公开(公告)号：WO2018177659A1

公开(公告)日：2018-10-04

申请号：PCT/EP2018/054360

申请日：2018-02-22

Applicant: ASML NETHERLANDS B.V.

Inventor： NIJE, Jelle ,  YPMA, Alexander ,  GKOROU, Dimitra ,  TSIROGIANNIS, Georgios ,  VAN WIJK, Robert Jan ,  CHEN, Tzu-Chao ,  SPIERING, Frans, Reinier ,  ROY, Sarathi ,  GROUWSTRA, Cédric, Désiré

IPC: G06K9/62 ,  G03F7/20

Abstract: A method of optimizing an apparatus for multi-stage processing of product units such as wafers, the method comprising: (a) receiving object data (210, 230) representing one or more parameters measured (206, 208) across wafers (204, 224) and associated with different stages of processing of the wafers; (b) determining fingerprints (213, 234) of variation of the object data across the wafers, the fingerprints being associated with different respective stages of processing of the wafers. The fingerprints may be determined by decomposing (212, 232) the object data into components using principal component analysis for each different respective stage; (c) analyzing (246) commonality of the fingerprints through the different stages to produce commonality results; and (d) optimizing (250- 258) an apparatus for processing (262) product units based on the commonality results.

公开(公告)号：WO2022012873A1

公开(公告)日：2022-01-20

申请号：PCT/EP2021/066813

申请日：2021-06-21

Applicant: ASML NETHERLANDS B.V.

Inventor： GKOROU, Dimitra ,  BASTANI, Vahid ,  SAHRAEIAN, Reza ,  TABERY, Cyrus, Emil

IPC: H01L21/66 ,  G03F7/20 ,  G05B19/418 ,  G05B23/02 ,  G03F7/70491 ,  G03F7/705 ,  G05B2219/45031 ,  G05B23/024 ,  G05B23/0243 ,  H01L21/67271 ,  H01L22/12 ,  H01L22/14 ,  H01L22/20

Abstract: Methods and apparatus for classifying semiconductor wafers. The method comprises: sorting a set of semiconductor wafers, using a model, into a plurality of sub-sets based on parameter data corresponding to one or more parameters of the set of semiconductor wafers, wherein the parameter data for semiconductor wafers in a sub-set include one or more common characteristics; identifying one or more semiconductor wafers within a sub-set based on a probability of the one or more semiconductor wafers being correctly allocated to the sub-set; comparing the parameter data of the one or more identified semiconductor wafers to reference parameter data; and reconfiguring the model based on the comparison. The comparison is undertaken by a human to provide constraints for the model. The apparatus is configured to undertake the method.

公开(公告)号：WO2021213746A1

公开(公告)日：2021-10-28

申请号：PCT/EP2021/057211

申请日：2021-03-22

Applicant: ASML NETHERLANDS B.V.

Inventor： SAHRAEIAN, Reza ,  BASTANI, Vahid ,  GKOROU, Dimitra ,  DOS SANTOS GUZELLA, Thiago

IPC: G03F7/20 ,  G06N5/04

Abstract: Apparatus and methods of configuring an imputer model for imputing a second parameter. The method comprises inputting a first data set comprising values of a first parameter to the imputer model, and evaluating the imputer model to obtain a second data set comprising imputed values of the second parameter. The method further comprises obtaining a third data set comprising measured values of a third parameter, wherein the third parameter is correlated to the second parameter; obtaining a prediction model configured to infer values of the third parameter based on inputting values of the second parameter; inputting the second data set to the prediction model, and evaluating the prediction model to obtain inferred values of the third parameter; and configuring the imputer model based on a comparison of the inferred values and the measured values of the third parameter.

公开(公告)号：WO2020177973A1

公开(公告)日：2020-09-10

申请号：PCT/EP2020/052953

申请日：2020-02-06

Applicant: ASML NETHERLANDS B.V.

Inventor： LARRANAGA, Maialen ,  GKOROU, Dimitra ,  HASIBI, Faegheh ,  YPMA, Alexander

IPC: G03F7/20 ,  G06N3/04

Abstract: A method of extracting a feature from a data set includes iteratively extracting a feature (244) from a data set based on a visualization (238) of a residual pattern comprised within the data set, wherein the feature is distinct from a feature extracted in a previous iteration, and the visualization of the residual pattern uses the feature extracted in the previous iteration. Visualizing (234) the data set using the feature extracted in the previous iteration may comprise showing residual patterns of attribute data that are relevant to target data. Visualizing (234) the data set using the feature extracted in the previous iteration may involve adding cluster constraints to the data set, based on the feature extracted in the previous iteration. Additionally or alternatively, visualizing (234) the data set using the feature extracted in the previous iteration may involve defining conditional probabilities conditioned on the feature extracted in the previous iteration.

公开(公告)号：WO2023280493A1

公开(公告)日：2023-01-12

申请号：PCT/EP2022/065403

申请日：2022-06-07

Applicant: ASML NETHERLANDS B.V.

Inventor： VAN HERTUM, Pieter ,  GKOROU, Dimitra ,  VAN SCHOUBROECK, Joachim, Kinley ,  KAREVAN, Zahra ,  YPMA, Alexander

IPC: G06N5/04 ,  G06N7/00 ,  G03F7/20 ,  G05B23/02

Abstract: A computer implemented method for diagnosing a system comprising a plurality of modules. The method comprises: receiving a causal graph, the causal graph defining (i) a plurality of nodes each representing a module of the system, wherein each module is characterized by one or more signals; and (ii) edges connected between the nodes, the edges representing propagation of performance between modules; generating a reasoning tool by augmenting the causal graph with diagnostics knowledge based on historically determined relations between performance, statistical and causal characteristics of at least one module out of the plurality of modules; obtaining a health metric of the at least one module, wherein the health metric is associated with the one or more signals associated with the at least one module; and using the health metric as an input to the reasoning tool to identify a module that is the most likely cause of the behaviour.

