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| موضوع: كتاب Handbook of Maintenance Management and Engineering الأربعاء 27 سبتمبر 2023, 1:53 am | |
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أخواني في الله أحضرت لكم كتاب Handbook of Maintenance Management and Engineering Mohamed Ben-Daya , Salih O. Duffuaa , Abdul Raouf , Jezdimir Knezevic , Daoud Ait-Kadi Editors
و المحتوى كما يلي :
Contents List of Contributors . Part I – Maintenance Organization 1 Maintenance Organization . 3 Ahmed E. Haroun and Salih O. Duffuaa 1.1 Introduction . 3 1.2 Maintenance Organization Objectives and Responsibility . 5 1.3 Determinants of a Maintenance Organization . 6 1.3.1 Maintenance Capacity Planning 6 1.3.2 Centralization vs Decentralization . 7 1.3.2 In-house vs Outsourcing 7 1.4 Design of the Maintenance Organization 8 1.4.1 Current Criteria for Organizational Change . 8 1.4.2 Criteria to Assess Organizational Effectiveness 9 1.5 Basic Types of Organizational Models . 9 1.6 Material and Spare Parts Management . 10 1.7 Establishment of Authority and Reporting . 13 1.8 Quality of Leadership and Supervision . 13 1.9 Incentives 13 1.10 Education and Training . 14 1.11 Management and Labor Relations 14 1.12 Summary . 15 References . 15 2 Maintenance Productivity and Performance Measurement 17 Aditya Parida and Uday Kumar 2.1 Introduction . 17 2.2 Performance Measurement and Maintenance Productivity . 19 2.3 Maintenance Performance 21 2.4 Measurement of Maintenance Productivity 23 .xxvxii Contents 2.4.1 Maintenance Performance Indicator (MPI) 24 2.4.2 MPM Issues . 24 2.4.3 MPM System . 27 2.5 MPI Standards and MPIs as in Use in Different Industries 31 2.5.1 Nuclear Industry . 32 2.5.2 Maintenance Indicators by EFNMS . 33 2.5.3 SMRP Metrics 34 2.5.4 Oil and Gas Industry 35 2.5.5 Railway Industry 36 2.5.6 Process Industry . 36 2.5.7 Utility Industry . 37 2.5.8 Auto-industry Related MPIs for the CEO 38 2.6 Concluding Remarks . 39 References . 39 Part II – Methods and Tools in Maintenance 3 Failure Statistics 45 Mohamed Ben-Daya 3.1 Introduction . 45 3.2 Introduction to Probability 45 3.2.1 Sample Spaces and Events . 45 3.2.2 Definition of Probability 46 3.2.3 Probability Rules 46 3.2.4 Conditional Probabilities 47 3.2.5 Random Variables 48 3.3 Probability Distributions . 49 3.4 Reliability and Failure Rate Functions 51 3.4.1 Introduction 51 3.4.2 Reliability Function . 52 3.4.3 Failure Rate Function . 52 3.4.4 Mean Time Between Failure (MTBF) . 53 3.5 Commonly Used Distributions 54 3.5.1 The Binomial Distribution . 54 3.5.2 The Poisson Distribution 55 3.5.3 The Normal Distribution 56 3.5.4 The Lognormal Distribution 58 3.5.5 The Exponential Distribution . 60 3.5.6 The Weibull Distribution . 61 3.6 Failure Statistics 63 3.6.1 Types of Data . 63 3.6.2 Parameter Estimation . 64 References . 73 4 Failure Mode and Effect Analysis 75 Mohamed Ben-Daya 4.1 Introduction . 75Contents xiii 4.2 FMEA Defined . 76 4.3 FMEA Process 78 4.4 FMEA Applications 83 4.5 Related Tools 83 4.5.1 Root Cause Analysis 83 4.5.2 Pareto Chart . 87 4.5.3 Cause and Effect Diagram . 87 References . 90 Part III – Maintenance Control Systems 5 Maintenance Control . 93 Salih O. Duffuaa and Ahmed E. Haroun 5.1 Introduction . 93 5.2 The Maintenance Control Function 95 5.3 The Control Process 96 5.4 Functional Structure of Maintenance Control . 97 5.5 Work Order System 99 5.5.1 Basic Documentation for Work Order System 99 5.5.2 Work Order System Flow 105 5.6 Tools Necessary for Effective Maintenance Control System . 107 5.6.1 Work Control . 108 5.6.2 Cost Control . 109 5.6.3 Quality Control 109 5.6.4 Plant Condition Control . 109 5.7 Effective Programs for Improving Maintenance Control 110 5.7.1 Emergency Maintenance 110 5.7.2 Reliability Improvement 110 5.7.3 Total Productive Maintenance . 111 5.7.4 Computerized Maintenance Management and Information Technology . 111 5.8 Summary . 112 References . 112 6 Guidelines for Budgeting and Costing Planned Maintenance Services 115 Mohamed Ali Mirghani 6.1 Introduction .115 6.2 An Overview of Budgeting and Costing Systems . 