Analysis of Carbon Footprints and Surface Quality in Green Cutting Environments for the Milling of AZ31 Magnesium Alloy

This investigation delves into the effectiveness of employing vegetable-based cutting fluids and nanoparticles in milling AZ31 magnesium alloy, as part of the pursuit of ecologically sustainable manufacturing practices. The study scrutinizes three different cutting environments: (i) dry cutting; (ii) minimum quantity lubrication (MQL) with rice bran oil as the base oil and turmeric oil as an additive; and (iii) MQL with rice bran oil as the base oil, and turmeric oil and kaolinite nanoparticles as additives. Fuzzy logic was implemented to develop the design of experiments and assess the impact of these cutting environments on carbon emissions, surface quality, and microhardness. Upon conducting an analysis of variance (ANOVA), it was determined that all the three input parameters (cutting environment, cutting speed, and feed) greatly affect carbon emissions. The third cutting environment (MQL + bio-oils + kaolinite) generated the lowest carbon emissions (average of 9.21 ppm) and surface roughness value (0.3 um). Confirmatory tests validated that the output parameters predicted using the multiobjective genetic algorithm aligned well with experimental values, thus affirming the algorithm’s robustness.