Inspection apparatus

Abstract

To provide an inspection apparatus with which accurate coordinates of a chip provided on a board can be obtained.SOLUTION: An inspection apparatus includes: a stage on which a target board is placed; a camera for imaging the target board to obtain a captured image; and a controller which calculates a target measurement value of target coordinates of a chip with respect to a target origin of the target board, on the basis of a distance between an image reference position and the chip in a pixel arrangement direction and a relative movement set value between the stage and the camera. The controller corrects the target measurement value by a projective transformation matrix to calculate a target correction value. The controller calculates an alignment measurement value of alignment coordinates with respect to an alignment origin, on the basis of a distance between the image reference position and an alignment mark which is aligned with the alignment origin of an alignment board. The controller calculates a parameter of the projective transformation matrix on the basis of the alignment measurement value and a known actual alignment measurement value.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to an inspection apparatus.

Background Art

[0002] As shown in Patent Document 1, an inspection apparatus that inspects a substrate based on an image obtained by imaging the substrate with a camera is known.

Prior Art Document

Patent Document

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] As this type of inspection apparatus, a substrate on which a plurality of chips are arranged side by side is placed on a stage, the substrate placed on the stage is imaged with a camera to obtain an imaging image, and the coordinates of each chip on the substrate are measured based on the imaging image.

[0005] However, in such an inspection apparatus, the measured values of the coordinates of each chip on the substrate obtained based on the imaging image may deviate from the true values due to various error factors.

[0006] The present disclosure has been made in view of such a point, and an object thereof is to provide an inspection apparatus capable of obtaining accurate coordinates of chips provided on a substrate.

Means for Solving the Problems

[0007] The inspection apparatus according to the present disclosure includes a stage on which a target substrate provided with a plurality of chips arranged side by side is placed, a camera that images the target substrate placed on the stage to obtain an imaged image partitioned into a plurality of pixels, and a distance in the direction in which the pixels are arranged between an image reference position in the imaged image and the chip reflected in the imaged image, and a relative movement set value between the stage and the camera, and a controller that calculates a target measurement value of the target coordinates of the chip with respect to a target origin provided on the target substrate. The controller corrects the target measurement value related to the target coordinates by a projective transformation matrix to calculate a target correction value related to the target coordinates. On the alignment substrate corresponding to the target substrate, a plurality of alignment marks corresponding to the plurality of chips are provided. On the alignment substrate, an alignment origin corresponding to the target origin is provided. The controller calculates an alignment measurement value of the alignment coordinates of the alignment mark with respect to the alignment origin based on the distance in the direction in which the pixels are arranged between the image reference position and the alignment mark reflected in the imaged image in a state where the alignment origin is aligned with the image reference position. The controller acquires a known alignment measured value of the alignment coordinates. The controller calculates the parameters of the projective transformation matrix based on the alignment measurement value and the alignment measured value.

[0008] In the inspection apparatus according to the present disclosure, the target measurement value of the target coordinates of the chip on the target substrate obtained based on the imaged image may deviate from the true value due to various error factors.

[0009] Therefore, in the inspection apparatus according to the present disclosure, by using the projective transformation matrix, the target measurement value is converted into a target correction value to approach the true value.

[0010] In particular, in the inspection apparatus according to the present disclosure, when obtaining the parameters of the projective transformation matrix, the alignment marks of the alignment substrate in a state where the alignment origin is aligned with the image reference position are used. Then, the parameters of the projective transformation matrix are calculated based on the alignment measurement values and known alignment measured values. Thereby, a highly accurate projective transformation matrix can be obtained.

[0011] As described above, it is possible to provide an inspection apparatus capable of obtaining accurate target coordinates of the chip provided on the target substrate.

[0012] In one embodiment, a plurality of the chips are provided on the target substrate in a line in a first direction and a second direction intersecting the first direction. The controller calculates a first target measurement value of a first target coordinate of the chip in the first direction with respect to the target origin based on a horizontal distance in a horizontal direction in which the pixels of the image reference position and the chip shown in the captured image are arranged, and a first relative movement setting value in the first direction between the stage and the camera. The controller calculates a second target measurement value of a second target coordinate of the chip in the second direction with respect to the target origin based on a vertical distance in a vertical direction in which the pixels of the image reference position and the chip shown in the captured image are arranged, and a second relative movement setting value in the second direction between the stage and the camera. The controller calculates a first target correction value related to the first target coordinate by correcting the first target measurement value related to the first target coordinate by the projective transformation matrix, and calculates a second target correction value related to the second target coordinate by correcting the second target measurement value related to the second target coordinate. The controller calculates a first alignment measurement value of a first alignment coordinate of the alignment mark in the first direction with respect to the alignment origin based on the horizontal distance in the horizontal direction in which the pixels of the image reference position and the alignment mark shown in the captured image are arranged with the alignment origin aligned with the image reference position. The controller calculates a second alignment measurement value of a second alignment coordinate of the alignment mark in the second direction with respect to the alignment origin based on the vertical distance in the vertical direction in which the pixels of the image reference position and the alignment mark shown in the captured image are arranged with the alignment origin aligned with the image reference position. The controller acquires a known first alignment actual measurement value related to the first alignment coordinate and a known second alignment actual measurement value related to the second alignment coordinate. The controller calculates the parameters of the projective transformation matrix based on the first alignment measurement value, the first alignment actual measurement value, the second alignment measurement value, and the second alignment actual measurement value.

