WO2023181918A1

WO2023181918A1 - Defect inspection device and defect inspection method

Info

Publication number: WO2023181918A1
Application number: PCT/JP2023/008619
Authority: WO
Inventors: 康之久世
Original assignee: 東レエンジニアリング株式会社; 東レエンジニアリング先端半導体Ｍｉテクノロジー株式会社
Priority date: 2022-03-25
Filing date: 2023-03-07
Publication date: 2023-09-28
Also published as: JP2023142884A; TW202348988A

Abstract

Provided is a defect inspection device making it possible, with a simple method, to automatically detect optimum optical conditions for imaging a region that includes a defect.　A defect inspection device 1 comprises: an optical microscope 10 provided with an imaging unit 14 for capturing an image of a chip 31; a control unit 20 for controlling optical conditions for capturing the image of the chip; and a storage unit 25 for storing the location of a defect in the chip that has been detected in advance. The imaging unit is provided with a detecting means for: capturing, while changing the optical conditions, a first image of a region that includes the defect stored in the storage unit as well as a second image of a region that does not include the defect in the same region as the region that includes the defect; and detecting the optimum optical conditions for imaging the region that includes the defect by comparing a feature amount of the first image and a feature amount of the second image.

Description

Defect inspection equipment and defect inspection method

The present invention relates to a defect inspection apparatus and a defect inspection method that inspect defects in chips formed on a wafer.

Semiconductor devices are manufactured by repeatedly forming multiple semiconductor device circuits (chips) in a matrix on a single semiconductor wafer, cutting them into individual chips, and packaging the diced chips. be done.

Before each chip is separated into pieces, the inspection image and the reference image are compared pixel by pixel while sequentially imaging the external pattern of each chip formed on the wafer, and the brightness of the contrasted pixels is determined. Defects within the chip are detected based on differences in values (for example, Patent Document 1).

Japanese Patent Application Publication No. 2007-155610

Defect inspection inside the chip is performed while taking an image of the chip with an optical microscope, but it is necessary to set the optical conditions of the optical microscope so that the defects can be clearly seen.

When a person manually sets the optical conditions, even if the location of the defect is known, the defect can be detected by moving the optical microscope to the area containing the defect, changing the optical conditions, and visually checking the inspection image. We are searching for optical conditions that will allow us to see clearly.

However, since there are many optical conditions, it is difficult for humans to search for all optical conditions, and since humans make visual judgments, there is a risk that defect detection may vary depending on the person.

The present invention has been made in view of the above problems, and its main purpose is to provide a defect inspection apparatus that uses an optical microscope to inspect defects in chips formed on a wafer in a simple manner. An object of the present invention is to provide a defect inspection device and a defect inspection method that can automatically detect the optimum optical conditions for imaging a region including a defect.

The defect inspection apparatus according to the present invention is a defect inspection apparatus that inspects defects in chips formed on a wafer, and includes an optical microscope equipped with an imaging unit that takes an image of the chip, and an optical microscope that uses the optical microscope to take an image of the chip. The imaging section includes a control section that controls optical conditions for imaging the defect, and a storage section that stores the position of a defect detected in advance in the chip. A first image of the stored defect-containing region and a second image of the defect-free region in the same region as the defect-containing region are captured, and the feature amount of the first image and the second image are captured. The apparatus is equipped with a detection means for detecting optimal optical conditions for imaging a region including a defect by comparing the feature amount of the image.

According to the present invention, in a defect inspection device that uses an optical microscope to inspect defects in chips formed on a wafer, optimal optical conditions for imaging a region containing defects can be automatically determined in a simple manner. It is possible to provide a defect inspection device and a defect inspection method capable of detecting defects.

1 is a diagram schematically showing the configuration of a defect inspection apparatus 1 according to a first embodiment of the present invention. 2 is a flowchart showing a method for detecting optimal optical conditions for imaging a region including a defect using the defect inspection apparatus according to the first embodiment. (A) to (C) are diagrams illustrating a method for detecting optimal optical conditions for imaging a region including a defect, according to the flowchart shown in FIG. 2. FIG. 7 is a diagram illustrating a method of detecting optimal optical conditions in a modification of the first embodiment. (A) to (C) are diagrams illustrating a method for creating learning data for a plurality of non-defective chips in the second embodiment of the present invention. (A) and (B) are diagrams showing the brightness value gi and sensitivity value Ai of each pixel in the defective area A. (A) and (B) are diagrams showing the luminance value g'i and sensitivity value A'i of each pixel in the non-defective area B.

