Experimental and Analytical Investigation into Cutting Forces during Turning of EN-31 Steel in Different Machining Conditions

Article Preview

Abstract:

Metal cutting is the way of processing the workpiece with tool having sharp cutting edges of different materials generating chips of different shapes and sizes. In present era of industry 4.0, metal machining should not be unrated during processing of hard grades metals and superalloys where large amount of cutting forces are generated. Also, the measurement of cutting forces provides the basic of economical machining and hence accurate evaluation in experimental and analytical manner has great importance. The traditional models of metal cutting have disagreement with experimental results due to missing of important mechanics terms. With the development of digital technology, the errors in calculation of cutting force have also been shortened due to consideration of terms absent in conventional models. In present investigation, the cutting forces have been evaluated experimentally using dynamometer and analytically with Astakhov’s methodology during turning of EN-31 steel. The results revealed that 12.9% observations have deviation more than 20%, whereas 16.67 % has zero deviation. Further, the feed rate has more influence on cutting forces as compared to speed and nose radius. In addition, the minimum quantity lubrication (MQL) of vegetable oil has lowered the cutting forces appreciably compared to dry machining.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

42-61

Citation:

Online since:

October 2022

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2022 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Viktor, P. Asthakov. (2005),On the inadequacy of the single-shear plane model of chip formation,, International Journal of Mechanical Sciences, Vol. 7 (2005), p.1649–1672.

DOI: 10.1016/j.ijmecsci.2005.07.002

Google Scholar

[2] Viktor, P Astakhov and Xinran, Xiao. (2008), Methodology for practical cutting force evaluation based on the energy spent in the cutting system,, Machining Science and Technology, Vol. 12, p.325–347.

DOI: 10.1080/10910340802306017

Google Scholar

[3] G. Petropoulos, I Ntziantzias and C. Anghel, A Predictive Model of Cutting Force In Turning Using Taguchi And Response Surface Techniques, 1st International Conference on Experiments/Process/System Modelling/Simulation/Optimization 1st IC-EpsMsO Athens, 6-9 July, (2005).

Google Scholar

[4] Fnides, B., Yallese, M A., MabroukI, T and Rigal, J.F. (2011), Application of response surface methodology for determining cutting force model in turning hardened AISI H11 hot work tool steel,, Indian Academy of Sciences, Sadhana Vol. 36, Part 1, February 2011, p.109–123.

DOI: 10.1007/s12046-011-0007-7

Google Scholar

[5] Abhang, L.B and Hameedullah, M. (2011), Modeling and Analysis for Surface roughness in Machining EN-31 Steel using Response Surface Methodology,, International Journal of Applied Research in Mechanical Engineering, Volume-1, Issue-1, 2011, pp.33-38.

DOI: 10.47893/ijarme.2011.1007

Google Scholar

[6] C. Nath, T. Kurfess, Obstruction-type Chip Breakers for Controllable Chips and Improved Cooling/Lubrication During Drilling – A Feasibility Study, Procedia Manuf. 5 (2016) 375–385, https://doi.org/10.1016/j.promfg.2016.08.032.

DOI: 10.1016/j.promfg.2016.08.032

Google Scholar

[7] S. Li, K. Zhu, In-situ tool wear area evaluation in micro milling with considering the influence of cutting force, Mech. Syst. Signal Process. 161 (2021), 107971, https://doi.org/10.1016/j.ymssp.2021.107971.

DOI: 10.1016/j.ymssp.2021.107971

Google Scholar

[8] X. Wu, J. Li, Y. Jin, S. Zheng, Temperature calculation of the tool and chip in slicing process with equal-rake angle arc-tooth slice tool, Mech. Syst. Signal Process. 143 (2020), 106793, https://doi.org/10.1016/j.ymssp.2020.106793.

DOI: 10.1016/j.ymssp.2020.106793

Google Scholar

[9] T. Zhou, L. He, Z. Zou, F. Du, J. Wu, P. Tian, Three-dimensional turning force prediction based on hybrid finite element and predictive machining theory considering edge radius and nose radius, J. Manuf. Process. 58 (2020) 1304–1317, https://doi.org/10.1016/j.jmapro.2020.09.034.

