Optimal Design of Spur Gears using Particle Swarm Optimization

TL;DR

This paper presents a method using Particle Swarm Optimization to design spur gears that minimize mass and failure, achieving significant reductions in key design variables compared to existing approaches.

Contribution

It introduces a PSO-based approach for optimizing multiple design variables of spur gears for mass and failure reduction, improving upon previous methods.

Findings

Mass reduction achieved by decreasing gear module and face width.

Optimized gear designs meet required center distance with fewer resources.

PSO effectively handles multi-objective gear design problems.

Abstract

Optimizing the design of spur gears, regarding their mass or failure reduction, leads to reduced costs. The proposed work is aimed at using Particle Swarm Optimization (PSO) to solve single and multiple-objective optimization problems concerning spur gears. Pinion, number of teeth, the module, the face width, and the profile shift coefficients of both the pinion and wheel. Mass, gear loss factor, specific sliding, contact ratio, and safety factors are variables considered for the formulation of the objective function. The results show that those variables are reduced when compared to the results of the literature. Mass reduction, for instance, was possible to be achieved due to the reduction of the gear module and face width, increasing the number of teeth to achieve the required working center distance of the gear.