公开(公告)号：WO2021001114A1

公开(公告)日：2021-01-07

申请号：PCT/EP2020/065619

申请日：2020-06-05

Applicant: ASML NETHERLANDS B.V.

Inventor： BASTANI, Vahid ,  SONNTAG, Dag ,  SAHRAEIAN, Reza ,  GKOROU, Dimitra

IPC: G03F7/20 ,  G05B19/418 ,  H01L21/66

Abstract: A method of determining a contribution of a process feature to the performance of a process of patterning substrates. The method may comprise obtaining a first model trained on first process data and first performance data. One or more substrates may be identified based on a quality of prediction of the first model when applied to process data associated with the one or more substrates. A second model may be trained on second process data and second performance data associated with the identified one or more substrates. The second model may be used to determine the contribution of a process feature of the second process data to the second performance data associated with the one or more substrates.

公开(公告)号：WO2021197730A1

公开(公告)日：2021-10-07

申请号：PCT/EP2021/054988

申请日：2021-03-01

Applicant: ASML NETHERLANDS B.V.

Inventor： KOULIERAKIS, Eleftherios ,  LANCIA, Carlo ,  GONZALEZ HUESCA, Juan Manuel ,  YPMA, Alexander ,  GKOROU, Dimitra ,  SAHRAEIAN, Reza

IPC: G03F7/20 ,  G03F7/705 ,  G03F7/70525

Abstract: Described is a method for determining an inspection strategy for at least one substrate, the method comprising: quantifying, using a prediction model, a compliance metric value for a compliance metric relating to a prediction of compliance with a quality requirement based on one or both of pre- processing data associated with the substrate and any available post-processing data associated with the at least one substrate; and deciding on an inspection strategy for said at least one substrate, based on the compliance metric value, an expected cost associated with the inspection strategy and at least one objective value describing an expected value of the inspection strategy in terms of at least one objective relating to the prediction model.

公开(公告)号：WO2021170325A1

公开(公告)日：2021-09-02

申请号：PCT/EP2021/051656

申请日：2021-01-26

Applicant: ASML NETHERLANDS B.V.

Inventor： LARRANAGA, Maialen ,  GKOROU, Dimitra ,  YPMA, Alexander

IPC: G03F7/20 ,  G05B19/418

Abstract: Described herein is a method comprising: determining a sequence of states of an object, the states determined based on processing information associated with the object, wherein the sequence of states includes one or more future states of the object; determining, based on at least one of the states within the sequence of states and the one or more future states, a process metric associated with the object, the process metric comprising an indication of whether processing requirements for the object are satisfied for individual states in the sequence of states; and initiating an adjustment to processing based on (1) at least one of the states and the one or more future states and (2) the process metric, the adjustment configured to enhance the process metric for the individual states in the sequence of states such that final processing requirements for the object are satisfied.

公开(公告)号：WO2018133999A1

公开(公告)日：2018-07-26

申请号：PCT/EP2017/082553

申请日：2017-12-13

Applicant: ASML NETHERLANDS B.V.

Inventor： YPMA, Alexander ,  GKOROU, Dimitra ,  TSIROGIANNIS, Georgios ,  HOOGENBOOM, Thomas, Leo, Maria ,  VAN HAREN, Richard, Johannes, Franciscus

IPC: G03F7/20 ,  G05B19/418 ,  H01L21/66

Abstract: The invention generates predicted data for control or monitoring of a production process to improve a parameter of interest. Context data (502) associated with operation of the production process (504) is obtained. Metrology/test (508) is performed on the product (506) of the production process (504), thereby obtaining performance data (510). A context-to-performance model is provided to generate predicted performance data (526) based on labeling of the context data (502) with performance data. This is an instance of semi-supervised learning. The context-to-performance model includes the learner (522) that performs semi-supervised labeling. The context-to-performance model is modified using prediction information related to quality of the context data and/or performance data. Prediction information may comprise relevance information relating to relevance of the obtained context data and/or obtained performance data to the parameter of interest. The prediction information may comprise model uncertainty information relating to uncertainty of the predicted performance data.

公开(公告)号：EP4538796A1

公开(公告)日：2025-04-16

申请号：EP23202760.7

申请日：2023-10-10

Applicant: ASML Netherlands B.V.

Inventor： GKOROU, Dimitra ,  SHANKAR, Aditya ,  KHEDEKAR, Satej ,  CHEN, Yiyu Lydia ,  DECOUCHANT, Jérémie, Éric, Alphonse, Pierre

IPC: G03F7/20

Abstract: Training a machine learning model used by different participants is described. Vertically federated learning is used to train the model with time series data sets. Time series data sets received from different participants are aligned, with each time series data set comprising different features corresponding to one or more samples common to each participant, but preserving the privacy of each time series data set for participants. First model parameters are received from a first participant. These are determined based on the aligning and first features provided by the first participant in a first time series data set. Second model parameters are received from a second participant. These are determined based on the aligning, second features provided by the second participant in a second time series data set, and semiconductor manufacturing process outputs associated with the second features. The model is trained based on the first and second model parameters.