support. Recent developments in information technology make iteasier to make digital documentation.

Spare part and warranty issuesThe sale of spare parts is an important source of income for the company, but,at the same time, warranty costs are substantial. Corrective maintenance ofteninvolves warranty considerations during part of the product’s service life. Thecompany want the market to have the impression that they providehigh-quality products that are reliable, durable, dependable, and come with nonegative surprises. As a result, they are continuously trying to improve theirproducts and to remove the need for spare parts. However, it often provesimpossible to design out maintenance, and as a result the products have to bedesigned for effective and efficient maintenance and support. Even if theproduct is designed for maintenance free life-cycle, random and unforeseenfailures can still occur. It is negative for both customers and manufacturer thatwarranty parts are needed. However, both warranty and service provision is away of reducing the risk for the customer.

TrainingThe company offers various training programs for their customers. However,there may be a need for the instructors to acquire hands-on experience from acustomized product application as seen from the customers’ viewpoint. Lack ofuser understanding of product capabilities, and a difficult user interface,reduces the user’s capability to utilize the product fully. The result can be avery dissatisfied customer. Incorrect use can also lead to increasedmaintenance, faster degradation, wear and tear, increased warranty costs forthe manufacturer. In the worst case, it can lead to accidents, reduced safety, anddamage to health and environment. Training of users and operators improvestheir ability to correctly apply/use and maintain the products and, not least,increase user satisfaction. The ability to take full advantage of productcapabilities and capacities, and to obtain maximum product value, alsoincreases.

Customer complaints resolution process: online service and assistanceThe company uses many databases and information systems to managecustomer feedback, complaints and product problem resolution, qualityassurance and control, field service reporting, information provision tocustomer with respect to product problem solutions, etc. They also have inplace telephone helplines and online/Internet support for fast problemresolution.

We observed that employees were often disturbed in their planned regularwork to resolve customer problems requiring expert assistance. This kind of

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product support work they call “fire-fighting activities” and often have highpriority. This kind of “work process disturbances” will exist as long asunplanned and unpredictable product failures can occur and the customers (orany intermediaries) do not have the required competence to resolve the problemthemselves. A more “proactive” approach would be to try to reduce theconsequences of such disturbances for both the customer and manufacturer, byplanning and accommodating for such activities (inserting contingencies inexperts’ time schedules, implementing possibilities for remote productsurveillance, improved communication, etc.). To remove the need for thiskind 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 inthis study.

Development of product support and maintenance concept:dimensioning of product supportBased on the discussions in the previous section, we find that product supportand maintenance concept is decided and affected by issues both during thedesign and operation phase. We will now discuss design and development ofproduct support during design phases of product development.

Product support and service delivery strategyProduct support needs are dependent on product characteristics such asreliability and maintainability, the customer’s skills and capabilities, and the

Figure 1.An overview of product

support and servicetypes observed in the

company


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environment in which the product is going to be used. Therefore, productsupport specifications should be based on design specifications and conditionsfaced by the customer. The idea is to be proactive in the design phase, notreactive in the exploitation phase.

After-sales services are often in response to a customer problem, e.g. productfailure restoration, problem diagnosis, expert assistance to resolve a problem,problem with using the product, etc. Therefore, after-sales service is a recoveryprocess that attempts to resolve a customer problem, which, if not resolved,causes dissatisfaction and a less satisfied customer. The service functiontherefore attempts to recover the customer satisfaction to the level it was beforethe occurrences of problems (Gronroos, 2000). In the long-term, a manufacturerwill benefit from supplying a product that needs as little maintenance aspossible.

It is important to understand operators’ requirements, performance targets,system attributes, and the competence level of operators and maintenancepersonnel before the design process is initiated. It is essential that customerneeds and organization culture are integrated with system attributes andproduct support strategy. Companies developing products and services need tounderstand what consequences and benefits product attributes have oncustomer needs and values, and how they affect customer expectation andsatisfaction. Product attributes related to customer satisfaction can be dividedinto “must be” attributes (basic requirements), “one-dimensional” attributes(performance requirements) and “attractive” attributes (surprise and delightrequirements) (Kano et al., 1984; Matzler and Hinterhuber, 1998). These arecaptured in the information pyramid depicted in Figure 2. The bi-directionalarrows show two concepts; namely, the concept of abstraction where concrete

Figure 2.Integration of customerneeds and productattributes

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product and service attributes provide consequences and benefits which fulfilthe customer’s needs and values, and the concept of translation whereinformation about customer’s needs and values are translated into concreteproducts and services (Johnson, 1998).

System engineering is an effective approach to incorporate customer’sspecifications into the design process. It is a top-down approach to productdevelopment, viewing the system as a whole, focusing on customer’s needs,wants, preferences, and requirements – starting with the functionalrequirements and the functional performance of the product. Figure 3.illustrates the relationship between product/system characteristics (reliabilityand maintainability), product exploitation (type of application), and productsupport. Designed product functional and RAMS characteristics influence howthe product is operated and maintained, as well as what kind of, how much, andwhen support is needed. Furthermore, product use and maintenance, customer’sskills and competencies, operational environment, etc., also influence what kindof product support needed. The continuous lines indicate primary influences,whereas broken lines indicate secondary influences. The box containing productcharacteristics and product support forms the functional product. To avoidblocking capital the customer can choose to buy only the function, and not theproduct (Markeset and Kumar, 2002). Of late, this has become increasinglypopular and a more attractive approach. With functional products, the usercompany focuses on core business processes (e.g. production) and need notworry about service/maintenance. In such an approach, both parties (supplierand customer) share the business risks.

Flaws and errors: root causes of product support and maintenance requirementsAs a product becomes increasingly complex, integrating advanced mechanical,electrical, software, and electronic subsystems and technical solutions, itbecomes 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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product can fail. As the components and sub-systems become more technicallyadvanced and the number of components increases, the possibilities of failurealso increase. Through exhaustive testing of prototypes before product releaseand use, many potential failures can be eliminated. In evolutionary design,there is the opportunity to improve the functional performance bydesigning-out weaknesses (physical, functional performance, etc.) foundduring exploitation. By adding something new or changing a standard product,by customizing it to fit a customer’s demands, wants, and desires, one alsointroduces various new possibilities of product failure.

Product failures can be attributed to failure in the design and deliveryprocesses, operational environment, or how the product is used. A designfailure can be defined as an inability of an engineering solution to perform itsintended function(s), while errors can be defined as the underlying cause fordesign failure (Voland, 1999). Both the specification process and theimplementation processes of the product creation process contribute todesign failures. The specification process is often a result of interactionbetween the manufacturer and the industrial customer, while the designspecification 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 workprocesses (design, analysis, manufacturing, assembly, maintenance, operation),and errors in user perspectives and attitudes as shown in Figure 4. Errors inwork processes can cause physical flaws and typically include incorrectcalculations, faulty assumptions, miscommunications, failure to followestablished procedures and routines, performing tasks out of order, etc.

Flaws in the perspective or attitude of the employees participating in aspecific work process can lead to errors in work processes. Reason (1990)defines human error as “the failure of planned actions to achieve their desiredends – without the intervention of some unforeseeable event”. Typicalexamples are error in judgment, error in moral perspective, over-confidence,under-confidence, indifference, arrogance, selfishness, and other forms offocusing on oneself rather than on others. Training and awareness-creating

Figure 4.Failures and errorsleading to productsupport and maintenancerequirement

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activities are therefore necessary to avoid such errors. The manufacturershould therefore carefully design the work processes for design,manufacturing, assembly, etc., and, not least, for supporting product use, toavoid errors in use and reduced reliability and quality, and, finally, for betterservice delivery performance.

Quality and reliability issuesCustomer satisfaction is related to both product characteristics and productsupport quality. Customer perception of product quality is affected by how wellthe product conforms to specification and fits to its intended use, and also byproduct reliability over time (Juran and Blanton, 1999). Customer satisfaction isalso affected by product characteristics such as maintainability, supportability,and product support, as well as by the processes involved in providing productsupport. Customer satisfaction is, in other words, not only decided by value andperformance of hardware purchased, but by the total value received, and by thequality of the interaction and relationship experience throughout the servicelife of the product.

“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 thedesign with respect to maintenance issues (Figure 6). After having identifiedmaintenance characteristics one has the possibility to try to eliminate thosecharacteristics that would cause maintenance costs. However, if maintenance isto be designed out, one has to consider the cost of reliability throughout theproduct’s life-cycle.

Furthermore, one has to consider costs and available state of the arttechnology. There are also other considerations such as product capacity,design alternatives, and payback of development cost, etc., to evaluate. Therewill always be trade-offs between these considerations. LCC analysis can beused to compare design alternatives and its results have to be balanced againstmarket 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 arriveat the best LCC alternative. If the LCC of the design out maintenance approach

Figure 5.“Design out”maintenance


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are higher compared to the alternative design for maintenance, one naturallyprefers the latter. As long as the failure or degradation mechanism is known,one can design a compensating maintenance and support strategy to reducerisk, and to make the product easy to maintain and support. The presence ofwear mechanisms causing maintenance does not mean that the system isunreliable – it may, however, become unreliable if the compensatingmechanisms are unreliable or fail. If the reliability is too low, maintainabilityissues such as accessibility to parts that need to be maintained, serviceabilityand interchangeability of parts and systems, use of modular design have to beconsidered (Blanchard et al., 1995; Dhillon, 1999; Ericsson and Erixon, 1999;Thompson, 1999). Warranty and life span are also issues to be evaluated. Theobjective of such analysis is to reduce product maintenance time and cost, andto determine labour and other related costs by using maintainability data toestimate item availability.

Other ways to reduce future maintenance needs, is to reduce capacity, tosubstitute/eliminate the weak functions, or to replace weak components byones that are more robust. If we allow the system/component to fail due tovarious limitations, then we need to have a provision for easy and quickrepair/replacement. Thus, when designing for maintenance, one will first haveto examine the reliability characteristics, and thereafter decide themaintainability characteristics. Both reliability and maintainability aretraded off to meet the design requirement. LCC analysis, in combination with

Figure 6.“Design for”maintenance and productsupport

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risk analysis methods, could be a viable tool for evaluating these issues(Blanchard and Fabrycky, 1998; Moss, 1985). Furthermore, the maintenanceprocedures need to be correct, precise, as well as easy to follow and technicalmethods need to be safe enough.

Operating environmentOperating environment should be seriously considered while dimensioningproduct support and service delivery performance strategies. More often thannot, the recommended maintenance program for systems and components arebased on their age without any consideration of operating environment. This,in turn, leads to many unexpected system and components failures. Thiscreates poor system performance and a higher LCC due to unplanned repairsand/or restoration as well as support. The environmental conditions in whichthe 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 andthereby on the maintenance need and product support requirement (Kumar andKumar, 1992; Kumar et al., 1992). Furthermore, the distance of user frommanufacturer, distributor/supplier can bring additional influence.

Design for data collection, diagnostics, prognostics, Internet applications, etc.During operation phase, manufacturers can benefit from obtaining informationabout the product’s technical health as well as conformance and deviationsfrom the expected performance targets. The collected data can be effectivelyused for the development of new generation of products, but, most importantly,it can be used for changing design to remove or reduce any critical weaknessesin design that lead to higher demands on service and maintenance. The datacan also be used to make prognoses about future maintenance and supportneeds, and to predict when to upgrade, modify or replace the equipment. SeeMarkeset and Kumar (2003) for further discussion.

The designer’s goal, in respect to design for diagnosability, is to create aprocess of determining the parameters that can signal product ill-health.Automated sensor-based diagnostics systems have been the focus in workconducted towards diagnostics in mechanical systems (Paasch and Ruff,1997).

Remote and real-time assessment of performance, which often is a must forautomated and complex systems, requires integration of various technologiessuch as sensory devices, reasoning agents, wireless communication, virtualintegration and interface platforms. In the near future, Internet and advancedcommunication technology can be used to facilitate easier assessment ofproduct performance, maintenance, and support system. Furthermore,advancements in information technology provide a better interface and thuslargely facilitate communications between users and the support system (Lee,2001).


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The capabilities of manufacturer’s service organization and customer’smaintenance organizationIn general, manufacturers/suppliers, besides being a manufacturer, also need tomaintain a service organization delivering services to their customers in thesame way as any other service organizations such as a hotel, travel agency,bank, etc. Therefore, most manufacturers usually have a service departmentresponsible for delivering services such as assistance in fault finding, failurediagnostics, supplying expert assistance, spare part delivery, spare partstorage, etc. However, many manufacturing companies are uncomfortable withthe intense service expectations of their customers. The service departmentusually functions in a different way than other internal departments, since itsrelationship with the customers is often of a much longer duration. The servicedepartment needs to stay in contact with the customers for the rest of theproduct life span. While designing and dimensioning a product support andservice delivery strategy, designers have to analyse the company’s own servicedelivery capabilities and to align them with customer’s needs. It is important toanalyse owners’ maintenance organization, location, level of competence,culture, etc., to arrive at the best service and maintenance alternative. If thesupplier is delivering a total functional system (i.e. including operation,maintenance, and support), the customer’s user environment, operation andmaintenance goals and strategies, and so on, need to be understood to assureoptimal and sustaining functional performance and customer satisfaction. Thiswill help the designer to design an appropriate service delivery system that willsatisfy the customer. As mentioned in the preceding section, this necessitatesthat manufacturing companies should analyse and understand its “customer”before adopting any strategy for service delivery. If not, the outcome can bepoor product support and a dissatisfied customer. This is mainly due to workculture gaps, separating service environments from manufacturingenvironments.

