Networked analysis systems

A. Diebold
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引用次数: 0

Abstract

Summary form only given. In-line and off-line metrology measurement and interpretation are a critical, but time consuming part of yield learning. Yield learning occurs during pilot line development and early volume manufacture. Networking analysis systems and whole wafer analysis tools can greatly reduce the cycle time associated with metrology during yield learning. Although in-line metrology tools have whole wafer capability, other tools such as scanning electron microscopes (equipped with energy dispersive spectroscopy: SEM/EDS) for defect review are recent developments. These SEM/EDS defect review tools (DRT) have coordinate locating stages and software capable of reading wafer defect maps from optical defect detection systems. In this paper, we discuss networked analysis systems and whole wafer tools for in/off-line analysis. The issues associated with data interpretation and management become greater with each new technology generation. We also discuss new network capabilities such as presorting electrical defects into similar types before physical characterization using "model yield learning".
网络化分析系统
只提供摘要形式。在线和离线计量测量和解释是产量学习的关键,但耗时的一部分。良率学习发生在中试生产线开发和早期批量生产期间。网络化分析系统和整片分析工具可以大大缩短与良率学习相关的计量周期。虽然在线测量工具具有整个晶圆的能力,但用于缺陷检查的其他工具,如扫描电子显微镜(配备能量色散光谱:SEM/EDS)是最近的发展。这些SEM/EDS缺陷审查工具(DRT)具有坐标定位阶段和能够从光学缺陷检测系统读取晶圆缺陷图的软件。在本文中,我们讨论了网络分析系统和整个晶圆工具的在线/离线分析。随着每一代新技术的出现,与数据解释和管理相关的问题变得越来越大。我们还讨论了新的网络功能,例如在使用“模型良率学习”进行物理表征之前将电气缺陷预测为相似类型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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