Inspection apparatus

Abstract

To provide an inspection apparatus which can classify a type of solder on the basis of a difference in the shape (texture) of a solidification structure appearing on a solder surface of an inspection object.SOLUTION: An inspection apparatus 10 comprises: an imaging unit 20 which images an inspection object 12; and a control unit 30. The control unit 30 acquires image data by imaging a solder portion on an inspection object 12 by the imaging unit 20, extracts a feature amount of the shape of a solidification structure appearing on a surface of the solder portion from the image data, and classifies the type of solder used for the solder portion on the basis of the feature amount.SELECTED DRAWING: Figure 1

Description

Technical Field

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

Background Art

[0002] In an inspection apparatus for inspecting the appearance of a substrate on which an electronic component or the like as an inspection object is mounted, the soldering state of the substrate is inspected (see, for example, Patent Document 1). In recent years, a large number of solders with a low lead content have been developed. Therefore, solders with different performances have been developed due to differences in composition (see, for example, Patent Document 2).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] As described above, in recent years, a large number of solders with a low lead content have been developed. However, from the viewpoint of quality assurance and the like, the type of solder used for each substrate is determined. However, there are cases where a type of solder different from the determined solder is used due to a mistake or the like. In such a case, the current inspection apparatus has a problem that it cannot classify the type of solder used on the substrate.

[0005] The present invention has been made in view of such problems, and an object thereof is to provide an inspection apparatus capable of classifying the type of solder based on the difference in the shape (texture) of the solidification structure appearing on the solder surface of the inspection object.

Means for Solving the Problems

[0006] To solve the aforementioned problems, the inspection apparatus according to the present invention comprises an imaging unit for imaging an object to be inspected and a control unit, wherein the control unit uses the imaging unit to image the solder portion on the object to be inspected and acquires image data, extracts characteristic quantities of the shape of the solidified tissue appearing on the surface of the solder portion from the image data, and classifies the type of solder used in the solder portion based on the characteristic quantities. [Effects of the Invention]

[0007] According to the inspection apparatus of the present invention, the type of solder can be classified based on the difference in the shape (texture) of the solidified structure that appears on the solder surface of the object being inspected. [Brief explanation of the drawing]

[0008] [Figure 1] This is an explanatory diagram illustrating the configuration of the inspection device. [Figure 2] This is an explanatory diagram for illustrating the projection angle of a lighting unit and the detection of its reflected light, where (a) shows the projection angle of each lighting source of the lighting unit, and (b) shows an example of the condition of the inspection surface of the object being inspected. [Figure 3] This is an explanatory diagram illustrating the correspondence between hue in the HSV color system and the projection angle of the lighting source of the lighting unit. [Figure 4] This is a flowchart showing the image synthesis process. [Figure 5] This is a flowchart showing the solder type classification process. [Figure 6] This is an explanatory diagram showing an example of a feature map. [Figure 7] This is a flowchart showing the flow of the first testing method. [Figure 8] According to the second inspection method flow chart, [Figure 9] This is a flowchart showing the flow of the third testing method. [Figure 10] This is a flowchart showing the flow of the fourth testing method. [Figure 11] This is a flowchart showing the flow of the fifth testing method. [Modes for carrying out the invention]

[0009] Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings. First, the configuration of the inspection apparatus 10 according to this embodiment will be described using Figure 1. This inspection apparatus 10 is an apparatus that inspects an object to be inspected 12 using image data of an object to be inspected obtained by imaging the object to be inspected 12. The object to be inspected 12 is, for example, an electronic circuit board on which a large number of electronic components are mounted. The inspection apparatus 10 determines whether the mounting state of the electronic components is good or bad based on the image data of the object to be inspected. This inspection is usually performed on multiple inspection items for each component. Inspection items are items that require determination of good or bad. Inspection items include, for example, inspection items for component placement such as missing parts, misalignment, and polarity reversal of the component itself, and inspection items for connections between components and the board such as soldering condition and lifting of component lead pins.

[0010] The inspection device 10 comprises an inspection table 14 for holding the object to be inspected 12, an imaging unit 20 for illuminating and imaging the object to be inspected 12, an XY stage 16 for moving the imaging unit 20 relative to the inspection table 14, and a control unit 30 for controlling the imaging unit 20 and the XY stage 16. For the sake of explanation, as shown in Figure 1, the surface on which the object to be inspected is placed on the inspection table 14 is defined as the XY plane, and the direction perpendicular to that surface (i.e., the imaging direction by the imaging unit 20 (the optical axis direction of the optical system of the camera unit 21)) is defined as the Z direction.

[0011] The imaging unit 20 is mounted on a movable table (not shown) of the XY stage 16 and is movable in both the X and Y directions by the XY stage 16. The XY stage 16 is, for example, a so-called H-shaped XY stage. Therefore, the XY stage 16 includes a Y linear motor that moves the movable table in the Y direction along a Y-direction guide extending in the Y direction, and two X-direction guides and an X linear motor that support the Y-direction guide at both ends and are configured to allow the movable table and Y-direction guide to move in the X direction. The XY stage 16 may further include a Z-movement mechanism for moving the imaging unit 20 in the Z direction, or a rotation mechanism for rotating the imaging unit 20. The inspection device 10 may further include an XY stage that allows the inspection table 14 to move, in which case the XY stage 16 that moves the imaging unit 20 may be omitted.

[0012] The imaging unit 20 comprises a camera unit 21, a half mirror 22, an illumination unit 23, and a projection unit 24. In the inspection apparatus 10 according to this embodiment, the camera unit 21, the half mirror 22, the illumination unit 23, and the projection unit 24 may be configured as a single imaging unit 20. In this single imaging unit 20, the relative positions of the camera unit 21, the half mirror 22, the illumination unit 23, and the projection unit 24 may be fixed, or each unit may be configured to be relatively movable. Alternatively, the camera unit 21, the half mirror 22, the illumination unit 23, and the projection unit 24 may be separate components and configured to be independently movable. In the following description, the case in which the object to be inspected 12 is illuminated using the half mirror 22 will be described, but the half mirror 22 may be omitted.

[0013] The camera unit 21 includes an imaging device that generates two-dimensional image data of an object, and an optical system (e.g., a lens) for forming an image on the imaging device. The camera unit 21 is, for example, a CCD camera. The maximum visual field of the camera unit 21 may be smaller than the inspection object placement area of the inspection table 14. In this case, the camera unit 21 images the entire inspection object 12 by dividing it into a plurality of partial images. The control unit 30 controls the XY stage 16 so that the camera unit 21 is moved to the next imaging position each time the camera unit 21 images a partial image and outputs partial image data. The control unit 30 synthesizes the partial image data to generate the entire image data of the inspection object 12.

[0014] Note that the camera unit 21 may be provided with an imaging device that generates a one-dimensional image instead of the two-dimensional imaging device. In this case, by scanning the inspection object 12 with the camera unit 21, the entire image of the inspection object 12 can be obtained.

