STATISTICAL METHODS FOR QUALITY, RELIABILITY AND MAINTAINABILITY
STATISTICAL METHODS FOR QUALITY, RELIABILITY AND MAINTAINABILITY

Author: K. MURALIDHARAN

Publisher: PHI Learning Pvt. Ltd.

Published: 2012-05-16

Total Pages: 365

ISBN-13: 8120345436

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A fine blend of the three disciplines, viz. quality, reliability and maintainability, this book provides a clear understanding of the concepts and discusses their applications using statistical tools and techniques. The concepts are critically assessed and explained to enable their use for management decision-making. The book describes many current topics such as six sigma, capability maturity model integration (CMMI), process data management, reliability system models, repairable system models, maintainability assessment and design and testing concepts. It is intended as a textbook for the undergraduate students of Mechanical Engineering and Production and Industrial Engineering. The book will also be useful to the postgraduate students of Applied Statistics, Quality and Reliability, and Quality and Productivity Management as well as to the management and engineering professionals. KEY FEATURES : Provides charts and plots to explain the concepts discussed. Gives an account of most recent developments. Gives illustrations of practical situations where tools can be applied immediately. Interspersed with plenty of worked-out examples to reinforce the concepts. Includes chapter-end exercises to drill the students in self-study.

Mathematical and Statistical Methods in Reliability
Mathematical and Statistical Methods in Reliability

Author: Bo Lindqvist

Publisher: World Scientific

Published: 2003

Total Pages: 569

ISBN-13: 9812383212

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This book contains extended versions of carefully selected and reviewed papers presented at the Third International Conference on Mathematical Methods in Reliability, held in Norway in 2002. It provides an overview of current research activities in reliability theory. The authors are all leading experts in the field. Readership: Graduate students, academics and professionals in probability & statistics, reliability analysis, survival analysis, industrial engineering, software engineering, operations research and applied mathematics research.

Quality and Reliability of Technical Systems
Quality and Reliability of Technical Systems

Author: Alessandro Birolini

Publisher: Springer Science & Business Media

Published: 2013-03-14

Total Pages: 538

ISBN-13: 3662029707

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High reliability, maintainability, and safety are expected from complex equipment and systems. To build these characteristics into an item, failure rate and failure mode analyses have to be performed early in the design phase, starting at the com ponent level, and have to be supported by a set of design guidelines for reliability and maintainability as well as by extensive design reviews. Before production, qualification tests of prototypes must ensure that quality and reliability targets have been reached. In the production phase, processes and procedures have to be selec ted and monitored to assure the required quality level. For many systems, availabi lity requirements must also be satisfied. In these cases, stochastic processes can be used to investigate and optimize availability, including logistical support. This book presents the state of the art of the methods and procedures necessary for a cost and time effective quality and reliability assurance during the design and production of equipment and systems. It takes into consideration that: 1. Quality and reliability assurance of complex equipment and systems requires that all engineers involved in a project undertake a set of specific activities from the definition to the operating phase, which are performed concurrently to achieve the best performance, quality, and reliability for given cost and time schedule targets.

Statistical Methods for Reliability Data
Statistical Methods for Reliability Data

Author: William Q. Meeker

Publisher: John Wiley & Sons

Published: 2022-01-24

Total Pages: 708

ISBN-13: 1118594487

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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.

Product Reliability, Maintainability, and Supportability Handbook
Product Reliability, Maintainability, and Supportability Handbook

Author: Michael Pecht

Publisher: CRC Press

Published: 2009-04-16

Total Pages: 482

ISBN-13: 1420009893

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To ensure product reliability, an organization must follow specific practices during the product development process that impact reliability. The second edition of the bestselling Product Reliability, Maintainability, and Supportability Handbook helps professionals identify the shortcomings in the reliability practices of their organizations and em

Statistical Methods for Quality Assurance
Statistical Methods for Quality Assurance

Author: Stephen B. Vardeman

Publisher: Springer

Published: 2016-08-26

Total Pages: 447

ISBN-13: 038779106X

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This undergraduate statistical quality assurance textbook clearly shows with real projects, cases and data sets how statistical quality control tools are used in practice. Among the topics covered is a practical evaluation of measurement effectiveness for both continuous and discrete data. Gauge Reproducibility and Repeatability methodology (including confidence intervals for Repeatability, Reproducibility and the Gauge Capability Ratio) is thoroughly developed. Process capability indices and corresponding confidence intervals are also explained. In addition to process monitoring techniques, experimental design and analysis for process improvement are carefully presented. Factorial and Fractional Factorial arrangements of treatments and Response Surface methods are covered. Integrated throughout the book are rich sets of examples and problems that help readers gain a better understanding of where and how to apply statistical quality control tools. These large and realistic problem sets in combination with the streamlined approach of the text and extensive supporting material facilitate reader understanding. Second Edition Improvements Extensive coverage of measurement quality evaluation (in addition to ANOVA Gauge R&R methodologies) New end-of-section exercises and revised-end-of-chapter exercises Two full sets of slides, one with audio to assist student preparation outside-of-class and another appropriate for professors’ lectures Substantial supporting material Supporting Material Seven R programs that support variables and attributes control chart construction and analyses, Gauge R&R methods, analyses of Fractional Factorial studies, Propagation of Error analyses and Response Surface analyses Documentation for the R programs Excel data files associated with the end-of-chapter problem sets, most from real engineering settings

