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G-DfAM: a methodological proposal of generative design for additive manufacturing in the automotive industry

Article dans une revue avec comité de lecture
Auteur
BRIARD, Tristan
ZAMARIOLA, Nicolo
320072 Arcelor Mittal
ccSEGONDS, Frederic
127758 Laboratoire Conception de Produits et Innovation [LCPI]

URI
http://hdl.handle.net/10985/19275
DOI
10.1007/s12008-020-00669-6
Date
2020
Journal
International Journal on Interactive Design and Manufacturing

Résumé

Metal additive manufacturing is an emerging technology in the industry and has a great potential. Moreover, new technologies like generative design can maximize this potential by computing complex optimized parts for additive manufacturing solutions. However, there is a lack of methodologies combining both recent and promising technologies. This paper first establishes a state of the art of design for additive manufacturing (DfAM) and generative design methodologies. Then it proposes a generic workflow for generative design tools and it proposes a challenge approach to develop a new DfAM method including generative design tools. Finally, a global 4-step methodology maximizing the potential of generative design and additive manufacturing, the G-DfAM method, is presented and validated through an automotive use case.

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LCPI_IJIDM_2020_BRIARD.pdf
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  • Laboratoire Conception de Produits et Innovation (LCPI)

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