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 |  موضوع: كتاب Handbook of Maintenance Management and Engineering الأربعاء 27 سبتمبر 2023, 1:53 am | |
| 
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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