ABOUT THE COURSE: Risk based approach is integral to design, operation, maintenance and regulation of engineering systems. Traditionally risk and reliability aspects were addressed employing qualitative and experience-based approach which tends to be, at times, arbitrary and not based on qualitative notions of safety and reliability. This course on ‘Risk-based Engineering’ extends the science of probabilistic risk assessment and reliability engineering and integrates with physics-of-failure approach, human factor engineering, application of prognostics and health and uncertainty prediction such that a systematic and rational based system can be established that is designed to address real-time engineering and management aspects with sound quantitative and rational basis, while optimizing risk and reliability such that safety as well as business objectives are not compromised. This is an applied subject that has been developed based on the R&D experience of over 10 years that captures the concept, fundamental, techniques and methods. of ‘Risk-based Engineering’. A book Co-authored by Prabhakar V Varde and Michael Pecht has been published through Springer in 2018.INTENDED AUDIENCE: Ph. D. students and researchers in engineering sciencesPREREQUISITES: B.Tech. in Engineering SciencesINDUSTRY SUPPORT: Probabilistic Risk Assessment (PRA) - that is at the core of risk-based engineering) for complex engineering systems like nuclear plants, process and chemical industry, Space and aviation systems forms an integral part of design and operations safety evaluation. Risk-based engineering has been design as an integrated approach to these applications.
Overview
Syllabus
Week 1: Introduction: Historical Perspective on Probabilistic Risk Assessment and Risk-based applications, Integrated Risk-based Engineering Approach, Factor of safety and uncertainty, Basic Framework for Integrated Risk-Based Engineering, Major Elements of Integrated Risk-Based Engineering.
Week 2:Risk characterization: Background, Definition of “Risk”, Risk Characterization Policy and Principles, Major Elements of Risk Characterization, Roles of People and Organizations, Risk Assessment Techniques, Failure Mode Effect and Criticality Analysis (FMECA), Hazard and Operability (HAZOP) Analysis, Probabilistic Risk Assessment (PRA), Quantitative Risk Assessment, Other Risk Assessment Approaches, Risk Metrics.
Week 3:Probabilistic approach to risk and reliability: The Bathtub Curve, Probability Theory: Main Concepts, Reliability, Derivation of Reliability Function from the First Principle, Reliability Characteristics, Mean Time to Failure (MTTF), Reliability, Availability, Probability Distribution Functions, Poisson Distribution, Joint Probability and Marginal Distribution, Statistical Estimation of Failure Rate, Point Estimate, Method of Moment, Maximum Likelihood Estimate, Bayesian Estimator, Confidence Interval Estimation, Goodness-of-Fit Tests.
Week 4:Systems Reliability Modelling and Analysis: Reliability Block Diagram, Fault Tree, Event Tree Analysis, Markov Modelling, Series, Parallel, Standby and complex configuration modelling, Bayesian updating. Confidence interval analysis, Importance and Sensitivity Analysis, Availability and Maintainability Analysis, Data Modelling and Analysis,
Week 5:Probabilistic Risk Assessment - I: Definition, Level 1, 2 and 3 PRA, Preliminary Hazard Analysis, Initiating Event Selection, Accident Sequence Modelling, System modelling, Data collection, analysis and management requirements, Quantification, Uncertainty and Sensitivity Analysis, Evaluation of risk statement for the plant / system. Special Features of PRA: Common Cause Failure, Human Reliability, Risk Ranking of System Structure of Components,
Week 6:Probabilistic Risk Assessment – II: Introduction to Low-power and shutdown PRA, Flood and Fire PRA, External Event PRA : Seismic & Flood, PRA applications in design, operation and regulation as part of risk-informed strategy.
Week 7:Human Reliability Analysis: A review of the current HR techniques and methods, limitation and advantages of each. Role of various stress inducing factors, role of cognition, consciousness and conscience in HR. Human Reliability requirements in PRA, Estimation of Human Reliability for normal and emergency conditions. Role of Plant simulator in human reliability evaluation.
Week 8:Physics-of-failure approach: Power and Limitation of PoF based approach to risk and reliability, role of operational and environmental stresses, Framework for PoF, Failure Mode Mechanism and Effect , Life testing for simulation the load. Role of intelligent approach to feature extraction, Canaries,
Week 9:Prognostics and health management: Definitions, traditional approach to life / reliability prediction, Fundamental concepts in prognostics and risk management, role of physics of failure in PHM, Data driven, Physics-of-Failure and Fusion approach to PHM. Degradation modelling, Accelerated Life testing, PHM Metrics. PHM standards.
