Über den Autor
Anatoly Lisnianski is the author and co-author of more than 80 scientific papers, one book and 3 book chapters. He has more than 30 years of experience in the fields of reliability, maintainability and risk analysis, both in industry and academia. Dr Lisnianski received his MSc degree in Electrical Engineering from the State University of Information Technology, Precision Mechanics and Optics, Sankt-Petersburg, Russia, in 1975 and his PhD degree in Reliability from the Federal Scientific & Production Centre "Aurora" in Sankt-Petersburg, Russia, where he was working from 1975 till 1989. Since 1991 he has been an expert engineer in the Planning, Development & Technology Division, Reliability Department, of The Israel Electric Corporation Ltd. He is also a scientific supervisor of the Centre for Reliability and Risk Management in the Sami Shamoon College of Engineering, Beer Sheva, Israel and senior lecturer at Haifa University.Ilia Frenkel is the author and co-author of more than 30 scientific publications. He has more than 35 years of experience in academia and industry in the fields of operational research, reliability and statistical quality control. Dr Frenkel received his MSc degree in Applied Mathematics from Voronezh State University, Russia, and his PhD degree in Operational Research and Computer Science, Institute of Economy, Ukrainian Academy of Science, formerly USSR. From 1988 till 1991 he was Department Chair and Associate Professor in the Applied Mathematics and Computers Department in the Volgograd Civil Engineering Institute, Russia. Now he is senior lecturer and director of the Centre for Reliability and Risk Management in the Sami Shamoon College of Engineering, Beer Sheva, Israel. He is a member of the editorial boards of scientific and professional journals.Yi Ding received his BEng from Shanghai Jiaotong University, China, and his PhD from Nanyang Technological University, Singapore, both in Electrical Engineering. From 2005 to 2006, he worked as a post-doctoral research fellow in the Centre for Reliability and Risk Management of SCE - Shamoon College of Engineering, Beer Sheva, Israel. From 2007 to 2008, he was a postdoctoral research fellow in the University of Alberta, Canada. Currently, he is a member of the academic staff at Nanyang Technological University. His research interests include: electric power systems reliability and security; restructured power systems management and policy; engineering systems reliability; and evolutionary programming and fuzzy modeling. His research papers have been published in several international journals, such as: IEEE Trans. on Power Systems, Fuzzy Sets & Systems, Reliability Engineering & System Safety, and IEE Proc.-Gener. Transm. Distrib.
Multi-state Systems in Nature and Engineering
Modern Stochastic Process Methods for MSS Reliability Assessment
Statistical Analysis of Reliability Data for Real-world MSS's
Universal Generating Function (UGF) Models
Combined UGF and Stochastic Process Technique
Aging Multi-state Systems
Reliability Associated Costs for MSS and Optimal Management Decisions
Fuzzy Multi-state System
Multi-state System Reliability Analysis and Optimization for Engineers and Industrial Managers presents a comprehensive, up-to-date description of multi-state system (MSS) reliability as a natural extension of classical binary-state reliability. It presents all essential theoretical achievements in the field, but is also practically oriented.
New theoretical issues are described, including:
. combined Markov and semi-Markov processes methods, and universal generating function techniques;
. statistical data processing for MSSs;
. reliability analysis of aging MSSs;
. methods for cost-reliability and cost-availability analysis of MSSs; and
. main definitions and concepts of fuzzy MSS.
Multi-state System Reliability Analysis and Optimization for Engineers and Industrial Managers also discusses life cycle cost analysis and practical optimal decision making for real world MSSs. Numerous examples are included in each section in order to illustrate mathematical tools. Besides these examples, real world MSSs (such as power generating and transmission systems, air-conditioning systems, production systems, etc.) are considered as case studies.
Multi-state System Reliability Analysis and Optimization for Engineers and Industrial Managers also describes basic concepts of MSS, MSS reliability measures and tools for MSS reliability assessment and optimization. It is a self-contained study resource and does not require prior knowledge from its readers, making the book attractive for researchers as well as for practical engineers and industrial managers.
Presents a comprehensive, up-to-date description of Multi-state System (MSS) reliability
Written by experts
With numerous illustrations