DOI: 10.1016/j.jmapro.2020.09.034

Google Scholar

[10] C.S. Kumar, P. Zeman, T. Polcar, A 2D finite element approach for predicting the machining performance of nanolayered TiAlCrN coating on WC-Co cutting tool during dry turning of AISI 1045 steel, Ceram. Int. 46 (2020) 25073–25088, https://doi.org/10.1016/j.ceramint. 2020.06.294.

DOI: 10.1016/j.ceramint.2020.06.294

Google Scholar

[11] A.K. Parida, K. Maity, Effect of nose radius on forces, and process parameters in hot machining of Inconel 718 using finite element analysis, Eng. Sci. Technol. an Int. J. 20 (2) (2017) 687–693, https://doi.org/10.1016/j.jestch.2016.10.006.

DOI: 10.1016/j.jestch.2016.10.006

Google Scholar

[12] S. Schindler, M. Zimmermann, J.C. Aurich, P. Steinmann, Thermo-elastic deformations of the workpiece when dry turning aluminum alloys - A finite element model to predict thermal effects in the workpiece, CIRP J. Manuf. Sci. Technol. 7 (2014) 233–245, https://doi.org/10.1016/j.cirpj.2014.04.006.

DOI: 10.1016/j.cirpj.2014.04.006

Google Scholar

[13] M. Sadeghifar, M. Javidikia, V. Songmene, M. Jahazi, Finite element simulation-based predictive regression modeling and optimum solution for grain size in machining of Ti6Al4V alloy: Influence of tool geometry and cutting conditions, Simul. Model. Pract. Theory. 104 (2020), 102141.

DOI: 10.1016/j.simpat.2020.102141

Google Scholar

[14] S. Razanica, A. Malakizadi, R. Larsson, S. Cedergren, B.L. Josefson, FE modeling and simulation of machining Alloy 718 based on ductile continuum damage, Int. J. Mech. Sci. 171 (2020) 105375, https://doi.org/10.1016/j.ijmecsci.2019.105375.

DOI: 10.1016/j.ijmecsci.2019.105375

Google Scholar

[15] S.K. Mishra, S. Ghosh, S. Aravindan, Performance of laser processed carbide tools for machining of Ti6Al4V alloys: A combined study on experimental and finite element analysis, Precis. Eng. 56 (2019) 370–385, https://doi.org/10.1016/j.precisioneng.2019.01.006.

DOI: 10.1016/j.precisioneng.2019.01.006

Google Scholar

[16] A.K. Parida, K. Maity, Effect of nose radius on forces, and process parameters in hot machining of Inconel 718 using finite element analysis, Eng. Sci. Technol. an Int. J. 20 (2) (2017) 687–693, https://doi.org/10.1016/j.jestch.2016.10.006.

DOI: 10.1016/j.jestch.2016.10.006

Google Scholar

[17] M. Du, Z. Cheng, S. Wang, Finite element modeling of friction at the tool-chip-workpiece interface in high speed machining of Ti6Al4V, Int. J. Mech. Sci. 163 (2019), 105100, https://doi.org/10.1016/j.ijmecsci.2019.105100.

DOI: 10.1016/j.ijmecsci.2019.105100

Google Scholar

[18] F.A.V. da Silva, J.C. Outeiro, Machining simulation of Inconel 718 using Lagrangian and Coupled Eulerian-Lagrangian approaches, Procedia CIRP. 102 (2021) 453–458, https://doi.org/10.1016/j.procir.2021.09.077.

DOI: 10.1016/j.procir.2021.09.077

Google Scholar

[19] V. Veeranaath, Experimental Investigation of Process Parameters in Orthogonal Machining of Ti6Al4V with TiC Coated PCBN Inserts – A Finite Element Analysis, Mater. Today Proc. 5 (2018) 19547–19554, https://doi.org/10.1016/j.matpr.2018.06.316.

