Performance of coated carbide cutting tool while machining aluminium alloy and mild steel

This paper discuss of the performance of coated carbide cutting tools in milling by investigating through the surface roughness. Response Surface Methodology (RSM) is implemented to model the face milling process that are using four insert of coated carbide TiNC as the cutting tool and mild steel AISI1020 and aluminium alloy AA6061 as materials due to predict the resulting of surface roughness. Data is collected from HAAS CNC milling machines were run by 15 samples of experiments for each material using DOE approach that generate by Box-Behnkin method due to table design in MINITAB packages. The inputs of the model consist of feed, cutting speed and depth of cut while the output from the model is surface roughness. Predictive value of surface roughness was analyzed by the method of RSM. The model is validated through a comparison of the experimental values with their predicted counterparts. A good agreement is found where from the RSM approaches show the 81.76% accuracy for mild steel and 80.09% accuracy for aluminium alloy which reliable to be use in Ra prediction and state the feed parameter is the most significant parameter followed by depth of cut and cutting speed influence the surface roughness. For Aluminium Alloy AA6061, the performance of coated carbide cutting tool is better than Mild Steel AISI1020. This project also identified that the increasing of surface roughness, Ra is proportional to the increasing of depth of cut and feed but inversely proportional to the increasing of cutting speed for both of the Aluminum Alloy (AA6061) and Mild Steel (AISI1020). The proved technique opens the door for a new, simple and efficient approach that could be applied to the calibration of other empirical models of machinin