Maskless exposure apparatus including image processing function for correcting position of substrate

Abstract

The purpose of a maskless exposure apparatus including an image processing function for correcting the position of a substrate according to an embodiment is to provide precise position measurement and correction functions capable of detecting and correcting a fine alignment error of the substrate. In addition, the purpose of an embodiment is to provide a maskless exposure apparatus including an image processing technology that automatically measures roll, yaw, and pitch of a substrate and reflects same in an exposure process.

Description

Maskless exposure device including image processing function for substrate position correction

[0001] The technical concept of the present disclosure relates to a maskless exposure apparatus including an image processing function for position correction of a substrate, and more specifically, to an apparatus and method for correcting image data to be exposed through image processing based on an image of a substrate.

[0002] Unless otherwise indicated in this specification, the contents described in this section are not prior art for the claims of this application, and are not to be recognized as prior art simply because they are included in this section.

[0003] In conventional semiconductor manufacturing processes, photolithography technology is generally used for patterning. This process includes an exposure step using a mask to transfer a designed circuit pattern onto a wafer coated with photoresist. The exposure process enables the formation of a desired circuit pattern by irradiating the wafer with a light source, such as ultraviolet (UV) or extreme ultraviolet (EUV), through the mask.

[0004] A commonly used mask forms a circuit pattern consisting of transparent and blocking sections by depositing an opaque film, such as metallic chrome, onto a quartz substrate and etching it. Subsequently, the mask is fixed to a stage, and light is irradiated onto the wafer following precise alignment.

[0005] However, conventional mask exposure processes require precise alignment for high-resolution pattern implementation, and minute errors or distortions in the mask occurring during this process can affect overlay accuracy and reduce yield. Furthermore, repetitive exposure processes can lead to contamination or damage to the mask, causing a degradation in the quality of the pattern transfer.

[0006] In particular, since the latest microfabrication processes require precision in the nanometer (nm) range, conventional mask-based lithography methods face limitations in satisfying these requirements. Accordingly, there is a need for the development of technologies that improve lithography precision and enhance resistance to mask contamination and damage.

[0007] In conventional mask exposure processes, masks are used to perform exposure for forming circuit patterns on a substrate; however, this presents challenges such as high manufacturing and management costs and complex process issues. Although maskless exposure devices have been introduced to address these issues, pattern alignment problems caused by minute positional errors in the substrate remain a challenge to be resolved. In particular, errors in the substrate’s Roll, Yaw, and Pitch can affect the precise positioning of the pattern, and failure to precisely measure and correct these errors can lead to a degradation in the quality of the exposed circuit. Accordingly, there is a need for technology that automatically measures and corrects substrate errors to perform high-precision exposure.

[0008] A maskless exposure apparatus including an image processing function for position correction of a substrate according to an embodiment aims to provide a precise position measurement and correction function capable of detecting and correcting minute alignment errors of a substrate.

[0009] In addition, the embodiment aims to provide a maskless exposure apparatus that includes image processing technology for automatically measuring the Roll, Yaw, and Pitch of a substrate and reflecting them in the exposure process.

[0010] Meanwhile, the technical problems of the present invention are not limited to those mentioned above, and other unmentioned technical problems will be clearly understood by a person skilled in the art from the description below.

[0011] A maskless exposure device according to an embodiment comprises: a management information processing device that transmits image data to be exposed to a controller via a high-speed communication method and transmits various preset exposure-related parameters to a trigger generation device; a controller that converts the image data received from the management information processing device into an output image and transmits it to a DMD control unit; a stage on which a substrate to be exposed is mounted, which moves in a direction opposite to the direction to be exposed, and which generates an encoder signal according to the movement and transmits it to a trigger generation device; an image capturing unit that captures an image of the substrate and transmits it to the management information processing device; a trigger generation device that calculates the number of pulses of the encoder signal received from the stage and generates a trigger signal and transmits it to a DMD control unit whenever the number of pulses of the encoder signal corresponding to the position to be exposed is calculated; and a DMD control unit that adjusts the angle of a specific micromirror of the DMD based on the output image received from the controller and the trigger signal received from the trigger generation device.

[0012] A light source emitting light for exposure; a DMD in which the angle of a specific micro-mirror is adjusted by the DMD control unit to reflect light from the light source and expose it to a desired location on the substrate; and an optical system that refracts the light reflected from the DMD to expose it to a desired location on the substrate; wherein the management information processing device may include: an image processing unit that calculates Roll (rotation), Yaw (left-right tilt), and Pitch (front-back tilt) errors of the substrate based on the image received from the image capturing unit; and an image correction unit that corrects the image to be exposed based on the Roll (rotation), Yaw (left-right tilt), and Pitch (front-back tilt) errors of the substrate calculated by the image processing unit to generate a corrected image.

