Investigation on the Effect of Graphene Nano-cutting Fluid Minimum Quantity Lubrication on the Machining Performance of Inconel 625

Abstract

Inconel 625 is a solid-solution strengthened nickel-based superalloy that found widespread usage in aerospace, marine, and nuclear applications due to its outstanding mechanical properties. Thus in the current study, the machining performance of Inconel 625 under nano-minimum quantity lubrication (nMQL) environment is investigated. Graphene nanoparticles were selected to enrich the physicochemical properties of coconut oil as a cutting fluid. Experiments were conducted using AlTiN PVD coated carbide cutting tool inserts under stable nano-cutting fluids of various concentrations and at different levels of cutting speed, feed, and depth of cut. The experiments were conducted according to Taguchi's L 16 orthogonal design. Surface roughness, tool flank wear, and material removal rate were selected as responses to study the effects of cooling conditions and machining parameters. The turning process performance was optimized by the grey relational multi-objective optimization method. Cutting speed of 80 m/min, feed of 0.05 mm/rev, depth of cut of 0.8 mm, and cooling condition with 0.50 wt. % graphene nanofluid MQL was established as the optimal machining conditions. Analysis of variance (ANOVA) was performed to identify the importance of input parameters on machining performance and the results indicate that feed and cooling conditions are the most influential parameters. Also, the tool wear mechanisms and chip morphology were identified and analyzed using SEM and EDS to understand the cutting tool performance under each cooling condition by considering the optimal machining parameters. The lesser tool wear and better chip morphology were obtained under 0.50 wt. % graphene nano-cutting fluid environment.

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Performance Evaluation of Graphene Nanofluid to Mitigate the Wear of a Diamond Tool in Micro-Machining of Ti6Al4V Alloy

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