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DESIGN TEACHING INTEGRATING ADDITIVE MANUFACTURING CONSTRAINTS

Published online by Cambridge University Press:  19 June 2023

Robin Kromer  and
Elise Gruhier
Robin Kromer*
Affiliation:
University of Bordeaux,CNRS, Arts et Metiers Science and Technology, Bordeaux INP, I2M Bordeaux, Esplanade des Arts et Metiers, 33405 Talence, France
Elise Gruhier
Affiliation:
CNRS, University of Bordeaux, Bordeaux INP, I2M Bordeaux, Esplanade des Arts et Metiers, 33405 Talence, France
*
Kromer, Robin, I2M, France, [email protected]

Abstract

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Additive manufacturing (AM) processes are now integrated in industry. Therefore, new methods to design AM parts taken into consideration capabilities and limitations are necessary. It is very difficult for teachers to effectively guide students with ideas emerging from generative design tools. AM requires significant preparation and compromises. Topological optimization is also used depending on requirements. A significant impact on the final part quality is related to the part orientation and geometric dimensions. Therefore, this white paper focuses on detailed design steps to prepare future technicians and engineers to design for additive manufacturing. Active teaching pedagogy guideline is proposed. Students have to think in 3D and use analysis tools to create and validate the optimised design. They use immersive tools to review constraints and model diagnostic algorithm to generate data. Present approaches with design guidelines and tools enable to create AM rules based on it. Questionnaire shows that students need explicit knowledge information. Features recognition and geometry diagnostic are mandatory for complex model. Immersive tool helps to evaluate post-processing. They can now relate AM product-process relationship.

Keywords

Additive ManufacturingRequirementsDecision makingTrainingVisualisation
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 1327 - 1336
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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