20.500.12556/DKUM-97197 Optimization of the rhomboidity of continuously cast billets using linear regression and genetic programming a real industrial study During the continuous casting of steel billets, several geometrical, inner and surface defects can occur due to the thermomechanical behavior during solidification. One of them is rhombic distortion (i.e. rhomboidity), which can lead to the occurrence of off-corner cracks and twisting of cast billets during further plastic deformation (i.e. rolling). Based on data of 2088 cast batches (64 different hypoeutectoid steel grades), 109,514 billets, produced from January 2022 to September 2022 in Štore Steel Ltd. (Slovenia), chemical composition (content of C, Si, Mn, S, Cr, Mo, Ni and V), casting parameters (average casting temperature, average difference between input and output cooling water, melt level, average cooling water flow and pressure in the first and second zone of secondary cooling) the linear regression and genetic programming were used in order to predict rhomboidity of continuously cast billets. The rhomboidity, in our case defined as relative diagonal difference, was determined using in-house developed computer vision system for measuring of rhomboidity. Based on the modelling results 9 batches (419 billets) of 42CrMos4 were cast in September 2022 with a 10 % higher water pressure in the first zone of secondary cooling (from 2.41 bar to 2.67 bar). The rhomboidity of continuously cast billets improved by 18.18 % (from 1.43 % to 1.21). continuous casting of steel casting defects rhombic distortion rhomboidity machine learning modelling optimization prediction linear regression genetic programming kontinuirano litje jekla napake pri litju rombična distorzija romboidnost strojno učenje modeliranje optimizacija napoved linearna regresija genetsko programiranje true false true Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering Angleški jezik Slovenski jezik https://apem-journal.org/ Content from this work may be used under the terms of the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Članek v reviji 2026-02-23 12:49:56 2026-02-23 12:49:56 2026-02-24 03:17:38 0000-00-00 00:00:00 2022 0 0 str. 469-478 no. 4 Vol. 17 Dec. 2022 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2022-06-15 2022-12-22 2022-12-30 669.1:004.43 136297219 10.14743/apem2022.4.449 1854-6250 APEM17-4_469-478.pdf APEM17-4_469-478.pdf 1 5FD1BA565C277EF3921CCF0250F94AF6 f2d9b2de715f032053a2108bb6ea149f98fd9f2db0af23f4cfb4bafaf2b8e95d 2b29e818-10ae-11f1-95c9-00155d580e1a https://dk.um.si/Dokument.php?lang=slv&id=203672 https://apem-journal.org/Archives/2022/APEM17-4_469-478.pdf 0 3169aa91-10ae-11f1-95c9-00155d580e1a https://dk.um.si/Dokument.php?lang=slv&id=203673 Fakulteta za strojništvo Advances in production engineering & management 0 0 0