KR101736060B1 - Inspection method - Google Patents

Abstract

To inspect the substrate, first a measurement area is set on the substrate and reference data for the measurement area is obtained. Next, the measurement data for the measurement area is acquired for each color, and the illumination condition is set using the reference data and the color-by-color measurement data obtained for the measurement area. Next, the feature object is set for the measurement area, and the reference data corresponding to the feature object is compared with the measurement data corresponding to the feature object according to the set illumination condition to obtain the amount of distortion between the reference data and the measurement data. Then, the distortion amount is compensated to set the inspection area in the measurement area. Thus, it is possible to set an accurate inspection region compensating for the distortion.

Description

{INSPECTION METHOD}

The present invention relates to an inspection method, and more particularly, to a method of inspecting a substrate.

In general, at least one printed circuit board (PCB) is provided in an electronic device, and various circuit elements such as a circuit pattern, a connection pad portion, a driving chip electrically connected to the connection pad portion, Respectively.

In general, a shape measuring device is used to check whether various circuit elements as described above are properly formed or disposed on the printed circuit board.

The conventional shape measuring apparatus sets a predetermined measurement area and checks whether a predetermined circuit element is properly formed in the measurement area. In the conventional measurement area setting method, an area in which a circuit element should theoretically merely be set as a measurement area.

The measurement area must be precisely set at a desired position so that measurement of a circuit element requiring measurement can be performed properly. However, a measurement object such as a printed circuit board is distorted such as warp and distortion of the base substrate The conventional measurement area can not be accurately set at a desired position and the image obtained by the camera of the photographing part is theoretically different from the position where the circuit element exists.

Therefore, it is required to set a measurement area that appropriately compensates for the distortion of the measurement object as described above.

SUMMARY OF THE INVENTION Accordingly, it is an object of the present invention to provide an inspection method capable of obtaining an optimal illumination condition for acquiring a feature object of good quality, and thereby setting an inspection area more accurately.

To inspect the substrate in accordance with an exemplary embodiment of the present invention, a measurement area is first set on the substrate. Then, reference data for the measurement area is obtained. Next, measurement data for the measurement area is acquired for each color. Then, the illumination condition is set using the reference data obtained for the measurement area and the measurement data for each color. Next, a feature object is set for the measurement area. Next, the reference data corresponding to the feature object is compared with the measurement data corresponding to the feature object according to the set illumination condition, and the amount of distortion between the reference data and the measurement data is acquired. Next, the distortion amount is compensated to set the inspection region in the measurement region.

Wherein the step of setting an illumination condition using the reference data and the color-by-color measurement data acquired for the measurement area includes a reference mask area including a conductive pattern in the reference data, Setting a reference mask area corresponding to the reference mask area and a reference mask area corresponding to the reference mask area in the color measurement data; And setting the illumination condition to increase the difference in gray scale between the measurement mask area and the measurement non-mask area.

The reference mask region may correspond to a signal line wiring substrate layer (signal layer) constituting the substrate.

In one embodiment, the gray value difference between the measurement mask area and the measurement unmask area is determined by a representative value of the gray value of the measurement mask area present in the measurement area, Lt; RTI ID = 0.0 > of gray values of < / RTI >

In another embodiment, the feature object is set as a feature block in a block unit so as to include a predetermined shape in the measurement area, and the step of setting the feature object for the measurement area includes: And may be performed before the step of comparing the reference data and the color-by-color measurement data to set the illumination condition. Wherein the gray value difference between the measurement mask area and the measurement unmask area is a sum of the representative value of the gray value of the measurement mask area existing in the feature block and the representative value of the gray value of the measurement non- Value can be defined by the difference between the values.

The color may include a first color, a second color, and a third color that are different from each other. The first color, the second color and the third color may be obtained directly by the measuring device. Further, the color may include a fourth color obtained by combining the first color and the second color, a fifth color obtained by combining the first color and the third color, a combination of the second color and the third color The first color, the sixth color, the first color, the second color, and the seventh color in which the third color is combined.

The distortion amount may be obtained by a quantified transformation formula between the reference data and the measurement data, and the quantified transformation formula may include a positional change, a gradient change, a magnitude change obtained by comparing the reference data and the measurement data And < RTI ID = 0.0 > deformability. ≪ / RTI >

The feature object may be set as a feature block of a block unit so as to include a predetermined shape in the measurement area, and the predetermined shape of the feature block may be a feature Lt; / RTI >

According to the present invention, an optimal illumination condition for acquiring a high-quality feature object can be obtained by setting the illumination condition such that the gray value difference is increased by using the information obtained for each color of the measurement data for the measurement area, Accordingly, the inspection area can be set more accurately.

