Substrate treatment method, substrate treatment apparatus, lithography apparatus, and article production method

Abstract

To provide a technique advantageous for attaining both throughput and detection accuracy when detecting a position of a substrate.SOLUTION: A substrate treatment method for treating a substrate includes: a measurement step of measuring a light intensity distribution obtained from a peripheral part when irradiating the peripheral part of the substrate with light from a light source part; a specification step of specifying a plurality of candidates concerning a peripheral position of the substrate from the light intensity distribution by applying each of a plurality of types of algorithms to the light intensity distribution measured in the measurement step; and a selection step of selecting one algorithm used for determining a position of the substrate from the plurality of types of algorithms on the basis of the plurality of candidates specified in the specifying step.SELECTED DRAWING: Figure 9

Description

[Technical field]

[0001] The present invention relates to a substrate processing method, a substrate processing apparatus, a lithography apparatus, and a method for manufacturing an article. [Background technology]

[0002] In a lithography apparatus that forms a pattern on a substrate, a process (so-called pre-alignment process) is performed to detect the position of the substrate before the substrate is transported onto a stage that holds the substrate. In the pre-alignment process, the peripheral position of the substrate is detected based on the light intensity distribution obtained from the peripheral portion of the substrate when the peripheral portion is irradiated with light, and the position (orientation and center of gravity) of the substrate is determined based on the detected peripheral position of the substrate. This makes it possible to control the positioning of the substrate when it is transported onto the stage.

[0003] Patent Document 1 describes a method for detecting an edge of a bonded wafer including a wafer support substrate and a semiconductor wafer bonded to the surface of the wafer support substrate, using an edge detection unit having a light source and a line sensor. In the method described in Patent Document 1, in a predetermined case, switching is made between detecting the edge of the semiconductor wafer and detecting the edge of the wafer support substrate. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2011-181721 A Summary of the Invention [Problem to be solved by the invention]

[0005] There are several types of substrates on which the pre-alignment process is performed, such as transparent substrates, opaque substrates, and substrates on which several components are bonded. When the type of substrate changes, the tendency of the light intensity distribution obtained from the peripheral portion of the substrate may change. Therefore, in order to accurately detect the position of the substrate even when the type of substrate changes, it is necessary to appropriately select an algorithm for determining the position of the substrate from the light intensity distribution according to the type of substrate. However, in order to select an algorithm, performing the pre-alignment process including the process of measuring the light intensity distribution multiple times with different types of algorithms may be disadvantageous in terms of throughput. In other words, in the pre-alignment process, it is desired to achieve both throughput and detection accuracy when detecting the position of the substrate.

[0006] Therefore, an object of the present invention is to provide an advantageous technique for achieving both throughput and detection accuracy when detecting the position of a substrate. [Means for solving the problem]

[0007] In order to achieve the above-mentioned object, a substrate processing method as one aspect of the present invention is a substrate processing method for processing a substrate, comprising: a measurement step of measuring a light intensity distribution obtained from a peripheral portion of the substrate when light from a light source unit is irradiated onto the peripheral portion of the substrate; an identification step of identifying a plurality of candidates for the peripheral position of the substrate from the light intensity distribution by applying each of a plurality of types of algorithms to the light intensity distribution measured in the measurement step; and a selection step of selecting one algorithm to be used for determining a position of the substrate from the plurality of types of algorithms based on the plurality of candidates identified in the identification step.

[0008] Further objects and other aspects of the present invention will become apparent from the following description of preferred embodiments with reference to the accompanying drawings. Effect of the Invention

[0009] According to the present invention, for example, it is possible to provide an advantageous technique for achieving both throughput and detection accuracy when detecting the position of a substrate. [Brief description of the drawings]

[0010] [Figure 1] 1 is a schematic diagram showing a configuration example of a substrate processing apparatus; [Diagram 2] FIG. 13 is a diagram showing an example of detecting the peripheral position of a substrate; [Diagram 3] FIG. 13 is a diagram showing an example of detecting the peripheral position of a substrate; [Figure 4] FIG. 13 is a diagram showing an example of detecting the peripheral position of a substrate; [Diagram 5] FIG. 13 is a diagram showing an example of detecting the peripheral position of a substrate; [Figure 6] FIG. 13 is a diagram showing an example of detecting the peripheral position of a substrate; [Figure 7] FIG. 13 is a diagram showing an example of a position waveform representing the outline of a substrate and an ideal position waveform; [Figure 8] Diagram for explaining formula (1) [Figure 9] 1 is a flowchart showing an operation flow of a pre-alignment process according to a first embodiment; [Figure 10] FIG. 1 is a diagram for explaining an example of a method for selecting an optimal algorithm. [Figure 11] FIG. 1 is a diagram for explaining an example of a method for selecting an optimal algorithm. [Figure 12] FIG. 1 is a diagram for explaining an example of a method for selecting an optimal algorithm. [Figure 13] FIG. 13 is a diagram showing an example of a position waveform representing the outline of a substrate and an ideal position waveform; [Figure 14] 11 is a flowchart showing the operation flow of a pre-alignment process according to the second embodiment. [Figure 15] 13 is a flowchart showing the operation flow of a pre-alignment process according to the third embodiment. [Figure 16] FIG. 1 is a diagram showing an example of a notch waveform representing the outline of a notch in a substrate and an example of an ideal notch waveform. [Figure 17] 13 is a flowchart showing the operation flow of a pre-alignment process according to the fourth embodiment. [Figure 18]Schematic diagram showing an example of the configuration of an exposure apparatus DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, the embodiments will be described in detail with reference to the attached drawings. Note that the following embodiments do not limit the invention according to the claims. Although the embodiments describe a number of features, not all of these features are essential to the invention, and the features may be combined in any manner. Furthermore, in the attached drawings, the same reference numbers are used for the same or similar configurations, and duplicated descriptions are omitted.

[0012] In this specification and the attached drawings, unless otherwise specified, directions are shown in an XYZ coordinate system in which the direction parallel to the holding surface for holding a substrate by a substrate chuck 111 described later is the XY plane. The directions parallel to the X-axis, Y-axis, and Z-axis in the XYZ coordinate system are the X-direction, Y-direction, and Z-direction, respectively, and the rotation around the X-axis, the rotation around the Y-axis, and the rotation around the Z-axis are θX, θY, and θZ, respectively. Control or drive regarding the X-axis, Y-axis, and Z-axis means control or drive regarding the direction parallel to the X-axis, the direction parallel to the Y-axis, and the direction parallel to the Z-axis, respectively. Furthermore, control or drive regarding the θX-axis, θY-axis, and θZ-axis means control or drive regarding the rotation around an axis parallel to the X-axis, the rotation around an axis parallel to the Y-axis, and the rotation around an axis parallel to the Z-axis, respectively. Furthermore, the position is information that can be specified based on the coordinates of the X-axis, Y-axis, and Z-axis, and the attitude is information that can be specified by the values ​​of the θX-axis, θY-axis, and θZ-axis.

[0013] First Embodiment A first embodiment of the present invention will be described. Fig. 1 is a schematic diagram showing an example of the configuration of a substrate processing apparatus 100 according to the present embodiment. The substrate processing apparatus 100 according to the present embodiment may include a substrate holding unit 110, a measuring unit 120, and a control unit .

[0014] The substrate processing apparatus 100 of this embodiment is an apparatus that performs a process (so-called pre-alignment process) to detect the position of the edge 11 of the substrate 10 before the substrate 10 is transported onto the substrate stage of the lithography apparatus. In the pre-alignment process, the position of the edge 11 of the substrate 10 is detected based on the light intensity distribution obtained from the edge portion 12 when the edge portion 12 of the substrate 10 is irradiated with light. By determining the orientation and center position of the substrate 10 based on the position of the edge 11 of the substrate 10 detected in such a pre-alignment process, the positioning of the substrate 10 when the substrate 10 is transported onto the substrate stage of the lithography apparatus can be controlled. Note that the positioning of the substrate 10 means adjusting (locating) the substrate 10 to a predetermined position and orientation in the translation direction (e.g., XY direction) and the rotation direction (e.g., θZ direction), and is sometimes called "alignment of the substrate 10". The substrate processing apparatus 100 that performs the pre-alignment process is sometimes called a "pre-alignment apparatus".

[0015] The substrate holding unit 110 is a mechanism for holding and driving the substrate 10, and may include a substrate chuck 111, a rotation drive unit 112, and a translation drive unit 113. The substrate chuck 111 holds the center of the substrate 10 on a holding surface parallel to the XY plane by vacuum suction force, electrostatic suction force, or the like. The rotation drive unit 112 rotationally drives the substrate chuck 111 in the θZ direction about the Z axis as the rotation axis, thereby rotationally driving the substrate 10 in the θZ direction. The translation drive unit 113 translationally drives the substrate chuck 111 and the rotation drive unit 112 in the XY direction, thereby translationally driving the substrate 10 in the XY direction.

[0016] In this embodiment, the substrate 10 held by the substrate holding part 110 has a notch in the peripheral portion 12. The notch of the substrate 10 may be a notch or an orientation flat. However, the substrate 10 may not have a notch. Furthermore, the type of substrate 10 held by the substrate holding part 110 and subjected to the pre-alignment process is arbitrary. That is, the substrate processing apparatus 100 of this embodiment can perform the pre-alignment process on various types of substrates 10 without being limited by the material, transparency, whether or not chamfering is performed, whether or not bonding is performed, and the like.

