Substrate processing method and apparatus, lithographic apparatus, article manufacturing method, and storage medium

Abstract

The invention provides a substrate processing method and apparatus, a lithographic apparatus, an article manufacturing method, and a storage medium. The substrate processing method of processing a substrate includes: a measurement step of measuring a light intensity distribution obtained from a peripheral edge portion when the peripheral edge portion of the substrate is irradiated with light from a light source unit; a specifying step of specifying a plurality of candidates of an edge position of the substrate according to the light intensity distribution by applying each of a plurality of types of algorithms to the light intensity distribution measured in the measuring step; and a selection step of selecting one algorithm for determining the position of the substrate from among the plurality of types of algorithms based on the plurality of candidates specified in the specifying step.

Description

Technical Field

[0001] The present invention relates to a substrate processing method, a substrate processing device, a photolithography device, an article manufacturing method, a storage medium and a computer program product. Background Art

[0002] In a photolithography apparatus that forms a pattern on a substrate, a process of detecting the position of the substrate (so-called pre-alignment) is performed before the substrate is transported onto a stage for holding the substrate. In the pre-alignment process, the edge position of the substrate is detected based on the light intensity distribution obtained from the peripheral edge portion of the substrate when the peripheral edge portion of the substrate is irradiated with light, and the position (orientation or center of gravity position) of the substrate is determined based on the detected edge position of the substrate. In this way, the positioning of the substrate can be controlled when the substrate is transported onto the stage.

[0003] Japanese Patent Laid-Open No. 2011-181721 describes a method of detecting an edge of a bonded wafer including a wafer support substrate and a semiconductor wafer bonded to a surface of the wafer support substrate using an edge detector including a light source and a line sensor. In the method described in Japanese Patent Laid-Open No. 2011-181721, semiconductor wafer edge detection and wafer support substrate edge detection are switched under predetermined circumstances.

[0004] There are various types of substrates that undergo pre-alignment processing, such as transparent substrates, opaque substrates, substrates obtained by bonding multiple components, and the like. If the type of substrate changes, the trend of the light intensity distribution obtained from the peripheral edge portion of the substrate will 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 based on the light intensity distribution according to the type of substrate. However, performing the pre-alignment processing including the light intensity distribution measurement step multiple times while changing the type of algorithm to select the algorithm may be disadvantageous in terms of throughput. That is, when detecting the position of the substrate, the pre-alignment processing is required to achieve both throughput and detection accuracy. Summary of the invention

[0005] For example, the present invention provides a technique that facilitates achieving both throughput and detection accuracy when detecting the position of a substrate.

[0006] According to one aspect of the present invention, there is provided a substrate processing method for processing a substrate, the substrate processing method comprising the following steps: a measuring step of measuring a light intensity distribution obtained from a peripheral edge portion of the substrate when the peripheral edge portion of the substrate is irradiated with light from a light source unit; a specifying step of specifying a plurality of candidates for the edge position of the substrate according to the light intensity distribution by applying each of a plurality of types of algorithms to the light intensity distribution measured in the measuring step; and a selecting step of selecting an algorithm for determining the position of the substrate from the plurality of types of algorithms based on the plurality of candidates specified in the specifying step.

[0007] According to another aspect of the present invention, a substrate processing device for processing a substrate is provided, the substrate processing device comprising: a measuring device configured to measure a light intensity distribution obtained from a peripheral edge portion of the substrate when the peripheral edge portion of the substrate is irradiated with light; and a controller configured to control the positioning of the substrate, wherein the controller specifies a plurality of candidates for the edge position of the substrate according to the light intensity distribution by applying each of a plurality of types of algorithms to the light intensity distribution measured by the measuring device, and selects an algorithm from the plurality of types of algorithms for determining the position of the substrate based on the plurality of candidates.

[0008] According to another aspect of the present invention, a non-transitory computer-readable storage medium is provided, which stores a program for causing a computer to execute a substrate processing method, the substrate processing method comprising the following steps: a specifying step, based on a result of measuring a light intensity distribution obtained from a peripheral edge portion of a substrate when the peripheral edge portion is irradiated with light, specifying a plurality of candidates for the edge position of the substrate according to the light intensity distribution by applying each of a plurality of types of algorithms to the light intensity distribution; and a selecting step, based on the plurality of candidates specified in the specifying step, selecting an algorithm from the plurality of types of algorithms for determining the position of the substrate.

[0009] According to another aspect of the present invention, a computer program product is provided, comprising a program for causing a computer to execute a substrate processing method, the substrate processing method comprising the following steps: a specifying step, based on a result of measuring a light intensity distribution obtained from the peripheral edge portion when the peripheral edge portion of the substrate is irradiated with light, specifying a plurality of candidates for the edge position of the substrate according to the light intensity distribution by applying each of a plurality of types of algorithms to the light intensity distribution; and a selecting step, based on the plurality of candidates specified in the specifying step, selecting an algorithm for determining the position of the substrate from the plurality of types of algorithms.

[0010] Further features of the present invention will become apparent from the following description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 is a schematic diagram showing an example of the arrangement of a substrate processing apparatus;

[0012] Figure 2 is a diagram showing an example of detecting an edge position of a substrate;

[0013] Figure 3 is a diagram showing an example of detecting an edge position of a substrate;

[0014] Figure 4 is a diagram showing an example of detecting an edge position of a substrate;

[0015] Figure 5 is a diagram showing an example of detecting an edge position of a substrate;

[0016] Figure 6 is a diagram showing an example of detecting an edge position of a substrate;

[0017] Fig. 7A and Figure 7B is a diagram showing an example of a position waveform representing the outer shape of a substrate and an ideal position waveform;

[0018] Figure 8 is a diagram for explaining equation (1);

[0019] Fig. 9 is a flowchart showing the operation sequence of the pre-alignment process according to the first embodiment;

[0020] Fig.10 is a diagram for explaining an example of an optimal algorithm selection method;

[0021] Fig.11A and Fig. 11B is a diagram for explaining an example of an optimal algorithm selection method;

[0022] Fig.12 is a diagram for explaining an example of an optimal algorithm selection method;

[0023] Fig.13A and Fig. 13B are diagrams each showing an example of a position waveform representing an external shape of a substrate and an ideal position waveform;

[0024] Fig.14 is a flowchart showing the operation sequence of the pre-alignment process according to the second embodiment;

[0025] Fig.15 is a flowchart showing the operation sequence of the pre-alignment process according to the third embodiment;

[0026] Fig.16A and Fig. 16B is a diagram showing an example of a cutout waveform representing the outer shape of a cutout portion of a substrate and an ideal cutout waveform;

[0027] Fig.17 is a flowchart showing the operation sequence of the pre-alignment process according to the fourth embodiment; and

[0028] Fig.18 is a schematic diagram showing an example of the arrangement of an exposure device. DETAILED DESCRIPTION

[0029] Hereinafter, the embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments are not intended to limit the scope of the present invention. A plurality of features are described in the embodiments, but are not limited to the invention requiring all of these features, and these features may be appropriately combined. In addition, in the accompanying drawings, the same reference numerals are given to the same or similar configurations, and their redundant descriptions will be omitted.

[0030] In the specification and the drawings, unless otherwise specified, directions will be indicated on an XYZ coordinate system in which a direction parallel to a holding surface of a substrate chuck 111 (described later) for holding a substrate is defined as an XY plane. Directions parallel to the X-axis, Y-axis, and Z-axis of the XYZ coordinate system are the X-direction, the Y-direction, and the Z-direction, respectively. Rotation about the X-axis, rotation about the Y-axis, and rotation about the Z-axis are θX, θY, and θZ, respectively. Control or drive about the X-axis, Y-axis, and Z-axis refers to control or drive about a direction parallel to the X-axis, a direction parallel to the Y-axis, and a direction parallel to the Z-axis, respectively. In addition, control or drive about the θX-axis, θY-axis, and θZ-axis refers to control or drive about a rotation about an axis parallel to the X-axis, a rotation about an axis parallel to the Y-axis, and a rotation about an axis parallel to the Z-axis, respectively. In addition, position is information that can be specified based on coordinates on the X-axis, Y-axis, and Z-axis, and orientation is information that can be specified by values ​​on the θX-axis, θY-axis, and θZ-axis.

[0031] <First Embodiment>

[0032] A first embodiment according to the present invention will be described. Figure 1 1 is a schematic diagram showing an example of the arrangement of the substrate processing apparatus 100 of the present embodiment. The substrate processing apparatus 100 of the present embodiment may include a substrate holder 110 , a measuring device 120 , and a controller 130 .

