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    • 1. 发明授权
    • Method and system of compressing raw fabrication data for fault determination
    • 压缩原始制造数据进行故障确定的方法和系统
    • US08510610B2
    • 2013-08-13
    • US13240305
    • 2011-09-22
    • Yij Chieh ChuYun-Zong Tian
    • Yij Chieh ChuYun-Zong Tian
    • G06F11/00
    • G05B23/0254G06F11/0754G06F11/3013G06F11/3082
    • The instant disclosure relates to a raw data compression method for the fabrication process. The method includes the steps of: inputting into a signal converter a collection of raw data points representing operational parameter of a semiconductor equipment within a predetermined time period; obtaining an approximation of the raw data points with a Fourier series; computing the Fourier coefficients and the residuals between the raw data points and the corresponding predicted values predicted by the Fourier series; determining if the residuals exceed an error threshold; recording and storing the Fourier coefficients as the compressed data if none of the residuals exceeds the error threshold; and recording the raw data point as abnormal data point if the corresponding residual exceeds the error threshold before recording and storing the Fourier coefficients and the abnormal data point as the compressed data.
    • 本公开涉及用于制造过程的原始数据压缩方法。 该方法包括以下步骤:在预定时间段内向信号转换器输入表示半导体设备的操作参数的原始数据点的集合; 用傅里叶级数获得原始数据点的近似值; 计算傅里叶系数和原始数据点之间的残差与由傅立叶级数预测的对应预测值; 确定残差是否超过误差阈值; 如果没有残差超过误差阈值,则将傅立叶系数作为压缩数据进行记录和存储; 并且如果在记录和存储傅立叶系数和异常数据点作为压缩数据之前相应的残差超过误差阈值,则将原始数据点记录为异常数据点。
    • 2. 发明授权
    • Fault detection method of semiconductor manufacturing processes and system architecture thereof
    • 半导体制造工艺的故障检测方法及其系统架构
    • US08756028B2
    • 2014-06-17
    • US13240348
    • 2011-09-22
    • Yij Chieh ChuYun-Zong Tian
    • Yij Chieh ChuYun-Zong Tian
    • G06F19/00H01L21/66G06T7/00
    • G06F19/00G05B19/4184G06T7/001G06T2207/30148H01L22/12H01L22/14H01L22/20Y02P90/14
    • A fault detection method of semiconductor manufacturing processes is disclosed. The method includes the steps of providing a storage device, collecting a fault detection and classification(FDC) parameter by the storage device, setting up a measurement site for measuring an online measurement parameter, collecting a wafer acceptance test(WAT) in correspondence to the FDC parameter, establishing a first relationship equation between the FDC parameter and the online measurement parameter, establishing a second relationship equation of the online measurement parameter and the WAT by using the first relationship equation, establishing a third relationship equation between the FDC parameter and the WAT, establishing a waning region of the manufacturing processes by using the first, second, and third relationship equations, and determining the situation of generating wafer defects according to the warning region. The present invention discloses a system architecture for the method.
    • 公开了半导体制造工艺的故障检测方法。 该方法包括以下步骤:提供存储装置,通过存储装置收集故障检测和分类(FDC)参数,设置用于测量在线测量参数的测量位置,收集对应于该测量参数的晶片验收测试(WAT) FDC参数,建立FDC参数和在线测量参数之间的第一关系式,建立第一关系式在线测量参数和WAT的第二关系式,建立FDC参数与WAT之间的第三关系式 通过使用第一,第二和第三关系式建立制造过程的下降区域,并根据警告区域确定产生晶片缺陷的情况。 本发明公开了一种用于该方法的系统架构。
    • 4. 发明授权
    • Method for detecting variance in semiconductor processes
    • 检测半导体工艺方差的方法
    • US08649990B2
    • 2014-02-11
    • US13170229
    • 2011-06-28
    • Yij Chieh ChuChun Chi ChenYun-Zong Tian
    • Yij Chieh ChuChun Chi ChenYun-Zong Tian
    • G06F19/00
    • G05B23/0221G05B2219/37224
    • A method of detecting variance by regression model has the following steps. Step 1 is preparing the FDC data and WAT data for analysis. Step 2 is figuring out what latent variable effect of WAT data by Factor Analysis Step 3 is utilizing Principal Component Analysis to reduce the number of FDC variables to a few independent principal components. Step 4 is demonstrating how the tools and FDC data affect WAT data by Analysis of covariance model, and constructing interrelationship among FDC, WAT and tools. The interrelationship can point out which parameter effect WAT significantly. By the method, when WAT abnormal situation happened, it is easier for engineers to trace where the problem is.
