Machining performance and corrosion analysis of Al 2 O 3 /TiO 2 -coated carbide inserts in dry turning of Ti-6Al-4 V using machine learning approaches

Abstract

Sustainable, high-efficiency machining of titanium alloys continues to be a major challenge in modern manufacturing. In this work, the machining performance of the Ti-6Al-4 V alloy was examined under dry turning conditions using Al₂O₃/TiO₂ coated carbide inserts fabricated via the high-velocity oxy-fuel (HVOF) technique. The effects of key machining parameters: cutting speed, feed rate, and depth of cut on responses such as cutting force and flank wear were systematically evaluated through experiments. The findings reveal that increasing cutting speed tends to lower cutting forces, whereas higher feed rates and depths of cut accelerate flank wear. To improve predictive capability, machine learning approaches, specifically Adaptive Boosting (AB) and Gradient Boosting (GB), were implemented. The AB model achieved better accuracy in forecasting cutting force, while both models produced reliable predictions for flank wear, as validated by performance indicators including the coefficient of determination (R²), mean squared error (MSE), and mean absolute error (MAE). Furthermore, corrosion performance was investigated using electrochemical testing in a 3.5 wt.% NaCl environment. The coated inserts showed reduced corrosion current density and increased charge transfer resistance compared to uncoated tools, confirming their enhanced corrosion resistance. Tafel polarization and Nyquist analyses confirmed enhanced electrochemical stability due to the barrier effect and formation of protective oxide layers. Surface morphology analysis using SEM and EDS revealed reduced surface degradation and improved coating integrity in coated inserts. Overall, the Al₂O₃/TiO₂ coated inserts significantly enhance machining performance, flank wear resistance, and corrosion protection, making them suitable for demanding industrial applications.