Fully updated and revised with more practical emphasis and more extensive use of case studies, this edition provides a comprehensive description of the main probabilistic methods employed in reliability and risk assessment, particularly fault tree analysis and failure mode, and effective analysis and their derivatives. Self-contained, each chapter focuses on a single subject or method and illustrates it with worked examples. The final chapter features four major case studies from recent projects to show how the methods have been applied to identify and quantify the risk and reliability characteristics against specific performance requirements. Focusing on the risk and reliability assessment of process plants, this book serves as a comprehensive reference to powerful analysis techniques for design, operation, and regulatory engineers involved directly with the safety and availability assessment of potentially hazardous process plants. It also serves as a text for undergraduate, graduate, and incompany courses and training. Contents: Introduction to Reliability and Risk Assessment; Reliability Mathematics; Qualitative Methods; Failure Mode and Effects Analysis; Quantific of Component Failure Probabilities; Reliability Networks; Fault Tree Analysis; Common Cause Failures; Maintainability; Markov Analysis; Simulation; Reliability Data Collection and Analysis; Risk Assessment; Case Study 1: Quantitative Safety Assessment of Ventilation Recirculation System in an Undersea Mine; Case Study 2: Failure Mode and Effects Criticality Analysis of Gas Turbine System; Case Study 3: In-Service Inspection of Structural Components (application to conditional maintenance of steam generators); Case Study 4: Business-interruption Risk Analysis. Appendix A: Expectation, Variance, and Standard Deviation. Appendix B: Standard Laplace Transforms; Glossary.
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John Andrews is a Professor in reliability and risk assessment methods in the Department of Mathematical Sciences at Loughborough University.
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