Response Surface Methodology-based Modeling and Optimization of AISI 1040 Turning Using Al2O3 and ZnO Nanofluids Under Minimum Quantity Lubrication
J. Environ. Nanotechnol., Volume 15, No 1 (March 2026) pp. 603-615
Abstract
Nanofluid‑based minimum quantity lubrication (MQL) supports near‑dry machining by reducing fluid consumption while maintaining cooling and lubrication. This study examines Al2O3 and ZnO mono nanofluids under MQL in turning AISI 1040 steel, with cutting speed, feed rate, and nanoparticle weight percentage as inputs, and cutting force, cutting temperature, and surface roughness as responses. Experiments were designed using Box–Behnken response surface methodology, and quadratic models were validated through analysis of variance. Case A (Al2O3 + MQL) showed greater reductions in cutting force and surface roughness, whereas Case B (ZnO + MQL) provided better temperature control. Multi‑response optimization for Case A identified low cutting speed (31.71 m/min), low feed (0.18 mm/rev), and 1 wt% nanoparticles as the best compromise among all three responses, supporting nanofluid‑based MQL as a sustainable machining strategy.
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