Customization Design Knowledge Representation to Support Additive Manufacturing

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 represent the design knowledge.