20.500.12556/RUL-130813 An intelligent agent-based architecture for resilient digital twins in manufacturing Digital twins (DTs) offer the potential for improved understanding of current and future manufacturing processes. This can only be achieved by DTs consistently and accurately representing the real processes. However, the robustness and resilience of the DT itself remain an issue. Accordingly, this paper offers an approach to deal with uncertainty and disruptions, as the DT detects these effectively and self-adapts as needed to maintain representativeness. The paper proposes an intelligent agent-based architecture to improve the robustness (including accuracy of representativeness) and resilience (including timely update) of the DT. The approach is demonstrated on a case of cryogenic secondary manufacturing. manufacturing systems digital twin machine learning proizvodni sistemi digitalni dvojčki strojno učenje true false false Angleški jezik Slovenski jezik Članek v reviji 2021-09-17 12:21:25 2021-09-17 12:21:28 2022-09-09 04:18:09 0000-00-00 00:00:00 2021 0 0 Str. 349-352 iss. 1 Vol. 70 2021 0000-00-00 PostprintKoncna Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 2023-06-11 658.5:004 0007-8506 10.1016/j.cirp.2021.04.049 76795907 RAZ_Vrabic_Rok_2021.pdf RAZ_Vrabic_Rok_2021.pdf 1 0D723A55DEB733DDEFAD37F34D58E676 272b825427ad10cdf43b09b7a82e4ce9e43baa8639bd8792878aae74755cad94 5c00b363-19d0-11ec-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=148163 https://www.sciencedirect.com/science/article/pii/S0007850621000731?via%3Dihub 1 c22af4e6-17a0-11ec-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=147975 Fakulteta za strojništvo 0 0 0