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This handbook will provide an understanding of standard and advanced Weibull and Log Normal techniques originally developed for failure analysis.
Reliability Engineering – A Life Cycle Approach is based on the author’s knowledge of systems and their problems from multiple industries, from sophisticated, first class installations to less sophisticated plants often operating under severe budget constraints and yet having to deliver first class availability. Taking a practical approach and drawing from the author’s global academic and work experience, the text covers the basics of reliability engineering, from design through to operation and maintenance. Examples and problems are used to embed the theory, and case studies are integrated to convey real engineering experience and to increase the student’s analytical skills. Additional subjects such as failure analysis, the management of the reliability function, systems engineering skills, project management requirements and basic financial management requirements are covered. Linear programming and financial analysis are presented in the context of justifying maintenance budgets and retrofits. The book presents a stand-alone picture of the reliability engineer’s work over all stages of the system life-cycle, and enables readers to: Understand the life-cycle approach to engineering reliability Explore failure analysis techniques and their importance in reliability engineering Learn the skills of linear programming, financial analysis, and budgeting for maintenance Analyze the application of key concepts through realistic Case Studies This text will equip engineering students, engineers and technical managers with the knowledge and skills they need, and the numerous examples and case studies include provide insight to their real-world application. An Instructor’s Manual and Figure Slides are available for instructors.
The Most Comprehensive Book on the SubjectChronicles the Development of the Weibull Distribution in Statistical Theory and Applied StatisticsExploring one of the most important distributions in statistics, The Weibull Distribution: A Handbook focuses on its origin, statistical properties, and related distributions. The book also presents various ap
Understand and utilize the latest developments in Weibull inferential methods While the Weibull distribution is widely used in science and engineering, most engineers do not have the necessary statistical training to implement the methodology effectively. Using the Weibull Distribution: Reliability, Modeling, and Inference fills a gap in the current literature on the topic, introducing a self-contained presentation of the probabilistic basis for the methodology while providing powerful techniques for extracting information from data. The author explains the use of the Weibull distribution and its statistical and probabilistic basis, providing a wealth of material that is not available in the current literature. The book begins by outlining the fundamental probability and statistical concepts that serve as a foundation for subsequent topics of coverage, including: • Optimum burn-in, age and block replacement, warranties and renewal theory • Exact inference in Weibull regression • Goodness of fit testing and distinguishing the Weibull from the lognormal • Inference for the Three Parameter Weibull Throughout the book, a wealth of real-world examples showcases the discussed topics and each chapter concludes with a set of exercises, allowing readers to test their understanding of the presented material. In addition, a related website features the author's own software for implementing the discussed analyses along with a set of modules written in Mathcad®, and additional graphical interface software for performing simulations. With its numerous hands-on examples, exercises, and software applications, Using the Weibull Distribution is an excellent book for courses on quality control and reliability engineering at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for engineers, scientists, and business analysts who gather and interpret data that follows the Weibull distribution
Dental Biomaterials: Imaging, Testing and Modelling reviews the materials used in this important area, their performance and how such performance can be measured and optimised. Chapters review optical and electron microscopy imaging techniques for dental biomaterial interfaces. Specific materials such as dental cements, fibre-reinforced composites, metals and alloys are discussed. There is an analysis of stresses, fracture, wear and ageing in dental biomaterials as well as an evaluation of the performance of dental adhesives and resin-dentin bonds. Chapters also review ways of assessing the performance of dental handpieces, crowns, implants and prosthesies. The book also reviews the use of computer models in such areas as bond strength and shape optimisation of dental restorations.With its distinguished editors and team of experienced contributors DDental Biomaterials: Imaging, Testing and Modelling researchers, materials scientists, engineers and dental practitioners with an essential guide to the use and performance of dental biomaterials. - An essential guide to the use and performance of dental biomaterials - Reviews optical and electron microscopy imaging techniques for dental biomaterial interfaces - Analyses stresses, fracture, wear and ageing in dental biomaterials and evaluates the performance of dental adhesives and resin-dentin bonds
A comprehensive perspective on Weibull models The literature on Weibull models is vast, disjointed, andscattered across many different journals. Weibull Models is acomprehensive guide that integrates all the different facets ofWeibull models in a single volume. This book will be of great help to practitioners in reliabilityand other disciplines in the context of modeling data sets usingWeibull models. For researchers interested in these modelingtechniques, exercises at the end of each chapter define potentialtopics for future research. Organized into seven distinct parts, Weibull Models: * Covers model analysis, parameter estimation, model validation,and application * Serves as both a handbook and a research monograph. As ahandbook, it classifies the different models and presents theirproperties. As a research monograph, it unifies the literature andpresents the results in an integrated manner * Intertwines theory and application * Focuses on model identification prior to model parameterestimation * Discusses the usefulness of the Weibull Probability plot (WPP)in the model selection to model a given data set * Highlights the use of Weibull models in reliability theory Filled with in-depth analysis, Weibull Models pulls together themost relevant information on this topic to give everyone fromreliability engineers to applied statisticians involved withreliability and survival analysis a clear look at what Weibullmodels can offer.
