Article2022

A multi-objective grouping genetic algorithm for modular design

Hwai-En Tseng · Chien-Cheng Chang · Shih-Chen Lee

16 citations0/0 files storedProceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture

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Product Development and Customization Manufacturing Process and Optimization Advanced Software Engineering Methodologies

Abstract

Due to the increasingly variable market competition, product modular design is gaining in importance. This study attempts to seek a balance in three perspectives on product design: connection intensity, cost-effectiveness, and environmental protection. A multi-objective grouping genetic algorithm is adopted. Grouping genetic algorithms feature the flexible grouping and correcting mechanisms of crossover and mutation to meet the requirements of grouping, making it possible to establish a reasonable multi-objective measurement method after grouping and further offer suggestions to improve the modular design. In this study, the ceiling fan is used as an example to verify the proposed method for evaluation of the grouping method in the Matlab program. Results of the ceiling fan case verify that the proposed multi-objective algorithm is effective in modular design.

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References

1998Modularity in design of products and systems 2005Modular and platform methods for product family design: literature analysis 1998Implications of Modularity on Product Design for the Life Cycle 1999Product modularization for life cycle engineering 2016A systematic literature review on modular product design 2007Modular design to support green life-cycle engineering 2017The role of modularity in sustainable design: A systematic review 2004Product Variety Optimization Simultaneously Designing Module Combination and Module Attributes

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