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Reliability : modeling, prediction, and optimization /
Bringing together business and engineering to reliability analysis With manufactured products exploding in numbers and complexity, reliability studies play an increasingly critical role throughout a product's entire life cycle-from design to post-sale support. Reliability: Modeling, Prediction,...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York :
Wiley,
©2000.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Front Matter
- Context of Reliability Analysis. An Overview
- Illustrative Cases and Data Sets
- Basic Reliability Methodology. Collection and Preliminary Analysis of Failure Data
- Probability Distributions for Modeling Time to Failure
- Basic Statistical Methods for Data Analysis
- Reliability Modeling, Estimation, and Prediction. Modeling Failures at the Component Level
- Modeling and Analysis of Multicomponent Systems
- Advanced Statistical Methods for Data Analysis
- Software Reliability
- Design of Experiments and Analysis of Variance
- Model Selection and Validation
- Reliability Management, Improvement, and Optimization. Reliability Management
- Reliability Engineering
- Reliability Prediction and Assessment
- Reliability Improvement
- Maintenance of Unreliable Systems
- Warranties and Service Contracts
- Reliability Optimization
- Epilogue. Case Studies
- Resource Materials
- Appendix A: Probability
- Appendix B: Introduction to Stochastic Processes
- Appendix C: Statistical Tables
- Appendix D: Basic Results on Stochastic Optimization
- References
- Author Index
- Subject Index
- Wiley Series in Probability and Statistics.
- Part A Context of Reliability Analysis
- 2 Illustrative Cases and Data Sets 31
- Part B Basic Reliability Methodology
- 3 Collection and Preliminary Analysis of Failure Data 67
- 4 Probability Distributions for Modeling Time to Failure 93
- 5 Basic Statistical Methods for Data Analysis 135
- Part C Reliability Modeling, Estimation, and Prediction
- 6 Modeling Failures at the Component Level 169
- 7 Modeling and Analysis of Multicomponent Systems 201
- 8 Advanced Statistical Methods for Data Analysis 243
- 9 Software Reliability 287
- 10 Design of Experiments and Analysis of Variance 319
- 11 Model Selection and Validation 375
- Part D Reliability Management, Improvement, and Optimization
- 12 Reliability Management 427
- 13 Reliability Engineering 467
- 14 Reliability Prediction and Assessment 511
- 15 Reliability Improvement 537
- 16 Maintenance of Unreliable Systems 559
- 17 Warranties and Service Contracts 589
- 18 Reliability Optimization 619
- Appendix A. Probability 725
- A.1 Introduction to Probability Theory 725
- A.2 Moment-Generating and Characteristic Functions 727
- A.3 Two or More Random Variables 728
- A.4 Laplace Transforms 731
- A.5 Functions of Random Variables 732
- Appendix B. Introduction to Stochastic Processes 735
- B.2 Markov Chains 737
- B.3 Point Processes 737
- B.4 Markov Processes 746
- Table C1 Fractiles of the Standard Normal Distribution 749
- Table C2 Fractiles of the Student-t Distribution 750
- Table C3 Fractiles of the Chi-Square Distribution 752
- Table C4 Factors for Two-Sided Tolerance Intervals, Normal Distribution 752
- Table C5 Factors for One-Sided Tolerance Intervals, Normal Distribution 753
- Table C6 Factors for Two-Sided Nonparametric Tolerance Intervals 754
- Table C7 Factors for One-Sided Nonparametric Tolerance Intervals 755
- Table C8 Fractiles of the F Distribution 756
- Table C9 Upper Percentage Points of the Studentized Range 762
- Appendix D. Basic Results on Stochastic Optimization 763
- D.1 Unconstrained Static Optimization 763
- D.2 Constrained Static Optimization 764
- D.3 Multistage Dynamic Static Optimization 766
- D.4 Continuous Time Dynamic Optimization 767.