Recent advances in science and technology have made modern computing and engineering systems more powerful and sophisticated than ever. The increasing complexity and scale imply that system reliability problems not only continue to be a challenge but also require more efficient models and solutions. This is the first book systematically covering the state-of-the-art binary decision diagrams and their extended models, which can provide efficient and exact solutions to reliability analysis of large and complex systems. The book provides both basic concepts and detailed algorithms for modelling and evaluating reliability of a wide range of complex systems, such as multi-state systems, phased-mission systems, fault-tolerant systems with imperfect fault coverage, systems with common-cause failures, systems with disjoint failures, and systems with functional dependent failures. These types of systems abound in safety-critical or mission-critical applications such as aerospace, circuits, power systems, medical systems, telecommunication systems, transmission systems, traffic light systems, data storage systems, and etc.
The book provides both small-scale illustrative examples and large-scale benchmark examples to demonstrate broad applications and advantages of different decision diagrams based methods for complex system reliability analysis. Other measures including component importance and failure frequency are also covered. A rich set of references is cited in the book, providing helpful resources for readers to pursue further research and study of the topics. The target audience of the book is reliability and safety engineers or researchers.
The book can serve as a textbook on system reliability analysis. It can also serve as a tutorial and reference book on decision diagrams, multi-state systems, phased-mission systems, and imperfect fault coverage models.
About the Author
Liudong Xing is a tenured professor in the Department of Electrical and Computer Engineering at the University of Massachusetts (UMass), Dartmouth. She received her PhD degree in Electrical Engineering from the University of Virginia, Charlottesville in 2002. Her current research focuses on reliability modelling and analysis of complex systems and networks. She has authored or co-authored over 190 technical papers. She is the recipient of the Leo M. Sullivan Teacher of the Year Award (2014), Scholar of the Year Award (2010), and Outstanding Women Award (2011) of UMass Dartmouth, as well as the IEEE Region 1 Technological Innovation (Academic) Award (2007). She is also the co-recipient of the Best Paper Award at the IEEE International Conference on Networking, Architecture, and Storage in 2009. She is a senior member of IEEE.
Suprasad V. Amari received the M.S. and Ph.D. degrees in Reliability Engineering from the Indian Institute of Technology, Kharagpur, India. He is a senior technical staff member at Relyence Corporation. Prior to joining Relyence, he has served as a Technical Fellow at Parametric Technology Corporation (PTC) for 14 years, where he was responsible for research, design, and development of PTC's reliability modeling and analysis software products. He has authored or coauthored 6 book chapters in Springer Handbooks and about 90 technical papers in the area of reliability engineering. He has been actively involved with Annual Reliability and Maintainability Symposium (RAMS) and currently serving as the Vice General Chair. He has received the 2013 RAMS Best Paper Award from American Society for Quality (ASQ) Reliability Division, the 2009 Stan Oftshun Award from the Society of Reliability Engineers (SRE) and the 2009 William A.J. Golomski Award from the Institute of Industrial Engineers (IIE). He is a senior member of ASQ, IEEE, and IIE. He is a member of ACM, SAE and SRE and an ASQ-certified Reliability Engineer.
Table of Contents
Preface xiiiNomenclature xix1 Introduction 11.1 Historical Developments 11.2 Reliability and Safety Applications 42 Basic Reliability Theory and Models 72.1 Probabiltiy Concepts 72.2 Reliability Measures 142.3 Fault Tree Analysis 173 Fundamentals of Binary Decision Diagrams 333.1 Preliminaries 343.2 Basic Concepts 343.3 BDD Construction 353.4 BDD Evaluation 423.5 BDD-Based Software Package 444 Application of BDD to Binary-State Systems 454.1 Network Reliability Analysis 454.2 Event Tree Analysis 474.3 Failure Frequency Analysis 504.4 Importance Measures and Analysis 544.5 Modularization Methods 604.6 Non-Coherent Systems 604.7 Disjoint Failures 654.8 Dependent Failures 685 Phased-Mission Systems 735.1 System Description 745.2 Rules of Phase Algebra 755.3 BDD-Based Method for PMS Analysis 765.4 Mission Performance Analysis 816 Multi-State Systems 856.1 Assumptions 866.2 An Illustrative Example 866.3 MSS Representation 876.4 Multi-State BDD (MBDD) 906.5 Logarithmically-Encoded BDD (LBDD) 946.6 Multi-State Multi-Valued Decision Diagrams (MMDD) 986.7 Performance Evaluation and Benchmarks 1026.8 Summary 1177 Fault Tolerant Systems and Coverage Models 1197.1 Basic Types 1207.2 Imperfect Coverage Model 1227.3 Applications to Binary-State Systems 1237.4 Applications to Multi-State Systems 1297.5 Applications to Phased-Mission Systems 1337.6 Summary 1398 Shared Decision Diagrams 1438.1 Multi-Rooted Decision Diagrams 1448.2 Multi-Terminal Decision Diagrams 1488.3 Performance Study on Multi-State Systems 1518.4 Application to Phased-Mission Systems 1638.5 Application to Multi-State k-out-of-n Systems 1688.6 Importance Measures 1768.7 Failure Frequency Based Measures 1808.8 Summary 183Conclusions 185References 187Index 205