High strength low alloy (HSLA) AISI grade 4140 is grabbing the eyes of automobile industries for its superior properties. However, the production of finished components of HSLA steel by machining under dry environment is challenging owing to high cutting temperature and friction. The usage of low-cost coated carbide tools and environment-friendly cooling-lubrication approach are thereof being given importance for the past few decades for economic and sustainable machining. In this study, the power consumption (Pc) during the hard turning process of AISI 4140 steel was analyzed using an AlTiSiN-coated carbide tool under various cutting environment conditions, including dry cutting, flooded cutting, and nanofluid-MQL cutting. For this study, the nanofluid was prepared by blending MWCNT nanoparticles with an environmentally friendly automotive radiator coolant, which served as the base fluid. Briefly, the cooling-lubrication performance is investigated by comparing the machining responses like machined surface morphology, tool wear, cutting force, and temperature. The variance analysis was adopted to determine the significance level of experimental parameters (speed, feed, nose radius, depth of cut, cutting environments) affecting the Pc. To predict and optimize Pc during hard turning with machining variables, the response surface method (RSM) was proposed. Following the predictive modeling and optimization, the results were applied for economic assessment and for energy saving carbon footprint evaluation. This innovative research also addresses comparative sustainability evaluation in hard turning under different C/L environments using life cycle assessment (LCA) towards cleaner and safer production. Results indicate that cutting speed was the most influential item on Pc enhancement. Furthermore, as compared to dry and flooded turning, lower cutting force, reduced cutting temperature, shorter width of flank wear, and better surface morphology are obtained under nanofluid-MQL machining. It is experienced that nanofluid-MQL machining outperformed towards sustainability improvement concerning techno-economically viable societal acceptable and environment friendliness.
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