• Journal of Korean Society for Quality Management
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• v.21 no.2
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• pp.131-139
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• 1993

The newly proposed model of the future reliability results in earlier fault-fixes having a greater effect than the fault which make the greatest contribution to the overall failure rate tend to show themselves earlier, and so are fixed earlier. The suggested model allows a variety of reliability measures to be calculated. Predictions of total execution time(debugging time) is to achieve a target reliability. This model could also apply to computer-hardware reliability growth resulting from the elimination of design error and fault.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.13-24
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• 2015

Customer complaints handling helps organizations to retain existing customers and attract new customers, as well. As Voice of the Customer (VOC) is one of the main sources of customer complaints, many organizations utilize VOC to enhance customer satisfaction. Effective management of VOC has been proved as one of the best ways to maintain organization's brand image and reputation. In spite of its importance, little has been reported on the utilization of VOC to detect faults in a telecommunication industry. In this paper, association rule mining based on VOC is used to identify root fault causes of a telecommunications network. To do that, VOC of a Communication Service Provider has been collected first. Then, association rule mining has also been conducted with various support and confidence levels. As a result, root fault causes of the telecommunications network can be identified. It is expected that this study can be used as a basis for decisions about customer satisfaction management such as preventive maintenances or reduction of the customer maintenance cost.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.5
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• pp.60-67
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• 2014

Wind power is one of the fastest growing renewable energy sources. The blades length and tower height of wind turbine have been growing steadily in the last 10 years in order to increase the output amount of wind power energy. The amount of wind turbine energy is increased by increasing the capacity of wind turbine, but the costs of preventive, corrective and replacement maintenance are also increased accordingly. Recently, Condition Monitoring System that can repair the fault diagnose and repair of wind turbine in the real-time. However, these system have a problem that cannot predict and diagnose of the fault. In this paper, wind turbine predict methodology is proposed by using the SVM method. In the case study, correlation analysis between wind turbine fault and external environmental factors is performed by using the SVM method.

• The Journal of Engineering Geology
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• v.20 no.4
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• pp.371-380
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• 2010

A three-dimensional finite element analysis was performed to predict the location of a fault zone ahead of a tunnel face based on convergence displacement. Geometrical models for the numerical analysis were developed based on the possible geometric intersection between the fault zone and the tunnel. Fifteen fault models were generated from combinations of faults with five different strikes (at $15^{\circ}$ intervals) and three dips (vertical, $45^{\circ}$ and $-45^{\circ}$) relative to the tunnel route. The displacements on the crown and side walls were calculated and analyzed using a vector orientation approach. As a result, nine representative prediction charts were developed, showing location and orientation of the fault zone based on convergence displacement.

• KNOM Review
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• v.24 no.1
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• pp.13-19
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• 2021

In recent, there is research to maximize production by preventing failures/accidents in advance through fault diagnosis/prediction and factory automation in the industrial field. Cloud technology for accumulating a large amount of data, big data technology for data processing, and Artificial Intelligence(AI) technology for easy data analysis are promising candidate technologies for accomplishing this. Also, recently, due to the development of fault diagnosis/prediction, the equipment maintenance method is also developing from Time Based Maintenance(TBM), being a method of regularly maintaining equipment, to the TBM of combining Condition Based Maintenance(CBM), being a method of maintenance according to the condition of the equipment. For CBM-based maintenance, it is necessary to define and analyze the condition of the facility. Therefore, we propose a machine learning-based system and data model for diagnosing the fault in this paper. And based on this, we will present a case of predicting the fault occurrence in advance.

• Journal of Power Electronics
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• v.18 no.5
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• pp.1608-1617
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• 2018

The rapid and correct isolation of faulty submodules (SMs) is of great importance for improving the reliability of modular multilevel converters (MMCs). Therefore, a fast diagnosis method containing fault detection and fault location determination was presented in this paper. An improved incremental predictive model of arm current was proposed to detect failures, and the multi-step prediction method was used to eliminate the negative impact of disturbances. Moreover, a control method was proposed to strengthen the fault characteristics to rapidly locate faulty arms and faulty SMs by detecting the variation rate of the SM capacitor voltage. The proposed method can rapidly and easily locate faulty SMs under different load conditions without the need for additional sensors. The experimental results have validated the effectiveness of the proposed method by using a single-phase MMC with four SMs per arm.

