Abstract
There has been much research in the area of thermal deformation in three-axis machine tools. This paper is concerned tool-to-workpiece displacement with thermal deformation and compensation method in five-axis machine tools. With considering motors operating conditions, the models were derived using data from temperature and displacement sensors by neural network.The results show that a 90% in RMSE view and a 70% in errors reducing ratio reducion of thermal errors has been gained after compensation.