This research explores the flank wear (VB), surface roughness (Ra) and chip morphology in turning of AISI D7 steel using AlTiSiN coated carbide tool under zinc oxide (ZnO) enriched nanofluid with minimum quantity lubrication (MQL) environment, which has not been addressed before. Experiments involving 30 trials were carried out, considering machining variables, viz. feed, nose radius, depth of cut, and cutting speed. A combined approach of central composite design of response surface method (RSM), analysis of variance, and desirability function approach (DFA) was applied for experimental investigation, prediction modeling, and multiple response optimization of surface roughness and flank wear in turning. Based on the research, the most leading factor influencing surface roughness and tool wear was the cutting speed. Machining under high nose radius resulted in enhanced surface finish, reduced tool vibration and tool wear. Under nano-MQL conditions, chip morphology exhibited the formation of segmented, saw-toothed chips. At high cutting speeds, several notable changes were observed: (a) the saw-tooth profile became more pronounced, (b) the spacing between individual teeth increased, (c) chip segmentation frequency decreased, and (d) overall chip thickness was reduced. The serrated edge saw-toothed chip formation during turning led to increased flank wear. Tool vibration corresponds to deteriorated surface morphology. The combination of AlTiSiN coated tool, and effective nano-MQL cooling-lubrication contributed to lower range of VB (0.137–0.293 mm) and Ra (0.248–0.425 µm) in turning. The optimum conditions for AISI D7 steel turning under nano-MQL determined using DFA, are feed of 0.04 mm/rev, cutting speed of 124 m/min, 1.2 mm of nose radius, and doc of 0.1 mm, leading to an optimal surface roughness (Ra = 0.263 µm), and flank wear (VB = 0.1704 mm).
Swain et al. (Sat,) studied this question.