YOLOv4-Based Semiconductor Wafer Notch Detection Using Deep Learning and Image Enhancement Algorithms

This study designs a system to precisely detect the angle of wafers on an ion implanter's electrostatic chuck (ESC). In specific ion implantation processes, ions may penetrate deeper than intended because of the channeling effect, compromising the device performance. To address this issue, the...

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Bibliographic Details
Published in:International journal of precision engineering and manufacturing 2024-09, Vol.25 (9), p.1909-1916
Main Authors: Wang, Hao, Sim, Hyo Jun, Hwang, Jong Jin, Kwak, Sung Jin, Moon, Seung Jae
Format: Article
Language:English
Subjects:
Algorithms
Deep learning
Engineering
Image degradation
Image enhancement
Image quality
Industrial and Production Engineering
Ion beams
Ion implantation
Machine learning
Materials Science
Object recognition
Performance evaluation
Short Communication
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Description
Summary:This study designs a system to precisely detect the angle of wafers on an ion implanter's electrostatic chuck (ESC). In specific ion implantation processes, ions may penetrate deeper than intended because of the channeling effect, compromising the device performance. To address this issue, the system adjusts the tilt of the ESC and the twist angles of the wafer to control the ion beam direction. Utilizing a camera-based machine learning system, the system identifies the wafer notch to ensure an accurate alignment of the ESC. However, factors such as insufficient lighting and vibrations affect notch detection, which can degrade image quality. To overcome these issues, this study explored various image-enhancement techniques and evaluated the performance of object detection algorithms on enhanced images.
ISSN:2234-7593
2005-4602
DOI:10.1007/s12541-024-01092-7