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Reliability and Availability Engineering: Modeling, Analysis, and Applications

Reliability and Availability Engineering: Modeling, Analysis, and Applications

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Kishor S. Trivedi, Andrea Bobbio
Cambridge University Press, 8/3/2017
EAN 9781107099500, ISBN10: 1107099501

Hardcover, 726 pages, 25.4 x 18 x 3.6 cm
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.

Part I. Introduction
1. Introduction
2. Dependability evaluation
3. Dependability metrics defined on a single unit
Part II. Non-State-Space Models (Combinatorial Models)
4. Reliability block diagram
5. Network reliability
6. Fault tree analysis
7. State enumeration
8. Dynamic redundancy
Part III. State-Space Models with Exponential Distributions
9. Continuous time Markov chain
availability models
10. Continuous time Markov chain
reliability models
11. Continuous time Markov chain
queueing systems
12. Petri nets
Part IV. State-Space Models with Non-Exponential Distributions
13. Non-homogeneous CTMC
14. Semi-Markov and Markov regenerative models
15. Phase type expansion
Part V. Multi-Level Models
16. Hierarchical models
17. Fixed-point iteration
Part VI. Case Studies
18. Case studies.