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

Abstract

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.

Citation

Tiwari, R. and Chandran, R. (2018), "Optimal design of deep-groove ball bearings based on multitude of objectives using evolutionary algorithms", Multidiscipline Modeling in Materials and Structures, Vol. 14 No. 3, pp. 567-588. https://doi.org/10.1108/MMMS-06-2017-0058