Information processing method, information processing device, and storage medium

Abstract

This information processing method is for processing information for inspecting a substrate on the basis of a captured image of the substrate. The image processing method includes: a step for acquiring a captured image of the substrate; a step for creating a two-dimensional histogram pertaining to the acquired captured image of the substrate, the two-dimensional histogram having as axes thereof the distance from the center of the substrate and brightness values; a step for extracting a specific unevenness distribution from the two-dimensional histogram on the basis of a predefined region definition, the specific unevenness distribution corresponding to a dissimilar unevenness in the captured image; and a step for acquiring feature amounts of the specific unevenness distribution extracted to determine the type of said specific unevenness distribution on the basis of said feature amounts.

Description

[Technical Field]

[0001] The present disclosure relates to an information processing method, an information processing device, and a storage medium. [Background technology]

[0002] The apparatus for analyzing defects in substrates disclosed in Patent Document 1 includes an imaging unit that images a substrate to be inspected, a defect feature extraction unit that extracts feature quantities of defects within the substrate surface based on the image of the substrate, and a defect feature quantity integration unit that integrates the defect feature quantities for multiple substrates.The apparatus also includes a defect determination unit that determines whether the integrated defect feature quantity exceeds a predetermined threshold, and an output unit that outputs the determination result of the defect determination unit. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2015-90964 Summary of the Invention [Problem to be solved by the invention]

[0004] The technology according to the present disclosure makes it possible to accurately perform inspection based on a captured image of a substrate even when the captured image has unevenness. [Means for solving the problem]

[0005] One aspect of the present disclosure is an information processing method for processing information for inspecting a substrate based on an image of the substrate, including the steps of: acquiring the image of the substrate; creating a two-dimensional histogram for the acquired image of the substrate, with axes representing distance from the center of the substrate and brightness value; extracting a specific unevenness distribution corresponding to heterogeneous unevenness in the image from the two-dimensional histogram based on a predetermined region definition; and acquiring features of the extracted specific unevenness distribution and determining the type of the specific unevenness distribution based on the features. [Effects of the Invention]

[0006] According to the present disclosure, even if the captured image of the substrate has unevenness, inspection can be performed accurately based on the captured image. [Brief explanation of the drawings]

[0007] [Figure 1] 1 is an explanatory diagram showing an outline of the internal configuration of a wafer processing system as a substrate processing system including a control device as an information processing device according to an embodiment of the present invention; [Figure 2] 1 is a diagram showing an outline of the internal configuration of the front side of a wafer processing system. [Figure 3] FIG. 2 is a diagram showing an outline of the internal configuration of the rear side of the wafer processing system. [Figure 4] 1 is a cross-sectional view showing an outline of the configuration of an inspection imaging device. [Figure 5] 1 is a longitudinal sectional view showing an outline of the configuration of an inspection imaging device. [Figure 6] FIG. 2 is a functional block diagram of a control device related to inspection in the wafer processing system. [Figure 7] 1 is a diagram showing an example of a captured image of a wafer W. FIG. [Figure 8] 1 is a diagram showing an example of a captured image of a wafer W. FIG. [Figure 9] FIG. 10 is a diagram illustrating an example of a two-dimensional histogram. [Figure 10] FIG. 10 is a diagram illustrating an example of a luminance value distribution. [Figure 11]FIG. 10 is a diagram illustrating an example of a specific unevenness distribution. [Figure 12] 10 is a flowchart showing the flow of a method for registering a specific unevenness distribution in database 210 before information processing based on the imaging results of the wafer. [Figure 13] 10 is a flowchart showing the flow of information processing for wafer inspection, including information processing based on the results of imaging the wafer W by the imaging device for inspection. DETAILED DESCRIPTION OF THE INVENTION

[0008] In the manufacturing process of semiconductor devices and the like, a resist pattern is formed on the substrate by sequentially performing a resist coating process in which a resist solution is applied to a substrate such as a semiconductor wafer (hereinafter referred to as a "wafer") to form a resist film, an exposure process in which the resist film is exposed to light, and a development process in which the exposed resist film is developed. After the resist pattern formation process, a layer to be etched is then etched using this resist pattern as a mask, and a predetermined pattern is formed in the layer to be etched. Note that when forming the resist pattern, a film other than the resist film may be formed below the resist film.

[0009] Furthermore, when forming a resist pattern or when etching using the resist pattern as described above, the substrate may be subjected to inspections such as defect inspection. In defect inspections, for example, whether the resist pattern is properly formed or whether foreign matter is attached to the substrate may be inspected. In recent years, captured images of the surface of the substrate may be used in such inspections as defect inspections.

[0010] However, since the captured image of the substrate is affected by the condition of the layers below the top layer of the substrate, i.e., the base, color unevenness, i.e., brightness unevenness, may occur even if the substrate is in a normal state. Depending on the inspection method, such unevenness may be determined to be an abnormality, making it impossible to perform an accurate inspection. In other words, it may not be possible to properly determine whether the unevenness in the captured image of the substrate is due to an abnormality in the substrate or is within the normal range that does not cause problems in terms of process performance.

[0011] The technology according to the present disclosure is intended to accurately perform inspection based on a captured image of a substrate even when the captured image has unevenness.

[0012] Hereinafter, an information processing method and an information processing device according to the present embodiment will be described with reference to the drawings. In this specification and the drawings, elements having substantially the same functional configurations are designated by the same reference numerals, and redundant description will be omitted.

[0013] <Wafer Processing System 1> Fig. 1 is an explanatory diagram showing an outline of the internal configuration of a wafer processing system as a substrate processing system including a control device as an information processing device according to this embodiment. Fig. 2 and Fig. 3 are diagrams showing an outline of the internal configuration of the front side and rear side, respectively, of the wafer processing system 1. Note that in this embodiment, an example will be described in which the wafer processing system 1 is a coating and developing processing system that performs photolithography processing on a wafer W as a substrate.

