Development of an integrated monitoring system for real-time electrostatic discharge checking and personal protective equipment compliance.

ABSTRACT: Electrostatic Discharge (ESD) poses a significant threat to the semiconductor industry, leading to premature failures of integrated circuits (ICs) and substantial financial losses. Currently, PPE usage relies solely on manual inspections, with no verification of proper wear, and real-time ESD alerts are provided only by wearable device LED indicators. This paper presents an integrated monitoring system combining Radio Frequency Identification (RFID) to check PPE completeness, Image Processing technology to verify proper PPE wear, targeting the ESD Category 3 garmet standard, and a real-time ESD checker to monitor body voltage discharge. The system includes M5stack Basic Core, YOLOv8 algorithm, and NodeMCU ESP32. The optimal detection distance for the RFID system was 0.75 meters, achieving precision, recall, and F1 scores of 100%, 73.33%, and 85%, respectively.For the image processing system, the optmal detection distance was 2 meters, yielding 100% precision, recall, and F1 scores, with a mean Average Precision (mAP) of 98%. The ESD checker demonstrated high accuracy and reliability, with a response time of 1 to 6 seconds, an operational capacity of 15 hours and 15 minutes, and a reliability rate of 92.28%. Mean voltages detected with and without ESD PPE were 48.87 V and 69.02 V (standing), and 71.32 V and 97.96 V (walking). This system effectively detects PPE compliance and monitors personnel’s voltage levels, ensuring safety in ESD-sensitive areas.

ABSTRACT: Electrostatic Discharge (ESD) poses a significant threat to the semiconductor industry, leading to premature failures of integrated circuits (ICs) and substantial financial losses. Currently, PPE usage relies solely on manual inspections, with no verification of proper wear, and real-time ESD alerts are provided only by wearable device LED indicators. This paper presents an integrated monitoring system combining Radio Frequency Identification (RFID) to check PPE completeness, Image Processing technology to verify proper PPE wear, targeting the ESD Category 3 garmet standard, and a real-time ESD checker to monitor body voltage discharge. The system includes M5stack Basic Core, YOLOv8 algorithm, and NodeMCU ESP32. The optimal detection distance for the RFID system was 0.75 meters, achieving precision, recall, and F1 scores of 100%, 73.33%, and 85%, respectively.For the image processing system, the optmal detection distance was 2 meters, yielding 100% precision, recall, and F1 scores, with a mean Average Precision (mAP) of 98%. The ESD checker demonstrated high accuracy and reliability, with a response time of 1 to 6 seconds, an operational capacity of 15 hours and 15 minutes, and a reliability rate of 92.28%. Mean voltages detected with and without ESD PPE were 48.87 V and 69.02 V (standing), and 71.32 V and 97.96 V (walking). This system effectively detects PPE compliance and monitors personnel's voltage levels, ensuring safety in ESD-sensitive areas.

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