Performance Evaluation of Al₂O₃-Based Castor Oil Nanofluid in MQL-Assisted Turning of AISI 316L Stainless Steel

This work offers a thorough evaluation of the sustainable turning of AISI 316L stainless steel provided by a Minimum Quantity Lubrication (MQL) system employing an environmentally friendly castor oil-based nanofluid enhanced with Al₂O₃ nanoparticles. The combined impacts of cutting speed (164–370 m/min), depth of cut (0.25–0.75 mm), and lubrication techniques (dry, standard soluble oil, and nanoparticle-based bio-nanofluid) on surface roughness were investigated using a Taguchi L9 orthogonal array. The ideal condition—370 m/min cutting speed, 0.5 mm depth of cut, and nanofluid lubrication—yielded a minimal surface roughness (Ra) of 0.532 µm, thus stressing the better performance of the Al₂O₃-enriched castor oil nanofluid. Following cutting speed and depth of cut, statistical analysis using Analysis of Variance (ANOVA) indicated that coolant type was the most prominent component, contributing 60.57% to the observed variability in surface quality. Using DEFORM-3D software to replicate chip creation, stress distribution, and temperature gradients under ideal machining conditions, Finite Element Analysis (FEA) was performed to augment the experimental results. Applying the nanofluid indicated improved chip-tool interaction and a significant decrease in localized thermal loads and cutting forces, therefore supporting its function in enhancing tribological and thermal stability. Integration of statistical optimization with FEM-based validation offers a strong framework for assessing bio-based nanofluid performance in sustainable machining. These results highlight the feasibility of Al₂O₃-Castor oil nanofluids as a green substitute for traditional lubricants, thereby supporting resource-efficient, low-carbon, high-precision metal cutting techniques matched with Industry 4.0 and environmental sustainability objectives.