What Every Engineer Should Know About Risk Engineering and Management

1. Risk Engineering - Dealing with System Complexity and Engineering Dynamics. 1.1 Understanding Failure Is Critical to Engineering Success. 1.2 Risk Assessment - Quantification of Potential Failures. 1.3 Risk Engineering - Converting Risk into Opportunities. 1.4 System Complexity – Measured By Wang Entropy. 1.5 Engineering - A Profession of Managing Technical Risk. 2. Risk Identification - Understanding the Limits of Engineering Designs. 2.1 The Fall of Icarus - Limits of Engineering Design. 2.2 Overload of Failures: Fracture and Its Mechanics. 2.3 Wear-Out Failures: Crack Initiation and Growth. 2.4 Environmental Impact: Temperature-Related Failure. 2.5 Software and Related “Hard” Failures. 2.6 Artificial Intelligence (AI) and its Shocking Failures. 3. Risk Assessment - Extending Murphy’s Law. 3.1 Titanic: Connoisseurs of Engineering Failure. 3.2 Risk Assessment: “How Likely It Is That A Thing Will Go Wrong”. 3.3 Risk Assessment for Multiple Failure Modes. 3.4 Fault Tree Analysis: Deductive Risk Assessment. 3.5 Event Tree Analysis: Inductive Risk Assessment. 3.6 A Risk Example: The TMI Accident. 3.7 An International Risk Scale. 3.8 Information Gain: Causal Risk Assessment Based On Wang Entropy. 4. Design for Risk Engineering - The Art of War Against Failures. 4.1 Challenger: Challenging Engineering Design. 4.2 Goal Tree: Understand “What” and “How”. 4.3 Path Sets and Wang Entropy: “All the Roads To Rome”. 4.4 FMEA: Failure Mode and Effect Analysis. 4.5 Redundancy and Fault Tolerance. 4.6 Risk Engineering and Integrating Information Science. 5. Risk Acceptability - Uncertainty in Perspective. 5.1 Uncertainty: Why Bridges Fall Down. 5.2 Risk Mitigation: How Buildings Stand Up. 5.3 From Safety Factor to Safety Index. 5.4 Converting Safety Index into Probability of Failure. 5.5 Quantitative Safety Goals: Probability vs. Consequence. 5.6 Diagnosability: Additional Element of Risk. 5.7 Risk and Benefit: Balancing the Engineering Equation. 6. From Risk Engineering to Risk Management. 6.1 Panama Canal: Recognizing and Managing Risk. 6.2 Project Risk Assessment: Quantify Risk Triangle. 6.3 Why Artificial Intelligence Projects Fail - How To Avoid?. 6.4 Project Risk Control. 7. Cost Risk - Interacting with Engineering Economy. 7.1 Engineering: The Art of Doing Well Inexpensively. 7.2 Taguchi’s Robust Design: Minimize Total Cost. 7.3 Step 1: Identify System Function and Noise Factors. 7.4 Step 2: Identify Total Cost-Function and Control Factors. 7.5 Step 3: Design Matrix of Experiments and Define Data Analysis. 7.6 Step 4: Conduct Experiments and Data Analysis. 7.7 Step 5: Prediction of Cost-Risk Under Selected Parameter Levels. 7.8 Life-Cycle Cost Management (LCCM). 7.9 Probabilistic Cost Drivers: Quantifying Complexity Of Project Budgeting. 8. Schedule Risk - Identifying and Controlling Critical Paths. 8.1 Schedule: Deliver Engineering Products on Time. 8.2 Critical Path: Driver of Schedule Risk. 8.3 Find and Analyze Critical Path. 8.4 Schedule Risk for a Single Dominant Critical Path. 8.5 Schedule Risk for Multiple Critical Paths. 8.6 Probabilistic Critical Paths: Quantifying Complexity of Project Scheduling. 9. Integrated Risk Management and Computer Simulation. 9.1 An Integrated View of Risk. 9.2 Integrated Risk Management. 9.3 Incorporating the Impact of Schedule Risk. 9.4 Monte-Carlo Simulation. 9.5 Digital Transformation in the Face of Covid-19. 9.6 Apply Wang Entropy to Analyze Mode Confusion, a Challenge to Risk Management at Age of Autonomy.

Biography

Dr. John X. Wang has served as a Functional Safety Expert at Ford Motor Company and a Technical Director at Capgemini. As Senior Principal Functional Safety Engineer at Flex, Dr. Wang has been spotlighted as Employee of the Month by “Under the Hood”, the online magazine published by Flex Automotive to employees around the Globe. Dr. Wang has authored/coauthored numerous books and papers on reliability engineering, risk engineering, engineering decision-making under uncertainty, robust design and Six Sigma, lean manufacturing, green electronics manufacturing, cellular manufacturing, and industrial design engineering - inventive problem-solving. As a recognized inventor, Dr. Wang has been granted two Patents related to Risk Engineering by the US Patent and Trademark Office.