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    • 3. 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。
    • 6. 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。