Accelerated Testing: Statistical Models, Test Plans, and Data Analysis (Wiley Series in Probability and Statistics)

Accelerated Testing: Statistical Models, Test Plans, and Data Analysis (Wiley Series in Probability and Statistics)

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Manufacturer: Wiley-Interscience
Author: Wayne B. Nelson
Binding: Paperback
Publication Date: 2004-09-21
Publisher: Wiley-Interscience
Label: Wiley-Interscience
Number Of Pages: 624
Features:

Editorial Review:
This practical resource presents modern, statistical methods for accelerated testing including test models, analyses of data, and plans for testing. Each topic is self-contained for easy reference. Coverage is broad and detailed enough to serve as a text or reference. This handy book features real test examples along with data analyses, computer programs, and references to the literature.
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Customer Reviews
Average Customer Rating:

best book in accelerated testing

2008-02-09
Nelson is a private consultant who has worked on countless practical problems in reliability from his consulting practice and previous employment at General Electric. He is an excellent lecturer and writer. His earlier book "Applied Life Data Analysis" was considered to be one of the best texts on reliability.
This book is very thorough in its treatment of all aspects of accelerated testing and is filled with many good references. Nelson carefully defines the mathematical models which consist of two components, (1) an acceleration function which describes how the mean lifetime changes as a function of the acceleration factor and (2) a probability distribution that explains the random variability of outcomes at each acceleration factor. A particular mean function could be the Arrhenius relationship and the probability distribution could be exponential. Hence there is not a single Arrhenius acceleration model but rather an Arrhenius-exponential, an Arrhenius-lognormal or an Arrhenius-Weibull model. The book is filled with interesting theory and examples. Nelson provides excellent practical guidance based on his wealth of experience.

Should be on every Developer and Engineer's shelf.

2006-11-01
Dr. Taylor does his usual great job covering a difficult subject - ties in well with his "Applied Life Data Analysis", the revered reliability resource. Because of his GE background, he emphasizes experimental plans and analysis methods (i.e.: partially censored) which permit you to make good predictions regarding a product or system while you are still collecting data (e.g.: management wants an answer NOW, even if the experiment is not completed). A few more examples of how "typical" systems behave would be helpful, but otherwise a great resource.

Great companion volume to Applied Life Data Analysis

2004-01-30
I agree with the previous reviewer that this is the definitive classic in accelerated life testing. It's a great companion volume to Dr. Nelson's "Applied Life Data Analysis" which remains one of the best reliability textbooks ever written. I have noticed that all major reliability and accelerated testing programs use this book as their main reference - proof of the books usefulness. My only compaint is with the publishers for the steep price - now that they're bringing out a lower cost version of Applied Life Data Analysis, I hope they'll bring out a low-cost or paperback version of this classic as well.

best statistical account of accelerated testing

2000-06-21
Nelson is a private consultant who has worked on countless practical problems in reliability from his consulting practice and previous employment at General Electric. He is an excellent lecturer and writer. His earlier book "Applied Life Data Analysis" was considered to be one of the best texts on reliability.

This book is very thorough in its treatment of all aspects of accelerated testing and is filled with many good references. Nelson carefully defines the mathematical models which consist of two components, (1) an acceleration function which describes how the mean lifetime changes as a function of the acceleration factor and (2) a probability distribution that explains the random variability of outcomes at each acceleration factor. A particular mean function could be the Arrhenius relationship and the probability distribution could be exponential. Hence there is not a single Arrhenius acceleration model but rather an Arrhenius-exponential, an Arrhenius-lognormal or an Arrhenius-Weibull model. The book is filled with interesting theory and examples. Nelson provides excellent practical guidance based on his wealth of experience.

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