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A STRUCTURED APPROACH TO REDUCE DESIGN ITERATIONS IN ADDITIVE MANUFACTURING

Published online by Cambridge University Press:  27 July 2021

Laura Wirths ,
Matthias Bleckmann  and
Kristin Paetzold
Laura Wirths*
Affiliation:
Bundeswehr University Munich
Matthias Bleckmann
Affiliation:
Bundeswehr Research Institute for Materials, Fuels and Lubricants (WIWeB)
Kristin Paetzold
Affiliation:
Bundeswehr University Munich
*
Wirths, Laura, Bundeswehr University Munich, Department of Aerospace Engineering, Germany, [email protected]

Abstract

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Additive Manufacturing technologies are based on a layer-by-layer build-up. This offers the possibility to design complex geometries or to integrate functionalities in the part. Nevertheless, limitations given by the manufacturing process apply to the geometric design freedom. These limitations are often unknown due to a lack of knowledge of the cause-effect relationships of the process. Currently, this leads to many iterations until the final part fulfils its functionality. Particularly for small batch sizes, producing the part at the first attempt is very important. In this study, a structured approach to reduce the design iterations is presented. Therefore, the cause-effect relationships are systematically established and analysed in detail. Based on this knowledge, design guidelines can be derived. These guidelines consider process limitations and help to reduce the iterations for the final part production. In order to illustrate the approach, the spare parts production via laser powder bed fusion is used as an example.

Keywords

3D printingAdditive ManufacturingDesign for Additive Manufacturing (DfAM)Process modellingDesign engineering
Type
Article
Information
Proceedings of the Design Society , Volume 1: ICED21 , August 2021 , pp. 231 - 240
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), 2021. Published by Cambridge University Press

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