Substrate inspection method and substrate inspection apparatus
阅读说明:本技术 基板检查方法和基板检查装置 (Substrate inspection method and substrate inspection apparatus ) 是由 久野和哉 清富晶子 于 2019-07-19 设计创作,主要内容包括:本发明提供基板检查方法和基板检查装置,能够在检查基板时准确地探测基板周缘部的宏观的异常。检查基板的方法包括以下工序:特征量获取工序,获取作为检查对象的所述基板的周缘部的图像、即检查对象周缘图像中的多个分割区域的各个分割区域的特征量,所述分割区域是将所述基板的周缘部的图像中的规定的区域进行分割所得到的区域;以及判定工序,基于所述特征量获取工序中的获取结果来进行与所述基板的周缘部的检查有关的规定的判定。(The invention provides a substrate inspection method and a substrate inspection apparatus, which can accurately detect macroscopic abnormality of a peripheral portion of a substrate when the substrate is inspected. The method for inspecting a substrate includes the steps of: a feature value acquisition step of acquiring a feature value of each of a plurality of divided regions in an image of a peripheral portion of the substrate to be inspected, the divided regions being obtained by dividing a predetermined region in the image of the peripheral portion of the substrate; and a determination step of performing a predetermined determination regarding inspection of the peripheral edge portion of the substrate based on the acquisition result in the feature amount acquisition step.)
1, A substrate inspection method for inspecting a substrate, the substrate inspection method comprising the steps of:
a feature value acquisition step of acquiring a feature value of each of a plurality of divided regions in an image of a peripheral portion of the substrate to be inspected, the divided regions being obtained by dividing a predetermined region in the image of the peripheral portion of the substrate; and
and a determination step of performing a predetermined determination regarding inspection of the peripheral portion of the substrate based on the acquisition result in the feature amount acquisition step.
2. The substrate inspection method according to claim 1,
in the determination step, the predetermined determination is performed based on the acquisition result in the feature amount acquisition step and the feature amount of the divided region in a reference peripheral image that is an image of the peripheral portion of the substrate that is a reference of the predetermined determination.
3. The substrate inspection method according to claim 1 or 2,
the feature amount is an average value of pixel values in the divided region.
4. The substrate inspection method according to claim 1 or 2,
the feature amount is a standard deviation of pixel values in the divided region.
5. The substrate inspection method according to claim 1 or 2,
the feature amount is a histogram of pixel values in the divided region.
6. The substrate inspection method according to claim 3,
the feature quantity is a quantity related to a pixel value of a specific color.
7. The substrate inspection method according to claim 1 or 2,
the divided region is a region obtained by dividing the predetermined region in a radial direction of the substrate.
8. The substrate inspection method according to claim 1 or 2,
the divided region is a region obtained by dividing the predetermined region in the circumferential direction of the substrate.
9. The substrate inspection method according to claim 1 or 2,
further comprises an imaging step of imaging the peripheral edge of the substrate,
the inspection target peripheral image is an image of the peripheral portion of the substrate obtained based on the imaging result in the imaging step.
10, kinds of substrate inspection apparatus for inspecting a substrate, the apparatus comprising:
a feature value acquisition unit that acquires a feature value of each of a plurality of divided regions in an image of a peripheral portion of the substrate to be inspected, the divided regions being obtained by dividing a predetermined region in the image of the peripheral portion of the substrate; and
and a determination unit that performs a predetermined determination regarding inspection of the peripheral edge portion of the substrate based on the acquisition result obtained by the feature amount acquisition unit.
Technical Field
The present disclosure relates to substrate inspection methods and substrate inspection apparatuses.
Background
Disclosure of Invention
Problems to be solved by the invention
The technology of the present disclosure can accurately detect macroscopic abnormalities in the peripheral portion of a substrate when the substrate is inspected.
Means for solving the problems
The aspects of the present disclosure are a method for inspecting a substrate, including a feature value acquisition step of acquiring a feature value of each of a plurality of divided regions in an image of a peripheral portion of the substrate as an inspection target, the divided regions being obtained by dividing a predetermined region in the image of the peripheral portion of the substrate, and a determination step of performing a predetermined determination regarding inspection of the peripheral portion of the substrate based on an acquisition result in the feature value acquisition step.
