Article ID: | iaor1994423 |
Country: | United Kingdom |
Volume: | 21 |
Issue: | 3 |
Start Page Number: | 213 |
End Page Number: | 239 |
Publication Date: | Aug 1993 |
Journal: | Engineering Optimization |
Authors: | Bras Bert, Mistree Farrokh |
Keywords: | engineering, quality & reliability, programming: multiple criteria, artificial intelligence: decision support |
Compromise Decision Support Problems (DSPs) are used to model engineering decisions involving multiple trade-offs. In this paper, the focus is on how to apply such decision models in robust design. Suh’s independence and information content axioms and Taguchi’s signal to noise ratio are used as metrics for the assessment and improvement of the quality in this decision model. As an example, a compromise DSP for the robust design of an electrical network is used. Traditionally, in robust design, parameter and tolerance design are done sequentially and not concurrently. Furthermore, each time parameter and tolerance design are done in practice, the focus is usually on looking at one parameter at a time and not on looking at multiple parameters simultaneously. Using the electrical network as an example, it is shown how parameter and tolerance design involving multiple parameters can be performed concurrently.