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Book : Systems Engineering: An Approach to Information-Based Design (1996)

Systems Engineering: An Approach to Information-Based Design

Publisher:Prentice Hall

Author(s):Hazelrigg, George A.

Published: 1996 • ISBN: 0134613449 • 469 pages • Delivery Format: Hard Copy - Paperback

Available from: Amazon (US)Amazon (UK)Amazon (DE)

Summary

A tentative theory and framework for systems engineering, which accounts for all phases in the life cycle of a product or service such that rational choices can be make concerning design options even when uncertainty and risk are high. Proposes a definition for the emerging field.

Content / Structure

Acknowledgements

Foreward

Preface

1 Introduction to Engineering Design and Decision Making

  • 1.1 The Engineering Process
  • 1.2 Historical Perspective
  • 1.3 The Decision-Making Process
  • 1.4 Beans in a Jar
  • 1.5 Summary
  • References
  • Problems

2 Design Options

  • 2.1 The Purpose of this Chapter
  • 2.2 The Role of Options in Decision Making
  • 2.3 System Objectives
  • 2.4 Options in Physical Design
  • 2.5 System Manufacture and Deployment
  • 2.6 Option in System Operation
  • 2.7 End-of-Life Options
  • 2.8 Paring the Option Space
  • 2.9 Summary
  • Reference
  • Problems

3 The Fundamentals of Probability Theory

  • 3.1 The Purpose of this Chapter
  • 3.2 The Concept of Probability
  • 3.3 Properties of a Random Variable
  • 3.4 The Mathematics of Random Variables
  • 3.5 Some Important Distributions
  • 3.6 Baye's Formula
  • 3.7 Hypothesis Testing
  • 3.8 Summary
  • References
  • Problems

4 Monte Carlo Modelling

  • 4.1 The Purpose of this Chapter
  • 4.2 The Notion of a Monte Carlo Model
  • 4.3 Random Number Generators
  • 4.4 Sampling a Distribution
  • 4.5 Formulating Monte Carlo Models
  • 4.6 Analysis of Monte Carlo Model Results
  • 4.7 An Alternative Analysis of Monte Carlo Results
  • 4.8 Monte Carlo Models with Embedded Decisions
  • 4.9 Summary
  • Reference
  • Problems

5 Optimization

  • 5.1 The Purpose of this Chapter
  • 5.2 The Need for Optimization in Systems Engineering
  • 5.3 Notions of Minimum and Maximum
  • 5.4 Maximation of a Function
  • 5.5 Search Methods
  • 5.6 Constrained Optimization
  • 5.7 Linear Programming
  • 5.8 Integer Programming
  • 5.9 Network Flow Optimization
  • 5.10 The Transportation Problem
  • 5.11 Calculus of Variations
  • 5.12 Summary
  • References
  • Problems

6 Engineering Microeconomics

  • 6.1 The Purpose of this Chapter
  • 6.2 The Concept of Preference
  • 6.3 Equilibrium Economics
  • 6.4 Discounting and Present Value
  • 6.5 Interest and Annuities
  • 6.6 Inflation and Deflation
  • 6.7 The Value of a Forecast
  • 6.8 Resource Economics
  • 6.9 Shadow Prices
  • 6.10 Summary
  • References
  • Problems

7 Utility Theory

  • 7.1 The Purpose of this Chapter
  • 7.2 Rationality
  • 7.3 The Notion of Utility
  • 7.4 Multiattribute Utility Functions
  • 7.5 Arrow's Impossibility Theorem
  • 7.6 Pareto Analysis
  • 7.7 Decision Making in the Presence of Risk
  • 7.8 The Value of Better Information
  • 7.9 The Value of Improved Safety
  • 7.10 Summary
  • References
  • Problems

8 Forecasting

  • 8.1 The Purpose of this Chapter
  • 8.2 Types of Forecasts
  • 8.3 Regression Analysis
  • 8.4 Logistic Curves
  • 8.5 Forecasting Uncertainty
  • 8.6 Forecasting Uncertainty with Embedded Decisions
  • 8.7 Shortcomings of Forecasts
  • 8.8 Summary
  • References
  • Problems