Interactive problem resolutionSome influential aspects of future product performance and failure arecontended to be fundamentally unpredictable and unknowable at the designstage (Bea, 2001). When such problems occur in the exploitation phase, aninteractive and improvised approach is often needed for fast, effective andcost-efficient problem resolution. Furthermore, the manufacturer,distributors, customer, and suppliers should design in contingencies, riskreduction activities, active intervention training, etc., in product support formaking the problem resolution process, for this kind of problem, as painlessand cost efficient as possible. By being proactive in the design stage, theconsequences are less in the product exploitation stage for this kind ofproblem.

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Development of maintenance concept: operation phaseOnce a system or product is commissioned for use, the maintenance concept ismore or less fully governed by the type of maintenance strategy adopted by theuser for the system. Establishing maintenance strategy requires understandingthe technical characteristics of the product, and functions to be performed. Ofcourse, one has to examine the types of resources (organization and level ofcompetence) available. Often an interactive approach is needed to deal withmaintenance problems in unpredictable environments such as mining, offshoreoil exploration and production, etc.

Furthermore, measures need to be started for implementing world-classmaintenance practices evolving from manufacturing and process industries;namely, total productive maintenance (TPM) and reliability centredmaintenance (RCM). TPM (see Nakajima, 1986) was developed in Japan andhas many successes in manufacturing sectors. On the other hand, RCM (seeMoubray, 1997) was developed in the USA and is popular among aerospaceand process industry for optimising maintenance processes. In fact, TPM andRCM have been major themes in the development of maintenance strategies forthe last ten years. Many companies have followed this route and havedemonstrated considerable improvements in plant and process performance(Dawson, 1996). Many industrial companies are also adopting thesephilosophies and practices in their operations and maintenance strategies.

The type of maintenance strategy decided on should be developed takinginto account internal resources (facilities, tools, competence, knowledge andmanpower, etc.) available to deal with maintenance and repair problems andissues. If there is a lack of competence or manpower to deal withmaintenance/service work, one has to rely on external resources.

The use of external resources and outsourcing of maintenanceContractors, distributors, and consultants who provide competence, knowledgeor manpower to operations and are not directly employed by the productowners, are termed as external resources. Of late, many users’ companies arefocusing on their core processes and competencies while outsourcing otherareas. With the advent of this trend, outsourcing of maintenance is becoming apopular way to deal with maintenance and support requirements.

Recently, many manufacturers and suppliers are offering total performanceguarantee for their products or are supplying a functional product asmentioned earlier. In such cases, the manufacturer and suppliers are taking thefull responsibility for the operation, maintenance, and support of the system.The customers only pay the supplier for the function they provide. This hasrevolutionised the product support issues from the designers’ point of view,forcing them to look for the best available solution that will lead to the lowestLCC. The past practice of making profit by the sale of spare parts and servicesto customers is no longer valid in case of functional products.


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Concluding remarksThe ultimate goal of the product, or service, is to facilitate or fulfil thecustomers’ goals. These goals therefore need to be designed into the product orservice. Furthermore, a performance indicator system should be used tomonitor the effectiveness and efficiency of the implemented operation,maintenance and support strategies (ee Kumar and Ellingsen (2000) for furtherdetails).

In this paper, we have discussed a general approach for the dimensioning ofproduct support by taking into account product design characteristics,information technology applications, capability of service deliveryorganizations, client service needs and expectations, the manufacturer’sdelivery capabilities, etc. It is clear that maintenance is more or less dependenton the designer’s perception of function to be performed, manufacturer’sservice delivery capability and user’s competence, and capability of any thirdparty involved. Products and services have to be designed from a holisticperspective benefiting and adding value for all participants. It is believed that ifdesigned properly, product support and support strategy can be a major sourceof revenue and profit for the manufacturers, product owners, andintermediaries. Furthermore, during the operational phase of systems, aconsiderable amount of savings can be made from service and maintenancecost by establishing an effective and efficient service and maintenancestrategy.

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Integration of RAMS and riskanalysis in product design anddevelopment work processes

A case studyTore Markeset

Stavanger University College, Stavanger, Norway, andUday 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 functionalperformance needs and have predictable life cycle cost (LCC). Due to design problems and poorproduct support, these systems are not able to meet the customers’ requirements. Major causes ofcustomer 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 bereduced 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 andmanufacturing is presented. The importance of LCC analysis, use of feedback information, andintegration of various information sources to facilitate easy RAMS implementation, incombination with risk analysis in the design phase, is discussed. An approach is suggested forintegration 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 duringthe study to create awareness and to improve learning and understanding of RAMS’ aspects ofexisting and future products and processes, is also presented.

Practical implicationsThe paper emphasises the importance of reliability, availability,maintainability and supportability (RAMS) characteristics for ensuringfailure-free operations of industrial products. It is argued that RAMScharacteristics must be considered during the design phase to facilitatecompetitive advantage for the product and to reduce the business riskassociated with non-performance of products and systems. A need for effectiveand efficient control of the information flow and the work processes involved inthe design, manufacturing, delivery, commissioning, and after-sales support



The authors are thankful to the company for assisting in sponsoring and financing this researchstudy. They are also thankful to all the employees of the company who helped us to perform thisstudy. Furthermore, they would like to thank anonymous reviewers for their valuable input andfeedback.

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DOI 10.1108/13552510310503240

was identified as critical to successful integration of RAMS and risk analysis inthe work processes. The paper demonstrates the application of RAMS tools andmethods on the basis of a case study performed in a manufacturing company.

Introduction and backgroundManufacturers of industrial systems/machines experience increased pressurefrom customers to deliver customized products with documented RAMScharacteristics and LCC, with improved quality, at a lower price, and in ashorter timeframe. The customers demand products that meet the functionalperformance needs and have predictable performance and cost throughout theservice life cycle. However, due to design problems, these systems are not ableto meet customer requirements in terms of system performance, effectivenessand efficiency. This is often due to poorly designed RAMS characteristicscombined with a poor maintenance strategy. This has given a new dimensionto the problem of effective and efficient service and maintenance managementof industrial systems/machines. To avoid the complexities of maintenancemanagement, many customers/users prefer to purchase only the requiredfunction, not the machines or systems. Thus, the responsibility of maintenanceand product support lies with the organization delivering the required function.With the advent of this trend, focus has shifted to the design of functionalproducts. The definition of a functional product is that the user is not buying amachine/system but the function it delivers. Figure 1 illustrates the definitionof a functional product and depicts the relationships between productcharacteristics, exploitation, and support. The continuous and broken linesindicate primary and secondary relationships, respectively. Designed productcharacteristics (hardware and software) define the types of exploitation theproduct can be subjected to and the type of product support needed to achievethe expected function and performance. Furthermore, the users and operatingenvironment can also influence the degree of support needed to achieve theexpected performance level (Markeset and Kumar, 2002).

Major causes of customer dissatisfaction are often traced back to unexpectedfailures, leading to unexpected costs. In general, product failures are oftencaused by the design engineers’ and manufacturers’ inability to predict

Figure 1.Functional product

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problems that may occur later in the product application phase. However, withproper consideration of RAMS in design, manufacturing, assembly, testing,and installation, the number of failures can be reduced and their consequencesminimized considerably. It is argued that if due attention is paid during thedesign phase to the “maintenance needs” of the system; considerable savingscan be made in the operation phase. Manufacturing companies can gain muchfrom improving the work processes involved in design, manufacturing,assembly, and delivery processes by integrating “the maintenance needsanalysis” at the design board stage.

Design is a process of balancing needs and functional requirements againstvarious 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 whereengineers have to make decisions concerning the translation of customer needs,desires, and wants into a product that can fulfill the functional requirements ina reliable and consistent way over time. This process should ensure a productof satisfactory quality in an effective and efficient way. Product complexitycaused by integration of electronics, data processing, processing controls,aspects of product acceptance and environmental concerns is steadilyincreasing, resulting in an ever-increasing number of questions andproblems to be considered in the design phase. This necessitatesinterdisciplinary cooperation and creativity among specialists, creating newdemands 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 amanufacturer and supplier of industrial systems with customers anddistributors worldwide. The company has recently experienced thatcustomers increasingly emphasise demands on product reliability,maintainability, support, and life-cycle costs, and has realized thatdocumented and predictable reliability, quality, maintainability, and LCC forthe product could be a competitive advantage. In addition, customers demandthe products be delivered with a shorter lead-time, with a shortercommissioning phase, and improved after-sales support. As a result, thecompany sees the need to implement and integrate systematic and formalizedRAMS synthesis and analysis, by incorporating RAMS data analysis togetherwith risk analysis into their design approach.

With this background, we will discuss fundamental issues related toimplementation of RAMS in product design and development, and related tointegration of reliability, maintainability and risk analysis tools and methods toenhance performance efficiency, to reduce product LCC and delivery time, andto increase customer satisfaction and product attractiveness. This approach isexpected to create a win-win situation for both manufacturers and customers.


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Integration of product performance requirements into the designprocessA product exists because there is a customer who is willing to pay for and usethe product. A manufacturer exists because the product needs to be made andbecause there is a market and customers for his product. In order to deliver theproduct or the required function, the manufacturer has to design the product,manufacture it, and provide any required support to meet expectedperformance demands. These work processes need to be managed andorganized. Suitable organizational systems and leadership therefore have to bein place to manage the work processes. This can be referred to as “customerpull” of the product development process. In this case the product and theproduct delivery system is created and formed on the customers’ terms (seeFigure 2). Customer needs, wants, and preferences are, in this case, integratedinto the products and serve as the drivers of product and organizationaldevelopment. In the other extreme, the manufacturer can “push” products onthe customers, based on what is technologically possible, and, moreover, formthe organization without taking customer’s needs, wants, and preferences intoconsideration. This reverse relationship is what we refer to as “technologicaland organizational push”. However, whether the driver for product andorganizational development is a pull or a push process, the increased market

Figure 2.Integrated productdevelopment facilitatinginteractive informationflow

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pressure in respect of cost, time and performance forces a need for effective andefficient distribution of, and access to, product and work process-relatedinformation, and for more proactive, reactive, and interactive information use.

It is important to integrate customer needs, wants, and preferences into thedesign as early as possible, as during this stage it is easier to influence productLCC and customer satisfaction. We argue that integration of RAMS and LCC incombination with risk analysis in the design and manufacturing process isfundamental in accomplishing and ensuring the success of new productdevelopment and for reaching the goals set at the outset.

There exists a large volume of literature discussing RAMS analysis fordifferent 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 acrossany literature where the issues related to implementation of RAMS and riskanalysis in design are discussed. Some of the notable exceptions are Blanchardand Fabrycky (1998), Dhillon (1999), Markeset and Kumar (2001), Sandbergand Stromberg (1999), Van Baaren and Smit (1998), Warburton et al. (1998). Fora mechanical system, Warburton et al. (1998) demonstrate a methodology forproviding the design engineer with the tools to understand and modelmechanical failure characteristics and thereby simulate product behaviour interms of design, operational, environmental and material parameters based onmathematical models expressing underlying failure processes and parameters.Moss (1985) describes how to design for minimal maintenance expense throughthe use of LCC analysis. However, this is difficult due to uncertainties and lackof data. Furthermore, product support is often not considered early enough inthe 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 ofdeveloping new products (Goffin, 1998). It seems little research has beenreported on how to integrate product support in design (Goffin and New, 2001).Support is needed to compensate for product unreliability, loss of productperformance quality and effectiveness, reduced product output quality, lack ofusability, etc.

Tools, methods and models in RAMS and risk analysisThere are many tools and methods available to assess RAMS, LCC and toapply 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 thedimensioning of product characteristics and product support. As the demandfor shorter delivery cycles increases, more effective and efficient workprocesses are more important than ever to examine factors affecting productperformance, maintenance, and support. We believe that routines forintegrating 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 tosustain competition, to deliver a superior product, and to continue growing,companies need to focus on making the design process as effective and efficientas possible. The Gate Model introduced by Cooper (1990) is one method used todefine routines and procedures, to control product development, to reduce risksin complex processes, and thus help create focus on the value creating activitiesin a value chain. In the Gate Model, a set of gates is assigned to various phasesof a project. In each phase, a number of checkpoints and tasks are evaluatedand approved before the project is allowed to enter the next phase. The idea isthat 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 areimplemented for a purpose and lead to a common goal. The inputs to the workprocess are customer needs, wants and desires, and the output is the productand services produced. Sometimes companies experience problems withintegrating design concepts and output from various groups, disciplines andwork processes into the product to fit the customer requirements. If thedifferent groups are focusing only on their own functions and do not try tointegrate their solution into the solutions from other disciplines, the end resultcould be less than optimal. Integration of solutions needs to be done as early aspossible in the design process. The overall product delivery process iscomposed of many sub-processes. If these sub-processes are considered asfunctions (or disciplines/groups), and there is competition between thembecause of result requirements to justify their existence, each of the functionswill often attempt to optimise themselves to look the best in the eyes of thebusiness management. However, it is important to realize that it is the overallgoal that is important, and which everybody should work on to reach and tooptimise together. This is a direct parallel to “systems thinking” in which thefocus is not on optimising the pieces, but rather on the fit between the pieces ofthe system (Liker et al., 1995). We believe that “systems thinking” is importantand valid both for work processes and for the product itself. It does not if acomponent/subsystem is designed to perfection if the rest of thesystem/product is not. After all, what the customer is primarily interested inis the functional performance of the product and the total product offered anddelivered, not the individual components.

