OPTIMISATION OF PRODUCT MARKING ACCURACY THROUGH THE IMPLEMENTATION OF A QR CODE SCANNER SYSTEM BASED ON RASPBERRY PI SBC IN THE AUTOMOTIVE MANUFACTURING INDUSTRY

Abstract

In automotive manufacturing, accurate product marking is essential for traceability and safety. One interior component requires laser marking of the label "AIR BAG" and the attachment of a QR code. However, production data revealed recurring defects due to missing QR code labels or skipped marking processes, which were caused by the lack of a verification system. This study aims to design and implement an automated QR code verification system using a Raspberry Pi 4, a single-board computer (SBC) of this type. The novelty of this approach lies in its cost-effective integration of hardware and image processing software (OpenCV) to detect QR codes in real time. The system is designed to scan for a QR code before the laser marking process begins. If a QR code is detected, a signal is sent to the laser machine to proceed with marking. It ensures that each product is verified correctly and marked. The method involved prototyping, software development, hardware integration, and implementation on a real production line. Results showed a significant reduction in marking-related defects and an improvement in process reliability. This solution minimizes operator error, enhances production efficiency, and supports quality assurance. Future work will focus on integrating the system with PLC-based controls and exploring machine learning techniques to enhance detection accuracy and facilitate predictive maintenance.