Thermal error optimization modeling and real-time compensation on a CNC turning center

Thermal errors are the largest contributor to the dimensional errors of a workpiece in precision machining. The error compensation technique is an effective way of reducing thermal errors. Accurate modeling of errors is a key part of error compensation. The thermal errors of a machine tool can be treated as the superposition of a series of thermal error modes. In this paper, five key temperature points of a turning center were obtained based on the thermal error mode analysis. A thermal error model based on the five key temperature points was proposed by using genetic algorithm-based back propagation neural network (GA-BPN). The GA-BPN method improves the accuracy and reduces computational cost for the prediction of thermal deformation in the turning center. A thermal error real-time compensation system was developed based on the proposed model. An experiment was carried out to verify the performance of the compensation system. The experimental results show that the diameter error of the workpiece reduced from about 27–10 μm after implementation of the compensation.