[0013] In addition, the image processing unit can extract reference markers or feature points on the substrate from the image, calculate the position error between the actual positions of the extracted feature points and the reference positions, calculate Roll (rotation), Yaw (left-right tilt), and Pitch (front-back tilt) information of the substrate based on the position error, and correct the position of the substrate based on the calculated Roll, Yaw, and Pitch information.

[0014] In addition, the image processing unit can correct the Roll, Yaw, and Pitch of the substrate by correcting and controlling the position and orientation of the stage supporting the substrate.

[0015] In addition, the image processing unit can estimate the attitude error of the substrate using matrix operations or the least squares method by utilizing the relative distance and angle between reference markers.

[0016] In addition, the image processing unit can detect a reference marker after performing a preprocessing process on the image that includes at least one of filtering, binarization, edge detection, or corner detection.

[0017] In addition, the reference position may include a preset alignment reference coordinate system based on the design drawing of the substrate or a master coordinate system.

[0018] In addition, the position error can be calculated based on the average value or weighted average value derived from a plurality of reference markers on the substrate.

[0019] In addition, the image processing unit can perform the position correction in a three-dimensional coordinate system when the substrate includes a curved or irregular shape.

[0020] The maskless exposure apparatus according to the embodiment enables high-resolution and high-precision patterning by detecting minute alignment errors of a substrate through an image processing function and correcting them in real time. Accordingly, the overlay accuracy in the exposure process is improved, thereby enhancing the overall process yield and productivity.

[0021] In addition, in the embodiment, attitude information such as Roll, Yaw, and Pitch of the substrate is automatically measured and reflected in the exposure process in real time, thereby minimizing errors even in processes requiring precision in the nanometer range. This enables increased exposure precision for complex three-dimensional structures or irregular substrates.

[0022] In addition, the embodiment uses a maskless exposure method, which reduces mask manufacturing and management costs and improves production flexibility by enabling rapid pattern switching even when changing products.

[0023] In addition, unlike conventional manual or semi-automatic alignment methods, the image processing-based automatic position correction in the embodiment minimizes operator intervention and enables a fully automated process flow, thereby significantly increasing the efficiency and repeatability of the entire process.

[0024] The effects obtainable from the exemplary embodiments of the present disclosure are not limited to those mentioned above, and other unmentioned effects can be clearly derived and understood by those skilled in the art to which the exemplary embodiments of the present disclosure belong from the description below. That is, unintended effects resulting from the implementation of the exemplary embodiments of the present disclosure can also be derived by those skilled in the art from the exemplary embodiments of the present disclosure.

[0025] FIG. 1 is a configuration diagram of a maskless exposure apparatus (100) according to an embodiment of the present disclosure.

[0026] FIG. 2 is a configuration diagram of a management information processing device (10) of a maskless exposure device (100) according to an embodiment of the present disclosure.

[0027] FIG. 3 is a diagram illustrating the process of an image processing unit according to an embodiment of the present invention recognizing feature points on a substrate and calculating position error and attitude error (Roll, Yaw, Pitch).

[0028] Figure 4 is a diagram showing the position correction process of a substrate according to an embodiment.

[0029] A maskless exposure device according to an embodiment comprises: a management information processing device that transmits image data to be exposed to a controller via a high-speed communication method and transmits various pre-set exposure-related parameters to a trigger generation device; a controller that converts the image data received from the management information processing device into an output image and transmits it to a DMD control unit; a stage on which a substrate to be exposed is mounted, which moves in a direction opposite to the direction to be exposed, and which generates an encoder signal according to the movement and transmits it to a trigger generation device; an image capturing unit that captures an image of the substrate and transmits it to the management information processing device; a trigger generation device that calculates the number of pulses of the encoder signal received from the stage and generates a trigger signal and transmits it to the DMD control unit whenever the number of pulses of the encoder signal corresponding to the position to be exposed is calculated; a DMD control unit that adjusts the angle of a specific micromirror of the DMD based on the output image received from the controller and the trigger signal received from the trigger generation device; and a light source that emits light for exposure. The above-mentioned DMD control unit controls the angle of a specific micro-mirror to reflect light from the light source and expose it to a desired location on the substrate; and the above-mentioned optical system refracts the light reflected from the above-mentioned DMD to expose it to a desired location on the substrate; and the above-mentioned management information processing device may include: an image processing unit that calculates Roll (rotation), Yaw (left-right tilt), and Pitch (front-back tilt) errors of the substrate based on the image received from the image capturing unit; and an image correction unit that corrects the image to be exposed based on the Roll (rotation), Yaw (left-right tilt), and Pitch (front-back tilt) errors of the substrate calculated by the image processing unit to generate a corrected image.

