Adjusting chamber performance by equipment constant updates

Patent metadata

Field	Value
Publication number	US-12560916-B2
Application number	US-202218070453-A
Country	US
Kind code	B2
Filing date	Nov 28, 2022
Priority date	Nov 28, 2022
Publication date	Feb 24, 2026
Grant date	Feb 24, 2026

Abstract

A method includes receiving, by a processing device, first trace data associated with a first processing chamber, wherein the first processing chamber satisfies one or more performance metrics. The method further includes generating target trace data based on the first trace data associated with the first processing chamber. The method further includes receiving second trace data associated with a second processing chamber, wherein the second processing chamber does not satisfy the one or more performance metrics. The method further includes generating, based on the target trace data and the second trace data, a first recommended corrective action associated with the second processing chamber, wherein the first recommended corrective action includes updating one or more equipment constants of the second processing chamber. The method further includes performing the first recommended corrective action.

First claim

What is claimed is:

1 . A method, comprising:
receiving, by a processing device, first trace data associated with a first processing chamber, wherein the first processing chamber satisfies one or more performance metrics; generating target trace data based on the first trace data associated with the first processing chamber; receiving second trace data associated with a second processing chamber, wherein the second processing chamber does not satisfy the one or more performance metrics; generating, based on the target trace data and the second trace data, a first recommended corrective action associated with the second processing chamber and a second recommended corrective action associated with the second processing chamber, wherein the first recommended corrective action and the second recommended corrective action comprise updating one or more equipment constants of the second processing chamber; scheduling performance of the first recommended corrective action and the second recommended corrective action such that the first recommended corrective action is scheduled to be performed before the second recommended corrective action; and performing the first recommended corrective action.

2 . The method of claim 1 , further comprising:
receiving first metrology data of a first substrate associated with the first trace data; and receiving second metrology data of a second substrate associated with the second trace data, wherein the first recommended corrective action is further based on the first metrology data and the second metrology data.

3 . The method of claim 1 , further comprising:
receiving a first set of equipment constants associated with the first processing chamber; and receiving a second set of equipment constants associated with the second processing chamber, wherein the first recommended corrective action is further based on the first set of equipment constants and the second set of equipment constants.

4 . The method of claim 1 , further comprising generating a plurality of recommended corrective actions, wherein the plurality of recommended corrective actions comprises the first recommended corrective action, and wherein generating the plurality of recommended corrective actions comprises generating a schedule for implementing at least two of the plurality of recommended corrective actions.

5 . The method of claim 1 , further comprising:
receiving third trace data associated with a third processing chamber, wherein the third processing chamber does not satisfy the one or more performance metrics; generating a plurality of recommended corrective actions, wherein the plurality of recommended corrective actions comprises the first recommended corrective action and a second recommended corrective action, and wherein the second recommended corrective action is associated with the third processing chamber; and performing the second recommended corrective action.

6 . The method of claim 5 , wherein performing of the first recommended corrective action and performing of the second recommended corrective action are scheduled such that at least one substrate is processed by the second processing chamber between performance of the first recommended corrective action and performance of the second recommended corrective action.

7 . The method of claim 1 , wherein generating the first recommended corrective action comprises:
providing the target trace data and the second trace data to a trained model; receiving output from the trained model indicative of the first recommended corrective action; and scheduling performance of the first recommended corrective action.

8 . The method of claim 7 , wherein the trained model comprises a trained machine learning model.

9 . The method of claim 1 , wherein the target trace data comprises a range of trace data values that satisfy one or more performance metrics.

10 . A system, comprising memory and a processing device coupled to the memory, wherein the processing device is to:
receive first trace data associated with a first processing chamber, wherein the first processing chamber satisfies one or more performance metrics; generate target trace data based on the first trace data associated with the first processing chamber; receive second trace data associated with a second processing chamber, wherein the second processing chamber does not satisfy the one or more performance metrics; generate, based on the target trace data and the second trace data, a first recommended corrective action associated with the second processing chamber and a second recommended corrective action associated with the second processing chamber, wherein the first recommended corrective action and the second recommended corrective action comprise updating one or more equipment constants of the second processing chamber; schedule performance of the first recommended corrective action and the second recommended corrective action such that the first recommended corrective action is scheduled to be performed before the second recommended corrective action; and perform the first recommended corrective action.

11 . The system of claim 10 , wherein the processing device is further to:
receive first metrology data of a first substrate associated with the first trace data; and receive second metrology data of a second substrate associated with the second trace data, wherein the first recommended corrective action is further based on the first metrology data and the second metrology data.

12 . The system of claim 10 , wherein the processing device is further to:
receive a first set of equipment constants associated with the first processing chamber; and receive a second set of equipment constants associated with the second processing chamber, wherein the first recommended corrective action is further based on the first set of equipment constants and the second set of equipment constants.

13 . The system of claim 10 , wherein the processing device is further to generate a plurality of recommended corrective actions, wherein the plurality of recommended corrective actions comprises the first recommended corrective action, and wherein generating the plurality of recommended corrective actions comprises generating a schedule for implementing at least two of the plurality of recommended corrective actions.

14 . The system of claim 10 , wherein the processing device is further to:
receive third trace data associated with a third processing chamber, wherein the third processing chamber does not satisfy the one or more performance metrics; generate a plurality of recommended corrective actions, wherein the plurality of recommended corrective actions comprises the first recommended corrective action and a second recommended corrective action, and wherein the second recommended corrective action is associated with the third processing chamber; and performing the second recommended corrective action.

15 . The system of claim 10 , wherein the target trace data comprises a range of trace data values that satisfy one or more performance metrics.

16 . A non-transitory machine-readable storage medium storing instructions which, when executed, cause a processing device to perform operations comprising:
receiving first trace data associated with a first processing chamber, wherein the first processing chamber satisfies one or more performance metrics; generating target trace data based on the first trace data associated with the first processing chamber; receiving second trace data associated with a second processing chamber, wherein the

Assignees

• Applied Materials Inc

Inventors

• Bhatia Sidharth
• Lindley Roger
• Ummethala Upendra
• Li Thomas
• Howells Michael
• Babayan Steven
• Dao Mimi-Diemmy

Classifications

• G05B19/41885

  characterised by modeling, simulation of the manufacturing system · CPC title

• G05B19/4188 Primary

  characterised by CIM planning or realisation · CPC title

• G05B2219/45031

  Manufacturing semiconductor wafers · CPC title

• Y02P90/02

  Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS] · CPC title

• G06N20/00

  Machine learning · CPC title