This research demonstrates a KPI ontology framework for predictive maintenance, suggesting improved alignment with strategic goals in 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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Pohl et al. (2026) studied this question.
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