[0013] According to such a configuration, even when the stage and the camera move relative to each other in the first direction and the second direction, the accurate first target coordinates and second target coordinates of the chip provided on the target substrate can be obtained.

[0014] In one embodiment, the controller uses the projective transformation matrix to correct the deviation of the target measurement value caused by the distortion of the camera to obtain the target correction value.

[0015] According to such a configuration, even when there is an error caused by the distortion of the camera, the projective transformation matrix can convert the target measurement value into a target correction value to approach the true value.

Advantages of the Invention

[0016] According to the present disclosure, it is possible to provide an inspection apparatus capable of obtaining accurate coordinates of a chip provided on a substrate.

Brief Description of the Drawings

[0017]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Embodiments for Carrying Out the Invention

[0018] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. The following description of the preferred embodiments is merely illustrative in nature and is in no way intended to limit the present disclosure, its applications, or its uses.

[0019] <First Embodiment> (Inspection Device) The inspection device 1 according to the first embodiment will be described. FIG. 1 shows the inspection device 1. The inspection device 1 includes a rail 10, a stage 20, a camera 30, and a controller 40. The rail 10 includes a first rail 11 and a second rail 12. The first rail 11 and the second rail 12 extend in the horizontal direction. The first rail 11 extends in the front-rear direction x as the first direction in the horizontal direction. The second rail 12 extends in the left-right direction y as the second direction in the horizontal direction. The front-rear direction x and the left-right direction y intersect (specifically, are orthogonal) to each other. The first rail 11 and the second rail 12 intersect at a reference position.

[0020] The stage 20 is formed, for example, in a plate shape with the up-down direction z as the thickness direction. The up-down direction z is orthogonal to the horizontal direction. The up-down direction z is also the vertical direction. The stage 20 extends in the horizontal direction.

[0021] The stage 20 is placed on the upper surface of the rail 10. Specifically, the stage 20 is placed on the upper surfaces of the first rail 11 and the second rail 12. The stage 20 moves along the rail 10 by an actuator (not shown). Specifically, the stage 20 moves in the front-rear direction x along the first rail 11. The stage 20 moves in the left-right direction y along the second rail 12.

[0022] The camera 30 is disposed above the stage 20. The camera 30 and the stage 20 are separated from each other in the vertical direction z. The imaging unit of the camera 30 faces the upper surface of the stage 20. The imaging axis of the camera 30 is orthogonal to the upper surface (horizontal plane) of the stage 20. The camera 30 is fixed by a bracket or the like (not shown). The camera 30 does not move along with the stage 20. Details of the camera 30 will be described later.

[0023] The controller 40 is built into the inspection apparatus 1 main body. The controller 40 includes, for example, a microcomputer mounted on a control board and a memory device that stores software for operating the microcomputer. The controller 40 controls an actuator to move the stage 20 along the rail 10. The controller 40 performs arithmetic processing described later.

[0024] (Target substrate) FIG. 2 shows the target substrate 50. The target substrate 50 is a substrate to be inspected by the inspection apparatus 1. The target substrate 50 is, for example, a semiconductor substrate. The target substrate 50 is, for example, in the shape of a rectangular plate.

[0025] The target substrate 50 is placed on the upper surface of the stage 20. The target substrate 50 moves in the front-rear direction x and the left-right direction y as the stage 20 moves along the rail 10.

[0026] A plurality of chips 51 are arranged side by side on the target substrate 50. When the target substrate 50 is placed on the stage 20, the plurality of chips 51 are arranged in a matrix in the front-rear direction x and the left-right direction y on the target substrate 50. The plurality of chips 51 are arranged at equal intervals in the front-rear direction x. The plurality of chips 51 are arranged at equal intervals in the left-right direction y.

[0027] The chip 51 is, for example, an integrated circuit. In FIG. 2, for clarity, the chip 51 is shown as a simple rectangular shape.

[0028] The target substrate 50 is provided with a target origin 52. The target origin 52 is constituted by, for example, a corner of the target substrate 50.

[0029] Let the coordinate of any chip 51 in the front-back direction x with respect to (referenced to) the target origin 52 be the first target coordinate X. Let the distance in the front-back direction x from the target origin 52 to the center of any chip 51 be the first target true value Xr. Let the coordinate of any chip 51 in the left-right direction y with respect to (referenced to) the target origin 52 be the second target coordinate Y. Let the distance in the left-right direction y from the target origin 52 to the center of any chip 51 be the second target true value Yr.

[0030] The user does not know the first target true value Xr and the second target true value Yr.

[0031] In FIG. 2, for simplicity, only the first target coordinate X and the second target coordinate Y for one chip 51 are illustrated, but actually, for all chips 51, there are the first target coordinate X and the second target coordinate Y.

[0032] (Captured image) FIG. 3 shows a captured image 70 obtained by imaging the chip 51 of the target substrate 50 with the camera 30. In FIG. 3, for simplicity, only one chip 51 is shown. As described above, the camera 30 does not move along with the stage 20. The target substrate 50 placed on the upper surface of the stage 20 and moving in the front-back direction x and the left-right direction y passes below the camera 30. The camera 30 images the chip 51 of the target substrate 50 placed on the stage 20 to obtain the captured image 70.

