Terje Aven & Uwe Jensen 
Stochastic Models in Reliability [PDF ebook] 

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This book  provides a comprehensive up-to-date presentation of some of the classical areas of reliability, based on a more advanced probabilistic framework using the modern theory of stochastic processes. This framework allows analysts to formulate general failure models, establish formulae for computing various performance measures, as well as determine how to identify optimal replacement policies in complex situations.

 

In this second edition of the book, two major topics have been added to the original version:  copula models which are used to study the effect of structural dependencies on the system reliability; and maintenance optimization which highlights delay time models under  safety constraints.

 

 

Terje Aven is Professor of Reliability and Risk Analysis  at University of Stavanger, Norway. Uwe Jensen is working as a Professor at the Institute of Applied Mathematics and Statistics of the University of Hohenheim in Stuttgart, Germany.

 

Review of first edition:

 

‘This is an excellent book on mathematical, statistical and stochastic models in reliability. The authors have done an excellent job of unifying some of the stochastic models in reliability. The book is a good reference book but may not be suitable as a textbook for students in professional fields such as engineering. This book may be used for graduate level seminar courses for students who have had at least the first course in stochastic processes and some knowledge of reliability mathematics. It should be a good reference book for researchers in reliability mathematics.’

 

–Mathematical Reviews (2000)

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Table of Content

Introduction.- Basic Reliability Theory.- Stochastic Failure Models.- Availability Analysis of Complex Systems.- Maintenance Optimization.

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Language English ● Format PDF ● Pages 297 ● ISBN 9781461478942 ● File size 3.0 MB ● Publisher Springer New York ● City NY ● Country US ● Published 2013 ● Edition 2 ● Downloadable 24 months ● Currency EUR ● ID 2772425 ● Copy protection Social DRM

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