Research methodology and approachThe study was conducted in two phases; namely, a preliminary study and amain project phase. In the preliminary study we aimed to become acquaintedwith the employees, to understand the work processes involved in design andmanufacturing, and to identify factors and areas that affect product designcharacteristics and service life performance. In the main project phase weselected some areas and work processes for a more detailed study.

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The main goal and purpose of the study was to identify areas where thecompany should focus for improvements in respect to the products and workprocesses involved in product design, development, delivery, and support. Oneof the goals was to evaluate information sources and to identify informationneeds not covered in the company’s existing databases. Furthermore, wewanted to evaluate how RAMS and risk analysis can be integrated in workprocesses. The study also aimed to motivate and provoke a discussion withinthe company about the design process and related problem areas, and to makethe employees involved aware of the issues and complexities involved.

The project goals were accomplished by the use of interviews, surveys in theform of questionnaires, data collection and analysis, discussions, participationin projects and meetings, etc. To get a holistic view of the company we selectedemployees from all departments and groups to participate in the surveys.Strengths, weaknesses, opportunities, and threats (SWOT) analysismethodology was applied in both the preliminary and main study toorganize and categorize information.

The study can be characterized as action research methodology, where theresearcher participates in the processes and operations under investigation(Westbrooke, 1995).

Case study: study and analysis of design and manufacturing processThe company observed in the study produces various types of flexible,advanced, integrated, and automated production systems based on advancedtechnology. The systems are powered by electrical motors and are controlled byadvanced software solutions, electronics and sensors. Their customers are usingthe products in high-performance production lines where uptime is critical. Eventhough the company has not been able to design out all needs for maintenance,the products are very reliable, dependable and durable. Through an excellentsupply and support network, their customers trust the company to providenecessary support when needed. However, if a production system failsunpredictably, the consequences can be very costly for the customer. Many of thecustomers therefore demand products which have documented and predictableservice life performance, a high technical performance and reliability, are durableand dependable, comply with health, safety and environmental standards, andare cost effective. Normally the customer purchases a production system to fitinto their production line from the industrial group’s closest regional office. If theregional office is not able to assist and resolve problems, the customercommunicates with the manufacturing company directly.

Products are categorized as standard products, customized products, anddevelopment products. The products are designed to last for 50,000 hours ofcontinuous use. The owner will need spare parts and may also need to upgradethe product due to any weaknesses discovered and/or technological developmentsthat increase product performance or maintenance effectiveness and efficiency.


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Work processes in design and manufacturingThe employees are organized in functional departments and sub-groupsaccording to specialization. Both the products and the work processesnecessary to produce the products have evolved in advancement andcomplexity resulting in a higher demand on employee specialization. One of theresults of this evolution is that fewer employees than before have a fullunderstanding and overview of the complexity of the products and the workprocesses. 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 productimprovements, are handled by the research and development department.

The study indicates that some work processes are not properly defined, orhave procedures, routines or checklists that are not followed or are not easy tofollow. Even if many of the required procedures, routines and checklists are inplace, time-pressure occasionally makes them difficult to follow. Procedures,routines, and checklists are used to coordinate and control the work process toensure that the actual output meets the expectations (or is according tospecifications and quality). The work processes need to be understood andformalized to maximize the output. It is important to consider the coordinationamong work processes to be able to achieve optimal results.

Product reliability and maintainability characteristics are designed into themanufacturing 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 foundationfor product reliability and quality. If too tight tolerances are given, or if thecomponent is difficult to manufacture and assemble, errors may be introducedin manufacturing and assembly, causing reduction of the designed-in reliabilityand increased quality problems. However, to produce the drawing, the engineermay need input from the manufacturing department about critical inputs thatmay make the component difficult to make, which further down the line caninfluence quality and product RAMS.

Many work process and product problems are caused by a lack ofunderstanding and awareness of why things are done in the way they are done.Often, when people communicate, they talk about the same thing but usedifferent terminology/language, or discuss different things using the sameterminology. To avoid confusion and misunderstanding there must be focus onhaving the same understanding and on using the same and agreed-onterminology. There must be a common understanding of why things are donethe way they are, and of the purpose of the activities. In this study, there areseveral indications of anomalies in perception between department managersand employees, and also between different departments. Focused training and

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follow-up are important for understanding and awareness, and also affectmotivation, attitudes and teamwork abilities. The training undertaken in thisproject has given positive responses with respect to this. In the trainingsessions given, the seminar started with a general introduction from one of thecompany managers, followed by a presentation of general theory explainingthe background, foundation and basic philosophy of RAMS integration, whichwas followed by a relevant application. Throughout the seminars theparticipants were encouraged to comment on the issues presented and toparticipate in discussions. The result was a better understanding of the topicand, hopefully, more motivated employees.

Software systems, databases, and information sourcesThe company uses advanced software systems for product design andanalysis, for administration and management of related documentation andanalysis, and for the production of their products. They also have in placemany databases and information systems to manage customer feedback,complaints and resolution of customer product problems, quality assuranceand control, field service reports, and information provision to customers withrespect to product problem solutions, etc. Some of the employees complain thatthere are too many information sources and no easy accessible overviews andexplanations 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 toobtain useful, relevant information when needed.

It was observed that many of the information systems were used for reactiveand not proactive improvement purposes. As data and informationaccumulates, the data should be identified and trended to identifyweaknesses and opportunities for improvement, and to avoid repeatingmistakes. The databases can also be used as a source of information whensolving similar problems, or during design and development of new productsand models. There seems to be a lack of information system integration andholistic perspective of possible use. Some of the information systems aredifficult to use and are error prone. Sometimes it is also difficult to access thedatabases. Common to many of them is that the information in them is of aqualitative format, which makes it difficult to search, filter and findinformation if needed. It also makes statistical analysis and trending in theworst cases impossible, and at best difficult, cumbersome and work intensive.More quantitative information is needed for producing better LCC analysis andavailability estimates for standard products. Many of the information sources,and the information therein, are intended for product improvements and not somuch for improvement of work processes. Improvement of products and workprocesses are intertwined and complementary activities, not mutuallyexclusive.


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Product development and testingThe 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 ofcomparison with competitors, and partly as a result of customer and marketdemands. Many product development efforts are a result of productcustomisation efforts toward special user needs evolving from cooperationwith customers and suppliers. The customer demands reliable, durable, anddependable products. As products become increasingly advanced, complex,and integrated, the number of ways they can fail increases as well. As changesor new technology are introduced to existing products and new products aredeveloped, new possibilities for weaknesses, failures and errors are alsointroduced. It was observed that many projects had insufficient time to test allnew changes and to optimise the design by designing prototypes usinglaboratory testing-facilities to improve maintainability, etc., before beingcompleted and introduced to the customers.

TrainingThe company offers training programs for their employees and customers. Allthe company employees need to be trained in respect to design for maintenanceissues and in utilization of new RAMS tools and methods. There was alsoobserved a need for training of manufacturing and assembly personnel withrespect to implementing new design solutions.

Integration of RAMS and risk analysis in design work processesRAMS activity coordination and integrationThe company has realized that both their products and work processesinvolved 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 productswith documented quality, reliability, maintainability and competitive LCC.Therefore, a RAMS coordinator position was created in the company. Since aRAMS coordinator deals with product and work process improvement withrespect to RAMS issues, it is a cross-functional and partly independentposition. This reduces the focus on interdepartmental optimisation, and insteadcreates a holistic view on product and work process improvements.

The coordinator is responsible for coordinating efforts focused onintegrating RAMS into design work processes, development and use ofRAMS tools and methods, utilization of information sources, data, andexperience which can be used to improve product reliability and, not least,training of employees in respect to these issues. The goal is to systematize andformalize the design methodology in respect to RAMS, to focus on product andwork process improvements, and to make the product performance more

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predictable. When a product problem is identified, the goal is to find the rootcause and prevent it from reoccurring. At least it should be possible to reducethe problem consequences by making the problem predictable and by includingmaintenance and support compensation activities. Efficient and effective use ofthe testing laboratory is also part of the RAMS coordinator’s responsibility.The goal is to be able to use the facility more proactively and interactivelyduring design, to reduce design iterations and rework, to reduce cost andlead-time, to improve both reliability and maintainability, and hence downtimeand costs for the customer. By creating the RAMS coordinator position, thecompany has managed to bring focus on the integration of RAMS and riskanalysis in the work processes.

RAMS tools and methodsCentral in the efforts of integrating RAMS into work processes is thedevelopment 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 thefailure also is included. FMECA analysis concentrates on identification of theevents and frequency resulting in failures and analysing their effects on thecomponents and systems. Information about possible ways the product can failand product weaknesses originate from experience, feedback from customersand suppliers, testing, analysis, spare part and warranty data, and projectreview reports, etc. If a failure mode is identified, its risk is predicted byestimation of failure frequency, consequence, and detectability. If the riskproves too high, efforts are initiated either to reduce frequency and/orconsequence, or by increasing the detectability to make it possible to avoid theevent, or at least to reduce the severity of the consequences. The analysis anddesign-out of the failure cause, or corrective action, has to be done in productdesign (Carter, 1997). The intention of the FMECA tool is to formalize andstandardize design processes with respect to RAMS, to meet demands fromcustomers in respect to documented reliability analysis, and to make it easier toidentify product improvement opportunities. The computerized tool is nowstarting to be used actively in the design process. Although FMECA analysishas been performed in the company for many years, only recently have effortsbeen initiated to formalize and systematize the analysis process.

The results from the analysis are gradually becoming popular and usedmore frequently. Such results provide a basis for decision making such asrecommendations for preventive maintenance, spare parts and maintenancetools (both for commissioning and exploitation phase), documentation(including procedures, routines, and checklists for installation, failurediagnosis, maintenance, etc.), and LCC predictions. The analysis also servesas 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 allproduct characteristics leading to unplanned corrective failures and warrantycosts. Corrective or unplanned maintenance is needed when the product failseither intentionally, as sometimes is the chosen strategy for components thatcan fail but which are not critical, or unintentionally as a result of overload,wrong use, design errors, etc. The whole point is to improve productperformance, reliability and predictability, reduce costs, increase profitmargins, and thereby to increase product-related performance and customersatisfaction.

RAMS information sourcesAs mentioned above, there exist many possible sources of information that canbe related to product and work process improvements. The problem is toidentify and route the interesting information to RAMS improvement activities,and to the RAMS tools and methods. To make efficient and effective use of theinformation 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 theinformation is to be routed to fulfill the various purposes, etc. In this study,several new ways to use databases and information sources to improveproducts and work processes were identified. For example, many concreteinformation system improvement possibilities are identified in the mapping ofthe RAMS information flow. The service reports have been improvedsomewhat as a result of suggestions from the employees and new informationuses. This can be considered an added benefit of the RAMS coordinator’sefforts of identifying information sources with information relevant to productimprovement.

Even though much of the information is focused on the products, often theroot cause of a product problem recorded can be traced back to work processes,activities, procedures, routines, or checklists in use during delivery of theproducts. This information must therefore be used and discussed withimprovement of both processes and product in mind. The company has used anintranet for some years for providing easy access to information sources, andhas recently also started to use the Internet to facilitate easy access toinformation and distribution of information. It is believed that integration ofthe Internet and intranet applications with the Stage Gate model can supportand accelerate new product development (see Howe et al., 2000).

Work process management and control: the Stage Gate modelRecently, the company has started to use a modified Stage Gate model toimprove project management and control, in parallel with traditional projecttools and methods. In this model, projects are divided into sequential stages, orphases, with go/no-go gates at the end of the phase. The purpose of the gates isto avoid a project entering the next phase before the goals of the first phase areaccomplished. The gates provide an opportunity to review what has been done

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to date and to adjust performance gaps, or to stop the project if the results arenot as anticipated and too much money has been spent. In this way the projectcan become easier to control and business risks reduced.

Recent developments in information and communication systems has madeit possible to perform design and manufacturing processes simultaneously, andhence more effective and efficient, resulting in reduced lead-time and costs(Yazdani and Holmes, 1999). To improve products, RAMS-related activitiesneed to be performed and evaluated as early as possible, preferably already inthe specification phase. As mentioned previously, the foundation for a reliableproduct is laid in the design phase. Product reliability cannot be improved inthe later stages of production. In these design implementation (manufacturing,assembly, etc.) stages there are many opportunities to reduce the inherent anddesigned-in reliability by not conforming to specifications given. Theintroduction of the Stage Gate model results in that representatives of laterstage functions, or work processes, have the possibility to influence the designat a much earlier stage through the gate reviews. This also forces, and gives anopportunity for, inter-disciplinary cooperation and coordination, which is bothrecommended and, in many cases, required. As Pahl and Grote (1996) point out“teamwork and individual work are complementary in an integrated andinterdisciplinary development process”. Furthermore, a risk analysis based onvarious factors such as economical, environmental, support, planning, etc.,thought to influence project feasibility, success and results, is performed at thebeginning of the project. This analysis is updated before the gate reviews andfunctions as a basis for decision making. To ensure that RAMS issues areconsidered at various design and manufacturing stages, the company hasstarted to use a RAMS activity template to define activities and tasks to beperformed at each project stage.