[0033] The field of view of the captured image 70 is, for example, rectangular. The captured image 70 is partitioned into a plurality of pixels 71. The plurality of pixels 71 are arranged in a matrix in the horizontal direction t and the vertical direction v. The plurality of pixels 71 are arranged at equal intervals in the horizontal direction t. The plurality of pixels 71 are arranged at equal intervals in the vertical direction v. If there are no error factors described later, the horizontal direction t in which the pixels 71 are arranged coincides with the front-back direction x, and the vertical direction v in which the pixels 71 are arranged coincides with the left-right direction y.

[0034] The captured image 70 has an image reference position 72. The image reference position 72 is, for example, at the center of the captured image 70.

[0035] Figure 3 shows a horizontal distance T and a vertical distance V. The horizontal distance T is the distance in the horizontal direction t in which the pixels 71 are arranged between the image reference position 72 in the captured image 70 and the chip 51 of the target substrate 50 imaged in the captured image 70. The vertical distance V is the distance in the vertical direction v in which the pixels 71 are arranged between the image reference position 72 in the captured image 70 and the chip 51 of the target substrate 50 imaged in the captured image 70.

[0036] (Target measured value) Figure 4 shows the measurement of the first target coordinate X and the second target coordinate Y related to the chip 51 provided on the target substrate 50. The target substrate 50 placed on the stage 20 moves in the front-rear direction x and the left-right direction y. The camera 30 does not move along with the stage 20. The camera 30 captures the chip 51 of the target substrate 50 placed on the stage 20 and moving in the front-rear direction x and the left-right direction y to obtain a captured image 70. The controller 40 measures the first target coordinate X and the second target coordinate Y related to the chip 51 of the target substrate 50 by the following method.

[0037] Data of the captured image 70 obtained by the camera 30 is input to the controller 40. The controller 40 calculates the horizontal distance T between the image reference position 72 and the chip 51 based on the captured image 70. The horizontal distance T is obtained based on the number of pixels 71 arranged in the horizontal direction t between the image reference position 72 and the chip 51 and the magnification in the horizontal direction t of the captured image 70.

[0038] The controller 40 acquires a first relative movement set value Lx in the front-rear direction x between the stage 20 and the camera 30. The first relative movement set value Lx is a set value of the relative movement amount in the front-rear direction x between the stage 20 and the camera 30. In this example, since the stage 20 is movable and the camera 30 is fixed, the first relative movement set value Lx is equal to the set value of the movement amount of the stage 20 in the front-rear direction x. For example, the first relative movement set value Lx is an input value that the user inputs to the controller 40 to move the stage 20 in the front-rear direction x.

[0039] Here, at the initial position (refer to the two-dot chain line in FIG. 4) where the target substrate 50 placed on the stage 20 is not moving, the target origin 52 of the target substrate 50 is aligned so as to overlap with the image reference position 72 of the captured image 70. If there are no error factors described later, the first relative movement set value Lx coincides with the actual movement amount of the target origin 52 in the front-rear direction x with respect to the image reference position 72.

[0040] As described above, the first target coordinate X is the coordinate of the chip 51 in the front-rear direction x with respect to (referenced to) the target origin 52. The controller 40 calculates a first target measurement value Xm of the first target coordinate X based on the horizontal distance T and the first relative movement set value Lx.

[0041] Specifically, the first target measurement value Xm is obtained by adding the horizontal distance T and the first relative movement set value Lx (Xm = T + Lx).

[0042] Data of the captured image 70 obtained by the camera 30 is input to the controller 40. The controller 40 calculates a vertical distance V between the image reference position 72 and the chip 51 based on the captured image 70. The vertical distance V is obtained based on the number of pixels 71 arranged in the vertical direction v between the image reference position 72 and the chip 51 and the magnification in the vertical direction v of the captured image 70.

[0043] The controller 40 acquires a second movement set value Ly in the left - right direction y between the stage 20 and the camera 30. The second movement set value Ly is a set value of the relative movement amount in the left - right direction y between the stage 20 and the camera 30. In this example, since the stage 20 is movable and the camera 30 is fixed, the second movement set value Ly is equal to the set value of the movement amount of the stage 20 in the left - right direction y. For example, the second movement set value Ly is an input value that the user inputs to the controller 40 to move the stage 20 in the left - right direction y.

[0044] As described above, at the initial position where the target substrate 50 placed on the stage 20 is not moving (refer to the two - dot chain line in FIG. 4), the target origin 52 of the target substrate 50 is aligned so as to overlap with the image reference position 72 of the captured image 70. If there are no error factors described later, the second movement set value Ly coincides with the actual movement amount in the left - right direction y of the target origin 52 with respect to the image reference position 72.

[0045] As described above, the second target coordinate Y is the coordinate in the left - right direction y of the chip 51 with respect to (referenced from) the target origin 52. The controller 40 calculates a second target measurement value Ym of the second target coordinate Y based on the vertical distance V and the second movement set value Ly.

