IP Library › Granted Patent US 11,024,022
Granted Patent B2
US 11,024,022 · App. 16/376,107 · Granted Jun 1, 2021

Data generation method and data generation device

Inventors: Yuhei Umeda (Kawasaki, JP); Tsutomu Ishida (Kawasaki, JP)
Assignee: FUJITSU LIMITED
G06T7/001G01N21/00G06N20/00G06T2207/30148
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,024,022
App. No.
16/376,107
Granted
Jun 1, 2021
Kind
B2
Abstract

A non-transitory computer-readable recording medium storing a program that causes a computer to execute a procedure, the procedure includes generating, for each of a plurality of wafers, extended coordinates including a position on the wafer and a value calculated from a distance from a center of the wafer and a contribution parameter, for each defect on the wafer by using information of a defect position on the wafer, generating a Betti number group by persistent homology processing for a plurality of extended coordinates generated for each of the plurality of wafers generating, for each of the plurality of wafers, a defect pattern image from a plurality of Betti number groups generated for the plurality of values of contribution parameter, and generating machine learning data associating a plurality of defect pattern images generated for the plurality of wafers with determination information associated with the plurality of wafers.

Claims (26)

1. A non-transitory computer-readable recording medium storing a program that causes a computer to execute a procedure, the procedure comprising:

generating, for each of a plurality of wafers, extended coordinates including a position over the wafer and a value calculated from a distance from a center of the wafer and a contribution parameter, for each defect of the wafer by using information of a defect position over the wafer;

generating a Betti number group by persistent homology processing for a plurality of extended coordinates generated for each of the plurality of wafers;

generating, for each of the plurality of wafers, a defect pattern image from a plurality of Betti number groups generated for the plurality of values of contribution parameter; and

generating machine learning data associating a plurality of defect pattern images generated for the plurality of wafers with determination information associated with the plurality of wafers.

2. The non-transitory computer-readable recording medium according to claim 1 ,

wherein the procedure generates the defect pattern image by combining the plurality of Betti number groups in order of the value of the contribution parameter.

3. The non-transitory computer-readable recording medium according to claim 1 ,

wherein the procedure generates the Betti number group by coupling time series data of the Betti number of each dimension generated by persistent homology processing for the generated plurality of extended coordinates.

4. The non-transitory computer-readable recording medium according to claim 1 ,

wherein the value representing the position over the wafer includes a value of a first axis and a value of a second axis orthogonal to the first axis, and

wherein a value calculated from the distance from the center and the value of the contribution parameter is a value obtained by multiplying a value representing the distance from the center by the value of the contribution parameter, and is also a value of a third axis orthogonal to the first and second axes.

5. The non-transitory computer-readable recording medium according to claim 1 ,

wherein the determination information is a label.

6. A data generation method comprising:

generating, for each of a plurality of wafers, extended coordinates including a position over the wafer and a value calculated from a distance from a center of the wafer and a contribution parameter, for each defect of the wafer by using information of a defect position over the wafer;

generating a Betti number group by persistent homology processing for a plurality of extended coordinates generated for each of the plurality of wafers;

generating, for each of the plurality of wafers, a defect pattern image from a plurality of Betti number groups generated for the plurality of values of contribution parameter; and

generating machine learning data associating a plurality of defect pattern images generated for the plurality of wafers with determination information associated with the plurality of wafers, by a processor.

7. A data generation device comprising:

a memory; and

a processor coupled to the memory and the processor configured to:

generate, for each of a plurality of wafers, extended coordinates including a position over the wafer and a value calculated from a distance from a center of the wafer and a contribution parameter, for each defect of the wafer by using information of a defect position over the wafer;

generate a Betti number group by persistent homology processing for a plurality of extended coordinates generated for each of the plurality of wafers;

generate, for each of the plurality of wafers, a defect pattern image from a plurality of Betti number groups generated for the plurality of values of contribution parameter; and

generate machine learning data associating a plurality of defect pattern images generated for the plurality of wafers with determination information associated with the plurality of wafers.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 5, 2019
From: UMEDA, YUHEI; ISHIDA, TSUTOMU
To: FUJITSU LIMITED
Reel/Frame 048813/0624 →
Priority Claims (1)
JP JP2017-040326 · Mar 3, 2017 · national
Continuity (2)
Continuation PCTJP2018004180 · Feb 7, 2018
Related Publication 20190228516A1 · Jul 25, 2019
Cited By (1)
US 12,633,391