[0014] 1, the wafer processing system 1 includes a cassette station 2 where, for example, a cassette C is transferred in and out from the outside, and a processing station 3 equipped with various processing devices that perform predetermined processes on wafers W. The wafer processing system 1 has a configuration in which the cassette station 2, the processing station 3, and an interface station 5 that transfers the wafers W between them and an exposure device 4 adjacent to the processing station 3 are integrally connected. The wafer processing system 1 also includes a control device 6 that controls the wafer processing system 1.

[0015] The cassette station 2 is divided into, for example, a cassette loading / unloading section 10 and a wafer transport section 11. For example, the cassette loading / unloading section 10 is provided at the end of the wafer processing system 1 on the negative side in the Y direction (the left side in FIG. 1). The cassette loading / unloading section 10 is provided with a cassette mounting table 12. A plurality of, for example, four mounting plates 13 are provided on the cassette mounting table 12. The mounting plates 13 are arranged in a row in the horizontal X direction (the up and down direction in FIG. 1). The cassettes C can be placed on these mounting plates 13 when they are loaded or unloaded from or to the outside of the wafer processing system 1.

[0016] The wafer transfer section 11 is provided with a wafer transfer device 21 that is movable on a transfer path 20 that extends in the X direction (the vertical direction in FIG. 1). The wafer transfer device 21 is also movable in the vertical direction and around the vertical axis (the θ direction), and can transfer wafers W between cassettes C on each mounting plate 13 and a transfer device in the third block G3 of the processing station 3, which will be described later.

[0017] The processing station 3 is provided with multiple blocks, for example, four blocks G1, G2, G3, and G4, each equipped with various devices. For example, a first block G1 is provided on the front side of the processing station 3 (the negative side in the X direction in FIG. 1), and a second block G2 is provided on the back side of the processing station 3 (the positive side in the X direction in FIG. 1). A third block G3 is provided on the cassette station 2 side of the processing station 3 (the negative side in the Y direction in FIG. 1), and a fourth block G4 is provided on the interface station 5 side of the processing station 3 (the positive side in the Y direction in FIG. 1).

[0018] In the first block G1, a plurality of liquid treatment devices are arranged as shown in Fig. 2. Specifically, in the first block G1, for example, a development treatment device 30, a lower anti-reflection coating formation device 31, a resist coating device 32, and an upper anti-reflection coating formation device 33 are arranged in this order from the bottom.

[0019] The developing treatment device 30 performs a developing treatment on the wafer W. The bottom anti-reflection film forming apparatus 31 forms an anti-reflection film (hereinafter referred to as a “bottom anti-reflection film”) below the resist film of the wafer W. The resist coating device 32 coats the wafer W with a resist liquid to form a resist film. The top anti-reflection film forming device 33 forms an anti-reflection film on the top layer of the resist film of the wafer W (hereinafter referred to as “top anti-reflection film”).

[0020] Each of the liquid processing apparatuses 30 to 33 in the first block G1 has a plurality of cups F1 arranged in the horizontal direction for accommodating wafers W during processing, and can process a plurality of wafers W in parallel. In liquid processing apparatuses 30-33, a predetermined processing liquid is applied onto wafer W by, for example, spin coating. In spin coating, processing liquid is ejected onto wafer W from, for example, a coating nozzle (not shown), and wafer W is rotated to spread the processing liquid over the surface of wafer W. In addition to cup F1, each of liquid processing apparatuses 30-33 is provided with a spin chuck F2 as a rotary holder that holds and rotates wafer W. In addition, cup F1 can collect processing liquid and the like that is shaken off from wafer W during rotation.

[0021] 3, the second block G2 is provided with a heat treatment device 40 that performs heating and cooling treatments on the wafer W, an adhesion device 41 as a hydrophobization treatment device that hydrophobizes the wafer W, and a peripheral exposure device 42 that exposes the peripheral portion of the wafer W, which are arranged in a vertical and horizontal direction. The number and arrangement of the heat treatment devices 40, adhesion devices 41, and peripheral exposure devices 42 can be selected arbitrarily.

[0022] In the third block G3, a plurality of transfer devices 50, 51, 52, 53, 54 are provided in order from the bottom, and above them, inspection imaging devices 55, 56, 57 are provided in order from the bottom. In addition, in the fourth block G4, a plurality of transfer devices 60, 61, 62 are provided in order from the bottom, and above them, inspection imaging devices 63, 64 are provided in order from the bottom.

[0023] 1, the area surrounded by the first block G1 to the fourth block G4 forms a wafer transfer area R. In the wafer transfer area R, for example, a wafer transfer device 70 is disposed.

[0024] The wafer transfer device 70 has a transfer arm 70a that is movable in, for example, the Y direction, the front-rear direction, the θ direction, and the up-down direction. The wafer transfer device 70 moves within the wafer transfer region R and can transfer the wafer W to predetermined devices in the surrounding first block G1, second block G2, third block G3, and fourth block G4. For example, as shown in FIG. 3, a plurality of wafer transfer devices 70 are arranged one above the other, and can transfer the wafer W to predetermined devices at approximately the same height in each of the blocks G1 to G4.

[0025] In addition, the wafer transfer region R is provided with a shuttle transfer device 80 that transfers the wafer W linearly between the third block G3 and the fourth block G4.

[0026] Shuttle transfer device 80 is movable linearly, for example, in the Y direction in Fig. 3. Shuttle transfer device 80 moves in the Y direction while supporting a wafer W, and can transfer the wafer W between delivery device 52 in the third block G3 and delivery device 62 in the fourth block G4.