ADVANTAGEOUS EFFECTS OF INVENTION
According to the present disclosure, it is possible to accurately detect macroscopic abnormalities at the peripheral portion of a substrate when inspecting the substrate.
Drawings
Fig. 1 is a plan view schematically showing the configuration of a substrate processing system according to the present embodiment.
Fig. 2 is a side view schematically showing the internal configuration of the substrate processing system according to the present embodiment.
Fig. 3 is a side view schematically showing the internal configuration of the substrate processing system according to the present embodiment.
Fig. 4 is a cross-sectional view schematically showing the structure of the inspection apparatus.
Fig. 5 is a vertical cross-sectional view schematically showing the structure of the inspection apparatus.
Fig. 6 is a side view schematically showing the configuration of the peripheral imaging subunit.
Fig. 7 is a view showing a state of reflection of light from the peripheral edge portion of the substrate.
Fig. 8 is a block diagram schematically showing the configuration of the control unit.
Fig. 9 is a diagram illustrating an example of an inspection target image.
Fig. 10A is a diagram showing an example of the reference peripheral image.
Fig. 10B is a diagram illustrating examples of the inspection target peripheral image.
Fig. 11A is a diagram illustrating another example of the imaging peripheral image.
Fig. 11B is a diagram illustrating another example of the imaging periphery image.
Fig. 11C is a diagram showing another example of the imaging peripheral image.
Fig. 12A is a diagram for explaining a specific example of judgment in the judgment section and inspection in the inspection section.
Fig. 12B is a diagram for explaining a specific example of the judgment in the judgment section and the inspection in the inspection section.
Fig. 13A is a diagram for explaining another specific example of judgment in the judgment section and inspection in the inspection section.
Fig. 13B is a diagram for explaining another specific example of the judgment in the judgment section and the inspection in the inspection section.
Fig. 13C is a diagram for explaining another specific example of the judgment in the judgment section and the inspection in the inspection section.
Fig. 13D is a diagram for explaining another specific example of the judgment in the judgment section and the inspection in the inspection section.
Detailed Description
First, a conventional substrate inspection apparatus described in
In a manufacturing process of a semiconductor device, a semiconductor wafer (hereinafter, referred to as a "wafer") as a substrate is subjected to various processes such as an ion implantation process, a film formation process, a photolithography process, and an etching process. In the photolithography process for forming a predetermined resist pattern on a wafer, a process for forming a resist film by applying a resist solution on the wafer, a development process for developing the resist film exposed to light in a predetermined pattern, and the like are performed in this order.
In the case of a wafer subjected to various processes related to the manufacturing process of the semiconductor device, the peripheral edge portion is made thinner than the center of the wafer by polishing the peripheral edge portion of the wafer. Thus, the peripheral region of the wafer surface is inclined with respect to the central region of the wafer surface. Further, the tilt and variations in processing conditions in various processes involved in the manufacturing process make it difficult to control the state of the peripheral edge of the wafer. Monitoring the state of the peripheral portion of the wafer to detect an abnormality contributes not only to an increase in the number of effective chips but also to an improvement in the yield of chips in the vicinity of the peripheral portion.
Therefore, the inspection unit of
As described above, as a method for inspecting the state of the peripheral edge portion of the wafer using the captured peripheral edge image obtained based on the imaging result of the peripheral edge portion of the wafer, for example, the following method is available. The periphery comparison method is a method of detecting an abnormality based on a difference between an image of a region to be inspected in a captured image and an image of a peripheral region thereof. In addition, there is also a method (edge tracking method) of acquiring a position of an edge of a film formed on a wafer from a light and a shade in an image. In this method, for example, when an annular film is formed along the peripheral edge portion of the wafer, the position of the inner edge of the annular film is obtained. Then, the distance from the edge of the wafer to the inner edge of the annular film can be calculated, and whether or not the film formation is acceptable can be determined based on the calculation result.
However, in any of the methods, a macroscopic abnormality cannot be detected, for example, in a case where a resist film is formed annularly along the peripheral edge portion of the wafer, such as a state shown in fig. 11C described later, in fig. 11C, the edge of the resist film R on the side opposite to the peripheral end surface side of the wafer W is clear, but in a case where no resist film R is formed on the peripheral end surface side of the wafer W, in the case where an abnormality such as that shown in fig. 11C exists, it is determined that a circular film is formed in the center portion in the above-described periphery comparison method, and it is determined that no abnormality exists because the edge of the resist film can be obtained in the above-described edge tracing method.
In the inspection of the peripheral edge portion of the wafer, a substrate image (golden image) as a reference is registered in advance, and abnormality determination is not performed by pattern matching based on the golden image. This is because: in the peripheral portion of the wafer, the matching between the patterns is poor, and it is difficult to accurately determine the abnormality even when the images are compared.
Next, a substrate processing method and a substrate inspection apparatus according to the present embodiment for detecting macroscopic abnormalities in the peripheral portion of a substrate when inspecting the substrate will be described with reference to the drawings. In the present specification and the drawings, elements having substantially the same functional configuration are denoted by the same reference numerals, and redundant description thereof is omitted.
Fig. 1 is a plan view schematically showing the configuration of a
As shown in fig. 1, the
The
The
The
As shown in fig. 2, a plurality of liquid processing apparatuses, for example, a developing
For example, three developing
In the developing
As shown in fig. 3, the second block G2 is provided with a
For example, in the third block G3, a plurality of passing
As shown in fig. 1, a wafer conveyance area D is formed in an area surrounded by the th block G1 to the fourth block G4, and the
The
In the wafer transfer area D, a
The
As shown in fig. 1, a
The
Next, the structure of the
As shown in fig. 5, a
Also, a front
The
The
The
As shown in fig. 4 to 6, the peripheral
The
The
When the wafer W held by the
In the
As shown in fig. 7, the reflected light reflected from the peripheral area Wp of the front surface Wf of the wafer W goes to the
Further, by providing the focus adjustment lens 427, the peripheral edge area Wp of the front surface Wf of the wafer W and the side end surface Ws of the wafer W are both clear in the image captured by the
As shown in fig. 5, the back
The
The
In the
As shown in fig. 1, the
As shown in fig. 8, the
Specifically, the
The feature
For example, as shown in fig. 9, the predetermined region a1 is a peripheral edge region Wp on the front surface Wf of the wafer W and is a region excluding the side end surface Ws and the chamfer of the wafer W, and an image Im1 of fig. 9 is an example of an inspection target peripheral edge image, and in this image Im1, the circumferential direction of the wafer W coincides with the left-right direction of the image, and the radial direction of the wafer W coincides with the up-down direction of the image, and in an image Im1 of fig. 9, a symbol N is a notch.
In the example shown in the figure, the divided regions a11 to a15 are regions obtained by dividing the predetermined region a1 in the radial direction of the wafer W. When the predetermined region is divided in the radial direction of the wafer W, the size of each divided region in the radial direction is set to 0.5mm or more.
The predetermined area, the number of divisions of the predetermined area, and the size of each divided area (in this example, the width of the wafer W in the radial direction) are set by a user, for example.
The "feature amount of the divided region" is, for example, an average value of pixel values in the divided region of the captured peripheral image, such as the inspection target peripheral image and a reference peripheral image described later.
The imaging peripheral image is composed of three color components of RGB (Red, Green, Blue: Red, Green, Blue). Therefore, the average value of the pixel values/luminance values of the specific color component in the divided region of the captured peripheral image may be set as "the feature amount of the divided region". In this example, the "feature amount of the divided region" is an average value of pixel values/luminance values of a specific color component in the divided region of the captured peripheral image. The specific color is set by a user, for example.
The determination unit 212 performs a predetermined determination regarding the inspection of the peripheral edge portion of the wafer W based on the acquisition result obtained by the feature
Specifically, when the number of divided regions determined to have an abnormality by the determination unit 212 is or more, the
Fig. 10A and 10B are diagrams for explaining specific examples of determination by the determination section 212 and inspection by the
Both the image of fig. 10A and the image of fig. 10B are images of the entire peripheral edge region of the front surface Wf of the wafer W, and have dark gray portions P1 and P11 and gray portions P2 and P12, and boundaries between the dark gray portions P1 and P11 and the gray portions P2 and P12 are not smooth, and have fine comb tooth shapes. In the conventional method (the above-described peripheral comparison method and edge tracking method), it is difficult to detect a boundary having a fine comb-tooth shape by separating regions having small differences in pixel values from each other. Therefore, in the conventional method, the widths of the gray portions P2 and P12 in the image having the boundaries between the dark gray portions P1 and P11 and the gray portions P2 and P12 as shown in fig. 10A and 10B cannot be determined.
In the image of fig. 10A, the width of the gray portion P2 is substantially fixed to 13mm in the circumferential direction of the wafer W, whereas in the image of fig. 10B, the width of the gray portion P12 is substantially fixed in the circumferential direction, but the width is smaller than that in the image of fig. 10A. Such a difference occurs due to a difference in processing conditions of wafer processing (including a difference in dissolution state and film thickness characteristics of a coating film after processing).
Table 1 shows an example of the average value of the pixel values of the color components in the slices F1 to F5 of the image in fig. 10A, and table 2 shows an example of the average value of the pixel values of the color components in the slices F1 to F5 of the image in fig. 10B.
[ Table 1]
Slicing
R
G
B
F1
120
179
211
101
144
203
100
106
193
101
101
190
101
101
190
[ Table 2]
Slicing
R
G
B
F1
124
182
208
F2
104
136
190
101
107
190
F4
102
104
193
F5
102
103
192
Table 3 shows the difference between the above average value in each of the slices F1 to F5 in the image of fig. 10A and the above average value in each of the slices F1 to F5 in the image of fig. 10B.
[ Table 3]
Slicing
R
G
B
F1
4
3
-3
F2
3
-8
-4
1
1
3
1
3
3
1
2
2
In the determination by the determination unit 212, the image in fig. 10A is set as a reference peripheral image, the average value of the pixel values of the green (G) component of the image is set as a parameter for determination, and the threshold value relating to the determination is set to, for example, 5. Then, since the average value of the pixel values of the green component in the slice F2 exceeds the threshold value, the determination unit 212 determines that there is an abnormality in the slice F2 of the inspection target peripheral image in fig. 10B. Then, the
Fig. 11A to 11C are views showing other examples of the picked-up edge image, and fig. 11A to 11C are images of the entire edge area of the front surface Wf of the wafer W, fig. 11A shows the picked-up edge image of the wafer W on which the ring-shaped resist film R is formed along the edge area, fig. 11B shows the picked-up edge image of the wafer W on which the resist film is not formed on the edge area, and fig. 11C is a picked-up edge image of the wafer W on which the edge of the resist film R on the side opposite to the wafer peripheral end surface is clear but the resist film R is not formed on the wafer peripheral end surface side.
In the determination by the determination unit 212, the image of fig. 11A (or an image similar thereto) is set as a reference peripheral image, and the predetermined region is set as a region including an annular resist film formed therein. In the determination by the determination unit 212, the average value of the luminance values of the specific color components in the divided regions is used as a parameter for the determination. Then, when the
Next, a process for the wafer W performed by using the
In the processing of the wafers W, first, the cassettes C containing a plurality of wafers W are placed on a
Then, the wafer W is carried by the
Subsequently, the wafer W is carried to the adhering
Next, the wafer W is transported to the upper anti-reflection
Next, the wafer W is carried to the
In the
If it is determined that the defect is not acceptable, the wafer W is transported to the
When the inspection is determined to be acceptable, , the wafer W is transported to the
After the development process is completed, the wafer W is carried to the
According to the present embodiment, a predetermined region in the inspection target peripheral image is divided into relatively large divided regions, and for each divided region, determination regarding inspection of the peripheral edge portion of the wafer W is performed based on the feature amount of the divided region. Therefore, macroscopic abnormalities such as large-scale coating defects can be accurately detected.
