Bayesian Methods In Reliability

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Bayesian Methods in Reliability

P. Sander,R. Badoux
Bayesian Methods in Reliability Book PDF

Author : P. Sander,R. Badoux
Publisher : Springer Science & Business Media
Page : 227 pages
File Size : 54,8 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9789401134828

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Bayesian Methods in Reliability by P. Sander,R. Badoux Pdf

When data is collected on failure or survival a list of times is obtained. Some of the times are failure times and others are the times at which the subject left the experiment. These times both give information about the performance of the system. The two types will be referred to as failure and censoring times (cf. Smith section 5). * A censoring time, t, gives less information than a failure time, for it is * known only that the item survived past t and not when it failed. The data is tn and of censoring thus collected as a list of failure times t , . . . , l * * * times t , t , . . . , t • 1 z m 2. 2. Classical methods The failure times are assumed to follow a parametric distribution F(t;B) with and reliability R(t;B). There are several methods of estimating density f(t;B) the parameter B based only on the data in the sample without any prior assumptions about B. The availability of powerful computers and software packages has made the method of maximum likelihood the most popular. Descriptions of most methods can be found in the book by Mann, Schafer and Singpurwalla (1974). In general the method of maximum likelihood is the most useful of the classical approaches. The likelihood approach is based on constructing the joint probability distrilmtion or density for a sample.

Bayesian Reliability

Michael S. Hamada,Alyson Wilson,C. Shane Reese,Harry Martz
Bayesian Reliability Book PDF

Author : Michael S. Hamada,Alyson Wilson,C. Shane Reese,Harry Martz
Publisher : Springer Science & Business Media
Page : 445 pages
File Size : 49,9 Mb
Release : 2008-08-15
Category : Mathematics
ISBN : 9780387779508

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Bayesian Reliability by Michael S. Hamada,Alyson Wilson,C. Shane Reese,Harry Martz Pdf

Bayesian Reliability presents modern methods and techniques for analyzing reliability data from a Bayesian perspective. The adoption and application of Bayesian methods in virtually all branches of science and engineering have significantly increased over the past few decades. This increase is largely due to advances in simulation-based computational tools for implementing Bayesian methods. The authors extensively use such tools throughout this book, focusing on assessing the reliability of components and systems with particular attention to hierarchical models and models incorporating explanatory variables. Such models include failure time regression models, accelerated testing models, and degradation models. The authors pay special attention to Bayesian goodness-of-fit testing, model validation, reliability test design, and assurance test planning. Throughout the book, the authors use Markov chain Monte Carlo (MCMC) algorithms for implementing Bayesian analyses -- algorithms that make the Bayesian approach to reliability computationally feasible and conceptually straightforward. This book is primarily a reference collection of modern Bayesian methods in reliability for use by reliability practitioners. There are more than 70 illustrative examples, most of which utilize real-world data. This book can also be used as a textbook for a course in reliability and contains more than 160 exercises. Noteworthy highlights of the book include Bayesian approaches for the following: Goodness-of-fit and model selection methods Hierarchical models for reliability estimation Fault tree analysis methodology that supports data acquisition at all levels in the tree Bayesian networks in reliability analysis Analysis of failure count and failure time data collected from repairable systems, and the assessment of various related performance criteria Analysis of nondestructive and destructive degradation data Optimal design of reliability experiments Hierarchical reliability assurance testing

System Reliability Theory

Marvin Rausand,Arnljot Hoyland
System Reliability Theory Book PDF

Author : Marvin Rausand,Arnljot Hoyland
Publisher : John Wiley & Sons
Page : 668 pages
File Size : 49,8 Mb
Release : 2003-12-05
Category : Technology & Engineering
ISBN : 047147133X

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System Reliability Theory by Marvin Rausand,Arnljot Hoyland Pdf

A thoroughly updated and revised look at system reliability theory Since the first edition of this popular text was published nearly a decade ago, new standards have changed the focus of reliability engineering and introduced new concepts and terminology not previously addressed in the engineering literature. Consequently, the Second Edition of System Reliability Theory: Models, Statistical Methods, and Applications has been thoroughly rewritten and updated to meet current standards. To maximize its value as a pedagogical tool, the Second Edition features: Additional chapters on reliability of maintained systems and reliability assessment of safety-critical systems Discussion of basic assessment methods for operational availability and production regularity New concepts and terminology not covered in the first edition Revised sequencing of chapters for better pedagogical structure New problems, examples, and cases for a more applied focus An accompanying Web site with solutions, overheads, and supplementary information With its updated practical focus, incorporation of industry feedback, and many new examples based on real industry problems and data, the Second Edition of this important text should prove to be more useful than ever for students, instructors, and researchers alike.

