Inspection during an industrial process is a important factor, as it aims to ensure efficiency and avoid waste. To achieve these objectives, process inspections are conducted
after each stage of the industrial process and also at its conclusion. This work proposes
a fast and practical system where a previously trained AI model can be saved and, from
there, inspections in an industrial process can begin. The system offers result visualization options and allows for the correction of the AI’s hits and misses, generating
metrics that enable monitoring the model’s performance. The system was developed
using the Streamlit framework, with YOLOV8 for AI training and a MySQL database for
information storage. For the development of the system, a didactic plant that simulates
an industrial piece capping process was used.
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