In the above-described periphery comparison method used in the conventional abnormality detection method, the allowable coating unevenness may be erroneously detected as a defect, but according to the present embodiment, such coating unevenness is not erroneously detected.
In addition, when an annular resist film is formed along the peripheral edge region of the front surface of the wafer W, if a large linear defect exists in the vicinity of the inner end of the resist film, the large linear defect may be erroneously recognized as the inner end of the annular resist film by the edge tracing method or the like. When the erroneous recognition is performed in this manner, it is impossible to accurately check the quality of the annular resist film. According to the present embodiment, such a large linear defect is not erroneously recognized as the inner end of the annular resist film, and the state of formation of the resist film can be accurately inspected.
In order to represent information on the wafer W, a laser mark including a plurality of dots may be formed in a peripheral edge region of the back surface of the wafer W. In the conventional method, the laser mark may be erroneously recognized as the edge of the resist film. In the conventional method, a wafer boat mark (japanese: ボート mark) which may be formed on the peripheral edge of the wafer W may be erroneously recognized as a defect. In contrast, in the present embodiment, when the predetermined region is set, the laser mark forming region and the wafer boat mark forming region are removed from the predetermined region as the removal region, so that the laser mark and the wafer boat mark are not erroneously recognized. The position of the laser mark forming region is fixed, but the wafer boat mark forming region differs for each wafer W. Therefore, when the wafer boat mark formation region is set as the exclusion region, it is preferable that a characteristic shape (pattern) of the wafer boat mark is registered in advance, and the wafer boat mark formation region is automatically recognized based on the registered pattern.
In the above example, the feature
Fig. 12A and 12B are diagrams for explaining specific examples of the judgment by the judgment section 212 and the inspection by the
Both the image of fig. 12A and the image of fig. 12B are images of the peripheral edge area Wp on the back surface Wb of the wafer W, which are images based on a light gray (red) component, and the image of fig. 12B has a large dark gray portion P21 due to macroscopic defects that are not present in the image of fig. 12B. In such a system, when the region having a different color is large, it is difficult to perform detection by the conventional method.
Table 4 shows an example of the average value of the pixel values of the red component in each of the lines B1 to B4 of the image in fig. 12A, and table 5 shows an example of the average value of the pixel values of the red component in each of the lines B1 to B4 of the image in fig. 11B.
[ Table 4]
Thread
R
B1
92
B2
188
B3
197
B4
199
[ Table 5]
R
B1
90
172
B3
167
B4
195
In the determination by the determination unit 212, the image of fig. 12A is set as a reference peripheral image, the average value of the pixel values of the red component of the image is set as a parameter for determination, and the threshold value relating to the determination is set to, for example, 5. Then, since the average value of the pixel values of the red component in the lines B2 and B3 of the inspection target peripheral image in fig. 12B exceeds the threshold value, the determination unit 212 determines that there is an abnormality in the divided region corresponding to the lines B2 and B3. Then, the
In the above example, a region obtained by dividing a predetermined region in an image of the peripheral portion of the substrate in the radial direction is defined as a divided region. The divided region may be a region obtained by dividing the predetermined region in the circumferential direction. When the divided regions are divided in the circumferential direction, the width of the divided regions in the circumferential direction is, for example, 30 ° to 60 °.
In the above example, the average value of the pixel values of the specific color component in the divided region is obtained as the feature amount of the divided region. Alternatively, the standard deviation of the pixel values in the divided region may be acquired as the feature amount of the divided region.
Fig. 13A to 13D are diagrams for explaining specific examples of the determination by the determination section 212 and the inspection by the
The image of fig. 13A and the image of fig. 13D are captured peripheral images of the wafer W in which the ring-shaped film is satisfactorily formed on the peripheral edge of the resist film along the peripheral edge. Further, the pixel value of the image of fig. 13D is higher than that of the image of fig. 13A. The image of fig. 13B and the image of fig. 13C are captured peripheral images of the wafer W on which the annular film is not partially formed on the peripheral edge of the resist film.
