Computer simulation plays a crucial role in the designing of sheet metal stamping processes for the prediction of process output, before try-out die sets are manufactured. Different commercial software packages are available on the market for sheet forming simulation, but their accuracy can vary, depending on the selection of the pre-processing parameters and on their formulation. Software benchmarking can be used to select the most appropriate package for a given application. Calibration, i.e. the inverse determination of the correct set of pre-processing parameters, can be used for improving the prediction accuracy. The scientific literature on numerical simulations of sheet metal forming processes presents some examples of software calibration and very few examples of benchmarking. The literature generally neglects a critical and important issue: the inherent variability of real forming processes. In this work, the experimental results of two similar multi-stage deep drawing processes are presented and compared to the simulation output of two popular software packages used in the industry. Statistical methods for benchmarking and calibration are proposed. The paper demonstrates how benchmarking can be misleading if process variability is not considered.

A Method for Benchmarking of FEM Packages for Multi-Stage Sheet Metal Forming Simulations

Strano M.;Semeraro Q.;
2022-01-01

Abstract

Computer simulation plays a crucial role in the designing of sheet metal stamping processes for the prediction of process output, before try-out die sets are manufactured. Different commercial software packages are available on the market for sheet forming simulation, but their accuracy can vary, depending on the selection of the pre-processing parameters and on their formulation. Software benchmarking can be used to select the most appropriate package for a given application. Calibration, i.e. the inverse determination of the correct set of pre-processing parameters, can be used for improving the prediction accuracy. The scientific literature on numerical simulations of sheet metal forming processes presents some examples of software calibration and very few examples of benchmarking. The literature generally neglects a critical and important issue: the inherent variability of real forming processes. In this work, the experimental results of two similar multi-stage deep drawing processes are presented and compared to the simulation output of two popular software packages used in the industry. Statistical methods for benchmarking and calibration are proposed. The paper demonstrates how benchmarking can be misleading if process variability is not considered.
2022
Proceedings of the 25th International Conference on Material Forming, ESAFORM 2022
Benchmarking, Calibration, Sheet Metal, Simulation, Variability
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1223046
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