Patents by Inventor Arnaud HUBAUX
Arnaud HUBAUX has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 12204252Abstract: A method for categorizing a substrate subject to a semiconductor manufacturing process including multiple operations, the method including: obtaining values of functional indicators derived from data generated during one or more of the multiple operations on the substrate, the functional indicators characterizing at least one operation; applying a decision model including one or more threshold values to the values of the functional indicators to obtain one or more categorical indicators; and assigning a category to the substrate based on the one or more categorical indicators.Type: GrantFiled: June 21, 2023Date of Patent: January 21, 2025Assignee: ASML NETHERLANDS B.V.Inventors: Arnaud Hubaux, Johan Franciscus Maria Beckers, Dylan John David Davies, Johan Gertrudis Cornelis Kunnen, Willem Richard Pongers, Ajinkya Ravindra Daware, Chung-Hsun Li, Georgios Tsirogiannis, Hendrik Cornelis Anton Borger, Frederik Eduard De Jong, Juan Manuel Gonzalez Huesca, Andriy Hlod, Maxim Pisarenco
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Patent number: 11994848Abstract: A method for configuring a semiconductor manufacturing process, the method including: providing an initial prediction model including a plurality of model parameters to one or more remote locations; receiving at least one updated model parameter from the one or more remote locations, the at least one model parameter is updated by training the initial prediction model with local data at the one or more remote locations; determining aggregated model parameters based on the at least one updated model parameter received from the one or more remote locations; and adjusting the initial prediction model based on the aggregated model parameters, the adjusted prediction model being operable to configure the semiconductor manufacturing process.Type: GrantFiled: March 12, 2020Date of Patent: May 28, 2024Assignee: ASML NETHERLANDS B.V.Inventors: Johannes Onvlee, Arnaud Hubaux
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Publication number: 20230341783Abstract: A method of determining matching performance between tools used in semiconductor manufacture and associated tools is described. The method includes obtaining a plurality of data sets related to a plurality of tools and a representation of the data sets in a reduced space having a reduced dimensionality. A matching metric and/or matching correction is determined based on matching the reduced data sets in the reduced space.Type: ApplicationFiled: January 19, 2021Publication date: October 26, 2023Applicant: ASML NETHERLANDS B.V.Inventors: Arnaud HUBAUX, Patrick WARNAAR, Scott Anderson MIDDLEBROOKS, Tijmen Pieter COLLIGNON, Chung-Hsun LI, Georgios TSIROGIANNIS, Sayyed Mojtaba SHAKERI
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Publication number: 20230333482Abstract: A method for categorizing a substrate subject to a semiconductor manufacturing process including multiple operations, the method including: obtaining values of functional indicators derived from data generated during one or more of the multiple operations on the substrate, the functional indicators characterizing at least one operation; applying a decision model including one or more threshold values to the values of the functional indicators to obtain one or more categorical indicators; and assigning a category to the substrate based on the one or more categorical indicators.Type: ApplicationFiled: June 21, 2023Publication date: October 19, 2023Applicant: ASML NETHERLANDS B.V.Inventors: Arnaud HUBAUX, Johan Franciscus Maria Beckers, Dylan John David Davies, Johan Gertrudis Cornelis Kunnen, Willem Richard Pongers, Ajinkya Ravindra Daware, Chung-Hsun Li, Georgios Tsirogiannis, Hendrik Cornelis Anton Borger, Frederik Eduard De Jong, Juan Manuel Gonzalez Huesca, Andriy Hlod, Maxim Pisarenco
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Publication number: 20230273529Abstract: Generating a control output for a patterning process is described. A control input is received. The control input is for controlling the patterning process. The control input includes one or more parameters used in the patterning process. The control output is generated with a trained machine learning mod& based on the control input, The machine learning model is trained with training data generated from simulation of the patterning process and/or actual process data, The training data includes 1) a plurality of training control inputs corresponding to a plurality of operational conditions of the patterning process, where the plurality of operational conditions of the patterning process are associated with operational condition specific behavior of the patterning process over time, and 2) training control outputs generated using a physical model based on the training control inputs.Type: ApplicationFiled: June 14, 2021Publication date: August 31, 2023Applicant: ASML NETHERLANDS B.V.Inventors: Satej Subhash KHEDEKAR, Henricus Jozef CASTELIJNS, Anjan Prasad GANTAPARA, Stephen Henry BOND, Seyed Iman MOSSAVAT, Alexander YPMA, Gerald DICKER, Ewout Klaas STEINMEIER, Chaoqun GUO, Chenxi LIN, Hongwei CHEN, Zhaoze LI, Youping ZHANG, Yi ZOU, Koos VAN BERKEL, Joost Johan BOLDER, Arnaud HUBAUX, Andriy Vasyliovich HLOD, Juan Manuel GONZALEZ HUESCA, Frans Bernard AARDEN
