The project “AI-based data collection and optimisation of additive manufacturing process parameters for titanium-based materials” collects process parameters of Laser Powder Bed Fusion (LPBF) processes from scientific literature using a self-developed software for data mining. It will develop new or adapt existing data schemas, include datasets from own LBPF experiments and will compare the completeness of data sets stored in the own lab with those typically provided in literature. Thus, as a major outcome it determines if the typical literature data in this field is sufficient for modelling and machine learning purposes of the community. The project is part of the project-oriented funding within the Helmholtz Association. The project integrates seamlessly with IUC02 extending and supplementing the current use case of creep reference datasets with a use case for data from advanced processing techniques.
| Acronym: | |
| Website: | https://www.helmholtz.de/en/research/research-fields/information/materials-systems-engineering/ |
| Contact: | Prof. Dr.-Ing. Florian Pyczak, head of department Metal Physics, Helmholtz-Zentrum Hereon |
| DFG Classification: | 4.31-02 - Materials in Sintering Processes and Generative Manufacturing Processes 4.31-04 - Mechanical Properties of Metallic Materials and their Microstructural Origins |
| Material/ Methodology: | Titanium alloys / Data Mining, Additive Manufacturing |
| Engagement: | 2 core groups planned to be extended to 4 core groups |
NFDI-MatWerk
Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under the National Research Data Infrastructure – NFDI 38/1 – project number 460247524.
NFDI-MatWerk
Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under the National Research Data Infrastructure – NFDI 38/1 – project number 460247524.
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