METHOD AND SYSTEM FOR EVALUATING A MACHINE TOOL OPERATING CHARACTERISTICS

• US 20100249976A1
• Filed: 03/31/2009
• Published: 09/30/2010
• Est. Priority Date: 03/31/2009
• Status: Active Grant

• Current Assignee: GlobalFoundries, Inc.
• Original Assignee: International Business Machines Corporation
• Inventors: Singh, Raminderpal, Lin, Hong, Ticknor, Adam Daniel, Slonim, Noam, Tipu, Fateh All, Mackey, Kevin, Aharoni, Ehud, Kei, Ramona, McCormack, Timothy M., Rosen-Zvi, Michal, Baseman, Robert J., Margalit, Oded
• Granted Patent: US 8,285,414 B2
• Time in Patent Office: Days
• US Class Current: 700/110
• CPC Class Codes: G05B 2219/32191 Real time statistical process monitoring
• CPC Class Codes: G05B 2219/32194 Quality prediction
• 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: G05B 23/0216 Human interface functionality, e.g. monitoring system providing help to the user in the selection of tests or in its configuration
• CPC Class Codes: G05B 23/0229 knowledge based, e.g. expert systems; genetic algorithms
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
• CPC Class Codes: Y02P 90/80 Management or planning
• CPC Class Codes: Y10T 409/309408 with cutter holder

Abstract

A method and system for evaluating a performance of a semiconductor manufacturing tool while manufacturing microelectronic devices are disclosed. At least one report is generated based on executions of at least one statistical test. The report includes at least one heat map having rows that correspond to sensors, columns that correspond to trace data obtained during recipe steps, and cells at the intersection of the rows and the columns. At least one sensor in the tool obtains trace data of a recipe step while manufacturing at least one microelectronic device. A computing device analyzes the obtained trace data to determine a level of operational significance found in the data and assigns a score to the trace data that indicates a level of operational significance. Then, the computing device places the score in a corresponding cell of the heat map. A user uses the cell for evaluating the tool performance.

Claims

1. A method for evaluating the performance of a machine tool while manufacturing microelectronic devices comprising:

generating at least one heat map having rows that correspond to sensors implemented in said machine tool, columns that correspond to recipe steps representing a process used to fabricate said microelectronic devices and cells at the intersection of said rows and said columns;

assigning each row of said heat map to a sensor;

assigning each column of said heat map to a recipe step;

using at least one sensor for obtaining trace data of a recipe step while manufacturing at least one microelectronic device;

analyzing the obtained trace data to determine a level of operational interest found in the data;

assigning a score to the trace data that indicates the determined level of operational significance;

associating the score with a corresponding cell of the heat map; and

accessing said score in said cell for evaluating the machine tool performance.

2. The method of claim 1 further comprising:

assigning, in said heat map, a color or shade to the score assigned to the trace data.

3. The method of claim 2 further comprising:

using the colored cell in combination with other similarly obtained colored cells in the heat map for evaluating the machine tool performance.

4. The method of claim 3 wherein said at least one heat map is a plurality of linked heat maps.

5. The method of claim 4 wherein said plurality of linked heat maps comprises:

a first heat map that displays analyses of current data; and

a second heat map that displays analysis of data from a past or reference period.

6. The method of claim 5 further comprising;

a third heat map that displays differences in analysis between said first and second heat maps.

7. The method of claim 1 wherein said cell is linked to one or more of:

a first graph that displays a trend over time of statistics characterizing time series collected while processing said microelectronic devices from all nominally identical processing tools;

a second graph that displays a trend over time of statistics characterizing time series collected while processing said microelectronic devices from a processing tool; and

a third graph that displays time series of histograms statistics from single sensors during single recipe steps for individual microelectronic devices.

8. The method of claim 4 wherein said plurality of linked heat maps comprises:

a first heat map that displays analysis of recent data; and

a second heat map that displays differences in analysis between two time periods;

in combination with

a list of currently implemented individual cell in individual chamber recipe reports that are ordered by the most statistically significant results.

