Optimization of Cutting Conditions for Surface Roughness in VMC 5-Axis

Abstract:

Vertical machining center (VMC) five-axis is advanced metal cutting process which used tomachine advanced materials for creating parts for industries like die, automotive, aerospace, machinerydesign, etc. Input parameters selection very important in VMC-five axis to obtain better surface finishon milled part and enhanced machining economics. In the present work, experimental analysis has beenplanned to study the significances of milling parameters on quality response, surface roughness (Ra) ofD3 steel. The experiments have been planned on D3 steel in VMC five axis as per Box-Behnken designof response surface methodology (RSM). Modeling and optimization have been done by hybrid RSMand Jaya optimization algorithm. The factor effects on Ra has been studied by analysis of signal-tonoise ratio. The concluding remarks has been drawn from the study

• Periodical: Materials Science Forum (Volume 969)
• Pages: 631-636
• DOI: https://doi.org/10.4028/www.scientific.net/MSF.969.631
• Online since: August 2019
• Authors: Ramesh Rudrapati*, Arun Patil
• Keywords: Jaya Algorithm, Milling, Milling Parameters, Response Surface Methodology, VMC Five-Axis

References

[1] J. Kundrák, A. P. Markopoulos, T. Makkai, N. E. Karkalos, A. Nagy, Multi-objective optimization study in face milling of steel. Proceed. of the Int. Sympos. for Prod. Resea. (2019) 3–15.

DOI: 10.1007/978-3-319-92267-6_1

[2] Lamikiz, L. N. L. de Lacalle, O. Ocerin, D. Díez, E. Maidagan, The Denavit and Hartenberg approach applied to evaluate the consequences in the tool tip position of geometrical errors in five-axis milling centres. Int J Adv Manuf Technol 37 (2008) 122–139.

DOI: 10.1007/s00170-007-0956-5

[3] D. P. Selvaraj, P. Chandramohan, P. Chandrasekar, Experimental investigations of nitrogen alloyed duplex stainless steel in dry milling process. J. of Engi. Sci. and Technol. 13 (2018) 321 – 331.

[4] T. Ozel, T. K. Hsu, E. Zeren, Effects of cutting edge geometry, workpiece hardness, feed rate and cutting speed on surface roughness and forces in finish turning of hardened AISI H13 steel. Int. J. Adv. Manuf. Technol. 25 (2005) 262–269.

DOI: 10.1007/s00170-003-1878-5

[5] P. V. Vinay, CH. S. Rao, Experimental analysis and modelling of grinding AISI D3 steel. Int. J. of Recent Adv. in Mecha. Engi. 4 (2015) 47-60.

DOI: 10.14810/ijmech.2015.4105

[6] R. Rudrapati, A. Bandyopadhyay, P. K. Pal. Investigation on surface roughness in cylindrical grinding. American Institute of Physics Conf. Proceed. 1315 (2011) 1359-1364.

[7] Md. A. P. Ullah, A. K. M. N. Amin, M. D. Arif, Optimization of surface roughness in end milling of medium carbon steel by coupled statistical approach with genetic algorithm. The First Int. Conf. on Interdisci. Resea. and Develop. (2011) Thailand.

[8] R. V. Rao. Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems. Int. J. of Industr. Engi. Comput. 7 (2016) 19–34.

DOI: 10.5267/j.ijiec.2015.8.004

[9] J. X. Ren, C. F. Yao, D. H. Zhang, Y. L. Xue, Y. S. Liang, Research on tool path planning method of four-axis high-efficiency slot plunge milling for open blisk. Int. J. Adv. Manuf. Technol. 45 (2009) 101–109.

DOI: 10.1007/s00170-009-2153-1

[10] X. FuGui, L. XinJun, Z. Hui, W. JinSong. Design and experimental study of the SPKM165, a five-axis serial-parallel kinematic milling machine. Sci. China Technol. Sci. 54 (2011) 1193–1205.

DOI: 10.1007/s11431-011-4314-3

[11] C. Zhang, H. Zhang, Y. Li, L. Zhou, Modeling and on-line simulation of surface topography considering tool wear in multi-axis milling process. Int. J. Adv. Manuf. Technol. 77 (2015) 735-749.

DOI: 10.1007/s00170-014-6485-0

[12] T.V. Do, N. A. Vu Le. Optimization of surface roughness and cutting force in MQL hard-milling of AISI H13 steel. LNNS 63 (2019) 448–454.

DOI: 10.1007/978-3-030-04792-4_58

[13] R. Rudrapati, P. Sahoo, A. Bandyopadhyay. Parametric optimization in CNC turning of aluminum alloy using hybrid RSM cum TLBO approach. IOP Conf. Series Mate. Sci. and Engg. 149 (2016) 1-13.

DOI: 10.1088/1757-899x/149/1/012039

[14] I. P. Okokpujie, O. O. Ajayi, S. A. Afolalu, A. A. Abioye, E.Y. Salawu, M. O. Udo, U. C. Okonkwo, K. B. Orodu, O. M. Ikumapayi, Modeling and optimization of surface roughness in end milling of aluminium using least square approximation method and response surface methodology, Int. J. of Mecha. Engi. and Technol. 9 2018 587–600.

[15] R.V. Rao, D.P. Rai, J. Balic, Surface grinding process optimization using Jaya algorithm. Comput. Intellig. in Data Mining 2 (2016) 487-495.

DOI: 10.1007/978-81-322-2731-1_46

[16] K. Abhishek, V. R. Kumar, S. Datta, S. S. Mahapatra. Application of JAYA algorithm for the optimization of machining performance characteristics during the turning of CFRP (epoxy) composites: comparison with TLBO, GA, and ICA. Engi. with Comp. 33 (2017) 457–475.

DOI: 10.1007/s00366-016-0484-8

[17] R. V. Rao, D.P. Rai, J. Balic, A new optimization algorithm for parameter optimization of nano-finishing processes. Scientia Iranica E 24 (2017) 868-875.

DOI: 10.24200/sci.2017.4068

[18] M. Das, R. Rudrapati, N. Ghosh, L. Rathod, Input Parameters optimization in EDM Process using RSM and JAYA Algorithm. Int. J. of Current Engi. and Technol. (2016) 109-112.

[19] R. Rudrapati, P. k. Pal, A. Bandyopadhyay, Modeling of surface roughness in cylindrical grinding. Int. J. of Machi. and Machi. of Mate. 12 (2012) 28-36.