Sustainable machining of monel 400 using hybrid cryogenic lubrication and multiobjective optimization

This study investigates the machinability of Monel 400 under four machining environments: dry cutting, Minimum Quantity Lubrication (MQL), cryogenic liquid nitrogen (LN₂) cooling, and hybrid cryogenic–minimum quantity lubrication (Cryo-MQL). The effects of these environments on surface roughness, specific cutting energy (SCE), and machining cost were evaluated. Cryo-MQL demonstrated the most favorable overall machining performance by combining the cooling capability of LN₂ with the lubricating action of MQL. Compared with dry machining, Cryo-MQL reduced surface roughness, SCE, and total machining cost by 48%, 29.17%, and 10.64%, respectively. Relative to MQL and cryogenic machining, surface roughness decreased by 10.34% and 15.22%, while SCE decreased by 19.05% and 22.73%, respectively. Machining cost was also reduced by 7.89% and 8.30% compared with MQL and cryogenic machining, respectively. A multi-objective optimization framework integrating Multi-Objective Particle Swarm Optimization (MOPSO) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) identified a balanced set of machining parameters. Experimental validation yielded prediction errors of 4.61%, 3.06%, and 2.79% for surface roughness, SCE, and machining cost, respectively. These findings demonstrate the machining-performance and economic advantages of Cryo-MQL, including improved surface quality, process-level energy efficiency, and reduced direct machining cost. The use of biodegradable sunflower oil further supports resource-conscious manufacturing. However, the environmental burdens associated with LN₂ production, purification, storage, and delivery were not quantified. Therefore, reduced SCE does not establish a direct reduction in carbon emissions. Comprehensive life-cycle assessment and carbon-footprint analysis are required to determine the net environmental impact and establish any contribution to SDG 13, while the findings indicate potential relevance to SDG 9 and SDG 12.