Performance Analysis of AISI 1040 Steel Turning Under Al₂O₃–ZnO Hybrid Nanofluid MQL Using Response Surface Methodology - A Step Towards Sustainable MachiningPages 155-168
Altaf Nalbandh Abstract:
UN’s SDG 9 aims to promote cleaner production and more resource efficient industrial processes. Environment-friendly cutting fluids play a crucial role in cutting operations by addressing environmental and health concerns for users. Nanofluid is a sustainable product that also encourages near-dry machining using minimum quantity lubrication (MQL). This study investigates the effect of an Al2O3–ZnO hybrid nanofluid applied through MQL on the turning performance of AISI 1040 steel. Cutting Speed, feed rate, and nanoparticle weight percentage were selected as control factors, while cutting force, cutting temperature, and surface roughness were considered as output responses. The experiments were planned using Response Surface Methodology (RSM) based on a Box–Behnken design for different cooling conditions and varying proportional ratios of Al2O3–ZnO nanoparticles to capture main and interaction effects among the process parameters. Analysis of variance confirmed the statistical significance and adequacy of the proposed models for all responses. The hybrid nanofluid cooling condition (75:25, Al2O3–ZnO) under MQL led to notable reductions in cutting temperature and surface roughness, along with lower cutting forces compared with conventional cutting conditions reported in this research. The multi-response optimization indicated that low cutting speed (31.71 m/min), low feed rate (0.18 mm/rev), and an intermediate nanoparticle weight percentage (1 wt%) provide the best compromise among cutting force, temperature, and surface roughness. The results highlight the potential of Al2O3–ZnO hybrid nanofluid-based MQL as a promising and sustainable cutting environment for improving machinability and surface integrity in steel turning operations. This encourages the use of such sustainable techniques in metal machining.
Keywords: Hybrid nanofluids,
MQL,
Response surface methodology,
ANOVA,
Al2O3,
ZnO
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