Comparative Study of Mono and Hybrid Nanofluids in MQL Turning of AISI 1040 Steel Using Box–Behnken RSM Approach

Abstract

The growing emphasis on sustainable manufacturing has increased interest in ecofriendly lubrication strategies for machining. Conventional flood cooling, despite its effectiveness, is associated with high fluid consumption, waste disposal concerns, and occupational health risks, motivating the use of near-dry alternatives such as minimum quantity lubrication (MQL). This study investigates the effect of mono and hybrid nanofluids under MQL on the turning performance of AISI 1040 steel. Three input parameters, cutting speed, feed rate, and nanoparticle weight percentage, were evaluated against three responses, cutting force, cutting temperature, and surface roughness. The experiments were designed using Response Surface Methodology with a Box–Behnken design to develop second order regression models and perform multi-response optimization. The models showed good agreement with the experimental results, confirming their predictive reliability. Among the tested conditions, the hybrid nanofluid Case E (75:25 Al2O3:ZnO) provided the best overall performance. The optimal combination of 31.71 m/min cutting speed, 0.11 mm/rev feed, and 1 wt% nanoparticle concentration produced the highest desirability. The findings indicate that mono and hybrid nanofluids under MQL can improve machining performance, with Case E offering the best balance of thermal control and friction reduction. However, the conclusions are limited to the studied parameter range and setup.

Keywords: Mono Nanofluids, Hybrid Nanofluids, Response Surface Methodology, ANOVA, Al2O3, ZnO