Use of Artificial Neural Networks to Investigate the Surface Roughness in CNC Milling Machine

In order to sustain in the global market competitiveness, maintaining the quality of the component plays a key role to satisfy the customer requirements. Quality can be determined by its surface roughness or by its surface finish. In this work, optimization of machine tool parameters is carried out for CNC milling machine. Machine tools can be used effectively by considering the optimal cutting parameters like speed, feed, and depth of cut. However these parameters greatly influence on the material removal rate and surface finish. This paper aims to investigate the surface roughness values at various speeds, feed and depth of cut conditions by using Artificial Neural Networks. ANN results show that there is no significant difference between the experimental values and predicted roughness values. From these results, conclude that the ANN is best suitable and accurate for solving the cutting parameter optimization.