Abstract
The article presents a method of determining the anisotropic friction model in metal forming using multilayer artificial neural networks based on experimental data obtained from the pin-on-disk tribometer. The experimental results show that the friction coefficient depends on the measured angle from the rolling direction and corresponds to the surface topography. Both the friction and material anisotropic models were implemented into a finite element (FE) model built using the commercial FE-package ABAQUS/Standard. When both the material and friction anisotropy are taken into account in the finite element analysis, this approach gives the most approximate numerical results to real processes.
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