Thermal error prediction and reliability sensitivity analysis of motorized spindle based on Kriging model

A large amount of heat is generated by motorized spindles during the machining process of CNC machine tools, and it is the main factor restricting the further improvement of machining accuracy. Furthermore, physical properties and material parameters of the motorized spindle are uncertain in practical engineering. Therefore, it is necessary to evaluate the reliability and reliability sensitivity of the motorized spindle system. In this paper, a new thermal error estimation model of motorized spindle is established based on multi-physical field coupling theory. The Quasi-Monte Carlo (QMC) method is introduced to calculate the reliability of the motorized spindle system. An accurate and efficient surrogate model, called Kriging, is used to calculate the reliability and reliability sensitivity of the motorized spindle system to further improve computational efficiency. Moreover, the experimental platform for measuring the temperature and thermal error of the motorized spindle is built to verify the applicability of the proposed model. The analytical framework proposed in this paper provide a guidance for the reliability design and robustness evaluation of motorized spindle.