[0015] The illumination unit 23 is configured to project illumination light for imaging by the camera unit 21 onto the surface of the inspection object 12. The illumination unit 23 includes one or more light sources that emit light having a wavelength or wavelength range selected from the wavelength range detectable by the imaging device of the camera unit 21. The illumination light is not limited to visible light, and ultraviolet light, X-rays, or the like may be used. When a plurality of light sources are provided, each light source is configured to project light of different wavelengths (e.g., red, blue, and green) onto the surface of the inspection object 12 at different light projection angles.

[0016] In the inspection apparatus 10 according to the present embodiment, the illumination unit 23 includes an epi-illumination source 23a that projects illumination light perpendicularly to the inspection surface of the inspection object 12 (that is, the surface (X-Y plane) facing the imaging unit 20), and a side illumination source (in this embodiment, consisting of an upper light source 23b, a middle light source 23c, and a lower light source 23d) that projects illumination light from an oblique direction with respect to the inspection surface of the inspection object 12. A half mirror 22 is disposed on the optical axis of the optical system of the camera unit 21, and a part of the illumination light emitted from the epi-illumination source 23a is reflected by this half mirror 22 and is configured to be projected onto the inspection object 12 through the optical axis. Here, a half prism may be used instead of the half mirror 22. In the inspection apparatus 10 according to the present embodiment, the side illumination sources 23b, 23c, and 23d are each ring illumination sources, and are configured to surround the optical axis of the camera unit 21 and project illumination light obliquely to the inspection surface of the inspection object 12. Each of these side illumination sources 23b, 23c, and 23d may be configured by arranging a plurality of light sources in an annular shape. The upper light source 23b, the middle light source 23c, and the lower light source 23d, which are side illumination sources, are each configured to project illumination light at different angles with respect to the inspection surface.

[0017] Also, each of the upper light source 23b, the middle light source 23c, and the lower light source 23d, which are side illumination sources, may be configured by one ring illumination source or may include a plurality of ring illumination sources. For example, the epi-illumination source 23a is attached to the side of the camera unit 21. Among the side illumination sources, the upper light source 23b may be configured as one ring illumination unit, and the middle light source 23c and the lower light source 23d may be configured as one ring illumination unit integrated together. In the present embodiment, the epi-illumination source 23a is a red illumination source. Among the side illumination sources, the upper light source 23b and the lower light source 23d are red illumination sources. Among the side illumination sources, the middle light source 23c is composed of a green illumination source, a blue illumination source, and a red illumination source.

[0018] As described above, this embodiment describes a case in which four types of light sources are used to illuminate the object under inspection 12 from different angles. However, the types (number) of light sources are not limited to four. It may be just the incident illumination source 23a, or a combination of the incident illumination source 23a and any of the side illumination sources 23b to 23d, or just the side illumination sources 23b to 23d or some of these. Furthermore, it may be just one of the light sources 23a to 23d, in which case it may be configured to acquire a monochrome image using a monochromatic light source.

[0019] In Figure 1, for reference, the light beam projected from the incident illumination source 23a, reflected from the inspection surface of the object under inspection 12, and projected onto the camera unit 21 is indicated by a dashed arrow. Here, the light reflected from the inspection surface of the object under inspection 12 enters the half mirror 22, and some of the light is transmitted and enters the camera unit 21. Similarly, projections from the side illumination sources 23b, 23c, 23d and the projection unit 24 are also indicated by dashed arrows. As an example, the light beam projected from the upper light source 23b, reflected from the inspection surface of the object under inspection 12, and entered onto the camera unit 21 is also shown. Here, for the sake of explanation, the surface of the object under inspection 12 is shown as a flat surface, but in reality, like a typical object under inspection, it has slopes and heights depending on the part.

[0020] The projection unit 24 projects a pattern onto the inspection surface of the object to be inspected 12. The object to be inspected 12, onto which the pattern is projected, is imaged by the camera unit 21. In the illustrated embodiment, the projection unit 24 is provided between the upper light source 23b and the middle light source 23c, but the arrangement of the projection unit 24 is not limited to this, and for example, the projection unit 24 may be provided outside the lower light source 23d.

[0021] The inspection device 10 creates a height map of the inspection surface of the object under inspection 12 based on the pattern image data of the object under inspection 12 captured while the pattern is projected from the projection unit 24. The control unit 30 detects local discrepancies in the pattern image relative to the projected pattern and determines the height of that area based on the local discrepancies. In other words, changes in the imaged pattern (the pattern projected onto the object under inspection 12 and captured by the camera unit 21) relative to the projected pattern (the pattern projected onto the object under inspection 12 from the projection unit 24) correspond to changes in height on the inspection surface.

[0022] Here, the projection pattern is preferably a one-dimensional stripe pattern in which bright and dark lines alternate periodically. The projection unit 24 is positioned to project the stripe pattern onto the inspection surface of the object to be inspected 12 from an oblique direction. Discontinuities in height on the inspection surface of the object to be inspected 12 are represented as pattern displacements in the stripe pattern image. Therefore, the height difference can be determined from the amount of pattern displacement. In the inspection apparatus 10 according to this embodiment, the control unit 30 creates a height map using the PMP (Phase Measurement Profilometry) method, which uses a stripe pattern whose brightness changes according to a sine curve. In the PMP method, the amount of displacement of the stripe pattern corresponds to the phase difference of the sine curve.

[0023] The projection unit 24 comprises a pattern forming apparatus, a light source for illuminating the pattern forming apparatus, and an optical system for projecting the pattern onto the inspection surface of the object to be inspected 12. The pattern forming apparatus may be a variable patterning apparatus capable of dynamically generating a desired pattern, such as a liquid crystal display, or a fixed patterning apparatus in which a pattern is fixedly formed on a substrate such as a glass plate. If the pattern forming apparatus is a fixed patterning apparatus, it is preferable to make the projection position of the pattern variable by providing a moving mechanism for moving the fixed patterning apparatus or by providing an adjustment mechanism in the optical system for pattern projection. Furthermore, the projection unit 24 may be configured to allow switching between multiple fixed patterning apparatuses having different patterns.

[0024] Multiple projection units 24 may be provided around the camera unit 21. The multiple projection units 24 are arranged to project patterns onto the object under inspection 12 from different projection directions. In this way, the area where shadows are cast and patterns are not projected due to height differences on the inspection surface can be reduced.

[0025] The control unit 30 shown in Figure 1 comprehensively controls the entire device. It is implemented as hardware using the CPU, memory, and other LSIs of any computer, and as software using programs loaded into memory. Here, however, the functional blocks realized through the coordination of these components are depicted. Therefore, it will be understood by those skilled in the art that these functional blocks can be realized in various ways using hardware alone, software alone, or a combination thereof.