[0017] The measuring unit 120 is a mechanism for measuring the light intensity distribution obtained from the peripheral portion 12 of the substrate 10 when the peripheral portion 12 is irradiated with light, and may include a light source unit 121 (light projecting unit) and a light receiving unit 122. The light source unit 121 is disposed, for example, on the back surface side (lower side) of the substrate 10, and emits light toward the peripheral portion 12 of the substrate 10 so that the peripheral portion 12 of the substrate 10 is disposed only in a part of the optical path. For example, an LED light source may be used as the light source unit 121. The light receiving unit 122 is disposed, for example, on the front surface side (upper side) of the substrate 10 so as to face the light source unit 121 (light emitting surface), and receives the light emitted from the light source unit 121. The light receiving unit 122 of this embodiment includes a light receiving element 122a (light receiving sensor) and an optical system 122b. The light receiving element 122a may be an imaging element such as a CCD image sensor or a CMOS image sensor. The optical system 122b is an imaging optical system for forming an image of the peripheral portion 12 of the substrate 10 on the light receiving surface (imaging surface) of the light receiving element 122a.

[0018] When the substrate 10 is a non-transparent substrate, the light emitted from the light source unit 121 and passing through the space outside the substrate 10 is received by the light receiving unit 122. On the other hand, when the substrate 10 is a transparent substrate and the peripheral portion 12 is chamfered, the light emitted from the light source unit 121 and passing through the space outside the substrate 10 and the light transmitted through the portions of the substrate 10 other than the peripheral portion 12 are received by the light receiving unit 122. The space outside the substrate 10 may be understood as a space that is not blocked by the substrate 10.

[0019] The measuring unit 120 measures the radial (X-direction) light intensity distribution obtained from a part of the peripheral portion 12 of the substrate 10, based on the light received (detected) by the light receiving unit 122 out of the light emitted from the light source unit 121. The measuring unit 120 sequentially measures such radial light intensity distribution while the substrate 10 is being rotated by the substrate holding unit 110. This makes it possible to obtain the radial light intensity distribution for the entire peripheral portion 12 of the substrate 10. Note that, hereinafter, the radial light intensity distribution may be simply referred to as the "light intensity distribution".

[0020] Here, the measurement unit 120 in this embodiment is configured as a transmission type sensor, but is not limited thereto, and may be configured as a reflection type sensor in which light emitted from the light source unit 121 and reflected by the peripheral portion 12 of the substrate 10 is detected by the light receiving unit 122. In addition, the measurement unit 120 (light source unit 121) is preferably bright field illumination. By using bright field illumination instead of dark field illumination, even if the peripheral portion 12 of the substrate 10 is chamfered, it is possible to prevent a decrease in detection accuracy of the position of the peripheral portion 11 of the substrate 10 due to the influence of reflected light in the chamfering.

[0021] The control unit 130 may be configured by a computer (information processing device) having a processor 131 such as a CPU (Central Processing Unit) and a storage unit 132 such as a memory. The control unit 130 is connected to each part of the substrate processing apparatus 100 via a line and controls each part of the substrate processing apparatus 100 (controls the pre-alignment process).

[0022] In this embodiment, the control unit 130 (processor 131) detects the position of the periphery 11 of the substrate 10 based on the light intensity distribution measured by the measurement unit 120, and controls the positioning of the substrate 10 based on the detection result. Specifically, the control unit 130 applies each of a plurality of types of algorithms to the light intensity distribution measured by the measurement unit 120, thereby identifying a plurality of candidates for the position of the periphery 11 of the substrate 10 in the radial direction from the light intensity distribution. Then, the control unit 130 selects one algorithm for determining the position of the substrate 10 from among the plurality of types of algorithms based on the identified plurality of candidates, and determines the position (orientation or center of gravity position) of the substrate 10 using the selected algorithm. This allows the control unit 130 to perform accurate positioning of the substrate 10 based on the determined position of the substrate 10. Note that the positioning of the substrate 10 may be understood as driving the substrate 10 so that the substrate 10 is disposed at a predetermined position, i.e., so that the positional deviation of the substrate 10 is reduced.

[0023] The storage unit 132 stores information required for executing the pre-alignment process. For example, the storage unit 132 stores a program for executing the pre-alignment process and a plurality of types of algorithms used in the pre-alignment process. Each of the plurality of types of algorithms is set to detect (identify) the position of the edge 11 of the substrate 10 from the light intensity distribution measured by the measurement unit 120 for each type of substrate 10 that may be subjected to the pre-alignment process in the substrate processing apparatus 100. The storage unit 132 also stores position information of the edge 11 of the substrate 10 determined by the processor 131 and measurement conditions of the light intensity distribution in the measurement unit 120 (e.g., the amount of light of the light source unit 121, etc.). In the following, the position of the edge 11 of the substrate 10 in the radial direction may be referred to as the "edge position".

[0024] [Detection of edge position] An example of detecting the peripheral position of the substrate 10 will be described with reference to Figs. 2 to 6. Figs. 2 to 6 show an example of detecting the peripheral position of the substrate 10 for each of a plurality of types of substrates 10 having different materials and structures. Each of Figs. 2 to 6 shows the structure of the peripheral portion 12 of the substrate 10 and the corresponding light intensity distribution obtained by the light receiving section 122 of the measurement section 120. The light intensity distribution is represented by taking the radial position of the substrate 10 as the horizontal axis and the received light intensity (light intensity) at the light receiving section 122 as the vertical axis.

[0025] 2 shows an example in which the substrate 10 is a non-transparent substrate (e.g., a silicon substrate) and a peripheral portion 12 of the substrate 10 is chamfered. In this example, a portion of the light from the light source unit 121 is blocked by the substrate 10, and therefore only light that has passed through a space outside the peripheral edge 11 of the substrate 10 is incident on the light receiving unit 122 of the measurement unit 120. Therefore, the light intensity distribution 141 obtained by the light receiving unit 122 has a shape in which the light intensity changes significantly with the peripheral edge 11 of the substrate 10 as a boundary, as shown in FIG.

[0026] In the example of FIG. 2, the algorithm for detecting the peripheral position of the substrate 10 uses a judgment threshold 151 set between the light intensity obtained outside the peripheral edge 11 of the substrate 10 and the light intensity obtained inside the substrate 10. In this algorithm, a point 141a where the light intensity becomes the judgment threshold 151 in the light intensity distribution 141 measured by the measurement unit 120 is specified as the peripheral position of the substrate 10. That is, in this algorithm, a point 141a where the light intensity first falls below the judgment threshold 151 from the peripheral edge of the substrate 10 toward the center (center of gravity) is specified as the peripheral position of the substrate 10 in the light intensity distribution 141 measured by the measurement unit 120. In this way, in the example of FIG. 2, the control unit 130 can detect (specify) the peripheral position of the substrate 10 by applying the algorithm using the judgment threshold 151 to the light intensity distribution.

[0027] 3 shows an example in which the substrate 10 is a transparent substrate (e.g., a glass substrate) and the peripheral portion 12 of the substrate 10 is chamfered. In this example, a part of the light from the light source unit 121 is reflected by the chamfered peripheral portion 12 of the substrate 10 and does not enter the light receiving unit 122 of the measurement unit 120. Therefore, of the light from the light source unit 121, light that has passed outside the peripheral portion 11 of the substrate 10 and light that has passed through portions of the substrate 10 other than the peripheral portion 12 enter the light receiving unit 122. Therefore, the light intensity distribution 142 obtained by the light receiving unit 122 has a shape in which the light intensity at the peripheral portion 12 is lower than the light intensity at other portions, as shown in FIG.

[0028] In the example of FIG. 3, the algorithm for detecting the peripheral position of the substrate 10 uses a judgment threshold 152 set between the light intensity obtained outside the peripheral edge 11 of the substrate 10 and the light intensity obtained for the peripheral portion 12 of the substrate 10. In this algorithm, among a plurality of points in the light intensity distribution 142 measured by the measuring unit 120 where the light intensity is the judgment threshold 152, a point 141a that satisfies a predetermined condition is specified as the peripheral position of the substrate 10. An example of the predetermined condition is that the light intensity is the first to become the judgment threshold 152 from the peripheral edge toward the center of the substrate 10. In other words, in the light intensity distribution 142 measured by the measuring unit 120, a point 141a where the light intensity is the first to become below the judgment threshold 152 from the peripheral edge toward the center of the substrate 10 is specified as the peripheral position of the substrate 10. In this way, in the example of FIG. 3, the control unit 130 can detect (specify) the peripheral position of the substrate 10 by applying an algorithm that uses the judgment threshold 152 and a predetermined condition to the light intensity distribution.

[0029] 4 shows an example in which the substrate 10 is a transparent substrate (e.g., a glass substrate) and the peripheral portion 12 of the substrate 10 is not chamfered. In this example, a part of the light from the light source unit 121 passes through the substrate 10, and the light intensity of the part of the light is reduced (i.e., dimmed). Therefore, the light intensity distribution 143 obtained by the light receiving unit 122 of the measuring unit 120 has a shape in which the light intensity changes with the peripheral edge 11 of the substrate 10 as a boundary, as shown in FIG. 4. However, in this example, since the substrate 10 passes light, the amount of change in light intensity in the light intensity distribution 143 is smaller than the amount of change in light intensity in the light intensity distribution 141 shown in FIG. 2.

