Parametric Optimization of Electrochemical Honing of Helical Gears by Response Surface Methodology and Genetic Algorithm

Abstract

Finishing is crucial for maximizing the service life and overall in-service performance of gears. This paper presents the parametric optimization of Electrochemical Honing (ECH) of helical gears using Response Surface Methodology (RSM) and Genetic Algorithm (GA) to predict the surface quality of gear teeth profile. A three factors three levels Box Behnken Design (BBD) of Response Surface Methodology (RSM) has been designed to investigate and analyze the effects of input variables: voltage, rotating speed and electrolyte concentration on measures of process performances: percentage improvement in average and maximum surface roughness (PIRa / PIRtm) value. Typical ranges of input parameters were investigated and regression models were developed and used respectively as constraints and objective function for parametric optimization using GA. The results established the feasibility of using the process to improve the surface quality of gear teeth profile.