Cyber-Physical System-based approach for intelligent data-driven maintenance operations in the rolling area

The paper proposes the overall vision and concepts as well as an overview of the activities developed within the CyberMan4.0 project, co-funded by the European Union through the Research Fund for Coal and Steel (RFCS), which aims at developing an innovative integrated maintenance model applicable in the rolling area of steel plants. Such model supports the transition from preventive to predictive maintenance by taking into account flexibility, machine uptime, product quality and cost. The research activities include application of advanced algorithms and extended sensing equipment including one newly developed sensor and relevant connection methodologies to support the change of strategy and to provide the necessary validation. As far as sensor information processing the project includes both new algorithms development and enhancement of existing methods, in particular in the field of machine learning. Existing systems have been enriched and equipped with robust software modules that have been integrated in a smart network to enhance communication among machines and humans and support daily maintenance operations. Four relevant use industrial cases have been faced, which will be summarized in the paper.