A genetic algorithm based method for product family design optimization

Brayan S. D'Souza, Timothy W. Simpson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationProceedings of the ASME Design Engineering Technical Conference
PublisherAmerican Society of Mechanical Engineers
Pages681-690
Number of pages10
ISBN (Electronic)0791836223
DOIs
StatePublished - 2002
Event28th Design Automation Conference - Montreal, Que., Canada
Duration: Sep 29 2002Oct 2 2002

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume2

Conference

Conference28th Design Automation Conference
CountryCanada
CityMontreal, Que.
Period9/29/0210/2/02

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Mechanical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

Fingerprint Dive into the research topics of 'A genetic algorithm based method for product family design optimization'. Together they form a unique fingerprint.

Cite this