[0046] Specifically, the second target measurement value Ym is obtained by adding the vertical distance V and the second movement set value Ly (Ym = V + Ly).

[0047] (Error factors) FIG. 5 shows an image of error factors. If there are no error factors, the first target measurement value Xm should coincide with the first target true value Xr which is the true value of the first target coordinate X, and the second target measurement value Ym should coincide with the second target true value Yr which is the true value of the second target coordinate Y.

[0048] However, in reality, due to various error factors, the first target measurement value Xm may deviate from the first target true value Xr (Xm ≠ Xr), and the second target measurement value Ym may deviate from the second target true value Yr (Ym ≠ Yr). Examples of error factors include, for example, the assembly error between the stage 20 and the camera 30, the imaging axis of the camera 30 not being orthogonal to the horizontal plane of the stage 20, the deviation of the position and angle of the stage 20, the deviation of the position and angle of the camera 30, the difference between the first movement setting values Lx and the second movement setting values Ly input by the user and the actual movement amount of the stage 20, the vibration of the stage 20, the vibration of the camera 30, the measurement error (distortion aberration) due to the distortion of the lens of the camera 30, the assembly error between the lens of the camera 30 and the image sensor of the camera 30, and so on.

[0049] Since the first target measurement value Xm and the second target measurement value Ym include errors, they will deviate from the first target true value Xr and the second target true value Yr. It is necessary to correct the first target measurement value Xm and the second target measurement value Ym by some method.

[0050] (Projection transformation matrix) The controller 40 corrects the first target measurement value Xm related to the first target coordinates X by the projection transformation matrix R to calculate the first target correction value Xc related to the first target coordinates X. The controller 40 corrects the second target measurement value Ym related to the second target coordinates Y to calculate the second target correction value Yc related to the second target coordinates Y. The projection transformation matrix R is also called a homography transformation matrix and is represented by Equation [Equation 1].

[0051]

Equation

[0052] The nine parameters a, b, c, d, e, f, g, h, s in the projection transformation matrix R must be set by the user. The parameters a~h, s are obtained by using the alignment substrate 60 described later. The projection transformation matrix R is stored, for example, in the memory of the controller 40.

[0053] (Alignment substrate) FIG. 6 shows an alignment substrate 60. The alignment substrate 60 corresponds to the target substrate 50. The alignment substrate 60 is a calibration substrate. The alignment substrate 60 is placed on the stage 20 in the same manner as the target substrate 50. The alignment substrate 60 has the same specifications as the target substrate 50. The shape and dimensions of the alignment substrate 60 are the same as those of the target substrate 50.

[0054] The alignment substrate 60 is provided with a plurality of alignment marks 61. The plurality of alignment marks 61 on the alignment substrate 60 correspond to the plurality of chips 51 on the target substrate 50. The shape and position of the plurality of alignment marks 61 on the alignment substrate 60 are the same as those of the plurality of chips 51 on the target substrate 50. The pitch and number of the alignment marks 61 are the same as those of the chips 51.

[0055] When the alignment substrate 60 is placed on the stage 20, the plurality of alignment marks 61 are arranged in a matrix in the front-back direction x and the left-right direction y on the alignment substrate 60. The plurality of alignment marks 61 are arranged at equal intervals in the front-back direction x. The plurality of alignment marks 61 are arranged at equal intervals in the left-right direction y. The alignment mark 61 is, for example, a mark simulating an integrated circuit.

[0056] The alignment substrate 60 is provided with an alignment origin 62. The alignment origin 62 on the alignment substrate 60 corresponds to the target origin 52 on the target substrate 50. The position of the alignment origin 62 on the alignment substrate 60 is the same as that of the target origin 52 on the target substrate 50. The alignment origin 62 is composed of, for example, a corner of the alignment substrate 60.

[0057] Let the coordinates of an arbitrary alignment mark 61 in the longitudinal direction x with respect to (referenced to) the alignment origin 62 be the first alignment coordinate X'. Let the distance in the longitudinal direction x from the alignment origin 62 to the center of an arbitrary alignment mark 61 be the first alignment measured value Xk'. Let the coordinates of an arbitrary alignment mark 61 in the lateral direction y with respect to (referenced to) the alignment origin 62 be the second alignment coordinate Y'. Let the distance in the lateral direction y from the alignment origin 62 to the center of an arbitrary alignment mark 61 be the second alignment measured value Yk'.

[0058] The first alignment coordinate X' corresponds to the first target coordinate X. The second alignment coordinate Y' corresponds to the second target coordinate Y. The first alignment measured value Xk' corresponds to the first target true value Xr. The second alignment measured value Yk' corresponds to the second target true value Yr.

[0059] The user knows in advance the first alignment measured value Xk' and the second alignment measured value Yk'. The first alignment measured value Xk' and the second alignment measured value Yk' have been measured in advance by, for example, a sensor or the like. The first alignment measured value Xk' is known. The second alignment measured value Yk' is known.

[0060] (Alignment measurement value) FIG. 7 shows a first alignment measurement value Xm' and a second alignment measurement value Ym' related to the alignment mark 61 of the alignment substrate 60.

