Optimization and prediction of safety coefficient for surface durability of planetary gearbox using Тaguchi design and Аrtificial Neural Network

Abstract

Optimization of parameters of planetary transmission by using Taguchi design was performed in this paper. Used values of safety coefficient for surface durability of internal gear of planetary gearbox were obtained by calculation. Considered parameters for optimizing are material, module and gear width. The influence of each parameter on the safety coefficient for surface durability of internal gear at 95% confidence interval was found by applying ANOVA analysis. The most influential parameter is gear module with a 74.034%, followed by the width of the gear with 16,858% and 8,874% material. Prediction of safety coefficient for surface durability of internal gear of planetary gearbox was performed by applying Artificial Neural Network (ANN).