Prediction of Tool Life in Turning-An Empirical Model Approach

The life of cutting tool in metal cutting plays an important role in the quality and cost of product. In this present study, an empirical model for the prediction of cutting tool life in turning operation is developed. The performance of the metal turning has been studied under varying operating conditions such as speed of cutting, feed rate and depth of cut. This study describes the operation of the experimental system and presents the measured data. The required turning operation is performed on a lathe machine with hardened material used as engine crank pin for work piece and Polycrystalline Cubic Boron Nitride (PCBN) for cutting tool. For developing the required empirical model. Linear Regression, Linear Cross Product Regression, Log Transformed Linear Regression and Log Transformed Cross Product Regression are employed. The values predicted from various empirical models are compared with the experimental values and concluded that which model is best fit for the objective. In general, the metal turning experiments and statistical tests demonstrate that "the empirical models developed in this work are best fit with acceptable range of deviations".