[0030] Hereinafter, various embodiments of the present disclosure are described in conjunction with the accompanying drawings. As various embodiments of the present disclosure may be subject to various modifications and may have various forms, specific embodiments are illustrated in the drawings and described in detail. However, this is not intended to limit the various embodiments of the present disclosure to specific forms, and it should be understood that they include all modifications and / or equivalents and substitutions that fall within the spirit and scope of the various embodiments of the present disclosure. In relation to the description of the drawings, similar reference numerals have been used for similar components.

[0031] In various embodiments of the present disclosure, terms such as “comprising” or “having” are intended to indicate the existence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0032] In various embodiments of the present disclosure, expressions such as “or” include any and all combinations of the words listed together. For example, “A or B” may include A, may include B, or may include both A and B.

[0033] Expressions such as "first," "second," "first," or "second" used in various embodiments of the present disclosure may modify various components of the various embodiments, but do not limit such components. For example, such expressions do not limit the order and / or importance of such components and may be used to distinguish one component from another.

[0034] When it is mentioned that a component is "connected" or "joined" to another component, it should be understood that the component may be directly connected or joined to the other component, but that a new component may also exist between the component and the other component.

[0035] In the embodiments of the present disclosure, terms such as "module," "unit," "part," etc. are used to refer to a component that performs at least one function or operation, and such component may be implemented in hardware or software, or in a combination of hardware and software. Additionally, a plurality of "modules," "units," "parts," etc. may be integrated into at least one module or chip and implemented as at least one processor, except where each needs to be implemented in specific individual hardware.

[0036] Terms such as those defined in commonly used dictionaries should be interpreted as having meanings consistent with their meanings in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in the various embodiments of the present disclosure.

[0037] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the attached drawings.

[0038] FIG. 1 is a configuration diagram of a maskless exposure device (100) according to an embodiment of the present disclosure. Referring to FIG. 1, the maskless exposure device (100) according to an embodiment of the present disclosure includes a management information processing device (10), a controller (110), a stage (170), an image capturing unit (180), a trigger generating device (190), a DMD control unit (120), a light source (140), a DMD (Digital Micromirror Device) (130), and an optical system (150).

[0039] The management information processing device (10) transmits image data to be exposed to the controller (110) via a high-speed communication method and transmits various exposure-related parameters set by the operator to the trigger generation device (200). The management information processing device (10) may be a type of computing device or a combination thereof, comprising at least one memory and at least one CPU (Central Processor Unit).

[0040] The controller (110) converts the image data received from the management information processing device (10) into an output image and transmits it to the DMD control unit (120).

[0041] The stage (170) can mount a substrate (160) to be exposed, moves in the opposite direction to the direction of exposure, and generates an encoder signal according to the movement and transmits it to a trigger generating device (190). The movement direction of the stage (170) is the y-axis direction, and generally, the stage (170) generates an encoder signal (pulse) every time it moves 0.1 µm along the y-axis. That is, if the stage (170) moves 100 mm, it generates 1,000,000 encoder signals cumulatively. However, this is just one example, and the movement distance of the stage (170) generating the encoder signal can be set differently.

[0042] The image capturing unit (180) captures an image of the substrate (160) mounted on the stage (170) and transmits it to the management information processing device (10). The image capturing unit (180) may be installed on the stage (170) and may be a type of camera capable of capturing images.

[0043] The trigger generating device (190) calculates the number of pulses of the encoder signal received from the stage (170) and, when the number of pulses of the encoder signal corresponding to the position to be exposed is calculated, generates a trigger signal and transmits it to the DMD control unit (120).

[0044] The DMD control unit (120) adjusts the angle of a specific micro-mirror of the DMD (130) by means of an output image received from the controller (110) and a trigger signal received from the trigger generating device (190).

[0045] DMD (130) is a device that displays images by controlling the reflection of light through mirrors with a size of 16 microns embedded on a silicon wafer at intervals of 1 micron. This technology is based on a small microchip called a Mirror-Device, which has hundreds of thousands of ultra-small aluminum mirrors placed on top of it. The basic principle of DMD is that these ultra-small mirrors change their positions according to the video signal, and when a source shines light on the surface of the aluminum mirrors, the mirrors collect the light through a lens and scan the video image.

