Abstract
This study investigates the thermo-mechanical behaviour of titanium alloys during milling with the aim of developing a predictive approach for reducing thermal loading and improving process stability. A three-dimensional finite element model was constructed in Kompas-3D and simulated in ANSYS Workbench using the Johnson–Cook constitutive and damage model. To systematically analyse the effects of process variables, a five-level experimental design was employed, in which cutting depth, feed rate, and spindle speed were varied. The results of 25 simulation runs were processed in ANETR-5 software to establish a regression model linking cutting parameters with the workpiece surface temperature. The findings revealed that heat accumulation is strongly localised at the tool–chip interface, while subsurface temperature stabilises near 101.9 °C. Cutting forces were observed to fluctuate in all coordinate directions, reflecting the intermittent engagement of milling teeth and providing insight into potential process instability. The regression model demonstrated high adequacy with SD = 28.76%, R = 0.948, and F = 12.093. Optimisation indicated that the combination of cutting depth t = 1 mm, feed rate S = 4500 mm/min, and spindle speed n = 4162 rpm yields the most favourable thermal response. The approach provides a reliable basis for optimising titanium machining, improving tool life, surface integrity, and overall cost efficiency.