Engineering Reliability and Risk Assessment explains how to improve the performance of a system using the latest risk and reliability models. Against a backdrop of increasing availability of industrial data, and ever-increasing global commercial competition, the standards for optimal efficiency with minimum hazards keep improving. Topics explained include Effective strategies for the maintenance of the mechanical components of a system, How to schedule necessary interventions throughout the product life cycle, How to understand the structure and cost of complex systems, Planning a schedule to improve the reliability and life of the system, software, system safety and risk informed asset management, and more.
1. Engineering Reliability and Risk Assessment - p. Page i 2. Cover - p. Page i 3. Front Matter - p. Page ii 4. Table of Contents - p. Page iii 5. Copyright - p. Page iv 6. Contributors - p. Page iv 7. List of Illustrations - p. Page vi 8. List of Tables - p. Page vii 9. Chapter 1 : Bayesian networks for failure analysis of complex systems using different data sources - p. Page vii 10. Chapter 2 : Failure modes and effect analysis model for the reliability and safety evaluation of a pressurized steam trap - p. Page 14 11. Chapter 3 : Reliability and availability analysis of a standby system with activation time and varying demand - p. Page 32 12. Chapter 4 : Fuzzy attack tree analysis of security threat assessment in an internet security system using algebraic t-norm and t-conorm - p. Page 49 13. Chapter 5 : A new flexible extension to a lifetime distributions, properties, inference, and applications in engineering science - p. Page 63 14. Chapter 6 : Markov and semi-Markov models in system reliability - p. Page 88 15. Chapter 7 : Emerging trends and future directions in software reliability growth modeling - p. Page 122 16. Chapter 8 : Reliability and profit analysis of a markov model having cost-free warranty with waiting repair facility - p. Page 142 17. Chapter 9 : Semi-Markov modeling applications in system availability analysis - p. Page 158 18. Chapter 10 : An α-cut interval-based similarity aggregation method to evaluate fault tree events for system safety under fuzzy environment - p. Page 183 19. Chapter 11 : Business analytics to advance industrial safety management - p. Page 198 20. Chapter 12 : Risk assessment and management of fire-induced domino effects in chemical industrial park - p. Page 212 21. Chapter 13 : Stability assessment using Bayesian network control for inverters in smart grid - p. Page 233 22. Index - p. Page 261
Engineering Reliability and Risk Assessment explains how to improve the performance of a system using the latest risk and reliability models. Against a backdrop of increasing availability of industrial data, and ever-increasing global commercial competition, the standards for optimal efficiency with minimum hazards keep improving. Topics explained include Effective strategies for the maintenance of the mechanical components of a system, How to schedule necessary interventions throughout the product life cycle, How to understand the structure and cost of complex systems, Planning a schedule to improve the reliability and life of the system, software, system safety and risk informed asset management, and more.
1. Engineering Reliability and Risk Assessment - p. Page i 2. Cover - p. Page i 3. Front Matter - p. Page ii 4. Table of Contents - p. Page iii 5. Copyright - p. Page iv 6. Contributors - p. Page iv 7. List of Illustrations - p. Page vi 8. List of Tables - p. Page vii 9. Chapter 1 : Bayesian networks for failure analysis of complex systems using different data sources - p. Page vii 10. Chapter 2 : Failure modes and effect analysis model for the reliability and safety evaluation of a pressurized steam trap - p. Page 14 11. Chapter 3 : Reliability and availability analysis of a standby system with activation time and varying demand - p. Page 32 12. Chapter 4 : Fuzzy attack tree analysis of security threat assessment in an internet security system using algebraic t-norm and t-conorm - p. Page 49 13. Chapter 5 : A new flexible extension to a lifetime distributions, properties, inference, and applications in engineering science - p. Page 63 14. Chapter 6 : Markov and semi-Markov models in system reliability - p. Page 88 15. Chapter 7 : Emerging trends and future directions in software reliability growth modeling - p. Page 122 16. Chapter 8 : Reliability and profit analysis of a markov model having cost-free warranty with waiting repair facility - p. Page 142 17. Chapter 9 : Semi-Markov modeling applications in system availability analysis - p. Page 158 18. Chapter 10 : An α-cut interval-based similarity aggregation method to evaluate fault tree events for system safety under fuzzy environment - p. Page 183 19. Chapter 11 : Business analytics to advance industrial safety management - p. Page 198 20. Chapter 12 : Risk assessment and management of fire-induced domino effects in chemical industrial park - p. Page 212 21. Chapter 13 : Stability assessment using Bayesian network control for inverters in smart grid - p. Page 233 22. Index - p. Page 261
