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Comprehensive coverage of system reliability evaluation and optimal systems design
Optimal Reliability Modeling presents a complete volume of information and strategies for determining the most effective ways to make systems meet all necessary performance requirements, while considering schedule, cost, and feasibility. This practical book interprets, evaluates, and provides examples of all reliability systems in both binary and multistate contexts, including parallel, series, standby, k-out-of-n and consecutive-k-out-of-n, and general system models, as well as providing detailed explanations of system design to better diagnose, maintain, and improve existing systems.
Vital topics that make Optimal Reliability Modeling a powerful hands-on tool include:
* Complexity analysis-for background knowledge on efficiency comparisons of system reliability evaluation algorithms
* The Markov chain imbeddable structure-an effective tool for system reliability analysis
* Majorization-a powerful tool for the development of invariant optimal designs for some system structures
* The multistate system reliability theory-systematically introduced for the first time in a text on engineering system reliability analysis
* The latest k-out-of-n and consecutive-k-out-of-n system models-includes physical explanations and various applications
Optimal Reliability Modeling is the ideal book on system reliability for statisticians; industrial, electrical, computer, and mechanical engineers; and researchers and students.
WAY KUO, PHD, is holder of the Wisenbaker Chair of Engineering in Innovation at Texas A&M University and Editor of IEEE Transactions on Reliability.
MING J. ZUO, PHD, is Professor of Industrial Engineering in the Department of Mechanical Engineering at the University of Alberta in Canada.
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