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NEURAL NETWORKS IN DESIGN TO EXPLOIT THE POTENTIAL OF ADDITIVE MANUFACTURING TECHNOLOGIES

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Description

Abstract:

Additive manufacturing offers the possibility of converting digital prototypes into real structures as quickly as possible thanks to the special feature of tool-free manufacturing. However, this process can only be used at optimum speed if bottlenecks can be effectively avoided. One of these is the design process. In the field of AM in particular, more and more powerful software solutions have recently been published which allow to accelerate the Design for additive Manufacturing, including most Computer-Aided-Design-tasks. In many areas, therefore, attempts are already being made to automate as much steps as possible, not infrequently using neural networks and artificial intelligence. This article uses the example of an automated structural optimization of a chair to demonstrate, why the use of neural networks in the design process is useful to further link the fields of conventional topology optimization and generative design to reduce product development time.

Reference: ADD-2022-014

Title: NEURAL NETWORKS IN DESIGN TO EXPLOIT THE POTENTIAL OF ADDITIVE MANUFACTURING TECHNOLOGIES
Author(s): M. Ott, N. Meihöfener, R. Koch
DOI: 10.48447/ADD-2022-014
Year of publication: 2022
Publication type: conference paper (PDF)
Language: German
Keywords: Artificial Intelligence; Neuronal Networks; 3D printing; Design for additive Manufacturing

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Die Ausbildung von Eigenspannungen nach der additiven Fertigung und nach dem Kugelstrahlen eines ferritischen Stahls

Publication type: conference paper (PDF)

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Author(s): J.-P. Brüggemann, L. Risse, S. C. Woodcock, G. Kullmer, H. A. Richard

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