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.

引用

页数：3

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