Table 6 shows examples of differences between the average value and standard deviation of the pixel values of the color components and the values of the image in fig. 13A in each block of the image in fig. 13B, table 7 shows examples of differences between the average value and standard deviation of the pixel values of the color components and the values of the image in fig. 13A in each block of the image in fig. 13C, and table 8 shows examples of differences between the average value and standard deviation of the pixel values of the color components and the values of the image in fig. 13A in each block of the image in fig. 13D.
[ Table 6]
[ Table 7]
[ Table 8]
In the determination by the determination unit 212, the image of fig. 13A is set as a reference peripheral image, the average value of the pixel values of the red (R) component of the image is set as a parameter for determination, and the threshold value relating to the determination is set to, for example, 10, and the
Therefore, the feature
The feature
Then, the determination unit 212 calculates, for each block, the difference between the standard deviation of the specific color component (red component in this example) in the block of the inspection target peripheral image and the standard deviation in the reference peripheral image. When the difference falls within a predetermined range, the determination unit 212 determines that there is no abnormality in the block of the inspection target peripheral image, and when the difference does not fall within the predetermined range, the determination unit 212 determines that there is an abnormality.
Here, in the determination by the determination unit 212, the image of fig. 13A is used as the reference peripheral image, the standard deviation of the pixel value of the red (R) component is used as the feature amount, and the predetermined range relating to the determination is set to 10 to 19, for example. The image in fig. 13B and the image in fig. 13C have blocks in which the difference between the standard deviation of the red component and the standard deviation of the reference peripheral image (the image in fig. 13A) does not fall within the predetermined range. In contrast, in the image of fig. 13D, the difference between the standard deviation of the red component of any block and the standard deviation of the reference peripheral image (the image of fig. 13A) is within the predetermined range. Therefore, only when the image of fig. 13B or the image of fig. 13C is acquired as the inspection target peripheral image, the determination unit 212 determines that there is an abnormality and the
In addition, when a region obtained by dividing the image in the radial direction is defined as a divided region, an average value of pixel values in the divided region may be used as the feature amount. In addition, when a region obtained by dividing the region in the circumferential direction is a divided region, the standard deviation of the pixel values in the divided region may be used as the feature amount.
In the above example, the divided regions are obtained by dividing a predetermined region in the image of the peripheral portion of the substrate in any of directions in the circumferential direction and the radial direction, but may be obtained by dividing the predetermined region in both the circumferential direction and the radial direction.
The range in which the feature amount is acquired, that is, the predetermined region includes only any of the front peripheral edge region and the rear peripheral edge region of the wafer W, but may include both the front peripheral edge region and the rear peripheral edge region.
When the predetermined region includes both the front and rear peripheral regions of the wafer W, the front and rear divided regions may be provided in the same manner, and when it is determined that there is an abnormality in both the front divided region and the rear divided region located on the rear side of the divided region, the inspection may be failed.
In addition, when the determination is made by the determination unit 212 so that only the peripheral edge area of the front surface of the wafer W is included in the predetermined area and there is a divided area determined to have an abnormality, the additional determination may be made by the determination unit 212 so that only the peripheral edge area of the back surface of the wafer W is included in the predetermined area. When the determination is made by the determination unit 212 so that only the peripheral edge area of the back surface of the wafer W is included in the predetermined area and there is a divided area determined to have an abnormality, the additional determination may be made by the determination unit 212 so that only the peripheral edge area of the front surface of the wafer W is included in the predetermined area.
When such an addition determination is performed, the addition determination may be performed by dividing the divided region on the back side of the divided region determined to have an abnormality in the previous determination by steps.
The predetermined region may include not only the peripheral edge region of the front surface and/or the back surface of the wafer W but also the side end surface of the wafer.
The predetermined region may be set such that the chamfer is excluded from the predetermined region based on the detection result of the edge of the wafer W or the like. Further, the predetermined region may be set so that only the following portions are included in the predetermined region based on the detection result of the edge of the wafer W and the like: the portion on the outer side of the portion on which the chamfer is formed is included.
In contrast to the above example, a histogram of pixel values in a divided region of the captured peripheral image may be extracted as the feature amount of the divided region. In this case, the determination unit 212 determines that there is an abnormality when, for example, a pixel value whose frequency deviation from the frequency of the reference peripheral image is equal to or greater than a predetermined value exists in the divided region to be determined.
