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With the growing complexity of engineered systems, reliability hasincreased in importance throughout the twentieth century. Initiallydeveloped to meet practical needs, reliability theory has become anapplied mathematical discipline that permits a priori evaluationsof various reliability indices at the design stages. Theseevaluations help engineers choose an optimal system structure,improve methods of maintenance, and estimate the reliability on thebasis of special testing. Probabilistic Reliability Engineeringfocuses on the creation of mathematical models for solving problemsof system design. Broad and authoritative in its content, Probabilistic ReliabilityEngineering covers all mathematical models associated withprobabilistic methods of reliability analysis, including--unique tothis book--maintenance and cost analysis, as well as many newresults of probabilistic testing. To provide readers with all necessary background material, thistext incorporates a thorough review of the fundamentals ofprobability theory and the theory of stochastic processes. Itoffers clear and detailed treatment of reliability indices, thestructure function, load-strength reliability models, distributionswith monotone intensity functions, repairable systems, the Markovmodels, analysis of performance effectiveness, two-pole networks,optimal redundancy, optimal technical diagnosis, and heuristicmethods in reliability. Throughout the text, an abundance of realworld examples and case studies illustrate and illuminate thetheoretical points under consideration. For engineers in design, operations research, and maintenance, aswell as cost analysts and R&D managers, ProbabilisticReliability Engineering offers the most lucid, comprehensivetreatment of the subject available anywhere. About the editor JAMES A. FALK is Professor and Chairman of the Department ofOperations Research at George Washington University. In addition tohis numerous publications, Dr. Falk has lectured internationally asa Fulbright Lecturer. Of related interest... The reliability-testing "bible" for three generations of EasternEuropean scientists, adapted for Western scientists andengineers... HANDBOOK OF RELIABILITY ENGINEERING Originally published in the USSR, Handbook of ReliabilityEngineering set the standard for the reliability testing oftechnical systems for nearly three generations of appliedscientists and engineers. Authored by a group of prominent Sovietspecialists in reliability, it provides professionals and studentswith a comprehensive reference covering mathematical formulas andtechniques for incorporating reliability into engineering designsand testing procedures. Divided into twenty-four self-containedchapters, the Handbook details reliability fundamentals, examinescommon reliability problems and solutions, provides a collection ofcomputation formulas, and illustrates practical applications. The Handbook's Russian editor and internationally recognized expertIgor A. Ushakov has joined with American engineering professionalsto bring this indispensable resource to English-speaking engineersand scientists. 1994 (0-471-57173-3) 663 pp.
Without proper reliability and maintenance planning, even the most efficient and seemingly cost-effective designs can incur enormous expenses due to repeated or catastrophic failure and subsequent search for the cause. Today’s engineering students face increasing pressure from employers, customers, and regulators to produce cost-efficient designs that are less prone to failure and that are safe and easy to use. The second edition of Reliability Engineering aims to provide an understanding of reliability principles and maintenance planning to help accomplish these goals. This edition expands the treatment of several topics while maintaining an integrated introductory resource for the study of reliability evaluation and maintenance planning. The focus across all of the topics treated is the use of analytical methods to support the design of dependable and efficient equipment and the planning for the servicing of that equipment. The argument is made that probability models provide an effective vehicle for portraying and evaluating the variability that is inherent in the performance and longevity of equipment. With a blend of mathematical rigor and readability, this book is the ideal introductory textbook for graduate students and a useful resource for practising engineers.
The book provides details on 22 probability distributions. Each distribution section provides a graphical visualization and formulas for distribution parameters, along with distribution formulas. Common statistics such as moments and percentile formulas are followed by likelihood functions and in many cases the derivation of maximum likelihood estimates. Bayesian non-informative and conjugate priors are provided followed by a discussion on the distribution characteristics and applications in reliability engineering.
An Integrated Approach to Product Development Reliability Engineering presents an integrated approach to the design, engineering, and management of reliability activities throughout the life cycle of a product, including concept, research and development, design, manufacturing, assembly, sales, and service. Containing illustrative guides that include worked problems, numerical examples, homework problems, a solutions manual, and class-tested materials, it demonstrates to product development and manufacturing professionals how to distribute key reliability practices throughout an organization. The authors explain how to integrate reliability methods and techniques in the Six Sigma process and Design for Six Sigma (DFSS). They also discuss relationships between warranty and reliability, as well as legal and liability issues. Other topics covered include: Reliability engineering in the 21st Century Probability life distributions for reliability analysis Process control and process capability Failure modes, mechanisms, and effects analysis Health monitoring and prognostics Reliability tests and reliability estimation Reliability Engineering provides a comprehensive list of references on the topics covered in each chapter. It is an invaluable resource for those interested in gaining fundamental knowledge of the practical aspects of reliability in design, manufacturing, and testing. In addition, it is useful for implementation and management of reliability programs.
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
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.
The book presents highly technical approaches to the probabilistic physics of failure analysis and applications to accelerated life and degradation testing to reliability prediction and assessment. Beside reviewing a select set of important failure mechanisms, the book covers basic and advanced methods of performing accelerated life test and accelerated degradation tests and analyzing the test data. The book includes a large number of very useful examples to help readers understand complicated methods described. Finally, MATLAB, R and OpenBUGS computer scripts are provided and discussed to support complex computational probabilistic analyses introduced.
Die Zuverlassigkeitsanalyse soll absichern, da? alle Komponenten eines Systems oder Produkts die Anforderungen an Funktionstuchtigkeit, -umfang und Budget erfullen. Alle wichtigen mathematischen Methoden, die in diesem Zusammenhang verwendet werden, stellt in diesem Buch einer der fuhrenden Spezialisten dieses Gebietes vor. Mit vielen realitatsnahen Beispielen und Fallstudien. (05/99)
Handbook for the computation and empirical estimation of reliability. Introduces an incomparable volume of easily applicable, cutting-edge results originated by prominent Russian reliability specialists. Completely covers probabilistic reliability, statistical reliability and optimization with simple, step-by-step, numerical examples. Offers a broad range of applications in engineering, operations research, cost analysis and project management. Explores reliability software extensively. Includes appendices with summary reviews of mathematical and statistical fundamentals.
Recent Advances in System Reliability Engineering describes and evaluates the latest tools, techniques, strategies, and methods in this topic for a variety of applications. Special emphasis is put on simulation and modelling technology which is growing in influence in industry, and presents challenges as well as opportunities to reliability and systems engineers. Several manufacturing engineering applications are addressed, making this a particularly valuable reference for readers in that sector. - Contains comprehensive discussions on state-of-the-art tools, techniques, and strategies from industry - Connects the latest academic research to applications in industry including system reliability, safety assessment, and preventive maintenance - Gives an in-depth analysis of the benefits and applications of modelling and simulation to reliability