[0026] Figure 1 shows an example of the configuration of the control unit 30. The control unit 30 comprises an inspection control unit 31 and a memory unit 35. The inspection control unit 31 comprises a height measuring unit 32, an inspection data processing unit 33, and an inspection unit 34. The inspection device 10 also includes an input unit 36 ​​for receiving input from a user or other device, and an output unit 37 for outputting information related to the inspection. The input unit 36 ​​and the output unit 37 are each connected to the control unit 30. The input unit 36 ​​includes, for example, input means such as a mouse or keyboard for receiving input from a user, and communication means for communicating with other devices. The output unit 37 includes known output means such as a display or printer.

[0027] The inspection control unit 31 is configured to perform various control processes for inspection based on input from the input unit 36 ​​and inspection-related information stored in the memory 35. The inspection-related information includes two-dimensional image data of the object to be inspected 12, a height map of the object to be inspected 12, and substrate inspection data (inspection data). Prior to inspection, the inspection data processing unit 33 creates substrate inspection data using the two-dimensional image data and height map of the object to be inspected 12, which are guaranteed to pass all inspection items. The inspection unit 34 performs the inspection based on the created substrate inspection data and the two-dimensional image data and height map of the object to be inspected 12.

[0028] PCB inspection data is inspection data created for each type of PCB. PCB inspection data is, in essence, a collection of inspection data for each component mounted on that PCB. The inspection data for each component includes the necessary inspection items for that component, the inspection window (the image inspection area) for each inspection item, and the inspection criteria that determine whether each inspection item is good or bad. One or more inspection windows are set for each inspection item. For example, in an inspection item that determines the quality of soldering on a component, typically the same number of inspection windows as the number of soldering areas on that component are set in an arrangement corresponding to the arrangement of the soldering areas. Furthermore, for inspection items that use image data that has undergone predetermined image processing, the details of that image processing are also included in the inspection data.

[0029] The inspection data processing unit 33 sets each item of the inspection data according to the board as part of the board inspection data creation process. For example, the inspection data processing unit 33 automatically sets the position and size of each inspection window for each inspection item to match the component layout of the board. The inspection data processing unit 33 may also accept user input for some items of the inspection data. For example, the inspection data processing unit 33 may accept tuning of inspection criteria by the user. The inspection criteria may be set using height information.

[0030] The inspection control unit 31 performs imaging of the object to be inspected 12 as a preprocessing step for creating substrate inspection data. The object to be inspected 12 used is one that has passed all inspection items. As described above, the imaging process is performed by illuminating the object to be inspected 12 with the illumination unit 23, controlling the relative movement of the imaging unit 20 and the inspection table 14, and sequentially capturing partial images of the object to be inspected 12 to acquire partial image data. Multiple partial image data are captured so that the entire object to be inspected 12 is covered. The inspection control unit 31 combines these multiple partial image data to generate full-surface substrate image data that includes the entire inspection surface of the object to be inspected 12. The inspection control unit 31 stores the full-surface substrate image data in the memory 35.

[0031] Furthermore, as a preprocessing step for creating a height map, the inspection control unit 31 projects a pattern onto the object under inspection 12 using the projection unit 24 while controlling the relative movement between the imaging unit 20 and the inspection table 14. The pattern image of the object under inspection 12 is divided and sequentially captured to obtain divided image data when the pattern is projected. Preferably, the projected pattern is a striped pattern whose brightness changes according to a sine curve based on the PMP method. The inspection control unit 31 synthesizes the divided image data obtained by imaging to generate pattern image data, which is image data of the entire inspection surface of the object under inspection 12. The inspection control unit 31 stores the pattern image data in the memory 35. Alternatively, pattern image data may be generated for only a part of the inspection surface instead of the entire surface.

[0032] The height measurement unit 32 creates a height map of the entire inspection surface of the object under inspection 12 based on the imaging pattern of the pattern image data. First, the height measurement unit 32 obtains a phase difference map of the inspection surface of the object under inspection 12 by determining the local phase difference between the pattern image data and the reference pattern image data for the entire image. The reference pattern image data is a pattern image projected by the projection unit 24 (i.e., image data generated by the pattern forming device built into the projection unit 24). The height measurement unit 32 creates a height map of the object under inspection 12 based on the reference surface that serves as the reference for height measurement and the phase difference map. The reference surface is, for example, the substrate surface of the electronic circuit board to be inspected. The reference surface does not necessarily have to be a plane, and may be a curved surface that reflects deformation such as warping of the substrate. The reference surface may be specified in advance by user input, or it may be determined for each individual substrate by, for example, the substrate surface height measurement method described later.

[0033] Specifically, the height measuring unit 32 determines the phase difference of the stripe pattern between each pixel of the imaging pattern image data and the corresponding pixel of the reference pattern image data. The height measuring unit 32 converts the phase difference into height. The conversion to height is performed using the local stripe width near the pixel in question. This is to interpolate the fact that the stripe width on the imaging pattern image data varies depending on the location. This is because, even if the stripe width of the reference pattern is constant, the stripe width changes linearly from one end to the other of the pattern projection area on the inspection surface because the distance from the projection unit 24 differs depending on the position on the inspection surface. Based on the converted height and the reference surface, the height measuring unit 32 determines the height from the reference surface and creates a height map of the object under inspection 12.

[0034] The inspection control unit 31 may create an object under inspection image data having a height distribution by associating the height information contained in the height map of the object under inspection 12 with each pixel of the two-dimensional image of the object under inspection 12. Alternatively, the inspection control unit 31 may perform a three-dimensional modeling display of the object under inspection 12 based on the object under inspection image data with a height distribution. Alternatively, the inspection control unit 31 may superimpose the height distribution onto the two-dimensional object under inspection image data and display it on the output unit 37. For example, the object under inspection image data may be color-coded according to the height distribution. Note that in the inspection apparatus 10 according to this embodiment, the projection unit 24 and the height measurement processing of the object under inspection 12 by the projection unit 24 do not need to be implemented.

[0035] Next, we will explain how to process the image data captured using the illumination unit 23. As described above, in the inspection apparatus 10 according to this embodiment, the light sources constituting the illumination unit 23 (incident illumination source 23a, and the upper light source 23b, middle light source 23c, and lower light source 23d, which are lateral illumination sources) are arranged to have different projection angles with respect to the reference surface of the object under inspection 12 (the inspection surface of the object under inspection 12, which is substantially parallel to the installation surface of the inspection apparatus 10), as shown in Figure 2(a). Specifically, the illumination light from the incident illumination source 23a is projected along the optical axis L of the optical system of the camera unit 21, that is, substantially perpendicular to the reference surface, and the projection angles are projected in the order of upper light source 23b, middle light source 23c, and lower light source 23d, so that they approach the horizontal direction.

