Intelligent Prediction Platform of Lathe Machine Based on Back Propagation Neural Network

Abstract

For the CNC machine tool, the processing parameters of cutting are a key factor to affect the manufacturing accuracy and tool wear. However, this study proposes a prediction system based on neural network algorithm to estimate the wear of turning tool. For neural network algorithm, the processing parameters, the cutting speed, feed rate and material removal rate are investigated as the input parameters of the BNN. The output parameters of the BNN are the wear of turning tool and the surface accuracy of workpiece. Experimental results showed that the turning cutting wear of prediction accuracy compared with the experiment is 93.44%. The max error of cutting wear between the prediction and the experiment is $15\mu \mathrm {m}.$