[0033] The substrate processing apparatus 100 of the present embodiment is an apparatus that performs a process of detecting the position of the edge 11 of the substrate 10 (so-called pre-alignment process) before the substrate 10 is transported to the substrate stage of the photolithography 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 peripheral edge portion 12 when the peripheral edge portion 12 of the substrate 10 is irradiated with light. By determining the orientation or center position of the substrate 10 based on the position of the edge 11 of the substrate 10 detected by the pre-alignment process, the positioning of the substrate 10 can be controlled when the substrate 10 is transported to the substrate stage of the photolithography apparatus. Note that the positioning of the substrate 10 is to adjust (arrange) the substrate 10 to a predetermined position or orientation in the translation direction (e.g., X and Y directions) and the rotation direction (e.g., θZ direction), which can also be referred to as "alignment of the substrate 10". The substrate processing apparatus 100 that performs the pre-alignment process can also be referred to as a "pre-alignment apparatus".

[0034] The substrate holder 110 is a mechanism for holding and driving the substrate 10, and may include a substrate chuck 111, a rotation driver 112, and a translation driver 113. The substrate chuck 111 holds the central portion of the substrate 10 in a manner of keeping the surface parallel to the XY plane using vacuum suction, electrostatic attraction, etc. The rotation driver 112 rotationally drives the substrate chuck 111 in the θZ direction with the Z axis as the rotation axis, thereby rotationally driving the substrate 10 in the θZ direction. The translation driver 113 translationally drives the substrate chuck 111 and the rotation driver 112 in the X and Y directions, thereby translationally driving the substrate 10 in the X and Y directions.

[0035] In the present embodiment, the substrate 10 held by the substrate holder 110 has a cutout portion in the peripheral edge portion 12. The cutout portion of the substrate 10 may be a notch or an orientation flat surface. Note that the substrate 10 may be a substrate without a cutout portion. In addition, the type of the substrate 10 held by the substrate holder 110 and subjected to the pre-alignment process is arbitrary. That is, the substrate processing apparatus 100 of the present embodiment can perform pre-alignment processing on various types of substrates 10 regardless of material, transparency, chamfering, bonding, etc.

[0036] The measuring device 120 is a mechanism for measuring the light intensity distribution obtained from the peripheral edge portion 12 when the peripheral edge portion 12 of the substrate 10 is irradiated with light, and may include a light source unit 121 (light projection unit) and a light receiving unit 122. The light source unit 121 is, for example, arranged on the back side (lower side) of the substrate 10, and emits light toward the peripheral edge portion 12, so that the peripheral edge portion 12 of the substrate 10 is arranged only in a part of the light path. For example, an LED light source can be used as the light source unit 121. The light receiving unit 122 is, for example, arranged on the front side (upper side) of the substrate 10 to face the light source unit 121 (light emitting surface), and receives light emitted from the light source unit 121. The light receiving unit 122 in the present 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 122 b is an imaging optical system configured to form an image of the peripheral edge portion 12 of the substrate 10 on a light receiving surface (imaging surface) of the light receiving element 122 a .

[0037] When the substrate 10 is an opaque substrate, light passing through a space outside the substrate 10 among the light emitted from the light source unit 121 is received by the light receiving unit 122. On the other hand, when the substrate 10 is a transparent substrate having a chamfered peripheral edge portion 12, light passing through a space outside the substrate 10 and light passing through a portion of the substrate 10 other than the peripheral edge portion 12 among the light emitted from the light source unit 121 are received by the light receiving unit 122. Note that the space outside the substrate 10 may be understood as a space that is not shielded by the substrate 10.

[0038] The measuring device 120 measures the light intensity distribution in the radial direction (X direction) obtained from a part of the peripheral edge portion 12 of the substrate 10 based on the light received (detected) by the light receiving unit 122 among the light emitted from the light source unit 121. While the substrate holder 110 rotationally drives the substrate 10, the measuring device 120 sequentially measures the light intensity distribution in the radial direction as described above. In this way, the light intensity distribution in the radial direction can be obtained for the entire peripheral edge portion 12 of the substrate 10. Note that the light intensity distribution in the radial direction may be simply referred to as "light intensity distribution" hereinafter.

[0039] Here, the measuring device 120 of the present embodiment is configured as a transmission sensor, but the measuring device 120 is not limited thereto and may be configured as a reflection sensor that detects light reflected by the peripheral edge portion 12 of the substrate 10 in the light emitted from the light source unit 121 through the light receiving unit 122. The measuring device 120 (light source unit 121) preferably performs bright field illumination. By performing bright field illumination instead of dark field illumination, even in the case where the peripheral edge portion 12 of the substrate 10 is chamfered, it is possible to prevent the detection accuracy of the position of the edge 11 of the substrate 10 from being reduced due to the influence of the reflected light caused by the chamfer.

[0040] The controller 130 may be formed of, for example, a computer (information processing device) including a processor 131 such as a central processing unit (CPU) and a storage unit 132 such as a memory. The controller 130 is connected to each unit of the substrate processing apparatus 100 through a line, thereby controlling each unit of the substrate processing apparatus 100 (controlling the pre-alignment process).

[0041] In the present embodiment, the controller 130 (processor 131) detects the position of the edge 11 of the substrate 10 based on the light intensity distribution measured by the measuring device 120, and controls the positioning of the substrate 10 based on the detection result. More specifically, the controller 130 applies each of a plurality of types of algorithms to the light intensity distribution measured by the measuring device 120 to specify a plurality of candidates for the position of the edge 11 of the substrate 10 in the radial direction according to the light intensity distribution. Then, the controller 130 selects one algorithm for determining the position of the substrate 10 from the plurality of types of algorithms based on the specified plurality of candidates, and determines the position (orientation or center of gravity position) of the substrate 10 using the one algorithm. Therefore, the controller 130 can accurately position the substrate 10 based on the determined position of the substrate 10. Note that the positioning of the substrate 10 can be understood as driving the substrate 10 to arrange the substrate 10 at a predetermined position, i.e., to reduce the position deviation of the substrate 10.

[0042] The storage unit 132 stores information required for performing the pre-alignment process. For example, the storage unit 132 stores a program for performing the pre-alignment process, and various types of algorithms for the pre-alignment process. Each of the various types of algorithms is configured to detect (specify) the position of the edge 11 of the substrate 10 from the light intensity distribution measured by the measuring device 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 light intensity distribution measurement conditions in the measuring device 120 (e.g., the amount of light of the light source unit 121, etc.). Note that the position of the edge 11 of the substrate 10 in the radial direction may be referred to as the "edge position" hereinafter.

[0043] [Edge position detection]

[0044] Will refer to Figures 2 to 6 An example of detecting the edge position of the substrate 10 is described. Figures 2 to 6 1 and 2 show examples of detecting the edge position of the substrate 10 for each of a plurality of types of substrates 10 different in material and structure from each other. Figures 2 to 6 1 and 2 show the structure of the peripheral edge portion 12 of the substrate 10, and the corresponding light intensity distribution obtained by the light receiving unit 122 of the measuring device 120. The light intensity distribution is shown, wherein the horizontal axis represents the position of the substrate 10 in the radial direction, and the vertical axis represents the light reception intensity (light intensity) in the light receiving unit 122.

[0045] Figure 2 An example is shown in which the substrate 10 is an opaque substrate (e.g., a silicon substrate) and the peripheral edge portion 12 of the substrate 10 is chamfered. In this example, part of the light from the light source unit 121 is blocked by the substrate 10, so that only the light that passes through the space outside the edge 11 of the substrate 10 enters the light receiving unit 122 of the measuring device 120. Therefore, as Figure 2 As shown, in the light intensity distribution 141 obtained by the light receiving unit 122 , the light intensity varies greatly at the edge 11 of the substrate 10 .

[0046] exist Figure 2 In the example shown, the algorithm for detecting the edge position of the substrate 10 uses a determination threshold 151 set between the light intensity obtained outside the edge 11 of the substrate 10 and the light intensity obtained inside the substrate 10. The algorithm specifies a point 141a where the light intensity matches the determination threshold 151 in the light intensity distribution 141 measured by the measuring device 120 as the edge position of the substrate 10. That is, the algorithm specifies a point 141a where the light intensity in the direction from the edge of the substrate 10 toward the center (center of gravity) falls below the determination threshold 151 for the first time in the light intensity distribution 141 measured by the measuring device 120 as the edge position of the substrate 10. In this way, Figure 2 In the example shown, the controller 130 may detect (specify) the edge position of the substrate 10 by applying an algorithm using a determination threshold 151 to the light intensity distribution.