[0036] Ideally, the intensity of the light projected from each of the light sources 23a to 23d of the lighting unit 23, and reflected from the object under inspection 12, is zero, except for the light that is reflected from the object under inspection 12 and directly incident on the camera unit 21. In other words, the intensity of the reflected light from the light source that directly incidents on the camera unit 21 after being reflected from the inspection surface of the inspection surface of the object under inspection 12 is greater than the angle (tilt state) of the inspection surface of the object under inspection 12 with respect to the reference plane, while the intensity of the reflected light from the other light sources is zero. For example, if solder with the cross-section shown in Figure 2(b) is formed on the inspection surface of the object under inspection 12, the intensity of the reflected light from the illumination light from each of the light sources 23a to 23d of the lighting unit 23, as detected by the image sensor of the camera unit 21, changes according to the angle of the surface of the solder with respect to the reference plane. In this embodiment, the inclined surfaces at angles of 0° to 15° relative to the reference plane have a high intensity of reflected light from the incident illumination source 23a, the inclined surfaces at angles of 15° to 45° have a high intensity of reflected light from the upper light source 23b, the inclined surfaces at angles of 45° to 65° have a high intensity of reflected light from the middle light source 23c, and the inclined surfaces at angles of 65° to 85° have a high intensity of reflected light from the lower light source 23d. Note that the relationship between each light source 23a to 23d of the illumination unit 23 and the angles of the inclined surfaces of the object under inspection 12 is just an example and is not limited to this configuration.

[0037] Based on the above, the intensity of each pixel in the image data obtained by lighting each of the light sources 23a to 23d of the lighting unit 23 and capturing it with the camera unit 21 is large when it matches the angle of the inclined surface described above, and close to 0 when it does not match.

[0038] Therefore, in the inspection apparatus 10 according to this embodiment, illumination light is projected from each of the light sources 23a to 23d of the illumination unit 23 and captured by the camera unit 21 to generate images of the R (red), G (green), and B (blue) components. Furthermore, these three images are combined to generate an RGB image (color image) to represent the inclination state of the inspection surface of the object to be inspected 12.

[0039] As shown in Figure 3, when a color is represented by hue H, saturation S, and lightness V (represented in the HSV color system), hue H is represented by the angle of a circle, and saturation S and lightness V are represented by the magnitudes in mutually orthogonal directions. In this hue H, R (red), G (green), and B (blue) are each located 120° apart. Therefore, by assigning image data obtained from reflected light projected from the upper light source 23b, that is, image data detecting reflected light from inclined surfaces of 15° to 45° (referred to as "Top" in Figure 3) in this embodiment, to R (red), assigning image data obtained from reflected light projected from the middle light source 23c, that is, image data detecting reflected light from inclined surfaces of 45° to 65° (referred to as "Side" in Figure 3) to G (green), and assigning image data obtained from reflected light projected from the lower light source 23d, that is, image data detecting reflected light from inspection surfaces of 65° to 85° (referred to as "Low" in Figure 3) to B (blue), it is possible to obtain RGB image data (color image data) by synthesizing these image data, and from this, image data expressed in RGB according to the inclination state can be obtained, so that the inclination state of the inspection surface of the object to be inspected 12 can be grasped from the color of this image data. Furthermore, as described above, by correlating the projection angles of the lateral illumination sources 23b to 23d of the lighting unit 23 with the hue H, image data (referred to as "Coaxis" in Figure 3) detecting reflected light from inclined surfaces with angles smaller than 15° to 45°, which are represented by R (red), can be displayed in a color intermediate between R (red) and B (blue) (purple). Therefore, even when using four or more light sources with different projection angles as the lighting unit 23, the inclination state of the inspection surface of the object under inspection 12 can be clearly represented by the RGB image data (color image data). In other words, the solder condition shown in Figure 2(b) can be determined from the RGB image (color image).

[0040] Furthermore, the color of the illumination light emitted from each of the light sources 23a to 23d of the lighting unit 23 does not need to match the color (RGB) assigned to the image data obtained by capturing the reflected light from each of these light sources 23a to 23d (since hue H represents the inclination (angle) of the inspection surface of the object under inspection 12). Therefore, the image sensor of the camera unit 21 does not need to be color (it is sufficient if it can detect light intensity). In the generation of RGB image data (color image data), differences in intensity are expressed by saturation S or brightness V.

[0041] The light sources 23a to 23d may be lit sequentially to capture an image of the object under inspection 12 with the camera unit 21, or the camera unit 21 may be configured with a camera capable of acquiring color image data, and the light sources 23a to 23d may be lit simultaneously to capture an image of the object under inspection 12 in a single image. In this case, image data of the R (red) component, image data of the G (green) component, and image data of the B (blue) component can be acquired from a single color image data.

[0042] Next, we will explain the image synthesis process of the inspection control unit 31 of the control unit 30 using Figure 4. As described above, the inspection control unit 31 controls the XY stage 16 and acquires image data of the inspection surface of the object under inspection 12 when illuminated by the incident illumination source 23a (hereinafter referred to as the "Coaxis image"), when illuminated by the upper light source 23b (hereinafter referred to as the "Top image"), when illuminated by the middle light source 23c (hereinafter referred to as the "Side image"), and when illuminated by the lower light source 23d (hereinafter referred to as the "Low image"), and the intensity of each pixel is stored in the memory 35. In the following explanation, the image data of the inspection surface of the object under inspection 12 (object under inspection image data) is assumed to consist of M × N pixels (where M and N are positive integers). The storage area for the image data (coaxis image) of the incident illumination source 23a for a pixel (i,j) is denoted as Ac(i,j), the storage area for the image data (Top image) of the upper light source 23b is denoted as At(i,j), the storage area for the image data (Side image) of the middle light source 23c is denoted as As(i,j), and the storage area for the image data (Low image) of the lower light source 23d is denoted as Al(i,j). Furthermore, the storage area for the R (red) component image data generated by the following process is denoted as Br(i,j), the storage area for the G (green) component image data is denoted as Bg(i,j), and the storage area for the B (blue) component image data is denoted as Bb(i,j). However, i = 0···M-1 and j = 0···N-1.

[0043] When the inspection control unit 31 of the control unit 30 captures image data of the inspection surface of the object to be inspected 12 by the light sources 23a to 23d of the illumination unit 23 as a result of the above-described process, it clears the storage areas Br(i,j), Bg(i,j), and Bb(i,j) of the RGB component image data (step S100). Then, the variable i, which counts the pixels in the column direction of the image data, is set to 0 (step S102), and the variable j, which counts the pixels in the row direction of the image data, is set to 0 (step S104). First, the intensity of the Coaxis image (Ac(i,j)) and the intensity of the Top image (At(i,j)) at pixel (i,j) are compared (step S106). If the intensity of the Coaxis image is greater than the intensity of the Top image, the value of the intensity of the Coaxis image is stored as the value of pixel (i,j) of the R component image data (the value of Ac(i,j) is set to Br(i,j)) (step S108). If the intensity of the Top image is less than or equal to the intensity of the Coaxis image, the value of the intensity of the Top image is stored as the value of pixel (i,j) of the R component image data (the value of At(i,j) is set to Br(i,j)) (step S110).

