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Evolved from the lectures of a recognized pioneer in developing the theory of reliability, Mathematical Models for Systems Reliability provides a rigorous treatment of the required probability background for understanding reliability theory.
This classroom-tested text begins by discussing the Poisson process and its associated probability laws. It then uses a number of stochastic models to provide a framework for life length distributions and presents formal rules for computing the reliability of nonrepairable systems that possess commonly occurring structures. The next two chapters explore the stochastic behavior over time of one- and two-unit repairable systems. After covering general continuous-time Markov chains, pure birth and death processes, and transitions and rates diagrams, the authors consider first passage-time problems in the context of systems reliability. The final chapters show how certain techniques can be applied to a variety of reliability problems.
Illustrating the models and methods with a host of examples, this book offers a sound introduction to mathematical probabilistic models and lucidly explores how they are used in systems reliability problems.
- Sales Rank: #5782953 in Books
- Published on: 2008-05-09
- Original language: English
- Number of items: 1
- Dimensions: 9.50" h x .75" w x 6.20" l, 1.15 pounds
- Binding: Hardcover
- 272 pages
Review
… The material presented in the book is classic material, but is also timeless because the basic theory, probability and statistical rigor and applications to system reliability are still relevant today and important for any student or practitioner of reliability theory. … This book has a very good set of problems, exercises and comments on how to solve these problems for every chapter. These problems are excellent if one wants to use this book as a textbook. … The rigor and mathematical development in the book is excellent. This book is also a good reference book in the field of reliability theory for researchers … .
―Journal of Quality Technology, Vol. 41, No. 2, April 2009
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