[0047] Figure 3 An example is shown in which the substrate 10 is a transparent substrate (e.g., a glass substrate) and the peripheral edge portion 12 of the substrate 10 is chamfered. In this example, part of the light from the light source unit 121 is reflected by the chamfered peripheral edge portion 12 of the substrate 10 and thus does not enter the light receiving unit 122 of the measuring device 120. Therefore, the light that passes outside the edge 11 of the substrate 10 and the light that passes through the portion of the substrate 10 other than the peripheral edge portion 12 among the light from the light source unit 121 enter the light receiving unit 122. Therefore, as Figure 3As shown, in the light intensity distribution 142 obtained by the light receiving unit 122, the light intensity of the peripheral edge portion 12 is lower than that of the other portions.

[0048] exist Figure 3 In the example shown, the algorithm for detecting the edge position of the substrate 10 uses a determination threshold 152 set between the light intensity obtained outside the edge 11 of the substrate 10 and the light intensity obtained for the peripheral edge portion 12 of the substrate 10. The algorithm designates a point 142a that satisfies a predetermined condition among a plurality of points where the light intensity matches the determination threshold 152 in the light intensity distribution 142 measured by the measuring device 120 as the edge position of the substrate 10. For example, the predetermined condition is a condition where the light intensity matches the determination threshold 152 for the first time in a direction from the edge toward the center of the substrate 10. That is, the algorithm designates a point 142a where the light intensity in the light intensity distribution 142 measured by the measuring device 120 first falls below the determination threshold 152 in a direction from the edge toward the center of the substrate 10 as the edge position of the substrate 10. In this way, Figure 3 In the example shown, the controller 130 may detect (specify) the edge position of the substrate 10 by applying an algorithm using a determination threshold 152 and a predetermined condition to the light intensity distribution.

[0049] Figure 4 An example is shown in which the substrate 10 is a transparent substrate (e.g., a glass substrate) and the peripheral edge portion 12 of the substrate 10 is not chamfered. In this example, part of the light from the light source unit 121 passes through the substrate 10, and at this time, the light intensity of the part of the light is reduced (i.e., becomes darker). Figure 4 As shown, in the light intensity distribution 143 obtained by the light receiving unit 122 of the measuring device 120, the light intensity changes at the edge 11 of the substrate 10 as a boundary. However, in this example, since the substrate 10 is light-transmissive, the amount of change in the light intensity in the light intensity distribution 143 is less than Figure 2 The amount of change in light intensity in the light intensity distribution 141 is shown.

[0050] exist Figure 4 In the example shown, the algorithm for detecting the edge position of the substrate 10 uses a determination threshold 153 set between the light intensity obtained outside the edge 11 of the substrate 10 and the light intensity obtained inside the edge 11 of the substrate 10. The algorithm specifies a point 143a where the light intensity matches the determination threshold 153 in the light intensity distribution 143 measured by the measuring device 120 as the edge position of the substrate 10. That is, the algorithm specifies a point 143a where the light intensity in the light intensity distribution 143 measured by the measuring device 120 first falls below the determination threshold 153 in the direction from the edge of the substrate 10 toward the center as the edge position of the substrate 10. In this way, Figure 4In the example shown, the controller 130 may detect (specify) the edge position of the substrate 10 by applying an algorithm using a determination threshold 153 to the light intensity distribution.

[0051] Figure 5 The substrate 10 is shown as an example of a bonded substrate formed by a transparent supporting substrate 10a (e.g., a glass substrate) and an opaque substrate 10b (e.g., a silicon substrate) bonded to the supporting substrate 10a. The outer shape of the supporting substrate 10a is larger than the outer shape of the opaque substrate 10b. Each of the peripheral edge portion 12a of the supporting substrate 10a and the peripheral edge portion 12b of the opaque substrate 10b is chamfered. In this example, part of the light from the light source unit 121 is reflected by the chamfered peripheral edge portion 12a of the supporting substrate 10a. Therefore, the light passes through the outside of the edge 11a of the supporting substrate 10a, and the portion of the supporting substrate 10a other than the peripheral edge portion 12a. In addition, part of the light that passes through the portion of the supporting substrate 10a other than the peripheral edge portion 12a is blocked by the opaque substrate 10b. Therefore, the light intensity distribution 144 obtained by the light receiving unit 122 of the measuring device 120 has Figure 5 Shape shown.

[0052] exist Figure 5 In the example shown, the algorithm for detecting the edge position of the support substrate 10a uses a determination threshold 154a set between the light intensity obtained outside the edge 11a of the support substrate 10a and the light intensity obtained for the peripheral edge portion 12a of the support substrate 10a. The algorithm designates a point 144a that satisfies a predetermined condition among a plurality of points in the light intensity distribution 144 measured by the measuring device 120 where the light intensity matches the determination threshold 154a as the edge position of the support substrate 10a. For example, the predetermined condition is the condition that the light intensity matches the determination threshold 154a for the first time in the direction from the edge toward the center of the substrate 10. That is, the algorithm designates a point 144a in the light intensity distribution 144 measured by the measuring device 120 where the light intensity first falls below the determination threshold 154a in the direction from the edge toward the center of the substrate 10 as the edge position of the substrate 10. In this way, Figure 5 In the illustrated example, the controller 130 may detect (specify) the edge position of the support substrate 10 a by applying an algorithm using a determination threshold 154 a and a predetermined condition to the light intensity distribution.

[0053] exist Figure 5In the example shown, the algorithm for detecting the edge position of the opaque substrate 10b uses a determination threshold 154b set between the light intensity obtained outside the edge 11b of the opaque substrate 10b and the light intensity obtained inside the opaque substrate 10b. The algorithm designates a point 144b that satisfies a predetermined condition among a plurality of points in the light intensity distribution 144 measured by the measuring device 120 where the light intensity matches the determination threshold 154b as the edge position of the opaque substrate 10b. For example, the predetermined condition is the condition that the light intensity matches the determination threshold 154b for the third time in the direction from the edge toward the center of the substrate 10. That is, the algorithm designates a point 144b in the light intensity distribution 144 measured by the measuring device 120 where the light intensity in the direction from the edge toward the center of the substrate 10 is lower than the determination threshold 154b for the second time as the edge position of the substrate 10. In this way, Figure 5 In the example shown, the controller 130 may detect (specify) the edge position of the opaque substrate 10 b by applying an algorithm using a determination threshold 154 b and a predetermined condition to the light intensity distribution.

[0054] Figure 6 The substrate 10 is shown as an example of a substrate formed by an opaque substrate 10c (e.g., a silicon substrate) and a transparent film 10d bonded to the opaque substrate 10c. The outer shape of the transparent film 10d is larger than the opaque substrate 10c. The peripheral edge portion 12c of the opaque substrate 10c is chamfered. In this example, part of the light from the light source unit 121 is blocked by the opaque substrate 10c. In addition, part of the light passing outside the edge 11c of the opaque substrate 10c passes through the transparent film 10d, and at this time, the light intensity of this part of the light is reduced (i.e., it becomes darker). Therefore, the light intensity distribution 145 obtained by the light receiving unit 122 of the measuring device 120 has the following characteristics: Figure 6 Shape shown.

[0055] exist Figure 6 In the example shown, the algorithm for detecting the edge position of the opaque substrate 10c uses a determination threshold 155. The determination threshold 155 is set between the light intensity obtained outside the edge 11c of the opaque substrate 10c and inside the transparent film 10d, and the light intensity obtained inside the opaque substrate 10c. The algorithm designates a point 145a in the light intensity distribution 145 measured by the measuring device 120 where the light intensity of the light intensity distribution measured by the measuring device 120 matches the determination threshold 155 as the edge position of the opaque substrate 10c. That is, the algorithm designates a point 145a in the light intensity distribution 145 measured by the measuring device 120 where the light intensity first falls below the determination threshold 155 in the direction from the edge of the substrate 10 toward the center as the edge position of the substrate 10. In this way, Figure 6 In the example shown, the controller 130 may detect (specify) the edge position of the opaque substrate 10 c by applying an algorithm using a determination threshold 155 to the light intensity distribution.

[0056] As described above, the light intensity distribution measured by the measuring device 120 (light receiving unit 122) changes depending on the material and transparency (transparent / opaque) of the substrate 10, whether the peripheral edge portion 12 is chamfered, and whether the substrate is bonded. That is, if the type of the substrate 10 changes, the tendency of the light intensity distribution measured by the measuring device 120 changes. Therefore, in order to accurately detect the edge position of the substrate 10 even if the type of the substrate 10 changes, it is necessary to appropriately select an algorithm for determining the position of the substrate according to the light intensity distribution according to the type of the substrate. However, selecting an algorithm by performing a process of measuring the light intensity distribution by the measuring device 120 while driving the substrate 10 rotationally multiple times by changing the type of the algorithm may be disadvantageous in terms of throughput. That is, when detecting the position of the substrate 10, it is desirable that the pre-alignment process achieves both throughput and detection accuracy. Therefore, in the present embodiment, multiple types of algorithms are applied to one light intensity distribution measured by the measuring device 120 to specify multiple candidates for the edge position of the substrate 10 according to the light intensity distribution. Then, based on the specified multiple candidates, one algorithm for determining the position of the substrate 10 is selected from the multiple types of algorithms. Note that the candidates for the edge position of the substrate 10 may be referred to as “edge position candidates” hereinafter.

