Multi-Objective Optimization of Micromachining Parameters for Titanium Alloy Ti-3Al-2.5V Using Grey Relational Analysis

This research investigates the multi-objective optimization of micro-milling processes for the titanium alloy Ti-3Al-2.5V (grade 9) through the application of grey relational analysis. The incorporation of nanometer-sized particles in hybrid machining lubricants plays a crucial role in improving heat transfer during machining. The approach aims to increase the efficiency and effectiveness of micro-milling by addressing various performance metrics simultaneously, leading to better machining results for this titanium alloy. Additionally, the integration of nanoparticles into the machining lubricant significantly improves the lubrication properties, reducing friction during the machining process. The study analyzed four machining parameters: machining speed, rate of feed, axial depth of cut, and the weight percentage concentration of hybrid machining lubricants Multi-wall Carbon Nano Tube and Alumina Oxide (MWCNT and Al2O3). The machining nanolubricant was formulated by adding 1% and 2% volume concentrations of MWCNT and Al2O3 nanoparticles to the industrial machining fluid. In this machining context, the friction between the machining tool and the Ti-3Al-2.5V work piece is a vital factor influencing the output quality. The results demonstrate that the chosen machining parameters and machining lubricants have a direct impact on the coefficient of friction and surface roughness. The study concludes that utilizing machining nanolubrication for machining Ti-3Al-2.5V (grade 9) significantly enhances the quality compared with traditional machining lubricants.