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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Main Authors: Ko, Hyunwoong, Moon, Seung Ki, Otto, Kevin
Other Authors: School of Mechanical and Aerospace Engineering
Format: Conference or Workshop Item
Language:English
Published: 2016
Subjects:
Online Access:https://hdl.handle.net/10356/84284
http://hdl.handle.net/10220/41703
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Institution: Nanyang Technological University
Language: English
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spelling 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
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Design for customization
Affordance
spellingShingle Design for customization
Affordance
Ko, Hyunwoong
Moon, Seung Ki
Otto, Kevin
Customization Design Knowledge Representation to Support Additive Manufacturing
description 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.
author2 School of Mechanical and Aerospace Engineering
author_facet 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
url https://hdl.handle.net/10356/84284
http://hdl.handle.net/10220/41703
_version_ 1681057970423595008