Predicting Temperature Fluctuation of Five Axis Controlled Compact Machine Tool Equipped with a Wave Motion Gear Device Based on a Thermal Network Model

The manufacturing industry accounts for more than 40% of the total final energy consumption. Therefore, energy-saving measures are still required. Against this background, stable accuracy over a long period of time is necessary to realize automation and unmanned operation of machine tools. Therefore, thermal deformation, which is up to 75% of the overall geometric error of the workpiece, is the most important issue. In this study, we proposed a modeling method to predict the temperature rise during machine tool operation. To reduce the power consumption, a reduction gear attached to the rotation control shaft was employed in this study, and a wave gear device was used as the reduction gear. Such a wave gear device has the characteristic in that its efficiency changes significantly with temperature change. Therefore, while considering the characteristics of the wave gear device, the power consumption was recorded by the internal information monitor of the servo motor, and the rotating axis was operated under various drive conditions. The results indicate that the lubricating oil influenced the power value. In addition, we succeeded in analyzing a temperature rise prediction model from the power loss.