Influence of geometric variables on spur gear volume

Gear system optimization is currently topical amongst researchers. To this end, problem formulation is key and therefore knowledge of parameter influence and variation behaviour is indispensable. In this research work, four gear volume models were investigated for volume minimization while considering six variables viz. face width, module, pinion tooth, hardness, and pinion and gear shaft diameters. Three algorithms viz. teaching learning-based optimization (TLBO), particle swarm optimization (PSO) and firefly algorithm (FA) are employed to obtain the optimal volume and design parameter variation study. The convergence rate of each algorithm for each gear model is contrasted against other algorithms applied in the study. Experimental runs have also been conducted to determine standard deviation and mean values. Variation studies on the volume objective reflect relevant observations noted for parameter setting and optimization. The results obtained can assist the designer in setting designer preferences with minimal resources expended thereby improving the problem-solving exercise.