Keywords
friction
sheet metal forming
steel sheet
surface roughness
How to Cite
Abstract
It is challenging to model the coefficient of friction, surface roughness, and related tribological processes during metal contact because of flattening, ploughing, and adhesion. It is important to choose the appropriate process parameters carefully when creating analytical models to overcome the challenges posed by complexity. This will ensure the production of sheet metal formed components that meets the required quality standards and is free from faults. This research analyses the impacts of nominal pressure, kinematic viscosity of lubricant, and lubricant pressure on the coefficient of friction and average roughness of DC05 deep-drawing steel sheets. The strip drawing test was used to determine the coefficient of friction. This work utilises the Categoric Boosting (CatBoost) machine learning algorithm created by Yandex to estimate the COF and surface roughness, intending to conduct a comprehensive investigation of process parameters. A Shapley decision plot exhibits the coefficient of friction prediction models via cumulative SHapley Additive exPlanations (SHAP) data. CatBoost has outstanding prediction accuracy, as seen by R2 values ranging from 0.955 to 0.894 for both the training and testing datasets for the COF, as well as 0.992 to 0.885 for surface roughness.
References
Bang, J., Park, N., Song, J., Kim, H. G., Bae, G., & Lee, M. G. (2021). Tool wear prediction in the forming of automotive DP980 steel sheet using statistical sensitivity analysis and accelerated U-bending based wear test. Metals, 11, 306. https://doi.org/10.3390/met11020306
Bay, N., Olsson, D. D., & Andreasen, J. L. (2008). Lubricant test methods for sheet metal forming. Tribology International, 41, 844–853. https://doi.org/10.1016/j.triboint.2007.11.017
Carcel, A. C., Palomares, D., Rodilla, E., & Pérez Puig, M. A. (2005). Evaluation of vegetable oils as pre-lube oils for stamping. Materials and Design, 26, 587–593. https://doi.org/10.1016/j.matdes.2004.08.010
Çavuşoğlu, O., Gürün, H. (2017). Statistical evaluation of the influence of temperature and surface roughness on aluminium sheet metal forming. Transactions Famena, 41, 57–64. https://doi.org/10.21278/TOF.41305
Daniel, D., Guiglionda, G., Litalien, P., & Shahani R. (2006). Overview of forming and formability issues for high volume aluminium car body panels. Materials Science Forum, 519-521, 795-802. https://doi.org/10.4028/www.scientific.net/MSF.519-521.795
Domitner, J., Silvayeh, Z., Shafiee Sabet, A., Öksüz, K. I., Pelcastre, L., & Hardell, J. (2021). Characterization of wear and friction between tool steel and aluminum alloys in sheet forming at room temperature. Journal of Manufacturing Processes, 64, 774-784. https://doi.org/10.1016/j.jmapro.2021.02.007
Dorogush, A. V., Ershov, V., & Gulin, A. (2018). CatBoost: gradient boosting with categorical features support. http://arxiv.org/abs/1810.11363
Gali, O. A., Riahi, A. R., & Alpas, A. T. (2013). The tribological behaviour of AA5083 alloy plastically deformed at warm forming temperatures. Wear, 302, 1257-1267. https://doi.org/10.1016/j.wear.2012.12.048
Groche, P., & Christiany, M., & Wu, Y. (2019). Load-dependent wear in sheet metal forming. Wear, 422-423, 252-260. https://doi.org/10.1016/j.wear.2019.01.071
Guillon, O., Roizard, X., & Belliard, P. (2001). Experimental methodology to study tribological aspects of deep drawing Application to aluminium alloy sheets and tool coatings. Tribology International, 34, 757–766. https://doi.org/10.1016/S0301-679X(01)00069-X
Ibragimov, B., & Gusev, G. (2019, December 8-14). Minimal variance sampling in stochastic gradient boosting. Proceedings of the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, pp. 1-11.
