A Method for the Determination of Theoretical Roughness in Face Milling Considering the Run-Out of the Inserts

Abstract:

A method is introduced for determining theoretical values of roughness characteristics of surfaces generated by tools having a defined edge geometry. The method is based on the CAD modelling of the theoretical cut surface, and can be used to model practically any complex tool geometry. In application to rotating tools (e.g. face milling), besides the variety of tool designs, the setting accuracy was also taken into consideration during the determination of theoretical values due to the simultaneous cutting of more than one edge. It will be demonstrated that in addition to the determination of 2D roughness parameters, the method is suitable to determine the 3D roughness parameters as the surface topography can be more accurately described with these characteristics. Experimental data is shown to validate of the extended modelling and calculation method.

• Periodical: Solid State Phenomena (Volume 261)
• Pages: 251-258
• DOI: https://doi.org/10.4028/www.scientific.net/SSP.261.251
• Online since: August 2017
• Authors: Csaba Felho*, János Kundrák
• Keywords: CAD Modelling, Face Milling, Surface Roughness

References

[1] P. Tamas, B. Illes: Process Improvement Trends for Manufacturing Systems in Industry 4. 0, Academic Journal of Manufacturing Engineering 14-4 (2016) 119-125.

[2] L. Dudás, M. Biró, L. L. Novák: Construction Modeling and Manufacturing Analysis of a New Rotary Combustion Engine, Intelligent Engineering Systems (INES), 2016 IEEE 20th Jubilee International Conference on. IEEE (2016) 89-94.

DOI: 10.1109/ines.2016.7555099

[3] P. Munoz-Escalona, P.G. Maropoulos, A geometrical model for surface roughness prediction when face milling Al 7075-T7351 with square insert tools, Journal of Manufacturing Systems 36 (2015) 216–223.

DOI: 10.1016/j.jmsy.2014.06.011

[4] N. Tamiloli, J. Venkatesan, B. Vijaya Ramnath, A grey-fuzzy modeling for evaluating surface roughness and material removal rate of coated end milling insert, Measurement 84 (2016) 68–82.

DOI: 10.1016/j.measurement.2016.02.008

[5] N. Liu, S.B. Wang, Y.F. Zhang, W.F. Lu, A novel approach to predicting surface roughness based on specific cutting energy consumption when slot milling Al-7075, International Journal of Mechanical Sciences 118 (2016) 13–20.

DOI: 10.1016/j.ijmecsci.2016.09.002

[6] S. Sheth, P.M. George, Experimental Investigation and Prediction of Flatness and Surface Roughness during Face Milling Operation of WCB Material, Procedia Technology 23 (2016) 344–351.

DOI: 10.1016/j.protcy.2016.03.036

[7] M. H. Ali, B. A. Khidhir, M.N.M. Ansari, B. Mohamed, FEM to predict the effect of feed rate on surface roughness with cutting force during face milling of titanium alloy, Housing and Building National Research Center (HBRC) Journal 9 (2013).

DOI: 10.1016/j.hbrcj.2013.05.003

[8] H. Hassanpour, M. H. Sadeghi, A. Rasti, S. Shajari, Investigation of surface roughness, microhardness and white layer thickness in hard milling of AISI 4340 using minimum quantity lubrication, Journal of Cleaner Production 120 (2016) 124–134.

DOI: 10.1016/j.jclepro.2015.12.091

[9] M. Hadad, M. Ramezani, Modeling and analysis of a novel approach in machining and structuring of flat surfaces using face milling process, International Journal of Machine Tools & Manufacture 105 (2016) 32–44.

DOI: 10.1016/j.ijmachtools.2016.03.005

[10] P. Michalik, J. Zajac, M. Hatala, D. Mital, V. Fecova, Monitoring surface roughness of thin-walled components from steel C45 machining down and up milling, Measurement 58 (2014) 416–428.

DOI: 10.1016/j.measurement.2014.09.008

[11] N. Masmiati, A.A.D. Sarhan, M.A.N. Hassan, M. Hamdi, Optimization of cutting conditions for minimum residual stress, cutting force and surface roughness in end milling of S50C medium carbon steel, Measurement 86 (2016) 253–265.

DOI: 10.1016/j.measurement.2016.02.049

[12] S. Wojciechowski, P. Twardowski, M. Pelic, R.W. Maruda, S. Barrans, G.M. Krolczyk, Precision surface characterization for finish cylindrical milling with dynamic tool displacements model, Precision Engineering 46 (2016) 158–165.

DOI: 10.1016/j.precisioneng.2016.04.010

[13] N.E. Karkalos, N.I. Galanis, A.P. Markopoulos: Surface roughness prediction for the milling of Ti–6Al–4V ELI alloy with the use of statistical and soft computing techniques, Measurement 90 (2016) 25–35.

DOI: 10.1016/j.measurement.2016.04.039

[14] I. Maňková, M. Vrabeľ, P. Kovac: Artificial neural network application for surface roughness prediction when drilling nickel based alloy. Manufacturing Technology, Vol. 13(2) (2013) 193–199.

DOI: 10.21062/ujep/x.2013/a/1213-2489/mt/13/2/193

[15] M. Kasina, K. Vasilko, Experimental Verification of the Relation between the Surface Roughness and the Type of Used Tool Coating. Manufacturing Technology 12 (2012) 27 – 30.

DOI: 10.21062/ujep/x.2012/a/1213-2489/mt/12/1/27

[16] J. Hricova, N. Naprstkova, Surface Roughness Optimization in Milling Aluminium Alloy by Using the Taguchi´s Design of Experiment. Manufacturing Technology 15-4 (2015) 541-546.

DOI: 10.21062/ujep/x.2015/a/1213-2489/mt/15/4/541

[17] C. Felho: Investigation of surface roughness in machining by single and multi-point tools, Ph.D. dissertation, Otto von Guericke University, Magdeburg, (2014).

[18] J. Kundrak: Increasing the effectiveness of machining by application of composite tools in boring of cylindrical and polygon surfaces, CSc Dissertation (in Russian), Tula, (1986).

[19] C. Felho, J. Kundrak: Effect of the Changing of the Feed on Surface Topography at Face Milling, International Journal of Mechanical Engineering 1 (2016) 114–121.

[20] C. Felho, B. Karpuschewski, J. Kundrak: Surface roughness modelling in face milling, Procedia CIRP 31 (2015) 136-141.

DOI: 10.1016/j.procir.2015.03.075

[21] B. Mikó, J. Beno, I. Mankova: Experimental Verification of Cusp Heights when 3D Milling Rounded Surfaces; Acta Polytechnica Hungarica, 9-6 (2012) 101-116.

DOI: 10.12700/aph.9.6.2012.6.7