About this Abstract |
Meeting |
1st World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022)
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Symposium
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First World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022)
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Presentation Title |
Hybrid Approach Combining Machine Learning and Finite Element Simulation for Process and Material Optimization |
Author(s) |
Pierre-Yves Lavertu, Emilie Storms |
On-Site Speaker (Planned) |
Pierre-Yves Lavertu |
Abstract Scope |
In today’s industrial context, the pace of innovation is constantly accelerating while development cycles are shortening. In this framework, additive manufacturing and Machine Learning (ML) are combined in order to provide a cutting-edge solution.
Dimensional stability and performance of 3D printed parts are highly dependent on the material selection and process parameters. Machine learning algorithms can be built to assess correlation between the process and material parameters to accelerate material selection and product development. The built ML algorithms can be used to determine optimal parameters which minimize warpage and maximize structural performance (stiffness, strength, durability, …). ML algorithms can also be used for material data enrichment minimizing testing cost while optimizing coverage of the design space. |
Proceedings Inclusion? |
Undecided |