Advancements in MQL machining: a comparative study of cutting fluids on AISI 630 steel

This study optimized minimum quantity lubrication (MQL) parameters to enhance the machining performance of AISI 630 steel, focusing on reducing tool-work interface temperature and surface roughness. An in-house developed MQL system utilizing vegetable oils (Azadirachta Indica, Ceiba Pentandra, Calophyllum Inophyllum) was employed. The experiments varied flow rates (700-900 ml/h), pressures (0.06-0.18 bar), and nozzle diameters (0.35-1.05 mm) on a center lathe using carbide tools. Taguchi's L18 orthogonal array and Grey Relational Analysis (GRA) were applied for optimization, while Analysis of Variance (ANOVA) supported predictive modeling. The optimal parameters for minimizing temperature were identified as 90 ml/h flow rate, 2.8 bar pressure, 1.5 mm nozzle diameter, and Calophyllum Inophyllum coolant, achieving a significant reduction to 118 degrees C-a 40% improvement over dry machining. For surface roughness, the optimal parameters of 90 ml/h flow rate, 2.8 bar pressure, 2 mm nozzle diameter, and Calophyllum Inophyllum coolant yielded a minimum value of 0.672 mu m, marking a 28% improvement. Regression models with R2 values exceeding 0.98 demonstrated strong predictive accuracy for machining responses. This research underscores the potential of MQL systems to enhance machining sustainability and performance by reducing temperature, surface roughness, and coolant usage. The study highlights the viability of vegetable oil-based coolants as eco-friendly, cost-effective alternatives, advancing sustainable manufacturing practices.