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What Every Engineer Should Know About Decision Making Under Uncertainty
John X. Wang
Certified Six Sigma Master Black Belt
Certified Reliability Engineer
Ann Arbor, Michigan
Contents
PREFACE
CHAPTER 1 ENGINEERING: MAKING HARD DECISIONS
UNDER UNCERTAINTY
1.1 Case Study: Galileo’s Cantilever Beam
1.2 Impact of Engineering Decision Making
1.3 Uncertainty and Risk Engineering
1.4 Decision Making and System Analysis
1.5 Engineering Decision Making in Six Steps
1.6 Customer-Focused Engineering Decision-Making System
1.7 Summary
References
CHAPTER 2 ENGINEERING JUDGMENT FOR DISCRETE
UNCERTAIN VARIABLES
2.1 Case Study: Production of Electronic Modules
2.2 How Would Engineers Flip Coins?
2.3 Synthesize Knowledge into a Simulation Model
2.4 Simulation for What-If Analysis
2.5 Simulating Conditional Independence
2.6 Production Quantity and Quality Measures
2.7 Summary
References
CHAPTER 3 DECISION ANALYSIS INVOLVING
CONTINUOUS UNCERTAIN VARIABLES
3.1 Case Study: A Bioengineering Firm
3.2 Normal Distributions
3.3 Lognormal Distributions
3.4 Selection Between Normal and Lognormal Distributions
3.5 Decision Tree Analysis
3.6 Capital Budgeting
3.7 Summary
References
Chapter 4 CORRELATION OF RANDOM VARIABLES AND ESTIMATING CONFIDENCE
4.1 Case Study: A Transportation Network
4.2 Covariance and Correlation
4.3 Linear Functions of Several Random Variables
4.4 Multivariate Normal Random Variables
4.5 Estimating Correlations from Data
4.6 Accuracy of Sample Estimates
4.7 Customer-Focused Engineering Decision Making
4.8 Summary
References
Chapter 5 PERFORMING ENGINEERING
PREDICTIONS
5.1 Case Study: A Construction Project
5.2 The Law of Expected Posteriors
5.3 Linear Regression Models
5.4 Regression Analysis and Least Squared Errors
5.5 The Theory of Constraints
5.6 Summary
References
CHAPTER 6 ENGINEERING DECISION VARIABLES –
ANALYSIS AND OPTIMIZATION
6.1 Case Study: Production Planning of Snowboards
6.2 Method 1: Simulating Payoffs for Each Engineering
Strategy
6.3 Method 2: Simulating Payoffs from Alternative Strategies
Simultaneously
6.4 Method 3: Optimizing Engineering Decision Variables to
Maximize Payoff
6.5 Value of Information for Engineering Decisions
6.6 Decision Criteria: How to Value Engineering Alternatives
6.7 Evaluation of Cash Flow Information: Payback Method
6.8 The Time Value of Money
6.9 Evaluation of Cash Flow Information: Net Present Value
(NPV) Method
6.10 Evaluation of Cash Flow Information: Internal Rate of
Return (IRR) Method
6.11 Variable Cash Flow
6.12 Project Ranking
6.13 Summary
References
CHAPTER 7 PROJECT SCHEDULING AND BUDGETING
UNDER UNCERTAINTY
7.1 Case Study: Expansion of a Fiber Optics Firm’s Office
Space
7.2 Establish a Project Scheduling Network
7.3 Spreadsheet Strategies for Solving CPM Problems Using
Excel
7.4 Solving Critical Path Problems Using Excel Solver
7.5 Crashing CPM Networks Using Excel
7.6 Developing an Approximate PERT Solution in Excel
7.7 Developing a Complete PERT Solution in Excel
7.8 Probabilistic Solutions to Project Scheduling Simulation
Using Excel
7.9 Project Budgeting
7.10 Summary
References
CHAPTER 8 PROCESS CONTROL – DECISIONS BASED
ON CHARTS AND INDEXES
8.1 Processes and Process Variability
8.2 Statistical Process Control
8.3 Types of Out-of-Control Conditions
8.4 Sampling and Control Charts
8.5 Steps in Determining Process Capability
8.6 Capability Indexes
8.7 Continuous Quality Improvement vs. Business
Process Re-engineering
8.8 Six Sigma Quality
8.9 Summary
References
CHAPTER 9 ENGINEERING DECISION MAKING:
A NEW PARADIGM
9.1 Engineering Decision Making: Past, Present, and
Future
9.2 Engineering Decision-Making Tool Box
9.3 Balancing Technical Merits, Economy, and Delivery
9.4 Engineering Decision Making in a Corporate Setting
9.5 Summary
References
APPENDIX A ENGINEERING DECISION-MAKING
SOFTWARE EVALUATION CHECKLIST
APPENDIX B FOUR PRIMARY CONTINUOUS
DISTRIBUTIONS
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