[0027] 1, a wafer transfer device 90 is provided on the positive side of the third block G3 in the X direction. The wafer transfer device 90 has a transfer arm 90a that is movable, for example, in the front-to-rear direction, the θ direction, and the up-and-down direction. The wafer transfer device 90 moves up and down while supporting a wafer W, and can transfer the wafer W to each delivery device in the third block G3.

[0028] The interface station 5 is provided with a wafer transfer device 100. The wafer transfer device 100 has a transfer arm 100a that is movable, for example, in the front-to-back direction, the θ direction, and the up-and-down direction. The wafer transfer device 100 supports a wafer W on the transfer arm 100a, for example, and can transfer the wafer W to each delivery device and exposure device 4 in the fourth block G4.

[0029] The control device 6 includes a computer equipped with a processor such as a CPU, a memory, a communication interface, and the like, and has a program storage unit (not shown). The program storage unit stores programs containing instructions for controlling the operation of the drive systems of the various processing devices and transport devices described above to realize predetermined functions of the wafer processing system 1, such as applying resist liquid to the wafer W, developing, heating, transferring the wafer W, imaging the wafer W, and controlling each device. In addition, the program storage unit also stores programs containing instructions for information processing for inspecting the wafer W (e.g., information processing based on the imaging results of the wafer W by the inspection imaging devices 55, 56, 57, 63, and 64). That is, the program storage unit also stores a program that runs on the computer of the control device 6 of the wafer processing system 1 and controls an information processing method based on the imaging results of the wafer W by the inspection imaging devices 55, 56, 57, 63, and 64. The above program may be recorded on a computer-readable storage medium M and installed into the control device 6 from the storage medium M. The storage medium M may be temporary or non-temporary. Furthermore, part or all of the program may be realized by dedicated hardware (circuit board).

[0030] <Inspection imaging device 55> Next, a description will be given of the configuration of the inspection imaging device 55. Figures 4 and 5 are a cross-sectional view and a longitudinal-sectional view, respectively, showing the outline of the configuration of the inspection imaging device 55.

[0031] The inspection imaging device 55 has a casing 110 as shown in Fig. 4. A mounting table 120 on which a wafer W is placed is provided within the casing 110 as shown in Fig. 5. The mounting table 120 can be rotated and stopped freely by a rotation drive unit 121 such as a motor. A guide rail 122 extending from one end side (the negative side in the X direction in Fig. 5) to the other end side (the positive side in the X direction in Fig. 5) within the casing 110 is provided on the bottom surface of the casing 110. The mounting table 120 and the rotation drive unit 121 are provided on the guide rail 122 and can be moved along the guide rail 122 by a drive unit 123.

[0032] An imaging unit 130 is provided on the side surface at the other end (the positive side in the X direction in FIG. 5 ) inside the casing 110. For example, a wide-angle CCD camera is used for the imaging unit 130, and the bit number of the image is, for example, 8 bits (256 gradations from 0 to 255). A half mirror 131 is provided near the center of the upper part of the casing 110. The half mirror 131 is provided in a position facing the imaging unit 130, with the mirror surface tilted 45 degrees upward toward the imaging unit 130 from a position facing vertically downward. An illumination unit 132 is provided above the half mirror 131. The half mirror 131 and the illumination unit 132 are fixed to the upper surface inside the casing 110. Illumination from the illumination unit 132 passes through the half mirror 131 and is directed downward. Therefore, light reflected by an object below the illumination unit 132 is further reflected by the half mirror 131 and captured by the imaging unit 130. That is, the imaging section 130 can capture an image of an object in the area illuminated by the illumination section 132. The imaging result by the imaging section 130 is input to the control device 6.

[0033] The configurations of the inspection imaging devices 56, 57, 63, and 64 are similar to the configuration of the inspection imaging device 55 described above, and therefore a description thereof will be omitted.

[0034] <Control device 6> Fig. 6 is a functional block diagram of the control device 6 related to inspection in the wafer processing system 1. Figs. 7 and 8 are each a diagram showing an example of a captured image of the wafer W. Fig. 9 is a diagram showing an example of a two-dimensional histogram created by a creation unit described later. Fig. 10 is a diagram showing an example of a luminance value distribution described later. Fig. 11 is a diagram showing an example of a specific unevenness distribution described later.

[0035] As shown in FIG. 6, the control device 6 has an acquisition unit 201, a creation unit 202, an extraction unit 203, and a judgment unit 204, which are realized by a processor such as a CPU reading and executing a program stored in a memory unit (not shown). In one embodiment, the control device 6 includes a database 210, which is described below.

[0036] The acquiring unit 201 acquires a captured image of the wafer W based on the imaging results of the wafer W by the inspection imaging devices 55, 56, 57, 63, and 64. Specifically, the acquiring unit 201 performs necessary image processing on the image captured by the imaging unit 130 of the inspection imaging devices 55, 56, 57, 63, and 64, for example, and thereby generates an image showing the entire surface of the wafer W as the captured image of the wafer W.

[0037] Note that wafers W are often subjected to processes involving rotation of the wafer W, such as spin coating processes and polishing processes on the backside of the wafer W. Therefore, as shown in FIG. 7, a captured image Im of the wafer W may exhibit an annular irregularity M1 centered on the center of the wafer W or concentric irregularities, even if the wafer W is in a normal state. Furthermore, as shown in FIG. 8, a captured image Im of the wafer W may exhibit non-concentric annular and non-concentric irregularities (i.e., heterogeneous irregularities) M2 and M3. However, even if the shapes of the irregularities M2 and M3 are non-concentric annular and non-concentric, the irregularities M2 and M3 do not necessarily indicate that the irregularities M2 and M3 are caused by an abnormal state of the wafer W. For example, of the irregularities M2 and M3, only the irregularity M2 may be caused by an abnormal state of the wafer W. In this case, in an inspection based on the captured image Im, it is necessary to obtain different inspection results for the portion of the captured image Im corresponding to the irregularity M2 and the portion of the captured image Im corresponding to the irregularity M3. For this purpose, the following creating unit 202, extracting unit 203 and determining unit 204 are provided.

