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Tensa, Melissa; Edmonds, Katherine; Ferrero, Vincenzo; Mikes, Alex; Soria Zurita, Nicolas; Stone, Rob; DuPont, Bryony

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Abstract:

The objective of this research is to support DfX considerations in the early phases of design. In order to do conduct DfX, designers need access to pertinent downstream knowledge that is keyed to early stage design activities and problem knowledge. Product functionality is one such ?key? connection between early understanding of the design problem and component choices which dictate product performance and impact, and repositories of design knowledge are one way to archive such design knowledge. However, curation of design knowledge is often a time-consuming activity requiring expertise in product modeling. In this paper, we explore a method to automate the populating of design repositories to support the overall goal of having up-to-date repositories of product design knowledge. To do this, we mine information from an existing repository to better understand the relationships between the components, functions, and flows of products. The resulting knowledge can be applied to automate functional decompositions once a product?s components have been entered and thus reliably provide that ?key? between early design activities and the later, component dependent characteristics.

Keywords:

Functional modelling, Design for X (DfX), Machine learning, Data-driven design, Product respository