Publisher's Synopsis
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.
In addition, this book provides a comprehensive introduction to load–strength interference models for reliability and risk analysis by introducing the overstress reliability integral: a generalisation of the load–strength interference integral with the time included. Furthermore, an efficient model for determining the probability of failure of loaded components and structures with internal flaws is also presented.
Reliability and Risk Models is essential reading for practising engineers, researchers and consultants dealing with reliability and risk assessment. Lecturers and graduate students involved in reliability engineering will also find it an excellent reference and it is a useful tool for actuaries, economists and lecturers in applied probability and statistics.
