Digital Twin Framework for Real-Time Simulation and Monitoring of Three-Axis CNC Machines in Industry 4.0

Abstract

Digital twin technology is rapidly transforming industrial operations by enabling real-time synchronization between physical systems and their virtual counterparts. Within the framework of Industry 4.0, this integration leverages advances in AI, IoT, and simulation to enhance system monitoring, analysis, and control. This paper presents the design and implementation of a cost-effective digital twin for a three-axis CNC milling machine using open-source software and embedded hardware. The system enables real-time visualization of spindle speed, axis movement, and vibration data, offering remote access via cloud tunnels.

A 3D model created in Fusion 360 is synchronized with real-time data through a URDF-based simulation in ROS, driven by inputs from AS5600 encoders and ESP32 microcontrollers. Calibration and testing procedures validate the system’s accuracy and responsiveness under practical machining conditions. This digital twin provides a replicable, affordable framework suitable for academic, research, and small-scale industrial applications.

By integrating low-cost sensing, data acquisition, and real-time simulation, this work demonstrates a practical approach to implementing digital twins beyond large-scale industrial settings. It contributes to the broader adoption of Industry 4.0 technologies by offering a scalable and educationally relevant prototype that bridges the gap between theory and hands-on industrial practice.