This work investigates the effects of cutting parameters on surface roughness (Ra, µm), cutting temperature (T, °C) at the chip–tool interface and the material removal rate during hard machining of AISI 1015 (43 ± 1 HRC) steel using carbide insert under dry and spray impingement cooling environment. A combined technique using orthogonal array and analysis of variance was employed to investigate the contribution of spindle speed, feed rate, depth of cut and air pressure on responses. It is observed that with spray impingement cooling, cutting performance improves compared to dry cutting. The predicted multi-response optimization setting (N3-f1-d1-P2) ensures minimization of surface roughness, cutting temperature and maximization of material removal rate.
The paper presents the development of flank wear model in turning hardened EN 24 steel with PVD TiN coated mixed ceramic insert under dry environment. The paper also investigates the effect of process parameter on flank wear (VBc). The experiments have been conducted using three level full factorial design techniques. The machinability model has been developed in terms of cutting speed (v), feed (f) and machining time (t) as input variable using response surface methodology. The adequacy of model has been checked using correlation coefficients. As the determination coefficient, R2 (98%) is higher for the model developed; the better is the response model fits the actual data. In addition, residuals of the normal probability plot lie reasonably close to a straight line showing that the terms mentioned in the model are statistically significant. The predicted flank wear has been found to lie close to the experimental value. This indicates that the developed model can be effectively used to predict the flank wear in the hard turning. Abrasion and diffusion has been found to be the dominant wear mechanism in machining hardened steel from SEM micrographs at highest parametric range. Machining time has been found to be the most significant parameter on flank wear followed by cutting speed and feed as observed from main effect plot and ANOVA study
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