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＜電子ブック＞
Introduction to Reliability Analysis : Probability Models and Statistical Methods / by Shelemyahu Zacks
(Springer Texts in Statistics. ISSN:21974136)

版	1st ed. 1992.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	1992
本文言語	英語
大きさ	XIII, 212 p : online resource
著者標目	*Zacks, Shelemyahu author SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Probabilities LCSH:Computer science -- Mathematics  全ての件名で検索 LCSH:Mathematical statistics FREE:Statistical Theory and Methods FREE:Probability Theory FREE:Probability and Statistics in Computer Science
一般注記	1. System Effectiveness -- 1.1 Basic Concepts and Relationships -- 1.2 Time Categories -- 1.3 Reliability and Related Functions -- 1.4 Availability, Maintainability and Repairability -- 1.5 Exercises -- 2. Life Distributions, Models and Their Characteristics -- 2.1 Types of Failure Observations -- 2.2 General Characteristics of Life Distributions -- 2.3 Some Families of Life Distributions -- 2.4 Discrete Distributions of Failure Counts -- 2.5 Exercises -- 3. Reliability of Composite Systems -- 3.1 System Reliability for Series and Active Parallel Independent Components -- 3.2 k Out of n Systems of Independent Components -- 3.3 The Decomposition Method -- 3.4 Minimal Paths and Cuts -- 3.5 The MTTF of Composite Systems -- 3.6 Sequentially Operating Components -- 3.7 Fault Tree Analysis -- 3.8 Exercises -- 4. Reliability of Repairable Systems -- 4.1 The Renewal Process -- 4.2 The Renewal Function and Its Density -- 4.3 Asymptotic Approximations -- 4.4 Increasing the Availability by Preventive Maintenance and Standby Systems -- 4.5 Exercises -- 5. Graphical Analysis of Life Data -- 5.1 Probability Plotting for Parametric Models with Uncensored Data -- 5.2 Probability Plotting with Censored Data -- 5.3 Non-Parametric Plotting -- 5.4 Graphical Aids -- 5.5 Exercises -- 6. Estimation of Life Distributions and System Characteristics -- 6.1 Properties of Estimators -- 6.2 Maximum Likelihood Estimation -- 6.3 MLE of System Reliability -- 6.4 MLE from Censored Samples—Exponential Life Distributions -- 6.5 The Kaplan-Meier PL Estimator as an MLE of R(t): Non-Parametric Approach -- 6.6 Exercises -- 7. Maximum Likelihood Estimators and Confidence Intervals for Specific Life Distributions -- 7.1 Exponential Distributions -- 7.2 Shifted Exponential Distributions -- 7.3 Erlang Distributions -- 7.4 Gamma Distributions -- 7.5Weibull Distributions -- 7.6 Extreme Value Distributions -- 7.7 Normal and Lognormal Distributions -- 7.8 Truncated Normal Distributions -- 7.9 Exercises -- 8. Bayesian Reliability Estimation and Prediction -- 8.1 Prior and Posterior Distributions -- 8.2 Loss Functions and Bayes Estimators -- 8.3 Bayesian Credibility and Prediction Intervals -- 8.4 Credibility Intervals for the Asymptotic Availability of Repairable Systems: The Exponential Case -- 8.5 Empirical Bayes Method -- 8.6 Exercises -- 9. Reliability Demonstration: Testing and Acceptance Procedures -- 9.1 Reliability Demonstration -- 9.2 Binomial Testing -- 9.3 Exponential Distributions -- 9.4 Sequential Reliability Testing -- 9.5 Sequential Tests for Poisson Processes -- 9.6 Bayesian Reliability Demonstration Tests -- 9.7 Accelerated Life Testing -- 9.8 Exercises -- Annotated Bibliography -- Appendix of Statistical Tables Reliability analysis is concerned with the analysis of devices and systems whose individual components are prone to failure. This textbook presents an introduction to reliability analysis of repairable and non-repairable systems. It is based on courses given to both undergraduate and graduate students of engineering and statistics as well as in workshops for professional engineers and scientists. As aresult, the book concentrates on the methodology of the subject and on understanding theoretical results rather than on its theoretical development. An intrinsic aspect of reliability analysis is that the failure of components is best modelled using techniques drawn from probability and statistics. Professor Zacks covers all the basic concepts required from these subjects and covers the main modern reliability analysis techniques thoroughly. These include: the graphical analysis of life data, maximum likelihood estimation and bayesian likelihood estimation. Throughout the emphasis is on the practicalities of the subject with numerous examples drawn from industrial and engineering settings HTTP:URL=https://doi.org/10.1007/978-1-4612-2854-7

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