Method for extracting process determinant conditions from a plurality of process signals

• US 6,420,194 B1
• Filed: 07/14/2000
• Issued: 07/16/2002
• Est. Priority Date: 10/12/1999
• Status: Expired due to Term

• Current Assignee: WSOU Investments, LLC (WSOU Holdings, LLC)
• Original Assignee: Lucent Technologies, Inc. (Nokia Corporation)
• Inventors: Reitman, Edward Alois
• Primary Examiner(s): Powell, William A.
• Application Number:
  US09/616,120
• Time in Patent Office: 732 Days
• Field of Search: 216/60, 216/67, 216/85, 216/84, 438/9, 438/14, 438/16, 438/710, 156/345.MT
• US Class Current: 438/9
• CPC Class Codes: H01L 21/67069 for drying etching
• CPC Class Codes: H01L 21/67242 Apparatus for monitoring, sorting or marking testing or measuring during manufacture H01L22/00, marks per se H01L23/544; testing individual semiconductor devices G01R31/26
• CPC Class Codes: H01L 21/6831 using electrostatic chucks
• CPC Class Codes: H01L 22/26 Acting in response to an ongoing measurement without interruption of processing, e.g. endpoint detection, in-situ thickness measurement endpoint detection arrangements in CMP apparatus B24B37/013, in discharge apparatus H01J37/32

Abstract

A system and method for identifying events in a manufacturing process from a sequence of m-dimensional input data signals, m≧2 obtained from monitoring of the manufacturing process utilizing a data processor for transforming each m-dimensional input data signal to a set of output data signals based on an orthogonal polynomial transform function, wherein the input data signals are used as coefficients in evaluating the polynomial transform functions. The data processor also integrates the transform function within the defined limits of the transform function to determine a scalar value as a function of time. A display system may be used to display a graph of the scalar values as a function of time for visually identifying events or the processor may identify events based on detected scalar values. The transform function may be Fourier, Chebyshev, Legendre or other polynomial type function.

Claims

1. A method for processing a sequence of sets of input data signals obtained from monitoring of a manufacturing process, each set of input data signals comprising m≧

2 data signals, the method comprising;

applying each set of input data signals as coefficients of an orthogonal polynomial transfer function; and

integrating within the defined limits of the polynomial transfer function for each data set to obtain a scalar value.

2. The method of claim 1 wherein the integer powers are even integers.

3. The method of claim 1 wherein the integer powers are odd integers.

4. The method of claim 1 wherein the method of integrating comprises piecewise integration of each term of the transfer function and summation of results of each piecewise integration.

5. The method of claim 1 and including the step of empirically selecting the integer powers to emphasize selected ones of the input data signals.

6. The method of claim 1 wherein the transfer function comprises a Fourier transform.

7. The method of claim 1 wherein the transfer function comprises a Chebyshev polynomial.

8. The method of claim 1 wherein the transfer function comprises a Legendre polynomial.

9. The method of claim 1 wherein the transfer fiction comprises an Andrews-Haar wavelet function.

10. A method according to claim 1 wherein each of said sets of input data signals reflects the state of an observed process.

11. A method according to claim 10 wherein each of said sets of input data signals comprise data signals I₁, I₂, . . . I_m that reflect real time observations of respective state variables of the observed process.

12. A method according to claim 10 wherein each of said sets of input data signals comprises data signals I₁, I₂, . . . I_m that reflects non-real time observations of the process.

13. The method of claim 10 wherein the observed process comprises a plasma etching process in an integrated circuit manufacturing process, each of the input data signals representing a measured characteristic of the etching process.

14. The method of claim 13 wherein each set of input data signals define the state of the etching process at a selected time.

15. The method of claim 14 wherein at least one of the input data signals exhibits a change at an endpoint of the etching process and the polynomial transfer function is selected to produce an amplitude spike in the integrated function concurrent with the endpoint.

16. The method of claim 15 wherein the input data signals are selected from the group comprising reflected RF power, dc bias, upper electrode temperature, lower electrode temperature, wall temperature, electrostatic chuck voltage, electrostatic chuck current, adaptive pressure control valve position, C1 capacitor position, C2 capacitor position, phase difference between RF applied and RF reflected and matching network error magnitude.

17. The method of claim 16 wherein the order of the coefficients corresponding to the selected input data signals is selected empirically to produce a maximum signal.

19. A method according to claim 6 and further comprising the step of integrating between upper and lower limits.

20. A method according to claim 6 wherein the state variables represent intensity values selected from the group comprising reflected RF power, dc bias, upper electrode temperature, lower electrode temperature, wall temperature, electrostatic chuck voltage, electrostatic chuck current, adaptive pressure control valve position, C1 capacitor position, C2 capacitor position, phase difference between RF applied and RF reflected and matching network error magnitude.

18. A method for determining endpoints in a semiconductor plasma etch process comprising the steps of:

obtaining in situ etch process data signals I₁, I₂, . . . I_m that are representative of real time observations of respective state variables of an observed plasma etch process and forming sets of data input signals based on the observed in situ etch process data signals I₁, I₂, . . . I_m;

transforming each set of input data signals to a set of output data signals based on an orthogonal polynomial transform function, wherein the in situ process data signals I₁, I₂, . . . I_m are coefficients in evaluating the polynomial transform function thereby generating a sequence of sets of output data signals; and

integrating the resulting polynomial transform function to determine an area as a function of time; and

evaluating the determined area at selected time intervals to identify process endpoints.

21. A method for determining endpoints in a semiconductor etch process comprising the steps of:

obtaining in situ etch process data signals I₁, I₂, . . . I_m that are representative of real time observations of respective state variables of an observed plasma etch process and forming sets of data input signals based on the observed in situ etch process data signals I₁, I₂, . . . I_m;

transforming each set of input data signals to a set of output data signals based on an orthogonal polynomial transform function wherein the in situ etch process data signals are used as coefficients in evaluating polynomial transform functions, thereby generating a sequence of sets of output data signals;

integrating the resulting polynomial transform function to determine a scalar as a function of time; and

displaying a graph of scalar values as a function of time to determine a plasma etch endpoint in time.

22. A method according to claim 21 wherein the etch point is identified by a change in magnitude of the scalar values.

23. A system for processing a sequence of m-dimensional input data signals, m≧

2, the system comprising;

a data processor for transforming each m-dimensional input data signal to a set of output data signals based on an orthogonal polynomial transform function, wherein the input data signals are used as coefficients in evaluating the polynomial transform functions, said data processor also integrating within the defined limits of the transform function to determine a scalar value as a function of time; and

a display system for displaying a graph of the scalar values as a function of time.

24. A system according to claim 23 wherein the multi-dimensional input data signals each represent the state of a monitored process at a particular time, and the displayed graph represents a data visualization of the state of the monitored process at discrete times.

25. A system according to claim 23 wherein the multi-dimensional input data signals each comprise I₁, I₂, . . . I_m data signals that reflect real time observations of respective state variables of the observed process.

26. A system according to claim 25 wherein the state variables represent intensity values of measured variables selected from the group comprising optical emission spectrum wavelengths that are monitored in the plasma etching process, reflected RF power, dc bias, upper electrode temperature, lower electrode temperature, wall temperature, electrostatic chuck voltage, electrostatic chuck current, adaptive pressure control valve position, C1 capacitor position, C2 capacitor position, phase difference between RF applied and RF reflected and matching network error magnitude.

27. A system according to claim 23 wherein the transform function comprises an adaptive algorithm.

28. A system according to claim 27 wherein the adaptive algorithm weights the input data signals as a function of likelihood of indicating an endpoint.