116 6.2.1 Budgeting Systems 116 6.2.2 Costing Systems 117 6.3 Proposed Budgetary System . 118 6.3.1 Planned Maintenance Operating Budget 118 6.3.2 Financial Budget 119 6.3.3 The Budget Cycle 120 6.3.4 Top Management Support 120 6.3.5 Budget Performance Reports . 122 6.4 Planned Maintenance Job Costing 123xiv Contents 6.4.1 Standard Cost Elements of a Planned Maintenance Job 123 6.4.2 Actual Cost Elements of a Planned Maintenance Job 128 6.4.3 Total Cost of a Planned Maintenance Job 129 6.4.4 Planned Maintenance Job Cost Variances . 129 6.4.5 Significant Cost Variances . 130 6.5 Summary and Conclusions . 131 References . 132 7 Simulation Based Approaches for Maintenance Strategies Optimization 133 Fouad Riane, Olivier Roux, Olivier Basile, and Pierre Dehombreux 7.1 Introduction .133 7.2 Reliability Models Estimation 134 7.2.1 Regression and ML Methods . 134 7.2.2 Uncertainty Affecting Reliability Model 136 7.3 Maintenance Performance 138 7.3.1 Availability Model . 138 7.3.2 Costs Model . 139 7.4 Simulation Based Maintenance Framework . 141 7.4.1 Toward a Unified Framework 141 7.4.2 Maintenance Strategies 142 7.4.3 Uncertainty Affecting Maintenance Performances 146 7.5 A Case Study 148 7.6 Conclusion 152 References . 152 Part IV – Maintenance Planning and Scheduling 8 Maintenance Forecasting and Capacity Planning 157 Hesham K. Alfares and Salih O. Duffuaa 8.1 Introduction .157 8.2 Forecasting Basics 158 8.3 Qualitative Forecasting Techniques 159 8.3.1 The Delphi Method 160 8.4 Quantitative Forecasting Techniques 161 8.4.1 Simple Moving Averages . 161 8.4.2 Weighted Moving Average 162 8.4.3 Regression Analysis . 163 8.4.4 Exponential Smoothing 165 8.4.5 Seasonal Forecasting 167 8.4.6 Box-Jenkins Time Series Models 171 8.5 Error Analysis . 172 8.6 Forecasting Maintenance Workload . 173 8.7 Maintenance Capacity Planning 175 8.8 Deterministic Approaches for Capacity Planning . 176 8.8.1 Modified Transportation Tableau Method . 176 8.8.2 Mathematical Programming Methods 179 8.9 Stochastic Techniques for Capacity Planning . 182Contents xv 8.9.1 Queuing Models . 182 8.9.2 Stochastic Simulation . 186 8.10 Summary . 188 References . 189 9 Integrated Spare Parts Management . 191 Claver Diallo, Daoud Aït-Kadi, and Anis Chelbi 9.1 Introduction .191 9.2 Spare Parts Identification and Classification 192 9.3 Determination of the Required Quantity of Spare Parts 193 9.3.1 Recommendations 193 9.3.2 Reliability and Availability Based Procedures . 193 9.3.3 Forecasting Procedure 198 9.3.4 Simulation 200 9.4 Inventory Control Policies 201 9.4.1 Model with Known and Constant Demand and Lead-time (EOQ Model) . 202 9.4.2 Model with Constant Demand and Perishable Items . 202 9.4.3 Model with Random Demand and Lead-time 203 9.5 Joint Maintenance and Provisioning Strategies 204 9.5.1 Joint Replacement and Ordering Policy for a Spare Unit (One Unit Provisioning). 205 9.5.2 Joint Replacement and Multiple Spare Parts Ordering Policy (Batch Provisioning) . 207 9.6 Inventory and Maintenance Policies for Reconditioned Spare Parts 209 9.6.1 Age of Recovered Parts to be Used for Replacement Actions . 209 9.6.2 Review of Inventory Control Policies with Random Returns 213 9.7 Collaborative Management of Spare Parts 213 9.7.1 Access to Documentation and Knowledge Bases 213 9.7.2 Lead-time Reduction 214 9.7.3 Virtually Centralized Spare Parts Stock (Inventory Pooling) 214 9.7.4 Joint Replenishment of Spare Parts 216 9.8 Conclusion 218 References . 218 10 Turnaround Maintenance . 223 Salih Duffuaa and Mohamed Ben-Daya 10.1 Introduction . 223 10.2 Turnaround Initiation 225 10.3 Work Scope . 226 10.4 Long Lead Time Resources 227 10.5 Contractors 228 10.6 TAM Planning 228 10.7 TAM Organization 229 10.8 Site Logistics . 230 10.9 TAM Budget . 230 10.10 Quality and Safety Plans . 231xvi Contents 10.10.1 Quality Plan . 231 10.10.2 Safety Plan . 231 10.11 TAM Communication Procedures 232 10.12 TAM Execution 233 10.13 TAM Closing and Final Report 233 10.14 Conclusion 234 References . 