[0061] The alignment origin 62 of the alignment substrate 60 is aligned so as to overlap with the image reference position 72 of the captured image 70. At this time, by abutting the alignment substrate 60 against a stopper or the like (not shown), the alignment origin 62 is positioned at the image reference position 72.

[0062] Data of the captured image 70 obtained by the camera 30 is input to the controller 40. Based on the captured image 70, the controller 40 calculates the horizontal distance T between the image reference position 72 and the alignment mark 61.

[0063] The horizontal distance T is the distance in the horizontal direction t in which the pixels 71 are arranged between the image reference position 72 in the captured image 70 and the alignment mark 61 of the alignment substrate 60 reflected in the captured image 70. The horizontal distance T is obtained based on the number of pixels 71 arranged in the horizontal direction t between the image reference position 72 and the alignment mark 61 and the magnification in the horizontal direction t of the captured image 70.

[0064] As described above, the alignment origin 62 of the alignment substrate 60 is aligned with the image reference position 72. Also, the first alignment coordinate X’ is the coordinate in the front-back direction x of the alignment mark 61 with respect to (referenced to) the alignment origin 62.

[0065] Based on the horizontal distance T in the state where the alignment origin 62 is aligned with the image reference position 72, the controller 40 calculates the first alignment measurement value Xm’ of the first alignment coordinate X’.

[0066] Due to error factors, the first alignment measurement value Xm’ may not match the first alignment actual measurement value Xk’ (Xm’≠Xk’).

[0067] Data of the captured image 70 obtained by the camera 30 is input to the controller 40. Based on the captured image 70, the controller 40 calculates the vertical distance V between the image reference position 72 and the alignment mark 61.

[0068] The vertical distance V is the distance in the vertical direction v in which the pixels 71 are arranged between the image reference position 72 in the captured image 70 and the alignment mark 61 of the alignment substrate 60 reflected in the captured image 70. The vertical distance V is obtained based on the number of pixels 71 arranged in the vertical direction v between the image reference position 72 and the alignment mark 61 and the magnification in the vertical direction v of the captured image 70.

[0069] As described above, the alignment origin 62 of the alignment substrate 60 is aligned with the image reference position 72. Further, the second alignment coordinate Y' is the coordinate in the left-right direction y of the alignment mark 61 with respect to (based on) the alignment origin 62.

[0070] The controller 40 calculates the second alignment measurement value Ym' of the second alignment coordinate Y' based on the vertical distance V in a state where the alignment origin 62 is aligned with the image reference position 72.

[0071] Due to error factors, the second alignment measurement value Ym' may not match the second alignment actual measurement value Yk' (Ym'≠Yk').

[0072] (Derivation of parameters of the projective transformation matrix) The parameters a to h, s of the projective transformation matrix R are derived by the following method.

[0073] The controller 40 acquires a known first alignment actual measurement value Xk' related to the first alignment coordinate X'. The first alignment actual measurement value Xk' is stored in the memory of the controller 40, for example. The controller 40 acquires a known second alignment actual measurement value Yk' related to the second alignment coordinate Y'. The second alignment actual measurement value Yk' is stored in the memory of the controller 40, for example.

[0074] As shown below, the controller 40 calculates the parameters a to h, s of the projective transformation matrix R based on the first alignment measurement value Xm', the first alignment actual measurement value Xk', the second alignment measurement value Ym', and the second alignment actual measurement value Yk'.

[0075] Specifically, using the alignment substrate 60, Equation [Equation 1] is replaced with Equation [Equation 2].

[0076]

Equation

[0077] On the right side of Equation [Equation 2], the first alignment correction value Xc' and the second alignment correction value Yc' are included. The first alignment correction value Xc' corresponds to the first target correction value Xc. The second alignment correction value Yc' corresponds to the second target correction value Yc. Since the first alignment correction value Xc' and the second alignment correction value Yc' include unknown parameters a to h, s, they have not yet been expressed as specific numerical values.

[0078] It is necessary to set the parameters a to h, s of the projective transformation matrix R so that the first alignment correction value Xc' (first target correction value Xc) approaches the first alignment measured value Xk' (first target true value Xr) and the second alignment correction value Yc' (second target correction value Yc) approaches the second alignment measured value Yk' (second target true value Yr).

[0079] The parameters a to h, s of the projective transformation matrix R are obtained, for example, by the least squares method. Specifically, a to h, s are obtained when the value N shown in Equation [Equation 3] is minimized.

[0080]

Equation

[0081] Since there are nine unknown parameters a to h, s in the projective transformation matrix R, nine equations can be set up and solved under nine conditions (for example, using nine alignment marks 61) so that the value N in Equation [Equation 3] is minimized.

[0082] (Function and Effect of the First Embodiment) In the inspection apparatus 1 according to the present embodiment, the target measured values Xm, Ym of the target coordinates X, Y of the chip 51 on the target substrate 50 obtained based on the captured image 70 may deviate from the target true values Xr, Yr, which are the true values, due to various error factors.

[0083] Therefore, in the inspection apparatus 1 according to the present embodiment, by using the projective transformation matrix R, the target measured values Xm and Ym are converted into target corrected values Xc and Yc to approach the target true values Xr and Yr, which are the true values.