Hereinafter, embodiments of the present invention will be described in detail based on the drawings. Note that the present invention is not limited to the following embodiments. Further, changes can be made as appropriate without departing from the range in which the effects of the present invention can be achieved.
(First embodiment)
FIG. 1 is a diagram schematically showing the configuration of a defect inspection apparatus 1 according to a first embodiment of the present invention.

As shown in FIG. 1, a defect inspection apparatus 1 according to the present embodiment is a defect inspection apparatus that inspects defects in chips formed on a wafer, and includes an optical microscope 10 and an optical microscope 10 for capturing an image of the chip. A control unit 20 that controls optical conditions, a storage unit 25 that stores the position of a defect detected in advance in the chip, and an optical microscope 10 that detect the optimal optical conditions for imaging a region containing a defect. Means 40 is provided.

The optical microscope 10 includes a stage 11 on which a wafer 30 is placed, a microscope main body 12 that holds the stage 11, an illumination section 13 that irradiates illumination light L onto the wafer 30, and an imaging section that captures an image of a chip. It is equipped with 14.

The illumination light L emitted from the illumination unit 13 is focused by the condenser lens 15, then deflected by the half mirror 16 along the optical axis of the objective lens 17, and is irradiated onto the surface of the wafer 30. The reflected light from the wafer 30 passes through the objective lens 17, the half mirror 16, and the coupling lens 18, and then enters the image sensor 19. The image captured by the image sensor 19 is subjected to image processing by the image processing section 35.

In the present embodiment, the detection means 40 detects optimal optical conditions for imaging a region including a defect based on the image information of the chip imaged by the imaging unit 14. The control unit 20 sets the optical microscope 10 to the optimal optical conditions detected by the detection means 40, images the chip, and detects defects in the wafer 30.

In this embodiment, the optical conditions of the optical microscope 10 controlled by the control unit 20 include the magnification of the objective lens 17, the type (coaxial, oblique, transmitted) and brightness of the illumination light L, and a differential interference filter (not shown). The position of the illumination light L, the filter of the illumination light L (not shown), etc. are diverse.

FIG. 2 is a flowchart showing a method for detecting optimal optical conditions for imaging a region containing a defect using the defect inspection apparatus 1 according to the present embodiment.

First, as shown in FIG. 3(A), a chip 31 formed on a wafer 30 is imaged in advance with an optical microscope 10 to detect defects within the chip 31. The position is registered in the storage unit 25 (step S101).

Next, as shown in FIG. 3B, the control unit 20 changes the optical conditions of the optical microscope 10 (step S102), and changes the image (first image) of the area (defect area) A including the defect 50. ) is imaged (step S103).

Next, as shown in FIG. 3B, under the same optical conditions, an image (second image) of an area (good product area) of the chip 31b that is the same area as the area A that includes the defect 50 and does not include the defect 50 is created. ) is imaged (step S104). Here, the defective area A and the non-defective area B are the same area within the chip.

Next, the brightness value (feature value) of the image (first image) of the defective area A is compared with the brightness value (feature value) of the image (second image) of the non-defective area B (step S105).

Next, if the search for the optimal optical conditions has not been completed (No in step S106), the optical conditions of the optical microscope 10 are changed (step S102), and steps S103 to S105 are repeated. If the search for the optimal optical conditions has been completed (Ys in step S106), the optical microscope 10 is set to the optimal optical conditions to detect defects within the wafer 30.

Table 1 shows the brightness value (A) of defective area A obtained by changing the optical conditions four times and capturing an image of defective area A and an image of non-defective area B under each optical condition. This is a table illustrating the brightness value of B (B) and the difference between the two brightness values (BA). Note that the numerical values of the brightness values indicate arbitrary units.

Even if the same areas A and B are imaged, if the optical conditions change, the brightness values of the images captured in areas A and B will also change, and the higher the clarity of the images, the larger the difference between them will be. Therefore, the difference (BA) between the brightness value (A) of the defective area A and the brightness value (B) of the non-defective area B is an evaluation value for determining the optimal optical conditions.

In the example shown in Table 1, among the four optical conditions, optical condition 2 has the largest difference (BA) in luminance value between the two. Therefore, in this case, optical condition 2 can be said to be the most suitable optical condition.

As described above, in this embodiment, by comparing the brightness value of the image of the defective area A (first image) and the brightness value of the image of the non-defective area B (second image), the area containing the defect is determined. The optimal optical conditions for imaging can be detected. This allows a margin for the threshold value when detecting a defect, so that it is possible to improve the detection accuracy when detecting a defect within a chip.

In addition, in Table 1, the optimal optical conditions were determined from the difference (B-A) between the brightness value (A) of defective area A and the brightness value (B) of non-defective area B, but the brightness value of defective area A (A) and the brightness value (B) of the non-defective area B may be compared using the ratio (B/A) between the two, as shown in Table 2.

