Friction torque and load capacity of bearings are very important performance indicators. The high speed and precision of machines presupposes the minimization of the friction torque of bearings, and the long service life is guaranteed by the maximization of the dynamic load capacity. However, the friction torque and dynamic load capacity increase and decrease respectively with the changes of the internal geometric parameters of bearings, so a machine with long service life and good friction characteristics can be realized only by multi-objective optimization of the dynamic load capacity and friction torque of bearings.
Many researchers studied to maximize the dynamic load capacity of bearings and to minimize their friction torque, but there is a lack of confidence in the optimization results due to the lack of correlation, many simplified parts and lack of enough constraints
Ball bearings are most widely used because of their small friction torque and relatively simple manufacturing process. Ri Jong Hak, a researcher at the Faculty of Mechanical Science and Technology, fully presented the constraints that reflect the actual conditions of ball bearings and developed a new mathematical model to simultaneously optimize the dynamic load capacity and friction torque. On this basis, he optimized them using the genetic algorithm and verified its accuracy by the FEM.
The proposed method can be applied to the determination of internal geometric parameters to simultaneously optimize the dynamic load capacity and friction torque of ball bearings.
For more information, you can refer to his paper “A Novel Methodology for Determining the Internal Geometric Parameters of a Ball Bearing in Consideration of Load Capacity and Friction Torque” in “Proceedings of KUTIC-2025”.