Practical Applications of Bayesian Reliability

Yan Liu,Athula I. Abeyratne
Practical Applications of Bayesian Reliability Book PDF

Author : Yan Liu,Athula I. Abeyratne
Publisher : John Wiley & Sons
Page : 265 pages
File Size : 53,7 Mb
Release : 2019-03-18
Category : Technology & Engineering
ISBN : 9781119287988

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Practical Applications of Bayesian Reliability by Yan Liu,Athula I. Abeyratne Pdf

Demonstrates how to solve reliability problems using practical applications of Bayesian models This self-contained reference provides fundamental knowledge of Bayesian reliability and utilizes numerous examples to show how Bayesian models can solve real life reliability problems. It teaches engineers and scientists exactly what Bayesian analysis is, what its benefits are, and how they can apply the methods to solve their own problems. To help readers get started quickly, the book presents many Bayesian models that use JAGS and which require fewer than 10 lines of command. It also offers a number of short R scripts consisting of simple functions to help them become familiar with R coding. Practical Applications of Bayesian Reliability starts by introducing basic concepts of reliability engineering, including random variables, discrete and continuous probability distributions, hazard function, and censored data. Basic concepts of Bayesian statistics, models, reasons, and theory are presented in the following chapter. Coverage of Bayesian computation, Metropolis-Hastings algorithm, and Gibbs Sampling comes next. The book then goes on to teach the concepts of design capability and design for reliability; introduce Bayesian models for estimating system reliability; discuss Bayesian Hierarchical Models and their applications; present linear and logistic regression models in Bayesian Perspective; and more. Provides a step-by-step approach for developing advanced reliability models to solve complex problems, and does not require in-depth understanding of statistical methodology Educates managers on the potential of Bayesian reliability models and associated impact Introduces commonly used predictive reliability models and advanced Bayesian models based on real life applications Includes practical guidelines to construct Bayesian reliability models along with computer codes for all of the case studies JAGS and R codes are provided on an accompanying website to enable practitioners to easily copy them and tailor them to their own applications Practical Applications of Bayesian Reliability is a helpful book for industry practitioners such as reliability engineers, mechanical engineers, electrical engineers, product engineers, system engineers, and materials scientists whose work includes predicting design or product performance.

Bayesian Networks for Reliability Engineering

Baoping Cai,Yonghong Liu,Zengkai Liu,Yuanjiang Chang,Lei Jiang
Bayesian Networks for Reliability Engineering Book PDF

Author : Baoping Cai,Yonghong Liu,Zengkai Liu,Yuanjiang Chang,Lei Jiang
Publisher : Springer
Page : 257 pages
File Size : 49,5 Mb
Release : 2019-02-28
Category : Technology & Engineering
ISBN : 9789811365164

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Bayesian Networks for Reliability Engineering by Baoping Cai,Yonghong Liu,Zengkai Liu,Yuanjiang Chang,Lei Jiang Pdf

This book presents a bibliographical review of the use of Bayesian networks in reliability over the last decade. Bayesian network (BN) is considered to be one of the most powerful models in probabilistic knowledge representation and inference, and it is increasingly used in the field of reliability. After focusing on the engineering systems, the book subsequently discusses twelve important issues in the BN-based reliability methodologies, such as BN structure modeling, BN parameter modeling, BN inference, validation, and verification. As such, it is a valuable resource for researchers and practitioners in the field of reliability engineering.

Reliability and Risk

Nozer D. Singpurwalla
Reliability and Risk Book PDF

Author : Nozer D. Singpurwalla
Publisher : John Wiley & Sons
Page : 396 pages
File Size : 48,7 Mb
Release : 2006-08-14
Category : Mathematics
ISBN : 9780470060339

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Reliability and Risk by Nozer D. Singpurwalla Pdf