[0046] The light source (140) emits light for exposure, and generally uses LEDs, lasers, etc. The DMD (130) adjusts the angle of a specific micro-mirror from the DMD control unit (120) to reflect the light from the light source (140) and expose it to a desired location on the substrate (160). The DMD is composed of several micro-mirrors arranged in an array form.

[0047] The optical system (150) functions to refract the light so that the light reflected from the DMD (130) can be exposed to a desired location on the substrate.

[0048] FIG. 2 is a configuration diagram of a management information processing device (10) of a maskless exposure device (100) according to an embodiment of the present disclosure. Referring to FIG. 2, the management information processing device (10) may include an image processing unit (12) and an image correction unit (14).

[0049] The image processing unit (12) can calculate the Roll (rotation), Yaw (left-right tilt), and Pitch (front-back tilt) errors of the substrate based on the image received from the image capturing unit (180), taking into account the position of the image capturing unit (180) and the position of the substrate. A plurality of marks may be inscribed on the substrate, and the Roll (rotation), Yaw (left-right tilt), and Pitch (front-back tilt) errors of the substrate can be calculated by taking into account the length between these plurality of marks.

[0050] The image correction unit (14) can generate a corrected image by correcting the image to be exposed based on the Roll (rotation), Yaw (left-right tilt), and Pitch (front-back tilt) errors of the substrate calculated by the image processing unit (12). Here, the corrected image may be a pre-distorted image to ensure accurate exposure by taking into account the Roll (rotation), Yaw (left-right tilt), and Pitch (front-back tilt) errors of the substrate.

[0051] In an embodiment, the image processing unit (12) extracts reference markers or feature points on a substrate from an image, calculates a position error between the actual positions of the extracted feature points and the reference positions, calculates Roll (rotation), Yaw (left-right tilt), and Pitch (front-back tilt) information of the substrate based on the position error, and corrects the position of the substrate based on the calculated Roll, Yaw, and Pitch information.

[0052] The image processing unit according to the embodiment processes an image of a substrate input from an image capturing unit to extract reference markers or feature points formed on the substrate, and calculates the actual position of the substrate based on the coordinates of the extracted feature points on the image. Subsequently, the image processing unit calculates the position error of the substrate by calculating the difference between the actual position and a previously stored reference position. The position error may include not only translational movement in the X-axis and Y-axis directions, but also attitude changes such as rotation (Roll), left-right tilt (Yaw), and front-back tilt (Pitch) of the substrate.

[0053] To this end, the image processing unit (12) analyzes the relative position, angle, and spacing between multiple feature points and quantitatively calculates attitude error information in three-dimensional space through matrix transformation or the least squares method. The calculated Roll, Yaw, and Pitch values ​​are transmitted to the control unit or correction algorithm module, and then, by controlling the stage or position control device that supports the substrate, the actual attitude of the substrate can be precisely corrected to match the alignment standard.

[0054] Through such a configuration, the maskless exposure device according to the present invention can improve overlay accuracy in a patterning process requiring high-precision alignment, and furthermore, can realize automated alignment correction even for curved substrates or irregular materials.

[0055] FIG. 3 is a diagram illustrating the process of an image processing unit according to an embodiment of the present invention recognizing feature points on a substrate and calculating position error and attitude error (Roll, Yaw, Pitch). Referring to FIG. 3, an image processing unit (12) according to an embodiment of the present invention extracts reference markers or feature points (P1~P9) on a substrate (100) from an image input from an image capturing unit. The substrate (100) includes a plurality of reference markers arranged in a certain pattern as shown in the drawing, and the ideal position of each marker is predefined according to a reference coordinate system (X, Y reference axes). However, in an actual captured image, the positions of the feature points deviate from the reference positions due to the influence of rotation, tilting, and positional movement of the substrate. The image processing unit (12) detects the coordinates of each feature point (P1~P9) on the image and performs the following procedure by comparing them with the reference coordinate system. In the embodiment, during the position error calculation (Translation Error) process, the degree to which the center of the substrate deviates from the reference position is calculated as ΔX and ΔY. Subsequently, an orientation error is calculated. In the embodiment, orientation errors such as roll, yaw, and pitch are calculated based on the distance and angle between multiple feature points. For example, yaw and pitch errors can be quantified through the difference between the reference distance and the actual distance between two reference markers shown in the drawing, as well as the direction of inclination. Subsequently, alignment vectors are generated and correction values ​​are derived. In FIG. 3, the arrows connected to each feature point represent movement vectors from the reference position to the actual position, and the alignment state of the entire substrate is mathematically modeled by comprehensively analyzing these vectors.

