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    • 3. 发明授权
    • Identification of outlier semiconductor devices using data-driven statistical characterization
    • 使用数据驱动统计特征识别离群半导体器件
    • US07494829B2
    • 2009-02-24
    • US11864283
    • 2007-09-28
    • Suresh SubramaniamAmit Vijay NaharThomas John AndersonKenneth Michael ButlerJohn Michael Carulli
    • Suresh SubramaniamAmit Vijay NaharThomas John AndersonKenneth Michael ButlerJohn Michael Carulli
    • G01R31/26G06F17/18
    • G01R31/2894
    • Systems and methods for identification of outlier semiconductor devices using data-driven statistical characterization are described herein. At least some preferred embodiments include a method that includes identifying a plurality of sample semiconductor chips that fail a production test as a result of subjecting the plurality of sample semiconductor chips to a stress inducing process, identifying at least one correlation between variations in a first sample parameter and variations in a second sample parameter (the sample parameters associated with the plurality of sample semiconductor chips) identifying as a statistical outlier chip any of a plurality of production semiconductor chips that pass the production test and that further do not conform to a parameter constraint generated based upon the at least one correlation identified and upon data associated with at least some of the plurality of production semiconductor chips, and segregating the statistical outlier chip from the plurality of production semiconductor chip.
    • 本文描述了使用数据驱动的统计表征来识别离群半导体器件的系统和方法。 至少一些优选实施例包括一种方法,其包括:通过对所述多个样品半导体芯片进行应力诱导过程,识别出第一样品中的变化之间的至少一个相关性,从而识别不能进行生产测试的多个样品半导体芯片 第二样本参数(与多个样本半导体芯片相关联的样本参数)的参数和变化,其识别通过生产测试的多个生产半导体芯片中的任一个的统计离群芯片,并且进一步不符合参数约束 基于所识别的所述至少一个相关性和与所述多个生产半导体芯片中的至少一些生成半导体芯片相关联的数据生成,并且将所述统计离群值芯片与所述多个生产半导体芯片分离。
    • 4. 发明申请
    • Identification of Outlier Semiconductor Devices Using Data-Driven Statistical Characterization
    • 使用数据驱动统计表征识别离子半导体器件
    • US20080262793A1
    • 2008-10-23
    • US11864283
    • 2007-09-28
    • Suresh SUBRAMANIAMAmit Vijay NAHARThomas John ANDERSONKenneth Michael BUTLERJohn Michael CARULLI
    • Suresh SUBRAMANIAMAmit Vijay NAHARThomas John ANDERSONKenneth Michael BUTLERJohn Michael CARULLI
    • G06F17/18
    • G01R31/2894
    • Systems and methods for identification of outlier semiconductor devices using data-driven statistical characterization are described herein. At least some preferred embodiments include a method that includes identifying a plurality of sample semiconductor chips that fail a production test as a result of subjecting the plurality of sample semiconductor chips to a stress inducing process, identifying at least one correlation between variations in a first sample parameter and variations in a second sample parameter (the sample parameters associated with the plurality of sample semiconductor chips) identifying as a statistical outlier chip any of a plurality of production semiconductor chips that pass the production test and that further do not conform to a parameter constraint generated based upon the at least one correlation identified and upon data associated with at least some of the plurality of production semiconductor chips, and segregating the statistical outlier chip from the plurality of production semiconductor chip.
    • 本文描述了使用数据驱动的统计表征来识别离群半导体器件的系统和方法。 至少一些优选实施例包括一种方法,其包括:通过对所述多个样品半导体芯片进行应力诱导过程,识别出第一样品中的变化之间的至少一个相关性,从而识别不能进行生产测试的多个样品半导体芯片 第二样本参数(与多个样本半导体芯片相关联的样本参数)的参数和变化,其识别通过生产测试的多个生产半导体芯片中的任一个的统计离群芯片,并且进一步不符合参数约束 基于所识别的所述至少一个相关性和与所述多个生产半导体芯片中的至少一些生成半导体芯片相关联的数据生成,并且将所述统计离群值芯片与所述多个生产半导体芯片分离。
    • 7. 发明授权
    • Semiconductor outlier identification using serially-combined data transform processing methodologies
    • 使用串行组合数据变换处理方法的半导体异常值识别
    • US08126681B2
    • 2012-02-28
    • US12566387
    • 2009-09-24
    • Amit V NaharJohn M CarulliKenneth M ButlerThomas J AndersonSuresh Subramaniam
    • Amit V NaharJohn M CarulliKenneth M ButlerThomas J AndersonSuresh Subramaniam
    • G06F19/00
    • G01R31/31718
    • A method for identifying outlier semiconductor devices from a plurality of semiconductor devices includes performing at least one electrical test to obtain electrical test data including at least one test parameter, applying at least a first data transform processing methodology to the electrical test data to generate processed test data, and applying a second data transform processing methodology that is different from the first data transform processing methodology to process the processed test data. The second data transform processing methodology applies an outlier test limit to identify non-outlier devices that comprise semiconductor devices from the semiconductor devices that conform to the outlier test limit and outlier devices that do not conform to the outlier test limit. The semiconductor devices are dispositioned using the outlier identification results. At least one of the data transform processing methodologies can include statistics.
    • 一种用于从多个半导体器件识别离群半导体器件的方法包括执行至少一个电测试以获得包括至少一个测试参数的电测试数据,对电测试数据应用至少第一数据变换处理方法以产生经处理的测试 数据,以及应用与第一数据变换处理方法不同的第二数据变换处理方法来处理处理的测试数据。 第二数据变换处理方法应用异常值测试极限以识别来自符合离群值测试极限的半导体器件的半导体器件的非离子化器件以及不符合离群值测试极限的异常值器件。 使用异常值识别结果对半导体器件进行配置。 数据变换处理方法中的至少一个可以包括统计。