Case studies in reliability and maintenance

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Title:

Series:

Wiley series in probability and statistics

Publication Information:

Hoboken, N.J. : Wiley-interscience, 2003

ISBN:

9780471413738

Subject Term:

Reliability (Engineering) -- Case studies

Maintainability (Engineering) -- Case studies

Added Author:

Blischke, Wallace R.

Murthy, D. N. Prabhakar

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Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
Searching... PSZ JB	30000010037283	TA169 C37 2003	Open Access Book	Book	Searching... Unknown
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Introducing a groundbreaking companion book to a bestselling reliability text
Reliability is one of the most important characteristics defining the quality of a product or system, both for the manufacturer and the purchaser. One achieves high reliability through careful monitoring of design, materials and other input, production, quality assurance efforts, ongoing maintenance, and a variety of related decisions and activities. All of these factors must be considered in determining the costs of production, purchase, and ownership of a product.
Case Studies in Reliability and Maintenance serves as a valuable addition to the current literature on the subject of reliability by bridging the gap between theory and application. Conceived during the preparation of the editors' earlier work, Reliability: Modeling, Prediction, and Optimization (Wiley, 2000), this new volume features twenty-six actual case studies written by top experts in their fields, each illustrating exactly how reliability models are applied.
A valuable companion book to Reliability: Modeling, Prediction, and Optimization, or any other textbook on the subject, the book features:
* Case studies from fields such as aerospace, automotive, mining, electronics, power plants, dikes, computer software, weapons, photocopiers, industrial furnaces, granite building cladding, chemistry, and aircraft engines
* A logical organization according to the life cycle of a product or system
* A unified format of discussion enhanced by tools, techniques, and models for drawing one's own conclusions
* Pertinent exercises for reinforcement of ideas
Of equal value to both students of reliability theory as well as professionals in industry, Case Studies in Reliability and Maintenance should be required reading for anyone seeking to understand how reliability and maintenance issues can be addressed and resolved in the real world.

Author Notes

WALLACE R. BLISCHKE, holds a PhD in Statistics and serves as Professor Emeritus at Marshall School of Business, University of Southern California.
D. N. PRABHAKAR MURTHY, PhD, is Professor of Engineering and Operations Management at the University of Queensland, St. Lucia, Australia. Together they have coauthored Reliability: Modeling, Prediction, and Optimization (Wiley); Warranty Cost Analysis; and Product Warranty Handbook.

Wallace R. Blischke and D. N. Prabhakar MurthyDonald H. Ebbeler, Jr. and Kim M. Aaron and George Fox and W. John WalkerChun Kin Chan and Michael TortorellaSeppo Virtanen and Per-Erik HagmarkMalcolm J. Faddy and Richard J. Wilson and Gerry M. WinterWilliam Q. Meeker and Luis A. Escobar and Stephen A. ZayacMichael Osterman and Abhijit Dasgupta and Thomas StadtermanLoon Ching Tang and Soon Huat OngMladen A. Vouk and Anthony T. RiversMin Xie and Guan Yue Hong and Claes WohlinNozer D. Singpurwalla and Yuling Cui and Chung Wai KongWilliam Q. Meeker and Luis A. EscobarSunita Chulani and Bert M. Steece and Barry BoehmLinda C. WolstenholmeRoger M. Cooke and Karen A. SlijkhuisNicholas A. J. HastingsU. Dinesh Kumar and John CrockerMichael Bulmer and John EcclestonRoger M. Cooke and Eric Jager and D. LewandowskiGilles C. ZwingelsteinXisheng Jia and Anthony H. ChristerElsayed A. ElsayedPeter G. A. Townson and D. N. Prabhakar Murthy and Hal GurgenciKarl D. Majeske and Mark D. Riches and Hari P. AnnadiKakuro Amasaka and Shunji OsakiPeter C. Sander and Luis M. Toscano and Steven Luitjens and Valia T. Petkova and Antoine Huijben and Aarnout C. BrombacherBermawi P. Iskandar and Wallace R. Blischke

