Abstract
Abstract The introduction and adoption of various semantic models for describing assets within a plant have paved the way for new opportunities. This contribution centers on the establishment and continuous maintenance of a plant asset management system based on knowledge graphs, utilizing the information contained in various semantic models. Additionally, it highlights how the graph can be leveraged in the creation and configuration of AI-based anomaly detection models, aimed at the monitoring of measurement values in a process plant. The concept paves the way for the wide deployment of AI models in monitoring applications in process industry.
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