Thin-film sensors for data-driven concentricity prediction in cup backward extrusion

Abstract

The manufacture of precise metal components by cold forging poses serious challenges to the process reliability under unstable process conditions. The detection of geometrical imperfections, such as concentricity deviations, is necessary for the operator to adjust the forging tool rack properly. In this paper, a novel piezoelectric thin-film sensor disc is introduced to detect such concentricity deviations based on the measurement of eccentric load, that is arising from elastic punch deformation. Experimental results showed, that the concentricity deviation of the produced parts efficiently can be predicted by processing measured force data using a support vector regression algorithm.