9. The method of claim 1, wherein the score is generated by one or more technique of:

mutual information, descriptive statistics, causal models, classification and regression trees, cost sensitive learning, ridge, lasso, elastic net, correlation coefficient, and T test.

11. The system of claim 17 further comprising:

means for assigning, in said heat map, a color or shade to the score assigned to the trace data.

12. The system of claim 18 further comprising:

means for using the colored cell in combination with other similarly obtained colored cells in the heat map for evaluating the machine tool performance.

15. The system of claim 17 wherein said cell is linked to one or more of:

means for providing a first graph that displays a trend over time of statistics characterizing time series collected while processing said microelectronic devices from all nominally identical processing tools;

means for providing a second graph that displays a trend over time of statistics characterizing time series collected while processing said microelectronic devices from a processing tool; and

means for providing a third graph that displays time series of histograms statistics from single sensors during single recipe steps for individual microelectronic devices

16. The system of claim 17, wherein the score is generated by one or more technique of:

mutual information, descriptive statistics, causal models, classification and regression trees, cost sensitive learning, ridge, lasso, elastic net, correlation coefficient, and T test.

17. A method of deploying a computer program product including programs of instructions in a computer readable medium for evaluating the performance of a machine tool while manufacturing microelectronic devices, wherein, when the programs of instructions are executed by at least one processor, the computer program product performs the steps of claim 1.

18. A computer readable medium embodying computer program instructions being executed by a processor for causing a computer to perform method steps for evaluating the performance of a machine tool while manufacturing microelectronic devices, said method steps comprising the steps of claim 1.

10. A system for evaluating the performance of a machine tool while manufacturing microelectronic devices comprising:

means for generating at least one heat map having rows that correspond to sensors implemented in said machine tool, columns that correspond to trace data obtained during recipe steps representing a process used to fabricate said microelectronic devices and cells at the intersection of said rows and said columns;

means for assigning each row of said heat map to a sensor;

means for assigning each column of said heat map to a recipe step;

means for using at least one sensor for obtaining trace data of a recipe step while manufacturing at least one microelectronic device;

means for analyzing the obtained trace data to determine a level of operational interest found in the data;

means for assigning a score to the trace data that indicates a determined level of operational significance;

means for associating the score with a corresponding cell of the heat map; and

means for accessing said score in said cell for evaluating the machine tool performance.

19. A method suitable for use in a manufacturing environment comprising a multiplicity of nominally identical independent tools, the method comprising the steps of:

configuring a computing device including a processor and a memory to generate a multi dimensional array of process trace data derived from at least one of the independent tools, wherein, said array including data representing a first dimension comprising a list of steps in a manufacturing recipe and data representing a second dimension comprising a list of a set of sensors generating measurements from at least one of the independent tools;

configuring said computing device including said processor and said memory to conduct an analysis on at least one preselected subset of said multi dimensional array for the purpose of evaluating at least one operating characteristic of at least one of the independent tools; and

configuring said computing device including said processor and said memory to present results of the analysis via a set of hierarchically linked and browseable graphics.

13. The system of claim 19 wherein said at least one heat map is a plurality of linked heat maps.

14. The system of claim 20 wherein said plurality of linked heat maps comprises:

means for providing a first heat map that displays analyses of current data; and

means for providing a second heat map that displays analysis of data from a reference period.

20. The method according to claim 19, wherein said multidimensional array further comprises data representing a third dimension comprising a specification of a set of nominally identical tools.

21. The method according to claim 19, wherein said multidimensional array further comprises data representing a third dimension comprising a specification of a time period data for process trace data collection.

22. The method according to claim 19, wherein said analysis comprises a step of conducting at least one statistical test on the process trace data.

23. The method according to claim 19) wherein said multidimensional array further comprises data representing a third dimension comprising a specification of measurements of a product quality or performance.

24. The method according to claim 23, wherein said analysis comprises a step of summarizing the results of multiple individual statistical tests.

25. A computer readable medium embodying computer program instructions being executed by a processor for causing a computer to perform method steps for use in a manufacturing environment comprising a multiplicity of nominally identical independent tools, said method steps comprising the steps of claim 19.