A pinhole is a pit, an agglomerate is a bump—in a 2D image both are just a dot. DaoAI's 3D point-cloud fusion restores the height dimension, and pits and bumps speak for themselves.
At this coating web plant, coating pinholes (local pit-like skips) and agglomerates (coating-clump bumps) are both micron-scale 3D defects that directly affect downstream barrier, insulation or appearance performance. The difficulty: in a 2D grayscale image, pits, bumps and surface stains can appear similarly light or dark, so 2D imaging struggles to distinguish defect type, let alone judge true severity.
Running at 120–400 m/min, any inspection must scan the full width without stopping the line. The prior 2D approach misjudged pinholes and agglomerates often—real defects below threshold were released as stains, while harmless stains repeatedly triggered stoppages—hurting both throughput and quality.
The DaoAI 3D Point-cloud Fusion Online Inspection Solution
DaoAI deployed 3D point-cloud fusion, reconstructing the coating surface topography under high-speed web conditions and expressing pinhole pits and agglomerate bumps directly as positive or negative deviations along the height axis. Combined with AI-AOI judgment, the system not only detects presence but distinguishes pit/bump type and quantifies depth or height, reliably catching >50μm defects at 120–400 m/min.
- 3D point cloud reconstructs coating topography; pinhole pits and agglomerate bumps separate directly by positive/negative height
- Online inspection at 120–400 m/min, with >50μm defects reliably detected
- Quantifies defect depth/height and grades by true severity, avoiding stoppages on harmless stains
- Fused with 2D data to cover both topography and appearance, reducing pit-bump-stain confusion
A pinhole is a pit, an agglomerate is a bump—restore the height dimension and defect type and severity are no longer guesswork.
After go-live, the plant achieved online type-resolved detection of pinholes and agglomerates at full 120–400 m/min production, reliably catching >50μm defects and grading them by depth/height. Stoppages from stains fell sharply, release of real 3D defects dropped markedly, coating-process anomalies could be traced quickly by defect type, and both throughput and yield rose together.
FAQ
How does DaoAI solve the detection problems of pinholes and agglomerations in the coating of coiled materials?
DaoAI uses the 3D fused point cloud solution to reconstruct the 3D morphology of the coating under high-speed coiled material online conditions. Combined with AI-AOI judgment, it can distinguish concave/convex types, quantify depth or height, reduce misjudgment, and improve production capacity and yield.
What are the advantages of DaoAI's 3D fused point cloud detection solution?
It can stably detect defects larger than 50μm at a high speed of 120-400 m/min, quantify the depth/height and classify them, avoid false shutdowns caused by harmless stains, and reduce confusion by integrating 2D information.
What results can be achieved after the implementation of the DaoAI solution?
The factory can achieve online classification detection of pinholes and agglomerations during full-speed production, reliably detect and classify defects larger than 50μm, reduce false shutdowns caused by stains and the omission rate of real defects, and quickly trace abnormalities.