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.References. Agresti, A. (1996). An introduction to categorical data analysis. NewYork, NY:Wiley. Assistant Secretary ... Advanced product quality planning ( APQP) and control plan: Reference manual (2nd ed.). ... New York, NY: McGraw- Hill.
|Title||:||Probabilistic Design for Optimization and Robustness for Engineers|
|Author||:||Bryan Dodson, Patrick Hammett, Rene Klerx|
|Publisher||:||John Wiley & Sons - 2014-07-21|