[0057] Here, the plurality of types of algorithms may include at least two types of algorithms that are different from each other in terms of the determination threshold for specifying the edge position of the substrate 10 according to the light intensity distribution. Figures 2 to 6 The algorithms used in the illustrated example may differ from each other in determining the threshold values ​​151 to 155. In addition, the plurality of types of algorithms may include at least two types of algorithms that differ from each other in a predetermined condition for selecting a point from a plurality of points in the light intensity distribution where the light intensity matches the determination threshold value. For example, Figure 3 and Figure 5 The algorithms used in the illustrated examples may differ from each other in predetermined conditions (more specifically, conditions regarding the number of times the light intensity in the direction from the edge toward the center of the substrate 10 matches the determination threshold).

[0058] [Choice of algorithm]

[0059] For example, the algorithm may be selected by obtaining an evaluation value of each of a plurality of edge position candidates. The evaluation value of each of a plurality of edge position candidates may be obtained based on at least one of the similarity between the outer shape of the substrate 10 obtained from the edge position and the first reference shape, and the roundness of the outer shape of the substrate 10 obtained from the edge position. Additionally or alternatively, the evaluation value may be obtained based on the similarity between the shape of the cutout portion of the substrate 10 obtained from the edge position and the second reference shape.

[0060] While the substrate 10 is rotationally driven by the substrate holder 110, by causing the measuring device 120 to sequentially measure the light intensity distribution in the radial direction, the controller 130 can obtain a position waveform 51 indicating the relationship between the position in the θZ direction (circumferential direction) and the edge position, as shown in FIG. Fig. 7A As shown. Fig. 7A , the horizontal axis represents the θZ direction position of the peripheral edge portion 12 (i.e., the rotation angle θ of the substrate 10) where the light intensity distribution is measured by the measuring device 120, and the vertical axis represents the edge position in the radial direction specified according to the light intensity distribution measured by the measuring device 120. The position waveform 51 can be understood as representing the outer shape of the substrate 10 obtained from the detection result of the edge position. The position waveform 51 includes a partial waveform 53 corresponding to the cutout portion of the substrate 10. Fig. 7A The example shown in exemplifies a case where the cutout portion of the substrate 10 is a notch.

[0061] For example, the controller 130 may obtain the 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 roundness 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 may be based on Figure 7B The controller 130 can calculate the error 52 between the position waveform 51 shown and the ideal position waveform 50. The ideal position waveform 50 is a waveform representing the ideal external shape of the substrate 10, and can be understood as a reference shape (first reference shape) representing the external shape of the substrate 10. The controller 130 can obtain the eccentricity (X, Y) and the rotation angle θ of the substrate 10 relative to the rotation center 125 of the substrate holder 110 to the substrate 10 based on the position waveform 51, thereby obtaining the ideal position waveform 50 using the following formula (1).

[0062]

[0063] Here, we will refer to Figure 8 Describe formula (1). Figure 8 , the θZ direction indicates the circumferential direction of the substrate 10, and the R direction indicates the radial direction of the substrate 10. Figure 8As shown, when the center of gravity 24 (center) of the substrate 10 is eccentric with respect to the rotation center 125 of the substrate 10 by the substrate holder 110, "r" represents the size of the eccentric vector 25 (the distance between the rotation center 125 and the center of gravity 24 of the substrate 10). "θ" represents the rotation angle of the substrate 10 by the substrate holder 110. The rotation angle θ can be understood as representing the θZ direction position of the peripheral edge portion 12 where the light intensity distribution is measured by the measuring device 120. A straight line connecting the rotation center 125 and the light receiving unit 122 (light receiving element 122a) is defined, and "α" represents the angle formed by the straight line and the eccentric vector 25. "L" represents the radius 26 of the substrate 10.

[0064] Alternatively, if Fig. 7A As shown, the controller 130 may obtain the evaluation value based on the similarity between the partial waveform 53 representing the shape of the cutout portion of the substrate 10 and the ideal partial waveform 54 representing the ideal external shape of the cutout portion. The similarity between the partial waveform 53 and the ideal partial waveform 54 may be based on Figure 7B The error 55 between the partial waveform 53 shown in FIG. 1 and the ideal partial waveform 54 is calculated. The ideal partial waveform 54 can be understood as a reference shape (second reference shape) representing the external shape of the cutout portion of the substrate 10, and can be obtained based on the design information (design data or standard information) of the cutout portion of the substrate 10.

[0065] [Operation sequence of pre-alignment processing]

[0066] Next, the operation sequence of the pre-alignment processing of the present embodiment will be described. Fig. 9 : is a flowchart showing the operation sequence of the pre-alignment processing of the present embodiment. Fig. 9 The flowchart may be executed by the controller 130 .

[0067] In step S101, the controller 130 controls the light of the light source unit 121 in the measuring device 120 before loading the substrate 10 on the substrate holder 110 of the substrate processing apparatus 100. The light control of the light source unit 121 is preferably performed in a state where the substrate 10 as a light shielding object does not exist in the light path. If the light control of the light source unit 121 is performed after the substrate 10 is loaded on the substrate holder 110, the light amount cannot be checked in the portion shielded by the substrate 10. Therefore, during the rotation operation of the substrate 10, the signal strength may exceed the allowable value.

[0068] In step S102, the controller 130 loads the substrate 10 onto the substrate holder 110 of the substrate processing apparatus 100 through a substrate conveying mechanism (substrate conveying robot) (not shown). The substrate 10 loaded onto the substrate holder 110 is held by the substrate chuck 111. At the stage where the substrate 10 is loaded onto the substrate holder 110, positioning of the substrate 10 is not performed, and the substrate 10 deviates from a desired position on the substrate holder 110 in the translation direction and the rotation direction.

[0069] Steps S103 to S105 constitute a step (a first measurement step) in which the measuring device 120 measures the light intensity distribution. In step S103, the controller 130 starts to rotationally drive the substrate 10 in the θZ direction by the substrate holder 110 (rotation driver 112), and also starts to measure the light intensity distribution in the peripheral edge portion 12 of the substrate 10 by the measuring device 120. In step S104, the controller 130 sequentially acquires information (data) of the light intensity distribution measured by the measuring device 120 from the measuring device 120, and stores it in the storage unit 132. Then, in step S105, after the substrate 10 is rotated by the amount of rotation required to determine the position of the substrate 10 (e.g., 360°), the controller 130 ends the rotational drive of the substrate 10 by the substrate holder 110 and the measurement of the light intensity distribution by the measuring device 120. The measurement of the light intensity distribution is performed while the substrate holder 110 (rotation driver 112) rotationally drives the substrate 10 in the θZ direction. That is, while the substrate 10 is rotationally driven by the substrate holder 110, the measuring device 120 sequentially (continuously) measures the light intensity distribution in the radial direction in a portion of the peripheral edge portion 12 of the substrate 10. In this way, the controller 130 can obtain the light intensity distribution in the radial direction for the entire peripheral edge portion 12 of the substrate 10.

[0070] In step S106, the controller 130 applies each of the plurality of types of algorithms to the light intensity distribution acquired through steps S103 to S105 to specify a plurality of edge position candidates according to the light intensity distribution (specifying step). The plurality of types of algorithms are set to specify the edge position according to the type of substrate 10, and are stored in the storage unit 132. The controller 130 reads out the plurality of algorithms from the storage unit 132, and applies each of the plurality of types of algorithms to one light intensity distribution. Therefore, the controller 130 can specify a plurality of edge position candidates according to one light intensity distribution. For each light intensity distribution acquired sequentially through steps S103 to S105, as described above, a plurality of edge position candidates are specified using the plurality of types of algorithms.

[0071] Here, as described above, the plurality of types of algorithms may include at least two types of algorithms that are different from each other in terms of a determination threshold for specifying the edge position of the substrate 10 according to a light intensity distribution. In addition, the plurality of types of algorithms may include at least two types of algorithms that are different from each other in terms of a predetermined condition for selecting a point from a plurality of points in a light intensity distribution when there are a plurality of points whose light intensity matches the determination threshold. The predetermined condition may include a condition regarding the number of times the light intensity in the light intensity distribution matches the determination threshold in the direction from the edge toward the center of the substrate 10. For example, the predetermined condition may be a condition that specifies a point at which the light intensity in the light intensity distribution in the direction from the edge toward the center of the substrate 10 is lower than the determination threshold a predetermined number of times as the edge position of the substrate 10. Alternatively, the predetermined condition may be a condition that specifies a point at which the number of pixels of the light receiving element 122a at which the light intensity is continuously lower than the determination threshold in the light intensity distribution reaches a predetermined number as the edge position of the substrate 10.