[0038] The creation unit 202 creates a two-dimensional histogram H for the captured image of the wafer W acquired by the acquisition unit 201, with the axes being the distance r from the center of the wafer W (i.e., the radial position from the center of the wafer W) and the brightness value V, as shown in Figure 9.

[0039] The extraction unit 203 extracts a specific unevenness distribution D from the two-dimensional histogram H created by the creation unit 202 based on a predetermined region definition. The specific unevenness distribution D is a distribution corresponding to the heterogeneous unevenness M2 and M3 described above in the captured image Im of the wafer W.

[0040] 10 from the two-dimensional histogram H created by the creation unit 202. The brightness value distribution VD1 is a distribution obtained by projecting the two-dimensional histogram H created by the creation unit 202 onto a two-dimensional plane whose axes are the distance (radial position) r from the center of the wafer W and the brightness value V. In other words, the extraction unit 203 performs a binarization process on the two-dimensional histogram H created by the creation unit 202 to acquire the brightness value distribution VD1. The area around the most frequent value Vm of the brightness value V at each radial position of the brightness value distribution VD1 is considered to correspond to the annular unevenness M1 or concentric unevenness centered on the center of the wafer W, which occurs even when the wafer W is in a normal state.

[0041] Therefore, the extraction unit 203 performs an inversion process on the luminance value distribution VD1 in the luminance value axis direction using the most frequent luminance value as a reference. For example, as shown in FIG. 11 , the extraction unit 203 performs an inversion process on the luminance value distribution VD1 around an axis P indicating the most frequent luminance value in the luminance value distribution VD1, thereby obtaining a luminance value distribution VD2 after the inversion process. In this embodiment, the overlapping portion VD3 between the luminance value distribution VD1 before the inversion process and the luminance value distribution VD2 after the inversion process is considered to correspond to the annular unevenness M1 or concentric unevenness centered on the center of the wafer W, which occurs even when the wafer W is in a normal state. Therefore, the overlapping portion VD3 between the luminance value distribution VD1 before the inversion process and the luminance value distribution VD2 after the inversion process is not particularly necessary for inspection, and therefore the extraction unit 203 extracts, as the specific unevenness distribution D, portions VD4 and VD5 that do not overlap between the luminance value distribution VD1 before the inversion process and the luminance value distribution VD2 after the inversion process. In other words, the extraction unit 203 extracts, as the specific unevenness distribution D, portions VD4 and VD5 of the brightness value distribution VD1 before the inversion process that do not overlap with the brightness value distribution VD2 after the inversion process.

[0042] In addition, during the inversion process, the extraction unit 203 may perform inversion process in the brightness value axis direction for each divided area obtained by dividing the brightness value distribution VD1 in the radial direction of the wafer W (the distance direction from the center of the wafer W), based on the most frequent brightness value in that divided area.

[0043] The determination unit 204 acquires the feature amount of the specific unevenness distribution D extracted by the extraction unit 203 (hereinafter, the specific unevenness distribution D extracted by the extraction unit 203 may be referred to as the extracted unevenness distribution De), and determines the type of the extracted unevenness distribution De based on the feature amount. Specifically, the determination unit 204 determines whether the extracted unevenness distribution De corresponds to unevenness when the state of the wafer W is normal, i.e., normal unevenness, or unevenness when the state of the wafer W is abnormal, i.e., abnormal unevenness. Abnormal unevenness is, for example, unevenness caused by a defect.

[0044] Moreover, the feature amount of the specific unevenness distribution D is specifically a feature amount relating to the shape of the specific unevenness distribution D. The feature amount relating to the shape of the specific unevenness distribution D is, for example, the following (A) to (I). (A) Center of gravity of specific unevenness distribution D (B) Coordinates of the rectangle circumscribing the specific unevenness distribution D (C) Area of specific unevenness distribution D (D) Perimeter of specific unevenness distribution D (E) Width of specific uneven distribution D in the luminance value axis direction (F) the radial width of the specific unevenness distribution D, (G) Average luminance value of specific unevenness distribution D (H) Irregularity of the outline of the specific unevenness distribution D (I) Edge histogram of specific unevenness distribution D

[0045] In one embodiment, the determining unit 204 determines the type of the extracted unevenness distribution De by referring to the database 210. The database 210 stores (i.e., registers) in advance, for each specific unevenness distribution D extracted from a past captured image of the wafer W, whether the specific unevenness distribution D corresponds to normal unevenness or abnormal unevenness. Hereinafter, the specific unevenness distribution D stored in advance in the database 210 may be referred to as a registered unevenness distribution Dr. In addition, the database 210 stores, for example, feature quantities of the registered unevenness distribution Dr for each registered unevenness distribution Dr.

[0046] The determination unit 204 identifies the registered unevenness distribution Dr that is most similar to the extracted unevenness distribution De based on the feature amount. For example, the determination unit 204 refers to the database 210, calculates the similarity of each registered unevenness distribution Dr to the extracted unevenness distribution De based on the feature amount, and identifies the registered unevenness distribution Dr that has the highest similarity. The feature amount used to calculate the similarity may be, for example, any two or more of the feature amounts (A) to (I) related to the shape of the specified unevenness distribution D described above. Furthermore, the similarity may be calculated using, for example, Euclidean distance, Mahalanobis distance, Manhattan distance, Minkowski distance, or cosine similarity.

