Genetic Algorithm for Optimizing Noiseless, Non-Lubricated Helical Gear Pair

This research is motivated by optimal designing of bevel gear pair for transmitting more power between shafts in the machine tool without noise and without lubricating oil. In this research, the parameters such as power, efficiency, weight and centre distance have been optimized since the parameters are the central part of the gear problem. The sub problem of reducing the noise, running without lubricants, standardizing the parameters, satisfying the bending and compressive stress had been considered as constraints. Thus the formulated problem became a nonlinear NP Hard problem with number of problem specific (approximate) heuristic procedures. In consequence, a need arises for a more structured design intended to provide solutions which are feasible and stable for most of the helical gear design problems. As a result, genetic algorithm has been used as the optimization approach and their relative performances by varying the parameters are compared by sensitivity analysis to reduce the computational time. The optimized genetic result had been used for helical gear manufacturing and the trial results were compared with the standard helical gear. It was found that the performance has been at par with the standard gear and also the optimized gear pair having 8% reduction of gear size and approx. 2 % increase in efficiency.