Taguchi Based Grey Relational Analyses for Multi Response Optimization of Control Parameters in CNC Turning of Aluminium 7075 Alloy

Abstract

-High speed turning has emerged as a key manufacturing technology in machining of different metals and alloys. Turning at high speed is performed on the order of five to ten times the conventional cutting speed. It is advantageous in many ways like reduction in cutting forces and temperature, low power consumption, improvement in surface finish, high MRR, better dimensional accuracy and better part quality [1, 2]. In order to achieve the quality output, it is necessary to optimize the process parameters (like speed, feed, depth of cut, nose radius) during the high speed machining of alloy. To achieve this goal, the current research work is aimed at optimizing the input parameters of CNC turning. The study applies Taguchi's design of experiment methodology and grey relational analysis to optimize the process parameters in turning aluminum alloy AA7075-T6 material, a high strength aluminum alloy used for aerospace application using coated carbide insert under dry environment condition and having four type insert nose radius such as 0.2, 0.4, 0.8, 1.2 mm. Experiment have been carried out based on L16 standard orthogonal array design with four process parameters namely cutting speed, feed rate , Depth of cut and nose radius for surface roughness and Material removal rate[3, 4].The data was analyzed using Grey Relational Analysis (GRA) coupled with Principal Component Analysis (PCA). Analysis of S/N ratio was done to obtain the optimum combination of input parameters. The Grey Relational Grade (GRG) at optimum setting of the input parameters was obtained by Regression analysis. The experimental results were validated by comparing the experimental value of GRG with that of the predicted value and the comparison shows a good relationship between them.

Optimizing the five magnetic abrasive finishing factors on surface quality using Taguchi-based grey relational analysis

“…Grey relational analysis (GRA)The GRA is a strategy for determining and describing the relationships that exist among a number of different responses. It is comprised of four stages, which are outlined in more detail below[49][50][51][52][53].…”