Real-Time Performance Monitoring of a CNC Milling Machine using ROS 2 and AWS IoT Towards Industry 4.0

The current trend of Industry 4.0 is bringing significant changes to manufacturing processes, with the Internet of Things (IoT) and Cyber-Physical Systems (CPS) becoming essential platforms for achieving high-quality products and throughput. This paper proposes a novel system design for the digital transformation of a CNC milling machine towards Industry 4.0, using a sensor network based on Robot Operating System 2 (ROS 2) connected to the Amazon Web Services (AWS) IoT platform. The system uses two sensors, an inductive proximity sensor (KD18-3008PA) for spindle speed monitoring and an infrared thermal sensor (MLX90614-DCC) for monitoring the tool bit temperature. Data from the sensors is collected using the ESP32-WROOM, which transmits the collected data to the Raspberry Pi 4 (RPi 4) running micro-ROS agents. The RPi 4 acts as an IoT gateway, publishing data to AWS IoT core, where it is stored and visualized using Amazon QuickSight. The proposed system enables real-time monitoring of the CNC milling machine's performance, facilitating predictive maintenance and improving efficiency. The results show that the proposed system design effectively achieves digital transformation and can be scalable and flexible, making it suitable for various applications and as a foundation for further research in Industry 4.0.