[0072] As a specific example, the various types of algorithms may include an algorithm that specifies a point 141a in the light intensity distribution 141 where the light intensity first falls below the determination threshold 151 in the direction from the edge toward the center of the substrate 10 as the edge position of the substrate 10, such as Figure 2 The various types of algorithms may include an algorithm that specifies a point 142a in the light intensity distribution 142 where the light intensity first falls below the determination threshold 152 in the direction from the edge of the substrate 10 toward the center as the edge position of the substrate 10, such as Figure 3 The various types of algorithms may include an algorithm that specifies a point 143a in the light intensity distribution 143 where the light intensity first falls below the determination threshold 153 in the direction from the edge of the substrate 10 toward the center as the edge position of the substrate 10, such as Figure 4 Example shown.

[0073] In addition, the various types of algorithms may include an algorithm that specifies a point 144a in the light intensity distribution 144 where the light intensity first falls below a determination threshold 154a in a direction from the edge toward the center of the substrate 10 as an edge position of the substrate 10, such as Figure 5 The various types of algorithms may include an algorithm that specifies a point 144b in the light intensity distribution 144 where the light intensity is lower than a determination threshold 154b for the second time in a direction from the edge of the substrate 10 toward the center as an edge position of the substrate 10, such as Figure 5 The various types of algorithms may include an algorithm that specifies a point 145a in the light intensity distribution 145 where the light intensity first falls below a determination threshold 155 in a direction from the edge of the substrate 10 toward the center as an edge position of the substrate 10, such as Figure 6Note that the determination thresholds 151 to 155 may be different values ​​from each other.

[0074] In step S107, the controller 130 calculates the Fig. 7A . As described above, the position waveform 51 is a waveform indicating the relationship between the θZ direction position and the edge position of the substrate 10, and can be understood as representing the external shape of the substrate 10. The position waveform 51 may include a partial waveform 53 corresponding to the cutout portion of the substrate 10. For example, the controller 130 draws edge position candidates of the substrate 10 specified for each algorithm based on the θZ direction position of the substrate 10. Therefore, the controller 130 can calculate the position waveform 51 for each algorithm. In addition, in step S107, the controller 130 can calculate the ideal position waveform 50 as described above.

[0075] In step S108, the controller 130 obtains an evaluation value of each of the plurality of edge position candidates (evaluation step). Step S108 may be understood as a step of obtaining evaluation values ​​of each of the plurality of types of algorithms. In the present embodiment, the controller 130 may obtain the evaluation value based on at least one of the similarity between the position waveform 51 and the ideal position waveform 50, the roundness 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 controller 130 may obtain the evaluation value based on the similarity between the position waveform 51 and the ideal position waveform 50, the roundness 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. Figure 7B The controller 130 may obtain the evaluation value by calculating the similarity between the position waveform 51 and the ideal position waveform 50 based on the sum value or variance value of the error 52 between the position waveform 51 and the ideal position waveform 50. Alternatively, the controller 130 may obtain the evaluation value by calculating the circularity based on the error between the true circle and the outer shape of the substrate 10 obtained from the position waveform 51. Figure 7B The sum value or variance value of the error 55 between the partial waveform 53 and the ideal partial waveform 54 shown is used to calculate the similarity between the partial waveform 53 and the ideal partial waveform 54 to obtain the evaluation value.

[0076] Here, the controller 130 may obtain an evaluation value based on a plurality of evaluation indices obtained from the edge position candidate. The plurality of evaluation indices may include at least two of the similarity between the position waveform 51 and the ideal position waveform 50, the roundness 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 controller 130 may weight each of the plurality of evaluation indices and obtain an evaluation value based on the weighted result. For example, the controller 130 may obtain the sum of the plurality of weighted evaluation indices as the evaluation value.

[0077] In step S109, the controller 130 selects one algorithm for determining the position of the substrate 10 from a plurality of algorithms as an optimal algorithm based on the evaluation value obtained for each edge position candidate in step S108 (selection step). For example, the controller 130 may select an edge position candidate having the best evaluation value among a plurality of edge position candidates, and select an algorithm for specifying the selected edge position candidate as the optimal algorithm. As a specific example, in the case where the sum of the errors 52 between the position waveform 51 and the ideal position waveform 50 is obtained as the evaluation value, the controller 130 may select an algorithm for specifying an edge position candidate having the smallest evaluation value among a plurality of edge position candidates as the optimal algorithm. On the other hand, in the case where the inverse of the sum of the errors 52 between the position waveform 51 and the ideal position waveform 50 is obtained as the evaluation value, the controller 130 may select an algorithm for specifying an edge position candidate having the largest evaluation value among a plurality of edge position candidates as the optimal algorithm.

[0078] Steps S110 to S113 constitute steps of controlling the positioning of the substrate 10 by using the optimal algorithm selected in step S109. In the present embodiment, the positioning of the substrate 10 may include the positioning of the substrate 10 held by the substrate holder 110, and the positioning of the substrate 10 when the substrate 10 is transported from the substrate holder 110 to a target transport destination. An example of the target transport destination is a substrate stage of a lithography apparatus.

[0079] In step S110, the controller 130 detects the position of the peripheral edge portion 12 (e.g., the cutout portion) of the substrate 10 held by the substrate holder 110 based on the edge position candidate specified by the optimal algorithm. Then, in step S111, the controller 130 performs precision measurement (a second measurement step) of re-measuring the light intensity distribution in the peripheral edge portion 12 of the substrate 10 by the measuring device 120. In the precision measurement, the controller 130 first positions the substrate 10 based on the position of the peripheral edge portion 12 (cutout portion) of the substrate 10 detected in step S110 so that the peripheral edge portion 12 (cutout portion) of the substrate 10 is arranged in the optical path of the measuring device 120. The positioning of the substrate 10 may be performed by the substrate holder 110 translationally and rotationally driving the substrate 10, or may be performed by re-placing the substrate 10 on the substrate holder 110 by a substrate conveying mechanism (substrate conveying robot) (not shown). Then, while the substrate holder 110 rotationally drives the substrate 10, the controller 130 sequentially measures the light intensity distribution in the peripheral edge portion 12 of the substrate 10 through the measuring device 120. In the present embodiment, the controller 130 can precisely measure the light intensity distribution in the cutout portion in the peripheral edge portion 12 of the substrate 10. By performing precise measurement as described above, the degradation of processing accuracy due to positional deviation of the substrate 10 can be reduced in subsequent substrate conveying operations and processing operations.

[0080] In step S112, the controller 130 determines the position of the substrate 10 (decision step). More specifically, the controller 130 specifies the edge position of the substrate 10 by applying an optimal algorithm to the light intensity distribution acquired in step S111. Then, the controller 130 calculates the position waveform 51 according to the specified edge 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 outer shape of the local area including the cutout portion in the peripheral edge portion 12 of the substrate 10, the edge position of the substrate 10, and the center of gravity position of the substrate 10.

[0081] In step S113, the controller 130 conveys the substrate 10 from the substrate holder 110 to the target conveying destination through the substrate conveying mechanism (substrate conveying robot) (not shown). At this time, the controller 130 may control the positioning of the substrate 10 when conveying the substrate 10 from the substrate holder 110 to the target conveying destination based on the position of the substrate 10 determined in step S112. For example, the controller 130 may calculate the eccentricity of the position X, Y, and θZ of the substrate 10 relative to the substrate holder 110 based on the position of the substrate 10 determined in step S112, and control the positioning of the substrate 10 based on the eccentricity. The positioning of the substrate 10 may be controlled so that the substrate 10 is set at a predetermined position and orientation.

[0082] Here, we will refer to Figures 10 to 12 The above steps S106 to S109 are described in more detail. In step S106, if Fig.10 As shown, the controller 130 applies multiple types of algorithms A to D to one light intensity distribution to specify edge position candidates for each algorithm. In step S107, the controller 130 calculates the position waveform 51 and the ideal position waveform 50 for each algorithm based on the edge position candidates specified for each algorithm in step S106.

