A Tandem Evolutionary Algorithm for Platform Product Customization

[+] Author and Article Information
George Q. Huang

Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam Road, Hong Konggqhuang@hku.hk

L. Li

Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam Road, Hong Konghkulily@hkusua.hku.hk

X. Chen

Faculty of Electromechanical Engineering, Guang Dong University of Technology, PR Chinaxchen@gdut.edu.cn

J. Comput. Inf. Sci. Eng 7(2), 151-159 (Aug 31, 2006) (9 pages) doi:10.1115/1.2720883 History: Received April 07, 2006; Revised August 31, 2006

The increasing demand for reduction in time to market has led to new product development methodologies focusing on reuse. Platform product customization emerges as a basic idea for avoiding designing a new product completely from scratch, but reusing a product platform instead. Key dimensions of some modules of the platform can be stretched or shrunk while modules themselves can be swapped to formulate multiple product variants in a family according to specific customer requirements. This paper formulates such a problem of platform product customization as an optimization problem consistent with the manufacturer’s goal in the design of product variant(s) while satisfying customer requirements and design constraints. Optimal customization takes place at the levels of product structure and module parameters. A tandem evolutionary algorithm is proposed for identifying the optimal structural composition and the optimal parameters of the corresponding structure. The encoding schemes and genetic operators for structure and parameter optimization are designed, respectively. A case study of gantry crane customization is given to illustrate how the proposed evolutionary customization design method is used. The effectiveness of the method is also evaluated through a series of sensitivity analyses.

Copyright © 2007 by American Society of Mechanical Engineers
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Figure 1

Representation of product platform: GBOM

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Figure 2

Procedure of PPCENGINE

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Figure 3

Representation of a structure individual: IBOM

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Figure 4

Steps of tandem evolutionary algorithm

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Figure 5

Crossover operation to two structure individuals

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Figure 6

Mutation operation to a structure individual

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Figure 7

Generic structure of single girder gantry crane

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Figure 8

Platform of the single girder gantry crane

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Figure 9

Evolutionary process for parameter optimization

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Figure 10

Evolutionary process for structure optimization for CRs

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Figure 11

Solutions for different customer requirements

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Figure 12

Effect of population size on structure optimization

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Figure 13

Effect of crossover rate on structure evolution

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Figure 14

Effect of the mutation rate on structure evolution




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