This work aims to investigate and assess the beneficial function and feasibility of nanofluids in minimum quantity lubrication (MQL) assisted machining. The goal is to develop newly generated CNT based nano hybrid cutting fluid and demonstrate its effect on surface roughness of Al alloy. Moreover, the fabricated nano hybrid cutting fluid will eventually reduce cutting fluid consumptions and maintain an eco-friendly environment. Three conditions were used to perform the machining process such as dry condition, conventional oil and Al2O3/CNT nanoparticle with EVO oil as base fluid. The lowest surface roughness achieved for nanofluid and the maximum surface roughness for the dry condition. In terms of looking for optimum parametric combination, Artificial Neural Network (ANN) and Response Surface Methodology (RSM) have been used. The ANN technique has proved its efficiency since its correlation coefficients, mean prediction errors (MPEs), and root mean square errors (RMSEs) are small compared to the RSM approach.
Keywords: Minimum quantity lubrication (MQL), Nano-fluid, ANN- RSM comparison, Aluminum Die casting, Al383, Surface roughness, Milling.