*Probabilistic Design for Optimization and Robustness:*

Presents the theory of modeling with variation using physical models and methods for practical applications on designs more insensitive to variation.

Provides a comprehensive guide to optimization and robustness for probabilistic design.

Features examples, case studies and exercises throughout.

The methods presented can be applied to a wide range of disciplines such as mechanics, electrics, chemistry, aerospace, industry and engineering. This text is supported by an accompanying website featuring videos, interactive animations to aid the readers understanding.

- Preface
- Acknowledgments
- 1 New product development process
- 2 Statistical background for engineering design
- 3 Introduction to variation in engineering design
- 4 Monte Carlo simulation
- 5 Modeling variation of complex systems
- 6 Desirability
- 7 Optimization and sensitivity
- 8 Modeling system cost and multiple outputs
- 9 Tolerance analysis
- 10 Empirical model development
- 11 Binary logistic regression
- 12 Verification and validation
- References
- Bibliography
- Answers to selected exercises
- Index
- End User License Agreement