(Publisher of Peer Reviewed Open Access Journals)

International Journal of Advanced Technology and Engineering Exploration (IJATEE)

ISSN (Print):2394-5443    ISSN (Online):2394-7454
Volume-6 Issue-50 January-2019
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Paper Title : Machining optimization of composite material by using response surface methodology
Author Name : Prateek Yadav and Neeraj Kumar
Abstract :

In this paper, the main objective is an experimental investigation of the various process (input) parameters and performed on a CNC milling machine because it is much better in comparison with other machines in context of accuracy and surface finish. The focus on the properties of the materials along with the cutting condition of the cutting tool and work piece has been made. Design of experiments has been used to study the effect of the main milling parameters such as cutting speed, feed rate and depth of cut on the surface roughness and material removal rate (MRR) of composite material (Al 6063-SiC). After this we use surface roughness and MRR as a response (output) variable in analysis the mathematical model and response surface methodology (RSM) is used for investigation the effect of parameter on surface roughness and MRR. RSM is also used for optimization of these parameters. The effects of three different parameters on the milling process are shown here, which are called cutting speed, depth of cut and feed rate. For this work we conducted 27 experiments from L27 orthogonal array methodology, we use different variables in every single experiment. The value of twenty-seven experiments of surface roughness and material removal rate was achieved by these tests. In this work, this study also serves to determine the contribution of each machining parameters and their interaction for surface roughness and MRR. The results show that the interaction of cutting speed and feed rate is the most relevant parameters of minimizing the surface roughness, feed rate or depth of cut is the influencing factors on maximization of material removal rate.

Keywords : Metal matrix composite, CNC milling machine, Process parameter, Surface roughness, MRR, RSM.
Cite this article : Yadav P, Kumar N. Machining optimization of composite material by using response surface methodology. International Journal of Advanced Technology and Engineering Exploration. 2019; 6(50):1-11. DOI:10.19101/IJATEE.2019.650002.
References :
[1]Patel MT. Optimization of milling process parameters-a review. International Journal of Advanced Research in Engineering and Applied Sciences. 2015; 4(9):24-37.
[Google Scholar]
[2]Malay, Gupta K, Gangwar J, Khan H N, Sharma N P, Mandal A, et al. Optimization of process parameters of CNC milling. International Journal of Advance Research and Innovation. 2016; 3(4):59-63.
[3]Raju BN, Roy MR, Rajesh S, Ramji K. Optimization of machining parameters for cutting AMMC’s on wire cut EDM using RSM. International Journal of Engineering Trends and Technology. 2015;23(2):82-9.
[Google Scholar]
[4]Ribeiro JE, Cesar MB, Lopes H. Optimization of machining parameters to improve the surface quality. Procedia Structural Integrity. 2017; 5:355-62.
[Crossref] [Google Scholar]
[5]Mukkoti VV, Sankaraiah G, Yohan M. Optimization of process parameters in CNC milling for machining P20 steel using NSGA-II. IOSR Journal of Mechanical and Civil Engineering. 2017; 14(3):57-63.
[Crossref] [Google Scholar]
[6]Hashmi KH, Zakria G, Raza MB, Khalil S. Optimization of process parameters for high speed machining of Ti-6Al-4V using response surface methodology. The International Journal of Advanced Manufacturing Technology. 2016; 85(5-8):1847-56.
[Crossref] [Google Scholar]
[7]Vardhan MV, Sankaraiah G, Yohan M, Rao HJ. Optimization of parameters in CNC milling of P20 steel using response surface methodology and Taguchi method. Materials Today: Proceedings. 2017; 4(8):9163-9.
[Crossref] [Google Scholar]
[8]Rudrapati R, Sahoo P, Bandyopadhyay A. Optimization of process parameters in CNC turning of aluminium alloy using hybrid RSM cum TLBO approach. In IOP conference series: materials science and engineering 2016 (pp. 1-13) IOP Publishing.
[Crossref] [Google Scholar]
[9]Singh B, Khanna R, Goyal K, Kumar P. Optimization of input process parameters in CNC milling machine of EN24 steel. International Journal of Research in Mechanical Engineering and Technology. 2013.
[Google Scholar]
[10]Yazdi MS, Khorram A. Modeling and optimization of milling processby using RSM and ANN methods. International Journal of Engineering and Technology. 2010; 2(5):474-80.
[Google Scholar]