Application of anlogic infotech EG4D20 FPGA in wafer and chip defect observation

This paper explores the feasibility and challenge of applying FPGA technology, specifically Anlogic Infotech EG4D20 FPGA, in wafer and chip defect detection. A preliminary FPGA-based chip defect observation system is constructed, enabling real-time monitoring of surface features on silicon wafers. This system rapidly displays existing defects on the silicon surface, meets the real-time image acquisition requirements of chip observation systems, and exhibits high reliability. Based on this research direction, a design scheme is proposed for an FPGA chip defect detection system equipped with the Yolov5 algorithm model. This scheme provides a new research approach for chip defect detection technology and highlights the immense potential of FPGA in this field.

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Publication Details

Published
2024-08-16
DOI
https://doi.org/10.1117/12.3035739
Citations
1
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.35
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Application of anlogic infotech EG4D20 FPGA in wafer and chip defect observation

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1 citations
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article

Application of anlogic infotech EG4D20 FPGA in wafer and chip defect observation

Yunzhou Qiu, Cheng Liu, Yaqian Deng, Siyu Zheng, Gentuan Jia
article en
1 citations

Abstract

This paper explores the feasibility and challenge of applying FPGA technology, specifically Anlogic Infotech EG4D20 FPGA, in wafer and chip defect detection. A preliminary FPGA-based chip defect observation system is constructed, enabling real-time monitoring of surface features on silicon wafers. This system rapidly displays existing defects on the silicon surface, meets the real-time image acquisition requirements of chip observation systems, and exhibits high reliability. Based on this research direction, a design scheme is proposed for an FPGA chip defect detection system equipped with the Yolov5 algorithm model. This scheme provides a new research approach for chip defect detection technology and highlights the immense potential of FPGA in this field.

Shanghai University (CN), Shanghai Institute of Microsystem and Information Technology (CN)
Openalex Percentile: Top 37%
Industrial Vision Systems and Defect Detection
0.35
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