Experimental investigation and optimization of hybrid turning of Ti6Al7Nb alloy under nanofluid based MQL by TOPSIS method

Abstract

The present work aims to decide on machining parameters and enhance machinability of the biomedical Ti6Al7Nb alloy using nanofluid MQL with nanoparticles of graphene (NMQL) and ultrasonic vibration assisted (UVA) machining methods were applied both separately and in a hybrid manner. Consequently, for the chosen cutting parameters, when compared to the conventional turning (CT) with vegetable cutting oil-based MQL, the UVA-NMQL hybrid method has achieved a reduction in cutting forces ranging from approximately 11% to 23%, a decrease in cutting temperatures by around 9% to 17%, and an enhancement in average surface roughness by roughly 15% to 53% across all the analyzed results compare to vegetable oil based conventional MQL turning conditions. Additionally, using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, the optimum cutting parameters were determined as UVA-NMQL cutting condition, 130 m/min cutting speed, and 0.1 mm feed value.