Spilt-phase chamber modeling for chamber matching and fault detection

• US 20060155410A1
• Filed: 01/10/2005
• Published: 07/13/2006
• Est. Priority Date: 01/10/2005
• Status: Active Grant

• Current Assignee: Applied Materials Incorporated
• Original Assignee: Applied Materials Incorporated
• Inventors: Yamartino, John M.
• Granted Patent: US 7,624,003 B2
• Time in Patent Office: Days
• US Class Current: 700/108
• CPC Class Codes: G05B 17/02 electric

Abstract

In at least one embodiment, the present invention is a method for thin-film process chamber data analysis, which includes acquiring chamber data, defining an adjustment portion of the chamber data and a steady-state portion of the chamber data, and forming a chamber model having an adjustment portion and a steady-state portion. The method can further include comparing the chamber model with a subject chamber to provide a chamber data comparison and utilizing the chamber data comparison.

Claims

1. A method for thin-film process chamber data analysis, the method comprising:

a) acquiring chamber data;

b) defining an adjustment portion of the chamber data and a steady-state portion of the chamber data; and

c) forming a chamber model having an adjustment portion and a steady-state portion.

2. The method of claim 1, wherein forming a chamber model having a adjustment portion and a steady-state portion comprises performing a multivariate analysis on the adjustment portion and the steady-state portion of the chamber data.

3. The method of claim 1, wherein acquiring chamber model data comprises acquiring chamber model data from more than one chamber.

4. The method of claim 1, wherein acquiring chamber model data comprises acquiring chamber model data from more than one run of a chamber.

5. The method of claim 1, further comprising comparing the chamber model with a subject chamber to provide a chamber data comparison.

6. The method of claim 5, further comprising utilizing the chamber data comparison.

7. The method of claim 6, wherein utilizing the chamber data comparison comprises adjusting the subject chamber.

8. The method of claim 6, wherein utilizing the chamber data comparison comprises at least one of:

(1) issuing a warning;

or (2) faulting the subject chamber.

9. The method of claim 8, wherein utilizing the chamber data comparison comprises faulting the subject chamber, wherein faulting the subject chamber comprises ceasing operation of the subject chamber.

10. The method of claim 1, wherein defining an adjustment portion of the chamber data and a steady-state portion of the chamber data comprises defining the adjustment portion of the chamber data as comprising chamber data acquired during a transition between at least two operational conditions of a chamber.

11. The method of claim 1, wherein defining an adjustment portion of the chamber data and a steady-state portion of the chamber data comprises defining the steady-state portion of the chamber data as comprising chamber data acquired when a chamber is operating in accordance to at least one predefined operational condition.

12. The method of claim 1, wherein acquiring chamber model data comprises measuring at least one chamber variable over time.

13. The method of claim 12, wherein forming a chamber model having an adjustment portion and a steady-state portion comprises performing a multivariate analysis on the adjustment portion and the steady-state portion of the chamber data, wherein performing a multivariate analysis comprises a forming a linear combination of the at least one chamber variable and individually weighting each of the at least one chamber variable.

14. The method of claim 12, wherein measuring at least one chamber variable over time comprises measuring at least one of:

(1) a chamber temperature;

(2) a chamber pressure;

(3) a gas flow rate;

(4) a bias RF power;

(5) a source RF power;

(6) a microwave power;

(7) a voltage reading;

(8) a current reading;

or (9) a pressure control valve position.

15. The method of claim 12, wherein measuring at least one chamber variable over time comprises measuring at least one of:

(1) a pressure;

(2) a pressure control valve position;

(3) a total gas flow;

(4) an individual gas flow;

(5) a RF measurement of voltage;

(6) a RF measurement of current;

(7) a RF measurement of phase;

(8) a forward RF power;

(9) a reflected RF power;

(10) a RF match tuning position;

(11) a microwave forward power;

(12) microwave reflected power;

(13) a microwave tuning position;

(14) an electrostatic chuck voltage;

(15) an electrostatic chuck current;

(16) a helium cooling pressure;

(17) a helium cooling flow;

(18) a helium cooling leak rate;

(19) a magnet current, and (20) a chamber component temperature.

16. The method of claim 5, wherein comparing the chamber model with a subject chamber is performed with the subject chamber offline.

17. The method of claim 5, wherein comparing the chamber model with a subject chamber is performed with the subject chamber online.

