Indexed on: 25 Mar '15Published on: 25 Mar '15Published in: The International Journal of Advanced Manufacturing Technology
Thermal error is one of the major contributors to dimensional errors of machine tools. In this paper, a hybrid thermal error modeling method is proposed to forecast the thermal expansion of a heavy boring and milling machine tool in z-axis. In this model, the thermal error in z-axis is calculated as the expansion of a one-dimensional rod. The inputs of the model are temperatures of spindle motor, hydrostatic bearing and environment, selected through fuzzy c-means (FCM) clustering method. The temperatures of the nodes in the rod are solved by Thomas algorithm and the coefficients of the model are optimized by genetic algorithm (GA). The accuracy of the proposed model is compared with that of the output error model and stepwise regression model, and the performance of the proposed model is better in accuracy. In addition, a compensation system is developed based on the proposed model to reduce the thermal error in z-axis.