Prediction of tool life by statistic method in end-milling operation

Abstract

The aim of the this study is to develop the tool life prediction model for P20 tool steel with aid of statistical method, using coated carbide cutting tool under various cutting conditions. This prediction model was then compared with the results obtained experimentally. By using Response Surface Method (RSM) of experiment, first and second order models were developed with 95% confidence level. The tool life was developed in terms of cutting speed, feed rate, axial depth and radial depth, using RSM and design of experiment. In general, the results obtained from the mathematical model are in good agreement with that obtained from the experiment data’s. It was found that the feedrate, cutting speed, axial depth and radial depth played a major role in determining the tool life. On the other hand, the tool life increases with a reduction in cutting speed and feedrate. For end-milling of P20 tool steel, the optimum conditions that is required to maximize the coated carbide tool life are as follow: cutting speed of 140 m/s, federate of 0.1 mm/rev, axial depth of 1.5 mm and radial depth of 2 mm. Using these parameters, a tool life of 39.46 min was obtained.