Enhancing machining efficiency of UNS S45000 alloy steel using cryogenically treated TiAlSiN coated tungsten carbide inserts

The turning process is critical in manufacturing sectors, particularly in machining high-strength materials in harsh environments for aerospace, automotive, railway, chemical, and energy applications. UNS S45000 steel, with its superior thermal conductivity, mitigates tool wear and improves chip formation, optimizing machining productivity and minimizing operational downtime. Various factors influence machining quality, including process parameters, tool integrity, and workpiece material properties. Coated tool inserts, renowned for their exceptional mechanical properties, enhance durability, wear resistance, and cutting performance, significantly extending tool life. This study evaluates the impact of resultant forces on TiAlSiN-coated WC tool inserts subjected to Physical Vapor Deposition (PVD). An additional 36-hour deep cryogenic treatment on the tool insert significantly enhanced its hardness compared to the coated tool. The coated insert exhibited a hardness of 54 RHN. In contrast, the cryogenically treated insert attained 79 RHN, resulting in a 68 % increase in hardness, contributing to improved wear resistance and performance during turning. The machining process is controlled via Cutting speed, cutting depth, and feed rate, with a Taguchi L27 full-factorial experimental design used to identify and establish correlations between the input variables. A pluralistic decision-making framework is employed, integrating Collective Intelligence Optimization, Moth Flame Optimization (MFO), Grasshopper Optimization (GHO), and Slap Swarm Optimization (SSO) algorithms. Nature-inspired optimization algorithms are applied to fine-tune input parameters, resulting in a 5 % reduction in resultant cutting force compared to experimental values. Validation tests confirm that the optimized parameters yield deviations within acceptable limits. The optimized parameters obtained were a Cutting speed of 95.415 m/sec, a Feed rate of 60.07353 mm/min, and a Depth of cut of 0.25080 mm. Reduction in cutting speed increases tool life by 18–29 %. The MFO algorithm determined the resultant force to be 84.384 N and the surface roughness to be 0.6138 µm as the optimal values. Among the tested algorithms, Moth-Flame Optimization (MFO) demonstrates the fastest convergence, outperforming the others in optimizing the machining process.