RAMS activity templateThe template is meant to include RAMS gate activities to check and control ifthe goals have been reached at the various project stages. RAMS goals mustreflect real customer needs, available technology, and customer willingness topay. They also have to reflect what is necessary with respect to marketcompetitiveness. It is important to consider the coordination between workprocesses to be able to get an optimal result. The FMECA tool is used in allproject meetings and is used as a checklist to ensure that identifiedimprovement actions identified are implemented and followed up. The endresult is that the design process becomes even more concurrent and dynamic,involving increased informal and formal information exchange. This has apositive effect on employee motivation and increases the understanding of howtheir contribution fits into the big picture. The holistic view should be that allactivities contribute to customer satisfaction.


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RAMS trainingMany work process and product problems are caused by unawareness and a lackof understanding of purpose and goals. Part of the RAMS coordinator’s job is tomotivate the various employees to take part in improving the products and to usethe tools available. As such, focused training and awareness-creation efforts andcoordination are of the utmost importance and can have a tremendous impact –both with respect to improving understanding and knowledge of the issuesinvolved, to improve motivation, attitude, teamwork abilities, and to create aholistic view of the products and work processes. Part of this is the effect ofgaining a common understanding of goals, focus areas, work processes,problems and, finally, but perhaps most importantly, customer satisfaction. Withbetter training, the employees should be able to design for RAMS at an earlierdesign phase and reduce the number of design iterations necessary to produce afinal and acceptable design. Project risk may also be reduced.

To improve the design in respect to reliability and maintainability, theemployees need to be trained in RAMS tools, methods and terminology. Allemployees need a similar understanding of what design for RAMS means andto use the same terminology. During the study, several courses were arrangedfor the employees to create awareness.

Figure 3 depicts a general dynamic product development process controlledby the Stage Gate model, together with support activities to integrate RAMS inthe design process. As shown in the figure, the product development processesare started simultaneously. To be able to include results and information fromlater 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 tobe in place for continuous communication with customers, regional offices andsuppliers. In simultaneous processes like these, the use of cross-functional andmulti-skilled integrated teams and facilitation for intensive communicationbetween work processes involved (depicted by many short, vertical, andbi-directional arrows in Figure 3) are of the utmost importance to coordinateand control the process. The participants also require an understanding andknowledge of the work process and a holistic view of the goals.

DiscussionCustomer feedback is important for having good input data for reliability,maintainability, LCC calculations, for product improvements, customersatisfaction 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 aninterest in the manufacturer improving the product’s characteristics.Manufacturers and customers are mutually dependent on each other – themanufacturer needs feedback from customers on product behaviour to improve

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the next product generation or version, while the product user may need spareparts, expert advice and help in maintaining the product, training, anddocumentation, etc. Somehow the manufacturer and customer have to create arelationship to take advantage of each other’s information, knowledge andintelligence (Liyanage et al., 2001). The recent development of communicationand information systems has made it much easier, quicker, and simpler toretrieve information directly from customers and products, to provide remotemonitoring and support, to interact with customers, suppliers, and servicepersonnel at remote locations, and to increase the speed of productdevelopment and delivery.

Product design characteristics and built-in reliability are dependent on howthe products are to be manufactured, assembled and installed. If, for example, acomponent is difficult to design and manufacture, there is a higher chance ofmaking mistakes, which may result in the component being weaker thanintended or having a damaging/detrimental effect on other components, etc. It is,therefore, important to consider how the product design is to be implemented inmanufacturing and assembly to avoid errors caused by unnecessarilycomplicated operations and tasks. Therefore, the manufacturer needs to havein place effective and efficient routines for integrating RAMS in the design andmanufacturing processes, for obtaining data and information from the customersthroughout the product service life, and to cooperate with the customers inmaintenance and support planning from the early concept phase to the end of theproduct service life (see also Markeset and Kumar (2003)).

Figure 3.Dynamic product

development processincluding Stage Gate

work process control andproactive, reactive and

interactive partnercommunication


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Some of the pieces of the puzzle related to integration of RAMS and riskanalysis discussed in this paper are shown in Figure 4.

Concluding remarksThe company studied is still in an early phase of integration of RAMS in itswork processes related to design. This is being implemented gradually andphase-wise with feedback to monitor the effects. By integrating RAMS in thework processes involved in delivering, installing, and supporting products, it isbelieved that business risk will be reduced. The company sees the need forimplementing training programs with focus on integration of RAMSconsiderations in the design phase in combination with risk and LCCanalysis. A need for effective and efficient control of the information flow andthe work processes involved in the design, manufacture, delivery,commissioning, and after-sales support was identified as critical tosuccessful integration of RAMS and risk analysis in work processes. Thecompany also has initiated measures to coordinate RAMS activities beingimplemented in different sections and departments.

We believe that successful integration of RAMS will provide the companywith a competitive edge and the successful implementation will mainly dependon the company’s ability to create awareness and understanding of the issues

Figure 4.An illustration ofcomponents of RAMSintegration process

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involved. The employees need to be trained to use the appropriate tools andmethods, and an infrastructure needs to be in place to make these tools andinformation sources available when needed. It is important to consider thecoordination between work processes, tools, and information sources to be ableto get an optimal result. Procedures, routines, and checklists need to be in placewhere they are needed; they need to be clear, concise, concrete, and precise to beefficient and effective. They also need to be updated regularly to reflectchanges in needs and uses. However, one must be careful not to introduce toomuch bureaucracy into the organization, as it tends to kill creativity andinnovation.

References

Barlow, R.E. and Proschan, F. (1981), Statistical Theory of Reliability and Life Testing, To BeginWith, 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 EffectiveServiceability 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”, BusinessHorizons, May-June, pp. 44-54.

Dhillon, B.S. (1999), Engineering Maintainability: How to Design for Reliability and EasyMaintenance, Gulf Publishing, Houston, TX.

Goffin, K. (1998), “Evaluating customer support during new product development: an explorativestudy”, J Prod Innov Manag, Vol. 15, pp. 42-56.

Goffin, K. and New, C. (2001), “Customer support and new product development – an explorativestudy”, 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 theInternet”, 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 ofelectric loaders using the proportional hazard model”, Reliability Engineering and SystemSafety, 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: commonthemes”, in Liker, J.K., Ettlie, J.E. and Campbell, J.C. (Eds), Engineered in Japan: JapaneseTechnology Management Practices, Oxford University Press, New York, NY.

Liyanage, J.P., Markeset, T. and Kumar, U. (2001), “On the knowledge driven performancemanagement grounded in process intelligence: with applications to asset maintenance andproduct development”, paper presented at IMSIO2: 2nd Conference on IntelligentManagement System in Operations, Salford, 3-4 July.

Markeset, T. and Kumar, U. (2001), “R&M and risk analysis tools in product design to reducelife-cycle cost and improve product attractiveness”, in Proceedings of The AnnualReliability 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 andmaintenance concepts for industrial systems”, paper presented at the IFRIMmmm 2002,Maintenance, Management and Modelling Conference, Vaxjo, 6-8 May.

Markeset, T. and Kumar, U. (2003), “Integration of RAMS information in design processes – acase study”, paper presented at the 2003 Annual Reliability and MaintainabilitySymposium, 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 Stromberg, U. (1999), “Gripen: with focus on availability performance and lifesupport 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, ProfessionalEngineering 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 automotiveindustry”, 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 formechanical 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 andoperations 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 ofinvesting in IT in the

maintenance departmentAn empirical study in a cement factory in

TanzaniaE.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 themaintenance department. The economics in this case was determined by conducting a quantitativeanalysis on the reduction of operational costs, on increase in productivity and on qualityimprovement. A comparison was made to analyse company performance in the maintenancebefore and after the introduction of IT in the maintenance department. The analysis shows thatthere were reductions of operational and inventory holding costs. Likewise, it was shown that therewas also improvement in product quality and productivity.

Practical implicationThere are very few researches, which are aimed at showing the economics ofinvesting in information technology (IT) in the maintenance department. Manycompanies introduced IT in the maintenance department from a technologicalpoint of view on aspiration of increasing the efficiency of job performance. Inaddition, several empirical researches established that there does not exist apositive relationship between the size of the investment in IT and theproductivity or profitability of the company. In some companies it was evennoted a negative correlation between the volume of investment in IT and theproductivity of the enterprise. This situation is termed as “productivityparadox of the information technology” (Stickel, 1997). The result of thisresearch work has shown a contrary, that there has been an increase inproductivity, reduction of downtime and reduction of the overall maintenancecost by introducing IT in the maintenance department.

IntroductionEconomic and social development of any society depends on theperformance of the production and infrastructure facilities invested withinthe society. The facilities can be a manufacturing enterprise (e.g. a textilemill, cement factory, etc.); an infrastructure facility (e.g. road, a highway,airport, etc.); a public utility (e.g. sewage system, telecommunication



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DOI 10.1108/13552510310503259

systems, etc.) or any other structures like dispensaries, health care centres,hospitals, schools, etc. These facilities cannot provide the intended servicesto the expected level if they are not taken care of. In other words, theperformance of these facilities will depend on the level and efficiency ofmaintenance provided by the concerned authority.

In the production sector, poor maintenance management of productionequipment is one of the key factors which resulted in low capacity utilisation inmany Tanzanian industries. A study conducted in the late 1990s shows thatthere is a general lack of awareness of the economic benefits resulting fromwell-maintained equipment and facilities (Bavu et al., 1997).

In the effort to improve the capacity utilisation and realise the benefitsof sound maintenance, some few industries in Tanzania have decided tointroduce IT in their maintenance departments. Among such industries,which so far have introduced IT in maintenance departments, are TanzaniaPortland Cement Company Limited (TPCC) and Coca-Cola Kwanza BottlersLimited. It is anticipated that applying computers in a maintenancedepartment will improve the maintenance system and hence increase thecapacity utilisation. In order to meet the challenges of global economy andimprove the chronic problem of low capacity utilisation, the Tanzanianindustries are required to reduce operational and maintenance costs, toimprove productivity, and to improve products quality. The production ofhigh-quality products is normally supported by a well-managedmaintenance system (Mjema and Kundi, 1996). The question to be askedis: “Has the introduction of IT in a maintenance department helped thecompanies to achieve better competitiveness?”. A difficult hurdle foranswering this question is that this type of investment yields results overtime, and seldom in the short-run. Likewise, it is difficult to quantify andcalculate 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 itscost structure or differentiate its products and services. Competitive advantageresults if a firm gains an advantage, such as increased market share orinformation asymmetries, over its competitors (Ohmae, 1992). The competitiveadvantage is a function of the ability of a firm’s workforce to exploit thecapabilities of IT creatively to develop new products or services. IT must createstructural differences if it is to provide sustainable competitive advantage(Porter, 1985). Competitive advantage derived from IT will occur only when ITimproves an organisation’s primary business functions, creates value-addingexperience that enhances customer services and focuses on changing demandpatterns and use (Adcock et al., 1993).

Regarding the concept of quality, for a company to achieve successes in thequality management it needs a better information system for reporting thechanges in the production parameters in the shortest possible time. Therefore,

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IT contributes greatly in the success of the quality programs. The quality of theproduct can be looked at from two perspectives: first is the producer’sperspective, and second is the customer’s perspective. From the producer’sperspective quality is achieved if there is conformance to specifications.Conformance to the specification is influenced by the quality of productionprocesses, which is influenced by maintenance.

A solution to meet the producer’s perspective of quality is to have anefficient preventive maintenance system, which can minimise equipmentbreakdown and avoid product defects. But with the rapid increase of industrialautomation, this has stimulated the search for a more effective preventivemaintenance program. To achieve this, introduction of IT in the maintenancedepartment seems to be a clear solution. It is therefore expected that the use ofIT in the maintenance department can help in quality improvement programs.However, there are some prerequisites for an economical introduction of an ITsystem into a maintenance management system. The prerequisites wereidentified as: defining precisely the objectives of an enterprise which canspecify the needs of an enterprise and the requirements for an IT system for theconcerned enterprise (Mjema and Kundi, 1996).

Likewise, IT employs an automatic data processing system to schedulemaintenance work and report maintenance data for management informationand control. With automatically scheduled preventive maintenance activities,there is a great reduction in emergency repairs, which increases equipmentavailability, improves the good working condition of the equipment, andimproves the quality of the production process and in totality improves thequality of the products. Pintelon et al. (1999) present some case experiences,whereby IT has been effectively implemented in the areas, such as in themanagement of work orders, expert systems for failure diagnosis of electronicequipment, and in configuration-based logistic support (CBLS) in a virtualenterprise.

The majority of modern computerised maintenance management systems(CMMS) have in-built maintenance material management systems. Materialsused and their costs are helpful for keeping inventory up to date and chargingmaterials to each piece of equipment. Having the material identified by itstracking number in the inventory control system is essential for documentingproper part usage and tracking and bill of material building (Winston, 2003).The CMMS can be used to control maintenance tasks such as the addition offluids, the changing of filters, the tightening of fittings, bearing inspection,lubrication, and plant and equipment inspections can be documented andmanaged using the system. Another application of CMMS is in periodicinspections. Leaks, fluid contamination, wear, condition of seals, vibration andnoise, and the condition of cables, wires, lights, and safety devices can berecorded (Veloz, 1998).


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Gould (1998) commented that the IT, which is the main essence behindtoday’s CMMS, is truly beyond after-the-fact score keeping. Properly deployedCMMS make information actionable for better maintenance decisions inreal-time. Using the CMMS enables the maintenance personnel to pull thefailure records of all the motor drives in the factory, for example, andgraphically display their operational and failure trends, which leads todynamic 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 tothe fact that either the same work is done with less effort or because the samework is done in less time. Either way, the computer cuts the cost per unit ofwork accomplished, saving the company money. CMMSs help keep everythingup and running as inexpensively as possible where downtime is reflecteddirectly in product costs (Gould, 1998).

