Über den Autor
Enrico Zio (BSc in nuclear engng., Politecnico di Milano, 1991; MSc in mechanical engng., UCLA, 1995; PhD, in nuclear engng., Politecnico di Milano, 1995; PhD, in nuclear engng., MIT, 1998) is Director of the Chair in Complex Systems and the Energetic Challenge of the European Foundation for New Energy of Electricite' de France (EDF) at Ecole Centrale Paris and Supelec, full professor, President and Rector's delegate of the Alumni Association and past-Director of the Graduate School at Politecnico di Milano, adjunct professor at University of Stavanger. He is the Chairman of the European Safety and Reliability Association ESRA, member of the scientific committee of the Accidental Risks Department of the French National Institute for Industrial Environment and Risks, member of the Korean Nuclear society and China Prognostics and Health Management society, and past-Chairman of the Italian Chapter of the IEEE Reliability Society. He is serving as Associate Editor of IEEE Transactions on Reliability and as editorial board member in various international scientific journals, among which Reliability Engineering and System Safety, Journal of Risk and Reliability, International Journal of Performability Engineering, Environment, Systems and Engineering, International Journal of Computational Intelligence Systems. He has functioned as Scientific Chairman of three International Conferences and as Associate General Chairman of two others. His research focuses on the characterization and modeling of the failure/repair/maintenance behavior of components, complex systems and critical infrastructures for the study of their reliability, availability, maintainability, prognostics, safety, vulnerability and security, mostly using a computational approach based on advanced Monte Carlo simulation methods, soft computing techniques and optimization heuristics. He is author or co-author of five international books and more than 200 papers on international journals.
1.Introduction.- 2.System Reliability and Risk Analysis.- 3.Monte Carlo Simulation- the Method.- 4.System Reliability and Risk Analysis by Monte Carlo Simulation.- 5.Practical Applications of Monte Carlo Simulation for System Reliability Analysis.- 6.Advanced Mont Carlo Simulation Techniques for System Failure Probability Estimation.- 7.Practical Applications of Advanced Monte Carlo Simulation Techniques for System Techniques for System Failure Probability Estimation
Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling.
Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques.
This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergraduate and graduate students as well as researchers and practitioners. It provides a powerful tool for all those involved in system analysis for reliability, maintenance and risk evaluations.
Illustrates the Monte Carlo simulation method and its application to reliability and system engineering to give the readers the sound fundamentals of Monte Carlo sampling and simulation Explains the merits of pursuing the application of Monte Carlo sampling and simulation methods when realistic modeling is required so that readers may exploit these in their own applications Includes a range of simple academic examples in support to the explanation of the theoretical foundations as well as case studies provide the practical value of the most advanced techniques so that the techniques are accessible