Flanges Quality Inspection with Computer Vision
Blog post from Roboflow
Automating flange quality inspection involves training an RF-DETR model on a labeled dataset of flange defects and integrating it into a Roboflow Workflow, which detects and classifies defects such as cracks, scratches, dents, and pinholes. The system categorizes images as pass, review, or fail based on confidence levels, logging each result to Vision Events and generating operator recommendations through a Gemini block. The process aims to reduce manual inspections over time by feeding review cases back into training, enhancing the model's accuracy. This inspection pipeline not only identifies and visualizes defects but also provides structured reports and quick summaries, leveraging Roboflow's capabilities to streamline quality control in manufacturing environments. The adaptable Workflow can be applied to various inspection tasks by simply swapping datasets and models, while maintaining the same triage and visualization processes.
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