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)
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1 Introduction
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2.5 Markov Process

As discussed in Section 2.3, the state space‐based methods belong to the analytical methods for system reliability analysis. Among the state space‐based methods, Markov models particularly, continuous‐time Markov chains (CTMCs) have commonly been applied to analyze reliability of systems with dynamic behavior and exponential component ttf distributions [7, 15 ].

Constructing a Markov model involves identifying system states and possible transitions among these states. In the Markov‐based system reliability analysis, each state typically denotes a distinct combination of failed and functioning components. A state transition governs the change of the system from one state to another state due to events such as failure of a component or repair of a component. Each state transition is characterized by certain parameter(s), such as a component's failure rate or repair rate [56]. The state transition diagram starts with an initial state ...