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Progressive methods and technologies are the key to the dynamic development of the automotive and electrical-engineering industries. The processes in sheet-metal processing have changed fundamentally since the end of the 1990s. Previously, the operations such as cutting, punching holes, etc., were carried out separately on different press machines. These operations can now be integrated into a single tool on one press machine due to the development of progressive tools and, especially, the fine-blanking technology. The result is an already completed component that can be used for the assembly. The development of progressive tools must be supported with the FEM simulations of sheet-metal processing that are dependent on their inputs. Therefore, only a correct material model can be expected to provide the right results. For the reasons described above, an experimental program dealing with measuring and fitting the data to the models with orthotropic material properties such as rolled sheets was designed and implemented. The aim is to obtain the material models of rolled sheets made of selected aluminum, copper and steel alloys. One of the objectives of the solution is to provide more efficient and more accurate data fitting because the more accurate the input material data are, the more accurate are the simulation results for sheet-metal processing. The optimization script using the simplex method was made for fitting. The main function of the optimization script is to specify the parameters of the material model iteratively and to compare the simulation results and the mechanical-test results. The script was programmed in the Python environment for the MSC.MARC/MENTAT software using the Johnson-Cook plasticity model. Fitting the data from the pressure tests by Rastegaev at different loading speeds is presented. The difference between the measured and simulated curves is less than 1 %.

Effective preparation of non-linear material models using a programmed optimization script for a nurimerical simulation of sheet-metal processing