DOI: 10.1016/j.matpr.2018.06.316

Google Scholar

[20] P. Niesłony, W. Grzesik, K. Jarosz, P. Laskowski, FEM-based optimization of machining operations of aerospace parts made of Inconel 718 superalloy, Procedia CIRP. 77 (2018) 570–573, https://doi.org/10.1016/j.procir.2018.08.220.

DOI: 10.1016/j.procir.2018.08.220

Google Scholar

[21] Korkmaz, Mehmet Erdi, Nafiz Yaşar, and Mustafa Günay. Numerical and experimental investigation of cutting forces in turning of Nimonic 80A superalloy., Engineering Science and Technology, an International Journal 23, no. 3 (2020): 664-673. https://doi.org/10.1016/j.jestch.2020.02.001.

DOI: 10.1016/j.jestch.2020.02.001

Google Scholar

[22] Gupta, Munish Kumar, Mehmet Erdi Korkmaz, Murat Sarıkaya, Grzegorz M. Krolczyk, Mustafa Günay, and Szymon Wojciechowski. Cutting forces and temperature measurements in cryogenic assisted turning of AA2024-T351 alloy: An experimentally validated simulation approach., Measurement 188 (2022): 110594.

DOI: 10.1016/j.measurement.2021.110594

Google Scholar

[23] Gupta, Munish Kumar, Mehmet Erdi Korkmaz, Murat Sarıkaya, Grzegorz M. Krolczyk, and Mustafa Günay. In-process detection of cutting forces and cutting temperature signals in cryogenic assisted turning of titanium alloys: An analytical approach and experimental study., Mechanical Systems and Signal Processing 169 (2022): 108772.

DOI: 10.1016/j.ymssp.2021.108772

Google Scholar

[24] F. Jafarian, M. Imaz Ciaran, D. Umbrello, P.J. Arrazola, L. Filice, H. Amirabadi, Finite element simulation of machining Inconel 718 alloy including microstructure changes, Int. J. Mech. Sci. 88 (2014) 110–121, https://doi.org/10.1016/j. ijmecsci.2014.08.007.

DOI: 10.1016/j.ijmecsci.2014.08.007

Google Scholar

[25] S.K. Mishra, S. Ghosh, S. Aravindan, 3D finite element investigations on textured tools with different geometrical shapes for dry machining of titanium alloys, Int. J. Mech. Sci. 141 (2018) 424–449, https://doi.org/10.1016/j.ijmecsci.2018.04.011.

DOI: 10.1016/j.ijmecsci.2018.04.011

Google Scholar

[26] M.E. Korkmaz, P. Verleysen, M. Günay, Identification of constitutive model parameters for nimonic 80A superalloy, Trans. Indian Inst. Met. 71 (12) (2018) 2945–2952, https://doi.org/10.1007/s12666-018-1394-9.

DOI: 10.1007/s12666-018-1394-9

Google Scholar

[27] M.E. Korkmaz, M. Günay, P. Verleysen, Investigation of tensile Johnson-Cook model parameters for Nimonic 80A superalloy, J. Alloys Compd. 801 (2019), 542–549, https://doi.org/10.1016/J.JALLCOM.2019.06.153.

DOI: 10.1016/j.jallcom.2019.06.153

Google Scholar

[28] A Dorogoy, D. Rittel, Determination of the johnson-cook material parameters using the SCS specimen, Exp. Mech. 49 (2009) 881–885, https://doi.org/ 10.1007/s11340-008-9201-x.

DOI: 10.1007/s11340-008-9201-x

Google Scholar

[29] Sagar, Chithajalu Kiran, Tarun Kumar, Amrita Priyadarshini, and Amit Kumar Gupta. Prediction and optimization of machining forces using oxley's predictive theory and RSM approach during machining of WHAs., Defence Technology 15, no. 6 (2019): 923-935.

DOI: 10.1016/j.dt.2019.07.004

Google Scholar

[30] Śniegulska-Grądzka, D., Nejman, M. and Jemielniak, K., 2019. Experimental verification of dependence of the cutting forces prediction accuracy on the uncut chip cross section modeling in turning. Procedia CIRP, 79, pp.51-56 https://doi.org/10.1016/j.procir.2019.02.010.

DOI: 10.1016/j.procir.2019.02.010

Google Scholar