Abstract: The Manufacturing Quality Control Tracker is an advanced data-driven platform designed to enhance quality assurance in manufacturing through real-time monitoring, statistical analysis, and predictive machine learning. Built using Python, Streamlit, Plotly, and Scikit-learn, the system enables automated defect detection, process monitoring, and trend analysis while adhering to ISO 9001 standards. This paper presents the system architecture, mathematical models, experimental results, and a comparative evaluation against existing approaches. Results demonstrate significant reductions in defect rates and improvements in production efficiency.

Keywords: Manufacturing Quality Control, Defect Detection, Streamlit, Machine Learning, Statistical Process Control, Real-Time Monitoring, ISO 9001.

Downloads: | DOI: 10.17148/IJIREEICE.2026.14421