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    • 8. 发明申请
    • EXPERT KNOWLEDGE METHODS AND SYSTEMS FOR DATA ANALYSIS
    • 专家知识数据分析方法与系统
    • WO2004030082A1
    • 2004-04-08
    • PCT/US2003/030391
    • 2003-09-26
    • LAM RESEARCH CORPORATIONYADAV, PuneetBAILEY, Andrew, D., III
    • YADAV, PuneetBAILEY, Andrew, D., III
    • H01L21/66
    • H01L22/20
    • A method for adjusting a data set defining a set of process runs, each process run having a set of data corresponding to a set of variables for a wafer processing operation is provided. A model derived from a data set is received (116). A new data set corresponding to one process run is received (118). The new data set is projected to the model (120). An outlier data point produced as a result of the projecting is identified (122). A variable corresponding to the one outlier data point is identified, the identified variable exhibiting a high contribution (126). A value for the variable from the new data set is identified. Whether the value for the variable is unimportant is determined (128). A normalized matrix of data is created, using random data and the variable that was determined to be unimportant from each of the new data set and the data set (132). The data set is updated with the normalized matrix of data.
    • 提供一种用于调整定义一组处理运行的数据集的方法,每个处理运行具有与用于晶片处理操作的一组变量相对应的一组数据。 接收从数据集导出的模型(116)。 接收对应于一个进程运行的新数据集(118)。 新数据集投影到模型(120)。 识别作为投影的结果产生的异常值数据点(122)。 识别对应于一个异常数据点的变量,所识别的变量表现出高贡献(126)。 识别来自新数据集的变量的值。 确定变量的值是否不重要(128)。 使用随机数据和被确定为与每个新数据集和数据集不重要的变量(132)来创建数据的归一化矩阵。 数据集用数据的归一化矩阵更新。