Table Of Contents:
Chapter 1 Introduction 1(26)

1.1 From Maintenance Management to Physical Asset Management 1(1)

1.2 The Challenges of Physical Asset Management 2(1)

1.2.1 Emerging Trends of Operation Strategies 2(1)

1.2.2 Toughening Societal Expectations 2(1)

1.2.3 Technological Changes 3(1)

1.3 Improving Physical Asset Management 3(3)

1.3.1 Maintenance Excellence 3(3)

1.3.1.1 Strategic 4(1)

1.3.1.2 Tactical 4(2)

1.3.1.3 Continuous Improvements 6(1)

1.3.2 Quantum Leaps 6(1)

1.4 Reliability through the Operator: Total Productive Maintenance 6(2)

1.5 Reliability by Design: Reliability-Centered Maintenance 8(4)

1.6 Optimizing Maintenance and Replacement Decisions 12(3)

1.7 The Quantitative Approach 15(9)

1.7.1 Setting Objectives 16(1)

1.7.2 Models 17(3)

1.7.3 Obtaining Solutions from Models 20(2)

1.7.4 Maintenance Control and Mathematical Models 22(2)

References 24(3)
Chapter 2 Component Replacement Decisions 27(72)

2.1 Introduction 27(3)

2.2 Optimal Replacement Times for Equipment Whose Operating Cost Increases with Use 30(8)

2.2.1 Statement of Problem 30(1)

2.2.2 Construction of Model 31(2)

2.2.3 Numerical Example 33(1)

2.2.4 Further Comments 34(2)

2.2.5 Applications 36(3)

2.2.5.1 Replacing the Air Filter in an Automobile 36(1)

2.2.5.2 Overhauling Boiler Plant 37(1)

2.3 Stochastic Preventive Replacement: Some Introductory Comments 38(1)

2.4 Optimal Preventive Replacement Interval of Items Subject to Breakdown (Also Known as the Group or Block Policy) 39(10)

2.4.1 Statement of Problem 39(1)

2.4.2 Construction of Model 40(2)

2.4.3 Determination of H(t) 42(5)

2.4.3.1 Renewal Theory Approach 42(2)

2.4.3.2 Discrete Approach 44(3)

2.4.4 Numerical Example 47(1)

2.4.5 Further Comments 48(1)

2.4.6 An Application: Optimal Replacement Interval for a Left-Hand Steering Clutch 48(1)

2.5 Optimal Preventive Replacement Age of an Item Subject to Breakdown 49(7)

2.5.1 Statement of Problem 49(1)

2.5.2 Construction of Model 49(4)

2.5.3 Numerical Example 53(1)

2.5.4 Further Comments 54(1)

2.5.5 An Application: Optimal Bearing Replacement Age 55(1)

2.6 Optimal Preventive Replacement Age of an Item Subject to Breakdown, Taking Account of the Times Required to Effect Failure and Preventive Replacements 56(3)

2.6.1 Statement of Problem 56(1)

2.6.2 Construction of Model 56(2)

2.6.3 Numerical Example 58(1)

2.7 Optimal Preventive Replacement Interval or Age of an Item Subject to Breakdown: Minimization of Downtime 59(5)

2.7.1 Statement of Problem 59(1)

2.7.2 Construction of Models 59(2)

2.7.2.1 Model 1: Determination of the Optimal Preventive Replacement Interval 59(1)

2.7.2.2 Model 2: Determination of Optimal Preventive Replacement Age 60(1)

2.7.3 Numerical Examples 61(2)

2.7.3.1 Model 1: Replacement Interval 61(1)

2.7.3.2 Model 2: Replacement Age 62(1)

2.7.4 Further Comments 63(1)

2.7.5 Applications 63(1)

2.7.5.1 Replacement of Sugar Refinery Cloths 63(1)

2.7.5.2 Replacement of Sugar Feeds in a Sugar Refinery 63(1)

2.8 Group Replacement: Optimal Interval between Group Replacements of Items Subject to Failure: The Lamp Replacement Problem 64(3)

