• International Journal of Contents
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• v.13 no.2
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• pp.57-65
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• 2017

Recently, due to the significance of Industry 4.0, the manufacturing industry is developing globally. Conventionally, the manufacturing industry generates a large volume of data that is often related to process, line and products. In this paper, we analyzed causes of defective products in the manufacturing process using the decision tree technique, that is a well-known technique used in data mining. We used data collected from the domestic manufacturing industry that includes Manufacturing Execution System (MES), Point of Production (POP), equipment data accumulated directly in equipment, in-process/external air-conditioning sensors and static electricity. We propose to implement a model using C4.5 decision tree algorithm. Specifically, the proposed decision tree model is modeled based on components of a specific part. We propose to identify the state of products, where the defect occurred and compare it with the generated decision tree model to determine the cause of the defect.

• Tunnel and Underground Space
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• v.28 no.2
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• pp.125-141
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• 2018

For a long-term mine development plan, the determination and design of mine tunnel size are very important because it is the basis of plans for equipment, transportation and operation. The ${\bigcirc}{\bigcirc}$ mine has had a difficulty in changing the mining plan due to the design of the tunnels with an emphasis on productivity improvement, and much effort was needed to maintain the mine tunnel. In this study, we designed the mine tunnel with optimized tunnel span considering the mechanical properties of rockmass and established the support plan. To do this, the estimation of the mechanical parameters(Swelling pressure, deformation coefficient and earth coefficient), field investigations and various analyses were carried out. As a result, it was necessary to consider the downsizing of the tunnel section in order to maintain the tunnel stability and dimension by using the roof bolt and analyzed that various functional constructions of the support material and method would be required to maintain the current tunnel size.

• Journal of Ocean Engineering and Technology
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• v.30 no.6
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• pp.526-534
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• 2016

This study had the goal of designing onboard structures for a pre-pilot mining test (PPMT), which is required for the commercialization of the deep-sea mining industry. This PPMT is planned to validate the performance of a hydraulic lifting system and verify the concept of operating through a moon-pool in the east sea, Korea. All of the onboard equipment and facility were designed by KRISO. Because the test was performed at the first development, it is difficult to determine what risk will occur in the facility. Therefore, risk-based design is required in the facility for the PPMT, which includes the facility layout, failure mode and effect analysis (FMEA), and risk reduction plan. All of the expected performances of the lifting system itself and the onboard facilities were qualitatively validated using the risk-based design.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.234-241
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• 2021

By recognizing the importance of demand forecasting, the military is conducting many studies to improve the prediction accuracy for repair parts. Demand forecasting for repair parts is becoming a very important factor in budgeting and equipment availability. On the other hand, the demand for intermittent repair parts that have not constant sizes and intervals with the time series model currently used in the military is difficult to predict. This paper proposes a method to improve the prediction accuracy for intermittent repair parts of the Patriot. The authors collected intermittent repair parts data by classifying the demand types of 701 repair parts from 2013 to 2019. The temperature and operating time identified as external factors that can affect the failure were selected as input variables. The prediction accuracy was measured using both time series models and data mining models. As a result, the prediction accuracy of the data mining models was higher than that of the time series models, and the multilayer perceptron model showed the best performance.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.460-468
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• 2021

A TBM is an equipment that excavates a tunnel with a full face by rotating a circular cutter head and its advantages are fast excavation rate and safe construction. A TBM, which is primarily used for tunnel excavation on civil construction sites, is easily adaptable to information and communication technology. Research related to unmanned and automated technology is being actively pursued. TBM applications for mining and energy resource development in other countries were investigated in this study. The difference of TBM applications between the mining and energy resource development and civil construction sites was examined. Technical factors such as geological conditions, depth, site access, TBM launching, alignment and inclination, TBM size, and others that should be considered when choosing a TBM were investigated. Finally, the advantages and disadvantages of TBM application in mines and the technical requirements for TBM for successful mine application are summarized.

