A manufacturing-oriented approach for multi-platforming product family design with modified genetic algorithm

  • Authors:

  • Zhuo Liu;Yoke San Wong;Kim Seng Lee

  • Affiliations:

  • Department of Mechanical Engineering, National University of Singapore, Singapore, Singapore 117576;Department of Mechanical Engineering, National University of Singapore, Singapore, Singapore 117576;Department of Mechanical Engineering, National University of Singapore, Singapore, Singapore 117576

  • Venue:
  • Journal of Intelligent Manufacturing
  • Year:
  • 2011

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Abstract

With highly fragmented market and increased competition, platform-based product family design has been recognized as an effective method to construct a product line that satisfies diverse customer's demands while aiming to keep design and production cost-effective. The success of the resulting product family often relies on properly resolving the inherent tradeoff between commonality across the family and performance loss. In this paper, a systematic multi-platforming product family approach is proposed to design a scale-based product family. In the light of the basic premise that increased commonality implies enhanced manufacturing efficiency, we present an effective platform decision strategy to quantify family design configuration using a commonality index that couples design varieties with production variation. Meanwhile, unlike many existing methods that assume a single given platform configuration, the proposed method addresses the multi-platforming configuration across the family, and can generate alternative product family solutions with different levels of commonality. A modified genetic algorithm is developed to solve the aggregated multiobjective optimization problem and an industrial example of a planetary gear train for drills is given to demonstrate the proposed method.