Non-graphic defect identification method

Abstract

The invention provides a non-graphic defect identification method, which comprises the following steps of: 1, scanning a wafer to be detected by a detection system by using an electron beam, and performing gray conversion on an obtained image to obtain a gray-scale map; step 2, finding out a bright spot cluster in the grey-scale map; 3, calculating the intensity and distribution characteristics of the bright spots in the bright spot cluster, and judging whether the defect is a non-graphic defect or not; 4, marking the original image corresponding to the grey-scale map, and transmitting the marked image to a storage system; and 5, confirming an updating result of the storage system. The non-graphic defects are successfully distinguished through image processing, the accuracy rate reaches 90% or above, only a single target picture needs to be shot, the picture does not need to be referred, and the detection time is greatly shortened.

Description

Technical Field

[0001] The present application relates to the field of semiconductor technology, and in particular to a method for identifying non-graphic defects. Background Art

[0002] The semiconductor manufacturing process needs to control the particles, residues, scratches, and COPs left behind in each process. These non-patterning defects are yield killers and are under constant monitoring. The existing standard process for non-patterning defect detection is to capture suspicious points through optical surface detection (surface scan), and then use electronic images (SEM images) to determine whether they are defects. Therefore, a large number of images need to be checked, and the detection is time-consuming and cannot distinguish between non-patterning defects and patterning defects. Summary of the invention

[0003] In view of the above-mentioned shortcomings of the prior art, the purpose of this application is to provide a non-graphic defect identification method to solve the problem that the non-graphic defect detection in the prior art takes a long time and cannot distinguish between non-graphic defects and graphic defects.

[0004] To achieve the above objectives and other related objectives, the present application provides a non-graphic defect recognition method, comprising:

[0005] Step 1: The detection system uses an electron beam to scan the wafer to be detected, and performs grayscale conversion on the obtained image to obtain a grayscale image;

[0006] Step 2: Find the bright spot cluster in the grayscale image;

[0007] Step 3, calculating the density and distribution characteristics of the bright spots in the bright spot cluster to determine whether it is a non-graphic defect;

[0008] Step 4: After marking the original image corresponding to the grayscale image, the marked image is transmitted to the storage system;

[0009] Step 5: Confirm the update result of the storage system.

[0010] Preferably, in step one, the wafer to be inspected is scanned using an electron beam through a scanning electron microscope.

[0011] Preferably, in step three, if the bright spots in the bright spot cluster have the characteristic of being concentratedly distributed along a portion of the edge of a certain graphic, it can be determined as a non-graphic defect.

[0012] Preferably, the pattern has an irregular shape.

[0013] Preferably, in step three, if the bright spots in the bright spot cluster are dispersed along the entire edge of a certain graphic and the size of the graphic does not match the preset target graphic size, it can be determined as a graphic defect.

[0014] Preferably, the pattern has a regular shape.

[0015] Preferably, the shape comprises a rectangle or a regular shape with corners.

[0016] Preferably, the regular shape having a corner includes an L-shape or a T-shape.

[0017] Preferably, in step 4, the label name of the non-graphic defect is determined according to the semiconductor manufacturing process implemented before the defect detection is performed.

[0018] Preferably, in step five, the marked images are classified according to the implementation objects and process conditions of the semiconductor manufacturing process.

[0019] As described above, the non-graphic defect recognition method provided by the present application has the following beneficial effects: non-graphic defects can be successfully distinguished through image processing with an accuracy rate of more than 90%, and only a single target image needs to be taken without reference images, which greatly reduces the detection time. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1A A comparison diagram showing a target image and a reference image used by an existing non-pattern defect recognition method;

[0022] Figure 1B A schematic diagram showing that a large number of secondary electrons are generated when the electron beam scans to the edge tip position;

[0023] Figure 1C Comparative electron photos showing that the irregular bright spots caused by secondary electrons have different characteristics between pattern defects and non-pattern defects;

[0024] Figure 2 A flowchart showing a non-graphic defect recognition method provided by an embodiment of the present application;

[0025] Figure 3A The display shows a local electronic image of a wafer obtained by using an electron beam scanning using the non-graphic defect recognition method provided by an embodiment of the present application;

[0026] Figure 3B Display as Figure 3A A grayscale image obtained by grayscale conversion of the image shown;

[0027] Figure 3C The resulting labeled image is shown. DETAILED DESCRIPTION

[0028] The following describes the implementation of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific implementations, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention.

[0029] The following will be combined with the accompanying drawings to clearly and completely describe the technical solutions in this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0030] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating directions or positional relationships, are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present application. In addition, the terms "first", "second", and "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0031] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, it can also be the internal connection of two components, it can be a wireless connection, or it can be a wired connection. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0032] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0033] When identifying non-graphic defects, the existing technology uses an automatic detection (ADC, Auto Defect Classification) process that requires comparing the target image with the reference image to find the difference in order to determine the abnormal location. The target image takes a long time to shoot, and if Figure 1A As shown, it is impossible to distinguish between graphic defects and non-graphic defects.

