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FEATURE-BASED METHOD TO FORMALISE ADDITIVE MANUFACTURING RELATED DATA AT THE MESOSCALE BASED ON A MEREOTOPOLOGICAL DESCRIPTION

Published online by Cambridge University Press:  19 June 2023

Chloe Douin ,
Elise Gruhier ,
Robin Kromer ,
Olivier Christmann  and
Nicolas Perry
Chloe Douin*
Affiliation:
I2M UMR 5295, Arts et Métiers ParisTech, Esplanade des Arts et Métiers, 33400 Talence, France
Elise Gruhier
Affiliation:
I2M UMR 5295, Arts et Métiers ParisTech, Esplanade des Arts et Métiers, 33400 Talence, France
Robin Kromer
Affiliation:
Univ. Bordeaux, I2M UMR 5295, 33500 Gradignan, France
Olivier Christmann
Affiliation:
LAMPA, Arts et Metiers ParisTech, 2 Boulevard du Ronceray, 49000 Angers, France
Nicolas Perry
Affiliation:
I2M UMR 5295, Arts et Métiers ParisTech, Esplanade des Arts et Métiers, 33400 Talence, France
*
Douin, Chloe, I2M UMR 5295, Arts et Métiers ParisTech, Esplanade des Arts et Métiers, 33400 Talence, France, France, [email protected]

Abstract

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Research on additive manufacturing has highlighted methods and guidelines to optimise the design process and improving finished product quality. There is still room for improvement in making AM as reliable as more traditional processes when considering industrial use. In terms of manufacturing, managing print parameters properly can improve reproducibility and repeatability of a part, in addition to its fidelity to the basic geometric model. However, a topological optimised geometry requires more than good parameterisation. Efforts are therefore being made to formalise knowledge so that it is explicit and accessible to designers. This paper proposes an approach based on the spatio-temporal evolution of a geometry during printing to quantify data at the meso scale. Previous studies have been conducted on the description of features in time, space and space-time, and on the influence of their arrangement within a part. Building on this work, a parameterised test specimen was designed to measure the quantitative impact of these arrangements on the final product. The method is then presented and illustrated through a case study to help the designer with quantitative predictive values of geometric parameters.

Keywords

Additive ManufacturingDesign for Additive Manufacturing (DfAM)Design methodsMereotopologyDesign of Experiments
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 1865 - 1874
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), 2023. Published by Cambridge University Press

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