[0047] The determination unit 204 then determines whether the extracted unevenness distribution De corresponds to normal unevenness or abnormal unevenness based on whether the registered unevenness distribution Dr that is most similar to the extracted unevenness distribution De (i.e., has the highest similarity) is registered in the database 210 as corresponding to normal unevenness or abnormal unevenness. If the most similar registered unevenness distribution Dr is registered as corresponding to normal unevenness, the determination unit 204 determines that the extracted unevenness distribution De corresponds to normal unevenness. On the other hand, if the most similar registered unevenness distribution Dr is registered as corresponding to abnormal unevenness, the determination unit 204 determines that the extracted unevenness distribution De corresponds to abnormal unevenness.

[0048] As shown in the figure, the control device 6 may further include a registration unit 205 that is realized by a processor such as a CPU reading and executing a program stored in a storage unit (not shown). The registration unit 205 registers the determination result by the determination unit 204 in the database 210. Specifically, the registration unit 205 stores the specific unevenness distribution D extracted by the extraction unit 203 in the database 210 together with the feature extracted from the specific unevenness distribution D by the determination unit 204 and the determination result by the determination unit 204 for the specific unevenness distribution D. When the registration unit 205 has registered, the determination unit 204 subsequently makes a determination by referring to the database 210 in which the determination results from the previous and previous determinations by the determination unit 204 are registered.

[0049] <Wafer processing> Next, the wafer processing performed in the wafer processing system 1 will be described.

[0050] First, a cassette C containing a plurality of wafers W is carried into the cassette station 2. Then, under the control of the control device 6, the wafers W in the cassette C are carried to the inspection imaging device 55 in the third block G3. Then, the wafers W before various films such as a bottom anti-reflection film are formed, i.e., in an initial state, are imaged by the imaging unit 130. The imaging result is output to the control device 6.

[0051] Next, the wafer W is transferred to the lower anti-reflection film forming apparatus 31 in the first block G1, where a lower anti-reflection film is formed on the wafer W. Subsequently, the wafer W is transferred to the heat treatment device 40 for the lower anti-reflection film in the second block G2, where the heat treatment of the lower anti-reflection film is performed. Thereafter, the wafer W is transferred to the inspection imaging device 63. Then, the imaging unit 130 images the wafer W after the formation of the lower anti-reflection film. The imaging result is output to the control device 6.

[0052] Next, the wafer W is transferred to the resist coating unit 32 in the first block G1, where a resist film is formed on the lower anti-reflection film of the wafer W. Subsequently, the wafer W is transferred to the heat treatment device 40 for PAB treatment in the second block G2, where the PAB treatment is performed. Thereafter, the wafer W is transferred to the inspection imaging device 56. Then, the imaging unit 130 images the wafer W after the resist film is formed. The imaging result is output to the control device 6.

[0053] Next, the wafer W is transferred to the top anti-reflection coating forming device 33 in the first block G1, where a top anti-reflection coating is formed on the resist film of the wafer W. Subsequently, the wafer W is transferred to the heat treatment device 40 for the top anti-reflection coating in the second block G2, where the heat treatment of the top anti-reflection coating is performed. Thereafter, the wafer W is transferred to the inspection imaging device 64. Then, the imaging unit 130 images the wafer W after the top anti-reflection coating is formed. The imaging result is output to the control device 6.

[0054] Next, the wafer W is transferred to the exposure apparatus 4 and exposed to a desired pattern. Subsequently, the wafer W is transferred to the heat treatment device 40 for PEB treatment in the second block G2, where the PEB treatment is performed. Next, the wafer W is transferred to the developing treatment device 30 in the first block G1, where the developing treatment is carried out, and a resist pattern is formed on the wafer W. Thereafter, the wafer W is transferred to the inspection imaging device 57. Then, the imaging unit 130 images the wafer W after the resist pattern is formed. The imaging result is output to the control device 6.

[0055] Then, the wafer W is returned to the cassette C, completing a series of wafer processing steps. Thereafter, the above-described wafer processing steps are carried out on the other wafers W.

[0056] <Information processing and registration method in database 210> Next, we will explain information processing for inspecting the wafer W, including information processing based on the imaging results of the wafer W by the inspection imaging devices 55, 56, 57, 63, and 64, and a method for registering the specific unevenness distribution D in the database 210 before the information processing based on the imaging results. First, a method for registering in advance in the database 210 will be described with reference to Fig. 12. Fig. 12 is a flowchart showing the flow of a method for registering the specific unevenness distribution D in the database 210 in advance of the information processing based on the imaging results.

[0057] The specific unevenness distribution D is registered in advance in the database 210 using, for example, a control device (not shown) external to the wafer processing system 1. First, an external control device, similar to the above-described acquisition unit 201, acquires an image of the wafer W based on the imaging results of the wafer W by an inspection imaging device (not shown) similar to the inspection imaging devices 55, 56, 57, 63, and 64 (step S1).

[0058] Next, an external control device, in the same manner as the aforementioned creation unit 202, creates a two-dimensional histogram H for the captured image of the wafer W acquired in step S1, with the axes being the distance r from the center of the wafer W and the brightness value V (step S2).

[0059] Next, an external control device extracts a specific unevenness distribution D from the two-dimensional histogram H created in step S2 based on a predetermined region definition, in the same manner as the above-mentioned extraction unit 203 (step S3).

[0060] Thereafter, the external control device acquires the feature amount of the specific unevenness distribution D extracted in step S3 in the same manner as the above-described determination unit 204 (step S4). Then, for example, the captured image of the wafer W acquired in step S1 and the specific unevenness distribution extracted in step S3 are displayed on a display device (not shown). After that, an operator who has checked the contents displayed on the display device inputs via an input device such as a keyboard, a mouse, or a touch panel whether the specific unevenness distribution extracted in step S3 corresponds to normal unevenness or abnormal unevenness.