33. The method of claim 1, wherein defining an adjustment portion of the chamber data and a steady-state portion of the chamber data comprises defining the adjustment portion of the chamber data as comprising chamber data acquired during an endpoint transition.

18. A split-phase chamber analysis method comprising:

a) executing a process run having at least one phase of operation;

b) measuring at least one chamber variable during the at least one phase of operation to form chamber data;

c) separating the chamber data into at least one adjustment portion and at least one steady-state portion for each of the at least one phase of operation; and

d) performing a multivariate analysis on the at least one adjustment portion and the at least one steady-state portion of the chamber data.

19. The split-phase chamber analysis method of claim 18, wherein executing a process run comprises executing a process run according to a process recipe comprising the at least one phase of operation, wherein each phase of the least one phase of operation has at least one operational condition defined in the process recipe.

20. The split-phase chamber analysis method of claim 19, wherein the at least one phase of operation comprises at least two phases of operation, and wherein the at least one adjustment portion comprises a transition between operational conditions of separate phases of the at least two phases of operation.

21. The split-phase chamber analysis method of claim 19, wherein the at least one steady-state portion comprises operation of chamber in accordance to at least one operational condition.

22. The split-phase chamber analysis method of claim 18, wherein executing a process run having at least one phase of operation comprises executing a process run having a recipe with a first phase of operation and a second phase of operation, wherein the first phase of operation has a first operational condition defined in the recipe, wherein the second phase of operation has a second process condition defined in the recipe.

23. The split-phase chamber analysis method of claim 22, wherein the at least one adjustment portion comprises a period of transition between the first operational condition and the second operational condition.

24. The split-phase chamber analysis method of claim 22, wherein the at least one steady-state portion comprises a period of operation of chamber in accordance with at least one of:

(1) the first operational condition; and

(2) the second operational condition.

25. The split-phase chamber analysis method of claim 18, wherein measuring at least one chamber variable comprises measuring at least one chamber variable over time.

26. The split-phase chamber analysis method of claim 25, wherein performing a multivariate analysis on the at least one adjustment portion and the at least one steady-state portion of the chamber data comprises a forming a linear combination of the at least one chamber variable and individually weighting each of the at least one chamber variable.

27. The split-phase chamber analysis method of claim 25, wherein measuring at least one chamber variable over time comprises measuring at least one of:

(1) a chamber temperature;

(2) a chamber pressure;

(3) a gas flow rate;

(4) a bias RF power;

(5) a source RF power;

(6) a microwave power;

(7) a voltage reading;

(8) a current reading;

or (9) a pressure control valve position.

28. The split-phase chamber analysis method of claim 25, wherein measuring at least one chamber variable over time comprises measuring at least one of:

(1) a pressure;

(2) a pressure control valve position;

(3) a total gas flow;

(4) an individual gas flow;

(5) a RF measurement of voltage;

(6) a RF measurement of current;

(7) a RF measurement of phase;

(8) a forward RF power;

(9) a reflected RF power;

(10) a RF match tuning position;

(11) a microwave forward power;

(12) microwave reflected power;

(13) a microwave tuning position;

(14) an electrostatic chuck voltage;

(15) an electrostatic chuck current;

(16) a helium cooling pressure;

(17) a helium cooling flow;

(18) a helium cooling leak rate;

(19) a magnet current, and (20) a chamber component temperature.

34. The split-phase chamber analysis method of claim 19, wherein the at least one adjustment portion comprises an endpoint transition.

29. A thin-film chamber analysis method for chamber matching comprising:

a) acquiring chamber model data from more than one known chamber;

b) defining a transition portion and a steady-state portion of at least one process phase of the chamber model data;

c) performing a multivariate analysis to form a chamber model with a transition portion and a steady-state portion;

d) comparing the chamber model with a subject chamber during an offline analysis; and

e) adjusting the subject chamber.

30. A thin-film chamber analysis method for fault detection comprising:

a) acquiring chamber model data from more than one run of a chamber;

b) defining a transition portion and a steady-state portion of at least one process phase of the chamber model data;

c) performing a multivariate analysis to form a chamber model with a transition portion and a steady-state portion; and

d) comparing the chamber model with a subject process run of the chamber.

31. The thin-film chamber analysis method for fault detection of claim 30, further comprising issuing a warning.

32. The thin-film chamber analysis method for fault detection of claim 30, further comprising faulting the chamber.