This project focuses on developing a machine learning-based sensor fault detection system for wafer manufacturing processes. The system utilizes data collected from various sensors during the wafer production process and applies machine learning techniques to identify faulty sensors or anomalous readings. Detecting sensor faults in real-time is crucial in wafer manufacturing to ensure product quality, reduce downtime, and improve overall process efficiency.
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