No.1022E 2026Special Edition on the Technologies that Support Manufacturing and Manufacturing Equipment Development of AI Technology for Automated Visual Inspection |
| Category | TECHNICAL REPORT |
|---|---|
| Author | M. KANO M. MOREILLON Data Analytics R&D Dept., Innovation Division Y. ARAI Process innovation Engineering Dept., Production Engineering Division A. NAKASE Data Analytics R&D Dept., Innovation Division E. KONDO Y. YAMASHITA D. HIBI Process innovation Engineering Dept., Production Engineering Division |
| Abstract | Automated visual inspection requires accurate detection of tiny defects. However, deep learning-based image classification methods often struggle with low accuracy for small anomalies. To solve this problem, we propose a novel approach that integrates image partitioning with data cleansing based on defect locations. Our experimental results demonstrate that this method significantly improves classification accuracy, particularly for defects located near the center of an image. To facilitate practical deployment in manufacturing environments, we have developed an in-house, no-code platform for building and utilizing AI models. This report presents the key features of our platform and discusses its potential for widespread adoption in real production settings. |
| Keyword | visual inspection, image classification, image partitioning, software KARAKURI |
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