A manufacturing-oriented approach for multi-platforming product family design with modified genetic algorithm |
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Authors: | Zhuo Liu Yoke San Wong Kim Seng Lee |
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Affiliation: | (1) Nanyang Technological University, Singapore, Singapore;(2) Pennsylvania State University, University Park, PA, USA;(3) University of Oklahoma, Norman, OK, USA |
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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. |
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