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Naslov:Reduction of surface defects by optimization of casting speed using genetic programming : an industrial case study
Avtorji:ID Kovačič, Miha (Avtor)
ID Župerl, Uroš (Avtor)
ID Gusel, Leo (Avtor)
ID Brezočnik, Miran (Avtor)
Datoteke:.pdf APEM18-4_501-511.pdf (1,19 MB)
MD5: 8625823A90B4D8547F97A9EF4945E35E
 
URL https://apem-journal.org/Archives/2023/Abstract-APEM18-4_501-511.html
 
Jezik:Angleški jezik
Vrsta gradiva:Članek v reviji
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FS - Fakulteta za strojništvo
Opis:Štore Steel Ltd. produces more than 200 different types of steel with a continuous caster installed in 2016. Several defects, mostly related to thermomechanical behaviour in the mould, originate from the continuous casting process. The same casting speed of 1.6 m/min was used for all steel grades. In May 2023, a project was launched to adjust the casting speed according to the casting temperature. This adjustment included the steel grades with the highest number of surface defects and different carbon content: 16MnCrS5, C22, 30MnVS5, and 46MnVS5. For every 10 °C deviation from the prescribed casting temperature, the speed was changed by 0.02 m/min. During the 2-month period, the ratio of rolled bars with detected surface defects (inspected by an automatic control line) decreased for the mentioned steel grades. The decreases were from 11.27 % to 7.93 %, from 12.73 % to 4.11 %, from 16.28 % to 13.40 %, and from 25.52 % to 16.99 % for 16MnCrS5, C22, 30MnVS5, and 46MnVS5, respectively. Based on the collected chemical composition and casting parameters from these two months, models were obtained using linear regression and genetic programming. These models predict the ratio of rolled bars with detected surface defects and the length of detected surface defects. According to the modelling results, the ratio of rolled bars with detected surface defects and the length of detected surface defects could be minimally reduced by 14 % and 189 %, respectively, using casting speed adjustments. A similar result was achieved from July to November 2023 by adjusting the casting speed for the other 27 types of steel. The same was predicted with the already obtained models. Genetic programming outperformed linear regression.
Ključne besede:continuous casting of steel, surface defects, automatic control, machine learning, modelling, optimisation, prediction, linear regression, genetic programming
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Poslano v recenzijo:03.11.2023
Datum sprejetja članka:21.12.2023
Datum objave:28.12.2023
Založnik:Chair of Production Engineering (CPE), University of Maribor, Faculty of Mechanical Engineering
Leto izida:2023
Št. strani:str. 501-511
Številčenje:Vol. 18, no. 4
PID:20.500.12556/DKUM-87711 Novo okno
UDK:681.5:004.42
COBISS.SI-ID:182007555 Novo okno
DOI:10.14743/apem2023.4.488 Novo okno
ISSN pri članku:1854-6250
Datum objave v DKUM:25.03.2024
Število ogledov:154
Število prenosov:9
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
Področja:Ostalo
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Vaša ocena:Ocenjevanje je dovoljeno samo prijavljenim uporabnikom.
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Gradivo je del revije

Naslov:Advances in production engineering & management
Skrajšan naslov:Adv produc engineer manag
Založnik:Fakulteta za strojništvo, Inštitut za proizvodno strojništvo
ISSN:1854-6250
COBISS.SI-ID:229859072 Novo okno

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:kontinuirano litje jekla, površinske napake, avtomatska kontrola, strojno učenje, modeliranje, optimizacija, napoved, linearna regresija, genetsko programiranje


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