Apparatus and method for detecting defects on silicon dies on a silicon wafer

• US 5,943,551 A
• Filed: 09/04/1997
• Issued: 08/24/1999
• Est. Priority Date: 09/04/1997
• Status: Expired due to Term

• Current Assignee: Texas Instruments, Inc.
• Original Assignee: Texas Instruments, Inc.
• Inventors: Thorne, Richard, Schemmel, Floyd
• Primary Examiner(s): Picardat, Kevin M.
• Assistant Examiner(s): COLLINS, DEVEN M
• Application Number:
  US08/923,578
• Time in Patent Office: 719 Days
• Field of Search: 438/14, 438/16, 438/460
• US Class Current: 438/14
• CPC Class Codes: G01R 31/2831 Testing of materials or semi-finished products, e.g. semiconductor wafers or substrates G01R31/318511 takes precedence; testing during manufacture H01L22/00
• CPC Class Codes: G01R 31/318505 Test of Modular systems, e.g. Wafers, MCM's
• CPC Class Codes: G01R 31/318511 Wafer Test
• CPC Class Codes: H01L 22/12 for structural parameters, e.g. thickness, line width, refractive index, temperature, warp, bond strength, defects, optical inspection, electrical measurement of structural dimensions, metallurgic measurement of diffusions electrical measurement of diffusions H01L22/14

Abstract

An apparatus and method for detecting defects on silicon dies on a silicon wafer (16) comprising an image acquisition system (10) and a computer (32) that determines a statistical die model by analyzing a random selection of dies (42) within a die matrix (37) and compares the statistical die model to matrices of silicon dies (38) to determine which silicon dies (38) have surface defects, is disclosed.

Claims

1. A method for detecting defects on silicon dies on a silicon wafer comprising the steps of:

obtaining images of a sample of die matrices on said silicon wafer using an image acquisition system;

calculating a statistical die model from said sample of die matrices;

obtaining an analysis image of a die matrix on said silicon wafer using an image acquisition system

comparing said statistical die model to said analysis image; and

determining whether said silicon dies within said analysis image have surface defects.

2. The method as recited in claim 1 further comprising the step of compiling a list of results from the comparison of said statistical die model with said analysis image.

3. The method as recited in claim 2 further comprising the step of compiling a list of defective silicon dies.

4. The method as recited in claim 3 wherein the step of compiling a list of defective silicon dies further comprises displaying said list of defective dies on a display unit.

5. The method as recited in claim 3 further comprises the step of printing said list of defective silicon dies.

6. A method for detecting defects on a silicon die on a silicon wafer comprising the steps of:

capturing an image of said silicon die;

converting said image into pixels;

separating said pixels into neighborhoods;

averaging said pixels within each of said neighborhoods to obtain a first average pixel value for each of said neighborhoods;

obtaining a second average pixel value for each of said neighborhoods from a standardized die image; and

comparing said first average pixel value with said second average pixel value to determine whether said silicon die has surface defects.

7. The method of claim 6 wherein said neighborhoods further include a square matrix of pixels.

8. The method of claim 6 wherein said neighborhoods further include a rectangular matrix of pixels.

9. The method of claim 6 wherein said neighborhoods further include a circular pattern of pixels.

10. The method of claim 6 wherein each of said neighborhoods overlap adjacent neighborhoods.

11. The method of claim 6 wherein each of said neighborhoods further includes a nine by nine matrix of pixels.