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.
"Reliability Physics and Engineering" provides critically important information for designing and building reliable cost-effective products. The textbook contains numerous example problems with solutions. Included at the end of each chapter are exercise problems and answers. "Reliability Physics and Engineering" is a useful resource for students, engineers, and materials scientists.
Dependability and cost effectiveness are primarily seen as instruments for conducting international trade in the free market environment. These factors cannot be considered in isolation of each other. This handbook considers all aspects of performability engineering. The book provides a holistic view of the entire life cycle of activities of the product, along with the associated cost of environmental preservation at each stage, while maximizing the performance.
This complete resource on the theory and applications of reliability engineering, probabilistic models and risk analysis consolidates all the latest research, presenting the most up-to-date developments in this field. With comprehensive coverage of the theoretical and practical issues of both classic and modern topics, it also provides a unique commemoration to the centennial of the birth of Boris Gnedenko, one of the most prominent reliability scientists of the twentieth century. Key features include: expert treatment of probabilistic models and statistical inference from leading scientists, researchers and practitioners in their respective reliability fields detailed coverage of multi-state system reliability, maintenance models, statistical inference in reliability, systemability, physics of failures and reliability demonstration many examples and engineering case studies to illustrate the theoretical results and their practical applications in industry Applied Reliability Engineering and Risk Analysis is one of the first works to treat the important areas of degradation analysis, multi-state system reliability, networks and large-scale systems in one comprehensive volume. It is an essential reference for engineers and scientists involved in reliability analysis, applied probability and statistics, reliability engineering and maintenance, logistics, and quality control. It is also a useful resource for graduate students specialising in reliability analysis and applied probability and statistics. Dedicated to the Centennial of the birth of Boris Gnedenko, renowned Russian mathematician and reliability theorist
Failure of components or systems must be prevented by both designers and operators of systems, but knowledge of the underlying mechanisms is often lacking. Since the relation between the expected usage of a system and its failure behavior is unknown, unexpected failures often occur, with possibly serious financial and safety consequences. Principles of Loads and Failure Mechanisms. Applications in Maintenance, Reliability and Design provides a complete overview of all relevant failure mechanisms, ranging from mechanical failures like fatigue and creep to corrosion and electric failures. Both qualitative and quantitative descriptions of the mechanisms and their governing loads enable a solid assessment of a system’s reliability in a given or assumed operational context. Moreover, a unique range of applications of this knowledge in the fields of maintenance, reliability and design are presented. The benefits of understanding the physics of failure are demonstrated for subjects like condition monitoring, predictive maintenance, prognostics and health management, failure analysis and reliability engineering. Finally, the role of these mechanisms in design processes and design for maintenance are illustrated.
This book considers all aspects of performability engineering, providing a holistic view of the activities associated with a product throughout its entire life cycle of the product, as well as the cost of minimizing the environmental impact at each stage, while maximizing the performance. Building on the editor's previous Handbook of Performability Engineering, it explains how performability engineering provides us with a framework to consider both dependability and sustainability in the optimal design of products, systems and services, and explores the role of performability in energy and waste minimization, raw material selection, increased production volume, and many other areas of engineering and production. The book discusses a range of new ideas, concepts, disciplines, and applications in performability, including smart manufacturing and Industry 4.0; cyber-physical systems and artificial intelligence; digital transformation of railways; and asset management. Given its broad scope, it will appeal to researchers, academics, industrial practitioners and postgraduate students involved in manufacturing, engineering, and system and product development.
“Failure Rate Modeling for Reliability and Risk” focuses on reliability theory, and to the failure rate (hazard rate, force of mortality) modeling and its generalizations to systems operating in a random environment and to repairable systems. The failure rate is one of the crucial probabilistic characteristics for a number of disciplines; including reliability, survival analysis, risk analysis and demography. The book presents a systematic study of the failure rate and related indices, and covers a number of important applications where the failure rate plays the major role. Applications in engineering systems are studied, together with some actuarial, biological and demographic examples. The book provides a survey of this broad and interdisciplinary subject which will be invaluable to researchers and advanced students in reliability engineering and applied statistics, as well as to demographers, econometricians, actuaries and many other mathematically oriented researchers.
Failure analysis is the preferred method to investigate product or process reliability and to ensure optimum performance of electrical components and systems. The physics-of-failure approach is the only internationally accepted solution for continuously improving the reliability of materials, devices and processes. The models have been developed from the physical and chemical phenomena that are responsible for degradation or failure of electronic components and materials and now replace popular distribution models for failure mechanisms such as Weibull or lognormal. Reliability engineers need practical orientation around the complex procedures involved in failure analysis. This guide acts as a tool for all advanced techniques, their benefits and vital aspects of their use in a reliability programme. Using twelve complex case studies, the authors explain why failure analysis should be used with electronic components, when implementation is appropriate and methods for its successful use. Inside you will find detailed coverage on: a synergistic approach to failure modes and mechanisms, along with reliability physics and the failure analysis of materials, emphasizing the vital importance of cooperation between a product development team involved the reasons why failure analysis is an important tool for improving yield and reliability by corrective actions the design stage, highlighting the ‘concurrent engineering' approach and DfR (Design for Reliability) failure analysis during fabrication, covering reliability monitoring, process monitors and package reliability reliability resting after fabrication, including reliability assessment at this stage and corrective actions a large variety of methods, such as electrical methods, thermal methods, optical methods, electron microscopy, mechanical methods, X-Ray methods, spectroscopic, acoustical, and laser methods new challenges in reliability testing, such as its use in microsystems and nanostructures This practical yet comprehensive reference is useful for manufacturers and engineers involved in the design, fabrication and testing of electronic components, devices, ICs and electronic systems, as well as for users of components in complex systems wanting to discover the roots of the reliability flaws for their products.
Complex high-technology devices are in growing use in industry, service sectors, and everyday life. Their reliability and maintenance is of utmost importance in view of their cost and critical functions. This book focuses on this theme and is intended to serve as a graduate-level textbook and reference book for scientists and academics in the field. The chapters are grouped into five complementary parts that cover the most important aspects of reliability and maintenance: stochastic models of reliability and maintenance, decision models involving optimal replacement and repair, stochastic methods in software engineering, computational methods and simulation, and maintenance management systems. This wide range of topics provides the reader with a complete picture in a self-contained volume.
Maintenance combines various methods, tools, and techniques in a bid to reduce maintenance costs while increasing the reliability, availability, and security of equipment. Condition-based maintenance (CBM) is one such method, and prognostics forms a key element of a CBM program based on mathematical models for predicting remaining useful life (RUL). Prognostics and Remaining Useful Life (RUL) Estimation: Predicting with Confidence compares the techniques and models used to estimate the RUL of different assets, including a review of the relevant literature on prognostic techniques and their use in the industrial field. This book describes different approaches and prognosis methods for different assets backed up by appropriate case studies. FEATURES Presents a compendium of RUL estimation methods and technologies used in predictive maintenance Describes different approaches and prognosis methods for different assets Includes a comprehensive compilation of methods from model-based and data-driven to hybrid Discusses the benchmarking of RUL estimation methods according to accuracy and uncertainty, depending on the target application, the type of asset, and the forecast performance expected Contains a toolset of methods and a way of deployment aimed at a versatile audience This book is aimed at professionals, senior undergraduates, and graduate students in all interdisciplinary engineering streams that focus on prognosis and maintenance.
