Engineering Decision Making and Risk Management

Emphasizes practical issues and examples of decision making with applications in engineering design and management Featuring a blend of theoretical and analytical aspects, Engineering Decision Making and Risk Management presents multiple perspectives on decision making to better understand and improve risk management processes and decision–making systems. Engineering Decision Making and Risk Management uniquely presents and discusses three perspectives on decision making: problem solving, the decision–making process, and decision–making systems. The author highlights formal techniques for group decision making and game theory and includes numerical examples to compare and contrast different quantitative techniques. The importance of initially selecting the most appropriate decision–making process is emphasized through practical examples and applications that illustrate a variety of useful processes. Presenting an approach for modeling and improving decision–making systems, Engineering Decision Making and Risk Management also features: Theoretically sound and practical tools for decision making under uncertainty, multi–criteria decision making, group decision making, the value of information, and risk management Practical examples from both historical and current events that illustrate both good and bad decision making and risk management processes End–of–chapter exercises for readers to apply specific learning objectives and practice relevant skills A supplementary website with instructional support material, including worked solutions to the exercises, lesson plans, in–class activities, slides, and spreadsheets An excellent textbook for upper–undergraduate and graduate students, Engineering Decision Making and Risk Management is appropriate for courses on decision analysis, decision making, and risk management within the fields of engineering design, operations research, business and management science, and industrial and systems engineering. The book is also an ideal reference for academics and practitioners in business and management science, operations research, engineering design, systems engineering, applied mathematics, and statistics. Jeffrey W. Herrmann, PhD, is Associate Professor at the University of Maryland, where he holds a joint appointment with the Department of Mechanical Engineering and the Institute for Systems Research. A member of the Institute of Industrial Engineers, the Institute for Operations Research and the Management Sciences, the American Society of Mechanical Engineers, and the American Society for Engineering Education, Dr. Herrmann’s research interests include production scheduling, decision making in product development, and public health preparedness planning.

1. Introduction to Engineering Decision Making 1.1 Introduction 1.2 Decision Making in Engineering Practice 1.3 Decision Making and Optimization 1.4 Decision Making and Problem Solving 1.5 Decision Making and Risk Management 1.6 Problems in Decision Making 1.7 The Value of Improving Decision Making 1.8 Perspectives on Decision Making Exercises References 2. Decision Making Fundamentals 2.1 Decision Characteristics 2.2 Objectives in Decision Making 2.3 Influence Diagrams 2.4 Rationality 2.5 Dominance 2.6 Choice Strategies 2.7 Making Tradeoffs 2.8 Reframing the Decision 2.9 Risk Acceptance 2.10 Measurement Scales Exercises References 3. Multicriteria Decision Making 3.1 Pugh Concept Selection Method 3.2 Analytic Hierarchy Process (AHP) 3.3 Multiattribute Utility Theory (MAUT) 3.4 Conjoint Analysis 3.5 Value of a Statistical Life 3.6 Compensation 3.7 The Impact of Changing Weights Exercises References 4. Group Decision Making 4.1 Ranking 4.2 Scoring and Majority Judgment 4.3 Arrow’s Impossibility Theorem Exercises References 5. Decision Making Under Uncertainty 5.1 Types of Uncertainties 5.2 Assessing a Subjective Probability 5.3 Imprecise Probabilities 5.4 Cumulative Risk Profile and Dominance 5.5 Decision Trees: Modeling 5.6 Decision Trees: Determining Expected Values 5.7 Sequential Decision Making 5.8 Modeling Risk Aversion 5.9 Robustness 5.10 Uncertainty Propagation: Sensitivity Analysis 5.11 Uncertainty Propagation: Method of Moments 5.12 Uncertainty Propagation: Monte Carlo Simulation Exercises References 6. Game Theory 6.1 Game Theory Basics 6.2 Zero–sum Games 6.3 Optimal Mixed Strategies for Zero–sum Games 6.4 The Minimax Theorem 6.5 Resource Allocation Games 6.6 Mixed Motive Games 6.7 Bidding 6.8 Stackelberg Games Exercises References 7. Decision–making Processes 7.1 Decision–making Contexts 7.2 Technical Knowledge and Problem Consensus 7.3 Optimization: Search and Evaluation 7.4 Diagnosing Risk Decision Situations 7.5 Values and Ethics 7.6 Systematic Decision–making Processes 7.7 The Decision–making Cycle 7.8 The Analytic–deliberative Process 7.9 Concept Selection 7.10 Decision Calculus 7.11 Recognition–primed Decision Making 7.12 Heuristics 7.13 Unconscious Decision Making 7.14 Search 7.15 Types of Search in Practice 7.16 Secretary Problem 7.17 Composite Decisions 7.18 Separation 7.19 Product Development Processes Exercises References 8. The Value of Information 8.1 The Expected Value of Perfect Information 8.2 The Expected Value of Imperfect Information 8.3 Experimentation to Reduce Ambiguity 8.4 Experimentation to Compare Alternatives 8.5 Experimentation to Compare Alternatives with Multiple Attributes Exercises References 9. Risk Management 9.1 Risk Management Process 9.2 Potential Problem Analysis 9.3 Risk Management Guide for DOD Acquisition 9.4 Risk Management at NASA 9.5 Precursors 9.6 Warnings 9.7 Risk Communication 9.8 Managing the Risk of a Bad Decision 9.9 Learning from Failures 9.10 Transforming Failure Information Exercises References 10. Decision–making Systems 10.1 Introduction to Decision–making Systems 10.2 Mechanisms of Organization Influence 10.3 Roles in Decision–making Systems 10.4 Information Flow 10.5 The Structure of Decision–making Systems 10.6 Product Development Organizations 10.7 Information Flow in Product Development 10.8 The Design Factory Exercises References 11. Modeling and Improving Decision–making Systems 11.1 Modeling Decision–making Systems 11.2 Rich Pictures 11.3 Swimlanes 11.4 Root Definitions 11.5 Conceptual Models 11.6 Models of Product Development Organizations 11.7 Improving Decision–making Systems 11.8 An Integrative Strategy Exercises References

Jeffrey W. Herrmann, PhD, is Associate Professor at the University of Maryland, where he holds a joint appointment with the Department of Mechanical Engineering and the Institute for Systems Research. A member of the Institute of Industrial Engineers, the Institute for Operations Research and the Management Sciences, the American Society of Mechanical Engineers, and the American Society for Engineering Education, Dr. Herrmann’s research interests include production scheduling, decision making in product development, and public health preparedness planning.