• Journal of the Korean Society for Precision Engineering
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• v.26 no.11
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• pp.77-84
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• 2009

Alignment error of the BGA lithography equipment is mainly caused by the dimensional change of the BGA panel which is generated during the manufacturing processes. To minimize the alignment error, 'mark alignment' algorithm in place of 'center alignment' algorithm was proposed and the optimal solution for the algorithm was derived by simple analytic form. The developed algorithm distributes evenly the alignment error over the whole panel which was evaluated by the numerical simulation. Finally, the developed algorithm was implemented to the controller of the lithography equipment and the alignment error was measured at the fiducial mark location. From the measurement, it is also concluded that the developed alignment algorithm be effective to reduce the maximum value of alignment error.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1233-1240
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• 2010

In the flat panel display and semiconductor industries, the visual alignment system is considered as a core technology which determines the productivity of a manufacturing line. It consists of the vision system to extract the centroids of alignment marks and the stage control system to compensate the alignment error. In this paper, we develop a Kalman filter algorithm to estimate the alignment mark postures and propose a coarse-fine alignment control method which utilizes both original fine images and reduced coarse ones in the visual feedback. The error compensation trajectory for the distributed joint servos of the alignment stage is generated in terms of the inverse kinematic solution for the misalignment in task space. In constructing the estimation algorithm, the equation of motion for the alignment marks is given by using the forward kinematics of alignment stage. Secondly, the measurements for the alignment mark centroids are obtained from the reduced images by applying the geometric template matching. As a result, the proposed Kalman filter based coarse-fine alignment control method enables a considerable reduction of alignment time.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.9
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• pp.909-915
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• 2009

This work is to develop a vision system for high precision alignment between upper and lower plates required at the imprinting process of the large LCD flat panel. We compose a gantry-stage that has highly repeated accuracy for high precision alignment and achieves analysis about thermal transformations of stage itself. Position error in the stage is corrected by feedback control from the analysis. This system can confirm alignment mark of upper and lower plates by using two cameras at a time for the alignment of two plates. Pattern matching that uses geometric feature is proposed to consider the recognition problem for alignment mark of two plates. It is algorithm to correct central point and angle for the alignment from the recognized mark of upper and lower plates based on the special characteristics. At the alignment process, revision for error position is performed through Look and Move techniques.

• Journal of the Semiconductor & Display Technology
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• v.6 no.1 s.18
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• pp.43-48
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• 2007

For exposure systems, very accurate alignment between the mask and the substrate is indispensable. In this paper, an automatic alignment system using machine vision for exposure systems is described. Machine vision algorithms are described in detail including extraction of an alignment mark's center position and camera calibration. Methods for extracting parameters for alignment are also presented with some compensation techniques to reduce alignment time. Our alignment system was implemented with a vision system and motion control stages. The performance of the alignment system has been extensively tested with satisfactory results. The performance evaluation shows alignment accuracy of lum within total alignment time of about $2{\sim}3$ seconds including stage moving time.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.4
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• pp.369-375
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• 2008

The kinematics and control problem of a visual alignment system is investigated, which plays a crucial role in the fabrication process of flat panel displays. The first solution is the inverse kinematics of a 4PPR parallel alignment mechanism. It determines the driving distance of each joint to compensate the misalignment between mask and panel. Second, an efficient vision algorithm for fast alignment mark recognition is suggested, where by extracting essential feature points to represent the geometry of a mark, the geometric template matching enables much faster object recognition comparing with the general template matching. Finally, the overall visual alignment process including the kinematic solution, vision algorithm, and joint control is implemented and experimental results are given.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.155-159
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• 2015

Light emitting devices (LEDs) are widely used in the liquid crystal display (LCD) industry, especially for LCD back light units. Therefore, much research has been performed to minimize manufacturing costs. However, the current process does not process LED chips from broken substrates even though the substrate is expensive sapphire wafer. This is because the broken substrates lose their alignment marks. After pre-processing, LED dies are glued onto blue tape to continue post-processing. If auxiliary alignment marks are stamped on the blue tape, post-processing can be performed using some of the LED dies from broken substrates. In this paper, a novel stamper module that can stamp the alignment mark on the blue tape is proposed, designed, and fabricated. In testing, the stamper was reliable even after a few hundred stamps. The module can position the stamp and apply the pattern effectively. By using this module, the LED industry can reduce manufacturing costs.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.260-265
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• 2015

This paper proposes a alignment system using edge feature. An alignment system obtains the position and orientation of printed circuit board(PCB) or liquid crystal display(LCD) panel through the fiducial marks. Thus, it is the indicator of the system performance how accurate we detect the positions of the fiducial marks in the target image. Edges have the geometrical characteristics such as positions, lengths, and shapes. These features are suitable for finding the marks and have the advantages of lighting variations, model occlusion, as well as variations in scale and angle. The performance of the proposed system is validated through the alignment experiment using an display panel alignment system included X, Y axis, and rotatable stage.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.6
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• pp.96-104
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• 2003

This paper presents the measurement and correction method of PCB alignment errors for PCB screen printer. Electronic equipment is getting smaller and yet must satisfy high performance standard. Therefore, there is a great demand for PCB with high density. However conventional PCB screen printer doesn't have enough accuracy to accommodate the demand for high-resolution circuit pattern and high-density mounting capacity of electronic chips. It is because the alignment errors of PCB occur when it is loaded to the screen printer. Therefore, this study focuses on the development of the system which is able to measure and correct alignment errors with high-accuracy. An automatic optical inspection part measures the PCB alignment errors using machine vision, and the high-accuracy 3-axis stage makes correction for these errors. This system used two CCD cameras to get images of two fiducial marks of PCB. The centers of fiducial marks are obtained by using moment, gradient method. The first method is calculating the centroid by using first moment of blob, and the latter method is calculating the center of the circle whose equation is obtained by curve-fitting the boundaries of fiducial mark. The operating system used to implement the whole set-up is carried in Window 98 (or NT) environment. Finally we implemented this system to PCB screen printer.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.3
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• pp.100-109
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• 2022

In this study, calibration technology that increases the alignment accuracy in large flexible flat panels was studied. For precise of calibration, a systematization of the calibration algorithm was established, and a calibration correction technique was studied to revise calibration errors. A coordinate systems of camera and UVW stage was established to get the global position of the mark, and equations for translational and rotational calibration were systematically derived based on geometrical analysis. Correction process for the calibration data was carried, and alignment experiments were performed sequentially in cases of the presence or absence of calibration-correction. Alignment results of both calibration correction and non-calibration correction showed accuracy performance less than 1㎛. On the other hand, the standard deviation in calibration-correction is smaller than non-calibration correction. Therefore, calibration correction showed improvement of the alignment repeatability.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.108-112
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• 2023

Precision manufacturing technology is rapidly developing due to the extreme miniaturization of semiconductor processes to comply with Moore's Law. Accurate and precise alignment, which is one of the key elements of the semiconductor pre-process and post-process, is very important in the semiconductor process. The center detection of wafer align marks plays a key role in improving yield by reducing defects and research on accurate detection methods for this is necessary. Methods for accurate alignment using traditional image sensors can cause problems due to changes in image brightness and noise. To solve this problem, engineers must go directly into the line and perform maintenance work. This paper emphasizes that the development of AI technology can provide innovative solutions in the semiconductor process as high-resolution image and image processing technology also develops. This study proposes a new wafer center detection method through variable thresholding. And this study introduces a method for detecting the center that is less sensitive to the brightness of LEDs by utilizing a high-performance object detection model such as YOLOv8 without relying on existing algorithms. Through this, we aim to enable precise wafer focus detection using artificial intelligence.