Model-based error motion prediction and fit clearance optimization for machine tool spindles

In this paper, the error motion issue of machine tool spindles is investigated. Firstly, a complete dynamic model of spindle systems is presented, in which the spindle shaft is discretized with the rigid body element and the rolling bearings are modelled using Gupta's theory. Secondly, the error motion prediction method is proposed based on the spindle model above, and then verified with the measurement on a grinding spindle. The fit clearance between bearing outer rings and the housing is introduced as a design parameter for error motion prediction under various conditions. The results show that the radial and tilt error motions increases nonlinearly with the raising of both clearance and rotation speed. Lastly, the model-based optimization scheme is given and the bearing fit clearance is optimized to meet the requirement of spindle design.