235 11 Maintenance Planning and Scheduling .237 Umar M. Al-Turki 11.1 Introduction . 237 11.2 Strategic Planning in Maintenance 240 11.3 Medium Range Planning .244 11.4 Short Range Planning . 247 11.5 Maintenance Scheduling . 247 11.5.1 Elements of Sound Scheduling 249 11.5.2 Maintenance Job Priority System . 249 11.6 Scheduling Techniques . 250 11.6.1 Gantt Charts and Scheduling Theory . 250 11.6.2 Project Scheduling .253 11.6.3 Critical Path Method 256 11.6.4 Program Evaluation Review Techniques (PERT) 258 11.7 Scheduling Using Computers 260 11.8 Summary . 260 References . 261 12 Models for Production and Maintenance Planning in Stochastic Manufacturing Systems . 263 E.K. Boukas 12.1 Introduction . 263 12.2 Problem Statement and Preliminary Results . 264 12.3 Dynamic Programming Approach 274 12.4 Linear Programming Approach 280 12.5 Conclusion 295 References . 296 Part V – Maintenance Strategies 13 Inspection Strategies for Randomly Failing Systems . 303 Anis Chelbi and Daoud Ait-Kadi 13.1 Introduction . 303 13.1.1 Notation .304 13.2 Basic Inspection Model . 305 13.2.1 Problem Definition .305 13.2.2 Working Assumptions and Mathematical Model . 306 13.3 Extensions of the Basic Model 308 13.3.1 Inspection Models for Single Component Systems . 308Contents xvii 13.4 Inspection Models for Multi-component Systems 318 13.4.1 Failure Tree Method Based Strategies . 318 13.4.2 Cases of Cold and Hot Stand-by Systems with Known and Partially Known Lifetime Distributions 319 13.4.3 Case of Systems with Components Failure Dependency . 320 13.5 Conditional Maintenance Models . 321 13.5.1 Conditional Maintenance Models for Single Component Systems 321 13.5.2 Conditional Maintenance Models for Multi-Component Systems . 329 13.6 Conclusion 331 References . 332 14 System Health Monitoring and Prognostics – A Review of Current Paradigms and Practices 337 Ranganath Kothamasu, Samuel H. Huang, William H. VerDuin 14.1 Maintenance Strategies: Motivations for Health Monitoring 337 14.2 Health Monitoring Paradigms . 340 14.3 Health Monitoring Tools and Techniques . 343 14.3.1 Reliability-based Maintenance . 343 14.3.2 Model-based Approach to FDI . 344 14.3.3 Signal-based FDI . 346 14.3.4 Statistical FDI/Maintenance . 347 14.4 Case Studies in System Monitoring and Control 347 14.5 Organizations and Standards . 352 14.6 Summary and Research Directions . 356 References . 357 15 Applied Maintenance Models . 363 K. Ito and T. Nakagawa 15.1 Introduction . 363 15.2 Missile Maintenance . 365 15.2.1 Expected Cost 366 15.2.2 Optimal Inspection Policies . 367 15.2.3 Numerical Illustrations . 370 15.3 Phased Array Radar Maintenance . 373 15.3.1 Cyclic Maintenance . 374 15.3.2 Delayed Maintenance 377 15.3.3 Numerical Illustrations . 379 15.4 Self-diagnosis for FADEC 380 15.4.1 Double Module System 381 15.4.2 Triple Module System 384 15.4.3 N Module System . 386 15.4.4 Numerical Illustrations . 386 15.5 Co-generation System Maintenance . 387 15.5.1 Model and Assumptions . 388 15.5.2 Analysis . 389 15.5.3 Optimal Policy 390 15.5.4 Numerical Illustration 391 References . 392xviii Contents 16 Reliability Centered Maintenance . 397 Atiq Waliullah Siddiqui and Mohamed Ben-Daya 16.1 Introduction . 397 16.2 RCM Philosophy . 400 16.2.1 RCM Principles and Key Features . 400 16.2.2 RCM Goals and Benefits . 401 16.2.3 System, System Boundary, Interfaces and Interactions 401 16.3 Failure and its Nature 404 16.4 RCM Methodology . 405 16.4.1 Selecting Systems Selection and Collecting Information 405 16.4.2 System Boundary Definition 407 16.4.3 System Description and Functional Block Diagram 407 16.4.4 System Functions and Functional Failure 410 16.4.5 Failure Mode and Effective Analysis (FEMA) 410 16.4.6 Logic or Decision Tree Analysis (LTA) 411 16.4.7 Task Selection 411 16.5 RCM Implementation . 411 16.5.1 Organizational Factors . 412 16.5.2 RCM Teams . 413 16.5.3 Scheduling Consideration and Training . 413 16.6 Conclusion 414 References . 414 17 Total Productive Maintenance . 417 17.1 Introduction to TPM . 417 17.2 Evolution Towards TPM . 