Abstract
Now a day’s most of turning operations are performed with carbide inserts. The inserts are also available with different configurations and coating materials. This work focuses on developing empirical models for prediction of surface roughness in hard turning with three different types of inserts namely physical vapor deposition (PVD), chemical vapor deposition (CVD) and uncoated (TTS) inserts. The effects of process parameters namely cutting speed, feed, and depth of cut on surface roughness have been studied while machining AISI 52100 steel. A central composite face centered design (CCF) was employed to conduct the experiments. One of the most important data mining techniques, linear regression analysis, is applied in developing the empirical models. From the models it can be observed that the better surface finish is obtained with physical vapor deposition (PVD) inserts followed by chemical vapor deposition (CVD) inserts and uncoated (TTS) inserts.
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