We all like to know how reliable and how risky certain situations are, and our increasing reliance on technology has led to the need for more precise assessments than ever before. Such precision has resulted in efforts both to sharpen the notions of risk and reliability, and to quantify them. Quantification is required for normative decision-making, especially decisions pertaining to our safety and wellbeing. Increasingly in recent years Bayesian methods have become key to such quantifications. Reliability and Risk provides a comprehensive overview of the mathematical and statistical aspects of risk and reliability analysis, from a Bayesian perspective. This book sets out to change the way in which we think about reliability and survival analysis by casting them in the broader context of decision-making. This is achieved by: Providing a broad coverage of the diverse aspects of reliability, including: multivariate failure models, dynamic reliability, event history analysis, non-parametric Bayes, competing risks, co-operative and competing systems, and signature analysis. Covering the essentials of Bayesian statistics and exchangeability, enabling readers who are unfamiliar with Bayesian inference to benefit from the book. Introducing the notion of “composite reliability”, or the collective reliability of a population of items. Discussing the relationship between notions of reliability and survival analysis and econometrics and financial risk. Reliability and Risk can most profitably be used by practitioners and research workers in reliability and survivability as a source of information, reference, and open problems. It can also form the basis of a graduate level course in reliability and risk analysis for students in statistics, biostatistics, engineering (industrial, nuclear, systems), operations research, and other mathematically oriented scientists, wherein the instructor could supplement the material with examples and problems.

Bayesian Reliability Analysis

Harry F. Martz,Ray A. Waller
Bayesian Reliability Analysis Book PDF

Author : Harry F. Martz,Ray A. Waller
Publisher : Unknown
Page : 778 pages
File Size : 47,9 Mb
Release : 1982-05-14
Category : Mathematics
ISBN : MINN:31951000486757M

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Bayesian Reliability Analysis by Harry F. Martz,Ray A. Waller Pdf

A comprehensive collection of and introduction to the major advances in Bayesian reliability analysis techniques developed during the last two decades, in textbook form. Focuses primary attention on the exponential, Weibull, normal, log normal, inverse Gaussian, and gamma failure time distributions, as well as the binomial, Pascal, and Poisson sampling models. Noninformative and natural conhugate prior distributions are emphasized, although other classes or prior distributions are also often considered. Background chapters on probability, statistics, and classical reliability analysis methods are also included.

System and Bayesian Reliability

Yu Hayakawa,Richard E. Barlow,Telba Irony,Min Xie
System and Bayesian Reliability Book PDF

Author : Yu Hayakawa,Richard E. Barlow,Telba Irony,Min Xie
Publisher : World Scientific
Page : 444 pages
File Size : 51,6 Mb
Release : 2001
Category : Technology & Engineering
ISBN : 9812799540

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System and Bayesian Reliability by Yu Hayakawa,Richard E. Barlow,Telba Irony,Min Xie Pdf

This volume is a collection of articles on reliability systems and Bayesian reliability analysis. Written by reputable researchers, the articles are self-contained and are linked with literature reviews and new research ideas. The book is dedicated to Emeritus Professor Richard E Barlow, who is well known for his pioneering research on reliability theory and Bayesian reliability analysis. Contents: System Reliability Analysis: On Regular Reliability Models (J-C Chang et al.); Bounding System Reliability (J N Hagstrom & S M Ross); Large Excesses for Finite-State Markov Chains (D Blackwell); Ageing Properties: Nonmonotonic Failure Rates and Mean Residual Life Functions (R C Gupta); The Failure Rate and the Mean Residual Lifetime of Mixtures (M S Finkelstein); On Some Discrete Notions of Aging (C Bracquemond et al.); Bayesian Analysis: On the Practical Implementation of the Bayesian Paradigm in Reliability and Risk Analysis (T Aven); A Weibull Wearout Test: Full Bayesian Approach (T Z Irony et al.); Bayesian Nonparametric Estimation of a Monotone Hazard Rate (M-W Ho & A Y Lo); and other papers. Readership: Students, academics, researchers and professionals in industrial engineering, probability and statistics, and applied mathematics.

The Theory and Applications of Reliability With Emphasis on Bayesian and Nonparametric Methods

Chris Tsokos
The Theory and Applications of Reliability With Emphasis on Bayesian and Nonparametric Methods Book PDF

Author : Chris Tsokos
Publisher : Elsevier
Page : 566 pages
File Size : 52,7 Mb
Release : 2012-12-02
Category : Technology & Engineering
ISBN : 9780323145855

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The Theory and Applications of Reliability With Emphasis on Bayesian and Nonparametric Methods by Chris Tsokos Pdf

