Modern approaches to processing technological information in industrial automation systems based on knowledge bases - Shevchenko, R.; Луцька, Н. М. (Energy and Automation, 2025)
This article is dedicated to the analysis of existing approaches and the synthesis of novel methods for processing technological information in industrial automation systems in the context of modeling digital twins of various interconnected sections and systems. The aim of the research is to analyze the challenges of knowledge base modeling and improve the efficiency of information processing by considering heterogeneous data. The study focuses on the automation systems of three sugar production sections: diffusion, defecosaturation, and evaporation. As part of the research, a general associative map was developed, enabling the structured organization of industrial automation systems, establishing relationships, and enriching data with context for further processing. A semantic knowledge base model was designed to define data influence zones and generate a data schema that accounts for data heterogeneity. The developed semantic model allows for rapid contextual and criteria-based searches, analysis of subsystem interactions, and the calculation of similarity levels in data and anomalies, which is crucial for mathematical modeling and the synthesis of multi-layered or cognitive digital twins of processes. Based on the semantic model, a production section visualization model was created, integrating technological documentation, SCADA system data, industrial data archives, external sources, and knowledge bases via the web using meta-knowledge. Using the Clojure programming language, search queries were generated to explore influence zones, context and mentions, as well as to calculate knowledge similarity. This approach enables the integration of multiple system models without significant additional costs, ultimately defining the structure of the digital twin while accounting for potential changes in knowledge systems. This ensures a systematic and efficient approach to data collection, processing, storage, and integration with other technological systems. An additional advantage is the ability to combine individual, already described digital twins into a multi-layered comprehensive model, providing a detailed representation of the technological process and enhancing decision-making efficiency.Key words: ontology, digital twin, knowledge base, data, intelligent knowledge management systems, automation