[0056] In the embodiment, when the calculated Roll, Yaw, and Pitch information is transmitted to the control unit, the orientation of the stage supporting the substrate is automatically corrected according to the corresponding error, thereby enabling a high-precision exposure process. Through this, even minute errors in the substrate can be quantitatively identified via precise position and orientation analysis using multiple reference markers, and the alignment accuracy and yield of the exposure process can be improved through automatic correction. In particular, this can be applied as a core technology for preventing error accumulation in maskless exposure systems.

[0057] Additionally, the image processing unit (12) corrects the Roll, Yaw, and Pitch of the substrate by correcting the position and orientation of the stage supporting the substrate. The image processing unit (12) recognizes reference markers or feature points from the image of the substrate received from the image capturing unit and calculates the position and orientation errors of the substrate based on this. The calculated position errors include not only the planar movement of the substrate (X, Y directions) but also three-dimensional orientation errors such as rotation (Roll), left-right tilting (Yaw), and front-back tilting (Pitch) of the substrate.

[0058] At this time, the image processing unit (12) uses the error information to correct and control the position and orientation of the stage (not shown) supporting the substrate, thereby ensuring that the substrate is precisely aligned with the reference position and orientation.

[0059] More specifically, the image processing unit (12) calculates a correction amount corresponding to Roll, Yaw, and Pitch values ​​and transmits this correction amount to the driving system of the stage (e.g., a multi-axis precision actuator or a tilt correction mechanism, etc.) so that the orientation of the substrate can be precisely adjusted based on 6 degrees of freedom (6-DOF).

[0060] This correction control process can be performed in real time, and accordingly, fine alignment errors of the substrate can be effectively eliminated before the exposure or patterning process.

[0061] The image processing unit (12) estimates the orientation error of the substrate using matrix operations or the least squares method based on the relative distance and angle between reference markers. The image processing unit (12) detects reference markers on the substrate from an image received from an image capturing unit and extracts the coordinates of each reference marker on the image. Subsequently, it calculates the orientation error of the substrate based on the relative distance and angle information between the extracted multiple reference markers. The orientation error includes the rotation (Roll), left-right tilt (Yaw), and front-back tilt (Pitch) of the substrate, and the image processing unit (12) applies mathematical modeling to quantitatively estimate this.

[0062] To this end, the image processing unit (12) constructs relative position data between reference markers in a vector form, and then applies a matrix transformation or the least squares method based on the difference from the ideal reference position to estimate the 3D attitude change amount of the entire substrate. For example, if the reference markers have a square or grid arrangement, the mapping relationship between the ideal position and the actual position is modeled as a 2D or 3D linear transformation matrix, and the optimal Roll, Yaw, and Pitch values ​​can be calculated through error minimization based on this. This method has the advantage of enabling robust correction against noise or recognition errors of some markers by estimating the overall attitude error by averaging it rather than local errors.

[0063] The following describes the process of mathematically modeling the orientation errors (Roll, Pitch, Yaw) of a substrate using a rotation matrix. The alignment error of a substrate may include not only simple two-dimensional planar movement but also orientation changes (Roll, Pitch, Yaw) in three-dimensional space. In the embodiments of the present invention, precise position and orientation correction are made possible by mathematically modeling these orientation errors based on a rotation matrix. The rotation error of the substrate can be expressed as individual rotation matrices based on three axes as follows.

[0064] Yaw rotation (Z-axis rotation)

[0065] The rotation matrix when the substrate is rotated around the vertical axis (Z-axis) is given by Equation 1.

[0066] Mathematical formula 1

[0067]

[0068] Pitch rotation (X-axis rotation)

[0069] The rotation matrix when the substrate is tilted forward and backward around the X-axis, which is one of the horizontal axes, is given by Equation 2.

[0070] Mathematical formula 2

[0071]

[0072]

[0073] Roll rotation (Y-axis rotation)

[0074] The rotation matrix when the substrate is rolled around the Y-axis is given by Equation 3.

[0075] Mathematical formula 3

[0076]

[0077] The image processing unit (12) according to the embodiment analyzes the relative position between reference markers on the substrate, estimates the rotation amounts θy, θp, and θr for each axis, and based on this, constructs a total rotation matrix R for overall posture correction as shown in Equation 4.

[0078] Mathematical formula 4

[0079]

[0080] The above-mentioned total rotation matrix R reflects the change in orientation in the three-dimensional space where the substrate is actually placed, and by using this to correct the orientation of the stage, the substrate can be precisely aligned with the reference coordinate system.