In addition, since it is possible to perform an operation such as defect inspection on the basis of the inspection area set as described above, it is possible to more accurately determine whether the substrate is defective or not.

1 is a flowchart illustrating an inspection method according to an embodiment of the present invention.
2 is a plan view showing an example of reference data in the inspection method of FIG.
3 is a plan view showing an example of measurement data in the inspection method of FIG.
4 is a flowchart illustrating an embodiment of setting the illumination condition of FIG.
FIG. 5 is a graph illustrating an embodiment for explaining a process of finding an illumination for increasing the gray value difference in FIG.

The present invention is capable of various modifications and various forms, and specific embodiments are illustrated in the drawings and described in detail in the text. It should be understood, however, that the invention is not intended to be limited to the particular forms disclosed, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the terms "comprising" or "having ", and the like, are intended to specify the presence of stated features, integers, steps, operations, elements, parts, or combinations thereof, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, parts, or combinations thereof.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the meaning in the context of the relevant art and are to be interpreted as ideal or overly formal in meaning unless explicitly defined in the present application Do not.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Reference will now be made in detail to the preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings.

FIG. 1 is a flowchart illustrating an inspection method according to an embodiment of the present invention. FIG. 2 is a plan view illustrating an example of reference data in the inspection method of FIG. 1, FIG. Fig.

Referring to FIGS. 1 to 3, in order to set a distortion-compensated inspection area according to an embodiment of the present invention, a measurement area (FOV) is first set on a substrate (S110).

The measurement area (FOV) means a predetermined area set on the substrate for inspecting the substrate. For example, the measurement area (FOV) of view).

Next, the reference data RI for the measurement area FOV is obtained (S120).

The reference data RI may be a theoretical planar image for the substrate 100, for example, as shown in Fig.

In one embodiment, the reference data RI may be obtained from CAD information or gerber information on the shape of the substrate. The CAD information and the gerber information include design basis information of the substrate, and generally include layout information about pads, circuit patterns, hole patterns, and the like.

In another embodiment, the reference data RI may be obtained from the learning information obtained by the learning mode. In the learning mode, for example, the substrate information is retrieved from the database, and if there is no substrate information as a result of the database search, the learning of the bare substrate is performed. Then, after the learning of the bare substrate is completed, A method of storing the substrate information in the database, and the like. That is, the design reference information of the printed circuit board is learned by learning the bare board of the printed circuit board in the learning mode, and the reference data RI can be obtained by acquiring the learning information through the learning mode.

Next, the measurement data (PI) for the measurement area (FOV) is acquired for each color (S130).

The measurement data PI may be an image obtained by actually photographing the substrate corresponding to the reference data RI with an inspection device such as a three-dimensional shape measuring device, for example, as shown in Fig. The measurement data PI is similar to the reference data RI shown in FIG. 2, but is somewhat distorted as compared with the reference data RI due to bending, warping, or the like of the substrate 100.

In one embodiment, the measurement data (PI) illuminates the measurement area (FOV) using an illumination unit of the inspection equipment, and the reflected image of the irradiated light is photographed using a camera mounted on the inspection equipment ≪ / RTI >

In one embodiment, the colors may include a first color, a second color, and a third color that are different from one another. That is, the illumination unit may include a first illumination source that generates light of the first color, a second illumination source that generates light of the second color, and a third illumination source that generates light of the third color have. Accordingly, the first color, the second color and the third color are obtained directly by the illumination unit of the inspection equipment. For example, the first color, the second color, and the third color may be red, green, and blue, respectively.

Measurement data PI according to colors other than the first color, the second color and the third color can also be obtained. For example, the color may include a fourth color combining the first color and the second color, a fifth color combining the first color and the third color, the second color, and the third color And a seventh color obtained by combining the first color, the second color, and the third color. The combined colors may be generated by combining measurement data (PI) according to the first color, the second color, and the third color. For example, the fourth color, the fifth color, the sixth color, and the seventh color may be yellow, red magenta, cyan, and white, respectively.

Thus, since the measurement data PI are acquired for each color, measurement data different from each other by the number of colors is obtained.

Next, an illumination condition is set by comparing the reference data RI obtained for the measurement area FOV and the measurement data PI for each color (S140), and a feature object is set for the measurement area (step S140) S150).

The setting of the illumination condition (S140) may be performed earlier than the setting of the feature object (S150), or may be performed later.

4 is a flowchart illustrating an embodiment of setting the illumination condition of FIG.

Referring to FIG. 4,

A reference mask area including a conductive pattern and a reference no mask area including no conductive pattern are set in the reference data RI. (S142).

