Project runtime: 01.06.2023 – 31.05.2026
2024-02-29_BMBF_KickOff_InSuKa
The manufacture of elastomer products is based to a large extent on empirical knowledge of production recipes and processing. Companies therefore often replicate existing recipes, which are optimised in an iteration loop. The central steps of this iteration loop are the production of compounds and moulded parts, the determination of the compound properties and the subsequent testing of semi-finished products or products. Only after these steps can optimisation take place. As a result, it is difficult to integrate fundamentally new raw materials and technological innovations in further developments. Because of the high costs involved, the use of new raw materials is often out of the question for end users. As a consequence, innovation opportunities in product development are often missed. To change this, conceptual developments towards a consistent digitalisation of data and an algorithmisation of predictive process and material models are to be advanced. The research activities focus on the creation of ontologies suitable for industry as a basis for the structured treatment of material and process data. In particular, the implementation of existing models will be analysed to predict the influence of mixing process parameters and formulation components on the properties of rubber compounds and rubber products made from them. This analysis is carried out with the help of algorithms for computer-aided optimisation. In addition, numerous characterisation methods (e.g. imaging methods) will be consistently automated and implemented by the use of ontologies. Both the analysis and the integration of the characterisation methods should help to use the prediction quality of the process-accompanying characterisation much more efficiently and quickly to optimise the mixing process and recipe in the future.