The Theory and Applications of Reliability: With Emphasis on Bayesian and Nonparametric Methods, Volume I covers the proceedings of the conference on ""The Theory and Applications of Reliability with Emphasis on Bayesian and Nonparametric Methods."" The conference is organized so as to have technical presentations, a clinical session, and round table discussions. This volume is a 29-chapter text that specifically deals with the theoretical aspects of reliability estimation. Considerable chapters on the technical sessions are devoted to initial findings on the theory and applications of reliability estimation, with special emphasis on Bayesian and nonparametric methods. A Bayesian analysis implies the use of suitable prior information in association with Bayes theorem while the nonparametric approach analyzes the reliability components and systems under the assumption of a time-to-failure distribution with a wide defining property rather than a specific parametric class of probability distributions. The clinical session chapters discuss the actual problems encountered in reliability estimation. The remaining chapters deal with the status of the subject areas and the empirical Bayes developments. These chapters also present various probabilistic and statistic methods for reliability estimation. Theoreticians and reliability engineers will find this book invaluable.

Bayesian Inference for Probabilistic Risk Assessment

Dana Kelly,Curtis Smith
Bayesian Inference for Probabilistic Risk Assessment Book PDF

Author : Dana Kelly,Curtis Smith
Publisher : Springer Science & Business Media
Page : 230 pages
File Size : 55,7 Mb
Release : 2011-08-30
Category : Technology & Engineering
ISBN : 9781849961875

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Bayesian Inference for Probabilistic Risk Assessment by Dana Kelly,Curtis Smith Pdf

Bayesian Inference for Probabilistic Risk Assessment provides a Bayesian foundation for framing probabilistic problems and performing inference on these problems. Inference in the book employs a modern computational approach known as Markov chain Monte Carlo (MCMC). The MCMC approach may be implemented using custom-written routines or existing general purpose commercial or open-source software. This book uses an open-source program called OpenBUGS (commonly referred to as WinBUGS) to solve the inference problems that are described. A powerful feature of OpenBUGS is its automatic selection of an appropriate MCMC sampling scheme for a given problem. The authors provide analysis “building blocks” that can be modified, combined, or used as-is to solve a variety of challenging problems. The MCMC approach used is implemented via textual scripts similar to a macro-type programming language. Accompanying most scripts is a graphical Bayesian network illustrating the elements of the script and the overall inference problem being solved. Bayesian Inference for Probabilistic Risk Assessment also covers the important topics of MCMC convergence and Bayesian model checking. Bayesian Inference for Probabilistic Risk Assessment is aimed at scientists and engineers who perform or review risk analyses. It provides an analytical structure for combining data and information from various sources to generate estimates of the parameters of uncertainty distributions used in risk and reliability models.

Bayesian Methods for Structural Dynamics and Civil Engineering

Ka-Veng Yuen
Bayesian Methods for Structural Dynamics and Civil Engineering Book PDF

Author : Ka-Veng Yuen
Publisher : John Wiley & Sons
Page : 320 pages
File Size : 42,7 Mb
Release : 2010-02-22
Category : Mathematics
ISBN : 0470824557

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Bayesian Methods for Structural Dynamics and Civil Engineering by Ka-Veng Yuen Pdf

Bayesian methods are a powerful tool in many areas of science and engineering, especially statistical physics, medical sciences, electrical engineering, and information sciences. They are also ideal for civil engineering applications, given the numerous types of modeling and parametric uncertainty in civil engineering problems. For example, earthquake ground motion cannot be predetermined at the structural design stage. Complete wind pressure profiles are difficult to measure under operating conditions. Material properties can be difficult to determine to a very precise level – especially concrete, rock, and soil. For air quality prediction, it is difficult to measure the hourly/daily pollutants generated by cars and factories within the area of concern. It is also difficult to obtain the updated air quality information of the surrounding cities. Furthermore, the meteorological conditions of the day for prediction are also uncertain. These are just some of the civil engineering examples to which Bayesian probabilistic methods are applicable. Familiarizes readers with the latest developments in the field Includes identification problems for both dynamic and static systems Addresses challenging civil engineering problems such as modal/model updating Presents methods applicable to mechanical and aerospace engineering Gives engineers and engineering students a concrete sense of implementation Covers real-world case studies in civil engineering and beyond, such as: structural health monitoring seismic attenuation finite-element model updating hydraulic jump artificial neural network for damage detection air quality prediction Includes other insightful daily-life examples Companion website with MATLAB code downloads for independent practice Written by a leading expert in the use of Bayesian methods for civil engineering problems This book is ideal for researchers and graduate students in civil and mechanical engineering or applied probability and statistics. Practicing engineers interested in the application of statistical methods to solve engineering problems will also find this to be a valuable text. MATLAB code and lecture materials for instructors available at http://www.wiley.com/go/yuen

