AI-driven VIN verification and RFID integration for error-proofing in automotive manufacturing

This paper presents an automated solution that combines deep learning-based computer vision with radio-frequency identification (RFID) technology to verify Vehicle Identification Numbers (VINs) during automotive production. The approach utilizes a YOLO-based object detection model for VIN localization and optical character recognition (OCR) for text extraction. An RFID tag linked to each component provides a reference VIN from the production system. A programmable logic controller (PLC) compares the AI-detected VIN with the RFID data in real time, halting the process if inconsistencies are detected. Otherwise, validated information is used to retrieve precise build instructions. This system enhances traceability, prevents assembly errors, and reduces rework, contributing to Industry 4.0 initiatives. Experimental validation confirmed the effectiveness of this integrated solution.