Pohl, Matthias und Staegemann, Daniel und Haertel, Christian und Turowski, Klaus (2026) A Performance Indicator Ontology for Predictive Maintenance in Smart Manufacturing. Procedia Computer Science. Elsevier. ISSN 1877-0509. (im Druck)
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Kurzfassung
Data-driven business operations have demonstrated significant enhancements in productivity and business performance. The emergence of Industry 4.0 and IoT technologies has transformed manufacturing processes through advanced Data Analytics and Artificial Intelligence integration, generating extensive data throughout production lifecycles. The research presents an integration of manufacturing Performance Indicators into a KPI ontology structure, establishing connections to Data Analytics evaluation metrics by incorporating metric elements into Performance Indicators. The framework is demonstrated through Predictive Maintenance applications. The integration enables organizations to better align performance measurement with strategic goals while fostering a continuous improvement culture. The proposed Smart Manufacturing KPI ontology offers a structured approach for evaluating the effectiveness of Data Analytics in manufacturing environments.
| elib-URL des Eintrags: | https://elib.dlr.de/221860/ | ||||||||||||||||||||
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| Dokumentart: | Zeitschriftenbeitrag | ||||||||||||||||||||
| Titel: | A Performance Indicator Ontology for Predictive Maintenance in Smart Manufacturing | ||||||||||||||||||||
| Autoren: |
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| Datum: | 2026 | ||||||||||||||||||||
| Erschienen in: | Procedia Computer Science | ||||||||||||||||||||
| Referierte Publikation: | Ja | ||||||||||||||||||||
| Open Access: | Nein | ||||||||||||||||||||
| Gold Open Access: | Nein | ||||||||||||||||||||
| In SCOPUS: | Ja | ||||||||||||||||||||
| In ISI Web of Science: | Nein | ||||||||||||||||||||
| Verlag: | Elsevier | ||||||||||||||||||||
| ISSN: | 1877-0509 | ||||||||||||||||||||
| Status: | im Druck | ||||||||||||||||||||
| Stichwörter: | Smart Manufacturing, Ontology, Performance Indicator, Industry 4.0, Predictive Maintenance | ||||||||||||||||||||
| HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||
| HGF - Programm: | Raumfahrt | ||||||||||||||||||||
| HGF - Programmthema: | keine Zuordnung | ||||||||||||||||||||
| DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||
| DLR - Forschungsgebiet: | R - keine Zuordnung | ||||||||||||||||||||
| DLR - Teilgebiet (Projekt, Vorhaben): | R - keine Zuordnung | ||||||||||||||||||||
| Standort: | Jena | ||||||||||||||||||||
| Institute & Einrichtungen: | Institut für Datenwissenschaften > Datenmanagement und -aufbereitung | ||||||||||||||||||||
| Hinterlegt von: | Pohl, Matthias | ||||||||||||||||||||
| Hinterlegt am: | 09 Jan 2026 08:12 | ||||||||||||||||||||
| Letzte Änderung: | 12 Jan 2026 12:30 |
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