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    COMPUTATIONAL METHODS FOR RELIABILITY AND RISK ANALYSIS

    by Enrico Zio (Polytechnic of Milan, Italy)

    This book illustrates a number of modelling and computational techniques for addressing relevant issues in reliability and risk analysis. In particular, it provides: i) a basic illustration of some methods used in reliability and risk analysis for modelling the stochastic failure and repair behaviour of systems, e.g. the Markov and Monte Carlo simulation methods; ii) an introduction to Genetic Algorithms, tailored to their application for RAMS (Reliability, Availability, Maintainability and Safety) optimization; iii) an introduction to key issues of system reliability and risk analysis, like dependent failures and importance measures; and iv) a presentation of the issue of uncertainty and of the techniques of sensitivity and uncertainty analysis used in support of reliability and risk analysis.

    The book provides a technical basis for senior undergraduate or graduate courses and a reference for researchers and practitioners in the field of reliability and risk analysis. Several practical examples are included to demonstrate the application of the concepts and techniques in practice.

     
    Contents:
    • Markov Reliability and Availability Analysis
    • Monte Carlo Simulations for Reliability and Availability Analysis
    • Markov Chain Monte Carlo for Applications to Reliability and Availability Analysis
    • Basics of Genetic Algorithms with Application to System Reliability and Availability Optimization
    • Dependent Failures
    • Importance Measures
    • Basic Concepts of Uncertainty and Sensitivity Analysis
     
    Readership: Undergraduates, graduates, academics and professionals in the fields of systems engineering and safety and risk analysis.
     


     
    364pp    Pub. date: Jan 2009  
    ISBN:   978-981-283-901-5
    981-283-901-1
       US$69 / £56

     


     

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    Updated on 6 November 2009