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Investigating designers’ preferred learning media to design for additive manufacturing

Published online by Cambridge University Press:  16 May 2024

Martins Obi ,
Patrick Pradel ,
Matt Sinclair ,
Richard Bibb  and
Mark Evans
Martins Obi*
Affiliation:
Coventry University, United Kingdom
Patrick Pradel
Affiliation:
Loughborough University, United Kingdom
Matt Sinclair
Affiliation:
Edinburgh Napier University, United Kingdom
Richard Bibb
Affiliation:
Nottingham Trent University, United Kingdom
Mark Evans
Affiliation:
Loughborough University, United Kingdom
*
[email protected]

Abstract

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In this exploratory study, designers’ preferred learning media in learning to design for Additive Manufacturing was explored. Furthermore, by deploying an online survey questionnaire, factors such as years of experience, and the categories of products designed were explored to understand how they influence designers’ learning media with a response from 201 respondents. The results show that designers have learned how to design for AM through experimentation and present the first step towards developing an appropriate Design for Additive Manufacturing knowledge dissemination approach.

Keywords

design for additive manufacturingdesign knowledgelearning mediaknowledge disseminationdesign practice
Type
Design for Additive Manufacturing
Information
Proceedings of the Design Society , Volume 4: DESIGN 2024 , May 2024 , pp. 1779 - 1788
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2024.

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