Automated visual inspection in the semiconductor industry: A survey

被引:182
|
作者
Huang, Szu-Hao [1 ]
Pan, Ying-Cheng [1 ]
机构
[1] Natl Tsing Hua Univ, Dept Ind Engn & Engn Management, Hsinchu 30013, Taiwan
关键词
Automated visual inspection; Semiconductor industry; Wafer; TFT-LCD; LED; NEURAL-NETWORK APPROACH; DEFECT INSPECTION; OPTICAL INSPECTION; WAVELET; TRANSFORM; RECONSTRUCTION; PATTERNS; SYSTEM; CHIPS;
D O I
10.1016/j.compind.2014.10.006
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Automated visual inspection is an image-processing technique for quality control and production line automation. This paper reviews various optical inspection approaches in the semiconductor industry and categorize the previous literatures by the inspection algorithm and inspected products. The vision-based algorithms that had been adopted in the visual inspection systems include projection methods, filtering-based approaches, learning-based approaches, and hybrid methods. To discuss about the practical applications, the semiconductor industry covers the manufacturing and production of wafer, thin-film transistor liquid crystal displays, and light-emitting diodes. To improve the yield rate and reduce manufacturing costs, the inspection devices are widely installed in the design, layout, fabrication, assembly, and testing processes of production lines. To achieve a high robustness and computational efficiency of automated visual inspection, interdisciplinary knowledge between precision manufacturing and advanced image-processing techniques is required in the novel system design. This paper reviews multiple defect types of various inspected products which can be referenced for further implementations and improvements. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 10
页数:10
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