[0081] Additionally, the image processing unit (12) detects a reference marker after performing a pre-processing process on the image that includes at least one of filtering, binarization, edge detection, or corner detection. The image processing unit (12) according to the embodiment performs a pre-processing process to detect a reference marker or a feature point on an image of a substrate input from an image capturing unit.

[0082] The above preprocessing process is essential for improving image quality and increasing the accuracy of feature extraction, and specifically, it may include at least one procedure among filtering, binarization, edge detection, and corner detection. Filtering: Performs spatial filtering, such as Gaussian filters and Median filters, to remove noise, thereby inducing image smoothing and improving detection accuracy. Binarization binarizes the pixel values ​​of the image to distinguish pixels as black and white based on a specific threshold, thereby clearly distinguishing the reference marker from the background. This is particularly effective when the marker has a certain contrast. Edge detection uses algorithms such as Sobel and Canny to detect the outlines (edges) of objects within the image and identify the boundaries of the marker. This is advantageous for recognizing marker shapes such as circles and squares. Corner detection uses algorithms such as Harris and Shi-Tomasi to detect the vertices of the marker or points where structural features are strongly apparent, thereby enabling the precise extraction of the marker location.

[0083] After performing the above preprocessing process, the image processing unit (12) detects the position of a reference marker from the preprocessed image and calculates the error with respect to the reference position based thereon, thereby allowing for precise analysis of the position and orientation of the substrate.

[0084] In the embodiment, the reference position includes a pre-set alignment reference coordinate system based on the design drawing of the substrate or a master coordinate system. In the embodiment, the image processing unit (12) calculates the actual position of a reference marker or feature point on the substrate and then calculates the position and orientation error through comparison with the corresponding reference position. Here, the reference position includes a pre-defined alignment reference coordinate system based on the layout design file of the substrate or a master coordinate system. More specifically, the reference position includes the ideal positions of reference markers defined on design information (CAD, GDS, etc.) used in the substrate manufacturing process or the photolithography process, and these may be stored in the form of absolute coordinates or relative coordinates according to the master coordinate system.

[0085] The image processing unit (12) can quantitatively analyze the translational movement and attitude error (Roll, Yaw, Pitch) of the substrate by calculating the difference value (Δx, Δy, Δθ, etc.) between the actual position of the marker recognized in real time and the reference position by referring to the reference coordinate system. In the embodiment, the error analysis method based on the reference coordinate system has the advantage of ensuring consistency and reliability in the repetitive alignment process because the reference position is clearly defined, and can be flexibly applied to various substrate shapes or pattern structures.

[0086] Additionally, the position error is calculated based on the average value or weighted average value calculated from a plurality of reference markers on the substrate. The image processing unit (12) extracts position information from each of the plurality of reference markers or feature points placed on the substrate and calculates the position error of the substrate based on the difference between the actual position of these markers and the reference position.

[0087] In this case, the position error is calculated not by simply using a single error value from individual markers, but based on the average or weighted average of the error values ​​derived from multiple reference markers.

[0088] More specifically, the representative position error of the entire substrate can be quantified by integrating the position deviations (Δx, Δy) in the X and Y directions measured at each reference marker using an average or weighted average method. In this case, the weighted average value can be calculated by assigning different weights according to the reliability, recognition quality, or position on the substrate of each marker, and can be expressed by Equation 5.

[0089] Mathematical formula 5

[0090]

[0091] In Equation 5, wi is the weight assigned to reference marker i, and Δxi and Δyi represent the positional error of the corresponding marker. This method can minimize the impact of local measurement errors or noise and is advantageous for improving the positional alignment reliability of the entire substrate.

[0092] Additionally, the image processing unit (12) performs position correction in a 3D coordinate system when the substrate includes a curved surface or an irregular shape. In an embodiment, the image processing unit (12) recognizes a plurality of reference markers or feature points on the substrate and calculates position and orientation errors based thereon. In particular, the position correction operation is configured to be performed in a 3D coordinate system so that precise alignment correction is possible even when the substrate includes a curved surface or an irregular shape rather than a flat surface.

[0093] More specifically, the image processing unit (12) converts the spatial coordinate information of the feature points extracted from the image into a three-dimensional form and then analyzes the difference from the ideal position defined in the reference coordinate system to quantitatively calculate a position error based on 6 degrees of freedom, including not only translational movement in the X, Y, and Z axis directions but also attitude errors such as Roll, Yaw, and Pitch.

