Symbolic AI and Digital Twin for Energy Monitoring and Operational Deviation Detection

This project is part of the AI4INO. The aim is to accelerate the digital transformation of the North-West region by creating an infrastructure equipped with high-performance computing equipment and specialized hardware and software modules for developing AI-based solutions, while facilitating effective collaboration between research organizations and SMEs through knowledge, resource, and expertise transfer.

The project is developing an integrated solution that connects industrial equipment to an energy digital twin system capable of monitoring real-time operation and energy consumption. The project uses symbolic AI and fuzzy logic to detect behavioural deviations even in the absence of large historical datasets, while also generating explainable alerts and recommendations through integration with the existing ERP maintenance module.

R&D activities

• Expanding the hardware capabilities of the smart boxes, including interfacing with electrical panels, vibration sensors, and edge AI components.
• Digitally modelling industrial equipment as energy twins, with symbolic behavioural profiles.
• Developing a symbolic AI module for the early detection of anomalies and functional degradation.
• Integrating the solution with the company’s existing ERP system for alert transmission, reporting, and correlation with scheduled maintenance.
• Validating the solution on a real production line involving multiple types of machinery.

Result A proprietary intelligent system consisting of interoperable hardware and software, capable of transforming the energy infrastructure of industrial equipment into a source of data for analysis, alerting, and operational optimisation, even in the absence of Big Data. The solution will have broad applicability for SMEs seeking to comply with new European regulations on energy efficiency and predictive maintenance.