TIME WEIGHTED MOVING AVERAGE FILTER
    2.
    发明申请
    TIME WEIGHTED MOVING AVERAGE FILTER 有权
    时间称重移动平均过滤器

    公开(公告)号:US20070239285A1

    公开(公告)日:2007-10-11

    申请号:US11278840

    申请日:2006-04-06

    IPC分类号: G05B15/00

    摘要: A method for estimating a state associated with a process includes receiving a state observation associated with the process. The state observation has an associated process time. A weighting factor to discount the state observation is generated based on the process time. A state estimate is generated based on the discounted state observation. A system includes a process tool, a metrology tool, and a process controller. The process tool is operable to perform a process in accordance with an operating recipe. The metrology tool is operable to generate a state observation associated with the process. The process controller is operable to receive the state observation, the state observation having an associated process time, generate a weighting factor to discount the state observation based on the process time, generate a state estimate based on the discounted state observation, and determine at least one parameter of the operating recipe based on the state estimate.

    摘要翻译: 用于估计与过程相关联的状态的方法包括接收与该过程相关联的状态观察。 状态观察具有相关的处理时间。 基于处理时间生成打折状态观察的权重因子。 基于贴现状态观察来生成状态估计。 系统包括处理工具,计量工具和过程控制器。 处理工具可操作以根据操作配方执行处理。 计量工具可操作以产生与该过程相关联的状态观察。 过程控制器可操作以接收状态观察,具有相关联的处理时间的状态观察,基于处理时间生成加权因子以折扣状态观察,基于打折状态观察生成状态估计,并且至少确定 基于状态估计的操作配方的一个参数。

    Method and system of diagnosing a processing system using adaptive multivariate analysis
    3.
    发明申请
    Method and system of diagnosing a processing system using adaptive multivariate analysis 有权
    使用自适应多变量分析诊断处理系统的方法和系统

    公开(公告)号:US20050060103A1

    公开(公告)日:2005-03-17

    申请号:US10660697

    申请日:2003-09-12

    申请人: Kevin Chamness

    发明人: Kevin Chamness

    IPC分类号: G05B23/02 H01L21/00 G01N31/00

    CPC分类号: H01L21/67253 G05B23/024

    摘要: A method and system of monitoring a processing system and for processing a substrate during the course of semiconductor manufacturing. As such, data is acquired from the processing system for a plurality of observations, the data including a plurality of data parameters. A principal components analysis (PCA) model is constructed from the data and includes centering coefficients. Additional data is acquired from the processing system, the additional data including an additional observation of the plurality of data parameters. The centering coefficients are adjusted to produce updated adaptive centering coefficients for each of the data parameters in the PCA model. The updated adaptive centering coefficients are applied to each of the data parameters in the PCA model. At least one statistical quantity is determined from the additional data using the PCA model. A control limit is set for the statistical quantity and compared to the statistical quantity.

    摘要翻译: 一种在半导体制造过程中监视处理系统和处理衬底的方法和系统。 因此,从处理系统获取多个观察数据,数据包括多个数据参数。 从数据构建主成分分析(PCA)模型,并包括对中系数。 从处理系统获取附加数据,附加数据包括对多个数据参数的附加观察。 调整中心系数以产生PCA模型中每个数据参数的更新的自适应居中系数。 更新的自适应居中系数被应用于PCA模型中的每个数据参数。 使用PCA模型从附加数据确定至少一个统计量。 对统计量设定控制限,并与统计量进行比较。