Application of deep learning-based wafer defect detection

Hanchen Dong; Zhixuan Jiang

doi:10.1117/12.3038875

7 August 2024 Application of deep learning-based wafer defect detection

Hanchen Dong, Zhixuan Jiang

Proceedings Volume 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024); 132290W (2024) https://doi.org/10.1117/12.3038875
Event: Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 2024, Nanchang, China

Abstract

With the rapid development of the integrated circuit industry, the complexity of the internal structure of the chip is increasing, to improve the inspection efficiency of defects and analyze the types of defects, is the guidance of the production process and the test equipment of each process segment is an important guarantee to improve the output. This paper develops a defect detection device for the back channel of wafer, splices and analyzes the captured images, and compares and classifies the types and sizes of defects on the surface of existing silicon wafer samples through image analysis. Combined with deep learning technology, automatic identification and classification of surface defects is realized. The system has good real-time performance, high efficiency and strong industrial application detection ability. The technical problems of defect detection such as long time, low efficiency and strong subjectivity are optimized.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hanchen Dong and Zhixuan Jiang "Application of deep learning-based wafer defect detection", Proc. SPIE 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 132290W (7 August 2024); https://doi.org/10.1117/12.3038875

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KEYWORDS

Semiconducting wafers

Defect detection

Deep learning

Image segmentation

Image classification

Image processing

Image fusion

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