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Integration of Hand Motion Sensor, Artificial Intelligence, and QR Code for Real-Time Monitoring of Welder’s Performance and Welding Quality: A Conceptual Framework
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Integration of Hand Motion Sensor, Artificial Intelligence, and QR Code for Real-Time Monitoring of Welder’s Performance and Welding Quality: A Conceptual Framework
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Integration of Hand Motion Sensor, Artificial Intelligence, and QR Code for Real-Time Monitoring of Welder’s Performance and Welding Quality: A Conceptual Framework
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Journal Article
Integration of Hand Motion Sensor, Artificial Intelligence, and QR Code for Real-Time Monitoring of Welder’s Performance and Welding Quality: A Conceptual Framework
2024
Overview
The welding quality, as the product of manual or semi-automatic welding process, is highly affected by the hand motion of the welders. In the shipbuilding industry, the welding inspection process is commonly performed after the welding process is finished by the welding inspectors. The research aims to develop a realtime monitoring system for welder’s performance by recording their hand motion. The hand motion sensors and QR codes are integrated through the Internet of Things (IoT) to monitor the welder’s performance and weldment quality. The realtime monitoring concept was developed by designing the monitoring concept utilising the QR code and Android mobile smartphone. The welder’s hands are equipped with the Inertial Measurement Unit (IMU) sensor to record their hand motion. The motion data are transferred directly from the IMU sensor to the smartphone storage through a Bluetooth connection. The data then are uploaded to the cloud storage through the internet connection. The stored recorded data was then analysed and compared with the qualified welders’ hand motions. After welding ends, the welder reports the visual appearance of the weldment and its location as identified by the QR code through the Android system. Finally, the functionality of the application prototype is tested, and the results show that the system can be used practically for real-time monitoring of welder performance and welding quality.