[0044] Next, the intensity of the Coaxis image (Ac(i,j)) and the intensity of the Low image (Al(i,j)) at pixel (i,j) are compared (step S112). If the intensity of the Coaxis image is greater than the intensity of the Low image, the value of the Coaxis image intensity is stored as the value of pixel (i,j) of the B component image data (the value of Ac(i,j) is set to Bb(i,j)) (step S114). If the intensity of the Low image is less than or equal to the intensity of the Coaxis image, the value of the Low image intensity is stored as the value of pixel (i,j) of the B component image data (the value of Al(i,j) is set to Bb(i,j)) (step S116).

[0045] Furthermore, the intensity of the Side image at pixel (i,j) (As(i,j)) is stored as the value of pixel (i,j) in the G component image data (the value of As(i,j) is set to Bg(i,j)) (step S118).

[0046] Then, 1 is added to the variable j (step S120), and it is determined whether the value of this variable j is less than or equal to N (step S122). If it is less than N, the process returns to step S106 and the above process is repeated. Also, if it is determined in step S122 that the value of variable j is greater than or equal to N, 1 is added to the variable i (step S124), and it is determined whether the value of variable i is less than or equal to M (step S126). If it is less than M, the process returns to step S104 and the above process is repeated.

[0047] Finally, using the R component image data Br(i,j), B component image data Bb(i,j), and G component image data Bg(i,j) (i=0···M-1, j=0···N-1) generated for all M×N pixels as described above, the value of the red component is determined from the value of Br(i,j), the value of the blue component is determined from the value of Bb(i,j), and the value of the green component is determined from Bg(i,j) for each pixel (i,j), and the color image data (RGB image data) is synthesized and stored in memory 35 (step S128).

[0048] Basically, the intensity of reflected light cannot be detected unless the projection angles of each light source 23a to 23d of the lighting unit 23 and the inclination state of the inspection surface of the object under inspection 12 are directly input to the camera unit 21. However, in some cases, light reflected from the inspection surface and then reflected again from other parts of the inspection surface of the object under inspection 12 (due to secondary reflection) may enter the camera unit 21 and be detected. Also, as explained using Figure 3, in this embodiment, of the hue H of the RGB image data that is finally generated, R (red) is assigned to Top (representing an inclination of 15° to 45°), and B (blue) is assigned to Low (representing an inclination of 65° to 85°). Therefore, when the intensity of the Coaxis image (Ac(i,j)) at pixel (i,j) is greater than the intensity of the Top image (At(i,j)) and the Low image (Al(i,j)), by setting the intensity of this Coaxis image as the value of the R image data and B image data (Br(i,j) and Bb(i,j)) at that pixel (i,j), it can be determined that the light is the angle at which reflected light from the incident illumination source 23a is incident on the camera unit 21 (a tilt state of 0° to 15°), and the hue H can be represented as purple. Furthermore, when the intensity of the Top image is greater than or equal to the intensity of the Coaxis image, it can be determined that the inspection surface corresponding to that pixel is at an angle where reflected light from the upper light source 23b directly incidents on the camera unit 21 (a tilt state of 15° to 45°), and the hue H is represented in red. When the intensity of the Low image is greater than or equal to the intensity of the Coaxis image, it can be determined that the inspection surface for that pixel is at an angle where reflected light from the lower light source 23d directly incidents on the camera unit 21 (a tilt state of 65° to 85°), and the hue H is represented in blue.

[0049] Furthermore, if the hue H of the coaxis is assigned to yellow, for example, it will also be yellow when the angle of the inspection surface is near the boundary between the slope state corresponding to Side (45°~65°) and the slope state corresponding to Low (65°~85°), making it impossible to distinguish the slope state. However, by assigning the hue H corresponding to the coaxis to purple, which is between R (red) and B (blue), the range of slope angles that is furthest apart, the slope state can be clearly distinguished. Similarly, by using purple, the effects of secondary reflection can also be eliminated.

[0050] As described above, by representing the inclination state (angle) of the inspection surface of the object to be inspected 12 as RGB image data corresponding to the angle of hue H in the HSV color system (see Figure 3), the change in the angle of hue H (i.e., the change in color) corresponds to the change in the angle of the inspection surface (for example, when the angle of the inspection surface changes from 0° → 30° → 55° → 75°, the color of the corresponding pixel in the RGB image changes from purple → red → green → blue), making it possible to intuitively understand the inclination state of the inspection surface. In the above explanation, we described the case where the Top, Side, and Low states are assigned to R (red), G (green), and B (blue), respectively (resulting in the Coaxis state being purple). However, for example, if the Top state is assigned to yellow, in Figure 3, it is possible to assign colors that are 120° shifted in hue H from yellow to the Side and Low states, and to make the Coaxis state a hue H between the Top and Low states.

[0051] Furthermore, by using RGB image data as described above, when the inclination of the inspection surface of the object being inspected 12 changes smoothly, the hue H changes according to the angle as described above. Therefore, when the change in hue H is not continuous or changes abruptly, it is possible to represent the possibility that the inspection surface is abnormal (the height of the inspection surface is abnormal). In addition, by estimating the inclination (angle) of the inspection surface from the change in hue H in the RGB image data, it can also be used as a material for measuring the height of the inspection surface.

[0052] Furthermore, the inspection targets using such RGB image data are not limited to the solder surface as described above; they can also be applied to the shape of the IC lead tips and the shape of the chip electrodes.

[0053] Next, when the object under inspection 12 is an electronic circuit board, the types of solder used to attach electronic components to this electronic circuit board and methods for classifying them will be explained.

[0054] Conventional solder is an alloy primarily composed of lead and tin. When heated and molten, the solder solidifies, forming a fine, lamellar eutectic structure of lead and tin, resulting in a smooth surface with minimal irregularities. On the other hand, in the case of so-called "lead-free solder," which is formulated with silver, copper, or other metals instead of lead to reduce the lead content, coarse dendritic primary crystals appear first during solidification, and the eutectic structure forms in the gaps between them. As a result, the surface of the solidified solder has numerous irregularities on the order of tens of micrometers, but their shape, size, and number vary depending on the metals incorporated into the solder and their proportions. Therefore, the type of solder used can be classified based on the shape of the solidified structure on the solder surface (the surface texture of the solidified solder), whether it is smooth or rough, and, in the case of a rough surface, the shape, size, and number of irregularities.

[0055] As described above, the inspection apparatus of this embodiment can acquire RGB image data (color image data) that represents the angle of the inspection surface by differences in color information by irradiating the surface of the object to be inspected 12 with illumination light emitted from different angles. The apparatus is configured to classify the type of solder used from the image data of the solder surface obtained using this RGB image data. The method for classifying the type of solder will be described below.

[0056] First, the method for classifying solder types will be explained using Figure 5. When the solder type classification process is started, the control unit 30 reads RGB image data containing the solder from the memory 35 (step S200). As described above, the board inspection data includes information on the inspection window, which is the inspection area on the image for each inspection item, and from this information, the location of the solder on the object under inspection 12 can be identified. Alternatively, the location of the solder can also be identified from the design data of the object under inspection 12. The control unit 30 also converts the read RGB image data to HSV and obtains the three axis values ​​of H (chromaticity), S (saturation), and V (luminance) (step S202).

