Conference Proceedings

CUSTOMIZATION DESIGN KNOWLEDGE REPRESENTATION TO SUPPORT ADDITIVE MANUFACTURING

Hyunwoong Ko, Seung Ki Moon, Kevin Otto, CC Kai (ed.), YW Yee (ed.), TM Jen (ed.), L Erjia (ed.)

PROCEEDINGS OF THE 1ST INTERNATIONAL CONFERENCE ON PROGRESS IN ADDITIVE MANUFACTURING | RESEARCH PUBLISHING SERVICES | Published : 2014

Abstract

The unique technologies of Additive Manufacturing (AM) have enabled new opportunities for product customization by eliminating the conventional design for manufacturing (DFM) constraints. To address the customization issues within a design for AM (DFAM) framework, this paper defines 2-step approaches: (1) representing design knowledge for customization and (2) systemically reflecting customized design factors to DFAM frameworks. As a start of the study, this paper represents design knowledge concerning customer's desired product use, customer's perceived preference, and product's functional features affecting design factors. We use Affordance Theory and Finite State Automata (FSA) to represe..

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University of Melbourne Researchers