420 17.3 Need of TPM 422 17.4 Basic Elements of TPM 424 17.5 Roadmap for TPM Implementation 429 17.6 An Ideal TPM Methodology . 435 17.6.1 Introduction Phase (Phase I) 435 17.6.2 TPM Initiatives Implementation Phase (Phase II) . 445 17.6.3 Standardization Phase (Phase III) 451 17.7 Barriers in TPM Implementation 453 17.8 Success Factors for Effective TPM Implementation . 456 17.9 Summary . 458 References . 458 18 Warranty and Maintenance . 461 D.N.P. Murthy and N. Jack 18.1 Introduction . 461 18.2 Maintenance Modelling 462 18.2.1 Reliability . 462 18.2.2 Types of Maintenance 462 I.P.S. Ahuja 18.2.3 Failure Modelling . 462Contents xix 18.3 Warranties . 465 18.3.1 Base Warranties . 465 18.3.2 Classification of Base Warranties. . 466 18.3.3 Warranty Servicing Cost Analysis . 466 18.3.4 Extended Warranties 467 18.4 Link Between Warranty and Maintenance 467 18.4.1 Taxonomy for Classification 467 18.4.2 Warranty Servicing Involving Only CM 468 18.4.3 Warranty Servicing Involving Both CM and PM 469 18.5 Maintenance Logistics for Warranty Servicing 470 18.5.1 Strategic Issues . 471 18.5.2 Tactical and Operational Issues . 472 18.6 Outsourcing of Maintenance for Warranty Servicing .474 18.6.1 Agency Theory . 474 18.7 Conclusions and Topics for Future Research 476 References . 476 19 Delay Time Modeling for Optimized Inspection Intervals of Production Plant . 479 Wenbin Wang 19.1 Introduction . 479 19.2 The DT Concept and Modeling Characteristics 480 19.3 The DT Models for Complex Plant . 483 19.3.1 The Down Time/Cost Model . 483 19.3.2 Modeling E[N f ((i −1)T, iT )] and E[N s (iT )] Under the Assumption of Perfect Inspections 484 19.3.3 Modeling E[N f ((i −1)T, iT )] and E[N s (iT )] Under the Assumption of Imperfect Inspections . 485 19.4 Delay Time Model Parameters Estimation . 487 19.4.1 Introduction 487 19.4.2 Complex System – Parameter Estimation 488 19.5 A Case Example 493 19.6 Other Developments in DT Modeling and Future Research Directions . 496 References . 497 20 Integrated E-maintenance and Intelligent Maintenance Systems . 499 Jayantha P. Liyanage, Jay Lee, Christos Emmanouilidis, and Jun Ni 20.1 Introduction . 499 20.2 Condition-based Maintenance Technology and the State of Development . 501 20.3 Integrated E-maintenance Solutions and Current Status . 503 20.4 Technical Framework for E-maintenance . 507 20.5 Watchdog Agent-based Intelligent Maintenance Systems 511 20.5.1 R2M-PHM Platform . 511 20.5.2 System Architecture . 512xx Contents 20.5.3 Toolbox for Multi-sensor Performance Assessment and Prognostics 514 20.5.4 Maintenance Decision Support System . 518 20.6 Technology Integration for Advanced E-maintenance . 520 20.6.1 Generic ICT Interface 520 20.6.2 Generic Interface Requirements for Watchdog Agents 525 20.6.3 Systems-user Interface Needs 528 20.7 Some Industrial Applications 528 20.7.1 E-maintenance Solutions for Complex Industrial Assets . 528 20.7.2 Watchdog Technology for Product Life-cycle Design and Management 532 20.7.3 Watchdog Technology to Trouble-shoot Bearing Degradation . 533 20.8 Challenges of E-maintenance Application Solutions 536 20.9 Conclusion 538 References . 539 Part VI – Maintainability and System Effectiveness 21 Maintainability and System Effectiveness . 547 J. Knezevic 21.1 Introduction . 547 21.2 The Concept of Maintainability 550 21.2.1 Maintainability Impact on System Effectiveness . 552 21.2.2 Maintainability Impact on Safety . 555 21.2.3 Undesirable Maintainability Practices . 558 21.2.4 Desirable Maintainability Practices . 559 21.3 Maintainability Analysis . 561 21.3.1 Measures of Maintaniablity . 565 21.3.2 Maintenance Labour-hour Factors . 568 21.3.3 Maintenance Frequency Factors 569 21.3.4 Maintenance Cost Factors 570 21.3.5 Related Maintenance Factors . 570 21.4 Empirical Data and Maintainability Measures 571 21.4.1 Possible Approaches to Analysis of Existing Data 571 21.4.2 Parametric Approach to Maintainability Data . 572 21.4.3 Distribution Approach to Maintainability Data . 572 21.4.4 Distribution Approach 575 21.5 Maintainability Engineering Predictions . 