###### Abstract
They investigated tool wear under three different machining conditions: minimum quantity lubrication (MQL), hybrid (liquid nitrogen-MQL), and dry machining. Their research revealed that the hybrid cooling approach outperformed both dry machining and MQL conditions in terms of minimizing tool wear. In their study on titanium grade 5 (Ti-6 Al-4V), [PERSON] et al. [17] conducted a thorough investigation and employed ANOVA for statistical analysis. Their research focused on evaluating process outcomes such as surface roughness, top burr width, and tool flank wear. They systematically examined the impact of process input parameters, including feed rate, cutting speed, and depth of cut, on these process outcomes. Their experimental design involved two levels for each parameter. The results emphasized that feed rate played a crucial role as a major influencing factor for surface roughness. Additionally, they noted that machining below the edge radius led to improved surface quality, particularly concerning surface roughness. [PERSON] et al. [18] studied the effects of tool coating and cutting process parameters when micro-machining Inconel 718. Their research focused on surface roughness and burr formation. Statistical analysis revealed that cutting velocity had a significant influence on surface roughness, while cutting depth had the greatest impact on burr formation. Additionally, the study found that feed rate and depth of cut influenced the types of burrs formed. Furthermore, in another study on Inconel 718, [PERSON] et al. [19] found that cutting parameters, tool condition, machine vibrations, and built-up edge (BUE) formation influenced surface roughness. They observed an initial decrease in surface roughness, followed by a gradual increase with cutting length. Researchers conducted a study on improving the sustainability of machining hard materials by investigating the influence of cooling conditions, including cryogenic cooling, on tool wear, specific cutting energy, and surface roughness. The findings showed that cryogenic cooling had a significant positive impact, improving tool wear by 33%, specific cutting energy by 10%, and surface roughness by 9% under optimized machining conditions [20]. [PERSON] et al. [21] discussed two methods for determining tool life: (a) measuring the dimensional accuracy of machined parts and (b) measuring the tool flank wear. Cutting temperature is a critical factor when working with metals, as it significantly affects tool wear. Research has highlighted that cutting speed is the primary variable influencing tool wear in machining processes. Higher cutting speeds generate more heat, leading to accelerated tool wear [22]. Tool wear is the leading cause of accuracy problems and can manifest in various forms, such as increased cutting force, dimensional changes, or the necessity for a replacement tool. Numerous empirical studies have investigated tool wear in various materials, including titanium grade 5 and Ti555.3. [PERSON] et al. [23] conducted a study on these materials, examining the influence of process parameters on tool wear, cutting forces, and chip geometry. Their research identified tool failure mechanisms related to diffusion and adhesion. Another study investigated the machinability of Ti-6 Al-4V aerospace alloy using cryogenic conditions, addressing its challenging properties. By creating a tool wear map based on cutting speed and feed rate, the research identified distinct wear regions, including an avoidance zone. Cryogenic machining improved tool life by up to 100% and increased material removal rates (MRRs) by 36%, offering valuable insights for optimizing Ti-6 Al-4V machining. In another study on titanium alloy, researchers focused on machining titanium alloy Ti-6 Al-4V at high speeds and compared dry and cryogenic conditions. Cryogenic machining significantly extended tool life by up to 170% while also promoting a more consistent and slower tool wear rate.