Product family platform selection using a Pareto front of maximum commonality and strategic modularity

被引:0
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作者
Kyle Baylis
Guanglu Zhang
Daniel A. McAdams
机构
[1] Texas A&M University,Department of Mechanical Engineering
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Product family design; Product platform; Modular design; Design structure matrix (DSM); Component clustering;
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摘要
Product family design offers a cost-effective solution for providing a variety of products to meet the needs of diverse markets. At the beginning of product family design, designers must decide what can be shared among the product variants in a family. Optimal design formulations have been developed by researchers to find one optimal component sharing solution based on commonality, cost or technical performance of a product family. However, these optimization methods may not be able to apply in consumer product design because some metrics (e.g., visual appeal and ergonomics) of a consumer product cannot be formulized. In this paper, we suggest a tradeoff between commonality and the quality of the modular architecture in product family platform selection. We introduce a method for designers to identify multiple component sharing options that lie along a Pareto front of maximum commonality and strategic modularity. The component sharing options along the Pareto front can be evaluated, compared, and further modified. We demonstrate the method using a case study of product family platform selection of high-end and low-end impact drivers and electric drills. In the case study, the quality of the modular architecture is evaluated using a design structure matrix (DSM) for each of product variants. Three architectures along the Pareto front with maximum commonality, optimal modularity, and a balanced solution of the two metrics are highlighted and further examined to validate the effectiveness of our method.
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页码:547 / 563
页数:16
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