-
公开(公告)号：US20210103221A1
公开(公告)日：2021-04-08
申请号：US16596732
申请日：2019-10-08
摘要： A method for process control using predictive long short term memory includes obtaining historical post-process measurements taken on prior products of the manufacturing process; obtaining historical in-process measurements taken on prior workpieces during the manufacturing process; training a neural network to predict each of the historical post-process measurements, in response to the corresponding historical in-process measurements and preceding historical post-process measurements; obtaining present in-process measurements on a present workpiece during the manufacturing process; predicting a future post-process measurement for the present workpiece, by providing the present in-process measurements and the historical post-process measurements as inputs to the neural network; and adjusting at least one controllable variable of the manufacturing process in response to the prediction of the future post-process measurement.
-
公开(公告)号：US09915942B2
公开(公告)日：2018-03-13
申请号：US14663628
申请日：2015-03-20
IPC分类号： G01R31/26 , G05B19/418
CPC分类号： G05B19/41875 , G05B2219/32187 , G05B2219/45031 , Y02P90/22
摘要： A method, a computer program product, and a computer system for identifying significant and consumable-insensitive trace features. A computer computes a residual in a first regression of one or more secondary factors on a target. The computer computes residuals in a second regression of the one or more secondary factors on each of one or more trace features in one or more trace feature sets. The computer computes, for the one or more trace feature sets, coefficients of determination in a third regression of the residuals in the second regression on the residual in the first regression. The computer ranks the one or more trace feature sets by sorting the coefficient of determination. The computer determines, based on rankings of the one or more trace feature sets, significant trace feature sets.
-
3.发明申请ENHANCING INVESTIGATION OF VARIABILITY BY INCLUSION OF SIMILAR OBJECTS WITH KNOWN DIFFERENCES TO THE ORIGINAL ONES 失效通过将具有已知差异的类似对象包含在原始主题中来增强可变性的调查公开(公告)号：US20130103178A1
公开(公告)日：2013-04-25
申请号：US13682184
申请日：2012-11-20
IPC分类号： G06F17/50
CPC分类号： G06F17/50 , G01R31/2894 , H01L22/14 , H01L22/20 , H01L2924/0002 , H01L2924/00
摘要： A system, method and/or computer program product for analyzing a functionality of at least two manufactured products obtain a first characteristic of a first manufactured product. The system acquires a second characteristic of a second manufactured product. The system identifies a common feature between the first characteristic and the second characteristic. The system identifies a distinguishable feature between the first characteristic and the second characteristic. The system determines a cause of a deviation of a functionality in the first manufactured product or the second manufactured product or both manufactured products based on the identified common feature or the identified distinguishable feature or both features.
摘要翻译： 用于分析至少两个制造产品的功能的系统，方法和/或计算机程序产品获得第一制成品的第一特征。 该系统获得第二制造产品的第二特性。 该系统识别第一特征和第二特性之间的共同特征。 该系统识别第一特征和第二特性之间的区别特征。 该系统基于所识别的共同特征或所识别的可区分特征或两个特征来确定第一制造产品或第二制造产品或两个制造产品中的功能性偏差的原因。
-
公开(公告)号：US20230281364A1
公开(公告)日：2023-09-07
申请号：US17686708
申请日：2022-03-04
IPC分类号： G06F30/27
CPC分类号： G06F30/27 , G06F2111/08
摘要： A system and method for learning a predictive function that can automatically learn different operating modes for a multi-modal system and predict the number of operating states for a multi-modal system and additionally the detailed structure for each state. Once learned, the predictive function (model) can be used to determine a mode of a new sample (an asset). Based on the determined components that maximize a log likelihood function, a mode of the new sample is detected into the model via dependency graphs. One aspect includes enforcing a lower bound for the number of sample points to form an operational mode for an asset. While a mode relates to sample points which maximizes like log-likelihood, an ability is provided to remove artifact modes due to noisy data by considering a sufficient sample data condition and maximizing log-likelihood. Domain knowledge can be incorporated into the model via dependency graphs.
-
5.发明申请SYSTEM AND METHOD FOR IDENTIFYING SIGNIFICANT AND CONSUMABLE-INSENSITIVE TRACE FEATURES 有权识别重要和消耗性追踪特征的系统和方法公开(公告)号：US20160274177A1
公开(公告)日：2016-09-22
申请号：US14663628
申请日：2015-03-20
IPC分类号： G01R31/26
CPC分类号： G05B19/41875 , G05B2219/32187 , G05B2219/45031 , Y02P90/22
摘要： A method, a computer program product, and a computer system for identifying significant and consumable-insensitive trace features. A computer computes a residual in a first regression of one or more secondary factors on a target. The computer computes residuals in a second regression of the one or more secondary factors on each of one or more trace features in one or more trace feature sets. The computer computes, for the one or more trace feature sets, coefficients of determination in a third regression of the residuals in the second regression on the residual in the first regression. The computer ranks the one or more trace feature sets by sorting the coefficient of determination. The computer determines, based on rankings of the one or more trace feature sets, significant trace feature sets.
摘要翻译： 一种方法，计算机程序产品和用于识别重要且不易消耗的痕迹特征的计算机系统。 计算机在目标上的一个或多个次要因素的第一回归中计算残差。 计算机在一个或多个跟踪特征集中的一个或多个跟踪特征的每个上的一个或多个次要因素的第二回归中计算残差。 对于一个或多个跟踪特征集，计算机计算第一回归中第二回归中残差的第三回归中的确定系数。 计算机通过对确定系数进行排序来排列一个或多个跟踪特征集。 计算机基于一个或多个跟踪特征集的排名来确定显着的跟踪特征集。
-
6.发明授权Enhancing investigation of variability by inclusion of similar objects with known differences to the original ones 失效通过将具有已知差异的相似对象与原始对象相结合，来增强对变异性的调查公开(公告)号：US08639375B2
公开(公告)日：2014-01-28
申请号：US13682184
申请日：2012-11-20
CPC分类号： G06F17/50 , G01R31/2894 , H01L22/14 , H01L22/20 , H01L2924/0002 , H01L2924/00
摘要： A system, method and/or computer program product for analyzing a functionality of at least two manufactured products obtain a first characteristic of a first manufactured product. The system acquires a second characteristic of a second manufactured product. The system identifies a common feature between the first characteristic and the second characteristic. The system identifies a distinguishable feature between the first characteristic and the second characteristic. The system determines a cause of a deviation of a functionality in the first manufactured product or the second manufactured product or both manufactured products based on the identified common feature or the identified distinguishable feature or both features.
摘要翻译： 用于分析至少两个制造产品的功能的系统，方法和/或计算机程序产品获得第一制成品的第一特征。 该系统获得第二制造产品的第二特性。 该系统识别第一特征和第二特性之间的共同特征。 该系统识别第一特征和第二特性之间的区别特征。 该系统基于所识别的共同特征或所识别的可区分特征或两个特征来确定第一制造产品或第二制造产品或两个制造产品中的功能性偏差的原因。
-
-
-
-
-
搜索结果
6 条记录 (耗时 0.015 秒)