[0083] In step S108, Fig.11A As shown, the controller 130 calculates the outer shape of the substrate 10 as the substrate peripheral shape based on the position waveform 51, and calculates the ideal circle (first reference shape) based on the ideal position waveform 50. In this way, the controller 130 can obtain an evaluation value based on the similarity between the position waveform 51 and the ideal position waveform 50 obtained based on the difference between the substrate peripheral shape and the ideal circle, and / or the circularity of the substrate peripheral shape. In addition, as Fig. 11B As shown, the controller 130 calculates the outer shape of the cutout portion of the substrate 10 (hereinafter sometimes referred to as the cutout shape) based on the partial waveform 53, and calculates the ideal cutout shape (second reference shape) of the substrate 10 based on the ideal partial waveform 54. In this way, the controller 130 can obtain an evaluation value based on the similarity between the partial waveform 53 obtained based on the difference between the cutout shape and the ideal cutout shape and the ideal partial waveform 54. The evaluation value is obtained for each algorithm. Fig.12 The evaluation values ​​obtained for each of the multiple types of algorithms A to D are schematically shown. In step S109, the controller 130 may select an algorithm having the best evaluation value from the multiple types of algorithms A to D based on the evaluation values ​​obtained for each of the algorithms A to D ( Fig.12 Algorithm C) in is taken as the optimal algorithm.

[0084] In step S108, a plurality of evaluation indices used to calculate the evaluation value may be weighted. The weighting process in step S108 will be described below. Figure 5 The light intensity distribution 144 shown in FIG. 1 is an example of applying two types of algorithms. The two types of algorithms include a first algorithm for detecting the edge position (first edge position) of the support substrate 10a and a second algorithm for detecting the edge position (second edge position) of the opaque substrate 10b.

[0085] In step S106 and step S107, the controller 130 uses the first algorithm and specifies the point 144a in the light intensity distribution 144 as the edge position (first edge position) of the support substrate 10a. In this way, the position waveform 64 and the ideal position waveform 63 of the first edge position can be obtained, as shown in FIG. Fig.13A Similarly, the controller 130 uses the second algorithm and specifies the point 144b in the light intensity distribution 144 as the edge position (second edge position) of the opaque substrate 10b. In this way, the position waveform 66 and the ideal position waveform 65 of the second edge position can be obtained, as shown in FIG. Fig.13A shown.

[0086] Then, in step S108, when calculating the evaluation values ​​from the respective position waveforms, the controller 130 performs a predetermined weighting process on at least one of the evaluation value of the first edge position and the evaluation value of the second edge position. Here, the predetermined weighting process may be performed based on the evaluation value of the first edge position obtained from the difference between the position waveform 64 and the ideal position waveform 63, and the evaluation value of the second edge position obtained from the difference between the position waveform 66 and the ideal position waveform 65.

[0087] For example, Fig.13A An example is shown in which the evaluation value obtained from the position waveform 64 and the ideal position waveform 63 of the first edge position is comparable to the evaluation value obtained from the position waveform 66 and the ideal position waveform 65 of the second edge position. In this example, a predetermined weighting process is performed so that the evaluation value of the second edge position is superior to the evaluation value of the first edge position. It can be understood that when the evaluation value of the first edge position is comparable to the evaluation value of the second edge position, the difference between the evaluation value of the first edge position and the evaluation value of the second edge position is less than the threshold value.

[0088] on the other hand, Fig. 13B An example is shown in which the evaluation value obtained from the position waveform 68 and the ideal position waveform 67 of the first edge position is sufficiently superior to the evaluation value obtained from the position waveform 70 and the ideal position waveform 69 of the second edge position. In this example, a predetermined weighting process is performed so as not to affect the priority order of the evaluation value of the first edge position and the evaluation value of the second edge position.

[0089] That is, in step S109, based on the weighted processing, if the evaluation value of the first edge position is comparable to the evaluation value of the second edge position, the second algorithm for detecting the second edge position is selected as the optimal algorithm. On the other hand, if the evaluation value of the first edge position is sufficiently superior to the evaluation value of the second edge position, the first algorithm for detecting the first edge position is selected as the optimal algorithm.

[0090] As described above, the substrate processing apparatus 100 of the present embodiment applies multiple types of algorithms to one light intensity distribution measured by the measuring device 120 to specify multiple edge position candidates based on the one light intensity distribution. Then, based on the multiple edge position candidates, one algorithm for determining the position of the substrate 10 is selected from the multiple types of algorithms as an optimal algorithm. According to the present embodiment, the optimal algorithm can be appropriately selected using one light intensity distribution without performing the process of measuring the light intensity distribution by the measuring device 120 while the substrate 10 is rotationally driven multiple times by changing the type of the algorithm. That is, when detecting the position of the substrate 10, throughput and detection accuracy can be achieved at the same time.

[0091] <Second Embodiment>

[0092] A second embodiment according to the present invention will be described. This embodiment basically follows the first embodiment, and matters not mentioned below can follow the first embodiment.

[0093] Fig.14 : is a flowchart showing the operation sequence of the pre-alignment processing of the present embodiment. Fig.14 The flowchart may be executed by the controller 130. Note that Fig.14 Steps S201 to S204 of the flowchart of Fig. 9 Steps S101 to S104 of the flowchart are similar, so a detailed description will be omitted here.

[0094] In step S205, the controller 130 applies each of the multiple types of algorithms to the light intensity distribution sequentially acquired from the measuring device 120 in step S204 to specify multiple edge position candidates based on the light intensity distribution. At this time, the controller 130 stores the specified multiple edge position candidates in the storage unit 132. In this way, whenever the light intensity distribution is acquired from the measuring device 120 in step S204, the controller 130 of the present embodiment applies each of the multiple types of algorithms to the light intensity distribution to specify multiple edge position candidates. That is, in the present embodiment, measuring the light intensity distribution in step S204 and specifying multiple edge position candidates in step S205 are performed in parallel. Note that since step S205 is parallel to step S205, the light intensity distribution is measured in step S204 and the multiple edge position candidates are specified in step S205. Fig. 9 The flowchart of FIG. 1 is similar to step S106, so a detailed description will be omitted here.

[0095] In step S206, after the substrate 10 is rotated by the amount of rotation required to determine the position of the substrate 10 (e.g., 360°), the controller 130 ends the rotation drive of the substrate 10 by the substrate holder 110 and the measurement of the light intensity distribution by the measurement device 120. Fig. 9 The flowchart of FIG. 1 is similar to step S105, so a detailed description will be omitted here.

[0096] In step S207, the controller 130 detects the position of the peripheral edge portion 12 (e.g., the cutout portion) of the substrate 10 held by the substrate holder 110. The detection of the position of the peripheral edge portion 12 in step S207 may be performed based on edge position candidates obtained by a pre-specified algorithm, or may be performed based on edge position candidates obtained by an algorithm used in a previous decision step. The algorithm used in the previous decision step may be an algorithm used for a previous batch, or an algorithm used for a previous substrate.

[0097] In step S208, the controller 130 positions the substrate 10 based on the position of the peripheral edge portion 12 (cutout portion) of the substrate 10 detected in step S207 so that the peripheral edge portion 12 (cutout portion) of the substrate 10 is arranged in the optical path of the measurement device 120. The positioning of the substrate 10 may be performed by driving the substrate 10 translationally and rotationally by the substrate holder 110, or may be performed by re-placing the substrate 10 on the substrate holder 110 by a substrate conveying mechanism (substrate conveying robot) (not shown).

[0098] Step S209 and step S210 are performed in parallel with step S208. In step S209, the controller 130 obtains an evaluation value for each of the plurality of edge position candidates. Then, in step S210, the controller 130 selects one algorithm for determining the position of the substrate 10 from the plurality of algorithms as the optimal algorithm based on the evaluation value obtained for each edge position candidate in step S209. Note that since steps S209 and S210 are respectively Fig. 9 Step S108 and step S109 of the flowchart are similar, so a detailed description will be omitted here.

[0099] In step S211, the controller 130 performs precision measurement of re-measuring the light intensity distribution in the peripheral edge portion 12 of the substrate 10 by the measuring device 120. In the precision measurement of the present embodiment, since the positioning of the substrate 10 has been performed in step S208, only the following steps may be performed: while the substrate 10 is rotationally driven by the substrate holder 110, the light intensity distribution in the peripheral edge portion 12 of the substrate 10 is sequentially measured by the measuring device 120. Note that since step S211 is similar to step S208, the light intensity distribution in the peripheral edge portion 12 of the substrate 10 is sequentially measured by the measuring device 120. Fig. 9 The flowchart of FIG. 1 is similar to step S111, so a detailed description will be omitted here.

