System reliability theory

System reliability theory

by Arnljot Høyland

Part of Wiley series in probability and mathematical statistics

1994

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About
Authored by two acknowledged leaders in the field of reliability analysis, the original version of this book has become both a classic text within mathematics and engineering departments in universities in Norway and Sweden, and a standard reference in companies throughout Scandinavia. Updated and expanded and available for the first time in English, System Reliability Theory offers a balanced presentation of both theory and practice, making it an ideal introduction to reliability analysis for both industrial statisticians and engineers. Comprehensive in scope, the methods and models the authors describe may be applied to the full range of technical systems - everything from offshore oil platforms and nuclear power plants, to manufacturing systems and public transportation systems - and are equally applicable to complete systems as well as specific subsystems such as fire and gas safety systems and emergency shutdown systems. The first half of the book begins with simple systems and constitutes a comprehensive elementary introduction to reliability theory. Chapters here are devoted to situations in which the stated variables of components and systems are binary and independent. Major topics covered are failure models, qualitative system analysis, component importance, and elementary life data analysis. Following chapters cover more complex situations in which the components and systems may be in a number of different states; renewal theory; dependent failures; life data analysis; accelerated life testing; and Bayesian reliability analysis. In addition to the many worked examples appearing throughout the text, each chapter concludes with a problems section which provides exercises and presents additional material on applications. An ideal reference for industrial statisticians and engineers working in the field of reliability and safety, System Reliability Theory is also a superior introductory text for graduate students in statistical mathematics and engineering.

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