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CLC number: TH12

On-line Access: 2015-01-04

Received: 2014-09-02

Revision Accepted: 2014-12-08

Crosschecked: 2014-12-25

Cited: 4

Clicked: 2579

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Wei WEI

http://orcid.org/0000-0002-0813-5167

Ang LIU

http://orcid.org/0000-0002-6300-5744

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Journal of Zhejiang University SCIENCE A 2015 Vol.16 No.1 P.1-10

http://doi.org/10.1631/jzus.A1400263


A multi-principle module identification method for product platform design


Author(s):  Wei Wei, Ang Liu, Stephen C. Y. Lu, Thorsten Wuest

Affiliation(s):  School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China; more

Corresponding email(s):   weiwei@buaa.edu.cn, angliu@usc.edu

Key Words:  Module identification, Modularization principles, Multi-objective optimization, Improved strength Pareto evolutionary algorithm (ISPEA2), Turbo expander


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Wei Wei, Ang Liu, Stephen C. Y. Lu, Thorsten Wuest. A multi-principle module identification method for product platform design[J]. Journal of Zhejiang University Science A, 2015, 16(1): 1-10.

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Abstract: 
In today’s competitive global business environment, platform strategy presents an opportunity for manufacturing companies to juggle increased customer demand for customized products and the inherited complexity and increased development cost that comes with it. The goal of this paper is to support module identification as an essential part of a module-based platform strategy approach. Based on various existing methods, this paper abstracted three principles, which include an internal clustering principle, an external independence principle, and an overall stability principle. The three principles should be holistically considered, and be simultaneously satisfied during the module identification. Both conceptual and mathematical modeling of the proposed multi-principle module identification method are elaborated. Then an improved strength Pareto evolutionary algorithm (ISPEA2) is used to address the multi-principle module identification problem and find the Pareto-optimal set. A fuzzy compromise selection method base on fuzzy set theory is also used to select the best compromise Pareto solution. An industrial case study in a turbo expander manufacturing company is provided to illustrate practical applications of the research. Finally, the result obtained by the proposed approach is compared with other established optimization approaches.

支持产品平台设计的多准则模块划分方法

目的:研究多准则约束下的产品模块划分方法,为企业建立稳健的模块化产品平台奠定基础。
方法:采用改进的多目标进化算法对建立的多准则模块划分数学模型求解,并采用模糊集合评价机制进行最优解的寻取,得到基于多准则模块划分方法的产品模块划分结果。
结论:通过改进的多目标进化算法求解多准则模块划分模型,能够得到有效支持产品平台设计的产品模块划分方案。通过与已有优化方法的比较验证了本文提出的多准则模块划分方法的优越性。

关键词:块划分;模块化准则;多目标优化; 改进的强度帕累托进化算法;透平膨胀机

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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