Autor(en): | Wiedau, Michael Tolksdorf, Gregor Oeing, Jonas Kockmann, Norbert |
Titel: | Towards a systematic data harmonization to enable AI application in the process industry |
Sprache (ISO): | en |
Zusammenfassung: | Current methods of artificial intelligence may often proof ineffective in the process industry, usually because of insufficient data availability. In this contribution, we investigate how data standards can contribute to fulfill the data availability requirements of machine learning methods. We give an overview of AI use cases relevant in the process industry, name related requirements and discuss known standards in the context of implicit vs. explicit data. We conclude with a roadmap sketching how to bring the results of this contribution into practical application. |
Schlagwörter: | Artificial intelligence Data integration KEEN project Ontology Process industry |
URI: | http://hdl.handle.net/2003/40765 http://dx.doi.org/10.17877/DE290R-22622 |
Erscheinungsdatum: | 2021-11-15 |
Rechte (Link): | https://creativecommons.org/licenses/by/4.0/ |
Enthalten in den Sammlungen: | Arbeitsgruppe Apparatedesign |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
---|---|---|---|---|
Chemie Ingenieur Technik - 2021 - Wiedau - Towards a Systematic Data Harmonization to Enable AI Application in the Process.pdf | DNB | 1.72 MB | Adobe PDF | Öffnen/Anzeigen |
Diese Ressource ist urheberrechtlich geschützt. |
Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons