Ball Bearing Fatigue and Wear Life Optimization Using Elastohydrodynamic and Genetic Algorithm

The present work attempts to improve the performance of rolling element bearings through the increase of fatigue life and the reduction of bearing wear. The formulation is based on Elastohydrodynamic to maximize the realistically evaluated minimum film thickness without significant increase in viscous friction torque. Design vectors are reduced in the present study relative to previous studies as some variables are considered as dependent variables. Other design vectors are not considered as variables in the study due to machining accuracy. This paper presents a more viable method to solve the multi-objective optimization problem using genetic algorithms (GAs) to reduce the chances of getting trapped in local maximum or minimum. Using a utility function, optimal Pareto points are obtained by changing the weight coefficients. Specific weights can be used depending on the designer decision whether to increase fatigue and wear life, or decrease the power consumption.