Contributors	p. xvii
Preface	p. xxv
1. Introduction and Overview	p. 1
1.1. Introduction	p. 1
1.2. Reliability, Maintenance, Maintainability, and Quality	p. 3
1.3. History of Reliability and Maintainability	p. 9
1.4. Applications	p. 10
1.5. Life Cycle Concepts	p. 11
1.6. Tools and Techniques for the Study of Reliability	p. 14
1.7. Reliability and Maintenance Data and Analysis	p. 19
1.8. Issues in Reliability and Maintenance	p. 23
1.9. Case Studies: An Overview	p. 24
References	p. 32
Part A. Cases with Emphasis on Product Design	p. 35
2. Space Interferometer Reliability-Based Design Evaluation	p. 37
2.1. Introduction	p. 37
2.2. Problem Description	p. 38
2.3. Alternative Optical Interferometer Designs	p. 39
2.4. Evaluation of Alternative Designs	p. 53
2.5. Interpretations, Conclusions, and Extensions	p. 59
References	p. 60
Exercises	p. 60
Acronyms	p. 61
3. Confidence Intervals for Hardware Reliability Predictions	p. 63
3.1. Introduction	p. 63
3.2. Approach	p. 64
3.3. Problem Description	p. 64
3.4. Reliability Modeling	p. 66
3.5. Subassembly hardware Reliability Prediction	p. 71
3.6. Construction of Component Failure Rate Database	p. 75
3.7. Comparing Field Reliability Results with Predictions	p. 78
3.8. Implementation	p. 79
3.9. Conclusions	p. 79
References	p. 80
Exercises	p. 81
4. Allocation of Dependability Requirements in Power Plant Design	p. 85
4.1. Introduction	p. 85
4.2. System Characterization	p. 87
4.3. Modeling Dependability and Requirements	p. 87
4.4. Allocation of Requirements	p. 94
4.5. Continued Allocation in the Fault Tree	p. 101
4.6. Conclusions	p. 103
References	p. 105
Exercises	p. 106
Part B. Cases with Emphasis on Development and Testing	p. 109
5. The Determination of the Design Strength of Granite Used as External Cladding for Buildings	p. 111
5.1. Introduction	p. 111
5.2. Properties of Granite	p. 113
5.3. Reliability Criteria	p. 115
5.4. Current Practices	p. 117
5.5. Case Study	p. 122
5.6. Conclusions	p. 129
References	p. 130
Exercises	p. 131
Appendix A. Rosa Antico Data	p. 132
Appendix B. White Berrocal Data	p. 134
6. Use of Sensitivity Analysis to Assess the Effect of Model Uncertainty in Analyzing Accelerated Life Test Data	p. 135
6.1. Introduction	p. 135
6.2. Weibull Distribution and Initial Data Analysis	p. 138
6.3. Response Surface Model Analysis	p. 146
6.4. Effect of Stroke Displacement on Spring Life	p. 151
6.5. Concluding Remarks	p. 157
References	p. 158
Exercises	p. 158
Appendix A. SPLIDA Commands for the Analyses	p. 159
Appendix B. Spring-Accelerated Life Test Data	p. 161
7. Virtual Qualification of Electronic Hardware	p. 163
7.1. Introduction	p. 163
7.2. Automotive Module Case Study	p. 167
7.3. Summary	p. 184
References	p. 184
Exercises	p. 185
8. Development of a Moisture Soak Model for Surface-Mounted Devices	p. 187
8.1. Introduction	p. 187
8.2. Experimental Procedure and Results	p. 189
8.3. The Moisture Soak Model	p. 191
8.4. Discussion	p. 199
References	p. 201
Exercises	p. 202
9. Construction of Reliable Software in Resource-Constrained Environments	p. 205
9.1. Introduction	p. 205
9.2. Constrained Development	p. 207
9.3. Model and Metrics	p. 210
9.4. Case Studies	p. 216
9.5. Summary	p. 227
References	p. 227
Exercises	p. 230
10. Modeling and Analysis of Software System Reliability	p. 233
10.1. Introduction	p. 233
10.2. NHPP Software Reliability Growth Models	p. 235
