Taguchi Grey Relational Analysis in Assessment of Surface Roughness and Flank Wear in Machining Optimization of AISI 4140 Steel

Abstract

Machining is important in metal manufacturing process to achieve near-nett shape, good dimensional accuracy and aesthetic requirements. But the current scenario depicts that the manufacturing industries constant focus is on lowering cost solutions with reduced lead time, better surface quality, maintaining competitiveness and efficiency. The work material considered in this work is AISI4140 alloy steel. This work material is machined using carbide tool with cutting speed, feed and depth of cut taken as the process parameters. The responses considered against these process parameters are surface roughness and flank wear. Designs of experiments are used to conduct the experiments for minimization of surface roughness and flank wear. Orthogonal array design is implemented to conduct the several experiments. Surface Roughness is measured using Mitutoyo Surface roughness tester and flank wear are investigated using scanning electron microscope. The Taguchi grey or grey relation analysis correlates the experimental data and the desired data and calculates the grey relational coefficient. This grey relational coefficient is used to determine the overall grey relational grade corresponding to the selected responses. The grey relation coefficient and grade are presented in this paper and proves to be consistent. The response graph for average grey relational grade and ANOVA for grey relational grade are also presented.