Method and apparatus for inspecting defects in a semiconductor wafer

• US 6,792,366 B2
• Filed: 12/11/2001
• Issued: 09/14/2004
• Est. Priority Date: 12/11/2001
• Status: Expired due to Fees

• Current Assignee: Hitachi, Ltd.
• Original Assignee: Hitachi, Ltd.
• Inventors: Shibuya, Hisae, Obara, Kenji, Hosoya, Naoki, Takagi, Yuuji
• Primary Examiner(s): PERT, EVAN T
• Application Number:
  US10/015,276
• Publication Number:
  US 20030109070A1
• Time in Patent Office: 1,008 Days
• Field of Search: 702/81-84, 438/14-18, 700/108-110, 700/121, 382/145, 382/149, 324/765
• US Class Current: 702/83
• CPC Class Codes: G06T 2200/24 involving graphical user interfaces [GUIs]
• CPC Class Codes: G06T 2207/30148 Semiconductor; IC; Wafer
• CPC Class Codes: G06T 7/0002 Inspection of images, e.g. flaw detection
• CPC Class Codes: G06T 7/0004 Industrial image inspection
• CPC Class Codes: G06T 7/41 based on statistical description of texture
• CPC Class Codes: H01L 22/20 Sequence of activities consisting of a plurality of measurements, corrections, marking or sorting steps

Abstract

In a wafer inspection and sampling system, wafer defects are detected and stored in a data store as defect data. Information is also provided, representative of clusters of defects on the wafer. A statistically based sampling of the defects is made to obtain a set of sampled defects. Subsequent detailed inspection and analysis of the sampled defects produces additional data which facilitate an understanding of process errors.

Claims

1. A method for inspecting a semiconductor wafer comprising:

receiving defect information representative of a plurality of defects on a semiconductor wafer;

taking a statistically-based sampling of said plurality of defects to produce a plurality of N sampled defects, N being a sample number; and

performing an inspection of each of said N sampled defects to produce summary information representative of results of said inspection of each of said N sampled defects.

2. The method of claim 1 further including receiving user-provided information comprising one or more statistical criteria, wherein said sample number N is a computed number resulting from one or more computations made based on said statistical criteria.

3. The method of claim 1 further including receiving user-provided information comprising one or more statistical criteria, wherein said sample number is produced by a table look-up of one or more data tables.

4. The method of claim 1 further including receiving user-provided information comprising one or more statistical criteria, wherein said sample number is produced by a combination of one or more computations made based on said statistical criteria and a table look-up of one or more data tables.

5. The method of claim 1 wherein said one or more statistical criteria comprise a reliability value and an allowable error value and said step of taking a statistically-based sampling includes randomly sampling N defects from said plurality of defects.

6. The method of claim 1 wherein said one or more statistical criteria comprise a reliability value and a dominant defect percentage value and said step of taking a statistically-based sampling includes randomly sampling N defects from said plurality of defects.

7. The method of claim 1 wherein said defect information is further representative of one or more clusters of said defects, said user-provided information further being representative of one of said one or more clusters, said step of sampling taking a statistically-based being performed on said one of said one or more clusters.

8. The method of claim 7 wherein said one or more clusters of said defects are classified based on density of detects.

9. The method of claim 1 wherein said step of receiving defect information includes performing a first inspection of said semiconductor wafer, said first inspection identifying the presence of a defect.

10. The method of claim 1 wherein said summary information includes first information indicative of clusters of said defects on said semiconductor wafer, second information indicative of a dominant defect in each of said clusters, and third information indicative of a distribution of different kinds of defects in each of said clusters, said method further including presenting said first information, one or more portions of said second information, and one or more portions of said third information.