Lamendola (1999) shows that the modern CMMS have very powerfulfeatures. The features include accounting, trending, and predicting functions.The CMMS can be tailored to collect data to what the end user needs. Forexample, if one wants to know how many minutes of downtime the plant airmotors suffer each month due to clogged air filters, one can set the system up totell you that. Likewise, if one wants to compare that information to whathappened in previous months it is possible to do that. That kind of powerfulfeature paved the way for advanced trending and prediction, based on realdata. 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 suchas information on equipment failure and repair characteristics, and on thecorresponding costs which can be used in strategic (i.e. long-term) planning, intactical (i.e. medium-term) planning and on operational (i.e. short-term)planning.

Through proper application of IT the maintenance department can get directinformation from the manufacturers of the equipment on importantmaintenance data. For example, PSDI Maximo users have electronic accessto maintenance and reliability benchmarking data from HSB ReliabilityTechnologies, a maintenance engineering consulting company. Users canautomatically load preventive maintenance tasks directly into their Maximomaintenance management systems. The one-click access to HSB’s exclusivereliability-centred maintenance information is integral to achieving optimalequipment performance and reducing the system’s implementation time(Gould, 1998).

Computerisation also beneficially affects maintenance work itself. Usingthe 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 forthe specific circumstances of the job. The computer cuts the planner’s time

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and, because the standard plan has all the parts and tools identified forsuccessfully performing the maintenance job, ensures that the job is doneright and with a minimum backtracking to get forgotten items. ModernCMMS are using open database compliance (ODBC), which allows quantumleaps in maintenance management and performance and file standardization.The file standardisation paved the way for other developments, such asadvanced analysis (Lamendola, 1999).

The computer can also be used to determine the most cost-effectivepreventive maintenance interval, to manage inventories of spare parts and toreduce the expense of training new personnel. In short, the objective here is toreduce the following cost elements as far as computerisation of maintenancework is concerned:

. inventory control costs;

. downtime costs; and

. labour costs.

Sometimes the machine fails because it is running out of spec during theproduction run. Such poor performance would not have occurred if propermaintenance was performed on the equipment and equipment utilization wasbeing tracked.

The trend in modern maintenance IT systems is to integrate maintenancesystems to enterprise resource planning (ERP) and other business systems.This integration creates “synergy” of the whole production system. Forinstance, the integration lets maintenance users transfer spare parttransactions and update work orders with part data and costs contained inthe ERP inventory module, or equipment usage data, which is critical for thepreventive maintenance (PM) schedules generated by the CMMS, can beautomatically updated using the equipment run times in the ERP shop floorcontrol module (Gould, 1998).

If computers are properly managed, they substantially increase productivity(Mensching and Adams, 1991). Productivity is generally determined byconsidering the relationship between input and the output. The inputs to beconsidered in this context are all the costs and resources utilised in themaintenance of the equipment. These include annual IT costs, labour costs,downtime costs, materials and spare parts costs used in the maintenance of theequipment. However, Pintelon et al. (1999) caution that buyinghighly-sophisticated IT hardware and software is not the complete answer;IT is only an enabler of changes. Therefore, to benefit from the implementationof IT, the better utilisation of IT resources should be accompanied by positivechanges in an organisation.

The percentage contribution of the maintenance activities towards totalproduction can be determined as output. Both the input and output data beforeand 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 aftercomputerisation of a maintenance department. Now knowing that manyindustries have taken efforts in introducing IT in their maintenancedepartments, the problem to be solved is: have they achieved any costreduction, an improvement in quality or an increase of productivity byintroducing IT?

ObjectiveThe objective of this research is to substantiate quantitatively the impact ofintroducing IT in the maintenance department with regard to the reduction ofoperational cost, improvement of the quality of products and improvement ofproductivity.

Research methodA quantitative analysis of the data obtained in this research work is done inrespect to the amount of downtime of the equipment and an analysis of themaintenance cost before and after the computerisation of the maintenancedepartment. The method used to collect the data for analysis involved thequestionnaire (see Appendix) in which the researchers collected quantitativedata regarding the downtime, and the cost involved in the introduction of IT inthe maintenance department. In addition, the researchers used documentaryreview, whereby the archival records of the company were visited. Likewise,direct interviews were used to collect the opinions of the interviewees andexplanations on some of the information, which was not clear from the datacollected.

Description of case study areaTPCC, is located about 30 kilometres from Dar es Salaam city centre. It hassome 30 years’ experience of cement manufacturing and distributionthroughout East Africa. Formerly, TPCC was a public company, but now itis owned jointly with Scancem International, being a cement-producingcompany in Europe. From 1985, a substantial rehabilitation program started tomodernise equipment and to upgrade machinery. The modernisation programwas not only in the fabric of the plant, but also in such elements as high-calibremanagement, preventive maintenance, computerisation, effective distributionand quality assurance.

Cement production process at TPCCTPCC manufactures cement from limestone and clay that are quarried close tothe plant. A fleet of dump trucks transports the raw material to one of the twocrushers. It is reduced to the necessary fineness for feeding to one of three kilnsby a combination of crushing and milling. Prior to entering a kiln, materialpasses through a pre-heater consisting of a series of cyclones heated by the

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kiln’s hot exhaust gases. The material is dried and partially calcimined beforeentering the kiln, aiding fuel efficiency. At the final stage of the productionprocess the cement clinker product is mixed with controlled quantities ofgypsum and ground into cement.

Maintenance department at TPCCThe maintenance department at TPCC is under the leadership of a deputymaintenance manager. The maintenance activities of the whole plant fall underthree departmental managers; namely, engineering manager, project managerand production manager. The deputy maintenance manager undertakes themaintenance planning and control, prepares and defines the annualmaintenance objectives, co-ordinates and controls all the maintenance andproduction 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 maintenanceunit. The work orders range from preventive to breakdown maintenance. Theproject manager undertakes every new project introduced in the plant. Sincenew projects do not occur every day, the project manager is assigned thepreventive maintenance unit activities. These activities include preparation ofthe master maintenance schedule and issuing of work orders to threeworkshops. Preventive maintenance unit personnel carry out some of the workorders.

The production manager has dual activities: apart from leading theproduction crew and all its activities to meet the production targets, he alsoleads a small group of maintenance personnel attached to him to meetemergence repair or preventive maintenance detected under regular productionwithout depending on assistance from either of the three workshops or thepreventive maintenance unit.

In the effort to improve the level of plant’s maintenance activities and toensure capacity utilisation, the maintenance department introduced acomputerised maintenance management system known as SMS in 1991.However, the SMS was not compatible for the year 2000, therefore themanagement introduced a new computerised maintenance managementsystem known as MP2.

The MP2 system is operated and controlled by the preventive maintenanceunit (PMU). The PMU is linked through a computer network with theengineering department, computer department, processing department and


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purchase department. The purchase department controls procurements ofmaterials and spare parts for the plant.

Benefits of IT in maintenanceThe benefits of IT can be classified as cost saving or cost avoidance, bothof which are usually quantifiable or tangible. Intangible benefits havequality features, which are difficult to quantify. The benefits of IT in themaintenance department can also be expressed in terms ofcost-displacement approach. In cost-displacement approach, the savings,in money or time, are accrued by making people more productive. Forexample, a word-processor can help a secretary type more pages in lesstime. In some cases, it is possible to actually identify the money that issaved (i.e. hard dollar saving).

In addition, the introduction of IT increases efficiency; this efficiency gain isnormally associated with cost reduction. Hard dollar savings do not always implycutbacks; however, “cost avoidance” benefits soccur when the efficiency gainsallow one to do more with the same resources. For example, a word-processormay allow a business to grow without hiring more secretaries. Therefore, for thecase of maintenance activities, typists can produce more work orders by usingmaintenance 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 ofcommunication between corporate (e.g. ERP) and shop-floor systems (Pintelonet al., 1999).

The research modelThe model used in this study shows the relationship between the computerisedmaintenance management system and the achievements in services and theperformance (see Figure 1). The parameters associated with the performanceare productivity, cost reduction and quality.

According to the model, each performance parameter depends on differentvariables:

Figure 1.A descriptive model for acomputerisedmaintenancemanagement

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. the productivity depends on the output/input ratio;

. quality as far as maintenance is concerned depends on productspecifications, availability and quality of the production process; and

. cost reduction parameter focuses in maintenance costs, downtime costsand inventories costs.

Proper and effective maintenance of the plant and equipment would result inminimising maintenance costs and reduces frequency of equipmentbreakdowns, thus improving overall plant productivity. Cost reductionimplies savings in the cost of production and distribution through theelimination of wastes and inefficiency. In other words, cost reduction meansreduction in unit costs and does not necessarily imply reduction in totalexpenditure, and it may involve increase in expenditure (Gupta, 1994). Forexample, a firm may spend more on research and development to improveproduct design so as to reduce unit cost of production. In this context, theTPCC incurred cost to purchase PCs, software and training of staff for thecomputerisation of the maintenance department with the purpose of reducingcost in the following variables:

. maintenance costs (labour, job planning, training, etc.);

. inventory costs; and

. downtime costs.

Reduction of labour costsA reduction in labour costs can be achieved through better machine loading,reduction in batch frequency, work simplification, training and motivation ofworkers, as well as the provision of better working facilities. Therefore, thecomputerisation of the maintenance department can be considered as a methodfor providing better working facilities with the objective of work simplification.The computerisation of the maintenance department simplifies the followingtypes of work:

. Job planning. The computer simplifies the process of job planningsignificantly. First, if a standard job plan already exists, the plan canbe retrieved and tailored to the specific task with minimal effort. Suchstandard plans would identify parts, tools and manpower requirements,as well as define the work to be done, eliminating the guesswork andpossible errors of writing a plan from scratch. Second, if a new jobplan must be developed, the planner can access all the informationshe/he needs from the various computer-stored files; equipment partslists and maintenance histories; parts and tools inventory and locationdata and personnel records concerning the skills and eligibility.Therefore, using a computer has saved the planner’s time and thusreducing costs.


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. Personnel record keeping. Personnel records are easily maintained as acomputer database, similar to an inventory system. Up-to-date records onall maintenance staff can quickly be requested by a job planner todetermine which employees have certain requisite skills, familiarity withparticular equipment or are eligible for overtime. The files can also beexpanded to track the time worked by the employee, and, in conjunctionwith salary data, can provide cost figures for input to a detailed job-costaccounting system.

. Training. The computer can function as an iterative learning tool,providing detailed maintenance training for new employees, updates andrefreshers on new equipment and maintenance techniques for currentemployees. The training is self-paced, iterative and designed to keep theemployee involved and interested. The computer-aided instruction ismore efficient than a class with an instructor, because it can be used atany time for any number of students and the information is retainedlonger than if the employee were merely given a book to read on thesubject. The objective of training is to make an employee learn. Thislearning may be defined as the technological changes that lower cost as aresult of experience (Gupta, 1994).

Reduction of inventory costsInventories of equipment, parts and materials in stores are easily maintainedin a computer database. Equipment records can contain all data aboutmachines, including parts lists and even maintenance records, makingdetailed equipment information readily accessible to authorised computer orterminal devices throughout the facility. Parts and stores inventory system,track volumes on hand, locations, consumption and shrinkage, reorder pointsand unit costs.

The inventory system can even be used to automatically trigger reorderand to maintain parts lists and manufacturers of acceptable substitute items.By computerisation of the inventory system it is expected to reduce theordering costs and holding costs. Therefore, both questionnaire and dataobservation approaches were used to find out if, after computerisation of theinventory control system, the ordering and the holding costs have beenreduced.

Reduction of downtime costsReduction of downtime cost can be achieved by improving the workingcondition of the production equipment, which, in return, reduces the number ofbreakdowns. The lower the rate of breakdowns the lesser is the downtime.Computerisation of the maintenance management activities improves thequality of equipment maintenance, which improves the working condition ofthe equipment. The work order process flow is the best method to be adopted to

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trace out how computerisation of the preventive maintenance schedule couldreduce the downtime when compared with the manually-operated preventivemaintenance schedule.

Productivity improvementProductivity 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. Higherproductivity means producing more from a given amount of inputs orproducing a given amount with lesser inputs (Gupta, 1994).

Productivity can be either at the level of a plant or at the macro level. In thisresearch the productivity was analysed at the plant level. An increase inproductivity means an increase in output that is proportionately greater thanan increase in inputs. Productivity may be measured either on aggregate basisor on individual basis. On aggregate basis output is compared with the inputfactors 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 andthis is called partial productivity or factor productivity. Because productivity isthe outcome of many input factors, this study was focused on maintenanceproductivity. The first consideration was the maintenance management costswith IT-related inputs and the second step considered maintenancemanagement costs without IT inputs. In the first step, the maintenanceproductivity 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 costsunder 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 maintenancemanagement 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 1984/1985for the purpose of rehabilitating the production equipment in order to improveproductivity. These rehabilitation costs are also distributed as annual investedcosts 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 thecompany, the questionnaire approach was used to collect productivity datafrom the respondents. This productivity information was compared with thedata collected by observation approach. From the input and output datacollected, the productivity before and after computerisation were calculatedand compared with the results found from the questionnaire approach. Becausetotal production output is affected by many factors, it was agreed among themain stakeholders that maintenance contributes to about 30 per cent of totaloutput.