[0100] In step S212, the controller 130 determines the position of the substrate 10. More specifically, the controller 130 specifies the edge position of the substrate 10 by applying the optimal algorithm to the light intensity distribution acquired in step S211. Then, in step S213, the controller 130 transports the substrate 10 from the substrate holder 110 to the target transport destination through a substrate transport mechanism (substrate transport robot) (not shown). Note that since steps S212 and S213 are identical, Fig. 9 Step S112 and step S113 of the flowchart are similar, so a detailed description will be omitted here.

[0101] As described above, in the present embodiment, the calculation of the evaluation value is performed in parallel with the control of the positioning of the substrate 10. In this way, the throughput of the substrate processing apparatus 100 can be further improved.

[0102] <Third Embodiment>

[0103] A third embodiment according to the present invention will be described. This embodiment basically follows the first embodiment, and matters not mentioned below can follow the first embodiment. The second embodiment can be applied to this embodiment.

[0104] Fig.15 : is a flowchart showing the operation sequence of the pre-alignment processing of the present embodiment. Fig.15 The flowchart may be executed by the controller 130. Note that Fig.15 Steps S301 to S310 of the flowchart of Fig. 9 Steps S101 to S110 of the flowchart are similar, so a detailed description will be omitted here.

[0105] In step S311, the controller 130 positions the substrate 10 based on the position of the peripheral edge portion 12 (cut portion) of the substrate 10 detected in step S310 so that the peripheral edge portion 12 (cut portion) of the substrate 10 is arranged in the optical path of the measurement device 120. The positioning of the substrate 10 may be performed by driving the substrate 10 translationally and rotationally by the substrate holder 110, or may be performed by re-placing the substrate 10 on the substrate holder 110 by a substrate conveying mechanism (substrate conveying robot) (not shown).

[0106] In step S312, the controller 130 starts translationally driving the substrate 10 in the X direction by the substrate holder 110 (translation driver 113), and starts measuring the light intensity distribution by the measuring device 120. For example, during the translationally driving the substrate 10 in the X direction by the substrate holder 110, the light receiving unit 122 (light receiving element 122a) of the measuring device 120 receives the light from the light source unit 121, thereby continuously acquiring the light intensity distribution in the peripheral edge portion 12 of the substrate 10 including the cutout portion in the X direction. That is, in step S312, by driving the cutout portion of the substrate 10 translationally in the X direction relative to the optical path of the measuring device 120, the light intensity distribution in the cutout portion of the substrate 10 is measured.

[0107] In step S313, the controller 130 sequentially acquires information (data) of the light intensity distribution measured by the measuring device 120 from the measuring device 120 and stores it in the storage unit 132. After the substrate 10 is translationally driven by an amount required to determine the position of the substrate 10, the controller 130 ends the translational drive of the substrate 10 and the measurement of the light intensity distribution by the measuring device 120 in step S314.

[0108] In step S315, the controller 130 applies each of the plurality of types of algorithms to the light intensity distributions sequentially acquired through steps S312 and S313, thereby specifying a plurality of candidates (candidates of cutout positions) for the positions of the cutout portions of the substrate 10. In this way, the controller 130 can obtain the following for each algorithm: Fig.16A The cutout waveform 60 is a waveform corresponding to the cutout portion of the substrate 10. Fig.16A , the horizontal axis represents the θZ direction position of the peripheral edge portion 12 where the light intensity distribution is measured by the measuring device 120 (i.e., the rotation angle θ of the substrate 10), and the vertical axis represents the edge position in the radial direction specified according to the light intensity distribution measured by the measuring device 120.

[0109] In step S316, the controller 130 calculates an ideal cut waveform 61 by performing a curve approximation using the least square method on the cut waveform 60. The ideal cut waveform 61 can be understood as representing an ideal external shape of the cut portion of the substrate 10. Note that in the present embodiment, the cut portion of the substrate 10 is represented as a notch, but the cut portion of the substrate 10 may be an oriented plane. In the case where the cut portion of the substrate 10 is an oriented plane, the controller 130 calculates the ideal cut waveform by performing a linear approximation using the least square method on the waveform corresponding to the cut portion of the substrate 10.

[0110] In step S317, the controller 130 obtains the evaluation value of each of the plurality of incision position candidates. Fig. 16BAs shown, the controller 130 obtains the error 62 between the notch waveform 60 and the ideal notch waveform 61, and obtains the evaluation value based on the error 62. For example, the controller 130 may obtain the evaluation value based on the sum value or variance value of the error 62. The evaluation value may be obtained for each algorithm. Here, if steps S312 to S316 are performed multiple times, the evaluation value may be based on the average value of the sum values ​​of the errors 62 obtained multiple times.

[0111] In step S318, the controller 130 compares the evaluation values ​​obtained for the algorithms obtained in step S317, and selects the algorithm having the best evaluation value as the optimal algorithm. The optimal algorithm selected in step S318 may be the same as or different from the optimal algorithm selected in step S309.

[0112] In step S319, the controller 130 uses the optimal algorithm selected in step S318 to determine the position of the substrate 10. More specifically, the controller 130 applies the optimal algorithm to the light intensity distribution acquired through steps S312 to S314, thereby specifying the edge position of the substrate 10. Then, the controller 130 calculates a position waveform according to the specified edge position of the substrate 10, and determines the position of the substrate 10 based on the position waveform.

[0113] In step S320, the controller 130 transfers the substrate 10 from the substrate holder 110 to the target transfer destination through a substrate transfer mechanism (substrate transfer robot) (not shown). At this time, the controller 130 may control the positioning of the substrate 10 when transferring the substrate 10 from the substrate holder 110 to the target transfer destination based on the position of the substrate 10 determined in step S319. Note that step S320 is similar to step S321. Fig. 9 The flowchart is similar to step S113, so the detailed description will be omitted here.

[0114] According to the present embodiment, as in the first embodiment, when detecting the position of the substrate 10 , both the throughput and the detection accuracy can be achieved.

[0115] <Fourth Embodiment>

[0116] A fourth embodiment according to the present invention will be described. This embodiment basically follows the first embodiment, and matters not mentioned below may follow the first embodiment. The second embodiment and / or the third embodiment may be applied to this embodiment.

[0117] Fig.17 : is a flowchart showing the operation sequence of the pre-alignment processing of the present embodiment. Fig.17 The flowchart may be executed by the controller 130. Note that, in addition to adding steps S114 to S115, Fig.17 Flowchart and Fig. 9Therefore, step S114 and step S115 will be described below, and detailed descriptions of other steps S101 to S113 will be omitted.

[0118] Step S114 is inserted between step S108 and step S109. In step S114, the controller 130 compares the evaluation values ​​obtained in step S108 for the plurality of edge position candidates respectively with the reference value to determine whether there is an edge position candidate having an evaluation value higher than the reference value. The reference value is set in advance to an evaluation value calculated based on a position waveform obtained when the position of the cutout portion 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 an edge position candidate having an evaluation value higher than the reference value, the process proceeds to step S109. If there is no edge position candidate having an evaluation value higher than the reference value, the process proceeds to step S115. In step S115, the controller 130 changes the plurality of types of algorithms applied to the light intensity distributions sequentially acquired through steps S103 to S105. Then, after changing the plurality of types of algorithms, the controller 130 performs steps S106 to S108. Here, the light intensity distributions applied by the plurality of types of algorithms after the change are the same as the light intensity distributions applied by the plurality of types of algorithms before the change. The various types of algorithms after the change may be different from the various types of algorithms before the change in determining the threshold value or the predetermined condition.

[0119] In this embodiment, with respect to the algorithm selected as the optimal algorithm in the pre-alignment processing performed in the past, the frequently selected algorithm and the infrequently selected algorithm can be applied to the light intensity distribution, respectively. More specifically, in the first step S106, the frequently selected algorithm used in the past pre-alignment processing can be applied to the light intensity distribution. On the other hand, if all evaluation values ​​obtained by the frequently selected algorithm are lower than the reference value, the infrequently selected algorithm can be applied to the light intensity distribution in the second step S106.

[0120] As described above, in the present embodiment, the algorithm for calculating the evaluation value and selecting the algorithm can be changed (switched). That is, fewer algorithms (algorithms that are often selected as the optimal algorithms) are applied in the first step S106 to step S108 than in the first embodiment. Therefore, compared with the first embodiment, the time required for the calculation processing using the algorithm can be shortened, and the throughput can be improved.

[0121] Note that the above embodiments are examples only. The present invention is not limited to the above arrangements and shapes, and modifications and changes may be made as appropriate within the scope of the present invention. For example, there may be two or more measuring devices 120 (sensors), and different algorithms may be applied to multiple measuring devices 120.

