Robust engineering design with genetic algorithms

Authors:
Babak Forouraghi
Affiliations:
Computer Science Department, Saint Joseph's University, Philadelphia, PA
Venue:
IEA/AIE'2004 Proceedings of the 17th international conference on Innovations in applied artificial intelligence
Year:
2004

Citing 0
Cited 2

Simultaneous optimal selection of design and manufacturing tolerances with alternative manufacturing process selection

Computer-Aided Design
Conservative multi-objective optimization considering design robustness and tolerance: a quality engineering design approach

Structural and Multidisciplinary Optimization

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper introduces a new robust optimization technique which performs tolerance and parameter design using a genetic algorithm. It is demonstrated how tolerances for control parameters can be specified while reducing the product's sensitivity to noise factors. As generations of solutions undergo standard genetic operations, new designs evolve, which exhibit several important characteristics. First, all control parameters in an evolved design are within a set of allowed tolerances; second, the resulting product response meets the target performance; and finally, the product response variance is minimal.