Binary Decision Diagrams and Extensions for System Reliability Analysis

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.

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.