Quality improvementThe modern concept of total quality management emphasises that qualitycontrol is a responsibility to be shared by all people in an organisation. Themaintenance function acts in a supporting role to keep equipment operatingeffectively to maintain quality standards as well as to maintain the quantitativeand 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 ingood condition to maintain the standard of workmanship which, in turn,conform to specifications which, as a result, improves quality of theproduct. The product design specifications should be achieved at the end ofthe production process in order to minimise scraps as well as defective

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products. The failure of the equipment generally affects the productspecifications. Therefore, the task in this study was to look at quality fromthis point of view.

The quality of the production process is a variable, which is sometimesreferred to as producibility or manufacturability. It measures the extent towhich the product design can be readily produced with the facilities andprocesses available to the operating forces (Juran and Gryan, 1998). If thefacilities are not properly maintained to achieve the highest working conditionlevel this shall result in:

. product faults due to faulted equipment; and

. increase in work-in-progress costs, e.g. costs of wasted raw materials andaverage processing costs.

Research resultsCost of implementation of IT at TPCCThere is no common agreement on what constitute an IT investment, andwhether IT investment is a capital investment or an expenditure (Weill, 1991;Bacon, 1992). Weill and Olson (1989) suggest that the definition on ITinvestment should be as broad as possible to encompass all IT-relatedexpenditures, such as people, training, documentation, consulting, externalservices, equipment, software, networks and communications. However, in thisresearch work it was only possible to retrieve data for purchase and installationof IT at TPCC. TPCC started the computerization of the maintenancedepartment in the year 1991. From 1991 to 1997, the computer software usedwas known as SMS, which was found to be not compliant to the millenniumbug (Y2K problem). Therefore, in 1998, they installed new software MP2 thatwas Y2K compliant. The cost for purchase and installation of the SMS systemin 1991 was not readily available, since it was installed under the assistance ofScancem International Experts as part of general contract to rehabilitate TPCC.The cost for the purchase and installation of the MP2 system in 1998 was Tshs33,634,329/= about US$ 50,000 (at that time).

Cost reduction after the implementation of ITRegarding the reduction of cost of maintenance, 86 per cent of the respondentsagreed that using computers, more work orders could be produced and thisreduces cost. Of these respondents, 58 per cent recommended that over 50 percent of cost reduction have been achieved if compared to manual work ordersproduction. Likewise, 86 per cent of the respondents felt that by usingcomputers the task of job planning has been reduced by 31-50 per cent.

After having the responses from the questionnaire, the researchers made adocumentary review of the maintenance cost data for the period 1984-1991before computerisation and between 1994-1999 after computerisation. Theresults 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 aftercomputerisation. However, one should note that the Tanzanian currency(Tshs.) is not a stable currency; the increase in the costs, for example, in theyear 1995 and 1996 could have been caused by devaluation of the Tanzanianshilling. To avoid this problem the researchers decided to convert the currencyto equivalent US dollar value at that period. The next reason in explaining whythe 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 thecompany and have a proper recording, whereas before computerisation it wasalmost 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 1988/1989were not available due to poor record keeping. This implies also that some ofthe maintenance costs were not properly recorded during the manual system.

Figure 2 summarises the analysis of the maintenance costs after thecomputerisation. From the data depicted in Figure 2, one can see that themaintenance costs after the computerisation of the maintenance departmenthas 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 costsRegarding the inventory levels, 92.9 per cent of respondents believe thatcomputerisation of the inventory system has helped in decreasing the holding

Year

Total annualmaintenance cost in

TshsExchange rate with

US$aTotal annual cost

in US$

Percentageincrease of

maintenance cost(using US$)

1994 778,000,000 512 1,519,5311995 1,009,000,000 581 1,736,661 14.291996 1,567,000,000 582 2,692,440 55.041997 1,496,000,000 630 2,374,603 211.801998 1,008,000,000 660 1,527,273 235.681999 926,000,000 750 1,234,667 219.16

Note: a Exchange rate source: Bank of Tanzania Economical Bulletin, Vol. XXIX No. 1

Table II.Maintenance costs forthe period 1994-1999 atTPCC aftercomputerisation

Year

Total annualmaintenance cost

in Tshs

Averageexchange ratewith US$

Total annualcost in US$

Percentageincrease of

maintenance cost

1984/1985 26,770,539 132 202,8071985/1986 29,027,648 156 186,075 28.251987/1988 30,920,375 198 156,164 216.071990/1991 30,965,975 219 141,397 29.46

Table I.Maintenance costs forthe period 1984-1991 atTPCC beforecomputerisation

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and ordering costs. An amount of Tshs 400 million was saved as holding costafter selling some spare parts, which were kept in storage for many yearswithout being used. Before computerisation, the ordering of spare parts wasnot scientifically conducted. There was no proper information of theconsumption rate of different kinds of spare parts. Consequently, the storewas full of different kinds of spare parts, some of which were not readilyneeded. After computerisation it was possible to identify the spare parts whichare frequently needed, and those whose consumption rate was very low. It wasalso possible to identify some spare parts which are no longer needed by thecompany. Therefore, the company disposed of those spare parts which were nolonger needed by the company and reduced the stock of the low rateconsumption spare parts. By doing so the company saved Tshs 400 million.

Analysis of the holding and ordering costs are depicted in Table III. If oneuses the Tanzanian shilling for analysis it may be concluded that only from1998 to 1999 both ordering and holding costs are decreasing. However, afterconverting the costs to a stable currency, it was shown that the inventoryholding cost has been decreasing after the introduction of the computer. Afterintroducing the new maintenance software MP2, adequate computer trainingwas given to the purchase department staff and this has allowed them to utilisethe software effectively. Consequently, they can use the computer to order onlythe necessary spare parts needed during a particular period.

Figure 2.Maintenance costs afterthe computerisation of

the maintenancedepartment at TPCC


425

Figure 3 summarises the trend in inventory holding costs. It is clearly depictedby the trend line that the holding cost has been decreasing for the period 1993to 1999.

In 1984, TPCC started a rehabilitation program to improve the plant conditionin order to improve the production capacity. The productivity improved from0.57 in 1984, when rehabilitation started, to 5.50 by 1990. The mean productivitybefore computerisation was 1.98. The data show that after introducing IT thehighest productivity achieved was 6.08 in 1991. The mean productivity achievedafter computerisation is 5.08, which is higher than the 1.98 attained beforecomputerisation. If these two means of productivity are compared it can beconcluded that productivity has improved above 50 per cent.

Through the interview method, the responses on downtime show that 86 percent of respondents agreed that by introducing IT in the maintenance

Figure 3.Inventory holding costsafter computerisation ofmaintenance departmentat TPCC

Years and amount spent in ordering and holding costsItem of inventory costcontrol 1993 1994 1995 1996 1997 1998 1999

Ordering costs [mill.] 3.0 3.5 6.0 6.5 7.0 7.6 6.1Exchange ratea 403 512 581 582 630 660 750Equivalent cost in US$ 7,444 6,836 10,327 11,168 11,111 11,515 8,133Holding costs [mill.] 0.5 0.6 0.6 0.7 0.71 0.78 0.60Equivalent cost in US$ 1,241 1,172 1,033 1,203 1,127 1,182 800

Note: a Exchange rate source: Bank of Tanzania Economical Bulletin (1999)

Table III.Inventory costs after thecomputerisation

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department, downtime has been reduced by 50 per cent. Regarding the overallcost of maintenance, 79 per cent of respondents agreed that, in totality, the useof IT in the maintenance department has reduced the downtime cost by 50 percent. However, a quantitative analysis of downtime data showed that the meandowntime before computerisation was 283 hours per month, while aftercomputerisation is 256 hours per month, which is 27 hours saving. Thisrepresents an average of 9 per cent decrease of downtime per month aftercomputerisation. This situation is depicted in Tables IV and V.It was not possible to get quality data from TPCC because the company refusedto disclose this data for security reasons. Therefore, the method used toindirectly find information about the quality performance at TPCC wasdetermination of availability of the equipment before and after computerisationof the maintenance department.

Data on the availability of the equipment are shown in Table VI. The datashow that the availability has been fluctuating between 45 per cent and 93 percent and the mean availability is 65 per cent. The availability before theintroduction of CMMS was around 50 per cent. This shows an increase by 15per cent of the availability before the introduction of CMMS. Availability beinga parameter of quality, we can also assume that quality has improved by 15 percent as far as availability is concerned.

ConclusionIn this research, the main objective was to find out quantitatively, the benefitsof introducing CMMS in the maintenance department. The quantitative datashows that there has been a decrease in downtime of the equipment by 9 percent; the overall maintenance cost has decreased from the highest of US $2.7

Year Kiln no.Uptime(hours)

Down time(hours)

Monthlyaverage

down timein hours

Monthly averagedown time forthe whole plant

in hours

Mean totalmonthly averagedowntime for thewhole period in

hours

1987 I 4,834 3,926 327.17II 5,885 2,875 239.58 26.3III 6,081 2,679 223.25

1988 I 4,624 4,136 344.67II 5,472 3,288 274.00 297.6III 5,978 2,782 231.80 283.3

1989 I 4,832 3,028 252.33II 1,145 7,615 634.58 367.6III 6,169 2,591 215.91

1990 I 6,360 2,400 200.00II 5,844 2,916 243.00 244.8III 5,262 3,498 291.50

Table IV.Uptime and downtimebefore computerisation


427

million per annum in 1996 to about US $1.2 million per annum in 1999. Theproductivity has increased by 50 per cent and the availability of the equipmenthas increased by an average of 15 per cent. Therefore, the introduction ofCMMS has helped to improve the performance of the company in terms ofproductivity and reduction of the overall operational unit cost.

References

Adcock, K., Helms, M.M. and Jih, W.K. (1993), “Information technology: can it provide asustainable 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.

Year Kiln no.Uptime(hours)

Down time(hours)

Monthlyaverage

down timein hours

Monthly averagedown time forthe whole plant

in hours

Mean totalmonthly averagedowntime for thewhole period in

hours

1994 I 3,970 4,790 399.17II 4,925 3,835 319.58 335.4III 5,299 3,461 288.42

1995 I 7,796.3 963.74 80.31II 7,599.1 1,160.86 96.74 90.5III 7,627.9 1,132.13 94.34

1996 I 8,188.0 571.97 46.66II 8,146.3 613.73 51.11 51.7III 8,083.6 676.36 56.36

1997 I 2,870.3 5,889.7 490.81 256II 4,461.0 4,299.0 358.25 400.9III 4,516.5 4,243.5 353.63

1998 I 4,523.8 4,236.2 353.02II 5,139.3 3,620.7 301.73 312.6III 5,364.2 3,395.8 282.98

1999 I 3,576.2 5,183.8 431.98II 4,866.1 3,893.9 324.49 345.1III 5,414.1 3,345.9 278.83

Table V.Uptime and downtimeafter computerisation

YearAverage uptime

(hours)Average

downtime (hours) Availability ¼ UptimeUptimeþDowntime

Meanavailability

1994 4,731.3 4,028.7 0.541995 7,674.4 1,085.6 0.881996 8,139.3 620.7 0.93 0.651997 3,949.3 4,810.7 0.451998 5,009.1 3,750.9 0.571999 4,618.8 4,141.2 0.53

Table VI.Availability of themachine after theintroduction of IT in themaintenance

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Bank of Tanzania Economical Bulletin (1999), Vol. XXIX No. 1.

Bavu, E., Sheya, A., Mlawa, H. and Kawambwa, S. (1997), Culture of Maintenance for SustainableDevelopment in Tanzania, TechMa, Dar es Salaam.

Connolly, D.J. (1999), “Understanding information technology investment decision-making in thecontext of hotel global distribution systems: a multiple-case study”, dissertation, VirginiaPolytechnic Institute and State University, Blacksburg, VA.

Gould, L.S. (1998), “Keeping up, running and profitable with CMMSs”, AutomotiveManufacturing & 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, NewDelhi.

Juran, J.M. and Gryan, F. (1998), Juran’s Quality Control Handbook, 4th ed., McGraw Hill BookCompany, 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 maintenancemanagement 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 formaintenance 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, TheFree Press, New York, NY.

Stickel, E. (1997), “IT-Investitionen zur Informationsbeschaffung und Produktivitatsparadox”,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 caseexamples 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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AppendixJQME9,4

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435

Application andimplementation issues of a

framework for costing plannedmaintenanceMohamed 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 aframework for costing planned maintenance. It outlines the methodology for the development ofthe case study and presents the major findings of the existing maintenance-costing system of theorganization under study. It presents the results of a pilot study of the application of the proposedcosting framework to a sample of planned maintenance jobs. It provides recommendations andidentifies critical issues for a successful implementation.

Practical implicationsProper cost assignment has a major impact on maintenance operations. Theframework in this paper provides an effective tool for cost assignment andtracking cost efficiency. Knowledge about major cost derivers will enableorganizations to optimize the utilization of resources in their plannedmaintenance (PM) activities and processes. Also the costing framework willreveal inefficiencies in the maintenance system and will identify the need forupdating maintenance time standards and material requirements planningactivities.

IntroductionPlanned (preventive) maintenance

. . . involves the repair, replacement, and maintenance of equipment in order to avoidunexpected failure during use. The primary objective of planned maintenance is theminimization of total cost of inspection and repair, and equipment downtime (measured inlost production capacity or reduced product quality) (Mann et al., 1995).

