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Wafer bin map inspection based on DenseNet

基于密集连接网络的晶圆图检测

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Abstract

Wafer bin map (WBM) inspection is a critical approach for evaluating the semiconductor manufacturing process. An excellent inspection algorithm can improve the production efficiency and yield. This paper proposes a WBM defect pattern inspection strategy based on the DenseNet deep learning model, the structure and training loss function are improved according to the characteristics of the WBM. In addition, a constrained mean filtering algorithm is proposed to filter the noise grains. In model prediction, an entropy-based Monte Carlo dropout algorithm is employed to quantify the uncertainty of the model decision. The experimental results show that the recognition ability of the improved DenseNet is better than that of traditional algorithms in terms of typical WBM defect patterns. Analyzing the model uncertainty can not only effectively reduce the miss or false detection rate but also help to identify new patterns.

摘要

晶圆图(WBM)检测是评估半导体生产工艺的关键手段,有效的检测方法能够提升生产效率与产 品良率。本文提出了一种基于密集连接网络的晶圆图缺陷模式检测方法,并根据晶圆图特点对模型结 构和损失函数进行了改进。此外,提出了一种受限均值滤波算法滤除噪声晶粒。在模型预测时,采用 基于熵的蒙特卡洛Dropout 算法来量化模型决策的不确定性。实验结果表明,对于典型的晶圆缺陷模 式,改进模型的识别能力优于传统算法。通过分析模型不确定性,不仅可以有效地降低漏检率和误检 率,还有助于发现新模式。

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Authors and Affiliations

  1. Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China

    Nai-gong Yu  (于乃功), Qiao Xu  (徐乔), Hong-lu Wang  (王宏陆) & Jia Lin  (林佳)

  2. Beijing Key Laboratory of Computing Intelligence and Intelligent System, Beijing, 100124, China

    Nai-gong Yu  (于乃功), Qiao Xu  (徐乔), Hong-lu Wang  (王宏陆) & Jia Lin  (林佳)

  3. Engineering Research Center of Digital Community, Ministry of Education, Beijing, 100124, China

    Nai-gong Yu  (于乃功), Qiao Xu  (徐乔), Hong-lu Wang  (王宏陆) & Jia Lin  (林佳)

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  1. Nai-gong Yu  (于乃功)
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  2. Qiao Xu  (徐乔)
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  3. Hong-lu Wang  (王宏陆)
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  4. Jia Lin  (林佳)
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Contributions

YU Nai-gong put forward the conceptualization and core methodology. XU Qiao designed the software and wrote the original draft. WANG Hong-lu conducted the investigation about the related work. LIN Jia was responsible for supervision and provided experimental resources. All authors replied to reviewers’ comments and revised the final version.

Corresponding author

Correspondence to Nai-gong Yu  (于乃功).

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Conflict of interest

YU Nai-gong, XU Qiao, WANG Hong-lu and LIN Jia declare that they have no conflict of interest.

Foundation item: Project(Z135060009002) supported by the Ministry of Industry and Information Technology of China; Project(KZ202010005004) supported by Beijing Municipal Commission of Education and Beijing Municipal Natural Science Foundation of China

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Yu, Ng., Xu, Q., Wang, Hl. et al. Wafer bin map inspection based on DenseNet. J. Cent. South Univ. 28, 2436–2450 (2021). https://doi.org/10.1007/s11771-021-4778-7

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