Experimental Analysis, Modeling, and Optimization of Roller Burnishing Process for AL7075 Using Minimum Quantity Lubrication

Abstract

This study presents a comprehensive examination of the roller burnishing process on AL7075 aluminum alloy utilizing minimum quantity lubrication (MQL). Mathematical models were constructed for the prediction of surface roughness and hardness distribution vs process factors such as spindle speed, feed rate, and number of passes. The experimental investigations employed the Taguchi L9 orthogonal array design, utilizing aluminum oxide Nano fluids dispersed in vegetable oil as the MQL medium. Results showed a marked improvement in surface quality of up to 90% in the reduction in surface roughness, as well as increased surface hardness. Regression models of R² = 92.87% for roughness and R² = 96.32% regarding hardness suggested the predictive capacity of the mathematical model. The best settings were found to be a spindle speed of 500 rpm, a feed rate of 0.3 mm/rev, and a depth of cut of 5 scratches. This gave the best surface roughness of 0.40 µm and a hardness value of 230 HV. This work helps to promote environmentally friendly machining processes by proving MQL an effective method in both reducing environmental pollution and preserving surface integrity.