abstract
- Industrial Cyber-Physical Systems (ICPS) deploy a network of connected and heterogeneous systems, integrating computational and physical components, improving production and quality. However, a fault-free system is still utopian, but methodologies related to fault detection and diagnosis are still being treated in isolation or a centralized approach, overlooking the technological advances related to ICPS such as IoT, AI and edge computing. With this in mind, the present work proposes a collaborative architecture for fault detection and diagnosis, regarding the exchange of information for collaborative detection and diagnosis adopting disruptive technologies. Laboratory-scale ICPS experiments were carried out to compare the proposed approach with the approach where each component separately intends to identify and diagnose faults. The results present a faster response generating a system more flexible and robust.