Earticle

초록

영어

In semiconductor manufacturing, the Clean and Coat (C&C) process critically influences product yield, yet its internal operation is difficult to observe directly. To address this limitation, we propose a patch-based region segmentation and recommendation framework for analyzing camera sensor images captured during C&C operations. The proposed method divides monitoring images into uniform patch regions suitable for AI-based image analysis and automatically recommends regions of interest that are most sensitive to abnormal phenomena such as wafer wobbling. A client–server monitoring system was implemented, where the frontend provides live or recorded video playback and the backend performs patch analysis using a FastAPI-based module. Experimental validation using a mock-up setup demonstrated that the system can accurately detect wafer boundaries, group surface brightness levels, and rank candidate patches in real time. The proposed framework effectively reduces operator dependence, improves consistency in region-of-interest configuration, and enhances the reliability of real-time C&C process monitoring. This study provides a foundation for integrating intelligent vision algorithms into semiconductor manufacturing environments.

목차

Abstract
1. Introduction
2. Wobbling Definition and Mock-up Setup
3. Proposed Patch Area Recommendation Algorithm
4. Experimental Implementation and Results
5. Conclusion
References

키워드

저자

• Kangsan Seo [ AI Engineer, Division of Technology, GSF Solution co. LTD ]
• Sungjin Hong [ Undergraduate Student, Dept. Artificial Intelligence Software, Cheongju University, Korea ]
• Junjun Zhang [ Associate Professor, School of Software, Henan University of Engineering, Zhengzhou, China ]
• Giseop Noh [ Assistant Professor, Dept. Software and Communications Engineering, Hongik University, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  The International Journal of Advanced Smart Convergence

• 간기

  계간

• pISSN

  2288-2847

• eISSN

  2288-2855

• 수록기간

  2012~2025

• 십진분류

  KDC 326 DDC 380