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Taguchi Approach to Optimize Surface Roughness for Turning AISI 4340 Steel


Prashant D. Kamble,Atul C. Waghmare,R.D. Askhedkar,R.D. Askhedkar,Shilpa B. Sahare
Abstract

The main aim of this paper is to optimize the material removal rate (MRR) in turning process. Taguchi methodology is used as an optimization tool to optimize the turning process. The input parameters for turning process are Cutting Environment, feed rate, nose radius, depth of cut and tool type. The response variable is Surface Roughness. Consideration of noise factor (uncontrollable factor) makes the design robust. Hence machine tool condition in terms of spindle vibration is taken. Cutting speed is kept constant (210 m/min). The results of ANOVA indicate that feed rate is the most significant machining parameters followed by nose radius, cutting environment, depth of cut and tool type. Based on the main effect plot of S/N ratio, the optimal machining parameters are the cutting environment at level 3 (A3 = MQL), nose radius at level 3 (B3= 1.2 mm), feed rate at level3 (C3=0.35 mm/rev), depth of cut at level 2 (D2 = 1.0 mm), and tool type at level 1 (E1= Uncoated or A3B3C3D2E1 in short. Surface roughness is optimized up to 0.98 um. Conformity test revealed that the predicted and experimental values of Surface roughness are within the range given by confidence interval

Volume 11 | 08-Special Issue

Pages: 3456-3463