Project Details
Projekt
Inverse optimisation of the die casting straightening process chain with consideration of uncertainties
Applicants
Dr.-Ing. Christoph Hartmann; Professor Dr.-Ing. Philipp Lechner; Professor Dr.-Ing. Wolfram Volk
Subject Area
Primary Shaping and Reshaping Technology, Additive Manufacturing
Term
since 2025
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 558559575
The production of aluminium structural components using high-pressure die casting has established itself in recent years, particularly in vehicle production, and is currently experiencing increasing demand in the context of mega- and gigacasting. In order to adjust the material properties of the structural components, such as strength, the workpiece then undergoes heat treatment. Multiple process parameters in this process chain influence the residual stress state of the components and ultimately their distortion. As the geometric requirements of structural components are crucial in addition to the mechanical properties, the geometric accuracy is improved in a forming process. This may be followed by further finishing processes. The aim of phase I of this research project is to model the die casting and forming process chain in an inversely solvable way and to be able to take uncertainties into account. This is to be implemented and validated using a scaled process chain for structural components. These solvers enable the various process steps to be optimised based on the end product, i.e. based on the requirements of the structural component. A key objective is the backward propagation of uncertainties, which also allows the robustness of the process chain to be analysed. The aim of process chain optimisation is to reduce the stochastic components of the distortion to a minimum and thus to be able to use only one constant forming process to improve the components geometrical accouracy. These modelling approaches should therefore not only make it possible to optimise the process chain with respect to the mechanical properties and geometric accuracy, but also offer the possibility of including the total process time per component and the robustness of the process chain into the optimisation.
DFG Programme
Priority Programmes
Co-Investigator
Dr.-Ing. Joel Schukraft
