Product platform two-stage quality optimization design based on multiobjective genetic algorithm

Authors:
Wei Wei;Yixiong Feng;Jianrong Tan;Zhongkai Li
Affiliations:
States Key Lab of Fluid Power Transmission and Control, Zhejiang University, Hangzhou 310027, PR China;States Key Lab of Fluid Power Transmission and Control, Zhejiang University, Hangzhou 310027, PR China;States Key Lab of Fluid Power Transmission and Control, Zhejiang University, Hangzhou 310027, PR China;States Key Lab of Fluid Power Transmission and Control, Zhejiang University, Hangzhou 310027, PR China
Venue:
Computers & Mathematics with Applications
Year:
2009

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Abstract

Product platform design (PFD) has been recognized as an effective means to satisfy diverse market niches while maintaining the economies of scale and scope. Numerous optimization-based approaches have been proposed to help resolve the tradeoff between platform commonality and the ability to achieve distinct performance targets for each variant. In this study, we propose a two-stage multiobjective optimization-based platform design methodology (TMOPDM) for solving the product family problem using a multiobjective genetic algorithm. In the first stage, the common product platform is identified using a nondominated sorting genetic algorithm II (NSGA-II); In the second stage, each individual product is designed around the common platform such that the functional requirements of the product are best satisfied. The design of a family of traction machine is used as an example to benchmark the effectiveness of the proposed approach against previous approachs.