• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.596-599
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• 2004

The robotic $CO_2$ welding is a manufacturing process to produce high quality joints for metal and it could provide a capability of full automation to enhance productivity. Despite the widespread use in the various manufacturing industries, the full automation of the robotic $CO_2$ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this research, an attempt has been made to develop an intelligent algorithm to predict the weld geometry (top-bead width, top-bead height, back-bead width and back-bead height) as a function of key process parameters in the robotic $CO_2$welding. To achieve this above objective, Taguchi method was employed using five different process parameters (tip gap, gas flow rate, welding speed, arc current, welding voltage) as a guide for optimization of process parameters.

• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.19-30
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• 2004

Due to the inefficient operation of the existing logistic facilities, the complicated distribution structure, and closed utilization of logistic information are causing high logistic costs. The general improvement in the distribution structure and the expansion of the logistic facilities are needed for solving these problems. However, existing unit-scale forecast is not considering the loading and unloading characteristics of the trucks and the improvement of operation efficiency from the mechanization and automation of the loading and unloading works. The queuing theory based on the status quo of the cargo trucks to the cargo terminals is considered in this study. The optimal scale estimation method(OSCM) which the loading and unloading characteristics of the cargo trucks were taken into consideration was suggested. Also, the relationship between the optimal scale of the cargo terminal and the mechanization, automation, and informationization of the present loading and unloading system was investigated. As a result, it showed that the regularity of the truck arrival and service times had less influence on the scale of the cargo terminal, but the improvement of the loading and unloading speeds and the service rate of the trucks did more influence on it.

• Journal of the Society of Naval Architects of Korea
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• v.39 no.2
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• pp.34-44
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• 2002

Approximately 70 percent of shop's hull plate consists of three-dimensional curved shell. Concerning with the research on the automation of plate forming many studies have been carried out for the last decade. The purpose of this study is to develop the simulator of heating on the basis of the reasonable mechanical model representing a heating phenomenon. The beating experiment has been carried out with varying parameters influencing on the results of heating information at the kinematics analysis, simulatorestimate the shape of deformed plate that process along the processing information. When we get the initial shape and the object shape, we calculate the processing information first, using kinematics analysis. In a simulator we estimate deformed shape from the processing information. After this we compare deformed shape and object shape. If the error of deformed shape and object shape is in the proper limits, that information is determined the final processing information. Else we repeat the process changing variable.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.47-53
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• 2011

The detection process of defective tags in most of Korean domestic RFID manufacturing companies is treated by on-hand processing after the job of chip bonding, so it has been requested to reduce the time and cost for manufacturing of RFID tags. Therefore, in this paper, we implement the system to perform the detection of defective tags after the process of chip bonding, and so provide the basis of software to establish the foundation of automation system for the detection of defected RFID tags which is requested in the related Korean domestic industrial field. We have developed the system by using UML in modeling phase and JAVA in implementation phase to reduce the cost of development of program and make it easy to maintain. The developed system in this paper shows the very enhanced performance in processing speed and perfect detection rate of defective tags, comparing to the method of on-hand processing.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5D
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• pp.705-717
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• 2011

The number of horizontal tower cranes, major hoisting machineries for lifting approximately 50% of entire materials in construction projects, is rapidly increasing, but a number of accidents related to the tower cranes are being continuously occurred in construction sites as well. In particular, telescoping works in the horizontal tower cranes have showed the greatest safety concerns such as falls and collapses. It is due to the fact that tasks inserting a new mast in the space made after raising telescoping cage by fluid pressure and ascending it to the required height in the telescoping works include a series of dangerous factors in safety aspects, and might cause very serious and unexpected accidents in construction sites. The primary objective of this research is to propose two conceptual models for automating the telescoping work in horizontal tower crane and conduct their technical feasibility analyses. In this study, a design concept, a position control system using hydraulic cylinders is suggested as a better alternative for automating the telescoping work. Its potential safety improvement rate compared to the conventional method is also analyzed and presented in this study.

• Journal of Power Electronics
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• v.16 no.5
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• pp.1884-1893
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• 2016

The ride-through control of a doubly-fed induction generator (DFIG) for the voltage sags on wind farms utilizing crowbar circuits by which the rotor side converter (RSC) is disabled has being reported in many literatures. An analysis and calculation of the transient current when the RSC is switched off are of significance for carrying out the low voltage ride through (LVRT) of a DFIG. The mathematical derivation is highlighted in this paper. The zero-state and zero-input responses of the transient current in the frequency domain through a Laplace transformation are investigated, and the transient components in the time domain are achieved. With the characteristics worked out from the linear resolving without modeling simplification, the selection of the resistance in the linear crowbar circuit and the value conversion from a linear circuit to a nonlinear one is proposed to setup the attenuation rate. In terms of grid code requirements, the theoretical analysis for the time constant of the transient components attenuation insures the controllability when the excitation of the RSC is resumed and it guarantees the reserved time for the response of the reactive power compensation. Simulations are executed in MATLAB/SIMPOWER and experiments are carried out to validate the theoretical analysis. They indicate that the calculation method is effective for selection of the resistance in a crowbar circuit for LVRT operations.

