System and method for analyzing semiconductor production data

• US 6,233,719 B1
• Filed: 10/27/1997
• Issued: 05/15/2001
• Est. Priority Date: 10/27/1997
• Status: Expired due to Term

• Current Assignee: KLA-Tencor Corporation
• Original Assignee: KLA-Tencor Corporation
• Inventors: Kulkarni, Ashok, Zhou, Steve, Hardikar, Manoj, Shiflett, Richard
• Primary Examiner(s): Smith, Matthew
• Assistant Examiner(s): Siek, Vuthe
• Application Number:
  US08/958,288
• Time in Patent Office: 1,296 Days
• Field of Search: 364/488, 364/489, 364/490, 364/491, 716/1, 707/1, 707/103, 707/503, 345/333, 345/334, 345/348
• US Class Current: 700/110
• CPC Class Codes: G06F 16/906 Clustering; Classification
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: Y10S 707/99931 Database or file accessing

Abstract

A software system and method is disclosed for extending classification attributes in the analysis of production data. The software operates in an object-oriented Windows® environment with increased flexibility because it permits the user to add classifications by dragging and dropping with a computer mouse. Thus, the system can be changed without reprogramming the software code, and is not limited by preprogrammed classifications. The classifications are preferably cluster classifications of defects in semiconductor processing such as scratches, particles, pinholes and blowouts. When a cluster classification is executed, a production map is filtered to remove the non-defect data according to the selected classification; the defect attribute is then readily visible. The filtered production maps may also be color coded for better visibility so that a plurality of corresponding defects in the map are visible in a plurality of corresponding colors. The maps of a plurality of cluster classifications also may be placed side by side for comparison.

Claims

1. A method of analyzing semiconductor production data from a production line, comprising the steps of:

establishing a table namespace of old semiconductor cluster classifications having first attributes;

selecting from a list box a new semiconductor cluster classification having second attributes;

adding said selected new cluster classification to said table namespace;

choosing said new semiconductor cluster classification from said table namespace;

executing an analytical routine on said production data from said new semiconductor cluster classification with said second attributes;

choosing a plurality of filters associated with said old and new semiconductor cluster classifications;

applying said plurality of filters to said semiconductor production data in sequence;

removing non-defect semiconductor product data from said semiconductor production data;

color coding each of said semiconductor cluster classifications so that said classifications can be more easily distinguished; and

if results of the executed analytical routine exceed a predetermined control level, sending a command to the production line to initiate a process change.

2. The method of claim 1, said executing step further comprising at least one of:

importing a namespace containing said second attributes for said new semiconductor cluster classification;

performing a pattern recognition function for said new semiconductor cluster classification; and

generating a graphical representation of said results of said analytical routine on said new semiconductor cluster classifications with said second attributes.

3. The method of claim 2, said importing step further comprising:

importing said namespace across the Internet or a local network.

4. The method of claim 1, further comprising;

displaying a plurality of graphical representations of said old and new semiconductor cluster classifications side by side.

5. The method of claim 1, wherein:

said executing of said analytical routine includes generating information about said new semiconductor cluster classifications of defects.

6. The method of claim 5, wherein:

said generating of information about said semiconductor cluster classifications of defects includes generating information about scratches, particles, pinholes and blowouts.

7. The method of claim 1, further comprising the step of:

importing said new semiconductor cluster classifications across a server.

8. The method of claim 1, further comprising the step of:

importing said new semiconductor cluster classification across the Internet.

9. A system for analyzing semiconductor production data from a production line, comprising:

a table namespace of old semiconductor cluster classifications having first attributes;

a list box containing a plurality of new semiconductor cluster classifications having second attributes;

a first analytical routine for execution on said production data from at least one of said old and new semiconductor cluster classifications with said first attributes and second attributes, respectively; and

a second analytical routine for applying a plurality of filters, associated with said old and new classifications, to said semiconductor production data in sequence, removing non-defect semiconductor production data from said semiconductor production data, and color coding each of said semiconductor cluster classifications so that said classifications are more easily distinguishable, and sending a command to the production line to initiate a process change if results of the second analytical routine exceed a predetermined control level.

10. The system of claim 9, said analytical routine further comprises at least one of:

an importation of a namespace having said second attributes for said new semiconductor cluster classification;

a pattern recognition function for said new semiconductor cluster classification; and

a graphical representation of results of said analytical routine on said old and new semiconductor cluster classifications.

11. The system of claim 10, wherein:

said namespace is imported over the Internet or a local network.

12. The system of claim 9, wherein:

said analytical routine is one of a number, mean, or standard deviation of defects over a particular lot identification, layer number or time period.

13. The system of claim 9, further comprising:

a plurality of graphical representations of said old and new semiconductor cluster classifications displayed side by side.

14. The system of claim 9, wherein:

said analytical routine generates information about semiconductor cluster classifications of defects.

15. The system of claim 14, wherein:

said semiconductor cluster classifications of defects include scratches, particles, pinholes and blowouts.

16. A system for analyzing semiconductor production data from a production line, comprising:

table namespace means for storing and displaying old semiconductor cluster classifications having first attributes;

list box means for storing and displaying a plurality of new semiconductor cluster classifications having second attributes;

first analytical routine means for execution on said semiconductor production data from at least one of said old and new semiconductor cluster classifications with said first attributes and second attributes respectively;

second analytical routine means for applying a plurality of filters, associated with at least one of said old and new semiconductor cluster classifications, to said semiconductor production data in sequence;

means for removing non-defect semiconductor production data from said semiconductor production data;

means for color coding each of said semiconductor cluster classifications so that said classifications can be more easily distinguished; and

means for sending a command to the production line to initiate a process change if results of the second analytical routine exceed a predetermined control level.

17. The system of claim 16, said analytical routine further comprises at least one of:

means for importing a namespace having said second attributes for said new semiconductor cluster classification;

means for performing pattern recognition for said new semiconductor cluster classification; and

means for graphically representing results of said analytical routine on said old and new semiconductor cluster classifications.

18. The system of claim 17, wherein:

means for importing said namespace over the Internet or a local network.

19. The system of claim 16, wherein:

said analytical routine means executes an operation of number, mean, or standard deviation of defects over a particular lot identification, layer number or time period.

20. The system of claim 16, further comprising:

means for displaying side by side a plurality of said old and new semiconductor cluster classifications.

21. The system of claim 16, wherein:

said analytical routine means generates information about semiconductor cluster classifications of defects.

22. The system of claim 20, wherein:

said semiconductor cluster classifications of defects include scratches, particles, pinholes and blowouts.

23. The system of claim 16, further comprising:

means for importing said new semiconductor cluster classification across a server.

24. The system of claim 16, further comprising:

means for importing said new semiconductor cluster classification across the Internet.