This study investigated the effect of nanofluid-based Minimum Quantity Lubrication (MQL) cooling strategy and machining parameters on machining power and surface roughness in milling process. Two nanofluids, Al₂O₃ and Fe₃O₄, were evaluated under identical cutting conditions. The results showed that the machining power using Al₂O₃ nanofluid was slightly lower than Fe₃O₄ (1%). However, it produced higher surface roughness (14.27%) than Fe₃O₄. Furthermore, machining parameters significantly affected the performance. Increasing cutting speed (vc = 3.23%), feed rate (fz = 0.93%), and depth of cut (ax = 0.33%) led to higher machining power due to increased material removal rate and cutting force. Surface roughness was mainly influenced by fz = 8.49% and ax = 6.16%, with feed rate identified as the dominant factor. Taguchi analysis and ANOVA revealed that depth of cut contributed most to machining power, while feed rate dominated surface roughness. The optimal machining power was achieved at vc = 22.5 m/min, fz = 0.028 mm/tooth, and ax = 0.5 mm, with values of 1.336 kW (Al₂O₃) and 1.341 kW (Fe₃O₄). Meanwhile, the best surface roughness was obtained at vc = 40.8 m/min, fz = 0.028 mm/tooth, and ax = 0.5 mm, with values of 0.596 µm (Al₂O₃) and 0.494 µm (Fe₃O₄).
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