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.
Table of Contents
- 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
- Answers to selected exercises
- End User License Agreement
- Title: Probabilistic Design for Optimization and Robustness for Engineers
- Release date: September 2014
- Publisher(s): Wiley
- ISBN: 9781118796191