Customization Design Knowledge Representation to Support Additive Manufacturing
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 approache...
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sg-ntu-dr.10356-842842020-09-24T20:12:36Z Customization Design Knowledge Representation to Support Additive Manufacturing Ko, Hyunwoong Moon, Seung Ki Otto, Kevin School of Mechanical and Aerospace Engineering Proceedings of the 1st International Conference on Progress in Additive Manufacturing (Pro-AM 2014) Singapore Centre for 3D Printing Design for customization Affordance 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. Published version 2016-12-06T08:03:45Z 2019-12-06T15:42:02Z 2016-12-06T08:03:45Z 2019-12-06T15:42:02Z 2014 Conference Paper Ko, H., Moon, S. K., & Otto, K. (2014). Customization Design Knowledge Representation to Support Additive Manufacturing. Proceedings of the 1st International Conference on Progress in Additive Manufacturing (Pro-AM 2014), 13-18. https://hdl.handle.net/10356/84284 http://hdl.handle.net/10220/41703 10.3850/978-981-09-0446-3_098 en 6 p. application/pdf |
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Design for customization Affordance |
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Design for customization Affordance Ko, Hyunwoong Moon, Seung Ki Otto, Kevin Customization Design Knowledge Representation to Support Additive Manufacturing |
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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. |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Ko, Hyunwoong Moon, Seung Ki Otto, Kevin |
format |
Conference or Workshop Item |
author |
Ko, Hyunwoong Moon, Seung Ki Otto, Kevin |
author_sort |
Ko, Hyunwoong |
title |
Customization Design Knowledge Representation to Support Additive Manufacturing |
title_short |
Customization Design Knowledge Representation to Support Additive Manufacturing |
title_full |
Customization Design Knowledge Representation to Support Additive Manufacturing |
title_fullStr |
Customization Design Knowledge Representation to Support Additive Manufacturing |
title_full_unstemmed |
Customization Design Knowledge Representation to Support Additive Manufacturing |
title_sort |
customization design knowledge representation to support additive manufacturing |
publishDate |
2016 |
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https://hdl.handle.net/10356/84284 http://hdl.handle.net/10220/41703 |
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1681057970423595008 |