Hao Wang, Hyo Jun Sim, Jong Jin Hwang, Sung Jin Kwak, Seung Jae Moon
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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 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.
期刊介绍:
The International Journal of Precision Engineering and Manufacturing accepts original contributions on all aspects of precision engineering and manufacturing. The journal specific focus areas include, but are not limited to:
- Precision Machining Processes
- Manufacturing Systems
- Robotics and Automation
- Machine Tools
- Design and Materials
- Biomechanical Engineering
- Nano/Micro Technology
- Rapid Prototyping and Manufacturing
- Measurements and Control
Surveys and reviews will also be planned in consultation with the Editorial Board.