10.3. Case Study	p. 238
10.4. Problems and Alternatives	p. 240
10.5. Case Study (Continued)	p. 244
10.6. Discussion	p. 247
References	p. 248
Exercises	p. 249
11. Information Fusion for Damage Prediction	p. 251
11.1. Introduction	p. 251
11.2. Approach Used	p. 252
11.3. Binary Random Variable and Test Data	p. 253
11.4. Physical Parameters and Expert Testimonies	p. 254
11.5. Information Fusion: A Bayesian Approach	p. 255
11.6. Data Analysis and Interpretation	p. 262
11.7. Conclusions	p. 263
References	p. 263
Exercises	p. 264
Appendix	p. 264
Part C. Cases with Emphasis on Defect Prediction and Failure Analysis	p. 267
12. Use of Truncated Regression Methods to Estimate the Shelf Life of a Product from Incomplete Historical Data	p. 269
12.1. Introduction	p. 269
12.2. Truncated Data Background	p. 273
12.3. Truncated Regression Model for the Truncated Product A Shelf-Life Data	p. 277
12.4. Comparison of Truncated and Censored Data Analysis	p. 283
12.5. Concluding Remarks and Extensions	p. 286
References	p. 288
Exercises	p. 288
Appendix. SPLIDA Commands for the Analyses	p. 290
13. Determining Software Quality Using COQUALMO	p. 293
13.1. Introduction	p. 293
13.2. Software Reliability Definitions	p. 294
13.3. Constructive Quality Model (COQUALMO)	p. 294
13.4. Case Study	p. 307
13.5. Conclusions	p. 309
References	p. 310
Exercises	p. 311
14. Use of Extreme Values in Reliability Assessment of Composite Materials	p. 313
14.1. Introduction	p. 313
14.2. Test Data and Background Knowledge	p. 314
14.3. Model Fitting and Prediction	p. 314
14.4. Strength Testing	p. 324
14.5. Discussion	p. 328
References	p. 329
Exercises	p. 329
15. Expert Judgment in the Uncertainty Analysis of Dike Ring Failure Frequency	p. 331
15.1. Introduction	p. 331
15.2. Uncertainty Analysis	p. 332
15.3. Expert Judgment Method	p. 333
15.4. The Dike Ring Expert Judgment Study	p. 337
15.5. Results	p. 339
15.6. Conclusions	p. 345
References	p. 347
Exercises	p. 348
Appendix. Example of Elicitation Question: Model Term Zwendl	p. 349
Part D. Cases with Emphasis on Maintenance and Maintainability	p. 351
16. Component Reliability, Replacement, and Cost Analysis with Incomplete Failure Data	p. 353
16.1. Introduction	p. 353
16.2. Maintenance Data	p. 354
16.3. Modeling Failures	p. 357
16.4. Component Replacement Policy Options	p. 361
16.5. Planned Replacement--Analysis and Costs	p. 364
16.6. Conclusion	p. 372
References	p. 373
Exercises	p. 374
Appendix. RELCODE Software	p. 375
17. Maintainability and Maintenance--A Case Study on Mission Critical Aircraft and Engine Components	p. 377
17.1. Introduction	p. 377
17.2. The Airline Company Profile	p. 381
17.3. Analysis of Unscheduled Maintenance	p. 383
17.4. Engine Reliability and Maintenance Policies	p. 387
17.5. Planned and Unplanned Maintenance in Engine	p. 391
17.6. Conclusions	p. 396
References	p. 397
Exercises	p. 398
18. Photocopier Reliability Modeling Using Evolutionary Algorithms	p. 399
18.1. Introduction	p. 399
18.2. System Characterization	p. 400
18.3. Preliminary Analysis	p. 401
18.4. Weibull Models	p. 405
18.5. Evolutionary (Genetic) Algorithm	p. 407
18.6. Model Fitting and Analysis	p. 408
18.7. Modeling Failures over Time	p. 415
18.8. Conclusions	p. 418
References	p. 419
Exercises	p. 419
Appendix	p. 421
19. Reliability Model for Underground Gas Pipelines	p. 423
19.1. Introduction	p. 423
19.2. Modeling Pipeline Failures	p. 425
