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shaped aluminium with cryotechnology

Digital materials and processes

Digitalization of manufacturing processes includes digitalization of material data. In recent years, LKR Leichtmetallkompetenzzentrum Ranshofen GmbH has continuously driven a digitalization process of materials information. The aim was the development of data-driven models for predicting process-structure-property relations. Improving the product quality and reduction of costly trials is one the main goals for large, as well as small scale semi-industrial production areas. As a first step, LKR focuses on forming processes at both lab- and semi-industrial scales. The long-term strategy is to include and link each individual step of a production chain starting from raw materials to finished products.

One example of recent activities is the modeling of the material flow behavior crucial for numerical process simulations. Together with national experts in data analytics, LKR is developing models for predicting the stress-strain curves using the algorithms of machine learning. Going further, the specific focus is given on integrating physics-based knowledge into data-driven modeling and generating so-called hybrid models for materials science.

 

Publications

  • E. Kabliman, A.H. Kolody, M. Kommenda, G. Kronberger. Prediction of flow curves for aluminum alloys using symbolic regression, AIP Conferences Proceedings 2113 (2019), 180009. doi.org/10.1063/1.5112747