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.

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.

Traditionally, the way to test a product's reliability was to build it--and then try to break it. As systems and technologies improved, TAAF (Test, Analyze and Fix) methodologies were developed and adopted. In today's global economy, with its short, technologically-intense product life cycles, TAAF cannot suffice. Reliability can no longer be a step or a series of steps in product development; it is something that needs to be acknowledged up front and built into the product from its very conception. Reliability, in other words, must be 'designed in.' Product developers now have many tools--software and hardware--at their disposal for building reliability in from the get go. From the organizational point of view, what better way to design in reliability than to make designers themselves responsible for the reliability of their designs? As "Mike Silverman" explains in "How Reliable is Your Product?," this is why the role of the reliability engineer is changing to one of mentor. Product developers are now responsible for going out and finding the best testing tools and then training the designers on their use, so that designers factor and build in reliability at every stage of product design. Mike has focused on reliability throughout his 25-year career, and has observed the position of reliability in the organization evolve. In this book, he condenses his expertise and experience into a volume of immense practical worth to the engineering and engineering management communities including designers, manufacturing engineers and reliability/quality engineers. Among other things, Mike discusses how reliability fits, or should fit, within the product design cycle. He provides a high-level overview of reliability techniques available to engineers today. He lucidly discusses the design of experiments and the role of failure management. With case studies and narratives from personal experience, Mike discusses optimal ways to utilize different reliability techniques. He highlights common errors of judgment, missteps and sub-optimal decisions that are often made within organizations on the path to total reliability. With"How Reliable is Your Product?" "Mike Silverman" has delivered what few have done before--a comprehensive yet succinct overview of the field of reliability engineering and testing. Engineers and engineering managers will find much in this book of immediate, practical value.

This unique volume presents chapters written on the areas of life-testing and reliability by many well-known researchers who have contributed significantly to these two areas over the years. Chapters cover a wide range of topics such as inference under censoring and truncation, reliability growth models, designs to improve quality, prediction techniques, Bayesian analysis of reliability, multivariate methods, accelerated testing, and more. The book is written in an easy-to-follow style, first presenting the necessary theoretical details and then illustrating the methods with a numerical examples wherever possible. Many tables and graphs that are essential for the use of some of the new methodologies are presented throughout the volume. Numerous examples provide the reader with a clear understanding of the methods presented as well as with insight into the applications of these results.

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.

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