[0034] In order to solve this problem, the present application provides a non-graphic defect identification method, which uses an electron beam to scan the wafer. When the electron beam scans to the edge tip position, a large number of secondary electrons are generated, such as Figure 1B As shown in Figure 1, the secondary electrons will cause a large number of irregular bright spots. Figure 1C As shown, these bright spots are dispersedly distributed at the edges of graphic defects and concentratedly distributed at the edges of non-graphic defects.

[0035] See also Figure 2 , which shows a flow chart of a non-graphic defect identification method provided in an embodiment of the present application.

[0036] like Figure 2 As shown, the non-graphic defect recognition method includes the following steps:

[0037] Step 1: The detection system uses an electron beam to scan the wafer to be detected, and performs grayscale conversion on the obtained image to obtain a grayscale image;

[0038] Step 2: Find the bright spot cluster in the grayscale image;

[0039] Step 3, calculating the density and distribution characteristics of the bright spots in the bright spot cluster to determine whether it is a non-graphic defect;

[0040] Step 4: After marking the original image corresponding to the grayscale image, the marked image is transmitted to the storage system;

[0041] Step 5: Confirm the update result of the storage system.

[0042] In step 1, the inspection system uses a scanning electron microscope (SEM) to scan the wafer to be inspected using an electron beam. Figure 3A The image shown in the figure is converted into grayscale. Figure 3B The grayscale image shown is conducive to a clearer display of irregular bright spots.

[0043] In step 2, a bright spot cluster is formed by densely distributed multiple bright spots, which is the basis for subsequent determination of the nature of the defect.

[0044] In step three, if Figure 3BAs shown in the figure, if the bright spots in the bright spot cluster have the characteristic of concentrated distribution along part of the edge of a certain figure, it can be determined as a non-graphic defect, and the figure usually has an irregular shape. If the bright spots in the bright spot cluster have the characteristic of dispersed distribution along the entire edge of a certain figure and the size of the figure does not match the preset target figure size, it can be determined as a graphic defect, and the figure usually has a regular shape, such as a rectangle, a regular shape with corners (L-shaped, T-shaped, etc.).

[0045] In step 4, the label name of the non-graphic defect is determined according to the semiconductor manufacturing process implemented before the defect detection is implemented. For example, if the photolithography process or the stripping process is implemented before the defect detection, the label name of the non-graphic defect is residual glue; if the etching process is implemented before the defect detection, the label name of the non-graphic defect is Figure 3C The particles shown.

[0046] In step five, Figure 3C For example, since the etching process targets different semiconductor film layers, the shapes and sizes of the generated particles are different. It is necessary to classify the marked images according to the implementation object and process conditions of the semiconductor manufacturing process.

[0047] It should be noted that the illustrations provided in this embodiment are only used to illustrate the basic concept of the present application in a schematic manner. Therefore, the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0048] In summary, the non-graphic defect recognition method provided by this application successfully distinguishes non-graphic defects through image processing, with an accuracy rate of more than 90%, and only requires taking a single target picture without reference pictures, which greatly reduces the detection time. Therefore, this application effectively overcomes the various shortcomings of the prior art and has a high industrial utilization value.

[0049] The above embodiments are merely illustrative of the principles and effects of the present application and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed by the present invention shall still be covered by the claims of the present application.

Claims

1. A non-graphic defect identification method, characterized in that: The method comprises: Step 1: The detection system uses an electron beam to scan the wafer to be detected, and performs grayscale conversion on the obtained image to obtain a grayscale image; Step 2, finding the bright spot cluster in the grayscale image; Step 3, calculating the density and distribution characteristics of the bright spots in the bright spot cluster to determine whether it is a non-graphic defect; Step 4: After marking the original image corresponding to the grayscale image, the marked image is transmitted to a storage system; Step 5: Confirm the update result of the storage system.

2. The method according to claim 1, characterized in that In the step 1, the wafer to be inspected is scanned by using an electron beam through a scanning electron microscope.

3. The method according to claim 1, characterized in that In the step three, if the bright spots in the bright spot cluster have the characteristic of being concentratedly distributed along a portion of the edge of a certain pattern, it can be determined as a non-pattern defect.

4. The method according to claim 3, characterized in that The pattern has an irregular shape.

5. The method according to claim 1, characterized in that In the step three, if the bright spots in the bright spot cluster are dispersed along the entire edge of a certain graphic and the size of the graphic does not match the preset target graphic size, it can be determined as a graphic defect.

6. The method according to claim 5, characterized in that The pattern has a regular shape.

7. The method according to claim 6, characterized in that The shape includes a rectangle or a regular shape with corners.

8. The method according to claim 7, characterized in that The regular shape with corners includes an L-shape or a T-shape.

9. The method according to claim 1, characterized in that: In the step 4, the label name of the non-graphic defect is determined according to the semiconductor manufacturing process implemented before the defect detection is implemented.

10. The method according to claim 1, characterized in that In the step five, the labeled images are classified according to the implementation object and process conditions of the semiconductor manufacturing process.

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