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IJCERT Journal ISSN(Online):2349-7084

International Journal
of Computer Engineering in Research Trends (IJCERT)

Scholarly, Peer-Reviewed, Open Access and Multidisciplinary


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International Journal of Computer Engineering in Research Trends. Scholarly, Peer-Reviewed,Open Access and Multidisciplinary

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Experimental Study of the Effects of Machining Parameters on the Surface Roughness in the Turning Process

Vikas B. Magdum , Dr. Vinayak R. Naik , , ,
Affiliations
1* Assistant Professor, Department of Mechanical Engineering, D. K. T. E. Society’s Textile and Engineering Institute, Ichalkaranji, Maharashtra, India, 416115 2 Professor and Head, Department of Mechanical Engineering, D. K. T. E. Society’s Textile and Engineering Institute, Ichalkaranji, Maharashtra, India, 416115
:10.22362/ijcert/2018/v5/i5/v5i502


Abstract
In this work, experiments are carried out to study the effect of cutting parameters cutting speed, feed rate, and depth of cut on surface roughness during dry turning of 40C8. The objective of this study is to build multiple regression models for a better understanding of the effects of spindle speed, feed and depth of cut on the surface roughness. Full factorial design of experiments corresponding to trials was followed for the experimental design. Analysis of variance determines the contribution of each factor on the output. It is found that feed rate is the most influencing parameter affecting the surface roughness (44.13%) and is followed by cutting speed and depth of cut. The developed predicted model, which includes the effect of spindle speed, feed rate an extent h decrease t and any two-variable interactions, gives an accuracy of about 91.91 %. This study is helpful for understanding and controlling effect of cutting parameters on the surface finish of machined surfaces in dry turning operation.


Citation
Vikas B. Magdum , Dr. Vinayak R. Naik (2018). Experimental Study of the Effects of Machining Parameters on the Surface Roughness in the Turning Process. International Journal of Computer Engineering In Research Trends, 5(5), 141-147. Retrieved from http://ijcert.org/ems/ijcert_papers/V5I502.pdf


Keywords : Surface Finish; ANOVA; Regression, Surface Roughness; Turning, SN ratio.

References
[1] C. Natarajan, S. Muthu and P. KaruPPuswamy, “Investigation of cutting parameters of surface roughness for a non-ferrous material using the artificial neural network in CNC turning”, Journal of Mechanical Engineering Research, ISSN 2141 – 2383 ©2011 Academic Journals, Vol. 3(1), PP. 1-14, January 2011.
[2] Ilhan asilturk, Harun Akkus, “Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method”, Measurement, Elsevier Ltd, PP 1-8, 2011.
[3] Jithin babu.r, a Ramesh Babu, “Correlation among the cutting parameters, surface roughness and cutting forces in turning process by experimental studies”, 5th International & 26th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014), IIT Guwahati, Assam, India, PP 459.1-459.6, December 12th –14th , 2014.
[4] Ilhan Asilturk, “On-line surface roughness recognition system by vibration monitoring in CNC turning using adaptive neuro-fuzzy inference system (ANFIS)”, International Journal of the Physical Sciences, ISSN 1992 - 1950 ©2011 Academic Journals Vol. 6(22), 2011, PP. 5353-5360, 2 October.
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[6] Suleyman Neseli, Suleyman Yaldız, Erol Turkes, “Optimization of tool geometry parameters for turning operations based on the response surface methodology”, Measurement, Elsevier, 44,  PP 580–587, 2011.
[7] H. M. Somashekara, Dr. N. Lakshmana Swamy, “Optimizing surface roughness in turning operation using Taguchi technique and ANOVA”, International Journal of Engineering Science and Technology (IJEST), ISSN: 0975-5462, Vol. 4, No.05, PP 1967-1973, May 2012.
[8] Jignesh G. Parmar, Prof. Alpesh Makwana, “Prediction of surface roughness for end milling process using Artificial Neural Network”, International Journal of Modern Engineering Research (IJMER), ISSN: 2249-6645, Vol.2, Issue.3, PP-1006-1013, May-June 2012. 
[9] M.F.F. Ab. Rashid and M.R. Abdul Lani, “Surface Roughness Prediction for CNC Milling Process using Artificial Neural Network”, Proceedings of the World Congress on Engineering 2010 Vol III, WCE 2010, London, U.K., PP 1-6, June 30 - July 2, 2010.
[10] M. Nalbant, H. Gokkaya, G. Sur, “Application of Taguchi method in the optimization of cutting parameters for surface roughness in turning”, Materials and Design, Elsevier, 28, PP 1379–1385, 2007.
[11] G. Akhyar, C. H. Che Haron, J. A. Ghani, “Application of Taguchi method in the optimization of tuning parameters for surface roughness”, International Journal of Science Engineering and Technology, ISSN: 1985-3785, Vol. 1, No. 3, PP 60-66, 2008.
[12] Dr. S. S. Mahapatra, Amar Patnaik, Prabina Ku. Patnaik, “Parametric Analysis and Optimization of Cutting Parameters for Turning Operations based on Taguchi Method”, Proceedings of the International Conference on Global Manufacturing and Innovation, PP 1-9, July 27-29, 2006.


DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i5/v5i502

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DOI:10.22362/ijcert