Comparing deterministic and statistical approaches for predicting “short can” defects in aluminium beverage can production

Comparing deterministic and statistical approaches for predicting “short can” defects in aluminium beverage can production

Wojciech Baran1, Krzysztof Regulski2, Sławomir Kąc2, Andrij Milenin2

1 CanPack S.A., Business Support Service, 32-800 Brzesko, Poland.

2 AGH University of Krakow, Faculty of Metals Engineering and Industrial Computer Science, 30-059 Krakow, Poland.



In the production of beverage cans, “short can” defects in the form of material discontinuities can occur during the deep drawing of cylindrical thin-walled aluminium products. These defects have a significant impact on production efficiency and scrap generation, and their occurrence is influenced by material and process properties. To determine the main influence of material on defect occurrence, two approaches were used: deterministic analysis of mechanical properties and microstructure, as well as statistical processing of production data using decision tree models. The latter approach was found to be more efficient, and a numerical tool was developed based on this approach to predict and reduce defect occurrence in the production process.

Cite as:

Baran, W., Regulski, K., Kąc, S., & Milenin, A. (2023). Comparing deterministic and statistical approaches for predicting “short can” defects in aluminium beverage can production. Computer Methods in Materials Science, 23(2), 29-38.

Article (PDF):


Short can, Deterministic, Analysis, Statistical methods, Predict, Defect, Reduce, Decision trees


Baran, W., Regulski, K., & Milenin, A. (2022). Influence of materials parameters of the coil sheet on the formation of defects during the manufacture of deep-drawn cups. Processes, 10(3), 578.

Chang, D.-F., & Wang, J.E. (1997). Influence of Process Parameters on the Ironing of Deep-Drawn Cups. Journal of Manufacturing Science and Engineering, 119(4B), 699–705.

Folle, L.F., Silveira Netto, S.E., & Schaeffer, L. (2008). Analysis of the manufacturing process of beverage cans using aluminum alloy. Journal of Materials Processing Technology, 205(1–3), 347–352.

Gao, E.-z., Li, H.-w., Kou, H.-ch., Chang, H., Li, J.-s., & Zhou, L. (2009). Influences of material parameters on deep drawing of thin-walled hemispheric surface part. Transactions of Nonferrous Metals Society of China, 19(2), 433–437.

Lewicki, P., & Hill, E. (2006). Statistics. Methods and Applications. StatSoft.

Milenin, A., Byrska, D.J., & Grydin, O. (2011). The multi-scale physical and numerical modeling of fracture phenomena in the MgCa0.8 alloy. Computers & Structures, 89(11–12), 1038–1049.

Rękas, A., Latos, T., Budzyn, R., Fijałkowski, M., & Brodawka, Ł. (2014a). The analysis of influence of sheet properties on the ironing process of thin-walled cylindrical shell products from aluminum alloys. Key Engineering Materials, 641, 232–245.

Rękas, A., Latos, T., Budzyn, R., Furman, A., & Siedlik, M. (2014b). The analysis of mechanical properties of 3XXX series aluminum sheets used for beverage can production. Key Engineering Materials, 641, 246–256

Rodríguez, J.J., Quintana, G., Bustillo, A., & Ciurana, J. (2016). A decision-making tool based on decision trees for roughness prediction in face milling. International Journal of Computer Integrated Manufacturing, 30(9), 943–957.

Schünemann, M., Ahmetoglu, M.A., & Altan, T. (1996). Prediction of process conditions in drawing and ironing of cans. Journal of Materials Processing Technology, 59(1–2), 1–9.

Simões, V.M., Coër, J., Laurent, H., Oliveira, M.C., Alves, J.L., Manach, P.Y., & Menezes, L.F. (2013). Sensitivity analysis of process parameters in the drawing and ironing processes. Key Engineering Materials, 554–557, 2256–2265.

Stewart, R., Niero, M., Murdock, K., & Olsen, S.I. (2018). Exploring the implementation of a circular economy strategy: the case of a closed-loop supply of aluminum beverage cans. Procedia CIRP, 69, 810–815.

Venkateswarlu, G., Davidson, M.J., & Tagore, G.R.N. (2010). Influence of process parameters on the cup drawing of aluminium 7075 sheet. International Journal of Engineering, Science and Technology, 2(11),

Wędrychowicz, P., Kustra, P., Paćko, M., & Milenin, A. (2021). A flow stress model of the AA3104-H19 alloy for the FEM simulation of the beverage can manufacturing process under large plastic deformations. Materials, 14(21), 6408,