[0030] In the algorithm for detecting the peripheral position of the substrate 10 in the example of FIG. 4, a judgment threshold 153 is used, which is set between the light intensity obtained outside the peripheral edge 11 of the substrate 10 and the light intensity obtained inside the peripheral edge 11 of the substrate 10. In this algorithm, a point 143a where the light intensity of the light intensity distribution 143 measured by the measurement unit 120 becomes the judgment threshold 153 is specified as the peripheral position of the substrate 10. That is, in this algorithm, a point 143a where the light intensity first falls below the judgment threshold 153 from the peripheral edge toward the center of the substrate 10 in the light intensity distribution 143 measured by the measurement unit 120 is specified as the peripheral position of the substrate 10. In this way, in the example of FIG. 4, the control unit 130 can detect (specify) the peripheral position of the substrate 10 by applying the algorithm using the judgment threshold 153 to the light intensity distribution.

[0031] FIG. 5 shows an example in which the substrate 10 is a laminated substrate made of a transparent support substrate 10a (e.g., a glass substrate) and a non-transparent substrate 10b (e.g., a silicon substrate) attached thereon. The outer shape of the support substrate 10a is larger than that of the non-transparent substrate 10b. In addition, the peripheral portion 12a of the support substrate 10a and the peripheral portion 12b of the non-transparent substrate 10b are each chamfered. In this example, a part of the light from the light source unit 121 is reflected by the chamfered peripheral portion 12a of the support substrate 10a. Therefore, the light passes outside the peripheral portion 11a of the support substrate 10a and the portion of the support substrate 10a other than the peripheral portion 12a. In addition, a part of the light that passes through the portion of the support substrate 10a other than the peripheral portion 12a is blocked by the non-transparent substrate 10b. Therefore, the light intensity distribution 144 obtained by the light receiving unit 122 of the measurement unit 120 has a shape as shown in FIG. 5.

[0032] In the example of FIG. 5, the algorithm for detecting the peripheral position of the support substrate 10a uses a judgment threshold 154a set between the light intensity obtained outside the peripheral edge 11a of the support substrate 10a and the light intensity obtained for the peripheral portion 12a of the support substrate 10a. In this algorithm, among a plurality of points in the light intensity distribution 144 measured by the measurement unit 120 where the light intensity is the judgment threshold 154a, the point 144a that satisfies a predetermined condition is identified as the peripheral position of the support substrate 10a. The predetermined condition is that the light intensity is the first to become the judgment threshold 154a from the peripheral edge toward the center of the substrate 10. In other words, in this algorithm, the point 144a where the light intensity is the first to become below the judgment threshold 154a from the peripheral edge toward the center of the substrate 10 in the light intensity distribution 144 measured by the measurement unit 120 is identified as the peripheral position of the substrate 10. In this way, in the example of FIG. 5, the control unit 130 can detect (identify) the peripheral position of the support substrate 10a by applying an algorithm that uses the determination threshold value 154a and predetermined conditions to the light intensity distribution.

[0033] In addition, in the example of FIG. 5, the algorithm for detecting the peripheral position of the non-transparent substrate 10b uses a judgment threshold 154b set between the light intensity obtained outside the peripheral edge 11b of the non-transparent substrate 10b and the light intensity obtained inside the non-transparent substrate 10b. In this algorithm, among a plurality of points in the light intensity distribution 144 measured by the measuring unit 120 where the light intensity is the judgment threshold 154b, the point 144b that satisfies a predetermined condition is identified as the peripheral position of the non-transparent substrate 10b. The predetermined condition is that the light intensity is the judgment threshold 154b the third time from the peripheral edge of the substrate 10 toward the center. In other words, in this algorithm, the point 144b where the light intensity is below the judgment threshold 154b the second time from the peripheral edge of the substrate 10 toward the center in the light intensity distribution 144 measured by the measuring unit 120 is identified as the peripheral position of the substrate 10. In this way, in the example of FIG. 5, the control unit 130 can detect (identify) the peripheral position of the non-transparent substrate 10b by applying an algorithm that uses the determination threshold value 154b and predetermined conditions to the light intensity distribution.

[0034] FIG. 6 shows an example in which the substrate 10 is a substrate consisting of a non-transparent substrate 10c (e.g., a glass substrate) and a transparent film 10d attached thereon. The outer shape of the transparent film 10d is larger than that of the non-transparent substrate 10c. In addition, a peripheral portion 12c of the non-transparent substrate 10c is chamfered. In this example, a part of the light from the light source unit 121 is blocked by the non-transparent substrate 10c. In addition, a part of the light that passes outside the peripheral portion 11c of the non-transparent substrate 10c passes through the transparent film 10d, and at that time, the light intensity of the part of the light is reduced (i.e., the light is dimmed). Therefore, the light intensity distribution 145 obtained by the light receiving unit 122 of the measuring unit 120 has a shape as shown in FIG. 4.

[0035] In the example of FIG. 6, a judgment threshold 155 is used in the algorithm for detecting the peripheral position of the non-transparent substrate 10c. The judgment threshold 155 is set between the light intensity obtained outside the peripheral edge 11c of the non-transparent substrate 10c and inside the transparent film 10d, and the light intensity obtained inside the non-transparent substrate 10c. In this algorithm, a point 145a where the light intensity of the light intensity distribution 145 measured by the measurement unit 120 becomes the judgment threshold 155 is specified as the peripheral position of the non-transparent substrate 10c. That is, in this algorithm, a point 145a where the light intensity first falls below the judgment threshold 155 from the peripheral edge to the center of the substrate 10 in the light intensity distribution 145 measured by the measurement unit 120 is specified as the peripheral position of the substrate 10. In this way, in the example of FIG. 6, the control unit 130 can detect (specify) the peripheral position of the non-transparent substrate 10c by applying the algorithm using the judgment threshold 155 to the light intensity distribution.

[0036] As described above, the light intensity distribution measured by the measuring unit 120 (light receiving unit 122) varies depending on the material and transparency (transparent / non-transparent) of the substrate 10, whether the peripheral portion 12 is chamfered, and whether or not the bonding process is performed. In other words, when the type of substrate 10 changes, the tendency of the light intensity distribution measured by the measuring unit 120 may change. Therefore, in order to accurately detect the peripheral position of the substrate 10 even if the type of substrate 10 changes, it is necessary to appropriately select an algorithm for determining the position of the substrate from the light intensity distribution according to the type of substrate. However, in order to select an algorithm, it may be disadvantageous in terms of throughput to perform a process of measuring the light intensity distribution by the measuring unit 120 multiple times while rotating the substrate 10 by changing the type of algorithm. In other words, in the pre-alignment process, it is desired to achieve both throughput and detection accuracy when detecting the position of the substrate 10. Therefore, in this embodiment, multiple types of algorithms are applied to one light intensity distribution measured by the measuring unit 120, so that multiple candidates for the peripheral position of the substrate 10 are identified from the light intensity distribution. Then, based on the identified candidates, one algorithm is selected from the multiple types of algorithms to be used for determining the position of the substrate 10. In the following, the candidates regarding the peripheral position of the substrate 10 may be referred to as "periphery position candidates".

[0037] Here, the multiple types of algorithms may include at least two types of algorithms with different judgment thresholds for identifying the peripheral position of the substrate 10 from the light intensity distribution. For example, the algorithms used in the examples of Figs. 2 to 6 described above may have different judgment thresholds 151 to 155. Furthermore, the multiple types of algorithms may include at least two types of algorithms with different predetermined conditions for selecting one location from multiple locations in the light intensity distribution when the multiple locations have a light intensity that is the judgment threshold. For example, the algorithms used in the examples of Figs. 3 and 5 described above may have different predetermined conditions (specifically, the condition for the number of times the light intensity becomes the judgment threshold from the peripheral edge toward the center of the substrate 10).

[0038] [Algorithm Selection] The algorithm may be selected, for example, by determining an evaluation value for each of a plurality of peripheral position candidates. The evaluation value for each of the plurality of peripheral position candidates may be determined based on at least one of the similarity between the outer shape of the substrate 10 obtained from the peripheral position and the first reference shape, and the circularity of the outer shape of the substrate 10 obtained from the peripheral position. Additionally or alternatively, the evaluation value may be determined based on the similarity between the shape of the cutout portion of the substrate 10 obtained from the peripheral position and the second reference shape.

[0039] The control unit 130 causes the measurement unit 120 to sequentially measure the radial light intensity distribution while rotating the substrate 10 by the substrate holding unit 110, thereby obtaining a position waveform 51 indicating the relationship between the position in the θZ direction (circumferential direction) and the peripheral position, as shown in FIG. 7(a). In FIG. 7(a), the horizontal axis indicates the position in the θZ direction of the peripheral portion 12 where the measurement of the light intensity distribution is performed by the measurement unit 120 (i.e., the rotation angle θ of the substrate 10), and the vertical axis indicates the peripheral position in the radial direction identified from the light intensity distribution measured by the measurement unit 120. The position waveform 51 may be understood as representing the outer shape of the substrate 10 obtained from the detection result of the peripheral position. The position waveform 51 also includes a partial waveform 53 corresponding to the cutout portion of the substrate 10. The example of FIG. 7(a) shows a case where the cutout portion of the substrate 10 is a notch.

