Optimal design of deep-groove ball bearings based on multitude of objectives using evolutionary algorithms

摘要

Purpose - In optimum designs of deep-groove ball bearings (DDGBs), an extended service life is one of the vital criteria. The life of a bearing depends on several factors. The purpose of this paper is to sequentially optimize three prime objectives for DDGB, i.e. the dynamic capacity (C_d), the maximum bearing temperature (T_(max)) and the elasto-hydrodynamic minimum film thickness (H_(min)). Design/methodology/approach - For solving constrained non-linear optimization formulations with multitude of objectives, an optimal design methodology has been put forth with the help of artificial bee colony algorithms. A study on the constraint violation has been carried out. By the Monte Carlo simulation method, a sensitivity investigation of diverse design variables has been done to examine variations in three objective functions and violation of constraints. Findings - Excellent improvement in the dynamic capacity (C_d), the maximum bearing temperature (T_(max)) and the elasto-hydrodynamic minimum film thickness (H_(min)) have been found in optimized bearing designs. Originality/value - Ball bearing design has been done based on multi-discipline objectives that are based on strength, tribology and thermal consideration. This type of design is essential in practical scenario where these physical phenomena will be present simultaneously.