• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.35
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• pp.115-122
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• 1995

This paper is developed with software system for the construction of periodic maintenance. The system includes records of equipment, maintenance work, failure mode analysis and work standards of maintenability, inspection & repair to establish periodic maintenance system. And the software program is designed with user-oriented to analyze maintenance data and maintenance system of periodic interval times. Also machine operator can easily apply maintenance management system in production & manufacturing field. Visual Basic in the environment of Window system is used as computer program language for graphics and data base management in IBM PC.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.87-93
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• 2012

In this paper, we proposed a faulty pattern detection algorithm of TCP(Tape Carrier Package)/COF(Chip On Film), and implemented a real-time system for inspecting TCP/COF. Since TCP/COF has very high resolution having several micro meters, the human operator should visually inspect all the parts through microscope. In this work, we implement an inspection system to detect the faulty pattern, so the operator can visually inspect only the designated parts by the inspection system through the monitor. The proposed defects detection algorithm for TCP/COF packages is implemented by the pattern matching method based on subtracting the reference image from test image. To evaluate performance of the proposal system. we made various experiments according to type of CCD camera and light source as well as illumination projection method. From experimental results, it is confirmed that the proposed system makes it possible to detect effectively the defective TCP/COF film.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.5
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• pp.421-427
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• 2008

A robot crane truck is developed by the Bridge Inspection Robot Development Interface(BRIDI) for an automated and/or teleoperated bridge inspection. This crane truck looks similar to the conventional bucket crane, but is much smaller in size and light-weight. At the end of the telescoping boom which is 12m long, a robot platform is mounted which allows the operator to scan the bridge structure under the deck trough the camera. Boom vibration induced by wind and deck movement can cause serious problems in this scanning system. This paper presents a control system to mitigate such vibration of the robot boom. In the proposed control system, an actuator is installed at the end of the working boom. This control system is studied using a mathematical model analysis with LQ control algorithm and a scaled model test in the laboratory. The study indicates that the proposed system is efficient for the vibration control of the robot booms, thereby demonstrating its immediate applicability in the field.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.134-141
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• 2003

An industrial product is designed and fabricated, followed by the inspection process in order to check whether it is dimensionally tolerable or not. The machining process produces a part such as a mold or die, in which the three-dimensional coordinate might be measured by a CMM (Coordinate Measuring Machine) for assessment of its dimension. It is not ignorable, however, that a CMM measurement requires a lot of operating time and cost, which has led to many studies on the OMM system. The OMM system can be categorized into contact and non-contact types, and each of which has its own strengths and weaknesses. Non-contacting types generally utilize structured lights, sounds or magnetic fields. Though they show rather poor performance in positional accuracy, the measuring speed is faster than the contacting probes. This paper presents the development of an OMM system based on a non-contacting laser displacement sensing apparatus and CAD model. The system is composed of software modules of center-aligning and measuring, which has been operated and verified on a NC machining center on a shop floor.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.6
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• pp.88-95
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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 fur 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 geometrical relationship between PCB, cameras, and xy$\theta$ stage is derived, and analytical equations for alignment errors are also obtained. The unknown parameters including camera declining angles and etc. can be obtained by initialization process. Finally, the proposed algorithm is verified by experiments by using test bench.

• 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 Technology Engineers
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• v.8 no.6
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• pp.55-63
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• 1999

The acceleration of the performance of machine tools influences the development of the semi-conductor and optical technology as the development of NC and measurement technology. Because the measurement has been done to unload condition without considering of mechanical stiffness in the case of machining center as we measure the quasi-static error of machine tools on general study people who works on the spot has many problems on the data value. Also there are no satisfiable results until now in spite of many studys about this because the deflections of the table and the shaft supporting a workpiece influence, influence the accuracy of the table and shaft supporting a workpiece influence the accuracy of the workpiece. And there is doubt about the inspection method of measured error. In this paper Therefor we will help working more accurately on the spot by measuring analyzing displaying the defoec-tion of the table and support shaft when we load on the table and the support shaft of machining center using laser interfer-ometer. Also we try to settle new conception of the measurement method and more accurate grasp of the deflection tenden-cy by verifing the tendency of the error measured through the comparison of the simulated error measured through the comparison of the simulated error using ANSYS a common finite element analysis program which is able to measure heat deformation material deformation and error resulted from this study.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.80-88
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• 2017

Although hazard identification is one of the most important steps of safety management process, numerous hazards remain unidentified in the construction workplace due to the dynamic environment of the construction site and the lack of available resource for visual inspection. To this end, our previous study proposed the collective sensing approach for safety hazard identification and showed the feasibility of identifying hazards by capturing collective abnormalities in workers' walking patterns. However, workers generally performed different activities during the construction task in the workplace. Thereby, an additional process that can identify the worker's walking activity is necessary to utilize the proposed hazard identification approach in real world settings. In this context, this study investigated the feasibility of identifying walking activities during construction task using Wearable Inertial Measurement Units (WIMU) attached to the worker's ankle. This study simulated the indoor masonry work for data collection and investigated the classification performance with three different machine learning algorithms (i.e., Decision Tree, Neural Network, and Support Vector Machine). The analysis results showed the feasibility of identifying worker's activities including walking activity using an ankle-attached WIMU. Moreover, the finding of this study will help to enhance the performance of activity recognition and hazard identification in construction.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.121-142
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• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.

• Journal of Biosystems Engineering
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• v.32 no.3
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• pp.179-189
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• 2007

Most of the seeds of cucurbitaceous rootstock species used for grafting were mainly sown by hand. This study was carried out to develop an on-line discriminating algorithm of seed direction using machine vision and an automatic seeding system. The seeding system was composed of a supplying device, feeding device, machine vision system, reversing device, seeding device and system control section. Machine vision was composed of a color CCD camera, frame grabber, image inspection chamber, lighting and personal computer. The seed image was segmented into a region of seed part and background part using thresholding technique in which H value of HSI color coordinate system. A seed direction was discriminated by comparing position between the center of circumscribed rectangle to a seed and the center of seed image. It took about 49ms to identify and redirect seed. Line-up status of seed was good the more than 95% of a sowed seed. Seeding capacity of this system was shown to be 10,140 grains per hour, which is three times faster than that of a typical worker.