Optimization of Minimum Quantity Lubrication with Al2O3 Nanoparticles for Improving Surface Roughness in the Hard Turning of SKD11 steel

This study investigates the application of Minimum Quantity Lubrication (MQL) with Al2O3 nanoparticles in hard turning of SKD11 steel to improve surface roughness, a key factor in machining hardened steel. Conventional flood cooling poses environmental and economic challenges, prompting the adoption of MQL as a more sustainable alternative. By integrating nano-sized particles into the cutting fluid, this research explores the effects of critical MQL parameters—namely, nanoparticle concentration, compressed air pressure, and lubricant flow rate—on surface quality. The experiments were designed using the Taguchi method, and the data was analyzed through Signal-to-Noise ratio (S/N) to identify the optimal conditions for minimizing surface roughness. Results reveal that nanoparticle concentration has the most significant impact, underscoring the potential of nanofluid-based MQL in enhancing machining performance in hard turning. These findings contribute valuable insights for optimizing MQL in sustainable manufacturing.