Experimental design and artificial neural network model for turning the 50CrV4 (SAE 6150) alloy using coated carbide/Cermet cutting tools

In this experimental study, the 50CrV4 (SAE 6150) steel was subjected to the machining tests with coated carbide and cermet cutting tools in a turning operation. The tests were carried out at various cutting speeds, feed rates and cutting depths. In the light of these parameters, cutting forces and surface-roughness values were determined. Three components (Fa, Fr and Fc) of the cutting forces were measured during the tests using a dynamometer, while the machined surface-roughness values were determined using a surface roughness measuring unit. A multiple regression analysis and experimental design were performed statistically. The measured surface-roughness values were used for the modeling with an artificial neural network system (ANNS). The relations between the cutting forces and the surface-roughness values were also defined.