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.

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.

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 compact and easy-to-understand text presents the underlying principles and practice of reliability engineering and life testing. It describes the various techniques available for reliability analysis and prediction and explains the statistical methods necessary for reliability modelling, analysis and estimation. The text also discusses in detail the concepts of life testing, its classification and methodologies as well as accelerated life tests, the methodologies and models of stress related failure rates evaluation, and data analysis. Besides, it elaborates on the principles, methods and equipment of highly accelerated life testing and highly accelerated stress screening. Finally, the book concludes with a discussion on the parametric as well as non-parametric methods generally used for reliability estimation, and the recent developments in life testing of engineering components. Key Features The book is up-to-date and very much relevant to the present industrial, research, design, and development scenarios. Provides adequate tools to predict the system reliability at the design stage, to plan and conduct life testing on the products at various stages of development, and to use the life test and field data to estimate the product reliability. Gives sufficiently large number of worked-out examples. Primarily intended as a textbook for the postgraduate students of engineering (M.Tech., Reliability Engineering), the book would also be quite useful for reliability practitioners, professional engineers, and researchers.

Includes the binomial tests of comparison and information on Accept-Reject Tests, the Sequential Probability Ratio Test, Bayesian MTBF and Reliability Demonstration Tests, as well as other important accelerated tests such as Arrhenius, Eyriing, Bazovsky, and Inverse Power Law.

Degradation, the chemical/physical response of building and con struction materials exposed to in-service environments, must be predicted prior to their installation in structures if materials are to be effectively selected, used and maintained. These assessments of materials degradation require that methods be available to aid prediction of service life. The objectives of building materials science are a) to charac terize and categorize materials, b) to predict, preferably in a mathematical sense, material or component response including expected service life, and c) to make improvements in material response through improvements in design, formulation, processing or specification. For building and construction materials, continued progress has been made towards objective (a), but little progress has been made towards objectives (b) and (c). Of these, the mathematical prediction of service life appears to be of greater importance, because, if general approaches or models having application to a wide range of building and construction materials can be identi fied, then the categorization, selection, use and improvement of materials can proceed in a systematic manner. Researchers in advanced technologies, such as aerospace, nuclear, electronics and medicine, have apparently been more successful than researchers in building and construction technology in responding to the need for reliable predictions of service life.

The ability to successfully predict industrial product performance during service life provides benefits for producers and users. This book addresses methods to improve product quality, reliability, and durability during the product life cycle, along with methods to avoid costs that can negatively impact profitability plans. The methods presented can be applied to reducing risk in the research and design processes and integration with manufacturing methods to successfully predict product performance. This approach incorporates components that are based on simulations in the laboratory. The results are combined with in-field testing to determine degradation parameters. These approaches result in improvements to product quality, performance, safety, profitability, and customer satisfaction. Among the methods of analyses included are: • Accelerated Reliability Testing (ART) • Accelerated Durability Testing (ADT) • system variability / input variability • engineering risk versus time and expense