The advantages of minimum quantity lubrication (MQL) in machining include good lubrication, cleanliness, lower costs, and manageability; nevertheless, MQL’s poor cooling characteristic is a severe drawback. However, effective machining depends heavily on picking the right process parameters and cutting fluid. In addition, technicians must have access to a straightforward optimization approach that allows them to quickly and simply identify the optimal parameter combinations for every given production procedure. The total machinability can be improved by considering optimization simultaneously for selecting optimal conditions. According to our findings, Thickness ratio of chip (rc), cutting temperature (T), and while Material Removal Rate (MRR) can be maximized, while cutting force (F) and roughness (Ra) may be minimized, respectively. Deliver the best outcomes with Taguchi-based principal component analysis (PCA)-Grey relational analysis (GRA) optimization. MQL with cutting oil at 360 m/min and a feed rate of 0.11 mm/rev were found to be the optimum process conditions. The PCA-GRA approach can be useful, but only in certain situations, such as when there are competing goals to consider.

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