首页> 外文会议>Conference on metrology, inspection, and process control for microlithography XXIV >Use of Wafer Backside Inspection and SPR to Address Systemic Tool and Process Issues
【24h】

Use of Wafer Backside Inspection and SPR to Address Systemic Tool and Process Issues

机译:使用晶圆背面检查和SPR解决系统性工具和流程问题

获取原文
获取外文期刊封面目录资料

摘要

Defects on the backside of wafers can be either tool or process induced and can cause lithography-related issues such as focus deviation or chuck contamination. Tool induced scratches, process induced contamination, or residues on the back of wafers often have unique signatures, such as a repeatable scratch caused by wafer handling equipment or a chuck imprint on the backside of a wafer. Certain backside defect signatures such as large scratches or divots can contribute to wafer breakage or reliability issues.Spatial Pattern Recognition (SPR) is a method of comparing defect patterns at the wafer level with known defect signatures stored in a library that is created from process data. These defect signatures can represent systemic issues with process tools, handling equipment, or the process itself.This paper describes a backside inspection method for identifying wafers with both known and new spatial pattern signatures. By reporting the frequency of each signature category, process partitioning can efficiently trace the source of these problems. In addition, new defect signatures can be automatically learned and added to the library. The paper also includes examples of how this method was used to identify backside defect patterns caused by process and tool excursions in a 300mm fabricator.
机译:晶圆背面的缺陷可能是工具引起的,也可能是过程引起的,并可能引起与光刻相关的问题,例如聚焦偏差或卡盘污染。工具引起的划痕,过程引起的污染或晶片背面的残留物通常具有独特的特征,例如由晶片处理设备引起的可重复划痕或晶片背面的卡盘压痕。某些背面缺陷特征(例如大的划痕或凹痕)可能会导致晶圆破裂或可靠性问题。 空间图案识别(SPR)是一种将晶圆级缺陷图案与存储在从过程数据创建的库中的已知缺陷特征进行比较的方法。这些缺陷特征可以代表过程工具,处理设备或过程本身的系统性问题。 本文介绍了一种背面检查方法,用于识别具有已知和新的空间图案特征的晶圆。通过报告每个签名类别的频率,进程划分可以有效地跟踪这些问题的根源。此外,可以自动学习新的缺陷签名并将其添加到库中。本文还提供了一些示例,说明了如何使用这种方法来识别300mm制造商中由于工艺和工具偏移而引起的背面缺陷图案。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号