Abstract
Since decades, additive manufacturing (AM) is sparking interest in industry and research laboratories. The assets of this process and its associated technologies no longer needs to be proven: part shape freedom, Buy-to-Fly ratio reduction, integration of lattice structures, etc. As these new technologies implies new expertise, new profiles have then emerged in the value chain. Among them, the CAD/CAM (Computer Aided Design & Manufacturing) engineers become a key player. However, these experts still need training as, for some technologies, they still proceed by trial and error, therefore processing rules would merit harmonization. This research strives to understand the practices of AM designers, through the analysis of their actions and their underlying selection criteria. To do so, the knowledge they produce and mobilize in a work situation is the start of this work.
This article proposes then a knowledge-based AM approach to represent key concepts and to model action-oriented knowledge. After a state of the art related to knowledge elicitation, elicitation techniques applied to the AM context are explained. A knowledge model applied to Electron Beam Melting process is presented subsequently as a solution.
The methodology combines procedural and conceptual knowledge, highlights action rules. It has the benefit of being a dynamic decision-making support for CAD/CAM engineering, as well as modular and easy to update. It could likewise be applicable to manufacturing activities but also to many processes.
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Grandvallet, C., Pourroy, F., Vignat, F. (2023). Towards a Knowledge-Based Additive Manufacturing Approach. In: Gerbino, S., Lanzotti, A., Martorelli, M., Mirálbes Buil, R., Rizzi, C., Roucoules, L. (eds) Advances on Mechanics, Design Engineering and Manufacturing IV. JCM 2022. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-15928-2_42
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