It provides a critical service function without which major businessinterruptions could take place. It is one of the two major components of



The data on the implementation of the proposed framework for costing planned maintenancewas collected and reported by Mr Abdullah Al-Rubaian, Mr Sulaiman Al-Namlah, and Mr TurkiAl-Rasheed in their term project in ACCT 552 (Managerial Accounting) at King Fahd Universityof Petroleum & Minerals’ EMBA Program. Their efforts are highly appreciated.

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Journal of Quality in MaintenanceEngineeringVol. 9 No. 4, 2003pp. 436-449q MCB UP Limited1355-2511DOI 10.1108/13552510310503268

maintenance load. The other component is unplanned (unexpected)maintenance (Duffuaa et al., 2000). Planned maintenance could be time- (oruse-based) or could be condition-based (Duffuaa et al., 1998).

Over the years the maintenance literature has been replete with research onengineering and planning issues as well as on issues related to the effectivenessof realizing PM schedules. The costing and cost efficiency issues of PMreceived 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 theapplication 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-houseplanned (preventive) maintenance in its operations.

(2) Gained familiarity with the existing costing system of PM in thebusiness organization under study. This is achieved by a“walk-through” the system to understand its documentary cycle andinformation support.

(3) Documented the understanding of the existing PM costing system.

(4) Compared the existing PM costing system with the proposed costingframework and identified the gaps between the two.

(5) Tested the practicality of the proposed costing framework through apilot study of PM jobs.

(6) Made recommendations that would enable the organization under studyimprove its PM costing practices.

(7) Identified critical implementation issues of the proposed costingframework.

General overview of the framework for costing PMThe framework for costing PM proposed by Mirghani (2001) identifies thestandard cost elements (direct materials, direct labor, and support services) of aPM job. The documentary support for these cost elements is indicated and theyare cross-referenced with the planned maintenance job cost sheet (PMJCS) thatrepresents the core of the proposed costing framework. The frameworkexplains how actual cost data could be captured, the documents that could beused for the data capture, and how they are cross-referenced with the plannedmaintenance job cost sheet (PMJCS). The framework also explains how thecost-efficiency variances of a PM job could be generated and reported tomaintenance management.

Direct materialsDirect materials represent all materials and component parts that are related toa PM job and traceable to it in an economically feasible manner. Economicfeasibility of cost traceability assures the tracing, to a cost object, direct costs

Costing plannedmaintenance

437

that are material (significant) in amount only. This assures the costeffectiveness of the costing system. Direct materials requirements should bedocumented in a bill of materials (BOM). The BOM should allow for normalspoilage of materials if some spoilage is inevitable or related to inherentcharacteristics of the PM job. The BOM will provide the basis for determiningthe standard quantities of direct materials that will be reflected in Panel A ofthe PMJCS. The BOM also provides the necessary data for the direct materialssection of a PM work order.

Direct laborDirect labor represents all labor skills that directly work on a PM job and theircost is traceable to that job in an economically feasible manner. PM direct laborusually is comprised of a team of several skills needed to assure the quality andcost effectiveness of the maintenance job. Thus, the mix of the labor skills hasto 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 providesinformation about processes to be performed the labor skill(s) to be applied, andthe amount of labor time to be utilized under normal conditions. The JWFSshould indicate if a certain degree of substitution of labor skills is permissiblein order to control the quality and cost of the PM job. Furthermore, the JWFSshould incorporate any inevitable labor downtime due to some inherentcharacteristics of the maintenance job. Inevitable labor downtime could be dueto waiting time for materials and parts, fatigue, and attendance to personalneeds. This is necessary so that the labor time standards are reasonablyattainable. The JWFS will provide the basis for determining the standard hoursand mix of direct labor that will be reflected in the direct labor section ofPanel A of the PMJCS. The JWFS provides the necessary data for the directlabor section of a PM work order.

Support activitiesIn addition to direct materials and direct labor, a PM job would require theservices 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 anddirect labor costs. They can be labeled as PM overhead costs. These costs arecommon to all PM jobs and are not amenable to traceability in an economicallyfeasible manner. Hence, the only feasible way to reflect them as part of the costs

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of a PM job is through allocation. The question is: on what basis? The followingapproaches could be followed:

(1) Look for a single common denominator to serve as a basis for PMoverhead costs allocation, like maintenance job labor hours or machinehours. Labor hours could be the relevant allocation basis if themaintenance job is labor-intensive. Machine hours could be a relevantallocation basis if the maintenance job requires the heavy use ofmachinery, like in a machine shop. However, this approach assumes thatall maintenance labor hours or machine hours require the same amountof overhead support. Furthermore, most likely a single basis foroverhead allocation may not have any causal relationship with theincurrence of PM overhead costs. Hence, using a single rate for applying(allocating) these overhead costs to PM jobs, could lead to costcross-subsidization among maintenance jobs, and eventually would leadto the distortion of PM costs making the cost information potentially (ifnot totally) misleading. In today’s business environment, the tolerableerror margin is narrower and organizations can no longer afford suchmistakes and remain competitive or get funded (Cokins, 1998).

(2) Since there are different support activities within PM, and sincemaintenance 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 overheadcosts are material (significant) in amount in relation to PM total costs.Activity-based costing (ABC) provides the answer. ABC is a system thatfirst accumulates support (overhead) costs of each support area and thenassigns 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 budgeteddemand.

An ABC system provides the prelude for improving the operations of anorganization through activity-based management (ABM).

(3) Use the predetermined overhead rates in the last of the four options toapply support overhead costs to PM jobs on the basis of itsplanned/actual usage of that activity. The predetermined overheadrates for the different support activity areas and the planned quantity ofsupport in each activity area provide the basis for entries in the supportservices section of Panel A of the PMJCS. ABC provides appropriate


439

building blocks for reliable maintenance costing as well as a betterunderstanding of the cost structure of a maintenance operation.

(4) Business organizations face significant threats in an increasingly globalenvironment. In this regard, ABC/ABM can support a more strategicapproach to cost management and a multitude of other businessdecisions (Fahy and O’Brien, 2000). ABC can provide more usefulinformation for decision making than traditional costing, but it involvesa paradigm change in thinking to make it truly effective (Walker, 1998).The ABC exercise provides information that guides resourcesmanagement, performance measurement, and more effective utilizationof resources.

Background of the business organization under studyARASCO is an agricultural services organization working in the Kingdom ofSaudi Arabia for the last 20 years. It has a number of facilities and serviceorganizations implementing planned preventive maintenance programs toensure continuity of operations and maximization of uptime. ARASCO is ajust-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 andaccreditation); and

. meat processing.

At ARASCO, PM is basically performed on equipment and facilities with apredetermined frequency. The main goal of performing PM periodically is toextend equipment life and assure its capacity in continuously supporting thecompany’s goals and targets. ARASCO is heavily dependent on PM formaintaining its ability to serve effectively and efficiently as a JIT supplier to itscustomers. Planned (preventive) maintenance is very critical to ARASCO’sbusiness 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 whichmeans that any downtime will also have serious implication on itstransportation cost and production and delivery schedules; and

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. the cost of unplanned downtime is very high, since the plants areprocessing plants and any breakdown will very likely cause a completeshutdown.

The frequency selected for performing PM tasks takes into consideration themaximum time allowable before failure or extensive and costly breakdownmaintenance work is performed. Defining the right tasks and their associatedintervals for execution is an important factor for controlling the cost of PMwork without sacrificing its value for the business.

Implementation of the framework of costing PM at ARASCOARASCO’s Al-Kharj Feed Mill was selected for the implementation of thePM-costing framework, since its maintenance philosophy and practices weresimilar to those exercised in other ARASCO facilities.

Al-Kharj Feed Mill has a planned preventive maintenance program sinceits inception in 1987. It has a yearly planned preventive maintenanceschedule which provides the details for the planned preventive maintenancework to be executed for the whole year, starting with the first week inJanuary and ending up on week 52 of the calendar year. For every week, thelist of all the equipment to be checked and maintained is indicated, with thetime needed to perform the job. The planned oiling and greasing program isscheduled separately.

At the beginning of every week the planned preventive maintenanceschedule covering the mechanical electrical and oiling and greasing for thewhole week is issued to the maintenance crew. Preventive maintenancechecklists are issued for every job order. The checklist’s upper part describesall the works to be done, and the lower part provides a space for a list of spareparts actually used.

During the execution of the maintenance work the maintenance crews writedown their remarks on the time it took them to complete the required work. If itis longer than the scheduled time, and also the number of people utilized, it isobvious that recording of the time and manpower was informal and looselyrecorded.

Weekly maintenance reports summarizing all the maintenance work carriedout 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 embeddedinto its total maintenance costs without any clear distinction betweenbreakdown and PM. It is also clear that the main objective of the PM activity isto ensure the smooth and continuous operations of ARASCO’s plants, and tomaintain its image as a reliable supplier to its own customers.

The existing PM system in ARASCO’s plants has succeeded in minimizingbreakdowns and the unplanned down time to less than 2 percent, but it isinadequate in providing cost information that could contribute to significant


441

improvements in its cost competitiveness and efficiency. By reviewing theunderlying documentation of the PM system, it has become apparent that theAl-Kharj plant has the ingredients for implementing the proposed costingframework. All the data inputs could become available by adopting thedocumentations recommended in the proposed costing framework to identifyall the proper inputs needed to obtain the standard and actual costs of PM atAl-Kharj plant.

Major findings of the existing system in comparison with proposedcosting frameworkBy analyzing the existing system, what is available and what is needed tosatisfy 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 thedevelopment of the standard inputs needed to carry out the scheduleeffectively and efficiently.

. There is no available list of material requirements for every PM job, butspare parts were ordered during the job execution. The materialrequirements should be identified at the planning stage. The plant hasenough historical data and manufacturers’ recommended maintenanceprogram for every machine, which could provide the basis for developinga BOM for each PM job. Such information is needed for the standarddirect 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 providethe 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 bedeveloped on the basis of the PM crew experience, time and motion study,and the knowledge gained during the implementation of the proposedcosting 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 jobtook longer than expected. Furthermore, the breakdown of the time it tookto 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 ofthe 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. Supportactivity costs could be assigned to PM jobs through ABC.

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It is noteworthy that the maintenance department provides maintenanceservices to a number of facilities at Al-Kharj complex, which consumesupport services resources differently. This will require an extensive and anelaborate study of the support services activities, costs, and cost driverswith a careful ABC analysis to ensure proper development of multipleoverhead rates. If this is not done methodically, the PM-costing systemwould result in cost cross-subsidization among maintenance jobs andamong cost centers. This would make the cost information misleading andwould 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 bereflected in the PMJCS. The actual support activities card described in theproposed costing framework will provide the actual utilization of supportservices by a specific maintenance job.

The pilot studyThe pilot study included 20 PM jobs. Ten jobs were from week 44 of the year2002 and ten jobs were from week 16 of the year 2003. The two weeks wereselected randomly. Any other two weeks would have given similar results.

The data for week 44 were obtained from the historical records of themaintenance department, whereas week 16 data were obtained through theactual implementation of the proposed costing framework during that week.Figure 1 and Tables I and II show sample results of applying the proposedcosting framework.

The results showed that the variances were generally very high, whichunderscores the need for better planning and more accurate and up-to-date coststandards. This indicates that the cost standards have to be continuouslyreviewed to improve the PM program. The results still indicate that the solemotivation behind the PM program is to minimize downtime withoutconsidering the cost aspects of it.

The pilot study provides evidence of the possibility of adopting the proposedcosting framework to assure the cost efficiency of a PM system. It alsoindicates the need for continuous improvements to the planning side of the PMprogram to improve reliability while realizing cost efficiencies. What isimportant is that there are enough indications that the proposed costingframework will contribute to capturing the PM cost elements and provideinformation that contribute to improving the cost efficiency of the overall PMsystem.

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 theprerequisites for a successful implementation.


443

Figure 1.Planned maintenance jobcost sheet

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444

Directmaterialcost

Directlabor

cost

Supportservices

cost

Total

Equipment

Description

AB

C%

AB

C%

AB

C%

AB

C%

FM

21074

Screw

conveyor

198.52

482.02

283.50

142.81

30.00

47.50

17.50

58.33

68.33

85.00

16.67

24.40

296.85

614.52

317.67

107.01

FM

21072

Ham

mer

mill

0.00

30.16

30.16

#DIV/0!

10.00

17.50

7.50

75.00

68.33

85.00

16.67

24.40

78.33

132.66

54.33

69.36

FM

21069

Elevators

0.00

0.00

0.00

0.00

30.00

30.00

0.00

0.00

68.33

85.00

16.67

24.40

98.33

115.00

16.67

16.95

FM

21086

FM

21190

Com

pressor

GA-55

240.98

240.98

0.00

0.00

10.00

15.00

5.00

50.00

964.60

981.27

16.67

1.73

1215.581237.25

21.67

1.78

AV2

1041

Toyota

Cam

ry98

288.08

41.34

246.74

285.65

120.00

105.00

215.00212.50

68.33

85.00

16.67

24.40

476.41

231.342245.07251.44

HV2

1001

Forklift#01

TCM

15.00

15.00

0.00

0.00

40.00

32.50

27.50

218.75

68.33

85.00

16.67

24.40

123.33

132.50

9.17

7.44

HV2

1003

Forklift#03

TCM

406.84

523.21

116.37

28.60

25.00

55.00

30.00

120.00

68.33

85.00

16.67

24.40

500.17

663.21

163.04

32.60

HV2

1011

Wheel

Loader

#2

238.80

550.80

312.00

130.65

45.60

60.00

14.40

31.58

68.33

85.00

16.67

24.40

352.73

695.80

343.07

97.26

HV2

1013

Track

Mobile

U2

1400

34.00

34.00

0.00

0.00

30.00

37.50

7.50

25.00

68.33

85.00

16.67

24.40

132.33

156.50

24.17

18.26

WT2

1038-08

WTP

Product

Water

Pump

282.22

244.94

37.28

13.21

60.00

80.00

20.00

33.33

68.33

85.00

16.67

24.40

410.55

409.94

20.61

0.15

Total

1704.442162.45

458.01

26.87

400.60

480.00

79.40

19.821579.571746.27166.70

10.55

3684.614388.72

704.11

19.11

Notes:

A=Planned;B=Actual;C=Variance

Table I.Week No 16 – 2003

Preventive maintenanceplanned vs actual cost

summary


445

Directmaterialcost

Directlabor

cost

Supportservices

cost

Total

Equipment

Description

AB

C%

AB

C%

AB

C%

AB

C%

FM

21072

Ham

mer

mill

0.00

0.00

0.00

#DIV/0!

