CN-122016796-A - Edge defect detection method, device, equipment, system and medium

CN122016796ACN 122016796 ACN122016796 ACN 122016796ACN-122016796-A

Abstract

The disclosure provides a method, a device, equipment, a system and a medium for detecting edge defects, wherein the method comprises the steps of scanning an edge of a wafer to be detected to obtain first mode detection data, identifying at least one target area from the first mode detection data, obtaining second mode detection data of the target area, wherein the second mode detection data comprises three-dimensional contour information of the target area, and determining defect classification results of the target area according to the three-dimensional contour information of the target area in the second mode detection data.

Inventors

ZHOU MIAO

Assignees

西安奕斯伟材料科技股份有限公司
西安奕斯伟硅片技术有限公司

Dates

Publication Date: 20260512
Application Date: 20251211

Claims (15)

1. A method for detecting an edge defect, the method comprising: scanning the edge of the wafer to be detected to obtain first mode detection data; identifying at least one target region from the first modality detection data; Acquiring second modality detection data of the target area, wherein the second modality detection data comprises three-dimensional contour information of the target area; And determining a defect classification result of the target area according to the three-dimensional contour information of the target area in the second mode detection data.
2. The detection method according to claim 1, wherein the determining the defect classification result of the target region according to the three-dimensional contour information of the target region in the second modality detection data includes: constructing a reference datum plane of the target area based on the three-dimensional contour information of the target area; Acquiring a height deviation value of each data point in the second mode detection data relative to the reference datum plane; And determining a defect classification result of the target area according to the polarity characteristics of the height deviation value.
3. The inspection method according to claim 2, wherein determining the defect classification result of the target area according to the polarity characteristics of the height deviation value comprises: when the height deviation value of the detected existence data point is a positive value and exceeds a first preset threshold value, judging the defect classification result of the target area as an attachment defect; And when the detected height deviation value of the existing data points is negative and the absolute value exceeds a second preset threshold, judging the defect classification result of the target area as a material-missing type defect.
4. A method according to claim 3, wherein after determining the defect classification result of the target region as a material-missing type defect, the method further comprises: obtaining aspect ratio parameters of defect characteristics in the target area; When the length-width ratio parameter is larger than a third preset threshold value, determining the defect classification result as a crack defect; And when the length-width ratio parameter is smaller than or equal to the third preset threshold value, confirming the defect classification result as a broken edge defect.
5. The method of claim 2, wherein constructing a reference surface of the target region based on the three-dimensional contour information of the target region comprises: identifying normal contour data points corresponding to background areas in the first modality detection data in second modality detection data of the target area; and fitting by using the normal contour data points to generate the reference datum plane.
6. The method of claim 1, wherein the scanning for the edge of the wafer to be measured to obtain the first mode detection data comprises: controlling a rotary table carrying the wafer to be tested to rotate; And in the process of rotating the wafer to be detected, acquiring a continuous image sequence of the edge of the wafer to be detected by utilizing an optical imaging device.
7. The method of claim 6, wherein the acquiring second modality detection data of the target area comprises: In the process of rotating the wafer to be detected, synchronously acquiring three-dimensional point cloud data of the edge of the wafer to be detected by using a laser scanning sensor; And the first mode detection data and the three-dimensional point cloud data are spatially aligned through the angle position information of the rotating table.
8. The method of claim 7, wherein identifying at least one target region from the first modality detection data comprises: comparing the gray value of each pixel point in the first mode detection data with a preset gray threshold value; and marking the area where the pixel point with the gray value exceeding the gray threshold value is located as the target area.
9. The method of claim 1, wherein the second modality detection data includes profile data for one or more cross-sections, each cross-section profile data including depth coordinates and axial coordinates in a sensor coordinate system.
10. A system for detecting edge defects, the system comprising: the rotary bearing table is used for adsorbing and driving the wafer to be tested to rotate; The imaging equipment is configured to acquire first mode detection data aiming at the edge of the wafer to be detected in the rotating process of the wafer to be detected, and the first mode detection data is a two-dimensional optical image; A scanning device configured to scan second modality detection data of the target area, wherein the second modality detection data includes three-dimensional profile information of the target area; Edge defect detection means, communicatively connected to said imaging device and to said scanning device, configured to perform the edge defect detection method steps of any one of claims 1 to 9.
11. The detection system of claim 10, wherein the scanning device is a laser line scanning sensor having a scanning frequency synchronized with an acquisition frequency of the imaging device.
12. The inspection system of claim 10, wherein the imaging device and the scanning device are mounted laterally of the rotating carrier and are field-of-view covered for the same edge region of the wafer under test.
13. An edge defect detection apparatus, characterized in that the detection apparatus comprises: The first acquisition unit is configured to scan the edge of the wafer to be detected and acquire first mode detection data; An identification unit configured to identify at least one target region from the first modality detection data; a second acquisition unit configured to acquire second modality detection data of the target area, wherein the second modality detection data includes three-dimensional profile information of the target area; And the determining unit is configured to determine a defect classification result of the target area according to the three-dimensional contour information of the target area in the second modality detection data.
14. A computing device comprising a processor and a memory, the processor configured to execute instructions stored in the memory to implement the method of edge defect detection as claimed in any one of claims 1 to 9.
15. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the method of edge defect detection according to any one of claims 1 to 9.

