Multi-objective Optimization of Machine Tool Spindle-Bearing System
- PDF / 4,214,497 Bytes
- 18 Pages / 595.276 x 790.866 pts Page_size
- 42 Downloads / 193 Views
International Journal of Precision Engineering and Manufacturing https://doi.org/10.1007/s12541-020-00389-7
REGULAR PAPER
Multi‑objective Optimization of Machine Tool Spindle‑Bearing System Van‑Canh Tong1 · Jooho Hwang1 · Jongyoup Shim1 · Jeong‑Seok Oh1 · Seong‑Wook Hong2 Received: 17 February 2020 / Revised: 24 May 2020 / Accepted: 19 July 2020 © Korean Society for Precision Engineering 2020
Abstract 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. Keywords Spindle-bearing system design · Multi-objective optimization · Particle swarm optimization · Friction torque · Natural frequency · Static stiffness List of symbols Np Number of particles in the swarm X Position vector of all the particles, i.e., design variables Xmax, Xmin Upper and lower bound vectors V Displacement vector i Particle number n Iteration number W Weighting parameter or particle inertia r0, r1, r2, r3 Vectors of independent random numbers between 0 and 1 P Local best location for a particle Gbest Global best location of all particles in the swarm cp, cs Acceleration constants
* Seong‑Wook Hong [email protected] 1
Department of Ultra Precision Machines and Systems, Korea Institute of Machinery and Materials, 156, Gajeongbuk‑ro, Yuseong‑gu, Daejeon 34103, South Korea
Department of Mechanical System Engineering, Kumoh National Institute of Technology, 61 Daehak‑ro, Gumi, Gyeongbuk 39177, South Korea
2
f1, f2 Objective functions N1, N2 First and second natural frequencies T Friction torque of the rolling bearing j Bearing index Z Total number of bearings K Static stiffness of the spindle
1 Introduction A spindle-bearing system is one of the most crucial components in most machine tools. The modern metal cutting machines employ a spindle-bearing system for driving a tool to perform the cutting. The general requirements of a s
Data Loading...
