A concept for a distributed Interchangeable knowledge base in CPPS
- As AI technology is increasingly used in production systems, different approaches have emerged from highly decentralized small-scale AI at the edge level to centralized, cloud-based services used for higher-order optimizations. Each direction has disadvantages ranging from the lack of computational power at the edge level to the reliance on stable network connections with the centralized approach. Thus, a hybrid approach with centralized and decentralized components that possess specific abilities and interact is preferred. However, the distribution of AI capabilities leads to problems in self-adapting learning systems, as knowledgebases can diverge when no central coordination is present. Edge components will specialize in distinctive patterns (overlearn), which hampers their adaptability for different cases. Therefore, this paper aims to present a concept for a distributed interchangeable knowledge base in CPPS. The approach is based on various AI components and concepts for each participating node. A service-oriented infrastructureAs AI technology is increasingly used in production systems, different approaches have emerged from highly decentralized small-scale AI at the edge level to centralized, cloud-based services used for higher-order optimizations. Each direction has disadvantages ranging from the lack of computational power at the edge level to the reliance on stable network connections with the centralized approach. Thus, a hybrid approach with centralized and decentralized components that possess specific abilities and interact is preferred. However, the distribution of AI capabilities leads to problems in self-adapting learning systems, as knowledgebases can diverge when no central coordination is present. Edge components will specialize in distinctive patterns (overlearn), which hampers their adaptability for different cases. Therefore, this paper aims to present a concept for a distributed interchangeable knowledge base in CPPS. The approach is based on various AI components and concepts for each participating node. A service-oriented infrastructure allows a decentralized, loosely coupled architecture of the CPPS. By exchanging knowledge bases between nodes, the overall system should become more adaptive, as each node can “forget” their present specialization.…
Verfasserangaben: | Christof ThimORCiDGND, Marcus GrumORCiDGND, Arnulf SchüfflerORCiDGND, Wiebke RolingORCiDGND, Annette KlugeORCiDGND, Norbert GronauORCiDGND |
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DOI: | https://doi.org/10.1007/978-3-030-90700-6_35 |
ISBN: | 978-3-030-90699-3 |
ISBN: | 978-3-030-90702-0 |
ISBN: | 978-3-030-90700-6 |
Titel des übergeordneten Werks (Englisch): | Towards sustainable customization: cridging smart products and manufacturing systems |
Verlag: | Springer |
Verlagsort: | Cham |
Herausgeber*in(nen): | Ann-Louise Andersen, Rasmus Andersen, Thomas Ditlev Brunoe, Maria Stoettrup Schioenning Larsen, Kjeld Nielsen, Alessia Napoleone, Stefan Kjeldgaard |
Publikationstyp: | Teil eines Buches (Kapitel) |
Sprache: | Englisch |
Datum der Erstveröffentlichung: | 01.11.2021 |
Erscheinungsjahr: | 2021 |
Datum der Freischaltung: | 20.09.2023 |
Freies Schlagwort / Tag: | CPPS; artificial intelligence; distributed knowledge base; learning |
Seitenanzahl: | 8 |
Erste Seite: | 314 |
Letzte Seite: | 321 |
Organisationseinheiten: | Wirtschafts- und Sozialwissenschaftliche Fakultät / Wirtschaftswissenschaften / Fachgruppe Betriebswirtschaftslehre |
DDC-Klassifikation: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
Peer Review: | Nicht ermittelbar |