Michael Todinov – Realiability & Risk Models
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Presenting a radically new approach and technology for setting reliability requirements, this superb book also provides the first comprehensive overview of the M/F-FOP philosophy and its applications. * Each chapter covers probabilistic models, statistical and numerical procedures, applications and/or case studies * Comprehensively examines a new methodology for problem solving in the context of real reliability engineering problems * All models have been implemented in C++ * The algorithms and programming code supplied can be used as a software toolbox for setting MFFOP * Case studies are taken from the nuclear, automotive and offshore industry to provide ‘real-world’ applications. Review “This well written book ranges widely over the field of reliability”. (Insight, March 2006) From the Back Cover An introduction to the MFFOP and cost-of-failure based approaches to reliability analysis and its applications. For many production systems it is important to guarantee a small risk of violating specified minimum failure-free operating periods before random failures. This is dictated by the high cost of failure and the intervention for repair. Reliability and Risk Models describes radically new approaches for setting quantitative reliability requirements based on the cost of failure and specified minimum failure-free operating periods (MFFOP). The cost-of-failure based reliability analysis provides a real alternative to the current reliability analysis disconnected from the cost of failure. Beginning with a comprehensive introduction to reliability and risk analysis based on random variables, this book:- Examines a new methodology for problem solving in the context of real reliability engineering problems.
- Demonstrates the new reliability methodology through a number of practical applications and case studies.
- Supplies the code of the algorithms which can be used for reliability analyses and setting quantitative reliability requirements.
- Gives a comprehensive overview of basic Monte Carlo simulation techniques and algorithms for solving reliability engineering problems.