2.8.1 Statement of Problem 64(1)

2.8.2 Construction of Model 65(1)

2.8.3 Numerical Example 66(1)

2.8.4 Further Comments 66(1)

2.8.5 An Application: Optimal Replacement Interval for a Group of 40 Valves in a Compressor 66(1)

2.9 Further Replacement Models 67(5)

2.9.1 Multistage Replacement 67(1)

2.9.2 Optional Policies 68(1)

2.9.3 Repairable Systems 69(3)

2.10 Spare Parts Provisioning: Preventive Replacement Spares 72(2)

2.10.1 Introduction 72(1)

2.10.2 Construction of Model 72(1)

2.10.2.1 The Constant-Interval Model 72(1)

2.10.2.2 The Age-Based Preventive Replacement Model 73(1)

2.10.3 Numerical Example 73(1)

2.10.3.1 Constant-Interval Policy 73(1)

2.10.3.2 Age-Based Policy 73(1)

2.10.4 Further Comments 74(1)

2.10.5 An Application: Cylinder Head Replacement Constant-Interval Policy 74(1)

2.11 Spare Parts Provisioning: Insurance Spares 74(7)

2.11.1 Introduction 74(1)

2.11.2 Classes of Components 75(4)

2.11.2.1 Nonrepairable Components 75(1)

2.11.2.2 Normal Distribution Approach 76(1)

2.11.2.3 Poisson Distribution Approach 76(1)

2.11.2.4 Repairable Components 77(2)

2.11.3 Cost Model 79(1)

2.11.4 Further Comments 79(1)

2.11.5 An Application: Electric Motors 80(1)

2.12 Solving the Constant-Interval and Age-Based Models Graphically: Use of Glasser's Graphs 81(4)

2.12.1 Introduction 81(2)

2.12.2 Using Glasser's Graphs 83(1)

2.12.3 Example 84(1)

2.12.4 Calculation of the Savings 84(1)

2.13 Solving the Constant-Interval and Age-Based Models Using the OREST Software 85(3)

2.13.1 Introduction 85(1)

2.13.2 Using OREST 86(2)

2.13.3 Further Comments 88(1)

References 88(1)

Problems 89(10)
Chapter 3 Inspection Decisions 99(36)

3.1 Introduction 99(1)

3.2 Optimal Inspection Frequency: Maximization of Profit 100(6)

3.2.1 Statement of Problem 100(1)

3.2.2 Construction of Model 101(3)

3.2.3 Numerical Example 104(1)

3.2.4 Further Comments 105(1)

3.3 Optimal Inspection Frequency: Minimization of Downtime 106(4)

3.3.1 Statement of Problem 106(1)

3.3.2 Construction of Model 106(1)

3.3.3 Numerical Example 107(1)

3.3.4 Further Comments 107(1)

3.3.5 An Application: Optimal Vehicle Fleet Inspection Schedule 108(2)

3.4 Optimal Inspection Interval to Maximize the Availability of Equipment Used in Emergency Conditions, Such as a Protective Device 110(5)

3.4.1 Statement of Problem 110(1)

3.4.2 Construction of Model 111(1)

3.4.3 Numerical Example 112(2)

3.4.4 Further Comments 114(1)

3.4.5 Exponential Failure Distribution and Negligible Time Required to Effect Inspection and Repair/Replacement 114(1)

3.4.6 An Application: Pressure Safety Valves in an Oil and Gas Field 115(1)

3.5 Optimizing Condition-Based Maintenance (CBM) Decisions 115(13)

3.5.1 Introduction 115(3)

3.5.2 The Proportional Hazards Model (PHM) 118(1)

3.5.3 Blending Hazard and Economics: Optimizing the CBM Decision 119(1)

3.5.4 Applications 120(2)

3.5.4.1 Food Processing: Use of Vibration Monitoring 121(1)

3.5.4.2 Coal Mining: Use of Oil Analysis 121(1)

3.5.4.3 Transportation: Use of Visual Inspection 122(1)

3.5.5 Further Comments 122(2)

3.5.6 Software for CBM Optimization 124(13)

3.5.6.1 Definition of an Event 125(3)

References 128(2)

Problems 130(5)
Chapter 4 Capital Equipment Replacement Decisions 135(46)