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Publication number: 20230260855Abstract: A method of determining a correction strategy in a semiconductor manufacturing process. The method can include obtaining functional indicator data relating to functional indicators associated with one or more process parameters of each of a plurality of different control regimes of the semiconductor manufacturing process and/or a tool associated with the semiconductor manufacturing process and using the functional indicator data as an input to a trained model to determine for which of the control regimes should a correction be determined so as to improve performance of the semiconductor manufacturing process according to at least one quality metric being representative of a quality of the semiconductor manufacturing process. The correction is then calculated for the determined control regime(s).Type: ApplicationFiled: June 21, 2021Publication date: August 17, 2023Inventors: Andriy Vasyliovich HLOD, Arnaud HUBAUX
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Patent number: 11687007Abstract: A method for categorizing a substrate subject to a semiconductor manufacturing process including multiple operations, the method including: obtaining values of functional indicators derived from data generated during one or more of the multiple operations on the substrate, the functional indicators characterizing at least one operation; applying a decision model including one or more threshold values to the values of the functional indicators to obtain one or more categorical indicators; and assigning a category to the substrate based on the one or more categorical indicators.Type: GrantFiled: January 9, 2020Date of Patent: June 27, 2023Assignee: ASML NETHERLANDS B.V.Inventors: Arnaud Hubaux, Johan Franciscus Maria Beckers, Dylan John David Davies, Johan Gertrudis Cornelis Kunnen, Willem Richard Pongers, Ajinkya Ravindra Daware, Chung-Hsun Li, Georgios Tsirogiannis, Hendrik Cornelis Anton Borger, Frederik Eduard De Jong, Juan Manuel Gonzalez Huesca, Andriy Hlod, Maxim Pisarenco
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Publication number: 20230124106Abstract: A method including: obtaining one or more models configured for predicting a process metric of a manufacturing process based on inputting process data; and using a reinforcement learning framework to evaluate the one or more models and/or model configurations of the one more models based on inputting new process data to the one or more models and determining a performance indication of the one or more models and/or model configurations in predicting the process metric based on inputting the new process data.Type: ApplicationFiled: February 24, 2021Publication date: April 20, 2023Inventor: Arnaud HUBAUX
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Publication number: 20220197264Abstract: A method for configuring a semiconductor manufacturing process, the method including: providing an initial prediction model including a plurality of model parameters to one or more remote locations; receiving at least one updated model parameter from the one or more remote locations, the at least one model parameter is updated by training the initial prediction model with local data at the one or more remote locations; determining aggregated model parameters based on the at least one updated model parameter received from the one or more remote locations; and adjusting the initial prediction model based on the aggregated model parameters, the adjusted prediction model being operable to configure the semiconductor manufacturing process.Type: ApplicationFiled: March 12, 2020Publication date: June 23, 2022Applicant: ASML NETHERLANDS B.V.Inventors: Johannes ONVLEE, Arnaud HUBAUX
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Publication number: 20220082949Abstract: A method for categorizing a substrate subject to a semiconductor manufacturing process including multiple operations, the method including: obtaining values of functional indicators derived from data generated during one or more of the multiple operations on the substrate, the functional indicators characterizing at least one operation; applying a decision model including one or more threshold values to the values of the functional indicators to obtain one or more categorical indicators; and assigning a category to the substrate based on the one or more categorical indicators.Type: ApplicationFiled: January 9, 2020Publication date: March 17, 2022Applicant: ASML NETHERLANDS B.V.Inventors: Arnaud HUBAUX, Johan Franciscus Maria BECKERS, Dylan John David DAVIES, Johan Gertrudis Cornelis KUNNEN, Willem Richard PONGERS, Ajinkya Ravindra DAWARE, Chung-Hsun LI, Georgios TSIROGIANNIS, Hendrik Cornelis Anton BORGER, Frederik Eduard DEJONG, Juan Manuel GONZALEZ HUESCA, Andriy HLOD, Maxim PISARENCO