    • 通过回归模型检测方差的方法具有以下步骤。 步骤1正在准备FDC数据和WAT数据进行分析。 第2步是通过因子分析步骤3来确定WAT数据的潜在变量效应是否利用主成分分析将FDC变量的数量减少到少数独立的主成分。 第4步演示了工具和FDC数据如何通过分析协方差模型影响WAT数据,并构建FDC,WAT和工具之间的相互关系。 相互关系可以显着地指出哪个参数效应WAT。 通过这种方法,当WAT异常情况发生时,工程师更容易追踪问题的位置。
    • 6. 发明申请
    • Method for assessing data worth for analyzing yield rate
    • 评估数据价值分析收益率的方法
    • US20100268501A1
    • 2010-10-21
    • US12458302
    • 2009-07-08
    • Yij Chieh ChuChun Chi ChenYun-Zong TianShih Chang KaoCheng-Hao Chen
    • Yij Chieh ChuChun Chi ChenYun-Zong TianShih Chang KaoCheng-Hao Chen
    • G06F19/00
    • G05B23/0221
    • A method for assessing data worth for analyzing yield rate includes: getting measured data with data points that corresponds to control variables of semiconductor manufacturing; transforming the data points into a distance matrix with matrix distances corresponding to differences of the data points under the control variables; expressing sample differences recorded in the distance matrix by two-dimension vectors and calculating similarity degrees of the two-dimension vectors and the distance matrix so as to take loss information as a conversion error value; calculating discriminant ability of the transformed two-dimension data and expressing the discriminant ability by an error rate of discriminant; and taking the conversion error value and the error rate of discriminant as penalty terms and calculating a quality score corresponding to the measured data. Thereby, before analyzing the yield rate of semiconductor manufacturing, analysts can determine whether data includes information affecting the yield rate based on the quality score.
    • 评估价值分析产出率的数据的方法包括:用与半导体制造控制变量对应的数据点获取测量数据; 将数据点转换成距离矩阵,矩阵距离对应于控制变量下数据点的差; 通过二维向量表示记录在距离矩阵中的样本差异,并计算二维向量和距离矩阵的相似度,以便将损失信息作为转换误差值; 计算变换后的二维数据的判别能力,并用判别式的误差率表示判别能力; 并将判别式的转换误差值和误差率作为惩罚项,并计算与测量数据相对应的质量得分。 因此,在分析半导体制造的成品率之前,分析人员可以根据质量得分确定数据是否包括影响产量率的信息。
    • 7. 发明授权
    • Method for assessing data worth for analyzing yield rate
    • 评估数据价值分析收益率的方法
    • US08265903B2
    • 2012-09-11
    • US12458302
    • 2009-07-08
    • Yij Chieh ChuChun Chi ChenYun-Zong TianShih Chang KaoCheng-Hao Chen
    • Yij Chieh ChuChun Chi ChenYun-Zong TianShih Chang KaoCheng-Hao Chen
    • G06F17/16
    • G05B23/0221
    • A method for assessing data worth for analyzing yield rate includes: getting measured data with data points that corresponds to control variables of semiconductor manufacturing; transforming the data points into a distance matrix with matrix distances corresponding to differences of the data points under the control variables; expressing sample differences recorded in the distance matrix by two-dimension vectors and calculating similarity degrees of the two-dimension vectors and the distance matrix so as to take loss information as a conversion error value; calculating discriminant ability of the transformed two-dimension data and expressing the discriminant ability by an error rate of discriminant; and taking the conversion error value and the error rate of discriminant as penalty terms and calculating a quality score corresponding to the measured data. Thereby, before analyzing the yield rate of semiconductor manufacturing, analysts can determine whether data includes information affecting the yield rate based on the quality score.
    • 评估价值分析产出率的数据的方法包括:用与半导体制造控制变量对应的数据点获取测量数据; 将数据点转换成距离矩阵,矩阵距离对应于控制变量下数据点的差; 通过二维向量表示记录在距离矩阵中的样本差异,并计算二维向量和距离矩阵的相似度,以便将损失信息作为转换误差值; 计算变换后的二维数据的判别能力,并用判别式的误差率表示判别能力; 并将判别式的转换误差值和误差率作为惩罚项,并计算与测量数据相对应的质量得分。 因此,在分析半导体制造的成品率之前,分析人员可以根据质量得分确定数据是否包括影响产量率的信息。
    • 10. 发明授权
    • Method for predicting cycle time
    • 预测周期时间的方法
    • US08090668B2
    • 2012-01-03
    • US12243301
    • 2008-10-01
    • Yi Feng LeeChun Chi ChenYun-Zong TianTsung-Wei Lin
    • Yi Feng LeeChun Chi ChenYun-Zong TianTsung-Wei Lin
    • G06F15/18G06E1/00
    • G06F17/30598G06Q10/06
    • A method for predicting cycle time comprises the steps of: collecting a plurality of known sets of data; using a clustering method to classify the known sets of data into a plurality of clusters; using a decision tree method to build a classification rule of the clusters; building a prediction model of each cluster; preparing data predicted set of data; using the classification rule to determine that to which clusters the predicted set of data belongs; and using the prediction model of the cluster to estimate the objective cycle time of the predicted set of data. Therefore, engineers can beforehand know the cycle time that one lot of wafers spend in the forward fabrication process, which helps engineers to properly arrange the following fabrication process of the lot of wafer.
    • 一种用于预测周期时间的方法包括以下步骤:收集多个已知的数据集; 使用聚类方法将已知的数据集合分类成多个聚类; 使用决策树方法构建集群的分类规则; 构建每个群集的预测模型; 准备数据预测数据集; 使用分类规则来确定预测的数据集合属于哪个集群; 并使用群集的预测模型来估计预测数据集的目标周期时间。 因此,工程师可以事先知道大量晶圆在正向制造过程中花费的周期时间,这有助于工程师正确布置晶圆批次的以下制造工艺。