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http://dx.doi.org/10.14775/ksmpe.2014.13.4.056

Application of Response Surface Methodology for Modeling and Optimization of Surface Roughness and Electric Current Consumption in Turning Operation  

Punuhsingon, Charles S.C. (Department of Systems Management & Engineering, Pukyong National University)
Oh, Soo-Cheol (Department of Systems Management & Engineering, Pukyong National University)
Publication Information
Journal of the Korean Society of Manufacturing Process Engineers / v.13, no.4, 2014 , pp. 56-68 More about this Journal
Abstract
This paper presents an experiment on the modeling, analysis, prediction and optimization of machining parameters used during the turning process of the low-carbon steel known as ST40. The parameters used to develop the model are the cutting speed, the feed rate, and the depth of the cut. The experiments were carried out under various conditions, with three level of parameters and two different treatments for each level (with and without a lubricant), to determine the effects of the parameters on the surface roughness and electric current consumption. These effects were investigated using response surface methodology (RSM). A second-order model is used to predict the values of the surface roughness and the electric current consumption from the results of experiments which collected preliminary data. The results of the experiment and the predictions of the surface roughness and electric current consumption under both treatments were found to be nearly identical. This result shows that the feed rate is the main factor that influences the surface roughness and electric current consumption.
Keywords
Turning Operation; Response Surface Methodology; Surface Roughness; Electric Current Consumption;
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1 Ahilan at al., "Modeling and prediction of machining quality in CNC turning process using intelligent hybrid decision making tools", Applied Soft Computing, Vol. 13, pp. 1543-1551, 2013.   DOI   ScienceOn
2 Benardos, P.G.,Vosniakos G.C, "Predicting surface roughness in machining: a review", International Journal of Machine Tools & Manufacture, Vol. 43, pp. 833-844, 2003.   DOI   ScienceOn
3 Bhattacharya at al., "Estimating the effect of cutting parameters on surface finish and power consumption during high speed machining of AISI 1045 steel using Taguchi design and ANOVA", Prod. Eng. Res. Devel, Vol. 3, pp. 31-40, 2009.   DOI
4 Davim at al. "Investigations into the effect of cutting conditions on surface roughness in turning of free machining steel by ANN models", Journal of materials processing technology, Vol. 205, pp. 16-23, 2008.   DOI   ScienceOn
5 Palanikumar, "Application of Taguchi and response surface methodologies for surface roughness in machining glass fiber reinforced plastics by PCD tooling", Int. J. Adv Manuf. Technol, Vol. 36, pp. 19-27, 2008.   DOI
6 Joardar at al., "Application of response surface methodology for determining cutting force model in turning of LM6/SiCP metal matrix composite", Measurement, Vol. 47, pp. 452-464, 2014.   DOI   ScienceOn
7 Ezilarasan at al., "An experimental analysis and measurement of process performances in machining of nimonic C-263 super alloy", Measurement, Vol. 46, pp. 185-199, 2013.   DOI   ScienceOn
8 Hamdan at al., "An optimization method of the machining parameters in high-speed machining of stainless steel using coated carbide tool for best surface finish", Int. J. Adv Manuf. Technol, Vol. 58, pp. 81-91, 2012.   DOI
9 Jafarian at al., "Improving surface integrity in finish machining of Inconel 718 alloy using intelligent systems", Int. J. Adv Manuf. Technol, Vol. 71, pp. 817-827, 2014.   DOI   ScienceOn
10 Kaynak., "Evaluation of machining performance in cryogenic machining of Inconel 718 and comparison with dry and MQL machining", Int. J. Adv Manuf. Technol, Vol. 72, pp. 919-933, 2014.   DOI   ScienceOn
11 Makadia and Nanavati, "Optimization of machining parameters for turning operations based on response surface methodology", Measurement, Vol. 46, pp. 1521-1529, 2013.   DOI   ScienceOn
12 Neseli at al., "Optimization of tool geometry parameters for turning operations based on the response surface methodology", Measurement, Vol. 44, pp. 580-587, 2011.   DOI   ScienceOn
13 Sarikaya and Gullu, "Taguchi design and response surface methodology based analysis of machining parameters in CNC turning under MQL", Journal of Cleaner Production, Vol. 65, pp. 604-616, 2014.   DOI   ScienceOn
14 Suresh at al., "Predictive modeling of cutting forces and tool wear in hard turning using response surface methodology", Procedia Engineering, Vol. 38, pp. 73-81, 2012.   DOI   ScienceOn
15 Singh and Rao, "A surface roughness prediction model for hard turning process", Int. J. Adv Manuf. Technol, Vol. 32, pp. 1115-1124, 2007.   DOI
16 Montgomery, C., "Design and Analysis of experiments", 4th ed. Wiley, New York, 1997.