Optical high-resolution image-based defect inspection on compound semiconductors

被引：0
|
作者：
Trautzsch, Thomas [1 ]
Mapelli, Alessandro [1 ]
Berndorfer, Timm [2 ]
Czogalla, Christian [2 ]
Pfuhl, Christoph [3 ]
机构：
[1] Confovis GmbH, Jena, Germany
[2] Semicond GmbH, United Monolith, Ulm, Germany
[3] NeuroCheck GmbH, Remseck, Germany
来源：
2023 IEEE INTERNATIONAL INTERCONNECT TECHNOLOGY CONFERENCE, IITC AND IEEE MATERIALS FOR ADVANCED METALLIZATION CONFERENCE, MAM, IITC/MAM | 2023年
关键词：
automated optical inspection; AOI; reliability; defects; compound semiconductors; gallium arsenide; GaAs; pHEMT; artificial intelligence; AI; deep learning;
D O I：
10.1109/IITC/MAM57687.2023.10154802
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
With the increase in volume and demand for smaller, faster, and more power-efficient integrated circuits, compound semiconductors have gained significant importance over silicon. In this paper, the authors intend to describe a novel implemented solution based on high-resolution images obtained with an automated optical inspection (AOI) system, combined with an artificial intelligence-based approach to identify, and classify defects for the purpose of a stable monitoring of the processing of compound semiconductors.
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页数：3
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