• Journal of the Korean Geophysical Society
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• v.5 no.2
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• pp.75-86
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• 2002

A TSP(Tunnel Seismic Prediction) survey which is modified VSP(Vertical Seismic Profiling) survey applied in tunnel was carried out at Pyongtaek and Incheon liquefied petroleum gas(LPG) storage cavern during excavation. The TSP survey in Pyongtaek LPG storage cavern which is located below Namyangho was performed to confirm the location and orientation of the fault detected at pre-investigation stage. The TSP survey was carried out in access tunnel, construction tunnel, and watercurtain tunnel to characterize 3 dimensional figure of the fault. The results of TSP survey are compared four in vestigation boreholes drilled in shelter of access tunnel. The fault was also detected by borehole survey and the location was coincided with the result of TSP survey. Depending on the result of TSP survey and core logging, the design such as cavern layout and length was changed. Another TSP survey was performed in Incheon LPG storage cavern which is located below sea. Because of poor geological information at pre-investigation stage and suffering from heavy leakage of groundwater, the TSP survey to detect fracture zone was carried out. The support and grouting design was reflected by the result of TSP survey.

• Geomechanics and Engineering
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• v.14 no.4
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• pp.337-344
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• 2018

The study of the mining effect influenced by a normal fault has great significance concerning the prediction and prevention of fault rock burst. According to the occurrence condition of a normal fault, the stress evolution of the working face and fault plane, the movement characteristics of overlying strata, and the law of fault slipping when the working face advances from footwall to hanging wall are studied utilizing UDEC numerical simulation. Then the inducing-mechanism of fault rock burst is revealed. Results show that in pre-mining, the in situ stress distribution of two fault walls in the fault-affected zone is notably different. When the working face mines in the footwall, the abutment stress distributes in a "double peak" pattern. The ratio of shear stress to normal stress and the fault slipping have the obvious spatial and temporal characteristics because they vary gradually from the higher layer to the lower one orderly. The variation of roof subsidence is in S-shape which includes slow deformation, violent slipping, deformation induced by the hanging wall strata rotation, and movement stability. The simulation results are verified via several engineering cases of fault rock burst. Moreover, it can provide a reference for prevention and control of rock burst in a fault-affected zone under similar conditions.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.235-245
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• 2011

Early criticality prediction models that determine whether a design entity is fault-prone or not are becoming more and more important as software development projects are getting larger. Effective predictions can reduce the system development cost and improve software quality by identifying trouble-spots at early phases and proper allocation of effort and resources. Many prediction models have been proposed using statistical and machine learning methods. This paper builds a prediction model using Support Vector Machine(SVM) which is one of the most popular modern classification methods and compares its prediction performance with a well-known prediction model, BackPropagation neural network Model(BPM). SVM is known to generalize well even in high dimensional spaces under small training data conditions. In prediction performance evaluation experiments, dimensionality reduction techniques for data set are not used because the dimension of input data is too small. Experimental results show that the prediction performance of SVM model is slightly better than that of BPM and polynomial kernel function achieves better performance than other SVM kernel functions.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.3
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• pp.95-100
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• 2003

Electronic equipment used in satellites are demanding extremely high reliability, so they should be designed to have immunity for some critical faults by using redundancy component. Generally, Communication satellites are assigned to meet the 15 years mission lifetime, of the analysis about faults must be performed to electronic equipments of satellite. This paper is a summary of the fault tolerance design research of command processor, the improvement of reliability and trade-off study of fault tolerance design result. The reliability prediction value of the satellite component used in this research was taken from Koreasat 3 and Kompsat 1. It is important to perform many trade-off studies for fault tolerance design, especially to choose the most proper fault tolerance method for the specified fault scenario.