• Journal of Surface Science and Engineering
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• v.42 no.1
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• pp.1-7
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• 2009

Resistive heating sources are widely used to prepare thin films by vapor deposition because they are cheap, and easy to install and handle in vacuum system. Graphite is one of materials used to make the resistive heating source, but until now only limited applications have been possible as it reacts easily with evaporating materials at high temperature. In this study, evaporation characteristics of aluminum have been investigated by using graphite boat thermally treated with BN powder. The employed graphite boat has been prepared by spray-coating BN power onto the cavity surface of the boat and thermal treatment with aluminum in vacuum at the temperature of more than $1400^{\circ}C$. The voltage-current characteristics as well as resistivity changes of the graphite boat have been investigated during aluminum evaporation according to the applied voltage and time. The evaporation aspect has been picturized during flash evaporation for 40 seconds based on the characterization results. The evaporation rate of the graphite boat has been compared with that of BN boat. The graphite boat showed some different characteristics compared with BN boat, in that the evaporation occurred at the last stage of flash evaporation. The film appearance according to the applied voltage has been compared, and also the reflectance of the resulting film has been investigated according to the film thickness. It has been found that the graphite boat thermally treated with BN powder can be used for aluminum evaporation without problem.

• Journal of the Korean Institute of Gas
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• v.2 no.3
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• pp.49-53
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• 1998

It takes quite a long time for an analyzer, such as gas chromatography, to measure a bulk property of a system, which prevents on-line measurements. Also, the cost of installation and maintenance is very high. Consequently, some other means is needed for on-line measurements of properties and the development of soft sensors based on process variables like temperature and pressure is of great interest. In the field of gas industry, the development of a soft sensor which makes indirect on-line measurements of gas compositions and flow rate, is in progress. In this paper, we proposed a hybrid inner model PLS which improved the prediction performance by taking into account the data structure, as an empirical modeling algorithm. When applied to a design of a soft sensor of a distillation tower, the hybrid inner model PLS showed better prediction performance than other methods.

• Journal of Information Technology Services
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• v.21 no.2
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• pp.97-107
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• 2022

Recently, interest in smart factories is increasing. Investments to improve intelligence/automation are also being made continuously in manufacturing plants. Facility automation based on sensor data collection is now essential. In addition, we are operating our factories based on data generated in all areas of production, including production management, facility operation, and quality management, and an integrated standard information system. When producing LCD polarizer products, it is most important to link trace information between data generated by individual production processes. All systems involved in production must ensure that there is no data loss and data integrity is ensured. The large-capacity data collected from individual systems is composed of key values linked to each other. A real-time quality analysis processing system based on connected integrated system data is required. In this study, large-capacity data collection, storage, integration and loss prevention methods were presented for optimization of LCD polarizer production. The identification Risk model of inspection products can be added, and the applicable product model is designed to be continuously expanded. A quality inspection and analysis system that maximizes the yield rate was designed by using the final inspection image of the product using big data technology. In the case of products that are predefined as analysable products, it is designed to be verified with the big data knn analysis model, and individual analysis results are continuously applied to the actual production site to operate in a virtuous cycle structure. Production Optimization was performed by applying it to the currently produced LCD polarizer production line.

• Journal of the Korea Safety Management & Science
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• v.25 no.4
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• pp.141-151
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• 2023

Recently, due to the expansion of the logistics industry, demand for logistics automation equipment is increasing. The modern logistics industry is a high-tech industry that combines various technologies. In general, as various technologies are grafted, the complexity of the system increases, and the occurrence rate of defects and failures also increases. As such, it is time for a predictive maintenance model specialized for logistics automation equipment. In this paper, in order to secure the operational safety and reliability of the parcel loading system, a predictive maintenance platform was implemented based on the Naive Bayes-LSTM(Long Short Term Memory) model. The predictive maintenance platform presented in this paper works by collecting data and receiving data based on a RabbitMQ, loading data in an InMemory method using a Redis, and managing snapshot DB in real time. Also, in this paper, as a verification of the Naive Bayes-LSTM predictive maintenance platform, the function of measuring the time for data collection/storage/processing and determining outliers/normal values was confirmed. The predictive maintenance platform can contribute to securing reliability and safety by identifying potential failures and defects that may occur in the operation of the parcel loading system in the future.