[0061] In response to an input from an operator via an input unit (not shown), the external control device registers information regarding the specific unevenness distribution D extracted in step S3, indicating whether the specific unevenness distribution corresponds to normal unevenness or abnormal unevenness, in the database 210 (step S5). At this time, the external control device also links the feature amount acquired in step S4 for the specific unevenness distribution to the specific unevenness distribution and registers it in the database 210. In addition, the external control device may also link and register in the database 210 wafer identification information (ID), lot identification information (ID), and device identification information (ID) for the wafer W from which the specific unevenness distribution was acquired from the captured image. The device identification information (ID) corresponds to information about the underlying film of the imaged wafer W (e.g., the type of underlying film, the number of layers of the underlying film, etc.). The above steps S1 to S5 are performed for each of the plurality of wafers W.

[0062] Next, information processing for inspecting the wafer W, including information processing based on the imaging results of the wafer W by the inspection imaging device 56 of the wafer processing system 1, will be described with reference to Fig. 13. Fig. 13 is a flowchart showing the flow of information processing for inspecting the wafer W, including information processing based on the imaging results of the wafer W by the inspection imaging device 56.

[0063] The acquisition unit 201 of the control device 6 of the wafer processing system 1 acquires an image of the wafer W based on the imaging result of the wafer W after the resist film is formed by the inspection imaging device 56 (step S11).

[0064] Next, the creation unit 202 of the control device 6 creates a two-dimensional histogram H with axes representing the distance r from the center of the wafer W and the brightness value V for the captured image of the wafer W after the resist film formation, acquired by the acquisition unit 201 (step S12). A radial image may be used to create this two-dimensional histogram H. A radial image is an image in which brightness values monotonically increase or decrease linearly from a portion corresponding to the center of the wafer W toward the radially outward direction, and the brightness values of the radial image correspond to the radial position of the wafer W. Here, the coordinates of the portion of the captured image of the wafer W where the wafer W exists are defined as point (xn, yn). The two-dimensional histogram H can be obtained by plotting (the brightness value of point (xn, yn) in the captured image of the wafer W and the brightness value of (xn, yn) in the radial image) for all points (xn, yn) in a three-dimensional space with axes representing the distance r from the center of the wafer W, the brightness value V, and the frequency. In this way, the two-dimensional histogram H can be easily created by using concentric images.

[0065] Next, the extraction unit 203 of the control device 6 extracts a specific unevenness distribution D from the two-dimensional histogram H created by the creation unit 202 based on a predetermined region definition (step S13). Specifically, for example, the extraction unit 203 obtains the above-mentioned brightness value distribution VD1 from the two-dimensional histogram H created by the creation unit 202. The extraction unit 203 also performs an inversion process on the brightness value distribution VD1 about an axis P indicating the most frequent brightness value in the brightness value distribution VD1, thereby obtaining a brightness value distribution VD2 after the inversion process. The extraction unit 203 then extracts, as the specific unevenness distribution D, a portion of the brightness value distribution VD1 before the inversion process that does not overlap with the brightness value distribution VD2 after the inversion process. Note that the extraction unit 203 may extract one or more specific unevenness distributions.

[0066] Thereafter, the determination unit 204 acquires the feature amount of the specific unevenness distribution D extracted by the extraction unit 203, that is, the extracted unevenness distribution De, and determines the type of the extracted unevenness distribution De based on the feature amount (step S14).

[0067] Specifically, the determination unit 204 acquires, for each extracted unevenness distribution De, all of the above-mentioned feature amounts (A) to (I) related to the shape of the extracted unevenness distribution De. Hereinafter, the feature amounts (A) to (I) are collectively referred to as a feature group.

[0068] Next, the determination unit 204 identifies, for each extracted unevenness distribution De, the specific unevenness distribution D registered in the database 210, i.e., the registered unevenness distribution Dr, that is most similar to the extracted unevenness distribution De, based on a group of features related to the shape of the extracted unevenness distribution De extracted by the determination unit 204. For example, the determination unit 204 refers to the database 210 and calculates, for each registered unevenness distribution Dr, a similarity to the extracted unevenness distribution De based on the group of features, and identifies the registered unevenness distribution Dr with the highest similarity. For example, the calculation of the similarity based on the group of similarities uses the Euclidean distance, Mahalanobis distance, Manhattan distance, or Minkowski distance from the group of features related to the shape of the extracted unevenness distribution De to the group of features related to the shape of the registered unevenness distribution Dr.

[0069] The calculation of the similarity may be performed for all registered unevenness distributions Dr, or may be performed only for the registered unevenness distributions Dr that correspond to the wafer ID, lot ID, or device ID of the wafer W to be inspected.

[0070] The determination unit 204 then determines whether the extracted unevenness distribution De corresponds to normal unevenness or abnormal unevenness, based on whether the registered unevenness distribution Dr with a high degree of similarity corresponds to normal unevenness or abnormal unevenness, as registered in the database 210. The determination result by the determination unit 204 may be displayed on a display device (not shown) such as a liquid crystal display panel.

[0071] In addition, if the feature value of the acquired extracted unevenness distribution De is not within a predetermined range and indicates an abnormal value, the judgment unit 204 may determine that the extracted unevenness distribution De corresponds to abnormal unevenness without calculating the similarity. Furthermore, even when the extracted unevenness distribution De is not continuous with the portion VD3 where the brightness value distribution VD1 before the inversion process and the brightness value distribution VD2 after the inversion process overlap (i.e., when the extracted unevenness distribution De exists in isolation), the determination unit 204 may determine that the extracted unevenness distribution De corresponds to abnormal unevenness without calculating the similarity. The determination unit 204 may also determine that the extracted unevenness distribution De corresponds to abnormal unevenness without calculating the similarity not only when the extracted unevenness distribution De is not continuous with the portion VD3 where the brightness value distribution VD1 before the inversion process and the brightness value distribution VD2 after the inversion process overlap, but also when the distance from the extracted unevenness distribution De to the portion VD3 is equal to or greater than a predetermined value. In these cases, it is not necessary to calculate the similarity, nor is it necessary to extract feature quantities of the extracted unevenness distribution De; however, the feature quantities may be extracted.