4.1 Introduction 135(2)

4.2 Optimal Replacement Interval for Capital Equipment: Minimization of Total Cost 137(8)

4.2.1 Statement of Problem 137(1)

4.2.2 Construction of Model 137(1)

4.2.3 Numerical Example 138(1)

4.2.4 Further Comments 139(2)

4.2.5 Applications 141(4)

4.2.5.1 Mobile Equipment: Vehicle Fleet Replacement 141(2)

4.2.5.2 Fixed Equipment: Internal Combustion Engine 143(2)

4.3 Optimal Replacement Interval for Capital Equipment: Maximization of Discounted Benefits 145(7)

4.3.1 Statement of Problem 145(1)

4.3.2 Construction of Model 145(4)

4.3.2.1 First Cycle of Operation 146(1)

4.3.2.2 Second Cycle of Operation 147(1)

4.3.2.3 Third Cycle of Operation 147(1)

4.3.2.4 nth Cycle of Operation 148(1)

4.3.3 Numerical Example 149(1)

4.3.4 Further Comments 150(1)

4.3.5 Proof that Optimization over a Long Period Is Not Equivalent to Optimization per Unit Time When Discounting Is Included 151(1)

4.4 Optimal Replacement Interval for Capital Equipment Whose Planned Utilization Pattern Is Variable: Minimization of Total Cost 152(6)

4.4.1 Statement of Problem 152(1)

4.4.2 Construction of Model 152(2)

4.4.2.1 Consider a Replacement Cycle of n Years 153(1)

4.4.3 Numerical Example 154(1)

4.4.4 Further Comments 155(3)

4.4.5 An Application: Establishing the Economic Life of a Fleet of Buses 158(1)

4.5 Optimal Replacement Policy for Capital Equipment Taking into Account Technological Improvement: Finite Planning Horizon 158(5)

4.5.1 Statement of Problem 158(1)

4.5.2 Construction of Model 159(1)

4.5.3 Numerical Example 160(2)

4.5.4 Further Comments 162(1)

4.5.5 An Application: Replacing Current Mining Equipment with a Technologically Improved Version 162(1)

4.6 Optimal Replacement Policy for Capital Equipment Taking into Account Technological Improvement: Infinite Planning Horizon 163(5)

4.6.1 Statement of Problem 163(1)

4.6.2 Construction of Model 163(1)

4.6.3 Numerical Example 164(2)

4.6.4 Further Comments 166(1)

4.6.5 An Application: Repair vs. Replace of a Front-End Loader 166(2)

4.7 Software for Economic Life Optimization 168(2)

4.7.1 Introduction 168(1)

4.7.2 Using PERDEC and AGE/CON 169(1)

4.7.3 Further Comments 170(1)

References 170(1)

Problems 171(10)
Chapter 5 Maintenance Resource Requirements 181(40)

5.1 Introduction 181(2)

5.1.1 The Facilities for Maintenance within an Organization 181(1)

5.1.2 The Combined Use of the Facilities within an Organization and Outside Resources 182(1)

5.2 Queuing Theory Preliminaries 183(3)

5.2.1 Queuing Systems 183(2)

5.2.2 Queuing Theory Results 185(1)

5.2.2.1 Single-Channel Queuing System 185(1)

5.2.2.2 Multichannel Queuing Systems 185(1)

5.3 Optimal Number of Workshop Machines to Meet a Fluctuating Workload 186(6)

5.3.1 Statement of Problem 186(1)

5.3.2 Construction of Model 187(1)

5.3.3 Numerical Example 187(3)

5.3.4 Further Comments 190(1)

5.3.5 Applications 191(1)

5.3.5.1 Optimizing the Backlog 191(1)

5.3.5.2 Crew Size Optimization 191(1)

5.4 Optimal Mix of Two Classes of Similar Equipment (such as Medium/Large Lathes) to Meet a Fluctuating Workload 192(15)

5.4.1 Statement of Problem 192(1)

5.4.2 Construction of Model 193(3)

5.4.2.1 Logic Flowchart 194(1)

5.4.2.2 Obtaining Necessary Information and Constructing Model 194(2)

5.4.3 Numerical Example 196(6)

5.4.4 Further Comments 202(2)

5.4.5 Applications 204(3)

5.4.5.1 Establishing the Optimal Number of Lathes in a Steel Mill 204(2)

5.4.5.2 Balancing Maintenance Cost and Reliability in a Thermal Generating Station 206(1)

5.5 Rightsizing a Fleet of Equipment: An Application 207(2)

5.5.1 An Application: Fleet Size in an Open-Pit Mine 208(1)

5.6 Optimal Size of a Maintenance Workforce to Meet a Fluctuating Workload, Taking Account of Subcontracting Opportunities 209(6)