[0094] Subsequently, based on the calculated three-dimensional position and orientation errors, control commands for the stage or drive system supporting the substrate are generated, and the position and orientation are automatically corrected so that the actual curved substrate or irregular substrate is aligned with the reference coordinate system.

[0095] Unlike 2D correction based on a flat substrate, this method has the advantage of enabling precise alignment even for complex shapes with Z-axis height variations or curvature, and can be effectively applied to patterning processes for flexible substrates, substrates for wearable devices, or curved sensor substrates.

[0096] Hereinafter, we will look at FIG. 4. The position correction method of the substrate shown in FIG. 4 can be performed by a maskless exposure device including an image processing unit (12).

[0097] Meanwhile, FIG. 4 is merely illustrative, and the concept of the present invention is not to be interpreted as being limited to that shown in FIG. 4. For example, each step may be configured in a different order than that shown in FIG. 4, at least one of the steps shown in FIG. 4 may not be performed, or one or more steps not shown in FIG. 4 may be additionally performed.

[0098] Below, the method for correcting the position of a substrate will be explained in turn. Since the operation (function) of the method for correcting the position of a substrate according to the embodiment is essentially the same as the function of the substrate position correction system, descriptions that overlap with FIGS. 1 to 3 will be omitted.

[0099] FIG. 4 is a diagram illustrating a substrate position correction process according to an embodiment. In step S110, reference markers or feature points on the substrate are extracted from an image, and in step S120, a position error between the actual positions of the extracted feature points and the reference positions is calculated. In step S130, Roll (rotation), Yaw (left-right tilt), and Pitch (front-back tilt) information of the substrate is calculated based on the position error. In step S140, the position of the substrate is corrected based on the calculated Roll, Yaw, and Pitch information.

[0100] The maskless exposure apparatus according to the embodiment enables high-resolution and high-precision patterning by detecting minute alignment errors of a substrate through an image processing function and correcting them in real time. Accordingly, the overlay accuracy in the exposure process is improved, thereby enhancing the overall process yield and productivity.

[0101] In addition, in the embodiment, attitude information such as Roll, Yaw, and Pitch of the substrate is automatically measured and reflected in the exposure process in real time, thereby minimizing errors even in processes requiring precision in the nanometer range. This enables increased exposure precision for complex three-dimensional structures or irregular substrates.

[0102] In addition, the embodiment uses a maskless exposure method, which reduces mask manufacturing and management costs and improves production flexibility by enabling rapid pattern switching even when changing products.

[0103] In addition, unlike conventional manual or semi-automatic alignment methods, the image processing-based automatic position correction in the embodiment minimizes operator intervention and enables a fully automated process flow, thereby significantly increasing the efficiency and repeatability of the entire process.

[0104] Meanwhile, the methods according to the various embodiments of the present invention described above can be implemented in the form of an application or software program that can be installed on an existing electronic device.

[0105] In addition, the whole or part of the method may be composed of multiple software function modules and implemented on an operating system (OS). Alternatively, each step may be composed of a single software function module, or each step may be combined to form a single software function module and implemented on an operating system. Therefore, even if all of the embodiments of the present disclosure are not implemented as a single software function module, if multiple software function modules implement each step of the present disclosure and multiple software function modules are implemented on a single operating system, it can be understood that the method of the present disclosure has been implemented.

[0106] In addition, the methods according to the various embodiments of the present invention described above can be implemented solely through software upgrades or hardware upgrades of existing electronic devices. Furthermore, the various embodiments of the present invention described above can also be performed through an embedded server equipped in an electronic device or an external server of the electronic device.

[0107] Meanwhile, according to one embodiment of the present invention, the various embodiments described above may be implemented as software comprising instructions stored on a computer-readable recording medium using software, hardware, or a combination thereof. In some cases, the embodiments described herein may be implemented as the processor itself. According to the software implementation, embodiments such as the procedures and functions described herein may be implemented as separate software modules. Each of the software modules may perform one or more functions and operations described herein.

[0108] Meanwhile, a computer or a similar device may include a device according to the disclosed embodiments, which is capable of calling instructions stored from a storage medium and operating according to the called instructions. When said instructions are executed by a processor, the processor may perform a function corresponding to said instructions directly or by using other components under the control of said processor. The instructions may include code generated or executed by a compiler or an interpreter.

[0109] A computer-readable recording medium may be provided in the form of a non-transitory computer-readable recording medium. Here, "non-transitory" simply means that the storage medium does not contain a signal and is tangible, without distinguishing whether data is stored semi-permanently or temporarily on the storage medium. In this context, a non-transitory computer-readable medium refers to a medium that stores data semi-permanently and is readable by a device, rather than a medium that stores data for a short moment, such as registers, caches, or memory. Specific examples of non-transitory computer-readable media may include CDs, DVDs, hard disks, Blu-ray discs, USBs, memory cards, and ROMs.

