Analysis and compensation of workpiece errors in turning

Abstract

A new method for workpiece error analysis and compensation in turning is introduced. It is known that the workpiece error consists of two parts: machine tool error (including the geometric error and thermal-induced error) and cutting-induced error. The geometric error of the machine tool is independent on machining operation and, hence, can be measured off-line using a fine-touch sensor with a Q-setter (FTS-Q) (also called quick touch setter). The thermal error of the machine tool is dependent on cutting speed, feed, machining time and environmental temperature. It can be estimated using a radius basis function (RBF) artificial neural network (ANN). The cutting-induced error plays a dominant role and can be estimated based on the cutting condition (speed, feed and depth of cut) and the motor currents (main spindle motor current and feed spindle motor current) using a two-stage RBF ANN. Based on the estimated error, the compensation can be done by overwriting the CNC code on-line. Experimental results indicate that the new method can reduce the workpiece error by as much as 75% (average workpiece error is reduced to 8 µm from 14 µm). The new method is also easy to implement in the shop floor.