Multi-objective design optimization for product platform and product family design using genetic algorithms

Satish V.K. Akundi, Timothy W. Simpson, Patrick M. Reed

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

37 Scopus citations

Abstract

Many companies are using product families and platform-based product development to reduce costs and time-to-market while increasing product variety and customization. Multi-objective optimization is increasingly becoming a powerful tool to support product platform and product family design. In this paper, a genetic algorithm-based optimization method for product family design is suggested, and its application is demonstrated using a family of universal electric motors. Using an appropriate representation for the design variables and by adopting a suitable formulation for the genetic algorithm, a one-stage approach for product family design can be realized that requires no a priori platform decision-making, eliminating the need for higher-level problem-specific domain knowledge. Optimizing product platforms using multi-objective algorithms gives the designer a Pareto solution set, which can be used to make better decisions based on the trade-offs present across different objectives. Two Non-Dominated Sorting Genetic Algorithms, namely, NSGA-II and ε-NSGA-II, are described, and their performance is compared. Implementation challenges associated with the use of these algorithms are also discussed. Comparison of the results with existing benchmark designs suggests that the proposed multi-objective genetic algorithms perform better than conventional single-objective optimization techniques, while providing designers with more information to support decision making during product family design.

Original languageEnglish (US)
Title of host publicationProceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conferences - DETC2005
Subtitle of host publication31st Design Automation Conference
PublisherAmerican Society of Mechanical Engineers
Pages999-1008
Number of pages10
ISBN (Print)079184739X, 9780791847398
DOIs
StatePublished - 2005
EventDETC2005: ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference - Long Beach, CA, United States
Duration: Sep 24 2005Sep 28 2005

Publication series

NameProceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference - DETC2005
Volume2 B

Other

OtherDETC2005: ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
CountryUnited States
CityLong Beach, CA
Period9/24/059/28/05

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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