Predicting Range of Chip Breaking of 3D Complex Groove Turning Inserts with Neural Networks

Abstract

BP neural networks model which was used to predict the rang of breaking chip of 3D complex groove turning inserts was established, then training and testing of the network was realized with MATLAB, finally ,range of breaking chip of the insert which was designed by the author was predicted. Percentage of accuracy of predicting results reached 91.67% comparing with the chip breaking experiment. This indicates that neural networks can be used to predict rang of breaking chip of turning inserts, so, saving the inserts which is used for cutting experiments and work of experiments, reducing the periodic time of inserts designing and development, increasing the competitive strength of inserts.