Computer Vision Integration for Automated Piece Positioning in an Industry 4.0 Setup

This paper presents the design and development of an alternative, cost-effective automated piece positioning system, specifically tailored for Small and Medium-sized Enterprises (SMEs), which integrates computer vision with EtherCAT-controlled servo motors. The proposed method combines a robust vision system with an AI-enhanced algorithm based on edge detection to precisely identify object contours. This enables a Programmable Logic Controller (PLC) to control the servo motor, adjusting the piece’s angle with high accuracy. Experimental results demonstrate the solution’s practical viability, achieving a minimal angular oscillation of less than 0.0012° and a promising low image processing time of approximately 20ms, showcasing its potential for enhancing manufacturing efficiency and quality in industrial applications.