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Influence of Machining Parameters on the Surface Roughness Obtained When Milling AISI 4140 Steel

Slimane Benchiheub(1*), Mohieddine Benghersallah(2)

(1) Research Laboratory of Advanced Technologies in Mechanical Production (LRTAPM), Department of Mechanical Engineering, Badji Mokhtar University, Algeria
(2) Research Laboratory of Advanced Technologies in Mechanical Production (LRTAPM), Department of Mechanical Engineering, Badji Mokhtar University, Algeria
(*) Corresponding author


DOI: https://doi.org/10.15866/ireme.v14i7.18270

Abstract


This study aims to investigate the influence of machining parameters on the surface roughness Ra produced during the milling of AISI 4140 steel (42CD4). The material used has undergone a heat treatment of quenching and tempering at different temperatures. The tests have been conducted using the unifactorial and multifactorial method (Complete factorial design with eight combinations). The results obtained show that with the increase in the frequency of rotation N, the roughness Ra decreases and the surface roughness improves. At a N=700 rpm speed, the roughness has been recorded at a 550 °C tempering is six times and seven times  respectively, higher than the ones obtained at 300 and 200°C and that the hardness decreases with the increase in temperature T. In addition, the analysis of variance ANOVA has showed that the feed rate f is the most significant factor followed by the rotation frequency N. The correlation coefficient R2 of the roughness Ra determined by the ANOVA is very satisfactory and testifies the good adequacy of the proposed model.
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Keywords


AISI 4140; P35; ANOVA; Surface Roughness; Milling Process

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References


B. Bloul, B. Aour, A. Bourdim, & R, Harhout, Modeling the surface finish of a ground part using ANN. 1st CMEEE International Congress - Marrakech, Morocco 2015.

M. Gaceb, S. Brahmi, Study of the influence of the surface finish on the fatigue resistance of a XC48 steel. 18th French Congress of Mechanics. CFM2007 Grenoble.

J. Jang, S. Anfis, Adaptive-network-based fuzzy inference system. IEEE Transactions on Systems, Man and Cybernetics, 23(3), 665-685, 1993.
https://doi.org/10.1109/21.256541

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, Vol. 58, pp. 416-428, 2014.
https://doi.org/10.1016/j.measurement.2014.09.008

F. Khettabi, A. Lagred, & A. Bouchareb, Contribution to improving the surface quality by optimizing the cutting parameters using the response surface methodology in dry milling. Rev. Sci. Technol., Synthèse 32: 115 -123, 2016.
https://doi.org/10.12816/0027957

K. Jakupi, N. Qehaja, A. Bunjaku, M. Bruçi, & H. Osmani, Modeling of surface roughness for dry milling, process using hss cutters. International Conference on Innovative Technologies, Leiria, 10. ‐12.09, IN‐TECH 2014.
https://doi.org/10.1016/j.proeng.2015.01.351

K. Kadirgama, M.M. Noor, M. Rahman, M.R.M. Rejab, C.H.C. Haron, & K. A. Abou-El-Hossein, Surface Roughness Prediction Model of 6061-T6 Aluminium Alloy Machining Using Statistical Method, Scientific Research, Vol. 25, (2), 1450-216X, 2009.

Q. Nexhat, and al, Mathematical model determination for surface roughness during CNC end milling operation on 42CrMo4 hardened steel. International Journal of Mechanical Engineering and Technology (IJMET), Volume 9, Issue 1, January, pp. 624–632, 2018.

K. Yusufl, Y. Nukman, T. M. Yusof, S. Z. Dawal, H. Qin Yang, T. M. I. Mahlia, K. F. Tamrin, Effect of cutting parameters on the surface roughness of titanium alloys using end milling process, Scientific Research and Essays, Vol.5, (10), pp.1992-2248, 2010.

V. Sathyamoorthy, S. Deepan, S. P. Sathya Prasanth & L. Prabhu, Optimization of Machining Parameters for Surface Roughness in End Milling of Magnesium AM60 Alloy, Indian Journal of Science and Technology, Vol 10(32), /ijst/, August 2017.
https://doi.org/10.17485/ijst/2017/v10i32/104651

Ü.K. İşleyena, & M. Karamanoğlu, The Influence of Machining Parameters on Surface Roughness of MDF in Milling Operation, BioResources. 14(2), 3266-3277, 2019.

A. Zerti, M.A Yallese, I. Meddour, S. Belhadi, A. Haddad, T. Mabrouki, Modeling and multi-objective optimization for minimizing surface roughness, cutting force, and power, and maximizing productivity for tempered stainless steel AISI 420 in turning operations. Int. J. Adv. Manuf. Technol. 2019, 102, 135–157.
https://doi.org/10.1007/s00170-018-2984-8

Stipkovic Filho, M., Stipkovic, M. A., Bordinassi, É. C., Delijaicov, S., & de Almeida, S. L. R. Experimental Numerical Model of Roughness in Finishing Face Milling of AISI 4140 Hardened Steel. In Improved Performance of Materials (pp. 83-91). Springer, Cham (2018).
https://doi.org/10.1007/978-3-319-59590-0_8

T. Zhou, L. He, J. Wu, F. Du 3 & Z. Zou, Prediction of Surface Roughness of 304 Stainless Steel and Multi-Objective Optimization of Cutting Parameters Based on GA-GBRT, Appl. Sci. 2019, 9, 3684.
https://doi.org/10.3390/app9183684

S. Sakthivelu, T. Anandaraj, M. Selwin, Multiobjective Optimization of Machining Conditions on Surface Roughness and MRR during CNC End Milling of Aluminium Alloy 7075 Using Taguchi Design of Experiments, Mechanics and Mechanical Engineering ,Vol. 21, No. 1 (2017) 95–103, Lodz University of Technology.

A.Saxena, et al, Surface roughness optimization in end milling using taguchi method and anova, International journal of research in aeronautical and mechanical, Vol.5, Issue.6. June 2017.

K.M. Fedosov, Planning experiments, Ed. Soudostroegné, (Leningrad, 1978).

A. Hebbar, Statistical methods for the extreme planning of experiments. Notions and applications, University of Mostaganem, Algeria, 2003.

U. Wiklund, M. Nordin, O. Wanstrand, & M. Larsson, Evaluation of a flexible physical vapor deposited TiC-C coating system, Surface & Coatings Technology 124, pp. 154-161, 2000.
https://doi.org/10.1016/s0257-8972(99)00627-1

T.I.M. Selinder, E. Sjostrand, M. Nordin, & S. Hogmark, Performance of PVD TiN/TaN and TiN/NbN superlattice coated cemented carbide tools in stainless steel machining. Surface & Coatings Technology 133-134, 2000, pp. 240-246, 2000.
https://doi.org/10.1016/s0257-8972(00)00933-6

T. Altan, B. Lilly, & Y.C. Yen, Manufacturing of dies and molds. CIRP Annals Manufacturing Technology, 50(2), 404-422, 2001.
https://doi.org/10.1016/s0007-8506(07)62988-6


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