19.3. Third-Party Interference	p. 428
19.4. Damage Due to Environment	p. 432
19.5. Failure Due to Corrosion	p. 433
19.6. Validation	p. 437
19.7. Results for Ranking	p. 439
19.8. Conclusions	p. 444
References	p. 444
Exercises	p. 445
20. RCM Approach to Maintaining a Nuclear Power Plant	p. 447
20.2. Introduction	p. 447
20.2. System Characterization and Modeling	p. 448
20.3. An Overview of RCM	p. 452
20.4. Field Data	p. 463
20.5. Maintenance of CVCS System	p. 466
20.6. Conclusions	p. 471
References	p. 473
Exercises	p. 474
Appendix	p. 476
21. Case Experience Comparing the RCM Approach to Plant Maintenance with a Modeling Approach	p. 477
21.1. Introduction	p. 477
21.2. Delay Time Concept	p. 479
21.3. Data Records and Analysis	p. 480
21.4. Factors Affecting Human Error Failures	p. 483
21.5. Modeling Assumptions	p. 484
21.6. Decision Model	p. 485
21.7. Estimating Parameters	p. 486
21.8. The Models	p. 487
21.9. The RCM Approach	p. 489
21.10. Discussion and Conclusions	p. 491
References	p. 493
Exercises	p. 494
Part E. Cases with Emphasis on Operations Optimization and Reengineering	p. 495
22. Mean Residual Life and Optimal Operating Conditions for Industrial Furnace Tubes	p. 497
22.1. Introduction	p. 497
22.2. Failure Mechanisms and Detection	p. 498
22.3. Residual Life Prediction: Deterministic Approaches	p. 499
22.4. Residual Life Prediction: Reliability Approach	p. 502
22.5. Optimum Operating Temperature	p. 509
22.6. Optimum Preventive Maintenance	p. 510
22.7. Summary	p. 511
References	p. 511
Exercises	p. 513
23. Optimization of Dragline Load	p. 517
23.1. Introduction	p. 517
23.2. Approach Used	p. 518
23.3. System Characterization	p. 519
23.4. Field Data	p. 521
23.5. Component Level: Modeling, Estimation, and Analysis	p. 523
23.6. System Level Modeling and Analysis	p. 529
23.7. Modeling the Effect of Dragline Load	p. 532
23.8. Optimal Dragline Load	p. 536
23.9. Conclusions and Recommendations	p. 538
References	p. 540
Exercises	p. 541
Appendix	p. 543
24. Ford's Reliability Improvement Process--A Case Study on Automotive Wheel Bearings	p. 545
24.1. Introduction	p. 545
24.2. Approach Used	p. 547
24.3. Quantitative Analysis Methods	p. 550
24.4. Data and Analysis	p. 558
24.5. Conclusions and Recommendations	p. 567
References	p. 568
Exercises	p. 569
25. Reliability of Oil Seal for Transaxle--A Science SQC Approach at Toyota	p. 571
25.1. Introduction	p. 571
25.2. Oil Seal	p. 572
25.3. Reliability Improvement at Toyota: A Cooperative Team Approach	p. 574
25.4. Reliability Improvement of Oil Seal	p. 576
25.5. Conclusion	p. 586
References	p. 586
Exercises	p. 587
Part F. Cases with Emphasis on Product Warranty	p. 589
26. Warranty Data Analysis for Assessing Product Reliability	p. 501
26.1. Introduction	p. 591
26.2. Reliability Metrics	p. 594
26.3. Field Feedback	p. 600
26.4. Analysis of Field Data	p. 604
26.5. Conclusions	p. 617
References	p. 620
Exercises	p. 621
27. Reliability and Warranty Analysis of a Motorcycle Based on Claims Data	p. 623
27.1. Introduction	p. 623
27.2. Product, Warranty and Data	p. 626
27.3. Methodology	p. 629
27.4. Preliminary Data Analysis	p. 638
27.5. Kalbfleisch-Lawless Analysis	p. 641
27.6. Gertsbakh-Kordonsky Analysis	p. 645
27.7. Warranty Analysis	p. 649
27.8. Conclusions	p. 651
References	p. 652
Exercises	p. 655
Index	p. 657

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