Parametric Optimization of CNC End Milling Process on Aluminium 6063 Alloy Using Grey Based Taguchi Method

Abstract:

This investigation focused on the multi-response optimization of CNC end milling of Aluminium 6063 Alloy material using Grey relational analysis and Taguchi method. Experiments were designed based on L9 Taguchi Orthogonal array, to arrive at an optimum parameter combination within the experimental domain. The spindle speed (S), feed rate (f) and depth of cut (d) which are known to have considerable effect on the selected responses i.e. surface roughness (Ra) and Material removal rate (MRR) and are considered as control parameters. The single objective optimization using Taguchi method more often results in conflicting requirements on control variables. To overcome this challenge, the Taguchi approach followed by Grey relational analysis was applied to solve this multi response optimization problem. The significance of these factors on overall quality characteristics of the milling process has also been evaluated quantitatively with the Analysis of variance method (ANOVA). Optimal results were verified through confirmation experiments. This shows feasibility of the Grey relation analysis in combination with Taguchi technique for continuous improvement in product quality in manufacturing industry and the suitability of the method to optimize the multi objective problems involved in CNC milling.

• Periodical: Applied Mechanics and Materials (Volume 867)
• Pages: 148-156
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.867.148
• Online since: July 2017
• Authors: Md Ashfaq Hussain*, K.K. Prasad, Anil S. Jadhav, Gangadhar Biradar
• Keywords: ANOVA, CNC End Milling Process, Grey Relation Analysis, Taguchi Method

References

[1] Sanjit Moshat, Saurav Datta. Asish Bandyopadhyay, & Pradip Kumar Paul, Parametric Optimization Of CNC End Milling Using Entropy Measurement Technique Combined With Grey Taguchi Method, International Journal Of Engineering, Science & Technology Vol. 2. No. 2. 2010, PP. 1-12.

DOI: 10.4314/ijest.v2i2.59130

[2] S. Thamizhmanii, S. Saparudin, S. Hasan. Analysis of Surface Roughness by Turning Process Using Taguchi Method, Journal of Achievement in Materials and Manufacturing Engineering, Volume20 Issues1-2 Jan-Feb (2007).

[3] Sanjit Moshat, Saurav Datta, Asish Bandyopadhyay, Pradip Kumar Paul, Parametric Optimization of CNC End Milling Process Parameter Using PCA Based Taguchi Method, International Journal of Engineering, Science & Technology vol. 2. No. 2. 2010. PP. 92-102.

DOI: 10.4314/ijest.v2i1.59096

[4] N. Ghosh, Y B Ravi, A Patra, S. Mukhopadhyay, S Paul, A.R. Mohanty, A. B. Chattopadhay Estimation Of Tool Wear During CNC Milling Using Neural Network Based Sensor Fusion, Mechanical System And Signal Processing 21-2007 p(466-479).

DOI: 10.1016/j.ymssp.2005.10.010

[5] Ab. Rashid M. F. F, Gans. Y, Muhammad N.Y. Mathematical Modeling to Predict Surface Roughness in CNC Milling. World Academy of Science, Engineering and Technology 53 (2009).

[6] Bulent Kaya, Cuneyt Oysu, Huseyin M. Eratic Force-Torque Based On Line Tool Wear Estimation System For CNC Milling Of Inconel 718 Using Neural Networks, Advanced engineering software42-2011 76-84.

DOI: 10.1016/j.advengsoft.2010.12.002

[7] Lohithaksha M Maiyar, Dr.R. Ramanujam, K. Venkatesan, Dr. J. Jerald Optimization of Machining Parameters for end milling of Inconel 718 Super Alloy Using Taguchi Based Grey Relational Analysis, 2013. Procedia Engineering. 64. 1276 – 1282.

DOI: 10.1016/j.proeng.2013.09.208

[8] Ugur Esme "use of Grey based Taguchi method in ball burnishing process for the optimization of surface roughness and Micro hardness of AA7075 aluminum alloy. 2010. Original scientific article. ISSN 1580-2949. UDK 669. 715: 620. 178.

[9] Madhav S Padke" Quality Engineering using Robust Design". 1989. Prentice Hall, Eaglewoods Cliffs, New Jersey-(1989).