Springer Modern Dynamic Reliability Analysis for Multi-state Systems: Stochastic Processes and the Lz-Transform (Springer Series in Reliability Engineering)

This book discusses recent developments in dynamic reliability in multi-state systems (MSS), addressing such important issues as reliability and availability analysis of aging MSS, the impact of initial conditions on MSS reliability and availability, changing importance of components over time in MSS with aging components, and the determination of age-replacement policies. It also describes modifications of traditional methods, such as Markov processes with rewards, as well as a modern mathematical method based on the extended universal generating function technique, the Lz-transform, presenting various successful applications and demonstrating their use in real-world problems. This book provides theoretical insights, information on practical applications, and real-world case studies that are of interest to engineers and industrial managers as well as researchers. It also serves as a textbook or supporting text for graduate and postgraduate courses in industrial, electrical, and mechanical engineering. From the Back Cover This book discusses recent developments in dynamic reliability in multi-state systems (MSS), addressing such important issues as reliability and availability analysis of aging MSS, the impact of initial conditions on MSS reliability and availability, changing importance of components over time in MSS with aging components, and the determination of age-replacement policies. It also describes modifications of traditional methods, such as Markov processes with rewards, as well as a modern mathematical method based on the extended universal generating function technique, the Lz-transform, presenting various successful applications and demonstrating their use in real-world problems. This book provides theoretical insights, information on practical applications, and real-world case studies that are of interest to engineers and industrial managers as well as researchers. It also serves as a textbook or supporting text for graduate and postgraduate courses in industrial, electrical, and mechanical engineering. About the Author Dr. Anatoly Lisnianski is a Senior Engineering Expert at the Reliability Department of the Israel Electric Corporation Ltd., Israel, and Scientific Supervisor of the Centre for Reliability and Risk Management at the SCE – Shamoon College of Engineering, Beer Sheva, Israel.  He holds a M.Sc. degree in Electrical Engineering from the University of Information Technology, Mechanics and Optics, St. Petersburg, Russia, and a Ph.D. degree in Reliability from the Federal Scientific & Production Centre “Aurora” in Sankt Petersburg, Russia, and was a Senior Researcher there from 1975 to 1989. In 1991 he began working in the Reliability department of the Israel Electric Corporation. He is the author and a co-author of more than 200 research papers, four books, several book’s chapters and inventions in the field of reliability and applied statistics. He is a senior member of IEEE and a member of the Israel Statistical Association. Dr. Ilia Frenkel is the researcher of the Centre for Reliability and Risk Management of the SCE – Shamoon College of Engineering, Beer Sheva, Israel. He holds a M.Sc. degree in Applied Mathematics from Voronezh State University, Russia, and a Ph.D. degree in Operational Research and Computer Science from the Institute of Economy, Ukrainian Academy of Science, formerly USSR. He has more than 40 years of academic experience, teaching at various universities and institutions in Russia and Israel. From 1988 to 1991, he worked as the Department Chair and an Associate Professor at the Applied Mathematics and Computers Department, Volgograd Civil Engineering Institute, Russia. He specializes in applied statistics and reliability with applications to preventive maintenance. He is the author and a co-author of more than 50 research papers, 3 books, and several book’s chapters in the fields of reliability, applied statistics, and produc