Reliability and Availability Engineering

Modeling, Analysis, and Applications

Nonfiction, Science & Nature, Technology, Engineering, Computers, General Computing
Cover of the book Reliability and Availability Engineering by Kishor S. Trivedi, Andrea Bobbio, Cambridge University Press
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Author: Kishor S. Trivedi, Andrea Bobbio ISBN: 9781108506021
Publisher: Cambridge University Press Publication: August 3, 2017
Imprint: Cambridge University Press Language: English
Author: Kishor S. Trivedi, Andrea Bobbio
ISBN: 9781108506021
Publisher: Cambridge University Press
Publication: August 3, 2017
Imprint: Cambridge University Press
Language: English

Do you need to know what technique to use to evaluate the reliability of an engineered system? This self-contained guide provides comprehensive coverage of all the analytical and modeling techniques currently in use, from classical non-state and state space approaches, to newer and more advanced methods such as binary decision diagrams, dynamic fault trees, Bayesian belief networks, stochastic Petri nets, non-homogeneous Markov chains, semi-Markov processes, and phase type expansions. Readers will quickly understand the relative pros and cons of each technique, as well as how to combine different models together to address complex, real-world modeling scenarios. Numerous examples, case studies and problems provided throughout help readers put knowledge into practice, and a solutions manual and Powerpoint slides for instructors accompany the book online. This is the ideal self-study guide for students, researchers and practitioners in engineering and computer science.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Do you need to know what technique to use to evaluate the reliability of an engineered system? This self-contained guide provides comprehensive coverage of all the analytical and modeling techniques currently in use, from classical non-state and state space approaches, to newer and more advanced methods such as binary decision diagrams, dynamic fault trees, Bayesian belief networks, stochastic Petri nets, non-homogeneous Markov chains, semi-Markov processes, and phase type expansions. Readers will quickly understand the relative pros and cons of each technique, as well as how to combine different models together to address complex, real-world modeling scenarios. Numerous examples, case studies and problems provided throughout help readers put knowledge into practice, and a solutions manual and Powerpoint slides for instructors accompany the book online. This is the ideal self-study guide for students, researchers and practitioners in engineering and computer science.

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