A Performance Indicator Ontology for Predictive Maintenance in Smart Manufacturing

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.

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Publication Details

Journal
Procedia Computer Science
Published
2026-01-01
DOI
https://doi.org/10.1016/j.procs.2026.02.416
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
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article

A Performance Indicator Ontology for Predictive Maintenance in Smart Manufacturing

Klaus Turowski, Daniel Staegemann, Christian Haertel, Matthias Pohl
Procedia Computer Science
Digital Transformation in Industry
article

A Performance Indicator Ontology for Predictive Maintenance in Smart Manufacturing

Klaus Turowski, Daniel Staegemann, Christian Haertel, Matthias Pohl
article en

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.

Procedia Computer ScienceVol. 277
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE), Otto-von-Guericke-Universität Magdeburg (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 13%
Digital Transformation in Industry
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