Product platform configuration for product families: Module clustering based on product architecture and manufacturing process

Product family design utilizes platform-based modularity to enable product variety and efficient mass-production. While product platform issues have attracted much attention from both academia and industry, traditional product platform design for product families emphasized the platform-based modula...

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Bibliographic Details
Published inAdvanced engineering informatics Vol. 52; p. 101622
Main Authors Zhao, Shuangyao, Zhang, Qiang, Peng, Zhanglin, Lu, Xiaonong
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.04.2022
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Summary:Product family design utilizes platform-based modularity to enable product variety and efficient mass-production. While product platform issues have attracted much attention from both academia and industry, traditional product platform design for product families emphasized the platform-based modularity that focuses on product structure dimension (functional or non-functional) to realize cost reductions during the design stage. Both the design architecture and manufacturing process are objectives that define product family modularity (PFM). They should be closely coupled with each other for the planning and configuration of platforms. This paper focuses on the product platform configuration by recognizing and utilizing shared product modules for product families. Instead of clustering product modules only based on their design structure, this approach differentiates each product variant, and considers the inherent relationship between product architecture and processing activities. The advantage is that similar components can be grouped and produced on a shared platform, thus benefitting from lower cost and shorter production time. First, both the architecture and manufacturing information of the product variety are captured in matrix format. Then, hierarchical clustering is applied over the components to generate PFM. Finally, a set of platforms are constructed to efficiently process most components of variants.
ISSN:1474-0346
1873-5320
DOI:10.1016/j.aei.2022.101622