[0122] <Embodiment of Photolithography Apparatus>

[0123] An embodiment of the photolithography apparatus according to the present invention will be described. The photolithography apparatus is an apparatus that is used for a photolithography process as a manufacturing process of a semiconductor device or a liquid crystal display device, and forms a pattern on a substrate. As the photolithography apparatus, there is an available exposure apparatus that transfers the pattern of the original plate onto the substrate by exposing the substrate to light that passes through the original plate. The exposure apparatus as the photolithography apparatus will be exemplified below.

[0124] Fig.18 2 is a schematic diagram showing an example of the arrangement of the exposure device 200. The exposure device 200 transfers the pattern on the original plate R onto the substrate S by, for example, a step-and-repeat scheme or a step-and-scan scheme. Fig.18 As shown, the exposure device 200 may include an illumination optical system 201, a master stage 202, a projection optical system 203, a substrate stage 204, a conveying device 205, and a controller 206. In the exposure device 200, the illumination optical system 201, the master stage 202, the projection optical system 203, and the substrate stage 204 are used as a forming unit for forming a pattern on a substrate S.

[0125] The exposure device 200 includes the above-mentioned substrate processing device 100 that processes the substrate S. The substrate processing device 100 performs a pre-alignment process on the substrate S when processing the substrate S. Then, the substrate S processed by the substrate processing device 100 is transported to the substrate stage 204 by the transport device 205. For example, the controller 130 of the substrate processing device 100 controls the positioning of the substrate S when the substrate S is transported to the substrate stage 204 by the transport device 205 based on the position of the substrate S determined by the pre-alignment process of the substrate S. Note that the controller 206 of the exposure device 200 and the controller 130 of the substrate processing device 100 may be formed integrally or separately.

[0126] <Example of the method for manufacturing an article>

[0127] The lithography apparatus as described above can be used to carry out an article manufacturing method for manufacturing various articles (for example, semiconductor IC devices, liquid crystal display devices, and MEMS). The article manufacturing method according to an embodiment of the present invention is suitable for manufacturing articles such as devices (semiconductor devices, magnetic storage media, or liquid crystal display devices). The article manufacturing method includes a processing step of processing a substrate by the above-mentioned substrate processing method (substrate processing device), a forming step of forming a pattern on the substrate after the processing step, and a manufacturing step of manufacturing an article from the substrate after the forming step. The processing step can be understood as a step of performing a pre-alignment process when processing the substrate. The product manufacturing method may also include other known steps (oxidation, deposition, vapor deposition, doping, planarization, etching, resist removal, cutting, bonding, packaging, etc.). Compared with conventional methods, the article manufacturing method according to this embodiment has advantages in at least one aspect of the performance, quality, productivity, and production cost of the article.

[0128] <Other embodiments>

[0129] The embodiments of the present invention may also be implemented by reading and executing computer executable instructions (e.g., one or more programs) recorded on a storage medium (which may also be more completely referred to as a "non-transitory computer-readable storage medium") to perform one or more functions in the above-mentioned embodiments, and / or a computer of a system or device including one or more circuits (e.g., an application-specific integrated circuit (ASIC)) for performing one or more functions in the above-mentioned embodiments, and the embodiments of the present invention may be implemented by, for example, reading and executing the computer executable instructions from the storage medium by the computer of the system or device to perform one or more functions in the above-mentioned embodiments, and / or controlling the one or more circuits to perform one or more functions in the above-mentioned embodiments. The computer may include one or more processors (e.g., a central processing unit (CPU), a microprocessing unit (MPU)), and may include a network of separate computers or separate processors to read and execute the computer executable instructions. The computer executable instructions may be provided to the computer, for example, from a network or the storage medium. The storage medium may include, for example, a hard disk, a random access memory (RAM), a read-only memory (ROM), a memory of a distributed computing system, an optical disk (such as a compact disc (CD), a digital versatile disc (DVD), or a Blu-ray disc (BD) TM ), flash memory devices, memory cards, etc.

[0130] The embodiments of the present invention may also be implemented by providing software (program) for performing the functions of the above-described embodiments to a system or device via a network or various storage media, and a computer or a central processing unit (CPU) or a microprocessing unit (MPU) of the system or device reads and executes the program.

[0131] While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments.The scope of the following claims is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures and functions.

Claims

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

2. The substrate processing method according to claim 1, wherein: Each of the plurality of types of algorithms is configured to specify the edge position based on a point in the light intensity distribution where the light intensity matches a determined threshold, and The plurality of types of algorithms include at least two types of algorithms that are different from each other in the determination threshold value.

3. The substrate processing method according to claim 1, wherein: Each of the plurality of types of algorithms is configured to specify the edge position based on a point satisfying a predetermined condition among a plurality of points in the light intensity distribution where the light intensity matches a determination threshold, and The plurality of types of algorithms include at least two types of algorithms that are different from each other in the predetermined condition.

4. The substrate processing method according to claim 1, further comprising the following steps: an obtaining step of obtaining an evaluation value for each of the plurality of candidates specified in the specifying step, in, In the selecting step, one algorithm is selected from the plurality of types of algorithms based on the evaluation values ​​obtained for the respective ones of the plurality of candidates obtained in the obtaining step.

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

6. The substrate processing method according to claim 4, wherein: In the obtaining 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 edge position.

7. The substrate processing method according to claim 4, wherein: In the obtaining step, the evaluation value is obtained for each of the plurality of candidates based on a similarity between a shape of the cutout portion of the substrate obtained from the edge position and a second reference shape.

8. The substrate processing method according to claim 4, wherein: In the obtaining step, the evaluation value is obtained for each of the plurality of candidates specified in the specifying step based on a plurality of evaluation indices obtained from the edge position, and The plurality of evaluation indexes include at least two of similarity between an outer shape of the substrate obtained from the edge position and a first reference shape, roundness of the outer shape of the substrate obtained from the edge position, and similarity between a shape of a cutout portion of the substrate obtained from the edge position and a second reference shape.

9. The substrate processing method according to claim 8, wherein: In the obtaining step, the evaluation value is obtained based on a result of applying a predetermined weighting to each of the plurality of evaluation indices.

10. The substrate processing method according to claim 4, further comprising the following steps: a re-measuring step of re-measuring a light intensity distribution obtained from the peripheral edge portion after positioning the substrate so that the peripheral edge portion of the substrate is arranged in an optical path of light from the light source unit; and determining the position of the substrate by applying the one algorithm selected in the selecting step to the light intensity distribution measured in the re-measuring step, in, The obtaining step is performed in parallel with the positioning of the substrate in the re-measuring step.

11. The substrate processing method according to claim 10, wherein: Positioning of the substrate in the re-measuring step is performed based on the candidate of the edge position specified in the specifying step using one of a pre-specified algorithm among the plurality of types of algorithms and the algorithm used in the previous deciding step.

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

13. A method for manufacturing an article, comprising the following steps: A processing step of processing the 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 after the processing step; and A manufacturing step of manufacturing an article from the substrate that has undergone the forming step.

14. A substrate processing device for processing a substrate, the substrate processing device comprising: a measuring device configured to measure a light intensity distribution obtained from the peripheral edge portion when the peripheral edge portion of the substrate is irradiated with light; as well as a controller configured to control positioning of the substrate, The controller specifies multiple candidates for the edge position of the substrate according to the light intensity distribution by applying each of multiple types of algorithms to the light intensity distribution measured by the measuring device, and selects an algorithm from the multiple types of algorithms for determining the position of the substrate based on the multiple candidates.

15. A lithography apparatus for forming a pattern on a substrate, the lithography apparatus comprising: The substrate processing device according to claim 14; as well as A forming device is configured to form a pattern on the substrate processed by the substrate processing apparatus.

16. A non-transitory computer-readable storage medium storing a program for causing a computer to execute a substrate processing method, the substrate processing method comprising the following steps: a specifying step of specifying a plurality of candidates for the edge position of the substrate according to the light intensity distribution by applying each of a plurality of types of algorithms to the light intensity distribution based on a result of measuring a light intensity distribution obtained from the peripheral edge portion of the substrate when the peripheral edge portion of the substrate is irradiated with light; and A selecting step of selecting one algorithm for determining the position of the substrate from among the plurality of types of algorithms based on the plurality of candidates specified in the specifying step.

17. A computer program product, comprising a program, wherein the program is used to cause a computer to execute a substrate processing method, wherein the substrate processing method comprises the following steps: a specifying step of specifying a plurality of candidates for the edge position of the substrate according to the light intensity distribution by applying each of a plurality of types of algorithms to the light intensity distribution based on a result of measuring a light intensity distribution obtained from the peripheral edge portion of the substrate when the peripheral edge portion of the substrate is irradiated with light; and A selecting step of selecting one algorithm for determining the position of the substrate from among the plurality of types of algorithms based on the plurality of candidates specified in the specifying step.

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