Week 10:Risk-conscious operations management operations risk management, dependability engineering, Risk scenario simulation, human-factor in RCOM, Intelligent methods, Human root cause analysis.
Week 11:Uncertainty Analysis: Conventional approaches to capture uncertainty, sources and uncertainty, Epistemic and Aleatory uncertainty, Uncertainty characterization in reliability and risk analysis. Monte – Carlo Approach for uncertainty. Assessment of Confidence bounds.
Week 12:Applications / Case Studies on Risk-based Engineering: Risk-based design, Risk-based Inservice Inspection, PRA based Operator Support Systems, Risk-based Maintenance Management, Safety System Test Interval optimization, Insurance Liability evaluation, Risk conscious operation Management. Risk- informed decision making in regulatory framework, Risk-monitor
Week 2:Risk characterization: Background, Definition of “Risk”, Risk Characterization Policy and Principles, Major Elements of Risk Characterization, Roles of People and Organizations, Risk Assessment Techniques, Failure Mode Effect and Criticality Analysis (FMECA), Hazard and Operability (HAZOP) Analysis, Probabilistic Risk Assessment (PRA), Quantitative Risk Assessment, Other Risk Assessment Approaches, Risk Metrics.
Week 3:Probabilistic approach to risk and reliability: The Bathtub Curve, Probability Theory: Main Concepts, Reliability, Derivation of Reliability Function from the First Principle, Reliability Characteristics, Mean Time to Failure (MTTF), Reliability, Availability, Probability Distribution Functions, Poisson Distribution, Joint Probability and Marginal Distribution, Statistical Estimation of Failure Rate, Point Estimate, Method of Moment, Maximum Likelihood Estimate, Bayesian Estimator, Confidence Interval Estimation, Goodness-of-Fit Tests.
Week 4:Systems Reliability Modelling and Analysis: Reliability Block Diagram, Fault Tree, Event Tree Analysis, Markov Modelling, Series, Parallel, Standby and complex configuration modelling, Bayesian updating. Confidence interval analysis, Importance and Sensitivity Analysis, Availability and Maintainability Analysis, Data Modelling and Analysis,
Week 5:Probabilistic Risk Assessment - I: Definition, Level 1, 2 and 3 PRA, Preliminary Hazard Analysis, Initiating Event Selection, Accident Sequence Modelling, System modelling, Data collection, analysis and management requirements, Quantification, Uncertainty and Sensitivity Analysis, Evaluation of risk statement for the plant / system. Special Features of PRA: Common Cause Failure, Human Reliability, Risk Ranking of System Structure of Components,
Week 6:Probabilistic Risk Assessment – II: Introduction to Low-power and shutdown PRA, Flood and Fire PRA, External Event PRA : Seismic & Flood, PRA applications in design, operation and regulation as part of risk-informed strategy.
Week 7:Human Reliability Analysis: A review of the current HR techniques and methods, limitation and advantages of each. Role of various stress inducing factors, role of cognition, consciousness and conscience in HR. Human Reliability requirements in PRA, Estimation of Human Reliability for normal and emergency conditions. Role of Plant simulator in human reliability evaluation.
Week 8:Physics-of-failure approach: Power and Limitation of PoF based approach to risk and reliability, role of operational and environmental stresses, Framework for PoF, Failure Mode Mechanism and Effect , Life testing for simulation the load. Role of intelligent approach to feature extraction, Canaries,
Week 9:Prognostics and health management: Definitions, traditional approach to life / reliability prediction, Fundamental concepts in prognostics and risk management, role of physics of failure in PHM, Data driven, Physics-of-Failure and Fusion approach to PHM. Degradation modelling, Accelerated Life testing, PHM Metrics. PHM standards.
Week 10:Risk-conscious operations management operations risk management, dependability engineering, Risk scenario simulation, human-factor in RCOM, Intelligent methods, Human root cause analysis.
Week 11:Uncertainty Analysis: Conventional approaches to capture uncertainty, sources and uncertainty, Epistemic and Aleatory uncertainty, Uncertainty characterization in reliability and risk analysis. Monte – Carlo Approach for uncertainty. Assessment of Confidence bounds.
Week 12:Applications / Case Studies on Risk-based Engineering: Risk-based design, Risk-based Inservice Inspection, PRA based Operator Support Systems, Risk-based Maintenance Management, Safety System Test Interval optimization, Insurance Liability evaluation, Risk conscious operation Management. Risk- informed decision making in regulatory framework, Risk-monitor
Taught by
Prof. Prabhakar V Varde
