Application of Evolutionary Optimization Techniques in Reverse Engineering of Helical Gears: An Applied Study

Reverse engineering plays an important role in the manufacturing and automobile industries designing complicated spare parts, reducing actual production time, allowing for multiple redesign possibilities, including shape alterations, different materials, changes to other significant parameters of component. Using reverse methodology, damaged gears can be identified modeled meticulously. Influential obtained shortest time. Because most time it is impossible solve gear-related inverse equations mathematically, metaheuristic methods used reverse-engineer gears. This paper presents a methodology based on measurement over balls span along with evolutionary optimization techniques determine geometry pure involute cylindrical helical gear. Advanced techniques, i.e., Grey Wolf Optimization, Whale Particle Swarm Genetic Algorithm, were applied considered case, effectiveness accuracy proposed algorithms compared. Confirmatory calculations experiments reveal remarkable efficiency Optimization compared obtaining influential gear design parameters.