What Every Engineer Should Know About Decision Making Under Uncertainty

John X. Wang

• Publisher: CRC Press
• Year: 2002
• eBook ISBN: 9780203910757
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Industrial Engineering
• Index: Technology & Engineering

Covering the prediction of outcomes for engineering decisions through regression analysis, this succinct and practical reference presents statistical reasoning and interpretational techniques to aid in the decision making process when faced with engineering problems. The author emphasizes the use of spreadsheet simulations and decision trees as important tools in the practical application of decision making analyses and models to improve real-world engineering operations. He offers insight into the realities of high-stakes engineering decision making in the investigative and corporate sectors by optimizing engineering decision variables to maximize payoff.

Table of contents

• Cover
• Half Title
• Series Page
• Title Page
• Copyright Page
• Table of Contents
• Preface
• Chapter 1: Engineering: Making Hard Decisions Under Uncertainty
• Chapter 2: Engineering Judgment for Discrete Uncertain Variables
• Chapter 3: Decision Analysis Involving Continuous Uncertain Variables
• Chapter 4: Correlation of Random Variables and Estimating Confidence
• Chapter 5: Performing Engineering Predictions
• Chapter 6: Engineering Decision Variables – Analysis and Optimization
• Chapter 7: Project Scheduling and Budgeting Under Uncertainty
• Chapter 8: Process Control – Decisions Based on Charts and Indexes
• Chapter 9: Engineering Decision Making: A New Paradigm
• Appendix A: Engineering Decision-Making Software Evaluation Checklist
• Appendix B: Four Primary Continuous Distributions
• Index
• About the Author