Taguchi Based Grey Relational Analyses for Multi Objective Optimization of Response Variables in CNC Lathe Turning of Aluminium 7075 Alloy

  Navneet Saini,  Jitender Panchal

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 set the process parameters (like speed, feed, depth of cut, nose radius) in such a way that it gives optimum combination of MRR and Surface roughness at the same time during the high speed machining of alloy. The study applies Taguchi's design of experiment methodology and grey relational analysis to optimize the response 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 Mean was used to obtain the best set of input parameters. The Grey Relational Grade (GRG) was obtained by Regression analysis at the value of input parameters suggested by optimization technique. 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.

Keywords- Nose radius, MRR, surface roughness, grey relational analysis, Taguchi approach

Unique Identification Number - IJEDR1703189
Page Number(s) - 1287-1297
Pubished in - Volume 5 | Issue 3 | September 2017
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Navneet Saini,  Jitender Panchal,   "Taguchi Based Grey Relational Analyses for Multi Objective Optimization of Response Variables in CNC Lathe Turning of Aluminium 7075 Alloy", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 3, pp.1287-1297, September 2017, Available at :http://www.ijedr.org/papers/IJEDR1703189.pdf