Knowledge-driven Design for Additive Manufacturing: A Framework for Design Adaptation

Schächtl P, Götz S, Schleich B, Wartzack S (2023)


Publication Language: English

Publication Type: Conference contribution

Publication year: 2023

Publisher: Cambridge University Press

Series: Volume 3: ICED23

City/Town: Cambridge

Pages Range: 2405-2414

Conference Proceedings Title: Proceedings of the Design Society

Event location: Bordeaux FR

URI: https://www.cambridge.org/core/journals/proceedings-of-the-design-society/article/knowledgedriven-design-for-additive-manufacturing-a-framework-for-design-adaptation/834D2049A41B65FC7CDFFCB459DD655A

DOI: 10.1017/pds.2023.241

Open Access Link: https://www.cambridge.org/core/journals/proceedings-of-the-design-society/article/knowledgedriven-design-for-additive-manufacturing-a-framework-for-design-adaptation/834D2049A41B65FC7CDFFCB459DD655A

Abstract

Due to the high freedom of design, additive manufacturing (AM) is increasingly substituting conventional manufacturing technology in several sectors. However, the knowledge and the awareness for the suitable design of additively manufactured components or assemblies ensuring manufacturability and fully realizing its potential is still lacking. In recent years, approaches and tools have emerged that allow the incorporation of existing knowledge of Design for Additive Manufacturing (DfAM) into the design process. Nevertheless, these applications mostly do not consider the formalisation of both restrictive and opportunistic DfAM guidelines for their integration in design tools.


Therefore, the following article presents a framework for the knowledge-driven adaptation of existing designs in the context of DfAM within an expert system. The novelty of the presented approach lies in the interdisciplinarity between the formalization of design guidelines and their integration and consideration within computeraided design for the semi-automated adaptation of functional non-assembly mechanisms. The application of the presented framework to a case study manufactured via Fused Layer Modeling (FLM) illustrates the applicability and benefits.

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How to cite

APA:

Schächtl, P., Götz, S., Schleich, B., & Wartzack, S. (2023). Knowledge-driven Design for Additive Manufacturing: A Framework for Design Adaptation. In Design Society (Eds.), Proceedings of the Design Society (pp. 2405-2414). Bordeaux, FR: Cambridge: Cambridge University Press.

MLA:

Schächtl, Paul, et al. "Knowledge-driven Design for Additive Manufacturing: A Framework for Design Adaptation." Proceedings of the 24th International Conference on Engineering Design (ICED23), Bordeaux Ed. Design Society, Cambridge: Cambridge University Press, 2023. 2405-2414.

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