DESIGN TEACHING INTEGRATING ADDITIVE MANUFACTURING CONSTRAINTS

DS 122: Proceedings of the Design Society: 24th International Conference on Engineering Design (ICED23)

Year: 2023
Editor: Kevin Otto, Boris Eisenbart, Claudia Eckert, Benoit Eynard, Dieter Krause, Josef Oehmen, Nad
Author: Kromer, Robin (1); Gruhier, Elise (2)
Series: ICED
Institution: 1: University of Bordeaux,CNRS, Arts et Metiers Science and Technology, Bordeaux INP, I2M Bordeaux, Esplanade des Arts et Metiers, 33405 Talence, France; 2: CNRS, University of Bordeaux, Bordeaux INP, I2M Bordeaux, Esplanade des Arts et Metiers, 33405 Talence, France
Section: Design Methods
Page(s): 1327-1336
DOI number: https://doi.org/10.1017/pds.2023.133
ISBN: -
ISSN: -

Abstract

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 Manufacturing, Requirements, Decision making, Training, Visualisation

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