In the example shown in Table 2, among the four optical conditions, optical condition 2 has the largest ratio (B/A) of both luminance values. Therefore, in this case, optical condition 2 can be said to be the most suitable optical condition.

(Modification of the first embodiment)
In the above embodiment, the brightness value of the image of the defective area A (first image) is compared with the brightness value of the image of the non-defective area B (second image) to image the area including the defect. Although the optimum optical conditions have been detected, the optimum optical conditions may also be detected by adding the difference in brightness values between images of different non-defective areas to the evaluation value.

As shown in FIG. 4, an area of the chip 31c that does not include the defect 50 is the same area as the area A that includes the defect 50 shown in FIG. 3(B), and is different from the chip 31b shown in FIG. (non-defective area) B' image (second image) is captured. Here, the defective area A and the non-defective area B' are the same area within the chip.

Next, the brightness value (B1) of the image of the non-defective area (first non-defective area) B shown in FIG. 3(C) and the image of the non-defective area (second non-defective area) B' shown in FIG. The brightness value (B2) is compared.

Table 3 shows the brightness value (A) of the defective area A, the brightness value (B1) of the first good area B, and the brightness value of the second good area The brightness value (B2) of B', the difference between the brightness value (A) and the brightness value (B1) (difference in the first brightness value) (D1=B1-A), the brightness value (B1) and the brightness value (B2) ) (difference in second brightness value) (D2=B1-B2), and the difference between the difference in first brightness value (D1) and the difference in second brightness value (D2) (D1-D2) ) is a table illustrating each example. Note that the numerical values of the brightness values indicate arbitrary units.

Here, the first brightness value difference (D1=B1-A) is the difference (B-A ) is the same as

Even if images of non-defective areas B and B' are captured under the same optical conditions, the brightness values B1 and B2 of the images captured in non-defective areas B and B' will vary due to variations between chips, but the images will have high clarity. The more the difference between the two becomes smaller. Therefore, the difference (B1-B2) between the brightness values of the non-defective areas also serves as an evaluation value for determining the optimal optical conditions. Therefore, the difference between the brightness value (A) of defective area A and the brightness value (B1) of non-defective area B (first brightness value difference: D1), and the difference in brightness value between non-defective areas B and B' ( The difference (D1−D2) from the second brightness value difference (D2) is an evaluation value for determining more optimal optical conditions.

In the example shown in Table 3, among the four optical conditions, optical condition 2 has the largest difference in brightness values (D1-D2). Therefore, in this case, optical condition 2 can be said to be the most suitable optical condition. In addition, by reducing the difference in brightness values between non-defective areas, it is possible to suppress the detection of false defects that would cause non-defective products to be considered defects.

(Second embodiment)
In the first embodiment, the brightness values of images captured in the non-defective area and the defective area were used as the feature values that serve as evaluation values for determining the optimal optical conditions. It may also be used as

As a defect inspection method, a good product learning method called the DSI (Die-to-Statistical Image) comparison method is known.

FIG. 5 is a diagram illustrating a method for creating learning data for a plurality of non-defective chips.

First, as shown in FIG. 5(A), a plurality of non-defective chips are imaged to obtain an image of the same area as the non-defective area B shown in FIG. 3(C). Here, the number of pixels P in area B is 12 (3×4).

Since images of the same area are acquired, the distribution of brightness values of each pixel forms a normal distribution that reflects the dispersion of non-defective products. Therefore, by performing statistical processing for each pixel, the average value Gi (i=1 to 12) and standard deviation σi (i=1 to 12 ) can be obtained.

Using the learning data obtained in this way, the sensitivity value Ai at each pixel in the defective area A and non-defective area B shown in FIGS. 3(B) and (C) is calculated for the wafer to be inspected. Calculated based on the following formula (1). Here, gi indicates the brightness value at each pixel.

FIG. 6(A) shows the luminance value gi of each pixel in the defective area A, and FIG. 6(B) shows the sensitivity value Ai of each pixel calculated using equation (1).

Similarly, FIG. 7(A) shows the luminance value g'i of each pixel in the non-defective area B, and FIG. 7(B) shows the sensitivity value A'i of each pixel calculated using equation (1). show.

In this way, the sensitivity value Ai of each pixel in the defect area A and the sensitivity value A'i of each pixel in the non-defective area B are obtained while changing the optical conditions of the optical microscope.

Then, under each optical condition, the maximum value Amax of the sensitivity value Ai of each pixel in the defective area A is compared with the maximum value A'max of the sensitivity value Ai of each pixel in the non-defective area B.

