Design optimization of an angular contact ball bearing for the main shaft of a grinder

Abstract

A conventional trial and error approach toward the design of non-standard bearings takes a significant amount of time to obtain an adequate design. In this study, a non-standard angular contact ball bearing for the main shaft of a grinder was optimized using design automation and optimization techniques. To manufacture a product as precisely as possible with a grinder, the radial and axial stiffness values of the grinder bearing must be selected as objective functions. To treat two objective functions, this study employed a global criterion method as a multi-objective optimization methodology. Eight constraints on the manufacturing, film thickness, friction, and fatigue life were imposed. Six geometric variables and an axial preload were selected as design variables. All design variables were regarded as discrete because they should have manufacture-possible dimensions. Quasi-static analysis taking dynamic effects into account was employed to analyze bearing performance. For efficient discrete optimization, this study proposed a hybrid method in which a micro-genetic algorithm and regression-based sequential approximate optimizer were both employed. Optimization results revealed that both stiffness values were enhanced while satisfying all design constraints. (C) 2016 Elsevier Ltd. All rights reserved.