FAB YIELD ENHANCEMENT SYSTEM

• US 20010051836A1
• Filed: 05/11/1998
• Published: 12/13/2001
• Est. Priority Date: 05/11/1998
• Status: Active Grant

• Current Assignee: Applied Materials Incorporated
• Original Assignee: Applied Materials Incorporated
• Inventors: MAIMON, AMOTZ, YARON, GAD, LAMEY, PATRICK H. Jr.
• Granted Patent: US 6,408,219 B2
• Time in Patent Office: Days
• US Class Current: 700/110
• CPC Class Codes: H01L 22/20 Sequence of activities consisting of a plurality of measurements, corrections, marking or sorting steps

Abstract

A yield enhancement system organizes defect classification and attribute information into a global classification scheme. The global classes are used to identify defect sources and to generate inspection and review plans. The system accumulates defect information in a database and continually refines the information to improve the accuracy of the classification assignments and the identification of the defect sources.

Claims

1. In a semiconductor fabrication plant, a defect classification method comprising the steps of:

receiving, from a wafer analysis tool, classification data associated with a defect;

receiving, from a wafer analysis tool, defect attribute data associated with the defect; and

assigning, based on the classification data and the defect attribute data, a global classification to the defect.

2. The method of

claim 1

wherein the assigning step further comprises the step of comparing at least one attribute of the global classification with yield data from the fabrication plant.

3. The method of

claim 1

wherein the assigning step further comprises the step of comparing the defect attribute data with attribute data stored in a database.

4. The method of

claim 1

further comprising the step of assigning, based on empirical defect data, a confidence level to the global classification.

5. The method of

claim 1

wherein the assigning step further comprises the step of comparing an attribute of the global classification with spatial signature analysis data associated with the defect.

6. The method of

claim 1

further comprising the step of identifying, based on the global classification, at least one suggested source of the defect.

7. The method of

claim 1

further comprising the step of generating update data for at least one of a wafer inspection plan and a wafer review plan.

8. The method of

claim 1

further comprising the step of generating corrective action data for a wafer process tool.

9. The method of

claim 1

further comprising the step of initiating a verification operation for a wafer process tool.

10. An automatic yield enhancement system for a semiconductor fabrication plant, comprising:

a global automatic defect classification module receiving defect classification data from at least one of inspection and review tools, and generating therefrom a global defect classification;

a defect reference database storing characteristics of various wafer defects; and

a defect source identification module receiving the global defect classification and data from the defect reference data base and determining therefrom defect identification data and defect source data.

11. The automatic yield enhancement system of

claim 10

, further comprising a learning module receiving the defect identification data and based thereupon adjusting operation parameters of the global automatic defect classification module.

12. The automatic yield enhancement system of

claim 10

, further comprising a learning module receiving the global defect classification and sending update information to at least one of the inspection and review tools.

13. The automatic yield enhancement system of

claim 10

, further comprising a corrective action module receiving data from at least one of the global automatic defect classification module, the defect reference database, and the defect source identification module, and providing a check list of proposed investigative and corrective actions to be taken for reducing identified defects.

14. The automatic yield enhancement system of

claim 10

, further comprising an equipment operation parameters module receiving the defect source data and based thereupon sending a self diagnostic instruction to the fabrication plant'"'"'s processing equipment.

15. The automatic yield enhancement system of

claim 10

, further comprising a sampling module receiving data from the inspection tool and the defect reference database and, based thereupon, generating a defect review sampling plan.

16. receiving defect attributes and classification data from inspection and review tools, and performing the following operations:

for each defect examining whether the classification of the inspection and review tools are the same and, if so, issuing the classification as the global classification;

when the classification of the inspection and review tools is different, examining the defect attributes data to determine global classification for the defect;

when the attributes and classification data do not lead to a predefined certainty in defect classification, searching a defect database to determine a global classification for the defect;

when necessary, based on the global classification, sending a signal to one of the inspection and review tool to adjust classification parameters.

17. A method of identifying a source of a wafer defect in a semiconductor fabrication plant, the method comprising the steps of:

receiving defect classification data from a wafer analysis tool;

generating a global defect classification;

storing characteristics of various wafer defects in a database; and

determining defect identification and defect source data from the global defect classification.