Book Image

Dynamic System Reliability

By : Liudong Xing, Gregory Levitin, Chaonan Wang
Book Image

Dynamic System Reliability

By: Liudong Xing, Gregory Levitin, Chaonan Wang

Overview of this book

This book focuses on hot issues of dynamic system reliability, systematically introducing the reliability modeling and analysis methods for systems with imperfect fault coverage, systems with function dependence, systems subject to deterministic or probabilistic common-cause failures, systems subject to deterministic or probabilistic competing failures, and dynamic standby sparing systems. It presents recent developments of such extensions involving reliability modeling theory, reliability evaluation methods, and features numerous case studies based on real-world examples. The presented dynamic reliability theory can enable a more accurate representation of actual complex system behavior, thus more effectively guiding the reliable design of real-world critical systems. The book begins by describing the evolution from the traditional static reliability theory to the dynamic system reliability theory and provides a detailed investigation of dynamic and dependent behaviors in subsequent chapters. Although written for those with a background in basic probability theory and stochastic processes, the book includes a chapter reviewing the fundamentals that readers need to know in order to understand the contents of other chapters that cover advanced topics in reliability theory and case studies.
Table of Contents (14 chapters)
Free Chapter
1 Introduction
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2.4 Binary Decision Diagram

In 1959, BDDs were first introduced by Lee to represent switching circuits [36]. In 1986, Bryant investigated the full potential for efficient BDD‐based algorithms [37]. Since then, BDD and their extended forms have been applied to diverse application domains [3848]. In 1993, BDDs were first adapted to the FT reliability analysis of binary‐state systems [ 4 , 10 ,11]. It has been shown by numerous studies that in most cases, the BDD‐based methods require less computational time and memory than other FT reliability analysis methods (e.g. cutsets, pathsets‐based inclusion-exclusion (I‐E) or sum of disjoint products (SDP) methods, and Markov‐based methods). Recently, BDDs and their extended forms have become the state‐of‐the‐art combinatorial models for efficient reliability analysis of diverse types of complex systems. Refer to [49] for a comprehensive discussion of BDD and their extended...