Multi-objective Optimization of Machine Tool Spindle-Bearing System

In this study, a multi-objective optimization is performed for the design of a spindle-bearing system based on particle swarm optimization (PSO). Multiple objectives, such as natural frequencies, static stiffness, and total friction torque are considered in this design optimization. Bearing preload and bearing locations are selected as the design variables. Pareto-optimal solutions are used to support the selection of optimal values of the design parameters. A finite element model is established for the analysis and design of the spindle system with four angular contact ball bearings. Two optimization processes are performed with the PSO technique. The first process involves the first two natural frequencies and friction torque of the spindle, whereas the second process focuses on the spindle’s static stiffness and friction torque. The simulation results show noticeable improvement in the objectives compared with those of the primitive spindle. The experiments conducted on an actual spindle system fabricated with the optimal design demonstrate the benefits of the optimal design. The proposed design method is expected to be very useful in the design optimization of machine tool spindle systems subjected to various customer-oriented objectives.