[0110] As described above, exemplary embodiments have been disclosed in the drawings and specification. Although specific terms have been used to describe the embodiments in this specification, they are used only for the purpose of explaining the technical concept of this disclosure and are not intended to limit the meaning or the scope of this disclosure as defined in the claims. Therefore, those skilled in the art will understand that various modifications and equivalent alternative embodiments are possible therefrom. Accordingly, the true technical scope of protection of this disclosure should be determined by the technical concept of the appended claims.

[0111] The maskless exposure apparatus according to the embodiment enables high-resolution and high-precision patterning by detecting minute alignment errors of a substrate through an image processing function and correcting them in real time. Accordingly, the overlay accuracy in the exposure process is improved, thereby enhancing the overall process yield and productivity.

[0112] In addition, in the embodiment, attitude information such as Roll, Yaw, and Pitch of the substrate is automatically measured and reflected in the exposure process in real time, thereby minimizing errors even in processes requiring precision in the nanometer range. This enables increased exposure precision for complex three-dimensional structures or irregular substrates.

[0113] In addition, the embodiment uses a maskless exposure method, which reduces mask manufacturing and management costs and improves production flexibility by enabling rapid pattern switching even when changing products.

[0114] In addition, unlike conventional manual or semi-automatic alignment methods, the image processing-based automatic position correction in the embodiment minimizes operator intervention and enables a fully automated process flow, thereby significantly increasing the efficiency and repeatability of the entire process.

[0115] 100: Maskless exposure device

Claims

1. A management information processing device that receives and stores image data to be exposed; A controller that receives image data from the above-mentioned management information processing device and converts the image data into an output image; A stage on which a substrate to be exposed is mounted, which moves in the opposite direction to the direction of exposure, and which generates an encoder signal according to the movement; An image capturing unit that captures an image of the above substrate and transmits it to the management information processing device; A trigger generating device that receives the encoder signal from the above stage, calculates the cumulative number of pulses of the received encoder signal, and generates a trigger signal when the cumulative number of pulses of the encoder signal corresponding to the position to be exposed is reached; A DMD control unit that receives the output image from the controller and generates a DMD control signal when it receives the trigger signal from the trigger generating device based on the output image; A light source that emits light for exposure; A DMD that receives a DMD control signal from the above DMD control unit and adjusts the angle of a specific micro-mirror based on the above DMD control signal to reflect light from the light source and expose it to a desired location on the substrate; and A maskless exposure apparatus comprising: an optical system for refracting light so as to expose light reflected from the DMD to a desired location on the substrate; The above-mentioned management information processing device is, An image processing unit that calculates Roll (rotation), Yaw (left-right tilt), and Pitch (front-back tilt) errors of the substrate based on the image received from the image capturing unit; and An image correction unit that generates a corrected image by correcting the image to be exposed based on the Roll (rotation), Yaw (left-right tilt), and Pitch (front-back tilt) errors of the substrate calculated by the image processing unit; comprising Maskless exposure device.

2. In paragraph 1, the image processing unit Extracting reference markers or feature points on a substrate from an image, calculating the position error between the actual positions of the extracted feature points and the reference positions, calculating Roll (rotation), Yaw (left-right tilt), and Pitch (forward-backward tilt) information of the substrate based on the position error, and correcting the position of the substrate based on the calculated Roll, Yaw, and Pitch information. Maskless exposure device.

3. In paragraph 2, the image processing unit Correcting the Roll, Yaw, and Pitch of a substrate by correcting the position and orientation of a stage supporting the substrate, Maskless exposure device.

4. In paragraph 2, the image processing unit Estimating the substrate attitude error through matrix operations or the least squares method using the relative distance and angle between reference markers, Maskless exposure device.

5. In paragraph 2, the image processing unit A method for detecting reference markers after performing a preprocessing process on an image that includes at least one of filtering, binarization, edge detection, or corner detection. Maskless exposure device.

6. In Paragraph 2, the above reference position is, A pre-set alignment reference coordinate system based on the design drawing of the substrate or a master coordinate system, including Maskless exposure device.

7. In paragraph 2, the above position error is, Calculated based on the average value or weighted average value calculated from multiple reference markers on the substrate, Maskless exposure device.

8. In paragraph 2, the image processing unit If the substrate includes a curved or irregular shape, the position correction is performed in a three-dimensional coordinate system. Maskless exposure device.

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