AUTOMATED MODEL BUILDING AND BATCH MODEL BUILDING FOR A MANUFACTURING PROCESS, PROCESS MONITORING, AND FAULT DETECTION

• US 20100057237A1
• Filed: 09/02/2008
• Published: 03/04/2010
• Est. Priority Date: 09/02/2008
• Status: Active Grant

• Current Assignee: MKS Instruments AB (Sartorius AG)
• Original Assignee: MKS Instruments Incorporated
• Inventors: KETTANEH, Nouna, WOLD, Svante Bjarne
• Granted Patent: US 8,494,798 B2
• Time in Patent Office: Days
• US Class Current: 700/103
• CPC Class Codes: G05B 19/41885 characterised by modeling, simulation of the manufacturing system
• CPC Class Codes: G05B 2219/32075 Predict workpiece measurements from measurements of previous workpieces
• CPC Class Codes: G05B 2219/32076 Adjust feedback from previous processes as function of elapsed time
• CPC Class Codes: G05B 2219/45031 Manufacturing semiconductor wafers

Abstract

A method for creating a new model of a manufacturing process according to a multivariate analysis including selecting a set of data representative of multidimensional data measured during a step or phase of a manufacturing process. The method also includes determining a set of model generation conditions based on the set of data and generating the new model specifying intervals for the multidimensional data measured during a future manufacturing process based on the set of model generation conditions.

Claims

1. A method for creating a new model of a manufacturing process according to a multivariate analysis, the method comprising:

selecting a set of data representative of multidimensional data measured during a step or phase of a manufacturing process;

determining a set of model generation conditions based on the set of data; and

generating the new model specifying intervals for the multidimensional data measured during a future manufacturing process based on the set of model generation conditions.

2. The method of claim 1, further comprising:

associating a set identifier or batch ID with the set of data and a step identifier or phase ID with the step of the manufacturing process during which the set of data was measured; and

associating a time variable or a maturity variable with the set of data.

3. The method of claim 1, further comprising excluding data not to be used during generation of the new model.

4. The method of claim 3, wherein excluding data comprises removing outliers from the set of data before the new model is generated.

5. The method of claim 3, wherein the excluded data exceed threshold parameters based on statistical calculations.

6. The method of claim 5, wherein the statistical calculation comprises at least one of a multivariate principal component analysis or partial least squares analysis.

7. The method of claim 6, wherein the multivariate principal component analysis or partial least squares analysis analysis includes a Hotelling T²-type calculation, a DModX calculation, or a combination thereof.

8. The method of claim 1, wherein the set of data includes raw data from one or more tools or data from an existing model.

9. The method of claim 1, wherein selecting further comprises importing raw data from one or more process tools or importing data from a previously-generated model.

10. The method of claim 9, further comprising scaling and centering of the imported data based on a unit variance or other statistical calculation.

11. The method of claim 9, wherein the imported data are adjusted according to a user-specified set of scaling and centering values before generation of the new model.

12. The method of claim 1, wherein the model generation conditions comprise included variables, excluded variables, included process steps, excluded process steps, maturity variables, time variables, or any combination thereof.

13. The method of claim 12, wherein at least one of the maturity variables are smoothed or linearized, or the time variables are normalized or both.

14. The method of claim 1, wherein the measured multidimensional data satisfying a threshold condition triggers generating the new model.

15. The method of claim 14, wherein the threshold condition is satisfied when a multivariate analysis of the multidimensional data results in a value that exceeds a threshold value.

16. The method of claim 15, wherein the multivariate analysis involves a Hotelling T²-type calculation, a DModX-type calculation, a weighted moving average-type calculation, or a multivariate control chart calculation, any of which are derived from a principal component analysis or a partial least squares analysis.

17. A system for generating data structures indicative of conditions of a manufacturing process or current quality of output of a manufacturing process, the system comprising:

a data supply module for communication with a set of manufacturing tools used for the manufacturing process and for communication with a memory including one or more previously-generated data structures;

a data management module in communication with the data supply module, for receiving data about the manufacturing process from the data supply module and for filtering or scaling the received data; and

a model generation module in communication with the data management module or data supply module for generating a model including a set of data associated with the manufacturing process based on the data and a set of user-specified conditions.

18. The system of claim 17, further comprising a model specification module in communication with the model generation module and a user interface, the model specification module responsive to user-generated specifications for generating the model.

19. The system of claim 17, further comprising an outlier removal module in communication with the model generation module and a user interface, the outlier removal module responsive to user-selected specifications for removing outlier data from the model.

20. A system for creating or updating a model according to a multivariate analysis, the system comprising:

a user interface including;

(a) a first window allowing a user to select raw data or data from a previously-generated model to be used to generate a new model;

(b) a second window allowing a user to determine model generation specifications including data to be included in the generated model and data to be excluded from the generated model;

(c) an area for displaying the data to be used to generate the model; and

(d) a user-responsive command portion to provide an instruction to a model generation module upon selection by the user for generating the model; and

a memory for storing the generated model.

21. The system of claim 20, further comprising a third window including a user-configurable spreadsheet portion to specify scaling, centering, or pre-processing values, procedures, or transformations for applying to the data before the model is generated.