Federated Learning for Anomaly Detection in Industrial IoT-enabled Production Environment Supported by Autonomous Guided Vehicles

Intelligent production requires maximum downtime avoidance since downtimes lead to economic loss. Thus, Industry 4.0 (today’s IoT-driven industrial revolution) is aimed at automated production with real-time decision-making and maximal uptime. To achieve this, new technologies such as Machine Learning (ML), Artificial Intelligence (AI), and Autonomous Guided Vehicles (AGVs) are integrated into production to optimize and automate many production processes. The increasing use of AGVs in production has far-reaching consequences for industrial communication systems. To make AGVs in production even more effective, we propose to use Federated Learning (FL) which provides a secure exchange of experience between intelligent manufacturing devices to improve prediction accuracy. We conducted research in which we exchanged experiences between the three virtual devices, and the results confirm the effectiveness of this approach in production environments.