Kim, H., Han, S., Yan, Q., & Altan, T. (2008). Evaluation of tool materials, coatings and lubricants in forming galvanized advanced high strength steels (AHSS). CIRP Annals, 57, 299–304. https://doi.org/10.1016/j.cirp.2008.03.029
Le, H. R., & Sutcliffe, M. P. F. (2002). Measurements of friction in strip drawing under thin film lubrication. Tribology International, 35, 123-128. https://doi.org/10.1016/S0301-679X(01)00104-9
Lee, B. H., Keum, Y. T., & Wagoner, R. H. (2002). Modeling of the friction caused by lubrication and surface roughness in sheet metal forming. Journal of Materials Processing Technology, 130-131, 60-63. https://doi.org/10.1016/S0924-0136(02)00784-7
Masters L.G., Williams D. K., & Roy R. (2013). Friction behaviour in strip draw test of pre-stretched high strength automotive aluminium alloys. International Journal of Machine Tools and Manufacture, 73, 17–24, https://doi.org/10.1016/j.ijmachtools.2013.05.002
Nabipour, M., & Keshavarz, P. (2017). Modeling surface tension of pure refrigerants using feed forward backpropagation neural networks. International journal of refrigeration, 75, 217–227. https://doi.org/10.1016/j.ijrefrig.2016.12.011
Najm, S.M., & Paniti, I. (2023). Investigation and machine learning-based prediction of parametric effects of single point incremental forming on pillow effect and wall profile of AlMn1Mg1 aluminum alloy sheets. Journal of Intelligent Manufacturing, 34, 331–367. https://doi.org/10.1007/s10845-022-02026-8
Severo, V., Vilhena, L., Silva, P. N., Dias, J. P., Becker, D., Wagner, S., & Cavaleiro, A. (2009). Tribological behaviour of W–Ti–N coatings in semi-industrial strip-drawing tests. Journal of Materials Processing Technology, 209, 4662–4667. https://doi.org/10.1016/j.jmatprotec.2008.11.040
Shisode, M., Hazrati, J., Mishra, T., Rooij, M., Horn, C., Beck, J., & Boogaard, T. (2021). Modelling boundary friction of coated sheets in sheet metal forming. Tribology International, 153, 106554. https://doi.org/10.1016/j.triboint.2020.106554
Sigvant, M., Pilthammar, J., Hol, J., Wiebenga, J. H., Chezan, T., Carleer, B., & van den Boogaard, T. (2019). Fiction in sheet metal forming: influence of surface roughness and strain rate on sheet metal forming simulation results. Procedia Manufacturing, 29, 512-519. https://doi.org/10.1016/j.promfg.2019.02.169
Szewczyk, M., & Szwajka, K. (2022). Analysis of the friction mechanisms of DC04 steel sheets in the flat strip drawing test. Advances in Mechanical and Materials Engineering, 94, 51-61. https://doi.org/10.7862/rm.2022.4
Spišák, E., Majerníková, J., Duľová Spišáková, E., & Kaščák, Ľ. (2016). Analysis of plastic deformation of double reduced sheets. Acta Mechanica et Automatica, 10(4), 271-274. https://doi.org/10.1515/ama-2016-0041
Trzepieciński, T., Szewczyk, M., & Szwajka, K. (2022). The use of non-edible green oils to lubricate DC04 steel sheets in sheet metal forming process. Lubricants, 10, 210. https://doi.org/10.3390/lubricants10090210
Venema, J, Matthews, D. T. A., Hazrati, J., Wörmann, J. & Van den Boogaard, A. H. (2017). Friction and wear mechanisms during hot stamping of AlSi coated press hardening steel. Wear, 380-381, 137-145. https://doi.org/10.1016/j.wear.2017.03.014
Wang, C., Ma, R., Zhao, J., & Zhao, J. (2017). Calculation method and experimental study of coulomb friction coefficient in sheet metal forming. Journal of Manufacturing Processes, 27, 126–137. https://doi.org/10.1016/j.jmapro.2017.02.016
Żaba, K., Kuczek, Ł., Puchlerska, S., Wiewióra, M., Góral, M., & Trzepieciński, T. (2023). Analysis of tribological performance of new stamping die composite inserts using strip drawing test. Advances in Mechanical and Materials Engineering, 40, 55–62. https://doi.org/10.7862/rm.2023.7
Żaba, K., Puchlerska, S., Pieja, T., & Pyzik, J. (2020). Process design for superalloys sheet rotary forming. Materials Science Forum, 985, 91-96. https://doi.org/10.4028/www.scientific.net/MSF.985.91