Pohl, Matthias and Staegemann, Daniel and Haertel, Christian and Turowski, Klaus (2026) A Performance Indicator Ontology for Predictive Maintenance in Smart Manufacturing. Procedia Computer Science. Elsevier. ISSN 1877-0509. (In Press)
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Abstract
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.
| Item URL in elib: | https://elib.dlr.de/221860/ | ||||||||||||||||||||
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| Document Type: | Article | ||||||||||||||||||||
| Title: | A Performance Indicator Ontology for Predictive Maintenance in Smart Manufacturing | ||||||||||||||||||||
| Authors: |
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| Date: | 2026 | ||||||||||||||||||||
| Journal or Publication Title: | Procedia Computer Science | ||||||||||||||||||||
| Refereed publication: | Yes | ||||||||||||||||||||
| Open Access: | No | ||||||||||||||||||||
| Gold Open Access: | No | ||||||||||||||||||||
| In SCOPUS: | Yes | ||||||||||||||||||||
| In ISI Web of Science: | No | ||||||||||||||||||||
| Publisher: | Elsevier | ||||||||||||||||||||
| ISSN: | 1877-0509 | ||||||||||||||||||||
| Status: | In Press | ||||||||||||||||||||
| Keywords: | Smart Manufacturing, Ontology, Performance Indicator, Industry 4.0, Predictive Maintenance | ||||||||||||||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||||||
| HGF - Program: | Space | ||||||||||||||||||||
| HGF - Program Themes: | other | ||||||||||||||||||||
| DLR - Research area: | Raumfahrt | ||||||||||||||||||||
| DLR - Program: | R - no assignment | ||||||||||||||||||||
| DLR - Research theme (Project): | R - no assignment | ||||||||||||||||||||
| Location: | Jena | ||||||||||||||||||||
| Institutes and Institutions: | Institute of Data Science > Data Management and Enrichment | ||||||||||||||||||||
| Deposited By: | Pohl, Matthias | ||||||||||||||||||||
| Deposited On: | 09 Jan 2026 08:12 | ||||||||||||||||||||
| Last Modified: | 12 Jan 2026 12:30 |
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