Enhanced descriptions from Syndetics:

Engineering reliability concerns failure data analysis, the economics of maintenance policies, and system reliability. This textbook develops the use of probability and statistics in engineering reliability and maintenance problems. The author uses probability models in the analysis of failure data, decision relative to planned maintenance, and prediction relative to preliminary design.

Some of the outstanding features include: The analysis of failure data for both continuous and discrete probability from a finite population perspective. Probability models derived from engineering considerations. An introduction to influence diagrams and decision making. Use of the operational bayesian approach.
The approach is fresh and interesting; it is motivated from problems in engineering and physical sciences and uses examples to illustrate the methodology. These examples, along with the use of real failure time data, will help the reader apply the techniques to real industrial situations.

This upper undergraduate or first-year graduate level book is largely self-contained relative to the background material required. Each chapter contains exercises, notes, references, and notation. Spreadsheets are used extensively in the exercises, and are also useful for the graphical analysis of failure data contained in the book.

A complimentary instructor's manual is available upon adoption.

Table of contents provided by Syndetics

• Preface; Acknowledgements; Introdcution
• Part I Failure Data Analysis
• Chapter 1 The Finite Population Exponential Model
• Chapter 2 Lifetime Data Analysis
• Chapter 3 Counting the Number of Failures
• Chapter 4 Strength of Materials
• Part II The Economics of Maintenance Decisions
• Chapter 5 The Economics of Maintenance and Inspection
• Part III System Reliability
• Chapter 6 Network Reliability
• Chapter 7 System Failure Analysis: Fault Trees
• Chapter 8 System Availability and Maintainability
• Chapter 9 Influence Diagrams
• Chapter 10 Making Decisions Using Influence Diagrams
• Appendix A Classical Statistics Is Logically Untenable
• Appendix B Bayesian Decision Analysis Is Self-Consistent
• References
• Index