[0040] For example, the control unit 130 can obtain an evaluation value based on at least one of the similarity between the position waveform 51 representing the outer shape of the substrate 10 and the ideal position waveform 50 representing the ideal outer shape of the substrate 10, and the circularity of the outer shape of the substrate 10 obtained from the position waveform 51. The similarity between the position waveform 51 and the ideal position waveform 50 can be calculated based on the error 52 between the position waveform 51 and the ideal position waveform 50 shown in FIG. 7(b). The ideal position waveform 50 is a waveform representing the ideal outer shape of the substrate 10, and may be understood as representing a reference shape (first reference shape) regarding the outer shape of the substrate 10. The control unit 130 can obtain the ideal position waveform 50 using the following formula (1) by obtaining the eccentricity (X, Y) and the rotation angle θ of the substrate 10 relative to the center of rotation 125 of the substrate 10 by the substrate holding unit 110 based on the position waveform 51. JPEG2025071674000002.jpg15170

[0041] Here, the formula (1) will be described with reference to FIG. 8. In FIG. 8, the θZ direction indicates the circumferential direction of the substrate 10, and the R direction indicates the radial direction of the substrate 10. As shown in FIG. 8, if the center of gravity 24 (center) of the substrate 10 is eccentric with respect to the center of rotation 125 of the substrate 10 by the substrate holding unit 110, "r" indicates the magnitude of the eccentricity vector 25 (the distance between the center of rotation 125 and the center of gravity 24 of the substrate 10). "θ" is the rotation angle of the substrate 10 by the substrate holding unit 110. The rotation angle θ may be understood as indicating the position in the θZ direction of the peripheral portion 12 where the measurement of the light intensity distribution is performed by the measurement unit 120. "α" indicates the angle between the straight line connecting the center of rotation 125 and the light receiving unit 122 (light receiving element 122a) and the eccentricity vector 25 when the straight line is defined. "L" is the radius 26 of the substrate 10.

[0042] Furthermore, as shown in Fig. 7(a), the control unit 130 may obtain the evaluation value based on the similarity between a partial waveform 53 representing the shape of the cutout of the substrate 10 and an ideal partial waveform 54 representing the ideal outer shape of the cutout. The similarity between the partial waveform 53 and the ideal partial waveform 54 may be calculated based on an error 55 between the partial waveform 53 and the ideal partial waveform 54 shown in Fig. 7(b). The ideal partial waveform 54 may be understood as representing a reference shape (second reference shape) related to the outer shape of the cutout of the substrate 10, and may be obtained from design information (design data, specification information) of the cutout of the substrate 10.

[0043] [Pre-alignment process flow] Next, the operation flow of the pre-alignment process of this embodiment will be described. Fig. 9 is a flowchart showing the operation flow of the pre-alignment process of this embodiment. The flowchart in Fig. 9 can be executed by the control unit 130.

[0044] In step S101, the control unit 130 adjusts the light intensity of the light source unit 121 in the measurement unit 120 before the substrate 10 is loaded onto the substrate holding unit 110 of the substrate processing apparatus 100. The light source unit 121 is preferably adjusted with the substrate 10, which acts as a light blocking object, not in the optical path. If the light intensity of the light source unit 121 is adjusted after the substrate 10 is loaded onto the substrate holding unit 110, the amount of light cannot be confirmed in the portion blocked by the substrate 10. As a result, there is a risk that the signal strength will exceed the allowable value during the rotational operation of the substrate 10.

[0045] In step S102, the control unit 130 causes a substrate transport mechanism (substrate transport robot) (not shown) to load the substrate 10 onto the substrate holding unit 110 of the substrate processing apparatus 100. The substrate 10 loaded onto the substrate holding unit 110 is held by a substrate chuck 111. At the stage when the substrate 10 is loaded onto the substrate holding unit 110, the substrate 10 has not been positioned, and the substrate 10 is shifted in the translational and rotational directions with respect to a desired position on the substrate holding unit 110.

[0046] Steps S103 to S105 are steps (first measurement steps) for measuring the light intensity distribution by the measurement unit 120. In step S103, the control unit 130 starts the rotational driving of the substrate 10 in the θZ direction by the substrate holding unit 110 (rotational driving unit 112) and starts the measurement of the light intensity distribution of the peripheral portion 12 of the substrate 10 by the measurement unit 120. In step S104, the control unit 130 sequentially acquires information (data) of the light intensity distribution measured by the measurement unit 120 from the measurement unit 120 and stores it in the storage unit 132. Next, in step S105, the control unit 130 rotates the substrate 10 by an amount of rotation (e.g., 360 degrees) required to determine the position of the substrate 10, and then ends the rotational driving of the substrate 10 by the substrate holding unit 110 and the measurement of the light intensity distribution by the measurement unit 120. The light intensity distribution is measured while the substrate 10 is being rotationally driven in the θZ direction by the substrate holding unit 110 (rotation drive unit 112). That is, the measurement unit 120 sequentially (continuously) measures the radial light intensity distribution for part of the peripheral portion 12 of the substrate 10 while the substrate 10 is being rotationally driven by the substrate holding unit 110. This allows the control unit 130 to obtain the radial light intensity distribution for the entire peripheral portion 12 of the substrate 10.

[0047] In step S106, the control unit 130 applies each of the multiple types of algorithms to the light intensity distribution acquired through steps S103 to S105, thereby identifying multiple edge position candidates from the light intensity distribution (identification step). The multiple types of algorithms are set for identifying edge positions according to the type of substrate 10, and are stored in the storage unit 132. The control unit 130 reads out the multiple algorithms from the storage unit 132, and applies each of the multiple types of algorithms to one light intensity distribution, thereby being able to identify multiple edge position candidates from the one light intensity distribution. Identification of multiple edge position candidates by using multiple types of algorithms in this manner is performed on each of the light intensity distributions acquired sequentially through steps S103 to S105.

[0048] Here, as described above, the multiple types of algorithms may include at least two types of algorithms with different judgment thresholds for identifying the edge position of the substrate 10 from one light intensity distribution. In addition, the multiple types of algorithms may include at least two types of algorithms with different predetermined conditions for selecting one of multiple locations when there are multiple locations in one light intensity distribution where the light intensity is the judgment threshold. The predetermined condition may include a condition for the number of times that the light intensity becomes the judgment threshold from the edge of the substrate 10 toward the center in the light intensity distribution. For example, the predetermined condition may be a condition that a location where the number of times that the light intensity becomes below the judgment threshold from the edge of the substrate 10 toward the center in the light intensity distribution becomes a predetermined number is identified as the edge position of the substrate 10. Alternatively, the predetermined condition may be a condition that a location where the number of pixels of the light receiving element 122a where the light intensity is continuously below the judgment threshold becomes a predetermined number in the light intensity distribution is identified as the edge position of the substrate 10.

[0049] As a specific example, the multiple types of algorithms may include an algorithm for identifying, as the peripheral position of the substrate 10, a location 141a in a light intensity distribution 141 where the light intensity first falls below a judgment threshold 151 from the peripheral edge of the substrate 10 toward the center, as in the example shown in Fig. 2. The multiple types of algorithms may include an algorithm for identifying, as the peripheral position of the substrate 10, a location 142a in a light intensity distribution 142 where the light intensity first falls below a judgment threshold 152 from the peripheral edge of the substrate 10 toward the center, as in the example shown in Fig. 3. The multiple types of algorithms may include an algorithm for identifying, as the peripheral position of the substrate 10, a location 143a in a light intensity distribution 143 where the light intensity first falls below a judgment threshold 153 from the peripheral edge of the substrate 10 toward the center, as in the example shown in Fig. 4.

[0050] The multiple types of algorithms may include an algorithm for identifying, as the peripheral position of the substrate 10, a location 144a where the light intensity in the light intensity distribution 144 first falls below a judgment threshold 154a from the periphery of the substrate 10 toward the center, as the peripheral position of the substrate 10, as shown in the example of FIG. 5. The multiple types of algorithms may include an algorithm for identifying, as the peripheral position of the substrate 10, a location 144b where the light intensity in the light intensity distribution 144 first falls below a judgment threshold 154b from the periphery of the substrate 10 toward the center, as shown in the example of FIG. 6. The multiple types of algorithms may include an algorithm for identifying, as the peripheral position of the substrate 10, a location 145a where the light intensity in the light intensity distribution 145 first falls below a judgment threshold 155 from the periphery of the substrate 10 toward the center, as the peripheral position of the substrate 10, as shown in the example of FIG. Note that the judgment thresholds 151 to 155 may be different values.

[0051] In step S107, the control unit 130 calculates the position waveform 51 shown in FIG. 7(a) for each of the multiple types of algorithms. As described above, the position waveform 51 is a waveform that indicates the relationship between the position of the substrate 10 in the θZ direction and the peripheral position, and may be understood as representing the outer shape of the substrate 10. The position waveform 51 may include a partial waveform 53 that corresponds to the cutout portion of the substrate 10. For example, the control unit 130 plots the peripheral position candidates of the substrate 10 identified for each algorithm in correspondence with the position of the substrate 10 in the θZ direction. This allows the control unit 130 to calculate the position waveform 51 for each algorithm. Also, in step S107, the control unit 130 may calculate the ideal position waveform 50 as described above.

