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This book introduces the reliability modelling and optimization of warm standby systems. Warm standby is an attractive redundancy technique, as it consumes less energy than hot standby and switches into the active state faster than cold standby. Since a warm standby component experiences different failure rates in the standby state and active state, the reliability evaluation is challenging and the existing works are only restricted to very special cases. By adapting the decision diagrams, this book proposes the methodology to evaluate the reliability of different types of warm standby systems and studies the reliability optimization. Compared with existing works, the proposed methods allow the system to have an arbitrary number of components and allow the failure time distribution of components to observe arbitrary distributions. From this book, the readers can not only learn how to evaluate and optimize the reliability of warm standby systems but also use the methods to study the reliability of other complex systems.
This book introduces the reliability modelling and optimization of warm standby systems. Warm standby is an attractive redundancy technique, as it consumes less energy than hot standby and switches into the active state faster than cold standby. Since a warm standby component experiences different failure rates in the standby state and active state, the reliability evaluation is challenging and the existing works are only restricted to very special cases. By adapting the decision diagrams, this book proposes the methodology to evaluate the reliability of different types of warm standby systems and studies the reliability optimization. Compared with existing works, the proposed methods allow the system to have an arbitrary number of components and allow the failure time distribution of components to observe arbitrary distributions. From this book, the readers can not only learn how to evaluate and optimize the reliability of warm standby systems but also use the methods to study the reliability of other complex systems.
Reliability Assessment and Optimization of Complex Systems delves into a range of tools and techniques for designing optimized complex systems. Each chapter explores system modeling and the implementation of various metaheuristics for optimization purposes. This book provides readers in the domain of applied mathematics with a comprehensive understanding of system reliability analysis and improvement, thereby offering substantial value to their knowledge and expertise. System reliability has become the paramount attribute of any production unit. The process of maximizing system reliability while adhering to multiple constraints is referred to as reliability optimization.There are two primary approaches to enhancing a system's performance and reliability: developing a product with reduced failures (failure avoidance) or incorporating resilience to ensure the system continues functioning even in the event of a failure (fault tolerance). - Explains the process and application of reliability-based design optimization - Covers many metaheuristic approaches such as reliability, cost, and the MTTF of the system - Provides the workings and applications of multi-objective optimizations
This book presents the latest key research into the performance and reliability aspects of dependable fault-tolerant systems and features commentary on the fields studied by Prof. Kishor S. Trivedi during his distinguished career. Analyzing system evaluation as a fundamental tenet in the design of modern systems, this book uses performance and dependability as common measures and covers novel ideas, methods, algorithms, techniques, and tools for the in-depth study of the performance and reliability aspects of dependable fault-tolerant systems. It identifies the current challenges that designers and practitioners must face in order to ensure the reliability, availability, and performance of systems, with special focus on their dynamic behaviors and dependencies, and provides system researchers, performance analysts, and practitioners with the tools to address these challenges in their work. With contributions from Prof. Trivedi's former PhD students and collaborators, many of whom are internationally recognized experts, to honor him on the occasion of his 70th birthday, this book serves as a valuable resource for all engineering disciplines, including electrical, computer, civil, mechanical, and industrial engineering as well as production and manufacturing.
In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved. The handbook will be essential reading for all engineers and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness.
Computing systems are of growing importance because of their wide use in many areas including those in safety-critical systems. This book describes the basic models and approaches to the reliability analysis of such systems. An extensive review is provided and models are categorized into different types. Some Markov models are extended to the analysis of some specific computing systems such as combined software and hardware, imperfect debugging processes, failure correlation, multi-state systems, heterogeneous subsystems, etc. One of the aims of the presentation is that based on the sound analysis and simplicity of the approaches, the use of Markov models can be better implemented in the computing system reliability.
This book provides different approaches used to analyze, draw attention, and provide an understanding of the advancements in the optimization field across the globe. It brings all of the latest methodologies, tools, and techniques related to optimization and industrial engineering into a single volume to build insights towards the latest advancements in various domains. Applications of Advanced Optimization Techniques in Industrial Engineering includes the basic concept of optimization, techniques, and applications related to industrial engineering. Concepts are introduced in a sequential way along with explanations, illustrations, and solved examples. The book goes on to explore applications of operations research and covers empirical properties of a variety of engineering disciplines. It presents network scheduling, production planning, industrial and manufacturing system issues, and their implications in the real world. The book caters to academicians, researchers, professionals in inventory analytics, business analytics, investment managers, finance firms, storage-related managers, and engineers working in engineering industries and data management fields.
This book is a collective work by many leading scientists, analysts, mathematicians, and engineers who have been working at the front end of reliability science and engineering. The book covers conventional and contemporary topics in reliability science, all of which have seen extended research activities in recent years. The methods presented in this book are real-world examples that demonstrate improvements in essential reliability and availability for industrial equipment such as medical magnetic resonance imaging, power systems, traction drives for a search and rescue helicopter, and air conditioning systems. The book presents real case studies of redundant multi-state air conditioning systems for chemical laboratories and covers assessments of reliability and fault tolerance and availability calculations. Conventional and contemporary topics in reliability engineering are discussed, including degradation, networks, dynamic reliability, resilience, and multi-state systems, all of which are relatively new topics to the field. The book is aimed at engineers and scientists, as well as postgraduate students involved in reliability design, analysis, experiments, and applied probability and statistics.