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.

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

The Birnbaum-Saunders Distribution presents the statistical theory, methodology, and applications of the Birnbaum-Saunders distribution, a very flexible distribution for modeling different types of data (mainly lifetime data). The book describes the most recent theoretical developments of this model, including properties, transformations and related distributions, lifetime analysis, and shape analysis. It discusses methods of inference based on uncensored and censored data, goodness-of-fit tests, and random number generation algorithms for the Birnbaum-Saunders distribution, also presenting existing and future applications. - Introduces inference in the Birnbaum-Saunders distribution - Provides a comprehensive review of the statistical theory and methodology of the Birnbaum-Distribution - Discusses different applications of the Birnbaum-Saunders distribution - Explains characterization and the lifetime analysis

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.

This book is devoted to the study of univariate distributions appropriate for the analyses of data known to be nonnegative. The book includes much material from reliability theory in engineering and survival analysis in medicine.