[0052] In step S108, the control unit 130 obtains an evaluation value for each of the multiple peripheral position candidates (evaluation step). Step S108 may be understood as a step of obtaining an evaluation value for each of multiple types of algorithms. In this embodiment, the control unit 130 can obtain the evaluation value based on at least one of the similarity between the position waveform 51 and the ideal position waveform 50, the circularity of the outer shape of the substrate 10 obtained from the position waveform 51, and the similarity between the partial waveform 53 and the ideal partial waveform 54. For example, the control unit 130 can obtain the evaluation value by calculating the similarity between the position waveform 51 and the ideal position waveform 50 from the sum or variance of the error 52 between the position waveform 51 and the ideal position waveform 50 shown in FIG. 7(b). Alternatively, the control unit 130 can obtain the evaluation value by calculating the circularity from the error between the outer shape of the substrate 10 obtained from the position waveform 51 and the perfect circle. The control unit 130 may obtain the evaluation value by calculating the similarity between the partial waveform 53 and the ideal partial waveform 54 from the sum or variance of the error 55 between the partial waveform 53 shown in Figure 7 (b) and the ideal partial waveform 54.

[0053] Here, the control unit 130 may obtain the evaluation value based on a plurality of evaluation indexes obtained from the peripheral position candidates. The plurality of evaluation indexes may include at least two of the similarity between the position waveform 51 and the ideal position waveform 50, the circularity of the outer shape of the substrate 10 obtained from the position waveform 51, and the similarity between the partial waveform 53 and the ideal partial waveform 54. In this case, the control unit 130 may weight each of the plurality of evaluation indexes and obtain the evaluation value based on the result. For example, the control unit 130 may obtain the evaluation value as the sum of the plurality of weighted evaluation indexes.

[0054] In step S109, the control unit 130 selects one algorithm to be used for determining the position of the substrate 10 as the optimum algorithm from among the multiple algorithms based on the evaluation value obtained for each peripheral position candidate in step S108 (selection step). For example, the control unit 130 may select the peripheral position candidate having the best evaluation value from among the multiple peripheral position candidates, and select the algorithm used to identify the selected peripheral position candidate as the optimum algorithm. As a specific example, when the control unit 130 obtains the sum of errors 52 between the position waveform 51 and the ideal position waveform 50 as the evaluation value, the control unit 130 may select the algorithm used to identify the peripheral position candidate having the smallest evaluation value from among the multiple peripheral position candidates as the optimum algorithm. On the other hand, when the control unit 130 obtains the reciprocal of the sum of errors 52 between the position waveform 51 and the ideal position waveform 50 as the evaluation value, the control unit 130 may select the algorithm used to identify the peripheral position candidate having the largest evaluation value from among the multiple peripheral position candidates as the optimum algorithm.

[0055] Steps S110 to S113 are processes for controlling the positioning of the substrate 10 using the optimal algorithm selected in step S109. The positioning of the substrate 10 in this embodiment can include positioning of the substrate 10 while it is held by the substrate holding unit 110, and positioning of the substrate 10 when it is transported from the substrate holding unit 110 to a target transport destination. An example of the target transport destination is on a substrate stage of a lithography apparatus.

[0056] In step S110, the control unit 130 detects the position of the peripheral portion 12 (e.g., a notch) of the substrate 10 held by the substrate holding unit 110, based on the peripheral position candidate identified by the optimization algorithm. Next, in step S111, the control unit 130 performs precision measurement (second measurement step) in which the measurement unit 120 remeasures the light intensity distribution of the peripheral portion 12 of the substrate 10. In the precision measurement, first, the control unit 130 positions the substrate 10 so that the peripheral portion 12 (notch) of the substrate 10 is disposed in the optical path of the measurement unit 120, based on the position of the peripheral portion 12 (notch) of the substrate 10 detected in step S110. The positioning of the substrate 10 may be performed by translating and rotating the substrate 10 by the substrate holding unit 110, or may be performed by re-mounting the substrate 10 on the substrate holding unit 110 by a substrate transport mechanism (substrate transport robot) (not shown). Next, the control unit 130 sequentially measures the light intensity distribution of the peripheral portion 12 of the substrate 10 using the measurement unit 120 while rotating the substrate 10 using the substrate holding unit 110. In the case of this embodiment, the control unit 130 can precisely measure the light intensity distribution of the notch in the peripheral portion 12 of the substrate 10. By performing such precise measurements, it is possible to reduce degradation in processing accuracy caused by positional deviation of the substrate 10 during subsequent substrate transport operations and processing operations.

[0057] In step S112, the control unit 130 determines the position of the substrate 10 (determination step). Specifically, the control unit 130 specifies the peripheral position of the substrate 10 by applying an optimum algorithm to the light intensity distribution acquired in step S111. Then, the control unit 130 calculates a position waveform 51 from the specified peripheral position of the substrate 10, and determines the position of the substrate 10 based on the position waveform 51. The position of the substrate 10 determined in step S112 may include at least one of the outline of a local area including the notch in the peripheral portion 12 of the substrate 10, the peripheral position of the substrate 10, and the position of the center of gravity of the substrate 10.

[0058] In step S113, the control unit 130 transports the substrate 10 from the substrate holding unit 110 to the target transport destination by a substrate transport mechanism (substrate transport robot) (not shown). At this time, the control unit 130 can control the positioning of the substrate 10 when the substrate 10 is transported from the substrate holding unit 110 to the target transport destination based on the position of the substrate 10 determined in step S112. For example, the control unit 130 can calculate the amount of eccentricity of the position X, Y, and θZ of the substrate 10 relative to the substrate holding unit 110 based on the position of the substrate 10 determined in step S112, and control the positioning of the substrate 10 based on the amount of eccentricity. The positioning of the substrate 10 can be controlled so that the substrate 10 is in a predetermined position and orientation.

[0059] Here, the above steps S106 to S109 will be described in more detail with reference to Fig. 10 to Fig. 12. In step S106, the control unit 130 applies multiple types of algorithms A to D to one light intensity distribution, as shown in Fig. 10, and identifies peripheral position candidates for each algorithm. In step SS107, the control unit 130 calculates a position waveform 51 and an ideal position waveform 50 for each algorithm, based on the peripheral position candidates identified for each algorithm in step S106.

[0060] In step S108, the control unit 130 calculates the outer shape of the substrate 10 from the position waveform 51 as the substrate outer peripheral shape, and calculates an ideal circle (first reference shape) from the ideal position waveform 50, as shown in FIG. 11(a). This allows the control unit 130 to calculate an evaluation value based on the similarity between the position waveform 51 and the ideal position waveform 50 obtained from the difference between the substrate outer peripheral shape and the ideal circle, and / or the circularity of the substrate outer peripheral shape. Also, the control unit 130 calculates the outer shape of the cutout portion of the substrate 10 (hereinafter, sometimes referred to as the cutout shape) from the partial waveform 53, as shown in FIG. 11(b), and calculates the ideal cutout shape (second reference shape) of the substrate 10 from the ideal partial waveform 54. This allows the control unit 130 to calculate an evaluation value based on the similarity between the partial waveform 53 obtained from the difference between the cutout shape and the ideal cutout shape, and the ideal partial waveform 54. Such an evaluation value is calculated for each algorithm. FIG. 12 shows a schematic diagram of the evaluation values ​​calculated for each of a plurality of types of algorithms A to D. In step S109, the control unit 130 can select one algorithm having the best evaluation value from among the multiple types of algorithms A to D (algorithm C in FIG. 12) as the optimal algorithm based on the evaluation value obtained for each of the algorithms A to D.

[0061] In addition, in step S108, weighting processing may be performed on a plurality of evaluation indexes used to calculate the evaluation value. In the following, an example of the weighting processing in step S108 will be described in which two types of algorithms are applied to the light intensity distribution 144 shown in Fig. 5. The two types of algorithms include a first algorithm for detecting the peripheral position (first peripheral position) of the support substrate 10a, and a second algorithm for detecting the peripheral position (second peripheral position) of the non-transparent substrate 10b.

[0062] In steps S106 to S107, the control unit 130 uses the first algorithm to identify the location 144a of the light intensity distribution 144 as the peripheral position (first peripheral position) of the support substrate 10a. As a result, as shown in FIG. 13(a), a position waveform 64 and an ideal position waveform 63 of the first peripheral position can be obtained. Similarly, the control unit 130 uses the second algorithm to identify the location 144b of the light intensity distribution 144 as the peripheral position (second peripheral position) of the non-transparent substrate 10b. As a result, as shown in FIG. 13(a), a position waveform 66 and an ideal position waveform 65 of the second peripheral position can be obtained.

[0063] Next, in step S108, when calculating the evaluation values ​​from the position waveforms, the control unit 130 performs a predetermined weighting process on at least one of the evaluation values ​​of the first peripheral position and the evaluation values ​​of the second peripheral position. Here, the predetermined weighting process can be performed based on the evaluation value of the first peripheral position obtained from the difference between the position waveform 64 and the ideal position waveform 63, and the evaluation value of the second position obtained from the difference between the position waveform 66 and the ideal position waveform 65.

