Vision-Based Measurement for Quality Control Inspection Integrated Into a Die-Casting Process in Industry 4.0 Era

Abstract

High-pressure die casting (HPDC) is a widely adopted manufacturing process in the automotive industry, renowned for producing complex metal components with high precision and surface quality. However, HPDC is inherently susceptible to defects such as shrinkage, high porosity, and filling irregularities, which can compromise product integrity and escalate production costs through increased rework and material waste. Although effective, traditional Statistical Process Control (SPC) methods require significant statistical expertise and are often cost-prohibitive for smaller manufacturers, limiting their widespread adoption. This study introduces and validates a tailored Vision-Based Measurement (VBM) system designed to automate real-time quality control within HPDC processes, enabling 100% inspection coverage without human intervention. Utilizing a COGNEX IS7600M camera and advanced image processing techniques, including Hough Transform and Sobel edge detection, the VBM system accurately measures the critical dimensions of a metallic clamping fork, a key automotive component. The system is integrated into the manufacturing workflow using the RAMI 4.0 architectural model, ensuring seamless communication with existing software applications used in the production process. Experimental validation involved assessing measurement uncertainty and implementing SPC charts, demonstrating enhanced process stability and a significant reduction in Non-Pass Rates (NPR) from 147 to 63, representing an approximately 57% decrease. A Failure Mode and Effects Analysis (FMEA) highlighted substantial reductions in direct and indirect defect detection and handling costs, resulting in financial savings of R ${\$}$ 2,179.50 per batch by minimizing rework and material waste. Additionally, the VBM system reduced inspection time from several minutes per component to approximately 7.7 seconds, lowering labor costs. Financial analysis revealed considerable cost savings, underscoring the system’s economic viability. This research demonstrates that integrating a VBM system into HPDC improves measurement accuracy and process control while offering significant financial benefits, making it a robust solution for enhancing quality control in the context of Industry 4.0.