Integrating MATLAB Image Processing with PLC-Based Automation Systems for Enhanced Process Control in Robotic Manufacturing Environments

In this study, we present a comprehensive framework for integrating MATLAB's image processing capabilities with Programmable Logic Controllers (PLCs) to enhance process control in robotic manufacturing systems.This integration aims to improve automation by enabling real-time defect detection, quality assurance, and adaptive control within industrial processes.We developed a simulation environment in MATLAB to model the interactions between image processing algorithms, PLCs, and robotic systems, allowing for virtual testing and validation.Key results demonstrate the effectiveness of the proposed system in optimizing automation, reducing defects, and increasing overall production efficiency.We also validate the framework through case studies in robotic assembly lines, illustrating the practical challenges and benefits of this approach.This paper concludes with a discussion on future research directions, including the potential for machine learning integration and advanced optimization techniques to further enhance the capabilities of such systems.