Piston Rod Defects Identification of Quality Control in Automotive Manufacturing

Team

MA Mahrukh Aqeel AY Aysha OW Owais Ahmed Siddiqui

Automotive Manufacturing Quality Control| Piston Rods Industrial Automation Computer Vision Image Processing Defect Detection Diameter Measurement Edge Detection Pixel-Based Technique Real-Time Monitoring Streamlit Python OpenCV 13 MP Camera Performance Requirements User Interface Classification

Abstract

The project develops an automated, vision-based system to detect defects and measure the diameter of piston rods for quality control in automotive manufacturing. It replaces manual inspection to improve accuracy and efficiency. The system uses a 13 MP / 4K USB camera and optimized, anti-glare, white background LED lighting on a custom bench for image acquisition. It utilizes pixel-based image processing for defect detection and edge localization methods for precise diameter measurement. Inspection results are visualized in real-time on a Electron react dashboard. The system is built using Python and OpenCV and must process each rod within 1–2 seconds.