9 Engineering Systems Modelling

  • 9.1 The Purpose of this Chapter
  • 9.2 Engineering Systems and System Models
  • 9.3 The Model-Building Process
  • 9.4 Sources of Error in Symbolic Models
  • 9.5 Design Models
  • 9.6 System Life Cycle Modeling
  • 9.7 Objective Functions
  • 9.8 Summary
  • Reference
  • Problems

10 Analysis of System Reliability

  • 10.1 The Purpose of this Chapter
  • 10.2 Notions of System Reliability
  • 10.3 System Reliability Diagrams
  • 10.4 Cartoons and Scenarios
  • 10.5 Decision and Event Trees
  • 10.6 Two DIfferent Monte Carlo Approaches
  • 10.7 Probabalistic Risk Assessment
  • 10.8 An Alternative to Probabilistic Risk Assessment
  • 10.9 Summary
  • References
  • Problems

11 Cost and Benefit Analysis

  • 11.1 The Purpose of this Chapter
  • 11.2 Costs
  • 11.3 Modelling System Cost
  • 11.4 Probabalistic Cost Analysis
  • 11.5 Benefits
  • 11.6 Probabalistic Benefit Analysis
  • 11.7 Benefit-Cost Analysis
  • 11.8 Project Selection
  • 11.9 Summary
  • References
  • Problems

12 Methods of Decision Analysis

  • 12.1 The Purpose of this Chapter
  • 12.2 Decisions and Decision Analysis
  • 12.3 Backward Induction
  • 12.4 Expected Utility Analysis
  • 12.5 The Use of Decision/Event Trees with an Infinite Number of Possible Outcomes
  • 12.6 Confidence Level Decision Making
  • 12.7 Minimax Decision Making
  • 12.8 Regret
  • 12.9 Bayes Solutions
  • 12.10 Summary
  • References
  • Problems

13 State Transition Matrix Models

  • 13.1 The Purpose of this Chapter
  • 13.2 The State Transition Matrix Model
  • 13.3 Example Problems
  • 13.4 Including Uncertainty in State Transition Matrix Models
  • 13.5 Summary
  • Problems

14 Modeling the Research and Development Process

  • 14.1 The Purpose of this Chapter
  • 14.2 Attributes of Research and Development Activities
  • 14.3 A Simulation Approach to Evaluating Research abd Development Activities
  • 14.4 Summary of the Simulation Approach
  • Reference
  • Problems

15 Information

  • 15.1 The Purpose of this Chapter
  • 15.2 A Quantitative Measure of Information
  • 15.3 Summary
  • Problems

16 System Life-Cycle Modeling and Optimization

  • 16.1 The Purpose of this Chapter
  • 16.2 Objective Functions of a Firm
  • 16.3 Objective Functions of Consumers
  • 16.4 Phases of a Product Life Cycle
  • 16.5 System Optimization and Improvement
  • 16.6 Long-Term Planning
  • 16.7 Model Validation
  • 16.8 The Use of Model Results in the Design Process
  • 16.9 Summary
  • Problems

17 Game Theory

  • 17.1 The Purpose of this Chapter
  • 17.2 The Description of a Game
  • 17.3 Types of Games
  • 17.4 Example Games
  • 17.5 Information in the Context of Game Theory
  • 17.6 Mixed Strategy Games
  • 17.7 The Nash Model
  • 17.8 The Minimax Theorem
  • 17.9 Solution of a Two-Player, Zero-Sum Game by Linear Programming
  • 17.10 Summary
  • References
  • Problems

18 Management of Engineering Systems Design and Operation

  • 18.1 The Purpose of this Chapter
  • 18.2 The Management of Engineering Systems Design
  • 18.3 The Management of Engineering Systems Operation
  • 18.4 Continuing Product Improvement
  • 18.5 Summary
  • Problems

19 Case Studies

  • 19.1 The Purpose of this Chapter
  • 19.2 Solution of the Bean Jar Problem
  • 19.3 Am Undersea Cable Design
  • 19.4 Summary of the Systems Engineering Approach

20 Concluding Remarks

Appendix A Vectors and Matrices

Appendix B A Test for the Utility Independence of Attributes

Appendix C Determination of the Weighting Factors in a Linearly Additive Utility Function

Name Index

Topic Index

About the Author

Copyright 1996 by Prentice-Hall, Inc.

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