Reliability modelling, 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,...

Full description

Saved in:
Bibliographic Details
Main Author: Blischke, W. R. 1934-
Other Authors: Murthy, D. N. Prabhakar
Format: Book
Language:English
Published: New York Wiley 2000
Series:Wiley series in probability and statistics. Applied probability and statistics section
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!
Table of Contents:
  • 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.