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http://dx.doi.org/10.21289/KSIC.2021.24.6.729

Automated Inspection System for Micro-pattern Defection Using Artificial Intelligence  

Lee, Kwan-Soo (Dept. of Optics and Mechatronics Engineering, College of Nano Science and Technology, Pusan National University)
Kim, Jae-U (Dept. of Optics and Mechatronics Engineering, College of Nano Science and Technology, Pusan National University)
Cho, Su-Chan (Dept. of Cogno-Mechatronics Engineering, College of Nano Science and Technology, Pusan National University)
Shin, Bo-Sung (Dept. of Optics and Mechatronics Engineering, College of Nano Science and Technology, Pusan National University)
Publication Information
Journal of the Korean Society of Industry Convergence / v.24, no.6_2, 2021 , pp. 729-735 More about this Journal
Abstract
Recently Artificial Intelligence(AI) has been developed and used in various fields. Especially AI recognition technology can perceive and distinguish images so it should plays a significant role in quality inspection process. For stability of autonomous driving technology, semiconductors inside automobiles must be protected from external electromagnetic wave(EM wave). As a shield film, a thin polymeric material with hole shaped micro-patterns created by a laser processing could be used for the protection. The shielding efficiency of the film can be increased by the hole structure with appropriate pitch and size. However, since the sensitivity of micro-machining for some parameters, the shape of every single hole can not be same, even it is possible to make defective patterns during process. And it is absolutely time consuming way to inspect all patterns by just using optical microscope. In this paper, we introduce a AI inspection system which is based on web site AI tool. And we evaluate the usefulness of AI model by calculate Area Under ROC curve(Receiver Operating Characteristics). The AI system can classify the micro-patterns into normal or abnormal ones displaying the text of the result on real-time images and save them as image files respectively. Furthermore, pressing the running button, the Hardware of robot arm with two Arduino motors move the film on the optical microscopy stage in order for raster scanning. So this AI system can inspect the entire micro-patterns of a film automatically. If our system could collect much more identified data, it is believed that this system should be a more precise and accurate process for the efficiency of the AI inspection. Also this one could be applied to image-based inspection process of other products.
Keywords
Artificial Intelligence; Quality Inspection; EM Wave; Micro-Patterns; ROC;
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