Abstract

Knowledge of material removal behavior and generated surface characteristics are crucial to improve grinding performance. A finite element model was developed using a single grit approach with the consideration of uncut chip thick variations along the grain path. It was found that the increase in cutting speed and the decrease in rake angle led to the generation of discontinuous chips in adiabatic shearing conditions. Besides, the larger shear stresses induced by friction in the grain-chip interface contributed to the formation of chips with larger discontinuities. The enlargement of subsurface damage (SSD) depth by 23.86% and 129.42% was caused by the increase in grain edge radius from 0.5 to 2.5 μm and the rise in maximum uncut chip thickness from 0.5 to 1.5 μm, respectively. However, the SSD depth firstly decreased, and then increased with the approach to more negative rake angles and larger cutting speeds. A multi-response optimization based on analysis of variance (ANOVA) and SSD predictive model calculated the optimum combination of influential parameters as maximum uncut chip thickness of 0.719 μm, cutting speed of 80 m/s, cutting edge radius of 0.5 μm, and rake angle of − 30°. This led to the minimum SSD depth of 0.406 μm and the maximum removal rate of 57.493 mm3/mm s. The experimental results confirmed the positive contribution of an eco-friendly nanofluid minimum quantity lubrication (NMQL), containing graphene nanoplatelets with 0.3 wt% concentration within the green nanofluid, to the significant improvement of surface roughness (by 41.09%, relative to dry grinding) and morphology.

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