576 21.5.1 Introduction 577 21.5.2 Concept of the Maintainability Block Diagram . 577 21.5.3 Derivation of the Expression for the Maintainability Function 580 21.5.4 Maintainability Characteristics for Different Design Options . 585 21.6 Maintainability Engineering Management 592 21.6.1 Role of the Maintainability Engineering Management Function . 593 21.6.2 MEMF Opportunities . 594 21.6.3 MEMF Obstacles . 594 21.6.4 Design Methods for Attaining Maintainability 596Contents xxi 21.6.5 Maintainability Engineering Management – Lessons Learned 603 21.7 Concluding Remarks . 607 References . 610 Part VII – Maintenance Safety, Environment and Human Error 22 Safety and Maintenance 613 Liliane Pintelon and Peter N. Muchiri 22.1 Setting the Scene . 613 22.2 Definitions 615 22.2.1 Maintenance . 615 22.2.2 Safety . 616 22.2.3 Hazard 616 22.2.4 Stimuli 616 22.2.5 Accident . 616 22.3 The Maintenance Link to Safety . 617 22.3.1 The Role of Maintenance . 617 22.3.2 Safety During Maintenance . 620 22.3.3 Maintenance for Safety 622 22.3.4 Human Errors in Maintenance . 625 22.3.5 Accident Causation Theories vs Maintenance . 626 22.4 Maintenance Policies and Concepts vs Safety 629 22.4.1 Definitions . 630 22.4.2 Maintenance Actions 630 22.4.3 Maintenance Policies . 631 22.4.4 Maintenance Concepts . 633 22.5 Maintenance Safety and Accident Prevention 636 22.5.1 Methods of Accidents and Hazards Avoidance in Maintenance 637 22.5.2 Analytical Approach 637 22.5.3 The Engineering Approach 638 22.5.4 Safety Culture 641 22.5.5 Safety Legislations . 642 22.6 Safety Measurement . 643 References . 646 23 Maintenance Quality and Environmental Performance Improvement: An Integrated Approach 649 Abdul Raouf 23.1 Introduction . 649 23.2 Maintenance Quality . 650 23.2.1 Improving Maintenance Quality 650 23.2.2 Benchmarking and Quality 651 23.2.3 Maintenance Audit . 655 23.2.4 Improving Maintenance Quality Based on Stakeholder Feedback 656 23.3 Lean Manufacturing – Maintenance Quality Relationship . 656 23.3.1 Basic Environmental Measure . 656 23.4 Integrated Approach 660xxii Contents 23.5 Conclusion 663 References . 663 24 Industrial Asset Maintenance and Sustainability Performance: Economical, Environmental, and Societal Implications 665 Jayantha P. Liyanage, Fazleena Badurdeen, R.M. Chandima Ratnayake 24.1 Introduction . 665 24.2 Industrial Activities and Sustainability Trends . 666 24.3 Sustainability Performance in Perspective 668 24.4 Sustainability Performance Framework: From Business to Asset 671 24.5 Defining Maintenance Custodianship Within an Asset’s Sustainability Performance . 676 24.6 Generic Maintenance Impact Management Process . 683 24.7 Adapting an Effective Asset Maintenance Practice for Sustainability 686 24.8 Conclusion 689 References . 689 25 Human Reliability and Error in Maintenance 695 B.S. Dhillon 25.1 Introduction . 695 25.2 Terms and Definitions . 695 25.3 Human Reliability and Error in Maintenance-Related Facts, Figures, and Examples . 696 25.4 Occupational Stressors, Human Performance Effectiveness, and Human Performance Reliability Function 697 25.5 Human Error Occurrence Ways, Consequences, and Classifications, and Maintenance Error in System Life Cycle . 700 25.6 Reasons for the Occurrence of Human Error in Maintenance and Top Human Problems in Maintenance 701 25.7 Mathematical Models for Performing Maintenance Error Analysis in Engineering Systems 702 25.7.1 Model I . 703 25.7.2 Model II . 705 25.8 Useful Guidelines to Reduce the Occurrence of Human Error in Maintenance . 707 References . 709 26 Human Error in Maintenance – A Design Perspective 711 Clive Nicholas 26.1 Introduction . 711 26.2 Human Error in Aircraft Maintenance 712 26.3 Significance of Maintenance Error . 713 26.4 Design Impact 717 26.5 Analysis Required for Design Solutions 718 26.5.1 Maintenance Tasks . 721 26.5.2 Maintenance Errors 722 26.5.3 Causal Factors 724Contents xxiii 26.6 Design Strategies and Principles . 726 26.6.1 Appreciate the Maintainer’s Perspective of the Aircraft . 729 26.6.2 Design for the Aircraft Maintenance Environment . 