[0064] 13(a) shows an example in which the evaluation value obtained from the position waveform 64 and ideal position waveform 63 of the first peripheral position is comparable to the evaluation value obtained from the position waveform 66 and ideal position waveform 65 of the second peripheral position. In this example, a predetermined weighting process is performed so that the evaluation value of the second peripheral position is dominant over the evaluation value of the first peripheral position. The evaluation value of the first peripheral position and the evaluation value of the second peripheral position being comparable may be understood as the difference between the evaluation value of the first peripheral position and the evaluation value of the second peripheral position being less than a threshold value.

[0065] 13(b) shows an example in which the evaluation value obtained from the position waveform 68 of the first peripheral position and the ideal position waveform 67 is sufficiently superior to the evaluation value obtained from the position waveform 70 of the second peripheral position and the ideal position waveform 69. In this example, a predetermined weighting process is performed so as not to affect the order of superiority between the evaluation value of the first peripheral position and the evaluation value of the second peripheral position.

[0066] That is, in step S109, if the evaluation value of the first peripheral position and the evaluation value of the second peripheral position are comparable based on the weighting process, the second algorithm for detecting the second peripheral position is selected as the optimal algorithm. On the other hand, if the evaluation value of the first peripheral position is sufficiently superior to the evaluation value of the second peripheral position, the first algorithm for detecting the first peripheral position is selected as the optimal algorithm.

[0067] As described above, the substrate processing apparatus 100 of this embodiment applies multiple types of algorithms to one light intensity distribution measured by the measuring unit 120, thereby identifying multiple peripheral position candidates from the one light intensity distribution. Then, based on the multiple peripheral position candidates, one algorithm used to determine the position of the substrate 10 is selected as an optimal algorithm from among the multiple types of algorithms. According to this embodiment, even if the process of measuring the light intensity distribution by the measuring unit 120 while rotating the substrate 10 is not performed multiple times with different types of algorithms, the optimal algorithm can be appropriately selected using one light intensity distribution. In other words, it is possible to achieve both throughput and detection accuracy when detecting the position of the substrate 10.

[0068] <Second embodiment> A second embodiment of the present invention will be described. This embodiment basically follows the first embodiment, and can follow the first embodiment except for the points mentioned below.

[0069] Fig. 14 is a flowchart showing the operation flow of the pre-alignment process of this embodiment. The flowchart in Fig. 14 can be executed by the control unit 130. Note that steps S201 to S204 in the flowchart in Fig. 14 are similar to steps S101 to S104 in the flowchart in Fig. 9, and therefore detailed description thereof will be omitted here.

[0070] In step S205, the control unit 130 applies each of the multiple types of algorithms to the light intensity distribution sequentially acquired from the measurement unit 120 in step S204, thereby identifying multiple peripheral position candidates from the light intensity distribution. At this time, the control unit 130 stores the identified multiple peripheral position candidates in the storage unit 132. In this manner, the control unit 130 of this embodiment identifies multiple peripheral position candidates by applying each of the multiple types of algorithms to the light intensity distribution every time the control unit 130 acquires a light intensity distribution from the measurement unit 120 in step S204. That is, in this embodiment, the measurement of the light intensity distribution in step S204 and the identification of multiple peripheral position candidates in step S205 are performed in parallel. Note that step S205 is the same process as step S106 in the flowchart of FIG. 9, and therefore a detailed description thereof will be omitted here.

[0071] In step S206, the control unit 130 rotates the substrate 10 by an amount of rotation (e.g., 360 degrees) required to determine the position of the substrate 10, and then ends the rotational driving of the substrate 10 by the substrate holding unit 110 and the measurement of the light intensity distribution by the measurement unit 120. Note that step S206 is the same process as step S105 in the flowchart of Fig. 9, and therefore a detailed description thereof will be omitted here.

[0072] In step S207, the control unit 130 detects the position of the peripheral portion 12 (e.g., a notch) of the substrate 10 while it is being held by the substrate holding unit 110. The detection of the position of the peripheral portion 12 in step S207 may be performed based on a peripheral position candidate obtained by a pre-specified algorithm, or may be performed based on a peripheral position candidate obtained by an algorithm used in the previous determination step. The algorithm used in the previous determination step may be the algorithm used in the previous lot, or the algorithm used in the previous substrate.

[0073] In step S208, based on the position of peripheral portion 12 (cutout portion) of substrate 10 detected in step S207, control unit 130 positions substrate 10 so that peripheral portion 12 (cutout portion) of substrate 10 is disposed in the optical path of measurement unit 120. Positioning of substrate 10 may be performed by translationally driving and rotating substrate 10 by substrate holding unit 110, or may be performed by re-mounting substrate 10 on substrate holding unit 110 by a substrate transport mechanism (substrate transport robot) (not shown).

[0074] Furthermore, steps S209 to S210 are performed in parallel with step S208. In step S209, control unit 130 calculates an evaluation value for each of the plurality of peripheral position candidates. Next, in step S210, control unit 130 selects one algorithm to be used for determining the position of substrate 10 as an optimum algorithm from among the plurality of algorithms, based on the evaluation value calculated for each peripheral position candidate in step S209. Note that steps S209 to S210 are similar to steps S108 to S109 in the flowchart of FIG. 9, respectively, and therefore detailed description thereof will be omitted here.

[0075] In step S211, the control unit 130 performs precision measurement to remeasure the light intensity distribution of the peripheral portion 12 of the substrate 10 using the measurement unit 120. Since the positioning of the substrate 10 has already been performed in step S208, the precision measurement of this embodiment can only perform a step of sequentially measuring the light intensity distribution of the peripheral portion 12 of the substrate 10 using the measurement unit 120 while the substrate 10 is rotationally driven by the substrate holding unit 110. Note that step S211 is the same step as step S111 in the flowchart of FIG. 9, and therefore a detailed description thereof will be omitted here.

[0076] In step S212, the control unit 130 determines the position of the substrate 10. Specifically, the control unit 130 specifies the peripheral position of the substrate 10 by applying an optimum algorithm to the light intensity distribution acquired in step S211. Next, in step S213, the control unit 130 transports the substrate 10 from the substrate holder 110 to the target transport destination by a substrate transport mechanism (substrate transport robot) (not shown). Note that steps S212 to S213 are similar to steps S212 to S213 in the flowchart of FIG. 9, and therefore detailed description thereof will be omitted here.

[0077] As described above, in this embodiment, the evaluation value is calculated in parallel with the control of the positioning of the substrate 10. This makes it possible to further improve the throughput of the substrate processing apparatus 100.

[0078] <Third embodiment> A third embodiment of the present invention will be described. This embodiment basically follows the first embodiment, and may follow the first embodiment except for the matters mentioned below. In addition, the second embodiment may be applied to this embodiment.

[0079] Fig. 15 is a flowchart showing the operation flow of the pre-alignment process of this embodiment. The flowchart in Fig. 15 can be executed by the control unit 130. Note that steps S301 to S310 in the flowchart in Fig. 15 are similar to steps S101 to S110 in the flowchart in Fig. 9, and therefore detailed description thereof will be omitted here.

[0080] In step S311, based on the position of peripheral portion 12 (cutout portion) of substrate 10 detected in step S310, control unit 130 positions substrate 10 so that peripheral portion 12 (cutout portion) of substrate 10 is located in the optical path of measurement unit 120. Positioning of substrate 10 may be performed by translationally driving and rotating substrate 10 by substrate holding unit 110, or may be performed by re-mounting substrate 10 on substrate holding unit 110 by a substrate transport mechanism (substrate transport robot) (not shown).

[0081] In step S312, the control unit 130 starts translational driving of the substrate 10 in the X direction by the substrate holding unit 110 (translational driving unit 113) and starts measurement of the light intensity distribution by the measurement unit 120. For example, while the substrate 10 is being translationally driven in the X direction by the substrate holding unit 110, the light receiving unit 122 (light receiving element 122a) of the measurement unit 120 receives light from the light source unit 121 and continuously acquires the light intensity distribution in the X direction of the peripheral portion 12 of the substrate 10 including the notch. That is, in step S312, the light intensity distribution of the notch of the substrate 10 is measured by translationally driving the notch of the substrate 10 in the X direction relative to the optical path of the measurement unit 120.

[0082] In step S313, the control unit 130 sequentially acquires information (data) on the light intensity distribution measured by the measurement unit 120 from the measurement unit 120 and stores it in the storage unit 132. Next, in step S314, the control unit 130 drives the substrate 10 in translation by an amount necessary to determine the position of the substrate 10, and then ends the translation drive of the substrate 10 and the measurement of the light intensity distribution by the measurement unit 120.

[0083] In step S315, the control unit 130 applies each of the multiple types of algorithms to the light intensity distributions sequentially acquired through steps S312 to S313, thereby identifying multiple candidates (notch position candidates) for the position of the notch of the substrate 10. In this way, the control unit 130 can obtain a notch waveform 60 as shown in FIG. 16(a) for each algorithm. The notch waveform 60 is a waveform corresponding to the notch of the substrate 10. In FIG. 16(a), the horizontal axis indicates the position in the θZ direction of the peripheral portion 12 where the light intensity distribution was measured by the measurement unit 120 (i.e., the rotation angle θ of the substrate 10), and the vertical axis indicates the radial peripheral position identified from the light intensity distribution measured by the measurement unit 120.