The conductive pattern includes, for example, a circuit pattern, a hole pattern, and the like, and has a shape corresponding to or included in the characteristic object. The characteristic object is a comparison object for obtaining a distortion amount between the reference data RI and the measurement data PI or a distortion amount between the reference data RI and the measurement data after the part is formed on the substrate It is used as a standard.

The feature object may include an object having the reference data RI and a predetermined shape positioned on a predetermined coordinate in the measurement data, and may directly correspond to the conductive pattern. For example, the feature object may include a hole pattern formed on the substrate, a corner portion of the curved circuit pattern, and the like, and the coordinates of the center point of the hole pattern or the corner point of the curved circuit pattern By comparing the reference data RI with the measurement data, a distortion amount described later can be obtained.

Alternatively, the feature object may be a feature block in units of blocks so as to include a predetermined shape, and the conductive pattern may correspond to the predetermined shape in the feature block. In this case, the reference data (RI) and the measurement data (PI) are compared with each other based on the feature objects of various shapes included in the feature block, so that a relatively accurate comparison can be performed.

The predetermined shape of the plurality of feature blocks in the block unit may have a two-dimensional delimiter capable of defining a two-dimensional plane so that the possibility of misunderstanding due to the shape of the periphery is eliminated. For example, the feature block may include various shapes such as a broken line, a rectangle, a circle, and combinations thereof, and a straight line can not define a two-dimensional plane and can not be included in the feature block.

As shown in FIG. 2, the reference data RI can be divided into a reference mask region RM in which the feature object exists and a reference non-mask region RNM in which the feature object does not exist.

In FIG. 2, the reference mask region in which the feature object exists is represented by gray (RM), and the reference non-mask region (RNM) in which the feature object is not present may be displayed in black. The classification may be performed automatically based on the predetermined type of the characteristic object or may be performed manually by the operator.

For example, the reference mask region RM may correspond to a signal line wiring substrate layer (signal layer) constituting the substrate, and the reference non-mask region RNM may be another region.

Next, the measurement mask area MM and the measurement unmask area MNM are set in the color-by-color measurement data PI (S144). The measurement mask area MM corresponds to the reference mask area RM and the measurement unmask area MNM corresponds to the reference unmask area RNM.

In one embodiment, as shown in FIG. 3, each of the color-by-color measurement data PI may be divided into the measurement mask area MM and the measurement non-mask area MNM.

Next, illumination for increasing the gray scale difference between the measurement mask area MM and the measurement non-mask area MNM is set as the illumination condition (S146).

Since the feature object is used as a comparison reference for obtaining the conversion relation between the reference data RI and the measurement data PI, it should be exactly specified from the reference data RI and the measurement data PI. If the distinction between the region corresponding to the feature object and the region adjacent to the feature object and not corresponding to the feature object is clear, accurate identification can be facilitated. Therefore, it is important to find an illumination condition that makes the distinction between the area corresponding to the characteristic object and the area not corresponding to the characteristic object clear.

For example, an illumination for increasing the gray value difference between the measurement mask area (MM) and the measurement unmask area (MNM) among the measurement data (PI) obtained for each color is found and set as the illumination condition.

In one embodiment, the gray value difference is a representative value of the gray value of the measurement mask area MM present in the measurement area FOV and the representative value of the gray value of the measurement non-mask area MNM present in the measurement area FOV, Lt; RTI ID = 0.0 > of gray values of < / RTI > For example, the representative value may include an average value, a median value, a mode value, and the like.

In another embodiment, when the feature object is a feature block of a block unit, the gray value difference may be a representative value of a gray value of the measurement mask area existing in the feature block, Lt; RTI ID = 0.0 > of gray values of < / RTI > For example, the representative value may include an average value, a median value, a mode value, and the like.

In this case, the feature object may be preset before the step (S140) of setting the illumination condition.

FIG. 5 is a graph illustrating an embodiment for explaining a process of finding an illumination for increasing the gray value difference in FIG.

Referring to FIG. 5, a gray value of the measurement mask area MM and a gray value of the measurement non-mask area MNM among the measurement data PI obtained for each color are shown in a histogram.

In the histogram, two convex shapes are shown. The measurement unmasked area MNM corresponds to the left side, and the measurement mask area MM corresponds to the right side.

For example, a representative value of the gray value of the measurement unmasked area MNM may be a first mode value Max1, and a representative value of the gray value of the measurement mask area MM may be a second mode value Max2 . Of course, the representative value of the gray value of the measurement non-mask area MNM and the representative value of the gray value of the measurement mask area MM may be an average value, a median value, or the like.

Next, the reference data corresponding to the feature object is compared with the measurement data corresponding to the feature object according to the set illumination condition, and the amount of distortion between the reference data and the measurement data is obtained (S160).