Mathematical and Statistical Models and Methods in Reliability
Mathematical and Statistical Models and Methods in Reliability

Author: V.V. Rykov

Publisher: Springer Science & Business Media

Published: 2010-11-02

Total Pages: 465

ISBN-13: 0817649719

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The book is a selection of invited chapters, all of which deal with various aspects of mathematical and statistical models and methods in reliability. Written by renowned experts in the field of reliability, the contributions cover a wide range of applications, reflecting recent developments in areas such as survival analysis, aging, lifetime data analysis, artificial intelligence, medicine, carcinogenesis studies, nuclear power, financial modeling, aircraft engineering, quality control, and transportation. Mathematical and Statistical Models and Methods in Reliability is an excellent reference text for researchers and practitioners in applied probability and statistics, industrial statistics, engineering, medicine, finance, transportation, the oil and gas industry, and artificial intelligence.

Applied Reliability Engineering and Risk Analysis
Applied Reliability Engineering and Risk Analysis

Author: Ilia B. Frenkel

Publisher: John Wiley & Sons

Published: 2013-08-22

Total Pages: 449

ISBN-13: 1118701895

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This complete resource on the theory and applications of reliability engineering, probabilistic models and risk analysis consolidates all the latest research, presenting the most up-to-date developments in this field. With comprehensive coverage of the theoretical and practical issues of both classic and modern topics, it also provides a unique commemoration to the centennial of the birth of Boris Gnedenko, one of the most prominent reliability scientists of the twentieth century. Key features include: expert treatment of probabilistic models and statistical inference from leading scientists, researchers and practitioners in their respective reliability fields detailed coverage of multi-state system reliability, maintenance models, statistical inference in reliability, systemability, physics of failures and reliability demonstration many examples and engineering case studies to illustrate the theoretical results and their practical applications in industry Applied Reliability Engineering and Risk Analysis is one of the first works to treat the important areas of degradation analysis, multi-state system reliability, networks and large-scale systems in one comprehensive volume. It is an essential reference for engineers and scientists involved in reliability analysis, applied probability and statistics, reliability engineering and maintenance, logistics, and quality control. It is also a useful resource for graduate students specialising in reliability analysis and applied probability and statistics. Dedicated to the Centennial of the birth of Boris Gnedenko, renowned Russian mathematician and reliability theorist

Case Studies in Reliability and Maintenance
Case Studies in Reliability and Maintenance

Author: Wallace R. Blischke

Publisher: John Wiley & Sons

Published: 2003-03-27

Total Pages: 691

ISBN-13: 0471458732

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Introducing a groundbreaking companion book to a bestselling reliability text Reliability is one of the most important characteristics defining the quality of a product or system, both for the manufacturer and the purchaser. One achieves high reliability through careful monitoring of design, materials and other input, production, quality assurance efforts, ongoing maintenance, and a variety of related decisions and activities. All of these factors must be considered in determining the costs of production, purchase, and ownership of a product. Case Studies in Reliability and Maintenance serves as a valuable addition to the current literature on the subject of reliability by bridging the gap between theory and application. Conceived during the preparation of the editors' earlier work, Reliability: Modeling, Prediction, and Optimization (Wiley, 2000), this new volume features twenty-six actual case studies written by top experts in their fields, each illustrating exactly how reliability models are applied. A valuable companion book to Reliability: Modeling, Prediction, and Optimization, or any other textbook on the subject, the book features: * Case studies from fields such as aerospace, automotive, mining, electronics, power plants, dikes, computer software, weapons, photocopiers, industrial furnaces, granite building cladding, chemistry, and aircraft engines * A logical organization according to the life cycle of a product or system * A unified format of discussion enhanced by tools, techniques, and models for drawing one's own conclusions * Pertinent exercises for reinforcement of ideas Of equal value to both students of reliability theory as well as professionals in industry, Case Studies in Reliability and Maintenance should be required reading for anyone seeking to understand how reliability and maintenance issues can be addressed and resolved in the real world.

Computational Methods for Reliability and Risk Analysis
Computational Methods for Reliability and Risk Analysis

Author: Enrico Zio

Publisher: World Scientific

Published: 2009

Total Pages: 363

ISBN-13: 9812839011

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This book illustrates a number of modelling and computational techniques for addressing relevant issues in reliability and risk analysis. In particular, it provides: i) a basic illustration of some methods used in reliability and risk analysis for modelling the stochastic failure and repair behaviour of systems, e.g. the Markov and Monte Carlo simulation methods; ii) an introduction to Genetic Algorithms, tailored to their application for RAMS (Reliability, Availability, Maintainability and Safety) optimization; iii) an introduction to key issues of system reliability and risk analysis, like dependent failures and importance measures; and iv) a presentation of the issue of uncertainty and of the techniques of sensitivity and uncertainty analysis used in support of reliability and risk analysis.The book provides a technical basis for senior undergraduate or graduate courses and a reference for researchers and practitioners in the field of reliability and risk analysis. Several practical examples are included to demonstrate the application of the concepts and techniques in practice.