STATISTICAL METHODS FOR QUALITY, RELIABILITY AND MAINTAINABILITY

STATISTICAL METHODS FOR QUALITY, RELIABILITY AND MAINTAINABILITY PDF

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 PDF

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.

Mathematical And Statistical Methods In Reliability

Mathematical And Statistical Methods In Reliability PDF

Author: Kjell A Doksum

Publisher: World Scientific

Published: 2003-10-10

Total Pages: 569

ISBN-13: 9814486264

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This book contains extended versions of 34 carefully selected and reviewed papers presented at the Third International Conference on Mathematical Methods in Reliability, held in Trondheim, Norway in 2002. It provides a broad overview of current research activities in reliability theory and its applications. There are chapters on reliability modelling, network and system reliability, reliability optimization, survival analysis, degradation and maintenance modelling, and software reliability. The authors are all leading experts in the field.A particular feature of the book is a historical review by Professor Richard E Barlow, well known for his pioneering research on reliability. The list of authors also includes the plenary session speakers Odd O Aalen, Philip J Boland, Sallie A Keller-McNulty, and Nozer Singpurwalla.

Statistical Methods for the Reliability of Repairable Systems

Statistical Methods for the Reliability of Repairable Systems PDF

Author: Steven E. Rigdon

Publisher: Wiley-Interscience

Published: 2000-04-14

Total Pages: 0

ISBN-13: 9780471349419

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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.

Product Reliability, Maintainability, and Supportability Handbook

Product Reliability, Maintainability, and Supportability Handbook PDF

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

Reliability, Maintainability and Risk

Reliability, Maintainability and Risk PDF

Author: David J. Smith

Publisher: Elsevier

Published: 2011-06-29

Total Pages: 436

ISBN-13: 9780080969039

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Reliability, Maintainability and Risk: Practical Methods for Engineers, Eighth Edition, discusses tools and techniques for reliable and safe engineering, and for optimizing maintenance strategies. It emphasizes the importance of using reliability techniques to identify and eliminate potential failures early in the design cycle. The focus is on techniques known as RAMS (reliability, availability, maintainability, and safety-integrity). The book is organized into five parts. Part 1 on reliability parameters and costs traces the history of reliability and safety technology and presents a cost-effective approach to quality, reliability, and safety. Part 2 deals with the interpretation of failure rates, while Part 3 focuses on the prediction of reliability and risk. Part 4 discusses design and assurance techniques; review and testing techniques; reliability growth modeling; field data collection and feedback; predicting and demonstrating repair times; quantified reliability maintenance; and systematic failures. Part 5 deals with legal, management and safety issues, such as project management, product liability, and safety legislation. 8th edition of this core reference for engineers who deal with the design or operation of any safety critical systems, processes or operations Answers the question: how can a defect that costs less than $1000 dollars to identify at the process design stage be prevented from escalating to a $100,000 field defect, or a $1m+ catastrophe Revised throughout, with new examples, and standards, including must have material on the new edition of global functional safety standard IEC 61508, which launches in 2010

System Reliability Theory

System Reliability Theory PDF

Author: Marvin Rausand

Publisher: John Wiley & Sons

Published: 2020-11-03

Total Pages: 864

ISBN-13: 1119373522

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Handbook and reference for industrial statisticians and system reliability engineers System Reliability Theory: Models, Statistical Methods, and Applications, Third Edition presents an updated and revised look at system reliability theory, modeling, and analytical methods. The new edition is based on feedback to the second edition from numerous students, professors, researchers, and industries around the world. New sections and chapters are added together with new real-world industry examples, and standards and problems are revised and updated. System Reliability Theory covers a broad and deep array of system reliability topics, including: · In depth discussion of failures and failure modes · The main system reliability assessment methods · Common-cause failure modeling · Deterioration modeling · Maintenance modeling and assessment using Python code · Bayesian probability and methods · Life data analysis using R Perfect for undergraduate and graduate students taking courses in reliability engineering, this book also serves as a reference and resource for practicing statisticians and engineers. Throughout, the book has a practical focus, incorporating industry feedback and real-world industry problems and examples.

Statistical Methods for Reliability Data

Statistical Methods for Reliability Data PDF

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.

Statistical Methods for Quality Assurance

Statistical Methods for Quality Assurance PDF

Author: Stephen B. Vardeman

Publisher: Springer

Published: 2016-08-26

Total Pages: 437

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 PDF

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.