Circular economy in automotive engineering.

The overarching goal of the joint project is to increase the lightweight construction potential of aluminum alloys for mobility applications while at the same time significantly improving sustainability, climate friendliness and cost efficiency. To increase sustainability and climate friendliness, secondary aluminum should be used from various sources, but in particular from end-of-life (EoL) scrap from vehicles. For this purpose, the entire process chain, starting from the EoL material sorting, the alloy production and composition through the processing to the component, must be considered and adapted and thereby built up across locations and digitally networked. Corresponding increases in efficiency can only be achieved through this holistic view of all steps along the process chain. Furthermore, it should be proven that through targeted adaptation of the entire process chain, the use of EoL material is also possible and cost-effectively mapped for highly stressed aluminum components.

The focus is on the further development of the sorting technology for EoL aluminum scrap based on the LIBS (Laser-Induced-Breakdown-Spectroscopy) process with regard to sorting and cost efficiency in order to achieve the most reliable sort and alloy-specific separation possible. In order to set up an adapted, cost-efficient process chain, the consequences of previously unknown increased concentrations of previously undesirable accompanying elements should also be researched. Specifications for modifying the alloy composition are then derived from this. In this context, it must be ensured that the property profile of the alloys does not deteriorate significantly. The process parameters of the cost-efficient shaping processes press hardening and direct forging must also be adapted to the secondary alloys. In the joint project, an overarching collaboration along the entire digitized and networked process chain is being implemented to increase the lightweight construction potential. Furthermore, methods and modeling approaches are researched and validated, with which the information and knowledge from the entire process chain are summarized in order to enable decision support in the case of inevitable target conflicts with regard to the different property profiles. The resulting digital process chain not only includes data integration, but also superordinate models for evaluating different scenarios.