[0084] In particular, in the inspection apparatus 1 according to the present embodiment, when obtaining the parameters a to h, s of the projective transformation matrix R, the alignment marks 61 of the alignment substrate 60 in a state where the alignment origin 62 is aligned with the image reference position 72 are used. Then, the parameters a to h, s of the projective transformation matrix R are calculated based on the alignment measured values Xm' and Ym' and the alignment actually measured values Xk' and Yk'. Thereby, a highly accurate projective transformation matrix R can be obtained.

[0085] As described above, it is possible to provide the inspection apparatus 1 capable of obtaining the accurate target coordinates X and Y of the chip 51 provided on the target substrate 50.

[0086] When deriving the parameters a to h, s of the projective transformation matrix R, by using the alignment actually measured values Xk' and Yk' as the correct values, a more accurate projective transformation matrix R can be obtained. Therefore, it is advantageous for bringing the target corrected values Xc and Yc closer to the target true values Xr and Yr, which are the true values.

[0087] According to the inspection apparatus 1 according to the present embodiment, even when the stage 20 and the camera 30 move relatively in the front-rear direction x and the left-right direction y, the accurate first target coordinates X and the second target coordinates Y of the chip 51 provided on the target substrate 50 can be obtained.

[0088] (Modification of the First Embodiment) The controller 40 may use the projective transformation matrix R to correct the deviation of the target measured values Xm and Ym caused by the distortion of the camera 30 to obtain the target corrected values Xc and Yc. Here, the distortion of the camera 30 may include not only physical distortion but also optical distortion. Examples of the optical distortion of the camera 30 include an error in the focus of the lens, a shading phenomenon, and a distortion aberration of the lens.

[0089] In this case, the values of the parameters a to h and s of the projection transformation matrix R used for distortion correction of the camera 30 may be different from the values of the parameters a to h and s of the projection transformation matrix R used for, for example, stage 20 misalignment correction. The projection transformation matrix R for camera 30 distortion correction and the projection transformation matrix R for stage 20 misalignment correction may be used separately, or one projection transformation matrix R having both functions may be used.

[0090] As an example, the distortion of the lens 31 of the camera 30 will be described. FIG. 8 shows the distortion of the lens 31 of the camera 30. In the camera 30 using the lens 31, distortion of the lens 31 occurs. The distortion occurs in the radial direction of the lens 31 and the tangential direction orthogonal to the radial direction. The radial distortion occurs on the projection plane Q because the exit angle does not match the incident angle when the light ray emitted from the subject P passes through the principal point of the lens 31 at a certain incident angle. The tangential distortion occurs due to the displacement of the center position and the inclination between the plurality of lenses constituting the lens 31. The distortion is represented by, for example, Expression [Equation 4] to Expression [Equation 6].

[0091]

Equation

[0092]

Equation

[0093]

Equation

[0094] Here, when an arbitrary point in the three-dimensional space is photographed to obtain image coordinates, the coordinates are set to (Xu, Yu) for the ideal lens 31 without distortion, and the coordinates are set to (Xd, Yd) for the actual lens 31 with distortion. r is the distance from the image center to the coordinates Xu and Yu. K1 to K5 are coefficients representing the distortion of the lens 31.

[0095] Among these, K3 and K4 represent tangential distortion aberration, but in practical applications, they are often negligible, so they may be simplified as in Equation [Equation 7] and Equation [Equation 8].

[0096]

Number

[0097]

Number

[0098] When using the actual lens 31 with distortion aberration, the coordinates Xd, Yd of the chip 51 correspond to the target measurement values Xm, Ym. The controller 40 may use the projection transformation matrix R as shown in Equation [Equation 9] to correct the deviation of the coordinates Xd, Yd (corresponding to the target measurement values Xm, Ym) of the chip 51 caused by the distortion of the lens 31 of the camera 30 to obtain the target correction values Xc, Yc.

[0099]

Number

[0100] For the nine parameters a~h, s, the same ones as those in the first embodiment may be used, or they may be separately obtained by the method described later.

[0101] For example, prepare a plurality of patterns of the known coordinates Xd, Yd of the chip 51 when using the actual lens 31 with distortion aberration and the known coordinates Xu, Yu of the chip 51 when using the ideal lens 31 without distortion aberration. The ideal coordinates Xu, Yu of the chip 51 are so to speak the correct values. The nine parameters a~h, s can be obtained by formulating a plurality of relational expressions shown in Equation [Equation 10] and solving them.

[0102]

Number

[0103] According to this modification example, even when there are errors caused by the distortion (especially the aberration) of the camera 30 (especially the lens 31), the projection transformation matrix R can convert the target measurement values Xm, Ym (for example, the coordinates Xd, Yd of the chip 51 when using the actual lens 31 with aberration) into the target correction values Xc, Yc, making them closer to the true values.

[0104] <Second Embodiment> The inspection apparatus 1 according to the second embodiment will be described. In the following description, the same components as those in the above embodiment are denoted by the same reference numerals, and detailed descriptions thereof are omitted.

[0105] In the inspection apparatus 1 according to the first embodiment, the controller 40 corrected the target measurement values Xm, Ym related to the target coordinates X, Y by the projection transformation matrix R to calculate the target correction values Xc, Yc related to the target coordinates X, Y.

