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.

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.

Drawing of real-world issues and with supporting data from industry, this book overviews the technique and equipment available to engineers and scientists to identify the solutions of the physical essence of engineering problems in simulation, accelerated testing, prediction, quality improvement, and risk during the design, manufacturing, and maintenance stages. For this goal the book integrates Quality Improvement and Accelerated Reliability/ Durability/ Maintainability/Test Engineering concepts. Accelerated Quality and Reliability Solutions includes new and unpublished aspects in quality: - complex analysis of factors that influence product quality, and other quality development and improvement problems during design and manufacturing ; in simulation: - the strategy for development of accurate physical simulation of field input influences on the actual product – a system of control for physical simulation of the random input influences – a methodology for selecting a representative input region for accurate simulation of the field conditions; in testing: - useful accelerated reliability testing (UART) – accelerated multiple environmental testing technology – trends in development of UART technology; in studying climate and reliability; in prediction: - accurate prediction (AP) of reliability, durability, and maintainability - criteria of AP - development of techniques, etc.. The book includes new and effective aspects integration of quality, reliability, and maintainability. Other key features: - Includes aspects of quality integrated with reliability which can help to solve earlier inaccessible problems during design, manufacturing, and usage - Develops a new approach to improving the engineering culture for solving quality and reliability problems. - Enables the accurate prediction of quality, reliability, durability, and maintainability - Proposes strategies for accelerated quality, reliability, durability, and maintainability improvement and development - Combines new techniques with equipment for accurate physical simulation of field situation (mechanical, electrical, multi-environmental, and other influences, as well as human and other factors) for development accelerated testing (including reliability testing) and research - Overviews the latest techniques in physical simulation; accelerated testing; prediction of reliability, durability, and maintainability; quality development and improvement; safety aspects of risk assessment, especially for transportation - Supported by real life examples and industry data - Deals with the latest techniques in physical simulation, accelerated testing, prediction of reliability, durability, maintainability, quality development and safety aspects of risk assessment - Provides step-by-step guidance on the accurate prediction of quality factors, the physical simulation of field situations and of accelerated reliability testing - Dramatically reduces recalls by solving product improvement problems through the integration of quality development with reliability

A high percentage of defense systems fail to meet their reliability requirements. This is a serious problem for the U.S. Department of Defense (DOD), as well as the nation. Those systems are not only less likely to successfully carry out their intended missions, but they also could endanger the lives of the operators. Furthermore, reliability failures discovered after deployment can result in costly and strategic delays and the need for expensive redesign, which often limits the tactical situations in which the system can be used. Finally, systems that fail to meet their reliability requirements are much more likely to need additional scheduled and unscheduled maintenance and to need more spare parts and possibly replacement systems, all of which can substantially increase the life-cycle costs of a system. Beginning in 2008, DOD undertook a concerted effort to raise the priority of reliability through greater use of design for reliability techniques, reliability growth testing, and formal reliability growth modeling, by both the contractors and DOD units. To this end, handbooks, guidances, and formal memoranda were revised or newly issued to reduce the frequency of reliability deficiencies for defense systems in operational testing and the effects of those deficiencies. "Reliability Growth" evaluates these recent changes and, more generally, assesses how current DOD principles and practices could be modified to increase the likelihood that defense systems will satisfy their reliability requirements. This report examines changes to the reliability requirements for proposed systems; defines modern design and testing for reliability; discusses the contractor's role in reliability testing; and summarizes the current state of formal reliability growth modeling. The recommendations of "Reliability Growth" will improve the reliability of defense systems and protect the health of the valuable personnel who operate them.

Recent Advances in Reliability and Maintenance Modeling contains the papers presented at the 11th Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM 2024, Nagoya, Japan, 26-30 August 2024). The contributions discuss and explore solutions to the various reliability challenges facing society. Reliability and maintenance is the technology required in various fields such as (but not limited to): - Power systems - Communication networks - Transportation - Cloud computing - Electronic systems - Buildings and infrastructure - Medical and healthcare - Aviation and railway systems. Recent Advances in Reliability and Maintenance Modeling is of interest to academics and professionals interested or involved in the above mentioned areas.

Recent Advances in System Reliability discusses developments in modern reliability theory such as signatures, multi-state systems and statistical inference. It describes the latest achievements in these fields, and covers the application of these achievements to reliability engineering practice. The chapters cover a wide range of new theoretical subjects and have been written by leading experts in reliability theory and its applications. The topics include: concepts and different definitions of signatures (D-spectra), their properties and applications to reliability of coherent systems and network-type structures; Lz-transform of Markov stochastic process and its application to multi-state system reliability analysis; methods for cost-reliability and cost-availability analysis of multi-state systems; optimal replacement and protection strategy; and statistical inference. Recent Advances in System Reliability presents many examples to illustrate the theoretical results. Real world multi-state systems, such as power generation and transmission, refrigeration, and production systems, are considered in the form of case studies, making the book a useful resource for researchers and postgraduate students.

This book focuses on the statistical aspects of the analysis of degradation data. In recent years, degradation data analysis has come to play an increasingly important role in different disciplines such as reliability, public health sciences, and finance. For example, information on products’ reliability can be obtained by analyzing degradation data. In addition, statistical modeling and inference techniques have been developed on the basis of different degradation measures. The book brings together experts engaged in statistical modeling and inference, presenting and discussing important recent advances in degradation data analysis and related applications. The topics covered are timely and have considerable potential to impact both statistics and reliability engineering.