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A Performance Indicator Ontology for Predictive Maintenance in Smart Manufacturing

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/
Document Type:Article
Title:A Performance Indicator Ontology for Predictive Maintenance in Smart Manufacturing
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Pohl, MatthiasUNSPECIFIEDhttps://orcid.org/0000-0002-6241-7675UNSPECIFIED
Staegemann, DanielUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Haertel, ChristianUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Turowski, KlausUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
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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