729 26.6.3 Protect the Aircraft and Protect the Maintainer . 731 26.6.4 Avoid Complexity of Maintenance Tasks . 732 26.6.5 Enable Adequate Maintenance Access . 732 26.6.6 Positively Standardise and Positively Differentiate 733 26.6.7 Build Error Detection into the Maintenance Process . 734 26.7 Conclusion 734 References . 735 Index . 737 List of Contributors Punjabi University, India Daoud Aït-Kadi, Université Laval, Québec, Canada Hesham K. Alfares, King Fahd University of Petroleum & Minerals, Saudi Arabia Umar M. Al-Turki, King Fahd University of Petroleum & Minerals, Saudi Arabia Fazleena Badurdeen, University of Kentucky, USA Olivier Basile, Faculté Polytechnique de Mon, Belgium Mohamed Ben-Daya, King Fahd University of Petroleum & Minerals, Saudi Arabia El-Kebir Boukas, École Polytechnique de Montréal, Canada Anis Chelbi, École Supérieure des Sciences et Techniques de Tunis Pierre Dehombreux, Faculté Polytechnique de Mon, Belgium B.S. Dhillon, University of Ottawa, Canada I.P.S. Ahuja,xxvi List of Contributors Claver Diallo, Dalhousie University, Canada Salih O. Duffuaa, King Fahd University of Petroleum & Minerals, Saudi Arabia Christos Emmanouilidis, CETI/ATHENA Research and Innovation Centre, Greece Ahmed Haroun, King Fahd University of Petroleum & Minerals, Saudi Arabia Samuel H. Huang, University of Cincinnati, Cincinnati, USA Kodo Ito, Mitsubishi Heavy Industries, Ltd., Japan Nat Jack, University of Abertay Dundee, UK J. Knezevic, MIRCE Akademy, UK Ranganath Kothamasu, University of Cincinnati, Cincinnati, USA Uday Kumar, Luleå University of Technology, Sweden Jay Lee, University of Cincinnati, USA Jayantha P. Liyanage, University of Stavanger, Norway Mohamed Ali Mirghani, King Fahd University of Petroleum & Minerals, Saudi Arabia Peter Muchiri, Katholieke University Leuven, Belgium D.N.P. Murthy, The University of Queensland, Australia Toshio Nakagawa, Aichi Institute of Technology, JapanList of Contributors xxvii Jun Ni, University of Cincinnati, USA Clive Nicholas, Mirce Akademy, UK Aditya Parida, Luleå University of Technology, Sweden Liliane Pintelon, Katholieke University Leuven, Belgium Abdul Raouf, University of Management and Technology, Pakistan R.M. Chandima Ratnayake, University of Stavanger, Norway Fouad Riane, Faculté Polytechnique de Mon, Belgium Olivier Roux, Faculté Polytechnique de Mon, Belgium Atiq Waliullah Siddiqui, King Fahd University of Petroleum & Minerals, Saudi Arabia William H. VerDuin, Vertech LLC, Chagrin Falls, USA Wenbin, Wang, University of Salford, UK Index accident, 616 causation, 626 causes, 623 description, 624 examples, 622 industry examples, 624 prevention, 636 rate, 620 reasons, 621 severity, 620 activity-based costing, 128 Agency Theory, 474 analysis of error, 719, 723, 726 worksheet, 719 analysis of suspended data, 70 ARMA, 171 authority, 4, 10, 13, 14 autonomous maintenance, 445 autonomous work teams, 440 autoregressive, 171 availability, 192, 193, 196, 207, 304, 314, 315, 317, 321 availability model, 138 backlog, 108 base warranty, 465 Bayesian parameter estimation, 347 budget breakdown maintenance, 120 capital, 119 cash, 119 committee, 120 cycle, 120 definition, 116 performance, 117 planned maintenance, 120 template, 121 variances, 117 budgetary process, 118 budgeting, 107 capacity planning, 6 definition, 175 formulation, 177 mathematical programming, 180 process, 175 queueing models, 183 simulation, 187 techniques, 176 centralized maintenance, 7, 9 centralized stock, 215 change management, 20 CMMS, 108, 422, 442 co-generation system, 364, 387, 388, 392 combined maintenance task, 579 condition monitoring, 342, 500, 503, 506, 520, 524 condition-based maintenance, 500 control actions, 348, 351 adaptive, 342, 348, 351, 356 algorithms, 350 cost, 109 parameters, 350 process, 96, 339, 350, 356 signals, 351 statistical, 350 steps, 98 strategy, 350, 351 structure, 97738 Index tools, 107 control barriers, 84 corrective deferred major, 174 corrective deferred minor, 173 corrective emergency, 173 corrective maintenance, 363 cost variance, 129 CPM, 253, 256 Croston method, 