JMMCE  Vol.3 No.4 , July 2015
Analysis on Multi Responses in Face Milling of Ammc Using Fuzzy-Taguchi Method
ABSTRACT
In this paper, Fuzzy-Taguchi Method has been used to identify the optimal combination of influential factors by analyzing the multi responses in the face milling. Milling experiment has been performed on AMMC (Aluminium Metal Matrix Composite), according to Taguchi orthogonal array (L27) for various combinations of influential parameters: speed, feed, depth of cut and coolant. Fuzzy logic is applied for the analysis of experimental response data of vibrations, temperature, surface roughness and resultant forces. The Fuzzy grade is calculated from this data and Fuzzy grade is optimized using Taguchi method in order to get the optimal parameter values, and also influence of parameters on individual responses is studied using Taguchi S/N ratio analysis. This work is useful for analysis of machining parameters in face milling.

Cite this paper
Sukumar, M. , Reddy, B. and Venkataramaiah, P. (2015) Analysis on Multi Responses in Face Milling of Ammc Using Fuzzy-Taguchi Method. Journal of Minerals and Materials Characterization and Engineering, 3, 255-270. doi: 10.4236/jmmce.2015.34028.
References
[1]   Shivanand, H.K., Benal, M.M., Sharma, S.C. and Govindraju, N. (2004) Comparative Studies on Mechanical Properties of Aluminium Based Hybrid Composites Cast by Liquid Melt Technique and P/M Route. Materials Processing for Properties and Performance, 3, 57-60.

[2]   Dalalah, D and Bataineh, O. (2009) A Fuzzy Logic Approach to the Selection of the Best Silicon Crystal Slicing Technology. Expert Systems with Applications, 36, 3712-3719.
http://dx.doi.org/10.1016/j.eswa.2008.02.020

[3]   Kuttolamadom, M.A., Hamzehlouia, S. and Laine Mears, M. (2010) Effect of Machining Feed on Surface Roughness in Cutting 6061 Aluminum. International Center for Automotive Research, Clemson university, South Carolina, United state, 2010-01-0218.

[4]   Soleymani Yazdi, M.R. and Khorram, A. (2010) Modeling and Optimization of Milling Process by Using RSM and ANN Methods. International Journal of Engineering and Technology, 2, 474-480. http://dx.doi.org/10.7763/IJET.2010.V2.167

[5]   Abuthakeer, S.S., Mohanram, P.V. and Mohankumar, G. (2011) The Effect of Spindle Vibration on Surface Roughness of Workpiece in Dry turning using ANN. International Journal of Lean Thinking, 2.

[6]   Gunay, M., Kacal, A. and Turgut, Y. (2011) Optimization of Machining in Milling of Ti-6Al-4V Alloy using Taguchi method. e-Journal of New World Sciences Academy, 6, Article No. 1A0165.

[7]   Çal1skan, H., Kurbanoglu, C., Panjan, P. and Kramar, D. (2012) Investigation of the Performance of Carbide Cutting Tools with Hard Coatings in Hard Milling Based on the Response Surface Methodology. The International Journal of Advanced Manufacturing Technology, 66, 883-893. http://dx.doi.org/10.1007/s00170-012-4374-y

[8]   Globocki Lakic, G., Sredanovic, B., Kramar, D., Nedic, B. and Kopac, J. (2013) Experimental Research Using of MQL in Metal Cutting. Tribology in Industry, 35, 276-285.

[9]   Al-Zubaidi, S. Ghani, J.A., Hassan, C. and Haron, C. (2013) Optimization of Cutting Conditions for End Milling of TiAL4V by Using a Gravitational Search Algorithm. Mechanica, 48, 1710-1715.

[10]   Jatin, P.S. (2013) Effect of Machining Parameters on Output Characteristics of CNC Milling Using Taguchi Optimization Technique. IJEBEA 13-335, 2013.

[11]   Venkata Ramaiah, P., Rajesh, N. and Dharma Reddy, K. (2013) Determination of Optimum Influential Parameters in Turning of Al6061 Using Fuzzy Logic. IJIRSET, 2.

[12]   Das, B., Roy, S., Rai, R.N. and Saha, S.C. (2014) Surface Roughness of Al-5Cu Alloy Using a Taguchi-Fuzzy Based Approach. Journal of Engineering Science and Technology Review, 7, 217-222.

 
 
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