[0057] As described above, the chromaticity information represents the degree of gradient of the solder portion, which reflects the macroscopic uneven surface shape of the solder portion. Therefore, the control unit 30 obtains granularity features (size, shape, number, etc. of irregularities (particles)) by labeling the chromaticity distribution using the three-axis values ​​obtained from the RGB image data (step S204). In addition, the saturation information is a continuous quantity corresponding to the diffuse reflectivity of the surface of the solder portion, and reflects the microscopic surface roughness of the solder portion. Specifically, when there is a lot of diffuse reflectivity, the saturation is close to 0, and when there is a lot of total reflection and specular reflection, the saturation becomes 100%, reflecting the microscopic surface roughness. Therefore, the control unit 30 obtains surface smoothness features (smooth or rough) from the saturation using the three-axis values ​​obtained from the RGB image data (step S206).

[0058] Finally, the control unit 30 compares the feature quantities obtained in steps S204 and S206 with a feature quantity map, for example, shown in Figure 6, to classify the solder type (step S208), and terminates the solder type classification process. Figure 6 shows a case where the solder type is classified using particle number, particle size, and surface smoothness as feature quantities.

[0059] One method for classifying solder types is contour matching, an algorithm that inspects specific regions within an image. Contour matching involves enclosing the contours of consecutive pixels (regions) that meet certain criteria, and then measuring their number, area, and contour length. While binarizing an image to determine the area of ​​irregularities yields similar values ​​whether the target pixels are dispersed or clustered, contour matching can capture regions that are clusters of pixels, thus accurately representing the shape (texture) of the solder surface. As mentioned above, the solder type classification process in this embodiment uses HSV-converted RGB image data, which improves the accuracy of the aforementioned feature quantities. It is also possible to classify solder using the original RGB image data that has not been HSV-converted.

[0060] If the surface irregularities of the coagulated tissue are finer than the resolution of the camera unit 21, resulting in a textured, pearlescent surface, diffuse reflected light will be captured. In this case, the RGB values ​​do not clearly separate according to the angle of illumination, as in specular reflection, and an image is captured where the illuminations appear to be mixed together. In this case, it becomes difficult to extract the granular contours themselves, but the characteristic of having finer irregularities than the resolution of the camera unit 21 can be obtained.

[0061] Alternatively, as a method for classifying solder types, machine learning such as deep learning can be used to perform classification. Specifically, by creating an AI model by training it with HSV-converted RGB image data for each solder type from a pre-selected image region, the solder type can be classified in inspection based on the image data of the solder portion (image data obtained by converting RGB image data to HSV) using this AI model. By using an AI model, the need for parameter adjustments for the classification process is eliminated. It is also possible to classify using the original RGB image data that has not been converted to HSV.

[0062] Furthermore, the classification of the type of solder used in the object under inspection 12 may be determined not only by looking at a single soldered section, but also by performing the above-described classification process on multiple soldered sections of the object under inspection 12, and classifying the most frequently classified type of solder as the type of solder used in the object under inspection 12.

[0063] Furthermore, when acquiring RGB image data converted to HSV format (specifically, image data where the color corresponds to the angle of the solder portion) from image data obtained by irradiating the object under inspection 12 with illumination light from different angles, it is desirable for classification of solder types to position the camera unit 21 such that the optical axis of the lens of the camera unit 21 and the solder surface are as close to perpendicular as possible. For this reason, in addition to the camera unit 21 described above (referred to as the "main camera"), a sub-camera may be provided to image the object under inspection 12 from an angle different from that of the main camera, and both the main camera and the sub-camera may be configured to acquire RGB image data corresponding to the angle of the solder portion. This sub-camera can be positioned, for example, at the location of the projection unit 24 in Figure 1. When generating RGB image data converted to HSV format from image data obtained by the sub-camera, it is desirable that the relationship between the color of the RGB image data obtained by the main camera and the angle of the solder portion be the same. That is, it is desirable that both the RGB image data obtained by the main camera and the RGB image data obtained by the sub-camera have the same color when the angle of the solder portion is the same.

[0064] In this way, when acquiring RGB image data with the main camera and sub-camera, the main camera may be used to image solder without components, and the sub-camera may be used to image good solder at an angle.

[0065] In the inspection apparatus 10 according to this embodiment, a certain field of view is required to inspect the soldering state and the mounting state of components, which would result in a lower resolution for the camera unit 21. However, as described above, by irradiating the object under inspection 12 with illumination light from different angles to acquire image data, and generating RGB image data from this image data that corresponds to the angle and color of the soldered parts, and using this data for classifying the type of solder, the type of solder can be classified accurately even with a low resolution for the camera unit 21. In other words, in this method of classifying the type of solder, it is not necessary to capture the shape of the solidified structure in detail, and it is sufficient for the camera unit 21 to have a resolution that is sufficient to capture the global features to a certain extent. For example, to capture a 20 μm structure, a resolution of 2 μm (1 / 10 of that) is generally required, but according to the method of this application, a resolution of 5 to 30 μm that can capture the global features is sufficient. Furthermore, by widening the field of view of the camera unit 21, the inspection speed of the object under inspection 12 can be improved.

[0066] Next, the inspection process for the soldered portion of the object to be inspected 12, which is performed in the inspection apparatus 10 according to this embodiment, will be described. Note that the inspection of the object to be inspected 12 in the inspection apparatus 10 is not limited to the inspection of the soldered portion, but also includes an inspection of the quality of the mounting state of the electronic components. However, in the following description, only the inspection of the soldered portion will be described.

[0067] -First testing method- First, the first solder inspection method will be explained using Figure 7. When inspection is started, the control unit 30 of the inspection device 10 brings the object to be inspected 12, which has been passed from the upstream process of the inspection device 10, into the inspection area (step S300). The control unit 30 also moves the imaging unit 20 using the XY stage 16 to image the recognition marks on the object to be inspected 12 (step S301). The position of the substrate can be accurately determined by the recognition marks, and the position of the solder can be accurately identified in subsequent processing.

[0068] Next, the control unit 30 moves the imaging unit 20 using the XY stage 16 to image the solder portion on the object under inspection 12, which will be used to classify the type of solder (step S302). As described above, the location of the solder can be identified from the design data and board inspection data of the object under inspection 12, and based on this information, images of the solder portion can be efficiently acquired.

[0069] When image data of the soldered portion is acquired in step S302, the control unit 30 uses the image data to perform the solder type classification process described above and classifies the type of solder used on the object under inspection 12 currently being inspected (step S303). The control unit 30 compares the type of solder classified in step S303 with the type of solder specified in the design data or board inspection data (step S304). If the control unit 30 determines that the type of solder being used is correct (identical to the type of solder specified in the design data or board inspection data) (step S304: "Y"), the control unit 30 images the other areas on the object under inspection 12 (step S305), inspects the soldering condition in each area (step S306), and once the inspection of all soldered portions is complete, the object under inspection 12 is moved to the next process (step S307), and the process returns to step S300 to inspect the next object under inspection 12.