199, 200 cumulative damage, 364, 388, 389, 392 cycle average method, 169 data censored, 63 complete, 63 decentralized maintenance, 7, 9 decentralized system, 214 decision support system, 506 Decision Support System, 518 degradation process, 312, 321, 324, 326, 328 Delphi method, 160 Deming’s 14 points, 650, 651, 652 detection, 77 detection evaluation criteria, 81 detection signal, 347 diagnosis and prognosis, 512 discounted Markov decision problem, 270 discounted Markov decision process, 270, 273 distribution binomial, 54 definition, 50 exponential, 60 lognormal, 58 normal, 56 Poisson, 55 Weibull, 61 duration of maintenance task, 566 dynamic programming principle, 276 e-maintenance application, 524, 536 e-maintenance solution, 503, 507, 508, 510, 528, 529, 530, 536, 537 engineering controls, 639 environmental performance, 656 equipment history, 409 ERP, 260 estimation method least squares, 67 maximum likelihood, 69 probability plotting, 64 European Agency for Safety and Health at Work, 643 exponential smoothing double, 166 simple, 165 extended warranty, 467 factor charting, 84 failure detection, 347 failure effect, 77 failure mode, 77 failure modes, 398, 400, 405 failure rate, 52 fault diagnosis, 356 techniques, 350 fault diagnosis and detection, 349 Fault Tree Analysis, 638 feedback, 99 FEMA, 410 FIMS, 107 FMEA, 638 forecasting model steps, 158 forecasting techniques, 158 free replacement warranty, 466 full authority digital electronic control, 363 full authority digital engine controller, 380, 381, 385 functional block diagram, 407 functional failure, 398, 405, 410 functionality, 548 functions, 6, 9, 15 Gantt chart, 250 hazard, 616 classes, 619 hazard prevention, 638 health monitoring, 537 history file, 103 Holt’s method, 166 human error, 712, 713, 718, 724, 726 consequence, 700 in maintenance, 625 influencing factors, 626 reasons, 701 reduction, 707 human errors categories, 625 classification, 700Index 739 human performance reliability, 699 imperfect repair, 468 incentives, 4, 13 indices maintenance, 96 production, 96 industrial hazard avoidance, 637 in-house maintenance, 4, 6, 7 inspection, 365, 366, 367, 370, 372, 482 alarm threshold, 323 basic model, 305 conditional, 322 degradation process, 324 example, 493 imperfect, 485 modeling, 483 multi-componenet system, 318 policies, 311 perfect, 484 intelligent maintenance system, 500, 506, 510, 511, 537 International Labour Organization, 643 inventory control, 199 control policies, 201 models, 202 parameters, 201 policies, 205 pooling, 214, 215 spare parts, 213 job card, 102 job cost sheet, 125 joint optimization of maintenance and inventory, 205 joint replenishment, 214 spare parts, 216 labor relations, 5, 14 LCC, 108 leadership, 4, 13 life cycle costing, 634 likelihood function, 487, 489, 491, 492, 494 logic tree analysis, 412 maintainability analysis, 561 concept, 549, 550 definition, 551 design issues, 596 design review, 587 desirable practices, 559 economic impact, 554 engineering, 572 engineering management function, 592, 593 engineering predictions, 577 function, 565, 567, 574, 582, 586 function derivation, 580 impact of system effectiveness, 552 impact on safety, 555 lessons learned, 603 measures, 568, 571, 581, 583 parametric approach, 572 statistics, 561, 572 undesirable practices, 558 maintainability block diagram, 577 maintainability data distribution approach, 572 maintenance error causes, 724 definition, 712 design, 717 detection, 719 examples, 713, 714, 715, 722, 734 mitigation, 727, 731 reasons, 712 safety impact, 713 maintenance error analysis, 702 maintenance models, 363 maintenance performance, 138, 146 maintenance philosophies, 340 maintenance prevention, 421, 449 maintenance strategy, 138, 142, 152, 243 maintenance system audit, 655 Markov decision problem, 279 Markovian jumps, 275 maximum likelihood method, 135 mean absolute deviation, 172 mean absolute percent error, 172 mean duration of maintenance task, 566, 575 mean squared error, 172 mean time between failure, 53 Mean Time Between Maintenance, 569 Mean Time Between