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    • 7. 发明授权
    • Method for evaluating efficacy of prevention maintenance for a tool
    • 评估工具预防维护功效的方法
    • US08195431B2
    • 2012-06-05
    • US12566974
    • 2009-09-25
    • Yi Feng LeeChun Chi ChenShih Chang KaoYun-Zong TianWei Jun Chen
    • Yi Feng LeeChun Chi ChenShih Chang KaoYun-Zong TianWei Jun Chen
    • G06F15/00G06F19/00
    • G06Q10/00
    • A method for evaluating efficacy of prevention maintenance for a tool includes the steps of: choosing a tool which has been maintained preventively and choosing a productive parameter of the tool; collecting values of the productive parameter generated from the tool during a time range for building a varying curve of the productive parameter versus time, modifying the varying curve with a moving average method; transforming the varying curve into a Cumulative Sum chart; and judging whether the values of the productive parameter generated from the tool after the prevention maintenance are more stable, compared with the values of the productive parameter generated from the tool before the prevention maintenance, according to the Cumulative Sum chart. Thereby, if the varying of the values of the productive parameter after the prevention maintenance isn't stable, then the efficacy of this prevention maintenance for the tool is judged not good.
    • 一种用于评估工具的预防维护功效的方法包括以下步骤:选择已预先维护的工具并选择工具的生产参数; 在用于构建生产参数对时间的变化曲线的时间范围内收集从工具产生的生产参数的值,以移动平均法修改变化曲线; 将变化曲线转换为累计总和图; 并且根据累计总和图来判断在防止维护之后从工具生成的生产参数的值是否比预防维护之前从工具产生的生产参数的值更稳定。 因此,如果防止维护后的生产参数的值的变化不稳定,则对该工具的该防止维护的功效被判断为不好。
    • 8. 发明授权
    • Method for planning a semiconductor manufacturing process based on users' demands using a fuzzy system and a genetic algorithm model
    • 使用模糊系统和遗传算法模型根据用户需求规划半导体制造过程的方法
    • US08170964B2
    • 2012-05-01
    • US12471711
    • 2009-05-26
    • Wei Jun ChenChun Chi ChenYun-Zong TianYi Feng LeeTsung-Wei Lin
    • Wei Jun ChenChun Chi ChenYun-Zong TianYi Feng LeeTsung-Wei Lin
    • G07B15/00
    • G06N3/126G06N7/02
    • A method for planning a semiconductor manufacturing process based on users' demands includes the steps of: establishing a genetic algorithm model and inputting data; establishing a fuzzy system and setting one output parameter representing percent difference of each cost function in neighbor generations; setting to have a modulation parameter corresponding to each input parameter for adjusting fuzzy sets of the output parameter; executing genetic algorithm actions; executing fuzzy inference actions; eliminating chromosomes that produce output parameter smaller than a defined lower limit, and the remaining chromosomes that produces the largest output parameter is defined as the optimum chromosome, wherein the genetic algorithm actions stops being executed upon the optimum chromosome; then determining whether or not a defined number of generations has been reached, if yes, executing the optimum chromosome of the last generation; if no, continuing executing the genetic algorithm actions, thereby finding the optimum semiconductor manufacturing process for users.
    • 一种基于用户需求的半导体制造过程规划方法,包括以下步骤:建立遗传算法模型并输入数据; 建立一个模糊系统,并设置一个输出参数,代表相邻代的每个成本函数的百分比差; 设置为具有对应于每个输入参数的调制参数,用于调整输出参数的模糊集合; 执行遗传算法动作; 执行模糊推理动作; 消除产生小于规定下限的输出参数的染色体,将产生最大输出参数的剩余染色体定义为最佳染色体,其中遗传算法动作停止在最佳染色体上执行; 然后确定是否已经达到定义数量的世代,如果是,则执行最后一代的最佳染色体; 如果否,继续执行遗传算法动作,从而为用户找到最佳的半导体制造过程。
    • 10. 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。