Maintenance, Replacement, and Reliability: Theory and Applications

by Jardine; Andrew K.S.

• ISBN13: 9780849339660
• ISBN10: 0849339669
• Format: Hardcover
• Copyright: 2005-09-29
• Publisher: CRC Press

Summary

Based on the results of research in physical asset management, Maintenance, Replacement, and Reliability: Theory and Applications introduces students to the tools for making data-driven decisions and how to use them. The book offers a solid theoretical foundation for these tools, demonstrating applications through various case studies. Firmly rooted in reality, the applications covered relate to areas such as food processing, the military, mining, transportation, steel, and petrochemical and pharmaceutical industries. Ideal for classroom use, this text features supplementary software that can be downloaded from the CRC Web site. The downloadable educational versions of software packages include: OREST, SMS, EXAKT for CBM optimization, PERDEC, Workshop Simulator, Crew Size Optimizer, and WiebullSoft.This book can be used as a textbook for a one-semester senior undergraduate or postgraduate course on maintenance decision analysis. It provides problem sets with answers at the end of each chapter, an extensive set of PowerPoint slides covering the various chapters and appendices, a solutions manual for the problems in the book, and a bank of more than 100 examination questions. Instructors who adopt the book can obtain these resources at www.crcpress.com.The authors approach the topic with the ideology that mathematical modeling is not a spectator sport. Their examination of the underpinning theories for formulating models and exploration of real-world applications make the book both informative and practical. It provides professors with the tools they need to easily teach their students how to transform data into information.

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–Smirnov 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—Smirnov Statistic (dα)	307	(2)
Appendix 12 Answers to Problems	309	(6)
Index	315