Description

Edge defect detection method, device, equipment, system and medium Technical Field The disclosure relates to the technical field of semiconductor manufacturing, and in particular relates to a method, a device, equipment, a system and a medium for detecting edge defects. Background In the semiconductor wafer manufacturing process, especially as process nodes shrink, edge regions (including bevel, vertex and sidewall) of the wafer under test become critical areas that affect yield. In the related scheme, the edge defect detection system mainly adopts a high-resolution optical imaging technology, and an abnormal region is identified by acquiring a two-dimensional gray level image. However, in the process of identifying edge defects using optical detection techniques, the edge defect detection system of the related scheme may have a defect misjudgment. For example, defects of attachments such as dust and water stains attached to the wafer surface and defects of material defects such as chipping and cracking show similar low gray values in the two-dimensional gray image. Such similarity can cause the edge defect detection system to erroneously determine that the attached matter defect is a material-missing defect, resulting in that a wafer which can eliminate the attached matter defect by cleaning is determined to be a defective wafer with the material missing, and scrapping or manual re-inspection is performed, thereby reducing the detection efficiency. Disclosure of Invention The disclosure provides a method, a device, equipment, a system and a medium for detecting edge defects, which can reduce the misjudgment rate of defect types and improve the detection efficiency. The technical scheme of the present disclosure is realized as follows: in a first aspect, the present disclosure provides a method for detecting an edge defect, including: scanning the edge of the wafer to be detected to obtain first mode detection data; identifying at least one target region from the first modality detection data; Acquiring second mode detection data of the target area, wherein the second mode detection data comprises three-dimensional contour information of the target area; And determining a defect classification result of the target area according to the three-dimensional contour information of the target area in the second mode detection data. In a second aspect, the present disclosure provides a system for detecting an edge defect, comprising: the rotary bearing table is used for adsorbing and driving the wafer to be tested to rotate; The imaging equipment is configured to acquire first-mode detection data aiming at the edge of the wafer to be detected in the wafer rotating process, and the first-mode detection data is a two-dimensional optical image; A scanning device configured to scan second modality detection data of the target area, wherein the second modality detection data includes three-dimensional profile information of the target area; an edge defect detection device, in communication with the imaging device and the scanning device, configured to perform the edge defect detection method steps of the first aspect. In a third aspect, the present disclosure provides an edge defect detection apparatus, including: The first acquisition unit is configured to scan the edge of the wafer to be detected and acquire first mode detection data; an identification unit configured to identify at least one target region from the first modality detection data; A second acquisition unit configured to acquire second modality detection data of the target area, wherein the second modality detection data includes three-dimensional profile information of the target area; And a determining unit configured to determine a defect classification result of the target region according to the three-dimensional contour information of the target region in the second modality detection data. In a fourth aspect, the present disclosure provides a computing device, including a processor and a memory, the processor configured to execute instructions stored in the memory to implement the method for detecting edge defects according to the first aspect. In a fifth aspect, the present disclosure provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method for detecting edge defects according to the first aspect. The present disclosure provides a method, apparatus, device, system, and medium for detecting edge defects, which introduces three-dimensional contour information as a defect classification basis, and can improve classification accuracy while maintaining higher detection efficiency compared with a scheme using only two-dimensional optical detection. Drawings Fig. 1 is a schematic structural diagram of an edge defect detection system provided in the present disclosure. Fig. 2 is a flow chart of a method for detecting an edge defect according to the present disclosure.