公开(公告)号：US10429320B2

公开(公告)日：2019-10-01

申请号：US14270148

申请日：2014-05-05

Applicant: KLA-Tencor Corporation

Inventor： Francis Raquel ,  Matthew Manzer ,  Christopher Lee

IPC: G01N21/95 ,  G01M99/00

Abstract: The present disclosure is directed to a method of tool matching that employs an auto-learning feedback loop to update a library of key parameters. According to the method, measurements are performed on a control wafer to collect a set of parameters associated with the process/analysis tool that is being matched. When deviated parameters correlate to a correctable tool condition (i.e. a tool matching event), the parameters are added to the library of key parameters. These key or critical parameters may be monitored on a more frequent basis to identify deviations that have a strong likelihood of matching with a correctable tool condition. The tool matching methodology advantageously allows for monitoring of an automatically updated list of key parameters instead of needing to look at the full set of parameters collected from a control wafer each time. As such, tool matching can be performed on a more frequent basis.

公开(公告)号：US20140358480A1

公开(公告)日：2014-12-04

申请号：US14270148

申请日：2014-05-05

Applicant: KLA-Tencor Corporation

Inventor： Francis Raquel ,  Matthew Manzer ,  Christopher Lee

IPC: G01M99/00 ,  G01N21/95

CPC classification number: G01N21/9501 ,  G01M99/008 ,  G01N2201/126

Abstract: The present disclosure is directed to a method of tool matching that employs an auto-learning feedback loop to update a library of key parameters. According to the method, measurements are performed on a control wafer to collect a set of parameters associated with the process/analysis tool that is being matched. When deviated parameters correlate to a correctable tool condition (i.e. a tool matching event), the parameters are added to the library of key parameters. These key or critical parameters may be monitored on a more frequent basis to identify deviations that have a strong likelihood of matching with a correctable tool condition. The tool matching methodology advantageously allows for monitoring of an automatically updated list of key parameters instead of needing to look at the full set of parameters collected from a control wafer each time. As such, tool matching can be performed on a more frequent basis.

Abstract translation: 本公开涉及一种使用自动学习反馈循环来更新关键参数库的工具匹配方法。 根据该方法，在控制晶片上进行测量以收集与正在匹配的过程/分析工具相关联的一组参数。 当偏差参数与可修正的刀具条件（即刀具匹配事件）相关时，将参数添加到关键参数库中。 可以在更频繁的基础上监视这些关键或关键参数，以识别具有与可修正工具条件匹配的强烈可能性的偏差。 工具匹配方法有利地允许监视自动更新的关键参数列表，而不是每次都需要查看从控制晶片收集的全部参数。 因此，可以更频繁地进行工具匹配。