IRJET- Determining the Effect of Cutting Parameters in CNC Turning (original) (raw)

Turning is one of the most important metal cutting operations in industries. The process of turning is influenced by many factors such as the spindle speed, feed rate, depth of cut, geometry of cutting tool cutting conditions etc. The finished product with desired attributes of size, shape, surface roughness and cutting forces developed are functions of these input parameters. Properties wear resistance, fatigue strength, coefficient of friction, lubrication, wear rate and corrosion resistance of the machined parts are greatly influenced by surface roughness. Surface roughness and material removal rate are the performance characteristics on the basis of which the machining parameters, including spindle speed, feed rate, depth of cut and material type are optimized in this dissertation work. The layout of the experiment is designed based on Taguchi's L16 orthogonal array and analysis of variance (ANOVA) is used to identify the effect of the machining parameters on individual responses. The S/N ratio is used to analyze the performance characteristics in CNC turning operation. The S/N ratio values are calculated by taking into consideration with the help of software Minitab 17 (trial version). Four levels of each machining parameters are used and experiments are done on MAXTURN PLUS, CNC lathe machine tool of MATAB using carbide insert tool. The results shows that optimum parameter for surface roughness is speed 1500 rpm (level 4), feed rate 0.1 mm/rev (level 1), depth of cut 1.0 mm (level 4) and material type EN47 (level 4). Whereas for material removal rate the optimum parameter is speed 1500 rpm (level 4), feed rate 0.19 mm/rev (level 4), depth of cut 1.0 mm (level 4) and material type EN8 (level 1). Further the ANOVA results shows that spindle speed and feed rate have statistically significant effect on surface roughness and in case of material removal rate depth of cut has statistically significant effect. A confirmation experiment is carried out to verify the optimal process parameter settings obtained during this study. The confirmation test results shows that the predicted values of surface roughness and material removal rate are in the acceptable zone with respect to the experimental values based on the optimized process parameters.