20.00

12.50

7.50

37.50

68.33

85.00

16.67

24.40

88.33

97.50

9.17

10.38

FM

21077

FM

21136-2

Unionspecial

sewing

sachine

0.00

386.13

386.13

#DIV/0!

2.00

12.00

10.00

500.00

68.33

85.00

16.67

24.40

70.33

483.13

412.80

586.95

FM

2

1140-1151

Elevators

0.00

23.54

23.54

#DIV/0!

12.00

40.00

28.00

233.33

68.33

85.00

16.67

24.40

80.33

148.54

68.21

84.91

FM

21189

Com

pressor

GA-30

0.00

500.00

500.00

#DIV/0!

20.00

25.00

5.00

25.00

68.33

85.00

16.67

24.40

88.33

610.00

521.67

590.59

FM

21200

Boiler

General

3448.903512.22

63.32

1.84

80.00

92.50

12.50

15.63

68.33

85.00

16.67

24.40

3597.233689.72

92.49

2.57

FP2

1004

RollerMill#

1(Ferral

Ross)

200.00

231.90

31.90

15.95

20.00

20.00

0.00

0.00

68.33

85.00

16.67

24.40

288.33

336.90

48.57

16.85

SL2

1009

Chain

Conveyor

0.00

0.00

0.00

#DIV/0!

40.00

35.00

25.00

212.50

68.33

85.00

16.67

24.40

108.33

120.00

11.67

10.77

AV2

1042

ServiceBus

GMC-1994

642.13

642.13

0.00

0.00

120.00

285.00

165.00

137.50

68.33

85.00

16.67

24.40

830.46

1012.13

181.67

21.88

HV2

1004

Forklift#04

TCM

0.00

38.91

38.91

#DIV/0!

15.00

37.50

22.50

150.00

68.33

85.00

16.67

24.40

83.33

161.41

78.08

93.70

HV2

1005

Forklift#05

TCM

0.00

10.12

10.12

#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

Total

4291.035344.951053.92

24.56

344.00

612.00

268.00

77.91683.30

850.00

166.70

24.40

5318.336806.951488.62

27.99

Notes:

A=Planned;B=Actual;C=Variance

Table II.Week No. 44 – 2002preventive maintenanceplanned vs actual costsummary

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446

. The direct materials and the man-hour requirements have to be reviewedand continuously updated to ensure the proper utilization of inputresources. The actual utilization of these two resources has to be properlycaptured to ensure that the figures recorded reflect reality, and that thevariation between standard and actual costs of PM are within theacceptable control limits. Acceptable control limits could be determinedstatistically through SPC techniques or through managerial judgment.Significant variances need to be investigated and explained resulting inappropriate corrective action(s). This should enhance furtherimprovement and development of a PM program that achieves theobjectives of high reliability and cost efficiency.

. The support services activities have to be analyzed using an ABCframework. It is important that this should be done methodically becausethe maintenance department support services are provided to a number offacilities in Al-Kharj complex; namely, the feed mill, the starch wet mill,the glucose refinery, the premix and the aqua feed plants which consumesupport services differently.

. An ABC system could be implemented in the entire Al-Kharj complex. Across-functional ABC implementation team could be formed to engage inactivity analysis and identification of causal cost drivers.

. The results indicated a need continuously to update time standards andthe process of planning PM.

. The spare parts required for the planned preventive maintenance systemshould be specified in BOM as part of the planning schedule and shouldnot be only identified as the work being executed. This will help inpreparing a realistic maintenance budget, and also provide guidance forpurchasing and managing the spare parts inventory properly. Theavailability of spare parts and other materials also require an effectiveinventory management system. This could be accomplished by utilizingthe plant historical data, and manufacturer’s recommended technicaldata.

. The planned preventive maintenance man-hour requirement per laborskill should be identified for every job order in detail. This could beobtained through analysis of plant historical data, time-and-motionstudies, and experience gained by the preventive maintenance team. Theactual man-hour per labor skill used in performance of the job should beproperly captured through labor time tickets.

. In implementing the proposed PM-costing framework, ARASCO canmake use of its enterprise resource planning (ERP) system since it hasfunctionalities that support the implementation of such a framework. Itcan easily accommodate the PMJCS and related forms. ERP systems do


447

support ABC systems, integrate operational and cost data, and have aflexible user-friendly reporting structure.

Critical implementation issuesThe proposed PM-costing framework represents a technical framework thatwould affect information flows and accountability for the utilization ofresources in an organization. Furthermore, it involves a new way of thinking.Not only to think about minimizing downtime but also to think of the costefficiency of achieving that. Hence, the following issues that need to beconsidered for a successful implementation:

. Top management support and commitment.

. A culture accepting cost efficiency as a major issue in managing a PMprogram 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 theproposed costing framework.

. The level of cost consciousness in the organization.

Concluding remarks and recommendation for future researchARASCO’s top management and maintenance management have decided toadopt the proposed PM costing framework. In fact, they think it would bebeneficial to them for evaluating the cost efficiency of both preventive andbreakdown maintenance. They indicated that it would provide very valuableinformation to monitor the cost efficiency of the maintenance operation. It willfacilitate the continuous improvement of maintenance and contributepositively to ARASCO’s total quality management (TQM) initiative.

For the future, case studies need to be developed for the proposed frameworkin both planned and breakdown maintenance.

References

Cokins, G. (1998), “Why is traditional accounting failing managers?”, Hospital MaterialManagement Quarterly, November, pp. 72-80.

Duffuaa, S., Raouf, A. and Campbell, J.D. (1998), Maintenance Planning and Control: Modelingand Analysis, John Wiley & Sons, New York, NY.

Duffuaa, S., Ben Daya, M., Al-Sultan, K. and Andijani, A. (2000), A Simulation Model forMaintenance 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. 32No. 1, February.

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448

Mirghani, M.A. (1996), “Aircraft maintenance budgetary and costing systems at the SaudiArabian Airlines: an integrated business approach”, Journal of Quality in MaintenanceEngineering, Vol. 2 No. 4, pp. 32-47.

Mirghani, M.A. (2001), “A framework for costing planned maintenance”, Journal of Quality inMaintenance 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 tertiaryinstitutions”, 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.


449

Note from the publisherAs managing editor of the Journal of Quality in Maintenance Engineering hereat Emerald, I would like explain the benefits available to you when you becomean author with Emerald.

In addition to achieving wide dissemination of your work by publishingwith Emerald, our author relations service – the Literati Club – providesservices and support for those authors who publish with an Emerald journal. Itis a tangible expression of commitment by a publisher to its authors andeditors, and the club offers support and resources for all Emerald contributorsworldwide.

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(1) A “thank-you” to outstanding authors and editors. An annual Awardsfor Excellence, which celebrates outstanding contributors among clubmembers in the following categories:. Best Paper Award for each participating journal;. Editor of the Year;. Leading Editor Awards; and. Research Award.

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(4) Complimentary personal subscription. You will personally receive acomplimentary subscription to any Emerald journal in your area ofinterest if your library takes out a full-price subscription.

(5) Calls for papers. All editors’ calls for papers in your areas of interest andprevious article keywords will be mailed or e-mailed to you personally.

(6) Future publications and new journal ideas. Editors give priorityconsideration to all articles you submit yourself, or on behalf ofcolleagues you wish to commend, and to new ideas for journal launches.

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For further information about the Literati Club, please see www.emeraldinsight.com/authors/index.htm For further information about how tosubmit material to JQME please see www.emeraldinsight.com/jqme.htm

JQME9,4

450

Journal of Quality in MaintenanceEngineeringVol. 9 No. 4, 2003pp. 450-451q MCB UP Limited1355-2511

More specifically to JQME, the usage statistics for 2003 to date have beenexcellent: there have been over 12,700 abstracts viewed in the period January toJune 2003 alone. Over 7,700 articles were downloaded as a result of this. Themost popular article downloaded during this time was “Strategic maintenancemanagement” by D.N.P. Murthy, A. Atrens and J.A. Eccleston, from issue 4 ofvolume 8.

We look forward to a successful year for JQME in 2004.

Rosie KnowlesManaging Editor

[email protected]

Note from thepublisher

451


Special Issue on

Costing and budgeting issues in maintenance

Journal of Quality in Maintenance Engineering (JQME) is aninternational refereed Journal published by Emerald, UK. JQMEpublishes articles in maintenance engineering and relatedfields. For more information on the editorial scope of JQME, thereviewing process, and article preparation requirements pleaseaccess its Web site at: www.emeraldinsight.com/journals/jqme/eabinfo.htm

A special issue of the Journal of Quality in Maintenance will bedevoted to costing and budgeting issues in maintenance. Theissue will cover recent advances, developments, andapplications of costing and budgeting techniques inmaintenance. The scope of the issue covers allocation andutilization of economic resources by maintenance operations asa critical business activity. Papers for this special issue aresolicited in the following areas:

. Cost accumulation and assignment in maintenance.

. Cost information for evaluating effectiveness and efficiencyof maintenance systems.

. Activity-based-costing (ABC) in maintenance.

. Activity-based-budgeting (ABB) in maintenance.

. Cost information for maintenance sourcing decisions.

. Role of maintenance costing and budgeting in continuousimprovement.

. 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 issueGuest Editors by October 31, 2003. Authors will be notified ofacceptance by March 1, 2004. Final papers for publication mustbe submitted by April 1, 2004. Submission of an electronicversion of the manuscript is required.

Guest editors

Dr Mohamed Ali Mirghani, KFUPM Box No. 791, Department ofACCT & 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 ofLouisville, Louisville, Kentucky, USA.Tel: 001 5028524813; Fax: 001 5028526072E-mail: [email protected]

Dr Mohamed A. El-Haram, Construction Management ResearchUnit, University of Dundee, Dundee, UK.E-mail: [email protected]

Call for papers

Index

453


Vol. 9 No. 4, 2003pp. 453-455

# MCB UP Limited1355-2511

Index to Journal of Quality inMaintenance Engineering,

Volume 9, 2003AuthorsABDLSAMAD, 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 torsionalvibration signals, No. 2, pp. 144-59.

AL-GHANIM, A., A statistical approach linking energy management to maintenance andproduction 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.EMBLEMSVAG, J. and TONNING, L., Decision support in selecting maintenance organization,

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.

JQME9,4

454

LI, W., SHI, T., LIAO, G. and YANG, S., Feature extraction and classification of gear faults usingprincipal 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 maintenanceperformance management, No. 4, pp 333-50.

MAKIS, V., see ZHAN, Y.

MARKESET, T. and KUMAR, U., Design and development of product support and maintenanceconcepts for industrial systems, No. 4, pp. 376-92.

MARKESET, T. and KUMAR, U., Integration of RAMS and risk analysis in product design anddevelopment 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 plannedmaintenance, No. 4, pp. 436-49.

MJEMA, E.A.M. and MWETA, M., An analysis of economics of investing in IT in themaintenance 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 consideringentropy, No. 1, pp. 83-91.

NISHIO, Y. and DOHI, T., Determination of the optimal software release time based onproportional hazards software reliability growth models, No. 1, pp. 48-65.

NOURELFATH, M., AIT-KADI, D. and SORO, W.I., Availability modeling and optimization ofreconfigurable manufacturing systems, No. 3, pp. 284-302.

PATANKAR, M.S. and TAYLOR, J.C., Posterior probabilities of causal factors leading tounairworthy 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.

TONNING, L., see EMBLEMSVAG, J.

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 rotatingmachinery 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 studyin a cement factory in Tanzania, MJEMA, E.A.M. and MWETA, M., No. 4, pp. 411-35.

Index

455

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 analysistechniques, AL-QAISIA, A., CATANIA, G. andMENEGHETTI, U., No. 2, pp. 176-201.

Cross-functional team working for overall equipment effectiveness (OEE), BAMBER, C.J.,CASTKA, P., SHARP, J.M. andMOTARA, Y., No. 3, pp. 223-238.

Decision support in selecting maintenance organization, EMBLEMSVAG, J. and TONNING, L.,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 softwarereliability 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 vibrationsignals, AL-BEDOOR, B.O., GHOUTTI, L., ADEWUSI, S.A., AL-NASSAR, Y. andABDLSAMAD, 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 casestudy, 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 onfractal 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. andAKERSTEN, 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.

maintenance management and modelling: the ifrim conference, may 2002, v¤xj¶ university, sweden

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