Stochastic Ageing And Dependence For Reliability
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Stochastic Ageing and Dependence for Reliability
Author: Chin Diew Lai
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-09-24
Ageing and dependence are two important characteristics in reliability and survival analysis, and they affect significantly the decision people make with regard to maintenance, repair/replacement, price setting, warranties, medical studies, and other areas. There are many papers published at different technical levels. This book aims at providing a state-of-the-art review of the subject so the interested readers may have a panoramic view of the theory and applications of the two areas. This book serves as reference book for professors and researchers involved in reliability and survival analysis. Students with basic probability and statistics knowledge interested in applications will also find the book useful. From the reviews: "This book is an important addition to several well-written books on reliability theory and concepts. The book fulfills the authors aim in providing a comprehensive treatment of both ageing and dependence concepts, with emphasis on reliability and survival analysis....Overall, I recommend this book to all serious-minded researchers, practitioners, teachers, and graduate students who would like to have the most up-to-date information available on the subject of stochastic ageing and dependencies in reliability. It also serves as reference book on reliability and survival analysis and is a good addition to one's statistical or reliability library." Suprasad V. Amari, International Journal of Performability Engineering, Vol. 3, No. 2, April 2007
Stochastic Modeling for Reliability
Author: Maxim Finkelstein
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-04-12
Focusing on shocks modeling, burn-in and heterogeneous populations, Stochastic Modeling for Reliability naturally combines these three topics in the unified stochastic framework and presents numerous practical examples that illustrate recent theoretical findings of the authors. The populations of manufactured items in industry are usually heterogeneous. However, the conventional reliability analysis is performed under the implicit assumption of homogeneity, which can result in distortion of the corresponding reliability indices and various misconceptions. Stochastic Modeling for Reliability fills this gap and presents the basics and further developments of reliability theory for heterogeneous populations. Specifically, the authors consider burn-in as a method of elimination of ‘weak’ items from heterogeneous populations. The real life objects are operating in a changing environment. One of the ways to model an impact of this environment is via the external shocks occurring in accordance with some stochastic point processes. The basic theory for Poisson shock processes is developed and also shocks as a method of burn-in and of the environmental stress screening for manufactured items are considered. Stochastic Modeling for Reliability introduces and explores the concept of burn-in in heterogeneous populations and its recent development, providing a sound reference for reliability engineers, applied mathematicians, product managers and manufacturers alike.
Reliability Assessments
Author: Franklin Richard Nash, Ph.D.
language: en
Publisher: CRC Press
Release Date: 2017-07-12
This book provides engineers and scientists with a single source introduction to the concepts, models, and case studies for making credible reliability assessments. It satisfies the need for thorough discussions of several fundamental subjects. Section I contains a comprehensive overview of assessing and assuring reliability that is followed by discussions of: • Concept of randomness and its relationship to chaos • Uses and limitations of the binomial and Poisson distributions • Relationship of the chi-square method and Poisson curves • Derivations and applications of the exponential, Weibull, and lognormal models • Examination of the human mortality bathtub curve as a template for components Section II introduces the case study modeling of failure data and is followed by analyses of: • 5 sets of ideal Weibull, lognormal, and normal failure data • 83 sets of actual (real) failure data The intent of the modeling was to find the best descriptions of the failures using statistical life models, principally the Weibull, lognormal, and normal models, for characterizing the failure probability distributions of the times-, cycles-, and miles-to-failure during laboratory or field testing. The statistical model providing the preferred characterization was determined empirically by choosing the two-parameter model that gave the best straight-line fit in the failure probability plots using a combination of visual inspection and three statistical goodness-of-fit (GoF) tests. This book offers practical insight in dealing with single item reliability and illustrates the use of reliability methods to solve industry problems.