Analysis on surface finish and chip morphology during dry turning process. (2021) - Mohan, R.; Harshavardhana, N.; Chaudhari, Manish; Jeyanthi, S.; Abimannan, Giridharan
Highlights: Proposed a regression model to predict surface roughness and chip thickness. Roughness profile and SEM images are used to study surface finish and chip thickness. Analyzed the effect of process variables on surface roughness and chip thickness. Abstract: In this paper the effect of input variables such as spindle rotation, feed rate and depth of cut on surface roughness and chip thickness which were taken as the output parameters were analysed during dry turning process. Single point carbide turning insert and AISI D2 tool steel were used as cutting tool and workpiece material respectively. 2D roughness profile and scanning electron microscope images were used to analyse surface roughness and chip thickness respectively. It is observed that surface roughness and chip thickness are affected mostly by feed rate. Minimum surface roughness of 0.242 μm and least chip thickness of 0.233 mm were achieved. A multiple linear regression model is proposed to estimate the influence of input variables on surface roughness and average chip thickness. The model predicts surface roughness and chip thickness with R 2 = 77.5% and R 2 = 78.1% respectively.