Through simple, practical approaches, Reliability Analysis and Prediction with Warranty Data: Issues, Strategies, and Methods helps Six Sigma black belts and engineers successfully interpret warranty data to make accurate predictions. It discusses how to use this data to define and analyze field problems, provides guidelines for discovering the roo
This book equips the reader with a compact information source on all the most recent methodological tools available in the area of reliability prediction and analysis. Topics covered include reliability mathematics, organisation and analysis of data, reliability modelling and system reliability evaluation techniques. Environmental factors and stresses are taken into account in computing the reliability of the involved components. The limitations of models, methods, procedures, algorithms and programmes are outlined. The treatment of maintained systems is designed to aid the worker in analysing systems with more realistic and practical assumptions. Fault tree analysis is also extensively discussed, incorporating recent developments. Examples and illustrations support the reader in the solving of problems in his own area of research. The chapters provide a logical and graded presentation of the subject matter bearing in mind the difficulties of a beginner, whilst bridging the information gap for the more experienced reader. The work will be of considerable interest to engineers working in various industries, research organizations, particularly in defence, nuclear, chemical, space or communications. It will also be an indispensable study aid for serious-minded students and teachers.
In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry. AI Techniques for Reliability Prediction for Electronic Components provides emerging research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. Featuring coverage on a broad range of topics such as data collection, fault tolerance, and health prognostics, this book is ideally designed for reliability engineers, electronic engineers, researchers, scientists, students, and faculty members seeking current research on the advancement of reliability analysis using AI.
"This text covers the development of decision theory and related applications of probability. Extensive examples and illustrations cultivate students' appreciation for applications, including strength of materials, soil mechanics, construction planning, and water-resource design. Emphasis on fundamentals makes the material accessible to students trained in classical statistics and provides a brief introduction to probability. 1970 edition"--
Bringing together business and engineering to reliability analysisWith manufactured products exploding in numbers and complexity,reliability studies play an increasingly critical role throughout aproduct's entire life cycle-from design to post-sale support.Reliability: Modeling, Prediction, and Optimization presents aremarkably broad framework for the analysis of the technical andcommercial aspects of product reliability, integrating concepts andmethodologies from such diverse areas as engineering, materialsscience, statistics, probability, operations research, andmanagement. Written in plain language by two highly respectedexperts in the field, this practical work provides engineers,operations managers, and applied statisticians with bothqualitative and quantitative tools for solving a variety ofcomplex, real-world reliability problems. A wealth of examples andcase studies accompanies: * Comprehensive coverage of assessment, prediction, and improvementat each stage of a product's life cycle * Clear explanations of modeling and analysis for hardware rangingfrom a single part to whole systems * Thorough coverage of test design and statistical analysis ofreliability data * A special chapter on software reliability * Coverage of effective management of reliability, product support,testing, pricing, and related topics * Lists of sources for technical information, data, and computerprograms * Hundreds of graphs, charts, and tables, as well as over 500references * PowerPoint slides are available from the Wiley editorialdepartment.
The objectives of Human Reliability are to build reliability into the job, into the machine, and into the environment, and to let man perform naturally. In this book the author shows how these objectives can be achieved by concentrating on human reliability issues during the design stage. This is done by illustrating the relationships between various design features and some aspect of human performance, e.g. human errors.The book is designed as a practical guide to the daily performance of tasks in Human Reliability as well as a general reference and tutorial introduction to the field. It is therefore both practical and theoretical: the first four chapters focus on principles and ramifications relevant to human error prevention; the latter four are primarily concerned with human reliability analysis and prediction methodology. Throughout the book there are extensive references, numerous ready-to-use recommendations, formulas and mathematical models, and computer programs for human reliability work for analyzing, predicting and preventing human errors in a variety of situations. Though some of the material requires undergraduate training in engineering, the more difficult mathematical expositions can be omitted without loss of continuity, but are available for the reader who needs a more complete understanding of the relevant theory.
This textbook reviews the methodologies of reliability prediction as currently used in industries such as electronics, automotive, aircraft, aerospace, off-highway, farm machinery, and others. It then discusses why these are not successful; and, presents methods developed by the authors for obtaining accurate information for successful prediction. The approach is founded on approaches that accurately duplicate the real world use of the product. Their approach is based on two fundamental components needed for successful reliability prediction; first, the methodology necessary; and, second, use of accelerated reliability and durability testing as a source of the necessary data. Applicable to all areas of engineering, this textbook details the newest techniques and tools to achieve successful reliabilityprediction and testing. It demonstrates practical examples of the implementation of the approaches described. This book is a tool for engineers, managers, researchers, in industry, teachers, and students. The reader will learn the importance of the interactions of the influencing factors and the interconnections of safety and human factors in product prediction and testing.
This book is intended for students and practitioners who have had a calculus-based statistics course and who have an interest in safety considerations such as reliability, strength, and duration-of-load or service life. Many persons studying statistical science will be employed professionally where the problems encountered are obscure, what should be analyzed is not clear, the appropriate assumptions are equivocal, and data are scant. In this book there is no disclosure with many of the data sets what type of investigation should be made or what assumptions are to be used.
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.
