Design optimization of a three-stage transmission using advanced optimization techniques

Gear transmission systems are very important machine elements and their failure can lead to losses or damage of other mechanical components that comprise a machine or device. Since gears are applied in numerous mechanical devices, there is need to design and subsequently optimize them for intended use. In the present work, two objectives, viz., volume and center distance, are minimized for a rotary tiller to achieve a compact design. Two methods were applied: (1) analytical method, (2) a concatenation of the bounded objective function method and teaching–learning-based optimization techniques, thereby improving the result by 44% for the former and 55% for the latter. Using a geometric model and previous literature, the optimal results obtained were validated with 0.01 variation. The influence of design variables on the objective functions was also evaluated using variation studies reflecting on a ranking according to objective. Bending stress variation of 12.4% was less than contact stress at 51% for a defined stress range

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

Design optimization of a three-stage transmission using advanced optimization techniques

Gear transmission systems are very important machine elements and their failure can lead to losses or damage of other mechanical components that comprise a machine or device. Since gears are applied in numerous mechanical devices, there is need to design and subsequently optimize them for intended use. In the present work, two objectives, viz., volume and center distance, are minimized for a rotary tiller to achieve a compact design. Two methods were applied: (1) analytical method, (2) a concatenation of the bounded objective function method and teaching–learning-based optimization techniques, thereby improving the result by 44% for the former and 55% for the latter. Using a geometric model and previous literature, the optimal results obtained were validated with 0.01 variation. The influence of design variables on the objective functions was also evaluated using variation studies reflecting on a ranking according to objective. Bending stress variation of 12.4% was less than contact stress at 51% for a defined stress range