[0106] In the inspection apparatus 1 according to the second embodiment, different from the case of the first embodiment, the controller 40 uses a machine learning model M instead of the projection transformation matrix R. FIG. 9 shows the configuration of the machine learning model M.

[0107] The machine learning model M is stored in the controller 40 (for example, a personal computer or the like).

[0108] The controller 40 executes the machine learning model M as follows. The controller 40 corrects the target measurement values Xm, Ym related to the target coordinates X, Y by the machine learning model M to calculate the target correction values Xc, Yc related to the target coordinates X, Y. When the machine learning model M is executed, the target measurement values Xm, Ym are input to the machine learning model M, and the machine learning model M calculates and outputs the target correction values Xc, Yc.

[0109] The machine learning model M is a supervised learning model. Specific machine learning models M include, for example, Ridge Regression, GDBT (Gradient Boosting Decision Tree), Multilayer Perceptron (MLP), etc.

[0110] The machine learning model M learns as follows. The machine learning model M uses the known target measurement values Xm, Ym related to the target coordinates X, Y and the known target actual measurement values Xk, Yk which are the known actual measurement values related to the target coordinates X, Y as the training data.

[0111] The known target measurement values Xm, Ym are obtained by collecting the data of the target measurement values Xm, Ym measured by the method described in the first embodiment. It is preferable to collect a large number of data of the known target measurement values Xm, Ym. The known target measurement values Xm, Ym deviate from the target true values Xr, Yr which are the true values of the target coordinates X, Y due to various error factors.

[0112] The known target actual measurement values Xk, Yk coincide with the target true values Xr, Yr which are the true values of the target coordinates X, Y. The known target actual measurement values Xk, Yk are so-called correct values. It is preferable to collect a large number of data of the known target actual measurement values Xk, Yk. The known target actual measurement values Xk, Yk are obtained, for example, by directly measuring with a sensor or the like.

[0113] During the learning of the machine learning model M, the known target measurement values Xm, Ym are given to the input layer of the machine learning model M as training data, and the known target actual measurement values Xk, Yk are given to the output layer of the machine learning model M as training data.

[0114] (Operation and Effect of the Second Embodiment) In the inspection apparatus 1 according to the present embodiment, the target measurement values Xm, Ym of the target coordinates X, Y of the chip 51 on the target substrate 50 obtained based on the captured image 70 may deviate from the target true values Xr, Yr which are the true values due to various error factors.

[0115] Therefore, in the inspection apparatus 1 according to the present embodiment, by using the machine learning model M, the target measured values Xm and Ym are converted into target correction values Xc and Yc, and are brought closer to the target true values Xr and Yr which are the true values.

[0116] In particular, in the inspection apparatus 1 according to the present embodiment, in the machine learning model M, the known target measured values Xm and Ym and the known target actually measured values Xk and Yk are used as teacher data. Thereby, a highly accurate machine learning model M can be obtained.

[0117] By obtaining the correlation between the target measured values Xm and Ym and the target actually measured values Xk and Yk by the machine learning model M, target correction values Xc and Yc close to the true values can be obtained.

[0118] As described above, it is possible to provide the inspection apparatus 1 capable of obtaining the accurate target coordinates X and Y of the chip 51 provided on the target substrate 50.

[0119] Based on the distances T and V in the directions t and v in which the pixels 71 of the image reference position 72 and the chip 51 are arranged, and the movement setting values Lx and Ly, the unknown target measured values Xmi and Ymi related to the target coordinates X and Y of the chip 51 with respect to the target origin 52 provided on the target substrate 50 can be easily calculated.

[0120] (Modification of the Second Embodiment) As described in the first embodiment, the alignment measurement values Xm' and Ym' related to the alignment coordinates X' and Y' correspond to the target measurement values Xm and Ym related to the target coordinates X and Y. Therefore, the machine learning model M may apply the known alignment measurement values Xm' and Ym' related to the alignment coordinates X' and Y' as the known target measurement values Xm and Ym related to the target coordinates X and Y to the teacher data.

[0121] As described in the first embodiment, the measured alignment values Xk', Yk' related to the alignment coordinates X', Y' match the true target values Xr, Yr related to the target coordinates X, Y. That is, the measured alignment values Xk', Yk' related to the alignment coordinates X', Y' match the known measured target values Xk, Yk related to the target coordinates X, Y. Therefore, the machine learning model M may apply the known measured alignment values Xk', Yk' related to the alignment coordinates X', Y' as teacher data as the known measured target values Xk, Yk related to the target coordinates X, Y.

[0122] According to this modification example, data necessary for learning the machine learning model M can be easily obtained.

[0123] <Other Embodiments> As described above, the present disclosure has been described by way of preferred embodiments. However, such descriptions are not limiting matters, and of course, various modifications, substitutions, or combinations are possible.

[0124] The controller 40 may be provided outside the inspection apparatus 1 main body instead of being built into the inspection apparatus 1 main body.

[0125] The stage 20 may be fixed and the camera 30 may be movable instead of the stage 20 being movable and the camera 30 being fixed. Alternatively, both may be movable.

