Advancing Industry 4.0 with Real-Time Machine Vision Integration in Cyber-Physical Systems

This study introduces a machine vision system integrated into cyber-physical systems (CPS) for enhanced in-dustrial control. The system employs a specialized script for real-time image processing and edge detection, with a focus on precision and speed. Results showcase the system's rapid processing capabilities and high-accuracy feature detection, facil-itated by machine learning algorithms that enable adaptability and iterative improvement. The system distinguishes itself by not only providing rapid and accurate feature recognition but also by outputting precise coordinates, crucial for micron-level manufacturing precision. An intuitive human-machine interface ensures seamless operation within industrial workflows. This integration significantly improves automated quality control and operational efficiency, demonstrating the system's potential to advance smart manufacturing in line with Industry 4.0 standards.