Replacements, 569 median rank, 65 missile, 364, 365, 373 model based approaches, 344 moral hazard, 474 moving average, 162 model, 171740 Index simple, 162 weighted, 162 MPIs auto industry, 38, 39 categories, 29 definition, 24 development, 25 oil industry, 35 process industry, 37 selection, 26 specifying, 26 testing, 29 utility industry, 37 MPM implementation, 29, 31 issues, 25 multi-criteria, 31 oil industry, 35 process industry, 37 system, 27 MTBM. See Mean Time Between Maintenance MTBR. See Mean Time Between Replacements neural networks, 344, 347, 350, 353 occupational safety, 613, 620, 632, 642, 643 occupational stressors, 697 occurrence, 77 occurrence evaluation criteria, 79 OEE, 110, 426 OPTIMAIN, 134, 141, 150, 152 optimal control problem, 268 organization structure, 3, 6, 15 design, 4, 8, 15 hybrid, 7, 10 matrix, 10, 12 organizational change, 8 OSHA, 642 outsourcing, 4, 6, 7, 15, 242 parameter estimation, 64,345 parity space relations, 346 patterns, 159 percentage restoration time, 574 percentual duration of maintenance task, 566 performance indicators, 22, 33, 34, 36, 661 personal protective clothing and/or equipment, 640 PERT, 253, 258 phased array radar, 364, 373, 374, 377 planner qualifications, 247 planning and forecasting, 98 planning horizon, 237 planning procedure, 246 planning sheet, 248 PM task selection, 411 PPE. See personal protective clothing and/or equipment predictive maintenance, 400, 420 preventive maintenance, 363, 420 productive maintenance, 421 productivity measurement, 21, 22 measurement factors, 23, 24 prognostic approach, 502 prognostic systems, 348, 356 proportional hazards modeling, 347 quality policy, 231 RCM, 342, 421, 635 RCM process, 398, 400, 411 regression method, 134, 135 regression models, 163 reliability estimation, 134, 152 reliability function, 52 reliability model estimation, 138 repeat jobs, 109 replacement at pro-rata cost, 466 residual generation, 345 responsibility, 5, 6, 13 risk pooling, 215 root cause analysis, 638 run to failure, 400 safe maintenance practices, 639 safety culture, 641 safety legislation, 642 safety monitoring, 232 safety performance indicators, 645 safety performance measurement, 644 safety policy, 231 sales force composite, 160 scheduling definition, 237, 247 elements, 249 objectives, 239 procedure, 249Index 741 seasonal factors, 169 sequential maintenance task, 579 service delivery, 471 service level, 198, 200, 215 severity, 77 severity evaluation criteria, 80 signal-based FDI, 346 simulation model, 134, 143,144, 150,151 spare part inventories, 473 spare parts centralization, 215 characteristics, 191 classification, 193 forecasting, 198 identification, 192 joint ordering, 216 kit, 192 maintenance, 212 optimal quantity, 195, 202 quantity, 193 reconditioned, 210 replacement, 207 virtually centralized, 214 spare parts management, 4, 10 standby systems, 319 state trajectories, 276 stationarity, 159 stimuli, 616 strategic planning process, 243 supervision, 4, 5, 7, 13 sustainability business, 672 compliance, 671, 676, 687 drivers, 674 issues, 673 maintenance impact, 679 performance, 678 risk, 687 sustainability performance measurement, 670 sustainable asset maintenance, 667 system boundary, 407 system function, 398, 400, 401, 405, 407, 409, 410 system interfaces, 408 TAM phases, 225 time-frequency analysis, 347 TPM, 635, 650 benchmark indices, 451 definition, 418 implementation, 429 KPI, 451 lean practices, 452 methodology, 435 need, 423 obstacles, 453 safety, 449 success factors, 456 tools, 425 training, 4, 7, 10, 14 types of censored data, 64 types of FMEA, 79 vibration monitoring, 350 visual workplace, 442 WAN, 507, 510 warranty and maintenance, 467 warranty logistics, 472 warranty servicing model, 468 watchdog agent, 510, 512, 514, 518, 525, 532, 536 wear, 323 web-based solutions, 505 wide-area networks, 505 work measurement, 107 work order flow, 105 form, 100 information, 101 planning, 98 system, 99 work package, 227 working relations chain of command, 4 delegation of authority,
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