Information processing device, recording medium, and process condition search method

US12253838B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-12253838-B2
Application numberUS-202217584712-A
CountryUS
Kind codeB2
Filing dateJan 26, 2022
Priority dateFeb 4, 2021
Publication dateMar 18, 2025
Grant dateMar 18, 2025

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  1. Title

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  2. Abstract

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

An information processing device includes: a machine learning model selection part configured to select a machine learning model appropriate for a data set used for learning of the machine learning model; a calculation part configured to perform an optimization calculation by using the selected machine learning model to calculate process conditions that can achieve a target process result, predicted values of a process result corresponding to each of the process conditions, and reliability of the predicted values; a process condition selection part configured to select, among the process conditions that can achieve the target process result, one or more process conditions according to the predicted values of the process result and the reliability of the predicted values; and a display controller configured to display the selected process conditions, the predicted values of the process result corresponding to each of the selected process conditions, and the reliability of the predicted values.

First claim

Opening claim text (preview).

What is claimed is: 1. A system comprising: an analysis server, which creates a machine learning model of a semiconductor manufacturing device executing a process according to a process condition and searches for a process condition that can achieve a target process result by using the machine learning model, the analysis server comprising: a machine learning model selector configured to select a machine learning model among a plurality of machine learning models created by using a plurality of regression methods; a calculator configured to perform an optimization calculation by using the selected machine learning model to calculate a plurality of process conditions that can achieve the target process result, predicted values of a process result corresponding to each of the plurality of process conditions, and reliability of the predicted values; a process condition selector configured to select, among the plurality of the process conditions that can achieve the target process result, one or more process conditions according to the predicted values of the process result and the reliability of the predicted values; and a display controller configured to display the selected process conditions, the predicted values of the process result corresponding to each of the selected process conditions, and the reliability of the predicted values, wherein the process condition selector is further configured to select the one or more process conditions among the plurality of process conditions that can achieve the target process result, based on priorities assigned to a plurality of target values included in the target process result, priorities assigned to a plurality of adjustment targets, which is included in the process conditions and to be adjusted in order to achieve the target process result, and achievement levels of the predicted values with respect to the target values of the process result; and a device controller configured to: control the semiconductor manufacturing device to execute the process according to each of the selected process conditions. 2. The system of claim 1 , the analysis server further comprising a determination part configured to determine whether to continue or terminate a process condition search based on a comparison result between actually measured values of a process result obtained by executing the process by the semiconductor manufacturing device according to each of the selected process conditions and target values of the process result. 3. The system of claim 2 , the analysis server further comprising a feedback part configured to feed back the selected process conditions and the actually measured values of the process result obtained by executing the process by the semiconductor manufacturing device according to each of the selected process conditions to the machine learning model selector. 4. The system of claim 1 , wherein the display controller is further configured to display an input field for inputting the priorities assigned to the target values, an input field for inputting the priorities assigned to the plurality of adjustment targets, and the machine learning model to be used, and to display a screen for receiving a change in the machine learning model to be used. 5. The system of claim 1 , the analysis server further comprising a feedback part configured to feed back the selected process conditions and actually measured values of the process result obtained by executing the process by the semiconductor manufacturing device according to each of the selected process conditions to the machine learning model selector. 6. At least one non-transitory computer-readable storage medium storing a first program that causes an analysis server, which creates a machine learning model of a semiconductor manufacturing device executing a process according to a process condition and searches for a process condition that can achieve a target process result by using the machine learning model, to execute: selecting a machine learning model among a plurality of machine learning models created by using a plurality of regression methods; performing an optimization calculation by using the selected machine learning model to calculate a plurality of process conditions that can achieve the target process result, predicted values of a process result corresponding to each of the plurality of process conditions, and reliability of the predicted values; selecting, among the plurality of the process conditions that can achieve the target process result, one or more process conditions according to the predicted values of the process result and the reliability of the predicted values; and displaying the selected process conditions, the predicted values of the process result corresponding to each of the selected process conditions, and the reliability of the predicted values, wherein the selecting the one or more process conditions includes selecting the one or more process conditions among the plurality of process conditions that can achieve the target process result, based on priorities assigned to a plurality of target values included in the target process result, priorities assigned to a plurality of adjustment targets, which is included in the process conditions and to be adjusted in order to achieve the target process result, and achievement levels of the predicted values with respect to the target values of the process result, and a second program that causes a device controller to execute: controlling the semiconductor manufacturing device to execute the process according to each of the selected process conditions. 7. A process condition search method for an analysis server, which creates a machine learning model of a semiconductor manufacturing device executing a process according to a process condition and searches for a process condition that can achieve a target process result by using the machine learning model, the process condition search method comprising: selecting a machine learning model among a plurality of machine learning models created by using a plurality of regression methods; performing an optimization calculation by using the selected machine learning model to calculate a plurality of process conditions that can achieve the target process result, predicted values of a process result corresponding to each of the plurality of process conditions, and reliability of the predicted values; selecting, among the plurality of the process conditions that can achieve the target process result, one or more process conditions according to the predicted values of the process result and the reliability of the predicted values; displaying the selected process conditions, the predicted values of the process result corresponding to each of the selected process conditions, and the reliability of the predicted values, wherein the selecting the one or more process conditions includes selecting the one or more process conditions among the plurality of process conditions that can achieve the target process result, based on priorities assigned to a plurality of target values included in the target process result, priorities assigned to a plurality of adjustment targets, which is included in the process conditions and to be adjusted in order to achieve the target process result, and achievement levels of the predicted values with respect to the target values of the process result; and, causing the semiconductor manufacturing device to execute the process according to the selected process conditions.

Assignees

Inventors

Classifications

  • Process monitoring, e.g. flow or thickness monitoring · CPC title

  • the criterion being a learning criterion · CPC title

  • based on a comparison with predetermined threshold or range, e.g. "classical methods", carried out during normal operation; threshold adaptation or choice; when or how to compare with the threshold · CPC title

  • Confirmation of fault detection, e.g. extra checks to confirm that a failure has indeed occurred · CPC title

  • Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA] · CPC title

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Frequently asked questions

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What does patent US12253838B2 cover?
An information processing device includes: a machine learning model selection part configured to select a machine learning model appropriate for a data set used for learning of the machine learning model; a calculation part configured to perform an optimization calculation by using the selected machine learning model to calculate process conditions that can achieve a target process result, pred…
Who is the assignee on this patent?
Tokyo Electron Ltd
What technology area does this patent fall under?
Primary CPC classification G05B13/0265. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Mar 18 2025 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 6 related publications on this page (citations in our corpus or others sharing the same primary CPC).