# US 12,118,709 B2 · Method for identifying cause of manufacturing defects

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- Number: US 12,118,709 B2
- Document ID: US12118709B2
- Status: Granted
- Kind: B2
- Application number: 17/678,184
- Filed: 2022-02-23
- Published: 2023-08-24
- Granted: 2024-10-15
- Earliest claimed: 2022-02-23
- Assignees: Nanya Technology Corporation
- Applicants: Nanya Technology Corporation
- Inventors: Ken-Huan Ho
- Web page: https://patentgrep.com/patent/US12118709B2

## CPC

- G06T 7/0004: {Industrial image inspection}
- G06T 7/0006: {using a design-rule based approach}
- G06T 2207/30148: Semiconductor; IC; Wafer
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL

## Abstract

A method for identifying a cause of manufacturing defects is provided. The method includes capturing, by an image capture unit, a number N of images from a semiconductor wafer, wherein each of the s umber N of images comprises a number M of geometric features, calculating, by a processing unit, a geometric center for each of the geometric features of the number N of images, calculating, based on the number N of images, a number M of average geometric centers associated with the number M of geometric features, and calculating a shift amount for each geometric feature of the number N of images.

## Claims

### Claim 1

A method for identifying a cause of manufacturing defects, comprising:
capturing, by an image capture unit, a number N of images from a semiconductor wafer, wherein each of the number N of images comprises a number M of geometric features;
calculating, by a processing unit, a geometric center for each of the geometric features of the number N of images;
calculating, based on the number N of images, a number M of average geometric centers associated with the number M of geometric features; and
calculating a shift amount for each geometric feature of the number N of images based on a difference between the geometric center of a specific geometric feature of the number M of geometric features and the average geometric center associated with the specific geometric feature of the number M of geometric features.

### Claim 2 (depends on 1)

The method of claim 1, wherein each of the number N of images covers different portions of the semiconductor wafer.

### Claim 3 (depends on 1)

The method of claim 1, further comprising:
in response to a shift amount of a specific geometric feature exceeding a first threshold, performing a first coordinate transformation on a first group of geometric features associated with a first manufacturing process.

### Claim 4 (depends on 3)

The method of claim 3, further comprising:
performing a second coordinate transformation on a second group of geometric features associated with a second manufacturing process.

### Claim 5 (depends on 4)

The method of claim 4, wherein the specific geometric feature belongs to the first group of geometric features and the second group of geometric features.

### Claim 6 (depends on 4)

The method of claim 4, further comprising:
comparing a y-coordinate value of the specific geometric feature obtained after the first coordinate transformation with a second threshold, and
comparing a y-coordinate value of the specific geometric feature obtained after the second coordinate transformation with the second threshold.

### Claim 7 (depends on 6)

The method of claim 6, further comprising:
determining that the shift amount of the specific geometric feature is caused by the first manufacturing process or the second manufacturing process based on:
whether the y-coordinate value of the specific geometric feature obtained after the first coordinate transformation exceeds the second threshold; and
whether the y-coordinate value of the specific geometric feature obtained after the second coordinate transformation exceeds the second threshold.

### Claim 8 (depends on 4)

The method of claim 4, wherein the first coordinate transformation is performed according to the following equations:
xT=x×cos θ1−y×sin θ1, and
yT=y×cos θ1+x×sin θ1
wherein
x represents a coordinate value on an x-axis;
y represents a coordinate value on a y-axis;
xT represents a transformed coordinate value on the x-axis;
yT represents a transformed coordinate value on the y-axis; and
θ1 represents an angle between the first group of geometric features and the x-axis.

### Claim 9 (depends on 4)

The method of claim 4, wherein the second coordinate transformation is performed according to the following equations:
xT=x×cos θ2+y×sin θ2, and
yT=y×cos θ2−x×sin θ2
wherein
x represents a coordinate value on an x-axis;
y represents a coordinate value on a y-axis;
xT represents a transformed coordinate value on the x-axis;
yT represents a transformed coordinate value on the y-axis; and
θ2 represents an angle between the second group of geometric features and the x-axis.

### Claim 10 (depends on 1)

The method of claim 1, further comprising building up a coordinate system for the number N of images, wherein
the coordinate system includes an origin of coordinate positioned at the center of each of the number N of images, and
each of the geometric features includes a coordinate value on an x-axis and a coordinate value on a y-axis.