Determining a next tool state based on fault detection information

• US 6,912,433 B1
• Filed: 12/18/2002
• Issued: 06/28/2005
• Est. Priority Date: 12/18/2002
• Status: Active Grant

• Current Assignee: Advanced Micro Devices, Inc.
• Original Assignee: Advanced Micro Devices, Inc.
• Inventors: Chong, Robert J., Miller, Michael L., Pasadyn, Alexander J., Green, Eric O.
• Primary Examiner(s): Von Buhr, Maria N.
• Application Number:
  US10/323,554
• Time in Patent Office: 923 Days
• Field of Search: 700 28- 34, 700108-111, 700117-121, 700174-177, 702189-197, 702 81- 84, 702 57- 59, 702182-185
• US Class Current: 700/110
• CPC Class Codes: G05B 19/41875 characterised by quality surveillance of production
• CPC Class Codes: G05B 2219/32182 If state of tool, product deviates from standard, adjust system, feedback
• CPC Class Codes: G05B 2219/45031 Manufacturing semiconductor wafers
• CPC Class Codes: G05B 2219/50065 Estimate trends from past measured values, correct before really out of tolerance
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

A method and apparatus are provided for determining a next tool state based on fault detection information. The method comprises receiving operational data associated with processing of a workpiece by a processing tool, determining at least a portion of noise associated with the processing of the workpiece based on analyzing the operational data and estimating a next state of the processing tool based on at least the determined portion of the noise.

Claims

1. A method, comprising:

receiving operational data associated with processing of a workpiece by a processing tool;

performing fault detection analysis on at least a portion of the received operational data;

determining at least a portion of noise associated with the processing of the workpiece based on analyzing the operational data;

adjusting the determined portion of the noise based on the fault detection analysis; and

estimating a next state of the processing tool based on at least the adjusted portion of the noise.

2. The method of claim 1, wherein receiving the operational data comprises receiving the operational data associated with the processing of a semiconductor wafer.

3. The method of claim 1, further comprising determining a control move based at least on the estimated next state of the processing tool.

4. The method of claim 3, further comprising processing a next workpiece based at least on the control move.

5. The method of claim 1, wherein determining at least the portion of the noise comprises determining at least one of a process noise and measurement noise associated with the processing of the workpiece.

6. The method of claim 5, wherein determining at least the portion of the noise comprises adjusting one or more elements of a covariance matrix based on analyzing the operational data.

7. The method of claim 6, wherein the covariance matrix represents at least one of a shift and drift in processing by the processing tool.

8. The method of claim 6, wherein adjusting the one or more elements of the covariance matrix comprises at least one of inflating or deflating the elements of the covariance matrix.

9. The method of claim 1, wherein receiving the operational data comprises receiving the operational data associated with processing of a plurality of workpieces by the processing tool.

10. An apparatus, comprising:

an interface adapted to receive operational data associated with processing of a workpiece by a processing tool; and

a control unit communicatively coupled to the interface, the control unit adapted to;

determine at least a portion of noise associated with the processing of the workpiece based on analyzing the operational data;

adjust the determined portion of the noise based on fault detection analysis that is performed based on at least a portion of the received operational data; and

estimate a next state of the processing tool based on at least the adjusted portion of the noise.

11. The apparatus of claim 10, wherein the control unit is adapted to receive the operational data associated with the processing of a semiconductor wafer.

12. The apparatus of claim 11, wherein the control unit is adapted to determine a control move based at least on the estimated next state of the processing tool.

13. The apparatus of claim 12, wherein the control unit is adapted to process a next workpiece based at least on the control move.

14. The apparatus of claim 10, wherein the control unit is adapted to determine at least one of a process noise and measurement noise associated with the processing of the workpiece.

15. The apparatus of claim 14, wherein the control unit is adapted to adjust one or more elements of a covariance matrix based on analyzing the operational data.

16. The apparatus of claim 15, wherein the control unit is adapted to estimate the next state based at least on the covariance matrix that represents at least one of a shift and drift in the processing by the processing tool.

17. An apparatus, comprising:

means for receiving operational data associated with processing of a workpiece by a processing tool;

means for analyzing, using a fault detection unit, at least a portion of the received operational data to determine a process variation associated with the processing of the workpiece;

means for determining at least a portion of noise associated with the processing of the workpiece based on analyzing the operational data;

means for adjusting the determined portion of the noise based on the determined process variation; and

means for estimating a next state of the processing tool based on at least the adjusted portion of the noise.

18. An article comprising one or more machine-readable storage media containing instructions that when executed enable a processor to:

receive operational data associated with processing of a workpiece by a processing tool;

adjust one or more noise parameters associated with the processing of the workpiece based on analyzing the operational data and based on fault detection analysis that is performed based on at least a portion of the received operational data; and

estimate a next state of the processing tool based on at least the one or more adjusted noise parameters.

19. The article of claim 18, wherein the instructions when executed enable the processor to generate a control move based at least on the estimated next state of the processing tool.

20. The article of claim 19, wherein the instructions when executed enable the processor to process a next workpiece based at least on the control move.

21. The article of claim 18, wherein the instructions when executed enable the processor to adjust one or more elements of a covariance matrix related to a level of uncertainty in the processing of the workpiece.

22. The article of claim 18, wherein the instructions when executed enable the processor to adjust the one or more parameters based on detecting a fault associated with the processing of the workpiece.

23. The article of claim 18, wherein the instructions when executed enable the processor to estimate a next each rate.

24. The article of claim 18, wherein the instructions when executed enable the processor to receive operational data associated with the processing of a semiconductor wafer.

25. A system, comprising:

a processing tool adapted to provide operational data associated with processing of a workpiece;

control unit adapted to;

receive the operational data;

determine at least a portion of noise associated with the processing of the workpiece based on analyzing the operational data;

adjust the determined portion of the noise based on fault detection analysis that is performed based on at least a portion of the received operational data; and

estimate a next state of the processing tool based on at least the adjusted portion of the noise.

26. The system of claim 25, wherein the control unit is associated with a fault detection and classification unit, further comprising an advanced process control framework coupled between the processing tool and the fault detection and classification unit.