The 3-year project has been approved by the Vlaio evaluation committee after receiving highly positive comments of the expert reviewers.
Our project “HSLAi” has been approved for funding by Vlaio
Within the context of digitalising our metallurgical research, a project proposal for regional funding was submitted to Vlaio together with ArcelorMittal Belgium. This project targets the investigation of novel Process-microStructure-Property correlations for future metallurgies by combining our unique bulk combinatorial experimentation with the use of Artificial Intelligence (AI) and Machine Learning (ML). The 3-year project has been approved by the Vlaio evaluation committee after receiving highly positive comments of the expert reviewers.
The combinatorial experimentation will allow to generate the “extensive and novel metallurgical dataset” that is needed for the high-dimensional parameter space. The modern machine learning techniques will be tuned and applied to extract much more information from time-series (“2D” data) and microstructural images (“3D” data) compared to what is realised today via manual and semi-automatic analysis and human interpretation. As a result, the project aims to discover and understand new influencing microstructural parameters in novel steel grades. This will enable to establish advanced Process-Microstructure-Property links as such targeting first dedicated AI/ML based correlative tools.
“Our expectations for this project are really high. This project can make a huge leap in the way metallurgical research is done and as such should allow to unravel advanced correlations in the P-S-P triangle to a much higher degree than ever before”