The amount of distortion may be obtained by a quantified transformation formula between the reference data (RI) and the measurement data (PI) corresponding to the comparison block.

Since the measurement data PI is distorted compared to the reference data RI corresponding to the theoretical reference information due to warping or distortion of the substrate, the measurement data PI is distorted between the reference data RI and the measurement data PI. The relationship can be defined by a transformation formula defined according to the amount of distortion.

The quantified transformation formula may be defined using at least one of a position change, a gradient change, a size change, and a deformation degree obtained by comparing the reference data (RI) and the measurement data (PI) .

On the other hand, for example, the conversion formula may be expressed by Equation (1).

In Equation (1), P _CAD is a coordinate of a target according to CAD information or gerber information, that is, a coordinate in the reference data RI, f (tm) is a transfer matrix, And P _real is the coordinates of the target in the measurement data PI obtained by the camera. The transformation matrix can be obtained by obtaining the theoretical coordinates P _CAD in the reference data RI and the real coordinates P _real in the measurement data PI.

For example, the transformation matrix may include a coordinate transformation matrix according to an affine transformation or a perspective transformation in which a point correspondence on the n-dimensional space is expressed by a linear expression. In order to define the coordinate transformation matrix, the number of feature objects may be appropriately set. For example, three or more feature objects may be set in affine transformation, and four or more feature objects may be set in case of perspective transformation.

On the other hand, the measurement data PI may be measured data (or photographed image) before the component is mounted on the substrate, for example, as shown in Fig. 3, It may be measured data (or photographed image).

Subsequently, the distortion amount is compensated to set the inspection area in the measurement area (S170).

Since the distortion amount indicates the degree of distortion generated in the measurement data PI by comparing with the reference data RI, if the compensation amount is compensated, the inspection area is divided into the first measurement area FOV, Can be closer to the shape. The setting of the inspection area may be performed on all or a part of the measurement area (FOV).

If the distortion amount is compensated to set the inspection area within the measurement data PI, it is possible to more accurately check whether the parts in the inspection area are defective or not. At this time, when the measurement data PI is measured data before mounting the component as shown in FIG. 3, the measurement data after component mounting is separately acquired and then the inspection is performed. Alternatively, when the measurement data PI is measured data after mounting the component, the inspection is performed using the measurement data PI.

Next, it may be optionally verified whether or not the set inspection area is valid. At this time, the verification may be performed directly using the characteristic object for obtaining the distortion amount, or separately using the characteristic object for verification.

According to the present invention, by setting the illumination condition such that the gray value difference is increased by using the information obtained for each color of the measurement data (PI) for the measurement area (FOV) It is possible to obtain the illumination condition, and accordingly, the inspection area can be set more accurately.

In addition, since it is possible to perform an operation such as defect inspection on the basis of the inspection area set as described above, it is possible to more accurately determine whether the substrate is defective or not.

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit and scope of the invention. Accordingly, the foregoing description and drawings are to be regarded as illustrative rather than limiting of the present invention.

10: Pad 20: Parts
22: terminal 30: circuit pattern
40: Circle 42: Hole
FB1: first feature block FB2: second feature block
MB1: first merging block MB2: second merging block
PI: measurement data RI: reference data

Claims (3)

The method comprising: setting a measurement area on a substrate;
Illuminating a plurality of illuminations with a plurality of illumination sources generating a plurality of lights for the measurement area;
Acquiring, by the plurality of lights, a plurality of measurement data for the measurement area;
Selecting measurement data having a relatively large gray scale difference between an area including a predetermined feature object and an area not including the feature object among the plurality of measurement data;
Comparing measurement data of the feature object included in the selected measurement data with reference data corresponding to the feature object to obtain a distortion amount of the measurement area; And
And setting the inspection area within the measurement area by compensating the distortion amount,
Wherein in the step of illuminating the plurality of illuminations by the plurality of illuminants that produce a plurality of lights for the measurement area,
The plurality of lights including a plurality of color lights,
And illuminates the plurality of color lights and the plurality of color lights selected from at least one color light according to the combination of the plurality of color lights. delete The method according to claim 1,
Wherein the feature object comprises a conductive pattern formed on the substrate,
Wherein the step of selecting measurement data having a relatively large difference in gray value between an area including a predetermined feature object and an area not including the feature object among the plurality of measurement data,
Identifying a measurement mask area including the conductive pattern and a measurement unmask area not including the conductive pattern within the plurality of measurement data; And
And selecting measurement data having a relatively large difference in gray value between the measurement mask area and the measurement non-mask area among the plurality of measurement data.

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