• Geomechanics and Engineering
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• v.27 no.6
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• pp.537-550
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• 2021

There are various technical problems need to be solved in the construction process of pre-setting an isolation wall into a double lane in the outburst prone mine. This study presents a methodology that pre-setting an isolation wall into a double lane without a coal pillar. This requires the excavation of two small section roadways to dig a wide section roadway, followed by construction of the separation wall. During this process the connecting lane is reserved. In order to ensure the stability of the separation wall, the required bearing capacity of the isolation wall is 4.66 MN/m and the deformation of the isolation wall is approximately 25 cm. To reduce the difficulty of implementing support the roadway is driven by 5 m/d. After the construction of the separation wall, the left side coal wall is brushed 1.5 m to make the width of the gas roadway reach 2.5 m and the roadway support utilizes anchor rod, ladder beam, anchor cable beam and net configuration. During construction, the concrete pump and removable self-propelled hydraulic wall mold are used to pump and pour the concrete of the isolation wall. In the process of mining, the stress distribution of coal body and isolation wall is detected and measured on site. The results demonstrate that the deformation of the surrounding rock of roadway and separation of roof in the roadway is small. The stress of the bolt and anchor cable is within equipment tolerance validating their selection. The roadway is well supported and the intended goal is achieved. The methodology can be used for reference for similar mine gas control.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.635-642
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• 2014

The space charge behaviors of oil-paper insulation affect the stability and security of oil-filled converter transformers of traditional and new energies. This paper presents the results of the electrical aging of oil-impregnated paper under AC-DC combined voltages by the pulsed electro-acoustic technique. Data mining and feature extractions were performed on the influence of electrical aging on charge dynamics based on the experiment results in the first stage. Characteristic parameters such as total charge injection and apparent charge mobility were calculated. The influences of electrical aging on the trap energy distribution of an oil-paper insulation system were analyzed and discussed. Longer electrical aging time would increase the depth and energy density of charge trap, which decelerates the apparent charge mobility and increases the probability of hot electron formation. This mechanism would accelerate damage to the cellulose and the formation of discharge channels, enhance the acceleration of the electric field distortion, and shorten insulation lifetime under AC-DC combined voltages.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.172-174
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• 2021

In the existing industry, maintenance was carried out in the form of preventive maintenance such as occurrence of unnecessary idle time due to limited monitoring and maintenance. However, with the advent of the Fourth Industrial Revolution, real-time monitoring is possible in many industries including mining, manufacturing, oil and gas, and commercial agriculture, and it is desired to minimize idle time due to maintenance. In particular, there is a growing interest in predictive maintenance that can reduce costs and maximize operational efficiency by predicting and maintaining a failure before equipment and equipment fail. In this study, we look at the predictive maintenance technology that can verify the abnormal condition of the equipment of the smart factory in advance and monitor the abnormal condition in real time.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.2
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• pp.65-70
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• 2015

In the PCB(Printed Circuit Board) manufacturing industry, the yield is an important management factor because it affects the product cost and quality significantly. In real situation, it is very hard to ensure a high yield in a manufacturing shop because products called chips are made through hundreds of nano-scale manufacturing processes. Therefore, in order to improve the yield, it is necessary to analyze main fault process and equipment that cause low PCB yield. This paper proposes a systematic approach to discover fault-causing processes and equipment by using a logistic regression and a stepwise variable selection procedure. We tested our approach with lot trace records of real work-site. A lot trace record consists of the equipment sequence that the lot passed through and the number of faults for each fault type in the lot. We demonstrated that the test results reflected the real situation of a PCB manufacturing line.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.161-166
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• 2021

Errors in the semiconductor process are generated by a change in the state of the equipment, and errors usually arise when the state of the equipment changes or when parts that make up the equipment have flaws. In this investigation, we anticipated that aging of the mass flow controller in the plasma enhanced chemical vapor deposition SiO2 thin film deposition method caused a minute flow rate shift. In seven cases, fourier transformation infrared film quality analysis of the deposited thin film was used to characterize normal and pathological processes. The plasma condition was monitored using optical emission spectrometry data as the flow rate changed during the procedure. Preprocessing was used to apply the collected OES data to the artificial immune system algorithm, which was then used to process diagnosis. Through comparisons between datasets, the learning algorithm compared classification accuracy and improved the method. It has been confirmed that data characterized as a normal process and abnormal processes with differing flow rates may be discriminated by themselves using the artificial immune system data mining method.