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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Yashchuk, Ivan
VTT Technical Research Centre of Finland
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (3/3 displayed)
- 2019Data-Driven Optimization Of Metal Additive Manufacturing Solutions
- 2019On The Linking Performance Evaluation Toolset To Process-structure-properties Mapping Of Selective Laser Melting 316L Stainless Steel Using Micromechanical Approach With A Length-scale Dependent Crystal Plasticity
- 2019Process-Structure-Properties-Performance Modeling for Selective Laser Meltingcitations
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document
Data-Driven Optimization Of Metal Additive Manufacturing Solutions
Abstract
The freedoms of additive manufacturing (AM) go beyond geometry, with metal AM it is possible to tailor powders, alloys, microstructures as well as processes and manufacturing parameters, to name a few. It is expected that with global data-driven optimization it becomes possible to tailor product and application specific metal AM solutions, subsequently significantly improving the competitiveness of respective AM products. In current work integrated computational materials engineering and machine learning (ML) are utilized to create a workflow for optimization of metal AM solutions. Physics-based models aid in the delivery of ML training data, and the resulting data-driven models are suited for fast and thorough optimization of metal AM products. Use case is presented with different performance metrics targeting critical product material properties which are optimized across the metal AM process to product performance chain.