The predetermined region in the image of the peripheral portion of the substrate, the number of divisions of the predetermined region, and the size of each divided region are set by a user, for example. In this setting, a reference peripheral image or the like may be displayed on a display unit (not shown).
A wafer W having no abnormality in the peripheral edge portion may be produced, and a reference peripheral edge image may be generated based on an imaging result obtained by imaging the wafer W by the
As for the setting of the "threshold value", "predetermined range", and specific color component relating to the feature amount, a plurality of pieces of lithography processing are actually performed in the same manner as described above, and the pixel values of the captured peripheral image obtained based on the imaging result at that time are displayed, and the like, and the user performs the setting based on the display result. These "threshold values" and the like may be automatically set based on the feature amount of the reference peripheral image.
In addition, the reference peripheral image may not be set or selected, and only the feature values of the respective divided regions of the reference peripheral image may be set.
The mounting position of the
In the above description, the inspection target peripheral image is an image obtained based on the imaging result of the
In the above description, the resist film formed on the wafer W in the process of manufacturing the semiconductor device is inspected, but the technique according to the present disclosure can be applied to other inspections performed when various processes related to the manufacturing process of the semiconductor device are performed.
The embodiments disclosed herein are considered to be illustrative in all respects, rather than restrictive. The above-described embodiments may be omitted, replaced, or modified in various ways without departing from the scope of the appended claims and the gist thereof.
The following configuration also falls within the technical scope of the present disclosure.
(1) A substrate inspection method for inspecting a substrate, the substrate inspection method comprising the steps of:
a feature value acquisition step of acquiring a feature value of each of a plurality of divided regions in an image of a peripheral portion of the substrate to be inspected, the divided regions being obtained by dividing a predetermined region in the image of the peripheral portion of the substrate; and
and a determination step of performing a predetermined determination regarding inspection of the peripheral edge portion of the substrate based on the acquisition result in the feature amount acquisition step.
In the above (1), a predetermined region in the inspection target peripheral image is divided into divided regions, and for each of the divided regions, a determination regarding the inspection of the peripheral portion of the substrate is performed based on the feature amount of the divided region. Therefore, macroscopic abnormalities such as large-scale coating defects can be accurately detected.
(2) In the substrate inspection method according to the above (1), in the determination step, the predetermined determination is performed based on the acquisition result in the feature amount acquisition step and the feature amount of the divided region in a reference peripheral image, which is an image of the peripheral portion of the substrate that is a reference of the predetermined determination.
(3) In the substrate inspection method described in (1) or (2), the feature amount is an average value of pixel values in the divided region.
(4) The substrate inspection method according to any one of above (1) to (3), wherein the feature amount is a standard deviation of pixel values in the divided regions.
(5) The substrate inspection method according to any one of items in items (1) to (4), wherein the feature amount is a histogram of pixel values in the divided region.
(6) The substrate inspection method according to any one of items in items (3) to (5), wherein the feature amount is an amount related to a pixel value of a specific color.
(7) The substrate inspection method according to any one of items in items (1) to (6), wherein the divided region is a region obtained by dividing the predetermined region in a radial direction of the substrate.
(8) The substrate inspection method according to any one of items in items (1) to (7), wherein the divided region is a region obtained by dividing the predetermined region in a circumferential direction of the substrate.
(9) The substrate inspection method according to any one of items above (1) to (8), further comprising an imaging step of imaging a peripheral edge portion of the substrate,
the inspection target peripheral image is an image of the peripheral portion of the substrate obtained based on the imaging result in the imaging step.
(10) A substrate inspection apparatus for inspecting a substrate, the apparatus comprising:
a feature value acquisition unit that acquires a feature value of each of a plurality of divided regions in an inspection target peripheral image, which is an image of the peripheral portion of the substrate obtained as a result of the imaging of the inspection target by the imaging unit, the divided regions being obtained by dividing a predetermined region in the image of the peripheral portion of the substrate; and
and a determination unit that performs a predetermined determination regarding inspection of the peripheral edge portion of the substrate based on the acquisition result obtained by the feature amount acquisition unit.
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