Szczegóły publikacji
Opis bibliograficzny
Towards an interoperable digital shadow system for continuous steel casting using explainable AI and Kubernetes / Piotr HAJDER, Mateusz MOJŻESZKO, Filip HALLO, Lucyna HAJDER, Krzysztof REGULSKI, Krzysztof BANAŚ, Monika PERNACH, Danuta SZELIGA, Krzysztof BZOWSKI, Kazimierz MICHALIK, Adam MROZEK, Łukasz SZTANGRET, Marek WILKUS, Tomasz JAŻDŻEWSKI, Wojciech JĘDRYSIK, Rafał NADOLSKI, Andrzej OPALIŃSKI, Łukasz RAUCH // W: 2025 IEEE international conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) [Dokument elektroniczny] : 17-21 March 2025, Washington D. C., USA : proceedings / IEEE. — Wersja do Windows. — Dane tekstowe. — Piscataway, NJ : IEEE, cop. 2025. — (IEEE International Conference on Pervasive Computing and Communications Workshops ; ISSN 2836-5348). — e-ISBN: 979-8-3315-3553-7. — S. 104–109. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 109, Abstr. — Publikacja dostępna online od: 2025-06-19
Autorzy (18)
- AGHHajder Piotr
- AGHMojżeszko Mateusz
- AGHHallo Filip
- AGHHajder Lucyna
- AGHRegulski Krzysztof
- AGHBanaś Krzysztof
- AGHPernach Monika
- AGHSzeliga Danuta
- AGHBzowski Krzysztof
- AGHMichalik Kazimierz
- AGHMrozek Adam
- AGHSztangret Łukasz
- AGHWilkus Marek
- AGHJażdżewski Tomasz
- AGHJędrysik Wojciech
- AGHNadolski Rafał
- AGHOpaliński Andrzej
- AGHRauch Łukasz
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 160929 |
|---|---|
| Data dodania do BaDAP | 2025-07-09 |
| Tekst źródłowy | URL |
| DOI | 10.1109/PerComWorkshops65533.2025.00049 |
| Rok publikacji | 2025 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Institute of Electrical and Electronics Engineers (IEEE) |
| Konferencja | IEEE International Conference on Pervasive Computing and Communications 2025 |
| Czasopismo/seria | IEEE International Conference on Pervasive Computing and Communications Workshops |
Abstract
Continuous casting of steel is a complex process that requires a large amount of data, which can be difficult to interpret by humans. This paper presents a digital shadow system for continuous steel casting, which integrates advanced technologies to achieve a scalable, interpretable, and efficient solution. The system consists of applications designed to model ladle movements and predict temperature drops in liquid steel during transportation. The implementation of the system leverages a modular and scalable architecture to enable effective monitoring and validation of the continuous casting process. The digital shadow framework combines predictive modeling, explainability, and orchestration tools such as Kubernetes and Argo Workflows to ensure a high degree of automation, reducing manual intervention, and ensuring consistency and reliability in steel production. The framework provides a detailed and real-time representation of the casting process, facilitating a deeper understanding of the operational dynamics and contributing to improving the quality of the steel billets.
