Data-based optimisation of metallurgical phenomena - recrystallisation, texture & residual stresses
Data-T-Rex aims to develop sustainable, intelligent and self-optimising manufacturing processes for high-quality light metal products. The focus is on the data-based optimisation of forming and heat treatment processes based on the metallurgical phenomena of recrystallisation, texture and residual stresses. Data-T-Rex takes into account a wide range of production routes relevant to the light metal industry – starting with the casting process, via the forming process to the various heat treatments.
In this context, the project offers the possibility to apply new tools to existing data through machine learning. In addition, interactions between the process steps can be better revealed, for example the precise relationships between casting, homogenisation, extrusion and heat treatment.
The development of a data-based process chain optimisation for light metal products planned in the project contributes to more efficient and sustainable production, as the resulting optimisation of manufacturing processes can achieve an avoidance of production waste and save energy.
Project manager Carina Schlögl from the LKR: "Sustainable optimisations in metal processing are possible where there is perfect interaction between material and process. The application of artificial intelligence in combination with highly innovative material characterisation offers particularly great innovation potential in this regard."