A Genetic Algorithm Based Method for Product Family Design Optimization

Abstract

Increased commonality in a family of products can simplify manufacturing and reduce the associated costs and lead-times. There is a tradeoff, however, between commonality and individual product performance within a product family, and in this paper we introduce a genetic algorithm based method to help find an acceptable balance between commonality in the product family and desired performance of the individual products in the family. The method uses Design of Experiments to help screen unimportant factors and identify factors of interest to the product family and a multiobjective genetic algorithm, the non-dominated sorting genetic algorithm, to optimize the performance of the products in the resulting family. To demonstrate implementation of the proposed method, the design of a family of three General Aviation Aircraft is presented along with a product variety tradeoff study to determine the extent of the tradeoff between commonality and individual product performance within the aircraft family. The efficiency and effectiveness of the proposed method is illustrated by comparing the family of aircraft against individually optimized designs and designs obtained from an alternate gradient-based multiobjective optimization method.

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