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GithubDefects on aluminium sheet surfaces, if carried forward into subsequent processes, often result in significantly higher rework costs. Manual visual inspection is inconsistent and poorly suited to high-speed production lines. OpenMV embeds defect recognition capability directly at the device edge.

During the production, processing, and subsequent surface treatment of aluminium panels, surface defects such as scratches, dents, and indentations not only affect the aesthetic quality of the product but may also adversely impact subsequent assembly, structural strength, and customer acceptance. If such defects are not detected promptly during the early stages of production, they often lead to increased rework costs and, in severe cases, result in the scrapping of entire batches, causing significant losses to the enterprise.
Traditional manual visual inspection heavily relies on operators’ experience and concentration, making it prone to missed defects or inconsistent judgment criteria in prolonged, high-intensity production environments—thus failing to meet modern manufacturing’s quality requirements for stability and consistency.
Based on SingTown’s OpenMV intelligent camera, continuous and stable online visual inspection can be achieved on aluminium plate production lines. The camera is installed at critical inspection points along the production line to capture real-time images of the aluminium plate surface during high-speed movement, providing a clear and stable data foundation for defect analysis.
OpenMV runs edge-enhancement, surface texture comparison, and defect feature-matching algorithms on-device, enabling fine-grained analysis of aluminium plate surfaces. By comparing normal textures against anomalous features, the system effectively magnifies subtle defects—such as scratches, pits or indentations—that are otherwise imperceptible to the naked eye, thereby enhancing detection sensitivity and accuracy.
When OpenMV detects defect features that do not meet quality standards, it can immediately output the identification result at the edge and synchronise with sorting, rejection or alarm devices on the production line to promptly isolate defective products, enabling early-stage quality issue handling and preventing defects from proceeding to subsequent processes.
As the detection logic runs entirely on the camera’s edge device, this solution does not rely on cloud computing, effectively reducing system latency and ensuring real-time responsiveness even in high-speed production line environments. OpenMV brings industrial vision inspection capabilities to the edge device, delivering a quality control solution for manufacturers that offers low latency, high consistency and easy deployment—supporting continuous optimisation and stable operation of production processes.

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Utilise the OpenMV smart camera to identify surface defects on aluminium plates in real time
Online identification of surface defects on aluminium sheets, such as scratches and dents, to support quality control.