Optimization and Prediction of Cutting Force and Surface Roughness in End Milling Process of AISI 304 Stainless Steel

Abstract:

The end milling process is most commonly used where the large amount material can be removed to produce almost final shape of component. The present work deals with the experimental study and optimization the machining parameter of AISI 304 stainless steel. The effects of spindle speed, feed rate and depth of cut have been studied on the cutting force and surface roughness using Taguchi’s 27 orthogonal arrays. Regression analyses were used to develop the model of response parameters. The analysis of the result shows, the surface roughness and the cutting force is increased with feed rate and depth of cut but decreased with increased the cutting speed. The ANOVA indicate the feed rate was the most dominate parameter on surface roughness and cutting force than speed and depth of cut.

• Periodical: Applied Mechanics and Materials (Volumes 813-814)
• Pages: 362-367
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.813-814.362
• Online since: November 2015
• Authors: Darshan A. Patel, Jitendra M. Mistry, Vrushit P. Kapatel, Dhaval R. Joshi
• Keywords: ANOVA, Cutting Force, Regression, Surface Roughness, Taguchi

References

[1] Julie Z. Zhang, Joseph C. Chen, E. Daniel Kirby, Surface roughness optimization in an end-milling operation using the Taguchi design method, Journal of Materials Processing Technology 184 (2007) 233–239.

DOI: 10.1016/j.jmatprotec.2006.11.029

[2] Mohamad Syahmi Shahrom , Nafrizuan Mat Yahya and Ahmad Razlan Yusoff, Taguchi Method Approach on Effect of Lubrication Condition on Surface Roughness in Milling Operation, Procedia Engineering 53 ( 2013 ) 594 – 599.

DOI: 10.1016/j.proeng.2013.02.076

[3] P.G. Benardos, G.C. Vosniakos, Prediction of surface roughness in CNC face milling using neural networks and Taguchi's design of experiments, Robotics and Computer Integrated Manufacturing 18 (2002) 343–354.

DOI: 10.1016/s0736-5845(02)00005-4

[4] J.A. Ghani, I.A. Choudhury, H.H. Hassan, Application of Taguchi method in the optimization of end milling parameters, Journal of Materials Processing Technology 145 (2004) 84–92.

DOI: 10.1016/s0924-0136(03)00865-3

[5] P Palanisamy, Prediction of cutting force and temperature rise in the end-milling operation, Journal of Engineering Manufacture (2006) 220: 1577.

[6] K.A. Abou-El-Hossein , K. Kadirgama, M. Hamdi, K.Y. Benyounis, Prediction of cutting force in end-milling operation of modified AISI P20 tool steel, Journal of Materials Processing Technology 182 (2007) 241–247.

DOI: 10.1016/j.jmatprotec.2006.07.037

[7] Emel Kuram , Babur Ozcelik, Multi-objective optimization using Taguchi based grey relational analysis for micro-milling of Al 7075 material with ball nose end mill, Measurement 46 (2013) 1849–1864.

DOI: 10.1016/j.measurement.2013.02.002

[8] Mohammed T. Hayajneh, Montasser S. Tahat, Joachim Bluhm, A Study of the Effects of Machining Parameters on the Surface Roughness in the End-Milling Process, Volume 1, Number 1, Sep. 2007 ISSN 1995-6665 Pages 1 – 5.

[9] Bhuvnesh Bhardwaj, Rajesh Kumar and Pradeep K Singh, Effect of machining parameters on surface roughness in end milling of AISI 1019 steel, Journal of Engineering Manufacture 2014 228: 704.

DOI: 10.1177/0954405413506417

[10] N. Suresh Kumar Reddy, P. Venkateswara Rao, Experimental investigation to study the effect of solid lubricants on cutting forces and surface quality in end milling, International Journal of Machine Tools & Manufacture 46 (2006) 189–198.

DOI: 10.1016/j.ijmachtools.2005.04.008

[11] Turgay Kıvak, Optimization of surface roughness and flank wear using the Taguchi method in milling of Hadfield steel with PVD and CVD coated inserts, Measurement 50 (2014) 19–28.

DOI: 10.1016/j.measurement.2013.12.017