Frontiers of Risk and Reliability Engineering Research

Transcription

1 Frontiers of Risk and Reliability Engineering Research Mohammad Modarres The Nicole Y. Kim Eminent Professor of Engineering Director, Center for Risk and Reliability Department of Mechanical Engineering Plenary Keynote Talk ASME-IMECE2015 Conference October 19, 2015 Houston, Texas

2 Outline Frontiers in Reliability Engineering Frontiers in Risk Analysis Reliability Science Prognosis and Health Management (PHM): Big Data, Damage Precursors Risk and Security of Complex Systems and Infrastructures

3 Key Areas of Research: Reliability Frontiers Issues with the Traditional Field / Test Data One Size Fits All concept! Reliability Estimates Rarely Match Reality Probabilistic Physics-of-Failure (PPoF) More than 50-Years of History in PoF (More Recently PPoF) Accelerated Reliability Testing for PPoF Model Development Empirical Model for Unit-Specific Models of Reliability Assessment Simulation-Based Reliability Assessment / Numerical Complexity Hybrid Reliability Combined System Analysis Techniques: BBN, DBN, FT, ET, Markov and Semi-Markov, FEM and FDM, FM, RBD, etc. Sensor-Based (Precursors) / Big Data Reliability Analysis Data Fusion, Machine Learning (GRP, SVM,..), Natural Language, Signal Processing, Detection Probability, Tensor-Based Computing Representative Sample-Based Approach Massively Parallel Processing (MPP) PHM of Cyber-Physical Complex Systems and Structures Science of Reliability Engineering

4 Key Areas of Research: Risk Frontiers Infrastructure Safety-Security-Resilience (SSR) Electronic Information Flow Embedded in Nearly Every Aspect of Modern Life Integrity of Complex Systems and Networks: Cyber-Human-Software- Physical (CHSP) Systems Highly Connected Infrastructure Networks: Electricity, Gas, and Water Pose Major Societal Risks Through Cyberspace Attacks Risk Management and Resilience Societal Disruption, Health, Safety and Resilience Goals Life-Cycle Risks of Advanced Energy Systems Renewable Systems (Building, Environmental, Internal and External) Nuclear Energy (Fission and Fusion) Climate Change Risks of Disruptions in Sustained Energy Supply Health System Risks Estimates 1 Puts Medical Errors as the Third Leading Cause of Death in the U.S., Just Behind Cardiovascular Diseases and Cancer! Simulation-Based Dynamic Probabilistic Risk Assessment High Power Computing Leading to Less Inductive Risk Models More Deductive Computer-Assisted Risk Scenario Generation 1. A New, Evidence-based Estimate of Patient Harms Associated with Hospital Care, James, John T., Journal of Patient Safety, 2013 Vol. 9 - Issue 3 - p

5 A New Theory of Damage: Science-Based Reliability Engineering Failure mechanisms leading to degradation share a common feature at a deeper level: Dissipation of Energy Dissipation (or equivalently entropy generation) Damage Degradation mechanisms Damage Dissipation energies Entropy generation Failure 1 occurs when the accumulated total entropy generated exceeds the entropic-endurance of the unit Rudolf Clausius Entropic-endurance describes the capacity of the unit to withstand entropy Entropic-endurance of identical units is equal Entropic-endurance of different units is different Entropic-endurance to failure can be measured (experimentally) and involves stochastic variability 1. Defined as the state or condition of not meeting a requirement, desirable behavior or intended function

6 Thermodynamics as the Science of Reliability Past Future Present Why Entropy? ü Entropy can model multiple competing degradation processes leading to damage ü Entropy is independent of the path to failure ending at similar total entropy at failure ü Entropy accounts for complex synergistic effects of interacting degradation processes ü Entropy is scale independent Ludwig Boltzmann Statistical Mechanics Entropy

7 Damage Precursors Big Data and PHM Applications Damage Precursors: Any recognizable variation of materials/physical properties influenced by the evolution of the hidden/ inaccessible/ unmeasurable damage during the degradation process Heterogeneous Big Data / Information Online and Offline Sensor Values Human Inspections Physical Model Predictions / Simulations

8 A Two-Stage Hybrid-Model PHM Approach Stage 1: Damage Precursor Model Microstructural Damage Mechanisms Stage 2: PPoF Models RUL Estimation Damage Precursors Sensor-Based Monitoring Extract Damage Indicators Machine Learning: Characterizing Precursor Indicator Failure Agents Model Parameters Initial Damage PPoF Models Future State of Health Current State of Health Partially Relevant Information Measurements Expert Judgments Measurement Errors Feature Extraction Measurement Errors Probability of Detection (POD) Built-in Sensors NDI Data Probability of Detection (POD)

9 Conclusions Reliability and Risk Analysis Now Forms an Integral Part of Modern Products, Systems and Infrastructures Design and Operation Exciting Research and Employment Opportunities Exist in Risk and Reliability Evidence: Number of Conferences, Educational Programs, Scholarly Journals, Human Resource Demands, Rate of Growth in New Technologies University-Government-Industry Research Teams will be Instrumental

10 Thank you for your attention!