[0070] On the other hand, if in step S304 the control unit 30 determines that the type of solder being used is incorrect (different from the type of solder specified in the design data or board inspection data) (step S304: "N"), the control unit 30 outputs a warning using the output unit 37, etc. (step S308) and terminates the inspection process. If a warning is output, an operator or other person removes the object to be inspected 12 from the inspection device 10 and checks the type of solder, etc.

[0071] Thus, according to the first inspection method, the type of solder used in the object under inspection 12 can be classified from the image of the solder portion, and a warning can be issued if it differs from the type of solder specified in the design data or board inspection data, thus enabling management of the type of solder used in the object under inspection 12.

[0072] -Second testing method- Next, a second solder inspection method will be explained using Figure 8. This second inspection method involves classifying the type of solder, reading inspection parameters set according to the type of solder used, and switching the board inspection data based on these inspection parameters to perform an inspection of the soldering condition.

[0073] When inspection begins, the control unit 30 brings the object to be inspected 12, which has been passed from the upstream process of the inspection device 10, into the inspection area (step S320). The control unit 30 also moves the imaging unit 20 using the XY stage 16 to image the recognition marks on the object to be inspected 12 (step S321). The position of the substrate can be accurately determined by the recognition marks, and the position of the solder can be accurately identified in subsequent processing.

[0074] Next, the control unit 30 moves the imaging unit 20 using the XY stage 16 to image the solder portion on the object under inspection 12, which will be used to classify the type of solder (step S322). Similar to the first inspection method, the location of the solder can be identified from the design data and board inspection data of the object under inspection 12, and based on this information, images of the solder portion can be efficiently acquired.

[0075] In step S322, when image data of the soldered portion is acquired, the control unit 30 uses the image data to perform the solder type classification process described above and classifies the type of solder used in the object under inspection 12 that is currently being inspected (step S323). Then, the control unit 30 reads the inspection parameters corresponding to the classified solder type (step S324). Here, we will specifically explain the case where either of the two types of solder, A or B, is used (the types of solder are not limited to these two). If the control unit 30 determines that the solder type is "A" (step S324: "Type A"), it reads the inspection parameters for solder type A from the memory 35, etc. (step S325). If the control unit 30 determines that the solder type is "B" (step S324: "Type B"), it reads the inspection parameters for solder type B from the memory 35, etc. (step S326).

[0076] When the control unit 30 reads the inspection parameters, it images other areas on the object to be inspected 12 (step S327), and uses the inspection parameters read in step S325 or step S326 to inspect the soldering condition in each area (step S328). Once the inspection of all soldered parts is complete, the object to be inspected 12 is moved to the next process (step S329), and the process returns to step S320 to inspect the next object to be inspected 12.

[0077] Thus, according to the second inspection method, the type of solder used on the object under inspection 12 can be classified from the image of the soldered portion, and inspection parameters for the soldering state can be read according to the classified type of solder, and the board inspection data can be switched according to these inspection parameters, so that an appropriate inspection can be performed according to the type of solder used.

[0078] -Third testing method- Next, a third solder inspection method will be explained using Figure 9. This third inspection method involves classifying the types of solder and generating board inspection data according to the type of solder used, and then performing the inspection.

[0079] When inspection begins, the control unit 30 reads the design data of the object to be inspected 12 from the memory 35 (step S340). The control unit 30 also brings the object to be inspected 12, which has been passed from the upstream process of the inspection device 10, into the inspection area (step S341). The control unit 30 also moves the imaging unit 20 using the XY stage 16 to capture recognition marks on the object to be inspected 12 (step S342). The position of the substrate can be accurately determined by the recognition marks, and the position of the solder can be accurately identified in subsequent processing.

[0080] Next, the control unit 30 moves the imaging unit 20 using the XY stage 16 to image the solder portion on the object under inspection 12, which will be used to classify the type of solder (step S343). Similar to the first and second inspection methods, the location of the solder can be identified from the design data and board inspection data of the object under inspection 12, and based on this information, images of the solder portion can be efficiently acquired.

[0081] In step S343, when image data of the soldered portion is acquired, the control unit 30 uses the image data to perform the solder type classification process described above and classifies the type of solder used in the object under inspection 12 that is currently being inspected (step S344). Then, the control unit 30 reads the inspection library corresponding to the classified solder type (step S345). Here, we will specifically explain the case where either of the two types of solder, A or B, is used (the types of solder are not limited to these two). If the control unit 30 determines that the solder type is "A" (step S345: "Type A"), it reads the inspection library for solder type A from the memory 35, etc. (step S346). If the control unit 30 determines that the solder type is "B" (step S345: "Type B"), it reads the inspection library for solder type B from the memory 35, etc. (step S347).

[0082] When the control unit 30 reads the inspection library, it images other areas on the object to be inspected 12 (step S348), and using the design data read in step S340 and the inspection library read in step S346 or step S347, it deploys the inspection library to each mounted component based on the design data (step S349). Then, the control unit 30 uses the deployed inspection library to inspect the soldering state in each area (step S350), and when the inspection of all soldered parts is completed, it moves the object to be inspected 12 to the next process (step S351), returns to step S340, and inspects the next object to be inspected 12.

[0083] Thus, according to the third inspection method, the type of solder used in the object under inspection 12 can be classified from the image of the soldered portion. Based on the classified type of solder, an inspection library can be deployed, and the quality of the soldering state and the mounting state of the electronic components can be inspected based on this inspection library. Therefore, since inspection data can be generated according to the type of solder used in the object under inspection 12, appropriate inspections can be performed according to the type of solder used.

[0084] -Fourth testing method- Next, a fourth solder inspection method will be explained using Figure 10. In the third inspection method, an inspection library was expanded according to the type of solder being used, but the fourth inspection method is configured to combine with the first inspection method and interrupt the inspection process when a solder type is classified as one that is not intended to be used.

[0085] When inspection begins, the control unit 30 reads the design data of the object to be inspected 12 from the memory 35 (step S360). The control unit 30 also brings the object to be inspected 12, which has been passed from the upstream process of the inspection device 10, into the inspection area (step S361). Then, the control unit 30 moves the imaging unit 20 using the XY stage 16 to capture recognition marks on the object to be inspected 12 (step S362). The position of the substrate can be accurately determined by the recognition marks, and the position of the solder can be accurately identified in subsequent processing.

[0086] Next, the control unit 30 moves the imaging unit 20 using the XY stage 16 to image the solder portion on the object under inspection 12, which will be used to classify the type of solder (step S363). As explained in the first inspection method, the location of the solder can be identified from the design data and board inspection data of the object under inspection 12, and based on this information, images of the solder portion can be efficiently acquired.