Table 4 shows the sensitivity value of defective area A (Amax), the sensitivity value of non-defective area B (A'max), and the difference between the two sensitivity values under each optical condition after changing the optical conditions four times. This is a table illustrating (A'maxB-Amax). Note that the numerical value of the sensitivity value indicates an arbitrary unit.

Even if the same areas A and B are imaged, if the optical conditions change, the sensitivity values of the images captured in areas A and B will also change, and the higher the clarity of the defective part in area A, the greater the difference from the learning data. The area becomes larger, and the difference from area B becomes larger. Therefore, the difference (Amax-A'max) between the sensitivity value (Amax) of the defective area A and the sensitivity value (A'max) of the non-defective area B is an evaluation value for determining the optimal optical conditions. The sensitivity value is a threshold value for detecting a target defect during inspection. Therefore, since the evaluation value is similar to that of an actual inspection, more accurate evaluation is possible than using a "luminance value."

In the example shown in Table 4, among the four optical conditions, optical condition 2 has the largest difference in luminance value (A'max-Amax) between the two. Therefore, in this case, optical condition 2 can be said to be the most suitable optical condition.

In addition, in Table 4, the optimal optical conditions were determined from the difference (A'max - Amax) between the sensitivity value (Amax) of defective area A and the sensitivity value (A'max) of non-defective area B. The sensitivity value (Amax) of A and the sensitivity value (A'max) of non-defective area B may be compared based on the ratio of the two (A'max/Amax).

Although the present invention has been described above using preferred embodiments, such descriptions are not limiting, and of course, various modifications are possible. For example, in the above embodiment, the brightness value and sensitivity value of images captured in a non-defective area and a defect area are used as an example of feature values that are evaluation values for determining the optimal optical conditions of an optical microscope, but the invention is not limited to this. Instead, other feature quantities may be used, such as a variance value or a brightness value after edge enhancement filter processing, as long as the feature quantity changes depending on the sharpness of the image.

1 Defect inspection equipment
10 Optical microscope
11 stage
12 Microscope body
13 Lighting section
14 Imaging section
15 Condensing lens
16 Half mirror
17 Objective lens
18 Combined lens
19 Image sensor
20 control section 25 storage section 30 wafer
31 Chip
35 Image processing section
40 Detection means
50 defects

Claims

A defect inspection device that inspects defects in chips formed on a wafer,
an optical microscope equipped with an imaging unit that captures an image of the chip;
a control unit that controls optical conditions for capturing an image of the chip with the optical microscope;
a storage unit storing the position of a defect detected in advance in the chip;
Equipped with
The imaging unit is configured to capture a first image of the area including the defect stored in the previous storage unit and an area including the defect in the same area as the area including the defect while changing the optical conditions with the control unit. capturing a second image of the area where there is no
Defect inspection, comprising a detection means for detecting optimal optical conditions for imaging the region including the defect by comparing the feature amount of the first image and the feature amount of the second image. Device.
The imaging unit includes capturing a plurality of the second images,
The detection means detects the defect by comparing the feature amounts of the plurality of second images in addition to comparing the feature amounts of the first image and the feature amounts of the second image. The defect inspection device according to claim 1, which detects optimal optical conditions for imaging a region including the defect.
1 . The optical condition in which the difference between the feature amount of the first image and the feature amount of the second image is maximum is detected as the optimal optical condition for imaging the region including the defect. Or the defect inspection device according to 2.
The difference between the feature amount of the first image and the feature amount of the second image is defined as a first difference, and the difference between the feature amounts of the plurality of second images is defined as a second difference. 3. The defect according to claim 1, wherein an optical condition in which a difference or a ratio between a difference of 1 and the second difference or a ratio is maximum is detected as an optimal optical condition for imaging the region including the defect. Inspection equipment.
The defect inspection device according to any one of claims 1 to 4, wherein the feature amount of the first image and the feature amount of the second image are brightness values or sensitivity values.
The optical conditions include at least one of a magnification of an objective lens for capturing an image of the chip, a type of illumination light irradiated to the chip, a brightness of the illumination light, and a filter for the illumination light. The defect inspection device according to any one of Items 1 to 5.
A defect inspection method for inspecting defects in the chips by capturing an image of a chip formed on a wafer with an optical microscope, the method comprising:
a step of registering the location of the defect in the chip in advance;
While changing the optical conditions of the optical microscope, capturing a first image of the region containing the defect and a second image of the region not containing the defect in the same region as the defect-containing region;
A defect inspection method comprising: detecting optimal optical conditions for imaging the region including the defect by comparing the feature amount of the first image and the feature amount of the second image. .