Artificial Intelligence Based Surface Roughness Prediction Modeling for Three Dimensional End Milling
Surface roughness is an index which determines the quality of machined products and is influenced by the cutting parameters. In this paper, the average surface roughness Ra (value) for Aluminum after ball end milling operation has been measured. 84 experiments have been conducted varying cutter axis inclination angle, spindle speed (S rpm), feed rate (fy mm/min), radial depth of cut (feed fx mm), axial depth of cut (t mm) in order to find Ra. This data has been divided into two sets on a random basis; 68 training data set and 16 testing data set. The training data set has been used to train different ANN and ANFIS models for Ra prediction. And testing data set has been used to validate the models.