[0126] The target substrate 50 and the alignment substrate 60 are not limited to a rectangular shape, and may be, for example, a circular shape. The target substrate 50 and the alignment substrate 60 do not have to be semiconductors. The target origin 52 and the alignment origin 62 may be provided not at the corners of the target substrate 50 and the alignment substrate 60, but at, for example, the center.

[0127] Regarding the first embodiment, the parameters of the projective transformation matrix R may be obtained by, for example, the Levenberg-Marquardt method or the least median method instead of the least squares method.

[0128] In the first embodiment, the projection transformation matrix R may be stored not in the memory of the controller 40 but in an external server. In this case, the controller 40 accesses the projection transformation matrix R in the external server to input data to the projection transformation matrix R or receive data output from the projection transformation matrix R.

[0129] In the second embodiment, the machine learning model M may be stored not in the memory of the controller 40 but in an external server. In this case, the controller 40 accesses the machine learning model M in the external server to input data to the machine learning model M or receive data output from the machine learning model M.

Industrial Applicability

[0130] Since the present disclosure can be applied to inspection apparatuses, it is extremely useful and has high industrial applicability.

Explanation of Signs

[0131] x Front-rear direction (first direction) y Left-right direction (second direction) z Up-down direction X First target coordinate Y Second target coordinate Xr First target true value Yr Second target true value Xc First target correction value Yc Second target correction value Xm First target measurement value Ym Second target measurement value Xk, Yk Target measured value X’ First alignment coordinate Y’ Second alignment coordinate Xk’ First alignment measured value Yk’ Second alignment measured value Xm’ First alignment measurement value Ym’ Second alignment measurement value Xc’ First alignment correction value Yc’ Second alignment correction value Lx First movement setting value Ly Second movement setting value M Machine learning model t Horizontal direction v Vertical direction T Horizontal distance V Vertical distance R Projection transformation matrix a~h, s Parameters 1 Inspection device 10 Rail 11 First rail 12 Second rail 20 Stage 30 Camera 31 Lens 40 Controller 50 Target substrate 51 Chip 52 Target origin 60 Alignment substrate 61 Alignment mark 62 Alignment origin 70 Captured image 71 Pixel 72 Image reference position

Claims

1. A stage on which a target substrate provided with a plurality of chips arranged side by side is placed; A camera that images the target substrate placed on the stage to obtain an imaged image partitioned into a plurality of pixels; Based on the distance in the direction in which the pixels are arranged between the image reference position in the imaged image and the chip reflected in the imaged image, and the relative movement setting value between the stage and the camera, a target measurement value of the target coordinates of the chip with respect to a target origin provided on the target substrate is calculated, and a controller; The controller corrects the target measurement value related to the target coordinates by a projective transformation matrix to calculate a target correction value related to the target coordinates; On the alignment substrate corresponding to the target substrate, a plurality of alignment marks corresponding to the plurality of chips are provided; On the alignment substrate, an alignment origin corresponding to the target origin is provided; The controller calculates an alignment measurement value of the alignment coordinates of the alignment mark with respect to the alignment origin based on the distance in the direction in which the pixels are arranged between the image reference position and the alignment mark reflected in the imaged image with the alignment origin aligned with the image reference position; The controller acquires a known alignment measured value of the alignment coordinates; The controller calculates parameters of the projective transformation matrix based on the alignment measurement value and the alignment measured value, an inspection device.

2. On the target substrate, a plurality of the chips are arranged side by side in a first direction and a second direction intersecting the first direction; The controller calculates a first target measurement value of the first target coordinates of the chip in the first direction with respect to the target origin based on the horizontal distance in the horizontal direction in which the pixels are arranged between the image reference position and the chip reflected in the imaged image, and the relative first movement setting value in the first direction between the stage and the camera; The controller calculates a second target measurement value of the second target coordinates of the chip in the second direction with respect to the target origin based on a vertical distance in a vertical direction in which pixels of the image reference position and the chip reflected in the captured image are arranged, and a second movement setting value that is relative in the second direction between the stage and the camera. The controller calculates a first target correction value related to the first target coordinates by correcting the first target measurement value related to the first target coordinates with the projective transformation matrix, and calculates a second target correction value related to the second target coordinates by correcting the second target measurement value related to the second target coordinates. The controller calculates a first alignment measurement value of the first alignment coordinates of the alignment mark in the first direction with respect to the alignment origin based on a horizontal distance in a horizontal direction in which pixels of the image reference position and the alignment mark reflected in the captured image are arranged in a state where the alignment origin is aligned with the image reference position. The controller calculates a second alignment measurement value of the second alignment coordinates of the alignment mark in the second direction with respect to the alignment origin based on a vertical distance in a vertical direction in which pixels of the image reference position and the alignment mark reflected in the captured image are arranged in a state where the alignment origin is aligned with the image reference position. The controller obtains a known first alignment actual measurement value related to the first alignment coordinates and a known second alignment actual measurement value related to the second alignment coordinates. The controller calculates the parameter of the projective transformation matrix based on the first alignment measurement value, the first alignment actual measurement value, the second alignment measurement value, and the second alignment actual measurement value. The inspection apparatus according to claim 1.

3. The controller uses the projective transformation matrix to correct a deviation of the target measurement value caused by distortion of the camera to obtain the target correction value. The inspection apparatus according to claim 1 or 2.

Images