Statistical Methods for the Reliability of Repairable Systems (Hardcover)

~ (Author), Asit P. Basu (Author) "A repairable system is a system that, when a failure occurs, can be restored to an operating condition by some repair process other than replacement..." (more)
Key Phrases: failure truncated case, time truncated case, time dot plot, Failure Number, Gamma Prior Lognormal Prior, Repeat Problem (more...)

Editorial Reviews

Review

"...a thorough and systematic presentation..." -- La Doc Sti, September 2000

"Intended for engineers, quality managers and statisticians, this book could also be used for a graduate level course in reliability." -- Short Book Reviews, Vol. 21, No. 2, August 2001

"This new book does a fantastic job of giving detailed coverage and practical illustration to repairable systems reliability..." -- Technometrics, Vol. 42, No. 4, May 2001

"This new book does a fantastic job of giving detailed coverage and practical illustration to repairable systems reliability..." (Technometrics, Vol. 42, No. 4, May 2001)

"Intended for engineers, quality managers and statisticians, this book could also be used for a graduate level course in reliability." (Short Book Reviews, Vol. 21, No. 2, August 2001)

"...a thorough and systematic presentation..." (La Doc Sti, September 2000)

"...a comprehensive presentation of materials associated with reliability of repairable systems..." (Journal of Quality Technology, Vol. 33, No. 4, October 2001)

"Most of the literature in reliability deals with modelling and estimation in non-repairable systems; however this book considers repairable systems only." (Zentralblatt MATH, Vol. 963, 2001/13)

"...will be found useful by academicians as well as by practitioners." (Mathematical Reviews, 2002b)

"...an excellent resource and textbook a book that will contribute to filling an existing need in the reliability area and will further motivate researchers to look into developing statistical methods appropriate for data from repairable systems..." (Journal of the American Statistical Association, Vol. 97, No. 458, June 2002)

Product Description

A unique, practical guide for industry professionals who need to improve product quality and reliability in repairable systems

Owing to its vital role in product quality, reliability has been intensely studied in recent decades. Most of this research, however, addresses systems that are nonrepairable and therefore discarded upon failure. Statistical Methods for the Reliability of Repairable Systems fills the gap in the field, focusing exclusively on an important yet long-neglected area of reliability. Written by two highly recognized members of the reliability and statistics community, this new work offers a unique, systematic treatment of probabilistic models used for repairable systems as well as the statistical methods for analyzing data generated from them.

Liberally supplemented with examples as well as exercises boasting real data, the book clearly explains the difference between repairable and nonrepairable systems and helps readers develop an understanding of stochastic point processes. Data analysis methods are discussed for both single and multiple systems and include graphical methods, point estimation, interval estimation, hypothesis tests, goodness-of-fit tests, and reliability prediction. Complete with extensive graphs, tables, and references, Statistical Methods for the Reliability of Repairable Systems is an excellent working resource for industry professionals involved in producing reliable systems and a handy reference for practitioners and researchers in the field.

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Product Details

• Hardcover: 224 pages
• Publisher: Wiley-Interscience; 1 edition (April 14, 2000)
• Language: English
• ISBN-10: 0471349410
• ISBN-13: 978-0471349419
• Product Dimensions: 9.4 x 6.1 x 0.9 inches
• Shipping Weight: 1.2 pounds (View shipping rates and policies)
• Average Customer Review: 4.5 out of 5 stars  See all reviews (2 customer reviews)
• Amazon.com Sales Rank: #1,813,355 in Books (See Bestsellers in Books)

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Customer Reviews

Most Helpful Customer Reviews

37 of 37 people found the following review helpful:

4.0 out of 5 stars not many books cover this topic, April 20, 2008

By	Michael R. Chernick "statman31147" (Holland PA) - See all my reviews (REAL NAME)

Most reliability curves or their survival curve counterparts analyze time to failure without considering that there may be a difference in distribution for a part that was repaired compared to one that is a perfectly new replacement or they assume that the part being analyzed is not repairable. But we know with automobiles and other complex systems there are parts that are usually replaced and other parts that are usually repaired. Sometimes you have a choice and usually it is economic considerations that dictate the decision. In practice repairable systems are common, airplanes, cars, trains, and televisions to name a few. Of course very simple items are designed not to be repairable with the light bulb being an obvious example. So there should be much more written about them. In both the reliability and survival literature the theory for repairable systems is maturing. The theory of recurrent events that is presented in fine books such as the one by Wayne Nelson and the even more recent text by Cook and Lawless. These methods are sometimes applicable to repairable systems. In his book Nelson refers to Harry Ascher's text as the only one available on the topic of repairable systems.

This text is a welcome current addition to the statistical methods and models used to address practical problems about systems that have repairable parts.

5 of 5 people found the following review helpful:

5.0 out of 5 stars Excellent reference book, February 13, 2004

By	"sameervittal" (Greenville, SC USA) - See all my reviews

This is a great reference book on repairable systems reliability. Too many reliability engineers, and especially their management, blindly rely on "Weibulls" for decision making. Often the subtle (and critical) difference between a non-repairable component models (like the usual Weibull & Lognormal models) and a repairable-system models are overlooked. This book clearly explains the differences between repairable & non-repairable systems, minimal-repair and renewal models, etc. It has a nice balance between theory and examples, and one of the best explanations of poisson process theory I have seen.

I have applied the methods described in this book to several industry data sets (from my own experience dealing with gas & steam turbine power plants, wind turbine farms, control systems, etc) and they work very well. And the theory finally helped clarify a lot of questions I had while using commercial reliability growth programs and standards.

The proofs can be a bit intimidatng for the novice, but its worth chugging through the math as some of the most useful (and practical) results are found in the lemmas. I would rate this as a classic for repairable systems reliability, just as Nelson's "applied life data analysis" is the classic for non-repairable systems. Both books should be on the bookshelf of any industrial or reliability engineer.