5.6.1 Statement of Problem 209(1)

5.6.2 Construction of Model 210(3)

5.6.3 Numerical Example 213(1)

5.6.4 Further Comments 214(1)

5.6.5 An Example: Number of Vehicles to Have in a Fleet (such as a Courier Fleet) 214(1)

5.7 The Lease or Buy Decision 215(4)

5.7.1 Statement of Problem 215(1)

5.7.2 Solution of Problem 216(3)

5.7.2.1 Use of Retained Earnings 216(1)

5.7.2.2 Use of Borrowed Funds 217(1)

5.7.2.3 Leasing 218(1)

5.7.2.4 Conclusion 219(1)

5.7.3 Further Comments 219(1)

References 219(1)

Problems 220(1)
Appendix 1 Statistics Primer 221(14)

A1.1 Introduction 221(1)

A1.2 Relative Frequency Histogram 221(1)

A1.3 Probability Density Function 222(4)

A1.3.1 Hyperexponential 223(1)

A1.3.2 Exponential 224(1)

A1.3.3 Normal 225(1)

A1.3.4 Weibull 225(1)

A1.4 Cumulative Distribution Function 226(1)

A1.5 Reliability Function 226(4)

A1.6 Hazard Rate 230(3)

Reference 233(1)

Further Reading 233(1)

Problems 233(2)
Appendix 2 Weibull Analysis 235(44)

A2.1 Weibull Distribution 235(4)

A2.1.1 Shape Parameter 235(1)

A2.1.2 Scale Parameter 236(2)

A2.1.3 Location Parameter 238(1)

A2.1.4 Fitting a Distribution Model to Sample Data 238(1)

A2.2 Weibull Paper 239(1)

A2.3 Weibull Plot 239(9)

A2.3.1 Estimating Cumulative Percent Failure, F(t) 239(2)

A2.3.2 Estimating the Parameters 241(3)

A2.3.3 Nonlinear Plot 244(4)

A2.4 Confidence Interval of Weibull Plot 248(3)

A2.5 Bq Life 251(1)

A2.6 Kolmogorov鈥揝mirnov Goodness-of-Fit Test 251(4)

A2.7 Analyzing Failure Data with Suspensions 255(4)

A2.8 Analyzing Grouped Failure Data with Multiple Suspensions 259(2)

A2.9 Analyzing Competing Failure Data 261(2)

A2.10 Hazard Plot 263(3)

A2.10.1 Nonlinear Plot 264(2)

A2.11 Other Approaches to Weibull Analysis 266(1)

A2.12 Analyzing Trends of Failure Data 267(3)

A2.12.1 Machine H 268(1)

A2.12.2 Machine S 269(1)

References 270(1)

Further Reading 270(1)

Problems 271(8)
Appendix 3 Time Value of Money: Discounted Cash Flow Analysis 279(10)

A3.1 Introduction 279(2)

A3.2 Present Value Formulas 281(3)

A3.3 Determination of Appropriate Interest Rate 284(1)

A3.4 Inflation 285(1)

A3.5 The Equivalent Annual Cost 285(1)

A3.6 Example: Selecting an Alternative A One-Shot Decision 286(2)

A3.7 Further Comments 288(1)

References 288(1)
Appendix 4 List of Applications of Maintenance Decision Optimization Models 289(4)
Appendix 5 Ordinates of the Standard Normal Distribution 293(2)
Appendix 6 Areas in the Tail of the Standard Normal Distribution 295(4)
Appendix 7 Values of Gamma Function 299(2)
Appendix 8 Median Ranks Table 301(2)
Appendix 9 Five Percent Ranks Table 303(2)
Appendix 10 Ninety-Five Percent Ranks Table 305(2)
Appendix 11 Critical Values for the Kolmogorov鈥擲mirnov Statistic (dα) 307(2)
Appendix 12 Answers to Problems 309(6)
Index 315