A completely revised and updated edition of a bestseller, Maintenance, Replacement, and Reliability: Theory and Applications, Second Edition supplies the tools needed for making data-driven physical asset management decisions. The well-received first edition quickly became a mainstay for professors, students, and professionals, with its clear presentation of concepts immediately applicable to real-life situations. However, research is ongoing and relentless—in only a few short years, much has changed. See What’s New in the Second Edition: New Topics The role of maintenance in sustainability issues PAS 55, a framework for optimizing management assets Data management issues, including cases where data are unavailable or sparse How candidates for component replacement can be prioritized using the Jack-knife diagram New Appendices Maximum Likelihood Estimated (MLE) Markov chains and knowledge elicitation procedures based on a Bayesian approach to parameter estimation E-learning materials now supplement two previous appendices (Statistics Primer and Weibull Analysis) Updated the appendix List of Applications of Maintenance Decision Optimization Models Firmly based on the results of real-world research in physical asset management, the book focuses on data-driven tools for asset management decisions. It provides a solid theoretical foundation for various tools (mathematical models) that, in turn, can be used to optimize a variety of key maintenance/replacement/reliability decisions. It presents cases that illustrate the application of these tools in a variety of settings, such as food processing, petrochemical, steel and pharmaceutical industries, as well as the military, mining, and transportation (land and air) sectors. Based on the authors’ experience, the second edition maintains the format that made the previous edition so popular. It covers theories and methodologies grounded in the real world. Simply stated, no other book available addresses the range of methodologies associated with, or focusing on, tools to ensure that asset management decisions are optimized over the product’s life cycle. And then presents them in an easily digestable and immediately applicable way.
Reliability, statistics, risk, safety, test substantiation, life estimates, cost, warranty analysis, life cycle costs.
This book provides engineers and scientists with a single source introduction to the concepts, models, and case studies for making credible reliability assessments. It satisfies the need for thorough discussions of several fundamental subjects. Section I contains a comprehensive overview of assessing and assuring reliability that is followed by discussions of: • Concept of randomness and its relationship to chaos • Uses and limitations of the binomial and Poisson distributions • Relationship of the chi-square method and Poisson curves • Derivations and applications of the exponential, Weibull, and lognormal models • Examination of the human mortality bathtub curve as a template for components Section II introduces the case study modeling of failure data and is followed by analyses of: • 5 sets of ideal Weibull, lognormal, and normal failure data • 83 sets of actual (real) failure data The intent of the modeling was to find the best descriptions of the failures using statistical life models, principally the Weibull, lognormal, and normal models, for characterizing the failure probability distributions of the times-, cycles-, and miles-to-failure during laboratory or field testing. The statistical model providing the preferred characterization was determined empirically by choosing the two-parameter model that gave the best straight-line fit in the failure probability plots using a combination of visual inspection and three statistical goodness-of-fit (GoF) tests. This book offers practical insight in dealing with single item reliability and illustrates the use of reliability methods to solve industry problems.
For practicing reliability engineers, a comprehensive guide to the Weibull distribution, which has wide applications to such tasks as troubleshooting, classifying failure types, and scheduling preventative maintenance and inspections. Describes parameter estimations, confidence intervals, goodness of fit, applications to multiple-censored data, and