Steven Mitchell Simmons
Architects in Boise, ID
License number
Utah 5181372-0301
Issued Date
Sep 4, 2002
Expiration Date
May 31, 2016
Category
Architect
Type
Architect
Address
Address
Boise, ID
Professional information
Yield Based, In-Line Defect Sampling Method
US Patent:
6613590, Sep 2, 2003
Filed:
May 2, 2001
Appl. No.:
09/847708
Inventors:
Steven J. Simmons - Boise ID
Assignee:
Micron Technology, Inc. - Boise ID
International Classification:
H01L 2100
US Classification:
438 14, 438 4, 438 7
Abstract:
A test method provides a sample of wafer level defects most likely to cause yield loss on a semiconductor wafer subdivided into a plurality of integrated circuits (ICs). Defect size and location data from an inspection tool is manipulated in an algorithm based on defect sizes and geometry parameters. The defects are classified by defect size to form size based populations. The contribution of each size range of defect population to yield loss is calculated and random samples for review are selected from each defect size population. The number of samples from each size defect population is proportional to the predicted yield impact of each sample. The method is rapid and permits on-line process modification to reduce yield losses.
Yield Based, In-Line Defect Sampling Method
US Patent:
6265232, Jul 24, 2001
Filed:
Aug 21, 1998
Appl. No.:
9/138295
Inventors:
Steven J. Simmons - Boise ID
Assignee:
Micron Technology, Inc. - Boise ID
International Classification:
G01R 3126, H01L 2166
US Classification:
438 14
Abstract:
A test method provides a sample of wafer level defects most likely to cause yield loss on a semiconductor wafer subdivided into a plurality of integrated circuits (IC's). Defect size and location data from an inspection tool is manipulated in an algorithm based on defect sizes and geometry parameters. The defects are classified by defect size to form size based populations The contribution of each size range of defect population to yield loss is calculated and random samples for review are selected from each defect size population. The number of samples from each size defect population is proportional to the predicted yield impact of each sample. The method is rapid and permits on-line process modification to reduce yield losses.
Yield Based, In-Line Defect Sampling Method
US Patent:
6890775, May 10, 2005
Filed:
Aug 29, 2003
Appl. No.:
10/651665
Inventors:
Steven J. Simmons - Boise ID, US
Assignee:
Micron Technology, Inc. - Boise ID
International Classification:
H01L021/00
US Classification:
438 14, 438 4, 438 7, 438701
Abstract:
A test method provides a sample of wafer level defects most likely to cause yield loss on a semiconductor wafer subdivided into a plurality of integrated circuits (ICs). Defect size and location data from an inspection tool is manipulated in an algorithm based on defect sizes and geometry parameters. The defects are classified by defect size to form size based populations. The contribution of each size range of defect population to yield loss is calculated and random samples for review are selected from each defect size population. The number of samples from each size defect population is proportional to the predicted yield impact of each sample. The method is rapid and permits on-line process modification to reduce yield losses.
Yield Based, In-Line Defect Sampling Method
US Patent:
2005015, Jul 21, 2005
Filed:
Feb 9, 2005
Appl. No.:
11/054266
Inventors:
Steven Simmons - Boise ID, US
International Classification:
H01L021/66
US Classification:
438014000
Abstract:
A test method provides a sample of wafer level defects most likely to cause yield loss on a semiconductor wafer subdivided into a plurality of integrated circuits (ICs). Defect size and location data from an inspection tool is manipulated in an algorithm based on defect sizes and geometry parameters. The defects are classified by defect size to form size based populations. The contribution of each size range of defect population to yield loss is calculated and random samples for review are selected from each defect size population. The number of samples from each size defect population is proportional to the predicted yield impact of each sample. The method is rapid and permits on-line process modification to reduce yield losses.