[0084] In step S316, control unit 130 calculates ideal notch waveform 61 by performing curve approximation using the least squares method on notch waveform 60. Ideal notch waveform 61 may be understood as representing an ideal outer shape of the notch portion of substrate 10. Note that in this embodiment, the notch portion of substrate 10 is represented as a notch, but the notch portion of substrate 10 may also be an orientation flat. If the notch portion of substrate 10 is an orientation flat, control unit 130 calculates the ideal notch waveform by performing linear approximation using the least squares method on the waveform corresponding to the notch portion of substrate 10.

[0085] In step S317, the control unit 130 obtains an evaluation value for each of the multiple notch position candidates. For example, as shown in FIG. 16(b), the control unit 130 obtains an error 62 between a notch waveform 60 and an ideal notch waveform 61, and obtains an evaluation value based on the error 62. For example, the control unit 130 may obtain the evaluation value based on a sum or variance of the error 62. The evaluation value may be obtained for each algorithm. Here, when steps S312 to S316 are performed multiple times, the evaluation value may be obtained based on an average value of the sum of the errors 62 for the multiple times.

[0086] In step S318, control unit 130 compares the evaluation values ​​for the algorithms obtained in step S317, and selects the algorithm with the best evaluation value as the optimal algorithm. The optimal algorithm selected in step S318 may be the same as the optimal algorithm selected in step S309, or it may be different.

[0087] In step S319, the control unit 130 determines the position of the substrate 10 using the optimum algorithm selected in step S318. Specifically, the control unit 130 specifies the peripheral position of the substrate 10 by applying the optimum algorithm to the light intensity distribution acquired through steps S312 to S314. Then, the control unit 130 calculates a position waveform from the specified peripheral position of the substrate 10, and determines the position of the substrate 10 based on the position waveform.

[0088] In step S320, the control unit 130 causes a substrate transport mechanism (substrate transport robot) (not shown) to transport the substrate 10 from the substrate holding unit 110 to the target transport destination. At this time, the control unit 130 can control the positioning of the substrate 10 when transporting the substrate 10 from the substrate holding unit 110 to the target transport destination, based on the position of the substrate 10 determined in step S319. Note that step S320 is the same process as step S113 in the flowchart of FIG. 9, and therefore detailed description thereof will be omitted here.

[0089] Similarly to the first embodiment, this embodiment also makes it possible to achieve both high throughput and high detection accuracy when detecting the position of the substrate 10.

[0090] <Fourth embodiment> A fourth embodiment of the present invention will be described. This embodiment basically follows the first embodiment, and may follow the first embodiment except for the matters mentioned below. In addition, the second embodiment and / or the third embodiment may be applied to this embodiment.

[0091] Fig. 17 is a flowchart showing the operation flow of the pre-alignment process of this embodiment. The flowchart in Fig. 17 can be executed by the control unit 130. Note that the flowchart in Fig. 17 is obtained by adding steps S114 to S115 to the flowchart in Fig. 9. Therefore, in the following, steps S114 to S115 will be described, and detailed descriptions of the other steps S101 to S113 will be omitted.

[0092] Step S114 is inserted between step S108 and step S109. In step S114, the control unit 130 compares the evaluation value obtained for each of the multiple peripheral position candidates in step S108 with a reference value, and determines whether or not there is a peripheral position candidate for which an evaluation value higher than the reference value has been obtained. The reference value is preset to an evaluation value calculated from a position waveform in which the position of the notch of the substrate 10 cannot be detected or the position of the center of gravity of the substrate 10 cannot be detected. If there is a peripheral position candidate for which an evaluation value higher than the reference value has been obtained, the process proceeds to step S109, and if there is no peripheral position candidate for which an evaluation value higher than the reference value has been obtained, the process proceeds to step S115. In step S115, the control unit 130 changes the multiple types of algorithms to be applied to the light intensity distributions sequentially obtained through steps S103 to S105. Then, after changing the multiple types of algorithms, the control unit 130 performs steps S106 to S108. Here, the light intensity distribution to which the multiple types of algorithms are applied after the change is the same as the light intensity distribution to which the multiple types of algorithms are applied before the change. The multiple types of algorithms after the change may have different determination thresholds or different predetermined conditions compared to the multiple types of algorithms before the change.

[0093] In addition, in this embodiment, the algorithms selected as optimal algorithms in the pre-alignment processing performed in the past can be divided into frequently selected algorithms and less frequently selected algorithms and applied to the light intensity distribution. Specifically, in the first step S106, the frequently selected algorithms used in the past pre-alignment processing can be applied to the light intensity distribution. On the other hand, if all the evaluation values ​​obtained by the frequently selected algorithms are below the reference value, in the second step S106, the less frequently selected algorithms can be applied to the light intensity distribution.

[0094] As described above, in this embodiment, it is possible to change (switch) the algorithm to calculate the evaluation value and select the algorithm. That is, in the first step S106 to S108, a smaller number of algorithms (algorithms that are frequently selected as optimal algorithms) are applied compared to the first embodiment. Therefore, it is possible to reduce the time required for the calculation process using the algorithms and improve the throughput compared to the first embodiment.

[0095] The above embodiment is merely an example, and is not limited to the above configuration and shape, and can be appropriately modified or changed within the scope of the present invention. For example, the number of measuring units 120 (sensors) may be two or more, and different algorithms may be applied to the multiple measuring units 120.

[0096] <Embodiments of the Lithography Apparatus> An embodiment of a lithography apparatus according to the present invention will be described. The lithography apparatus is an apparatus that is employed in a lithography process, which is a manufacturing process for semiconductor devices and liquid crystal display devices, and forms a pattern on a substrate. An example of the lithography apparatus is an exposure apparatus that transfers a pattern of an original onto the substrate by exposing the substrate through an original. In the following description, an exposure apparatus will be taken as an example of the lithography apparatus.

[0097] 18 is a schematic diagram showing an example configuration of an exposure apparatus 200. The exposure apparatus 200 transfers a pattern of an original R onto a substrate S by, for example, a step-and-repeat method or a step-and-scan method. As shown in FIG. 18, the exposure apparatus 200 may include an illumination optical system 201, an original stage 202, a projection optical system 203, a substrate stage 204, a transport device 205, and a controller 206. In the exposure apparatus 200, the illumination optical system 201, the original stage 202, the projection optical system 203, and the substrate stage 204 function as a forming unit that forms a pattern on the substrate S.

[0098] The exposure apparatus 200 also includes the above-mentioned substrate processing apparatus 100 that processes the substrate S. The substrate processing apparatus 100 performs a pre-alignment process on the substrate S as the process of the substrate S. Then, the substrate S processed in the substrate processing apparatus 100 is transported onto the substrate stage 204 by the transport apparatus 205. For example, the control unit 130 of the substrate processing apparatus 100 controls the positioning of the substrate S when the transport apparatus 205 transports the substrate S onto the substrate stage 204, based on the position of the substrate S determined by the pre-alignment process of the substrate S. Note that the control unit 206 of the exposure apparatus 200 and the control unit 130 of the substrate processing apparatus 100 may be configured as an integrated unit or may be configured separately.

[0099] <Embodiment of the article manufacturing method> The above-mentioned lithography apparatus can be used to implement an article manufacturing method for manufacturing various articles (semiconductor IC elements, liquid crystal display elements, MEMS, etc.). The article manufacturing method in the embodiment of the present invention is suitable for manufacturing articles such as devices (semiconductor elements, magnetic storage media, liquid crystal display elements, etc.). The article manufacturing method includes a processing step of processing a substrate by the above-mentioned substrate processing method (substrate processing apparatus), a forming step of forming a pattern on the substrate that has undergone the processing step, and a manufacturing step of manufacturing an article from the substrate that has undergone the forming step. The processing step may be understood as a step of performing a pre-alignment process as the processing of the substrate. Furthermore, the article manufacturing method may include other well-known steps (oxidation, film formation, deposition, doping, planarization, etching, resist stripping, dicing, bonding, packaging, etc.). The article manufacturing method in the present embodiment is advantageous in at least one of the performance, quality, productivity, and production cost of the article compared to the conventional method.

[0100] <Other embodiments> The present invention can also be realized by a process in which a program for implementing one or more of the functions of the above-described embodiments is supplied to a system or device via a network or a storage medium, and one or more processors in a computer of the system or device read and execute the program. The present invention can also be realized by a circuit (e.g., ASIC) for implementing one or more of the functions.