[0087] When image data of the solder portion is acquired in step S363, the control unit 30 uses the image data to perform the solder type classification process described above and classifies the type of solder used in the object under inspection 12 that is currently being inspected (step S364). The control unit 30 also determines whether the type of solder classified in step S364 is a known type of solder (a type of solder that may be set in the design data or board inspection data) (step S365). Specifically, if the control unit 30 determines that the type of solder being used is known (step S365: "Y"), the control unit 30 reads the inspection library corresponding to the classified type of solder from the memory 35 (step S366), images other areas on the object under inspection 12 (step S367), and uses the design data read in step S360 and the inspection library read in step S366 to deploy the inspection library to each mounted component based on the design data (step S368). Then, the control unit 30 inspects the soldering condition in each area based on the deployed inspection library (step S369), and once all soldering inspections are complete, it moves the object under inspection 12 to the next process (step S370), returns to step S360, and inspects the next object under inspection 12.

[0088] On the other hand, if the control unit 30 determines in step S365 that the type of solder being used is unknown (step S365: "N"), the control unit 30 outputs a warning using the output unit 37, etc. (step S371) and terminates the inspection process. If a warning is output, an operator or other person removes the object to be inspected 12 from the inspection device 10 and checks the type of solder, etc.

[0089] Thus, according to the fourth inspection method, the type of solder used in the object under inspection 12 can be classified from the image of the soldered portion, and a warning can be issued if it is not a known type of solder, thus enabling management of the type of solder used in the object under inspection 12. Furthermore, since an inspection library can be set according to the type of solder, appropriate inspections can be performed according to the type of solder used.

[0090] -Fifth testing method- Finally, Figure 11 will be used to explain the fifth solder inspection method. In the second inspection method, inspection parameters were read according to the type of solder being used, and the board data was switched based on these parameters to inspect the soldering condition. The fifth inspection method is a combination of the first inspection method and is configured to interrupt the inspection process when the solder type is classified as one that is not intended to be used.

[0091] When inspection begins, the control unit 30 brings the object to be inspected 12, which has been passed from the upstream process of the inspection device 10, into the inspection area (step S380). The control unit 30 also moves the imaging unit 20 using the XY stage 16 to image the recognition marks on the object to be inspected 12 (step S381). The position of the substrate can be accurately determined by the recognition marks, and the position of the solder can be accurately identified in subsequent processing.

[0092] Next, the control unit 30 moves the imaging unit 20 using the XY stage 16 to image the solder portion on the object under inspection 12, which will be used to classify the type of solder (step S382). Similar to the first inspection method, the location of the solder can be identified from the design data and board inspection data of the object under inspection 12, and based on this information, images of the solder portion can be efficiently acquired.

[0093] In step S382, when image data of the solder portion is acquired, the control unit 30 uses the image data to perform the solder type classification process described above and classifies the type of solder used in the object under inspection 12 currently being inspected (step S383). Once the solder type is classified, the control unit 30 determines whether the solder type classified in step S383 is a known solder type (a solder type that may be set in the design data or board inspection data) (step S384). Specifically, if the control unit 30 determines that the solder type being used is known (step S384: "Y"), the control unit 30 reads the inspection parameters corresponding to the classified solder type (step S385). Here, we will specifically explain the case where either of the two types of solder, A or B, is used (the types of solder are not limited to these two). If the control unit 30 determines that the solder type is "A" (step S385: "Type A"), it reads the inspection parameters for solder type A from the memory 35, etc. (step S386). If the control unit 30 determines that the solder type is "B" (step S385: "Type B"), it reads the inspection parameters for solder type B from the memory 35, etc. (step S387).

[0094] When the control unit 30 reads the inspection parameters, it images other areas on the object to be inspected 12 (step S388), and uses the inspection parameters read in step S386 or step S387 to inspect the soldering condition in each area (step S389). Once the inspection of all soldered parts is complete, it moves the object to be inspected 12 to the next process (step S390), and returns to step S380 to inspect the next object to be inspected 12.

[0095] On the other hand, if the control unit 30 determines in step S384 that the type of solder being used is unknown (step S384: "N"), the control unit 30 outputs a warning using the output unit 37, etc. (step S391) and terminates the inspection process. If a warning is output, an operator or the like removes the object to be inspected 12 from the inspection device 10 and checks the type of solder, etc.

[0096] Thus, according to the fifth inspection method, the type of solder used on the object under inspection 12 can be classified from the image of the soldered area, and a warning can be issued if it is not a known type of solder, thus enabling management of the type of solder used on the object under inspection 12. Furthermore, inspection parameters for the soldering state can be read according to the classified type of solder, and the board inspection data can be switched based on these inspection parameters, so that appropriate inspections can be performed according to the type of solder used. [Explanation of Symbols]

[0097] 10 Inspection equipment 12. Subject under inspection 20. Imaging Unit (Imaging Section) 21 Camera Unit 23 Lighting unit (light source) 30 Control Unit (Control Section)

Claims

1. an imaging unit that images an object to be inspected; a control unit; The control unit The imaging unit captures an image of the solder portion on the object to be inspected to obtain image data; extracting, from the image data, feature quantities of the shape of the solidification structure appearing on the surface of the solder portion; The solder used in the solder portion is classified based on the feature amount. Inspection equipment.

2. a light source that irradiates the object under inspection with illumination light; The control unit Acquiring image data of the solder portion; generating RGB image data in which the angle of the solder portion and color information are associated with each other from the image data; The solder used in the solder portion is classified based on the RGB image data. The inspection device according to claim 1 .

3. The illumination light has a plurality of light sources that irradiate from different angles. The inspection device according to claim 2 .

4. The color information corresponds to a hue in the HSV color system. The inspection device according to claim 3 .

5. The control unit Based on the design data or inspection data of the object to be inspected, a position on the object to be inspected of a solder portion from which image data to be used for classifying the solder is acquired is identified. The inspection device according to any one of claims 1 to 4.

6. The control unit Inspecting the test object based on the classified solder. The inspection device according to any one of claims 1 to 4.

7. The control unit Inspection data is selected according to the classified solder, and the object to be inspected is inspected based on the selected inspection data. The inspection device according to any one of claims 1 to 4.

8. The control unit Inspection data is generated according to the classified solder, and the object to be inspected is inspected based on the generated inspection data. The inspection device according to any one of claims 1 to 4.

9. The feature amount is the size or number of irregularities on the surface of the solder part. The inspection device according to any one of claims 1 to 4.

10. The control unit The solder is classified based on an AI model generated by machine learning from the feature amount and the solder. The inspection device according to any one of claims 1 to 4.

11. the imaging unit has a plurality of camera units with different imaging angles relative to the object under inspection, The control unit The solder is classified using each of the image data of the object to be inspected captured by the plurality of camera units. The inspection device according to any one of claims 1 to 4.

12. The control unit Acquiring image data of a plurality of solder parts, and classifying the solder of the solder part corresponding to each image data according to the image data; The solder that is most frequently found among the classified solders is classified as the solder used in the test object. The inspection device according to any one of claims 1 to 4.

13. The control unit In addition to the above solder classification, The soldering condition of the soldered portion on the test object is inspected. The inspection device according to any one of claims 1 to 4.

14. The control unit The inspection is stopped depending on the classified solder. An inspection device according to any one of claims 1 to 4.

Images