Machining performance of SS 304 steel with hybrid nanocutting fluids using Taguchi-based gray relational analysis

Traditional cutting fluids are often insufficient in managing the heat, friction generated during machining and environmental issues. The use of hybrid nanocutting fluids contributes to green manufacturing by reducing the need for excessive coolant flow and minimizing environmental impact. This study investigates the machining performance of SS 304 steel using hybrid nanocutting fluids and evaluates the results through Taguchi-based Gray Relational Analysis (GRA). The hybrid nanocutting fluids were formulated by dispersing a combination of nanoparticles into a conventional cutting fluid. A series of turning experiments were conducted using Taguchi L27 design of experiment. The results demonstrated that the neem oil with 1.5% alumina and graphene inclusion observed significantly improved the machining efficiency of SS 304 steel, offering reduced tool temperature, cutting forces, tool vibrations and surface roughness. A notable reduction of cutting temperature, cutting force, tool vibration, and surface roughness by 35%, 18%, 27%, and 34% respectively is observed. From GRA, outstanding results is obtained at cutting speed 900 rpm, a feed rate of 40 mm/min, a depth of cut of 0.6 mm, and a 1.5 vol % concentration of hybrid nanofluid. The optimal cutting condition helps in reducing the cutting temperature, tool vibrations cutting forces and improves surface roughness.