[0101] <Summary of the embodiment> The disclosure of this specification includes at least the following substrate processing method, substrate processing apparatus, lithography apparatus, and article manufacturing method. (Item 1) A substrate processing method for processing a substrate, comprising the steps of: a measuring step of measuring a light intensity distribution obtained from a peripheral portion of the substrate when the peripheral portion is irradiated with light from a light source unit; a specifying step of specifying a plurality of candidates for a peripheral position of the substrate from the light intensity distribution measured in the measuring step by applying each of a plurality of types of algorithms to the light intensity distribution; a selection step of selecting one algorithm to be used for determining the position of the substrate from among the plurality of types of algorithms based on the plurality of candidates identified in the identification step; A substrate processing method comprising: (Item 2) each of the plurality of types of algorithms is set to identify the peripheral position based on a point where the light intensity in the light intensity distribution becomes a determination threshold; 2. The substrate processing method according to item 1, wherein the plurality of types of algorithms include at least two types of algorithms having different determination thresholds. (Item 3) each of the plurality of types of algorithms is set to identify the peripheral position based on a portion among the plurality of portions that satisfies a predetermined condition when a plurality of portions exist in the light intensity distribution where the light intensity is equal to a determination threshold value; 3. The substrate processing method according to item 1 or 2, wherein the plurality of types of algorithms include at least two types of algorithms in which the predetermined conditions are different from each other. (Item 4) The method further includes an evaluation step of determining an evaluation value for each of the plurality of candidates identified in the identification step, 4. The substrate processing method according to any one of items 1 to 3, characterized in that in the selection process, one algorithm is selected from the plurality of types of algorithms based on the evaluation value obtained for each of the plurality of candidates in the evaluation process. (Item 5) 5. The substrate processing method according to item 4, characterized in that in the evaluation process, the evaluation value is calculated for each of the plurality of candidates based on the similarity between the outline of the substrate obtained from the peripheral position and a first reference shape. (Item 6) 6. The substrate processing method according to item 4 or 5, wherein in the evaluation step, the evaluation value is calculated for each of the plurality of candidates based on the circularity of the outer shape of the substrate obtained from the peripheral position. (Item 7) 7. A substrate processing method according to any one of items 4 to 6, characterized in that in the evaluation process, for each of the plurality of candidates, the evaluation value is calculated based on the similarity between the shape of the cutout portion of the substrate obtained from the peripheral position and a second reference shape. (Item 8) In the evaluation step, the evaluation value is calculated for each of the plurality of candidates identified in the identification step based on a plurality of evaluation indexes obtained from the peripheral positions; 5. The substrate processing method according to item 4, wherein the plurality of evaluation indexes include at least two of a similarity between an outer shape of the substrate obtained from the peripheral position and a first reference shape, a circularity of the outer shape of the substrate obtained from the peripheral position, and a similarity between a shape of a cutout portion of the substrate obtained from the peripheral position and a second reference shape. (Item 9) 9. The substrate processing method according to item 8, wherein in the evaluation step, the evaluation value is calculated based on a result of applying a predetermined weighting to each of the plurality of evaluation indexes. (Item 10) a second measurement step of positioning the substrate so that the peripheral portion of the substrate is disposed in an optical path of light from the light source unit, and re-measuring a light intensity distribution obtained from the peripheral portion; a determining step of determining a position of the substrate by applying the one algorithm selected in the selecting step to the light intensity distribution measured in the second measuring step; Further comprising: 10. The substrate processing method according to any one of items 4 to 9, wherein the evaluation step is performed in parallel with positioning of the substrate in the second measurement step. (Item 11) Item 11. The substrate processing method according to item 10, wherein the positioning of the substrate in the second measurement step is performed based on the candidate edge position identified in the identification step by a pre-specified algorithm from among the plurality of types of algorithms or an algorithm used in the previous determination step. (Item 12) 12. The substrate processing method according to any one of items 1 to 11, wherein the measuring step and the identifying step are performed in parallel. (Item 13) A processing step of processing a substrate using the substrate processing method according to any one of items 1 to 12; a forming step of forming a pattern on the substrate that has been subjected to the processing step; a manufacturing process for manufacturing an article from the substrate obtained by the forming process; A method for manufacturing an article, comprising: (Item 14) A substrate processing apparatus for processing a substrate, a measurement unit that measures a light intensity distribution obtained from a peripheral portion of the substrate when the peripheral portion is irradiated with light; A control unit for controlling the positioning of the substrate; Equipped with the control unit identifies a plurality of candidates for the peripheral position of the substrate from the light intensity distribution by applying each of a plurality of types of algorithms to the light intensity distribution measured by the measurement unit, and selects one algorithm to be used for determining the position of the substrate from the plurality of types of algorithms based on the plurality of candidates. (Item 15) 1. A lithographic apparatus for forming a pattern on a substrate, comprising: Item 15. The substrate processing apparatus according to item 14, a forming unit for forming a pattern on the substrate processed by the substrate processing apparatus; 1. A lithographic apparatus comprising:

[0102] The invention is not limited to the above-described embodiments, and various modifications and variations are possible without departing from the spirit and scope of the invention. Accordingly, the following claims are appended to apprise the public of the scope of the invention. [Explanation of symbols]

[0103] 10: substrate, 100: substrate processing apparatus, 110: substrate holder, 120: measuring section, 130: control section

Claims

1. A substrate processing method for processing a substrate, comprising the steps of: a measuring step of measuring a light intensity distribution obtained from a peripheral portion of the substrate when the peripheral portion is irradiated with light from a light source unit; a specifying step of specifying a plurality of candidates for a peripheral position of the substrate from the light intensity distribution measured in the measuring step by applying each of a plurality of types of algorithms to the light intensity distribution; a selection step of selecting one algorithm to be used for determining a position of the substrate from among the plurality of types of algorithms based on the plurality of candidates identified in the identification step; A substrate processing method comprising:

2. each of the plurality of types of algorithms is set to identify the peripheral position based on a point where the light intensity in the light intensity distribution becomes a determination threshold; 2. The substrate processing method according to claim 1, wherein the plurality of types of algorithms include at least two types of algorithms in which the determination thresholds are different from each other.

3. each of the plurality of types of algorithms is set to identify the peripheral position based on a portion among the plurality of portions that satisfies a predetermined condition when a plurality of portions exist in the light intensity distribution where the light intensity is equal to a determination threshold value; 2. The substrate processing method according to claim 1, wherein the plurality of types of algorithms include at least two types of algorithms having different predetermined conditions.

4. The method further includes an evaluation step of determining an evaluation value for each of the plurality of candidates identified in the identification step, 2. The substrate processing method according to claim 1, wherein in the selection step, one algorithm is selected from the plurality of types of algorithms based on the evaluation value obtained for each of the plurality of candidates in the evaluation step.

5. 5. The substrate processing method according to claim 4, wherein in the evaluation step, the evaluation value is calculated for each of the plurality of candidates based on a similarity between an outer shape of the substrate obtained from the peripheral position and a first reference shape.

6. 5. The substrate processing method according to claim 4, wherein in the evaluation step, the evaluation value is obtained for each of the plurality of candidates based on a circularity of an outer shape of the substrate obtained from the peripheral position.

7. 5. The substrate processing method according to claim 4, wherein in the evaluation process, the evaluation value is calculated for each of the plurality of candidates based on the similarity between the shape of the notch of the substrate obtained from the peripheral position and a second reference shape.

8. In the evaluation step, the evaluation value is calculated for each of the plurality of candidates identified in the identification step based on a plurality of evaluation indexes obtained from the peripheral positions; 5. The substrate processing method of claim 4, wherein the multiple evaluation indexes include at least two of a similarity between an outer shape of the substrate obtained from the peripheral position and a first reference shape, a circularity of the outer shape of the substrate obtained from the peripheral position, and a similarity between a shape of a notch of the substrate obtained from the peripheral position and a second reference shape.

9. 9. The substrate processing method according to claim 8, wherein in the evaluating step, the evaluation value is calculated based on a result of applying a predetermined weighting to each of the plurality of evaluation indexes.

10. a second measurement step of positioning the substrate so that the peripheral portion of the substrate is disposed in an optical path of light from the light source unit, and re-measuring a light intensity distribution obtained from the peripheral portion; a determining step of determining a position of the substrate by applying the one algorithm selected in the selecting step to the light intensity distribution measured in the second measuring step; Further comprising:

5. The substrate processing method according to claim 4, wherein the evaluation step is performed in parallel with positioning of the substrate in the second measurement step.

11. 11. The substrate processing method according to claim 10, wherein the positioning of the substrate in the second measurement step is performed based on the candidate edge position identified in the identification step by a pre-specified algorithm from among the plurality of types of algorithms or an algorithm used in a previous determination step.

12. 2. The substrate processing method according to claim 1, wherein the measuring step and the identifying step are performed in parallel.

13. A process for processing a substrate by using the substrate processing method according to any one of claims 1 to 12; a forming step of forming a pattern on the substrate that has been subjected to the processing step; a manufacturing process for manufacturing an article from the substrate obtained by the forming process; A method for manufacturing an article, comprising:

14. A substrate processing apparatus for processing a substrate, a measurement unit that measures a light intensity distribution obtained from a peripheral portion of the substrate when the peripheral portion is irradiated with light; A control unit for controlling the positioning of the substrate; Equipped with the control unit identifies a plurality of candidates for the peripheral position of the substrate from the light intensity distribution by applying each of a plurality of types of algorithms to the light intensity distribution measured by the measurement unit, and selects one algorithm from the plurality of types of algorithms to be used for determining the position of the substrate based on the plurality of candidates.

15. 1. A lithographic apparatus for forming a pattern on a substrate, comprising: A substrate processing apparatus according to claim 14 ; a forming unit for forming a pattern on the substrate processed by the substrate processing apparatus; 1. A lithographic apparatus comprising:

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