GRA OF SAE 8620 FOR OPTIMIZING SURFACE ROUGHNESS AND MATERIAL REMOVAL RATE

Low carbon Alloy steel has widespread applications in industries. In present work machining parameters for SAE 8620 have been optimized using Grey relational analysis (GRA) in view ofsurface roughness (SR) and material removal rate (MRR) as responses.Machining experiments were conducted on CNC lathe machine.L27 orthogonal array design has been used to develop relationships for predicting SR and MRR. MS EXCEL software has been used for analysis grey relational grade of each level of parameters. The optimum parameter values have been achieved for turning performance with respect toSR and MRR. Feed rate (FR)has shown significant role on turning performance with 95% confidence interval.Low carbon Alloy steel has widespread applications in industries. In present work machining parameters for SAE 8620 have been optimized using Grey relational analysis (GRA) in view ofsurface roughness (SR) and material removal rate (MRR) as responses.Machining experiments were conducted on CNC lathe machine.L27 orthogonal array design has been used to develop relationships for predicting SR and MRR. MS EXCEL software has been used for analysis grey relational grade of each level of parameters. The optimum parameter values have been achieved for turning performance with respect toSR and MRR. Feed rate (FR)has shown significant role on turning performance with 95% confidence interval