公开(公告)号：US20240427308A1

公开(公告)日：2024-12-26

申请号：US18213790

申请日：2023-06-23

Applicant: Applied Materials, Inc.

Inventor： Rituraj Nandan ,  Ramachandran Subramanian ,  Brett Robert Schroeder ,  Pardeep Kumar ,  Zhenxing Han ,  Martha Inez Sanchez ,  Bharath Ram Sundar ,  Madhur Singh Sachan ,  Sundar Narayanan

IPC: G05B19/4099

Abstract: A method includes receiving data indicative of a range of processing conditions associated with a plurality of substrate processing operations. The data indicative of the range of processing conditions includes a first range of values of a first property and a second range of values of a second property of the processing conditions. The method further includes receiving data indicative of processing performance associated with the plurality of processed substrates. The data includes a first set of data associated with a first indication of substrate performance and a second set of data associated with a second indication of substrate performance. The method further includes performing analysis relating the processing conditions to the processing performance. The method further includes generating a visualization presenting results of the analysis including representations of the first indication of substrate performance and the second indication of substrate performance.

公开(公告)号：US11989495B2

公开(公告)日：2024-05-21

申请号：US17139330

申请日：2020-12-31

Applicant: Applied Materials, Inc.

Inventor： Debkalpo Das ,  Raman K Nurani ,  Ramachandran Subramanian ,  Bibhavendra Singh ,  Bharath Sundar

IPC: G06F30/33 ,  G06F18/213 ,  G06F18/214 ,  H01L21/70

CPC classification number: G06F30/33 ,  G06F18/213 ,  G06F18/214 ,  H01L21/702

Abstract: A method includes obtaining sensor data associated with a deposition process performed in a process chamber to deposit film on a surface of a substrate. The method further includes generating a plurality of physics based outputs using a transformation function and the sensor data. The method further includes mapping the physics based outputs to a training set. The method further includes training a virtual model based on the training set and the sensor data, wherein the virtual model is trained to generate predictive metrology data associated with the film.

公开(公告)号：US20220246457A1

公开(公告)日：2022-08-04

申请号：US17168041

申请日：2021-02-04

Applicant: APPLIED MATERIALS, INC.

Inventor： Bharath Ram Sundar ,  Raman K Nurani ,  Ramkishore Sankarasubramanian ,  Ramachandran Subramanian ,  Bharath Muralidharan ,  Ramaswamy Melatoor Narayanan ,  Ganapathi Raman Sankaranarayanan

IPC: H01L21/67 ,  G06N20/00 ,  G06N5/04 ,  H01L21/66

Abstract: Methods and systems for detecting outliers at a manufacturing system using machine learning are provided. Data collected by a sensors at a manufacturing system during a current process performed for a first set of substrates is provided as input to a trained machine learning model. One or more outputs are obtained from the trained machine learning model. A first amount of drift of a first set of parameter values for the first set of substrates from a target set of parameter values for the first set of substrates is extracted from the one or more outputs. A second amount of drift of each of the first set of parameter values for the first set of substrates from a corresponding parameter value of a second set of parameter values for a second set of substrates processed according to the current process at the manufacturing system prior to the performance of the current process for the first set of substrates is also extracted from the one or more outputs. A substrate health rating is assigned for each of the first set of substrates based on the first amount of drift. A sensor health rating is assigned for each of the sensors at the manufacturing system based on the second amount of drift. An indication of the substrate health rating for each of the first set of substrates and the sensor health rating for each of the sensors are transmitted to a client device connected to the manufacturing system.

公开(公告)号：US20250021832A1

公开(公告)日：2025-01-16

申请号：US18221301

申请日：2023-07-12

Applicant: Applied Materials, Inc.

Inventor： Bharath Ram Sundar ,  Jagadeesh Govindaraj ,  Raman Krishnan Nurani ,  Ramachandran Subramanian ,  Nusrat Jahan Chhanda ,  Sundar Narayanan

IPC: G06N5/022

Abstract: A method includes obtaining, by a processing device, first data indicative of substrate generation parameters of a first substrate. The processing device further obtains second data indicative of properties of the first substrate. The processing device further obtains third data indicative of substrate generation parameters of a second substrate. The processing device further receives fourth data indicative of properties of the second substrate. The method further includes providing a user interface (UI). The UI includes a first UI element for presenting a visual depiction of the second data and a second UI element for presenting a visual depiction of the fourth data. The method further includes receiving user input of a classification of the first substrate and the second substrate. The method further includes performing analysis relating the first data and the third data to the user classifications. The method further includes performing a corrective action based on the analysis.

公开(公告)号：US20240249052A1

公开(公告)日：2024-07-25

申请号：US18624471

申请日：2024-04-02

Applicant: Applied Materials, Inc.

Inventor： Debkalpo Das ,  Raman K. Nurani ,  Ramachandran Subramanian ,  Bibhavendra Singh ,  Bharath Sundar

IPC: G06F30/33 ,  G06F18/213 ,  G06F18/214 ,  H01L21/70

CPC classification number: G06F30/33 ,  G06F18/213 ,  G06F18/214 ,  H01L21/702

Abstract: A method includes obtaining sensor data associated with a deposition process performed in a process chamber to deposit film on a surface of a substrate. A plurality of physics-based outputs are generated using a transformation function and the sensor data. The transformation function is used to at least one of estimate site availability for growth at an equilibrium condition for the process chamber or estimate boundary layer thickness in an equilibrium condition for the process chamber. The physics-based outputs are mapped to a training set and a virtual model is trained based on the training set and the sensor data. The virtual model is trained to generate predictive metrology data associated with the film.

公开(公告)号：US11842910B2

公开(公告)日：2023-12-12

申请号：US17168041

申请日：2021-02-04

Applicant: APPLIED MATERIALS, INC.

Inventor： Bharath Ram Sundar ,  Raman K Nurani ,  Ramkishore Sankarasubramanian ,  Ramachandran Subramanian ,  Bharath Muralidharan ,  Ramaswamy Melatoor Narayanan ,  Ganapathi Raman Sankaranarayanan

IPC: H01L21/66 ,  G06N5/04 ,  H01L21/67 ,  G06N20/00

CPC classification number: H01L21/67288 ,  G06N5/04 ,  G06N20/00 ,  H01L22/12

Abstract: Methods and systems for detecting outliers at a manufacturing system using machine learning are provided. Data collected by a sensors at a manufacturing system during a current process performed for a first set of substrates is provided as input to a trained machine learning model. One or more outputs are obtained from the trained machine learning model. A first amount of drift of a first set of parameter values for the first set of substrates from a target set of parameter values for the first set of substrates is extracted from the one or more outputs. A second amount of drift of each of the first set of parameter values for the first set of substrates from a corresponding parameter value of a second set of parameter values for a second set of substrates processed according to the current process at the manufacturing system prior to the performance of the current process for the first set of substrates is also extracted from the one or more outputs. A substrate health rating is assigned for each of the first set of substrates based on the first amount of drift. A sensor health rating is assigned for each of the sensors at the manufacturing system based on the second amount of drift. An indication of the substrate health rating for each of the first set of substrates and the sensor health rating for each of the sensors are transmitted to a client device connected to the manufacturing system.