[0072] After the determination by the determination unit 204, the registration unit 205 registers the determination result by the determination unit 204 in the database 210 (step S15). Specifically, the registration unit 205 stores the specific unevenness distribution D extracted by the extraction unit 203 in the database 210 together with the feature extracted from the specific unevenness distribution D by the determination unit 204 and the determination result by the determination unit 204 for the specific unevenness distribution D. Furthermore, the registration unit 205 may also store in the database 210 the wafer ID, lot ID, and device ID related to the wafer W to be determined, i.e., the wafer W to be inspected, in association with the specific unevenness distribution D. If an operator who has checked the determination result by the determination unit 204 finds that the determination result is incorrect, the determination result by the determination unit 204 is rewritten by the operator and then registered in the database 210.

[0073] The information processing for inspecting the wafer W, including the information processing based on the imaging results of the wafer W by the inspection imaging devices 55, 57, 63, and 64, is similar to the information processing for inspecting the wafer W, including the information processing based on the imaging results of the wafer W by the inspection imaging device 56 described above.

[0074] <Major Effects> As described above, the information processing method according to this embodiment processes information for inspecting a substrate based on a captured image of the substrate. The method includes an acquisition step of acquiring the captured image of the substrate and a creation step of creating a two-dimensional histogram H for the captured image of the substrate, the two-dimensional histogram H having axes representing distance from the center of the substrate and brightness value. The information processing method according to this embodiment also includes an extraction step of extracting a specific unevenness distribution D corresponding to heterogeneous unevenness (i.e., non-concentric annular and non-concentric circular unevenness) in the captured image from the two-dimensional histogram H created in the creation step based on a predetermined region definition. In this extraction step, portions of the two-dimensional histogram H corresponding to annular unevenness M1 or concentric circular unevenness that may occur even when the wafer W is in a normal state are not extracted. The information processing method according to this embodiment also includes a determination step of acquiring feature quantities of the specific unevenness distribution D extracted in the extraction step and determining the type of the specific unevenness distribution D based on the feature quantities. Therefore, according to this embodiment, it is possible to suppress determination of annular unevenness M1 or concentric unevenness occurring in a captured image of the wafer W as abnormal unevenness even when the wafer W is in a normal state. In other words, according to this embodiment, even when unevenness occurs in the captured image of the wafer W, inspection based on the captured image can be performed more accurately.

[0075] Furthermore, conventionally, a captured image of the wafer W is directly subjected to binarization processing, and an abnormality determination is performed on an area extracted from the image after the binarization processing. In contrast, in this embodiment, a two-dimensional histogram H with the radial position r as its axis is first created from the captured image of the wafer W, and then a binarization process is performed on the two-dimensional histogram H to generate a brightness value distribution VD1. An abnormality determination is then performed on a region extracted from this brightness value distribution VD1, i.e., a specific unevenness distribution D. Therefore, in this embodiment, unlike conventional techniques, the region subject to abnormality determination includes information on the radial position r, which is important for unevenness determination. In other words, in this embodiment, the region subject to abnormality determination can be treated as a shape feature that takes into account the radial position r, which is important for unevenness determination. Therefore, according to this embodiment, the accuracy of inspection based on the captured image of the wafer W can be improved.

[0076] Furthermore, in the information processing method according to this embodiment, the determining step refers to a database in which, for each specific unevenness distribution D, it is determined whether the specific unevenness distribution corresponds to unevenness caused by defects or normal unevenness, and determines whether the extracted unevenness distribution De corresponds to unevenness caused by defects or normal unevenness. Therefore, it is possible to more accurately determine whether the extracted unevenness distribution corresponds to unevenness caused by defects or normal unevenness.

[0077] Furthermore, in the information processing method according to this embodiment, a brightness value distribution VD1 obtained by projecting a two-dimensional histogram H onto a predetermined two-dimensional plane is subjected to an inversion process in the brightness value axis direction using the most frequent brightness value as a reference, and a portion that does not overlap between the brightness value distribution VD1 before the inversion process and the brightness value distribution VD2 after the inversion process is extracted as the specific unevenness distribution D. Therefore, a portion in the brightness value distribution VD1 that should not be extracted as the specific unevenness distribution D can be excluded from the specific unevenness distribution D in accordance with the state of the captured image of the wafer W to be inspected.

[0078] <Other test examples> The inspection of the wafer W based on the captured image of the wafer W according to this embodiment may be performed in parallel with the conventional inspection of the wafer W based on the captured image of the wafer W.

[0079] <Another example of similarity calculation> In the example of the abnormality, the similarity was calculated for all the specific unevenness distributions D registered in the database 210, but since the specific unevenness distribution D is affected by the undersurface of the wafer W to be inspected, the similarity may be calculated only for the specific unevenness distribution D corresponding to the undersurface of the wafer W to be inspected. In this case, the undersurface of the wafer W to be inspected and the specific unevenness distribution registered in the database 210 correspond to which undersurface is determined based on, for example, the device ID.

[0080] <Regarding the color of the captured image of the wafer W> In the above, for the sake of simplicity, the captured image of the wafer W has been assumed to be monochromatic. However, the captured image of the wafer W is generally composed of the three primary colors of RGB (Red, Green, and Blue). Therefore, in practice, the information processing according to this embodiment is performed, for example, for each of R, G, and B. In this case, if the extracted unevenness distributions De overlap between RGB, the determination of normality / abnormality for the extracted unevenness distributions De is performed, for example, by majority voting. In other words, a determination result that is common to two or more of the three RGB colors is adopted.

