Comparative study on optimum design of rolling element bearing

Long fatigue life is the most important objective in the optimum design of rolling element bearing. In the present study the fatigue life of a radial ball bearing is maximized. The nonlinear constrained optimization problem has been solved using particle swarm optimization algorithm and a hybrid PSO and Teaching Learning based Optimization algorithm. The algorithm uses a ranking method of constraint handling and contact stress has been introduced as a new constraint. The results have been compared with the established available results. A constraint violation study has been carried out to prioritize the constraints. A convergence study has been performed to identify the key design variables. Encouraging results in terms of objective function values and CPU time have been reported in this study.