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A digital twin architecture for real-time supervision of an olive oil production mill
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Orientador(es)
Resumo(s)
The food processing industry is a highly complex sector that is increasingly embracing Industry 4.0 technologies, such as Cyber-Physical Systems, Artificial Intelligence, the Internet of Things, and Digital Twins (DTs), to enhance efficiency, quality, and sustainability. While DTs have demonstrated promising results in industries like dairy, beverages, and chocolate, their implementation in olive oil production remains limited. Key challenges include the need to create models adaptable to different device categories and the lack of standardized methods for capturing and transferring data between physical assets and their virtual counternarts. This work proposes a scalable architecture, based on ISO 23247, for developing DTs that support decision-making, 3D visualization, and simulation. The architecture was experimen-tally validated through a case study of an olive oil production mill where a DT was implemented. The resulting application integrated essential features such as data- and event-driven production monitoring for rapid anomaly detection, as well as digital model management to ensure the DT evolved in step with changes in the physical system's infrastructure.
Descrição
Palavras-chave
Digital Twin Monitoring Olivel Oil Mill Industrial IoT Industry 4.0
Contexto Educativo
Citação
Scheifer, Hendrick; Jorge, Luísa; Pires, Flávia; Vaz, Clara B. (2025). A digital twin architecture for real-time supervision of an olive oil production mill. In 12th International Conference on Internet of Things: Systems, Management and Security (IOTSMS). Lyon, France. ISSN 2832-3033. DOI: 10.1109/IOTSMS68530.2025.11408590
Editora
IEEE