[0081] Furthermore, the information processing according to this embodiment may be performed on only a portion of RGB, for example. In this case, which color to process the information on is determined based on, for example, at least one of the wafer ID, lot ID, and device ID associated with the wafer W to be inspected. Furthermore, in this case, instead of calculating the similarity for the specific unevenness distributions D of all colors registered in the database 210, the similarity may be calculated only for the specific unevenness distribution corresponding to the color to be processed. Which color the specific unevenness distribution registered in the database 210 corresponds to is determined based on, for example, at least one of the wafer ID, lot ID, and device ID.

[0082] <Other examples of features> In the above example, the determination unit 204 acquires feature quantities related to the shape of the specific unevenness distribution D as feature quantities of the specific unevenness distribution D. Alternatively, the determination unit 204 may extract feature quantities of the specific unevenness distribution D using a trained model. Specifically, the trained model is, for example, a trained convolutional neural network (CNN) such as Alexnet. In this case, for example, all outputs from a fully connected layer of the CNN model are used as feature quantities of the specific unevenness distribution D. As the feature amount of the specific unevenness distribution D, both the feature amount related to the shape of the specific unevenness distribution D and the feature amount extracted using the trained model may be used.

[0083] <Other variations> In the example of the abnormality, information processing for inspecting the wafer W, including information processing based on the imaging results of the wafer W, was performed by the control device 6 possessed by the wafer processing system 1, but it may also be performed by an information processing device external to the wafer processing system 1.

[0084] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive, and the above-described embodiments may be omitted, substituted, or modified in various ways without departing from the scope and spirit of the appended claims. [Explanation of symbols]

[0085] 6. Control device 201 Acquisition Department 202 Creation Department 203 Extraction part 204 Judgment section D Specific uneven distribution De Extraction unevenness distribution H Two-dimensional histogram Im Captured Image V Brightness value W wafer

Claims

1. 1. An information processing method for processing information for inspecting a substrate based on a captured image of the substrate, comprising: acquiring an image of the substrate; creating a two-dimensional histogram of the acquired image of the substrate, with the axes representing the distance from the center of the substrate and the brightness value; extracting a specific unevenness distribution corresponding to heterogeneous unevenness in the captured image from the two-dimensional histogram based on a predetermined region definition; acquiring a feature amount of the extracted specific unevenness distribution, and determining a type of the specific unevenness distribution based on the feature amount.

2. 2. The information processing method according to claim 1, wherein the determining step refers to a database in which, for each of the specific unevenness distributions, it is determined whether the specific unevenness distribution corresponds to unevenness caused by a defect or normal unevenness, and determines whether the specific unevenness distribution extracted in the extracting step corresponds to unevenness caused by a defect or normal unevenness.

3. The information processing method according to claim 2 , further comprising the step of registering a determination result in said determining step in said database.

4. 4. The information processing method according to claim 3, wherein the determining step refers to the database in which determination results from previous or previous determining steps are registered.

5. The information processing method according to any one of claims 1 to 4, wherein the extraction step performs an inversion process in a luminance value axis direction based on the most frequent value of the luminance value on a luminance value distribution obtained by projecting the two-dimensional histogram onto a two-dimensional plane whose axes are the distance from the center of the substrate and the luminance value, and extracts, as the specific unevenness distribution, a portion where the luminance value distribution before the inversion process and the luminance value distribution after the inversion process do not overlap.

6. 5. The information processing method according to claim 1, wherein the determining step acquires a feature amount relating to the shape of the specific unevenness distribution as the feature amount of the specific unevenness distribution.

7. The information processing method according to claim 1 , wherein the determining step extracts the feature amount of the specific unevenness distribution using a trained model.

8. A readable computer storage medium storing a program that runs on a computer of a control unit that controls the information processing method in order to cause an information processing device to execute the information processing method according to any one of claims 1 to 4.

9. An information processing device that processes information for inspecting a substrate based on a captured image of the substrate, an acquisition unit that acquires a captured image of the substrate; a creation unit that creates a two-dimensional histogram of the acquired captured image of the substrate, the histogram being based on the distance from the center of the substrate and the brightness value; an extracting unit that extracts a specific unevenness distribution corresponding to heterogeneous unevenness in the captured image from the two-dimensional histogram based on a predetermined region definition; and a determination unit that acquires a feature amount of the extracted specific unevenness distribution and determines a type of the specific unevenness distribution based on the feature amount.

10. 10. The information processing apparatus according to claim 9, wherein the determination unit refers to a database in which, for each of the specific unevenness distributions, it is determined whether the specific unevenness distribution corresponds to unevenness caused by a defect or normal unevenness, and determines whether the specific unevenness distribution extracted in the extraction step corresponds to unevenness caused by a defect or normal unevenness.

11. The information processing apparatus according to claim 10 , further comprising a registration unit that registers the determination result by said determination unit in said database.

12. The information processing apparatus according to claim 11 , wherein the determination unit refers to the database in which determination results from the determination unit before the last time are registered.

13. The information processing device according to any one of claims 9 to 12, wherein the extraction unit performs an inversion process in a luminance value axis direction based on a most frequent value of the luminance values for a luminance value distribution obtained by projecting the two-dimensional histogram onto a two-dimensional plane whose axes are a distance from a center of the substrate and a luminance value, and extracts a portion that does not overlap between the luminance value distribution before the inversion process and the luminance value distribution after the inversion process as the specific unevenness distribution.

14. 13. The information processing apparatus according to claim 9, wherein the determining unit acquires, as the feature amount of the specific unevenness distribution, a feature amount relating to the shape of the specific unevenness distribution.

15. The information processing device according to claim 9, wherein the determining unit extracts the feature amount of the specific unevenness distribution using a trained model.

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