Statistical Methods for Reliability Data

William Q. Meeker,Luis A. Escobar,Francis G. Pascual
Statistical Methods for Reliability Data Book PDF

Author : William Q. Meeker,Luis A. Escobar,Francis G. Pascual
Publisher : John Wiley & Sons
Page : 708 pages
File Size : 43,6 Mb
Release : 2022-01-24
Category : Technology & Engineering
ISBN : 9781118594483

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Statistical Methods for Reliability Data by William Q. Meeker,Luis A. Escobar,Francis G. Pascual Pdf

An authoritative guide to the most recent advances in statistical methods for quantifying reliability Statistical Methods for Reliability Data, Second Edition (SMRD2) is an essential guide to the most widely used and recently developed statistical methods for reliability data analysis and reliability test planning. Written by three experts in the area, SMRD2 updates and extends the long- established statistical techniques and shows how to apply powerful graphical, numerical, and simulation-based methods to a range of applications in reliability. SMRD2 is a comprehensive resource that describes maximum likelihood and Bayesian methods for solving practical problems that arise in product reliability and similar areas of application. SMRD2 illustrates methods with numerous applications and all the data sets are available on the book’s website. Also, SMRD2 contains an extensive collection of exercises that will enhance its use as a course textbook. The SMRD2's website contains valuable resources, including R packages, Stan model codes, presentation slides, technical notes, information about commercial software for reliability data analysis, and csv files for the 93 data sets used in the book's examples and exercises. The importance of statistical methods in the area of engineering reliability continues to grow and SMRD2 offers an updated guide for, exploring, modeling, and drawing conclusions from reliability data. SMRD2 features: Contains a wealth of information on modern methods and techniques for reliability data analysis Offers discussions on the practical problem-solving power of various Bayesian inference methods Provides examples of Bayesian data analysis performed using the R interface to the Stan system based on Stan models that are available on the book's website Includes helpful technical-problem and data-analysis exercise sets at the end of every chapter Presents illustrative computer graphics that highlight data, results of analyses, and technical concepts Written for engineers and statisticians in industry and academia, Statistical Methods for Reliability Data, Second Edition offers an authoritative guide to this important topic.

Modern Statistical and Mathematical Methods in Reliability

Alyson G. Wilson
Modern Statistical and Mathematical Methods in Reliability Book PDF

Author : Alyson G. Wilson
Publisher : World Scientific
Page : 430 pages
File Size : 45,6 Mb
Release : 2005
Category : Mathematics
ISBN : 9789812563569

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Modern Statistical and Mathematical Methods in Reliability by Alyson G. Wilson Pdf

This volume contains extended versions of 28 carefully selected and reviewed papers presented at The Fourth International Conference on Mathematical Methods in Reliability in Santa Fe, New Mexico, June 21-25, 2004, the leading conference in reliability research. A broad overview of current research activities in reliability theory and its applications is provided with coverage on reliability modeling, network and system reliability, Bayesian methods, survival analysis, degradation and maintenance modeling, and software reliability. The contributors are all leading experts in the field and include the plenary session speakers, Tim Bedford, Thierry Duchesne, Henry Wynn, Vicki Bier, Edsel Pena, Michael Hamada, and Todd Graves.

Introduction to Reliability Analysis

Shelemyahu Zacks
Introduction to Reliability Analysis Book PDF

Author : Shelemyahu Zacks
Publisher : Springer Science & Business Media
Page : 226 pages
File Size : 53,6 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461228547

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Introduction to Reliability Analysis by Shelemyahu Zacks Pdf

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.

System Reliability Theory

Arnljot Høyland,Marvin Rausand
System Reliability Theory Book PDF

Author : Arnljot Høyland,Marvin Rausand
Publisher : John Wiley & Sons
Page : 536 pages
File Size : 53,9 Mb
Release : 2009-09-25
Category : Technology & Engineering
ISBN : 9780470317747

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System Reliability Theory by Arnljot Høyland,Marvin Rausand Pdf

A comprehensive introduction to reliability analysis. The first section provides a thorough but elementary prologue to reliability theory. The latter half comprises more advanced analytical tools including Markov processes, renewal theory, life data analysis, accelerated life testing and Bayesian reliability analysis. Features numerous worked examples. Each chapter concludes with a selection of problems plus additional material on applications.