System and method for detecting defects on a wafer and related non-transitory computer-readable medium
A system configured to detect defects on a wafer is provided. The system includes an inspection subsystem configured to acquire scan data of a target region on the wafer. The target region comprises a plurality of circuit layout streaming data on the wafer and the defects in proximity to the circuit layout streaming data or in the circuit layout streaming data. A graphic design subsystem (GDS) is configured to store a map of circuit layout streaming data of the wafer. A software tool for designing electronic systems is configured to label the scan data with attributes from the map of circuit layout streaming data. A decision subsystem is configured to qualify the process based on a predetermined defect level from the labeled scan data by using a multi-dimension clustering method, wherein the predetermined defect level is an accumulated defect formed on the semiconductor wafer during processing.
1 . A system configured to qualify a semiconductor wafer process, comprising:
an inspection subsystem configured to acquire scan data of a target region on a semiconductor wafer, wherein the target region comprises circuit layout streaming data on the semiconductor wafer and a plurality of defects in proximity to the circuit layout streaming data or in the circuit layout streaming data;
a graphic design subsystem (GDS) configured to store a map of the circuit layout streaming data of the semiconductor wafer;
a software tool for designing electronic systems configured to label the scan data with attributes from the map of the circuit layout streaming data; and
a decision subsystem configured to qualify the semiconductor wafer process based on a predetermined defect level from the labeled scan data by using a multi-dimension clustering method, wherein the predetermined defect level is an accumulated defect formed on the semiconductor wafer during processing,
wherein the decision subsystem is configured to group a plurality of entries of the scan data into entry groups through the multi-dimension clustering method,
wherein the decision subsystem is configured to expand each entry group based on grey levels of the scan data and determine entries out of a deviation range as the defects, and wherein the decision subsystem is configured to apply different types of gains to different entry groups and filter different entry groups by different types of filters.
2 . The system of claim 1 , wherein the scan data is based on an electron beam inspection (EBI) image, and the EBI image includes the circuit layout streaming data and the defects.
3 . The system of claim 1 , wherein the circuit layout streaming data comprises vias and metal lines.
4 . The system of claim 1 , wherein the attributes comprise a length of a via, a width of the via, and a distance between the via and an adjacent via.
5 . The system of claim 1 , wherein the attributes comprise a pattern density of a metal line, a connection type between the metal line and a via underlying the metal line, and a connection type between the metal line and a second metal line underlying the metal line.
6 . The system of claim 1 , wherein the scan data and the map of the circuit layout streaming data are correlated to determine the target region on the semiconductor wafer.
7 . The system of claim 6 , wherein the scan data is labeled with a first attribute subset, wherein the first attribute subset is selected from a portion of the map of the circuit layout streaming data based on a correlation between the scan data and the map of the circuit layout streaming data.
8 . The system of claim 1 , wherein the multi-dimension clustering method comprises a clustering algorithm including one of K-Means, Mean-Shift, DBSCAN, OPTICS, or HDBSCAN.
9 . The system of claim 8 , wherein the decision subsystem is configured to determine outliers of each entry group as the defects.
10 . The system of claim 1 , wherein the multi-dimension clustering method comprises extending the labeled scan data to a multi-dimensional space based on the corresponding attributes and wherein data points of the scan data in the multi-dimensional space are grouped on a projected plane.
11 . The system of claim 1 , wherein the defects further comprise defects of an EUV (Extreme ultraviolent lithography) process, defects of an epitaxy, defects of misalignment, or Nanosheet or gate-all-around (GAA) specific defects.
12 . A system configured to qualify a semiconductor wafer process, comprising:
an inspection subsystem, configured to acquire scan data of a target region on a semiconductor wafer, wherein the target region comprises circuit layout streaming data on the semiconductor wafer and a plurality of defects in proximity to the circuit layout streaming data or in the circuit layout streaming data;
a graphic design subsystem (GDS), configured to store a map of the circuit layout streaming data of the semiconductor wafer;
a software tool, configured to label the scan data with attributes from the feature map of the circuit layout streaming data; and
a decision subsystem, configured to determine a process healthiness from the labeled scan data by using a multi-dimension clustering method and a predetermined value,
wherein the decision subsystem is configured to group a plurality of entries of the scan data into entry groups through the multi-dimension clustering method,
wherein the decision subsystem is configured to expand each entry group based on grey levels of the scan data and determine entries out of a deviation range as the defects, and wherein the decision subsystem is configured to apply different types of gains to different entry groups and filter different entry groups by different types of filters.
13 . The system of claim 12 , wherein the circuit layout streaming data comprises vias and metal lines.
14 . The system of claim 12 , wherein the attributes comprise a length of a via, a width of the via, and a distance between the via and an adjacent via.
15 . The system of claim 12 , wherein the scan data and the map of circuit layout streaming data are correlated to determine the target region on the wafer.
16 . The system of claim 12 , wherein the labeled circuit layout streaming data are generated based on a calibrated first image and calibrated second images obtained from the circuit layout streaming data and the defects.
17 . The system of claim 12 , wherein the decision subsystem is configured to group a plurality of entries of the scan data into entry groups through the multi-dimension clustering method, and determine outliers of each entry group as the defects.
18 . The system of claim 12 , wherein the multi-dimension clustering method comprises extending the labeled scan data to a multi-dimensional space based on the corresponding attributes and wherein data points of the scan data in the multi-dimensional space are grouped on a projected plane.
19 . A system configured to qualify a semiconductor wafer process, comprising:
an inspection subsystem, configured to acquire scan data of a target region on a semiconductor wafer, wherein the target region comprises circuit layout streaming data on the semiconductor wafer and a plurality of defects in proximity to the circuit layout streaming data or in the circuit layout streaming data;
a graphic design subsystem (GDS), configured to store a layout feature map of the circuit layout streaming data of the semiconductor wafer;
a software tool, configured to label the scan data with attributes from the feature map of the circuit layout streaming data; and
a decision subsystem, configured to determine the plurality of defects from the labeled scan data using a multi-dimension clustering method,
wherein the decision subsystem is configured to group a plurality of entries of the scan data into entry groups through the multi-dimension clustering method,
wherein the decision subsystem is configured to expand each entry group based on grey levels of the scan data and determine entries out of a deviation range as the defects, and wherein the decision subsystem is configured to apply different types of gains to different entry groups and filter different entry groups by different types of filters.
20 . The system of claim 19 , wherein the scan data is based on an electron beam inspection (EBI) image, and the EBI image includes the circuit layout streaming data and the defects.