Wafer Plot Classification Using Neural Networks and Tensor Methods
Wafer Plot Classification Using Neural Networks and Tensor Methods
复制标题
使用神经网络和张量方法进行晶圆图分类
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
N. Sumikawa
中科院分区：
文献类型：
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作者：
A. Wahba;Chuanhe Jay Shan;Li;N. Sumikawa
本文提出了一个自动化的流程来分类的基础上获得的生产测试数据的晶圆图。晶圆图基于通过/未通过位置。分类是通过两套技术，生成对抗网络和张量分析建立的晶圆模式识别模型。主要重点是开发自动流程。实验结果的基础上，从微控制器生产线的生产测试数据将展示建议的分类流程的实用性。
This paper presents an automated flow to classify wafer plots obtained based on production test data. The wafer plots are based on pass/fail locations. The classification is achieved through wafer pattern recognition models built with two sets of techniques, Generative Adversarial Networks and Tensor analysis. The primary focus is on developing the automatic flow. Experiment results based on production test data from a microcontroller product line will be presented to demonstrate the usefulness of the proposed classification flow.