experimental design integrated with a Fuzzy Mamdani inference system was employed to determine the optimal machining conditions. The best-performing combination of machining conditions-cutting speed of 70 m/min, feed rate of 0.05 mm/tooth, and depth of cut of 0.15 mm under CNT-MQL lubrication-resulted in the maximum multi-performance characteristics index (MPCI), achieving a value of 0.78. Overall, CNT-reinforced soybean oil demonstrates strong potential as an effective nano-lubricant for improving machining performance of nickel-based alloys under MQL conditions. The findings of this research demonstrate that nano-lubrication incorporating carbon nanotubes (CNTs) serves as a promising strategy to significantly improve machining performance, prolong tool durability, and achieve superior surface finish when processing hard-to-machine materials.
Abdullah et al. (Sun,) studied this question.