• Journal of Ocean Engineering and Technology
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• v.28 no.6
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• pp.533-539
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• 2014

A maintenance system for an offshore plant uses an optimal maintenance method, process, and period based on operation information data and economic evaluation techniques. Maintenance is performed after one or more indicators show that equipment is going to fail or that equipment performance is deteriorating. A maintenance system is based on the use of real-time data to prioritize and optimize the LNG-FPSO topside equipment resources.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1793-1802
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• 2017

In the recent years, IT and Network Technology has rapidly advanced environment in accordance with the needs of the times, the usage of the smart learning service is increasing. Smart learning is extended from e-learning which is limited concept of space and place. This system can be easily exposed to the various security threats due to characteristic of wireless service system. Therefore, this paper proposes the improvement methods of smart learning system security by use of faults analysis methods such as the FTA(Fault Tree Analysis) and FMECA(Failure Mode Effects and Criticality Analysis) utilizing the consolidated analysis method which maximized advantage and minimized disadvantage of each technique.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.131-133
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• 1999

This paper proposed the technique of the fault-types classification using Adaptive Network Fuzzy Inference System in the distribution system. Fault and fault-like data in the linear RL load, arc furnace load and converter load were extracted by EMTP. These were characterized into 5 input variables and fuzzified automatically by learning. This technique was tested using another fault data unused learning.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.100-101
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• 1998

In this paper, we've studied on the Breakdownpatterns which hove an effect on Down-Time of Medical Equipment. This study is based on the statistics of MMS(Maintenance Management System) accumulated since the opening of Samsung Medical Center. We hope that this paper, which is acquired through the analysis about the seasonal feature, the work pattern feature and the period used, is useful to reduce a term of Down-Time and to retrench hospital management cost.

• IE interfaces
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• v.16 no.1
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• pp.27-33
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• 2003

The maintenance cost in K Steelworks has been continuously increased in proportion to the production cost. However, there seems to be a possibility of reducing cost through the optimization of maintenance actions. The failure types of the equipment in steelworks ate various with different failure cost. Thus the failure rate and cost of each type of failures should be considered simultaneously when the optimum maintenance period is to be determined. It is considered that the equipment undergoes periodic replacement and a specified number of incomplete preventive maintenance actions are performed during a replacement period. Assuming that the time to failure follows a Weibull distribution, the parameters of the failure rate are estimated using the maximum likelihood estimation. The optimal replacement period is determined to minimize the average cost per unit time. As the result of analysis it is suggested that the existing maintenance period for a hot-rolling equipment can be extended significantly.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.808-810
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• 1996

In this paper, neural network, which has learning capability, is used for fault type classification and fault section estimation for high speed relaying. The potential of the neural network approach is demonstrated by simulation using ATP. The instantaneous values of voltages and currents are used the inputs of neural networks. This approach determines the fault section directly. In this paper, back-propagation network(BPN) is used for fault type classification and fault section estimation and can use for high speed relaying because it determines fault section within a few msec.

• Journal of the Korean Geographical Society
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• v.43 no.2
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• pp.220-234
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• 2008

In many security monitoring contexts, the performance or efficiency of surveillance sensors/networks based on a single sensor type may be limited by environmental conditions, like illumination change. It is well known that different modes of sensors can be complementary, compensating for failures or limitations of individual sensor types. From a location analysis and modeling perspective, a challenge is how to locate different modes of sensors to support security monitoring. A coverage-based optimization model is proposed as a way to simultaneously site k different sensor types. This model considers common coverage among different sensor types as well as overlapping coverage for individual sensor types. The developed model is used to site sensors in an urban area. Computational results show that common and overlapping coverage can be modeled simultaneously, and a rich set of solutions exists reflecting the tradeoff between common and overlapping coverage.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.5
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• pp.437-445
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• 2018

Devices have a lot of small breakdowns rather than big breakdowns. But it often wastes time and increases cost of maintenance, such as calling a service technician for small breakdowns. So, if we use remote control and monitoring service using Internet of Things, we can minimize the time period and cost for the maintenance. However, security is important because remote control and monitoring services contain personal information which when leaked, may be dangerous. There are many types of Internet based monitoring devices that are in use, but it is difficult to expect a high level of security because there are many cases in which the performance is minimal. Therefore, in this paper, we classify remote control and monitoring services based on Internet of Things type and derive encryption requirement for four types. We also compared and analyzed the lightweight cryptographic algorithms that can be expected to use high performance even on the Internet of Things. And it is derived that LED is used as a equipment management type, DESLX as a environment management type, CLEFIA as a healthcare management type and LEA as a security management type are the optimal lightweight cryptographic algorithms for each type.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.127-134
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• 2021

In this study, an anomaly detection (AD) algorithm was implemented to detect the failure of a marine air compressor. A lab-scale experiment was designed to produce fault datasets (time-series electric current measurements) for 10 failure modes of the air compressor. The results demonstrated that the temporal pattern of the datasets showed periodicity with a different period, depending on the failure mode. An AD model with a convolutional autoencoder was developed and trained based on a normal operation dataset. The reconstruction error was used as the threshold for AD. The reconstruction error was noted to be dependent on the AD model and hyperparameter tuning. The AD model was applied to the synthetic dataset, which comprised both normal and abnormal conditions of the air compressor for validation. The AD model exhibited good detection performance on anomalies showing periodicity but poor performance on anomalies resulting from subtle load changes in the motor.

• Journal of Korean Society of Steel Construction
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• v.16 no.4 s.71
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• pp.407-414
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• 2004

Bridges in common use are expected to have more varieties of load in their connected members and bolts than in construction. Faults in connection members or bolts occur so often according to the time flow. One of the purposes of this study is to find out the behavior and structural features of high-tension bolted joints with faults that are very difficult and cost much to find out through experimentation with finite element analysis. Another purpose of this study is to provide sufficient data, estimated experimental results, and the scheme of the test plate for an economical experimental study in the future. Surveys of bridges with a variety of faults and statistical classifications of their faults were performed, as was a finite element analysis of the internal stress and the sliding behavior of standard and defective bridge models. The finite element analysis of the internal stress was performed according to the interval of the bolt, the thickness of the plate, the distance of the edge, the diameter of the bolt, and the expansion of the construction. Furthermore, the analysis explained the sliding behavior of high-tension bolt joints and showed the geometric non-linear against the large deformation, and the boundary non-linear against the non-linear in the contact surface, including the material non-linear, to best explain the exceeding of the yield stress by sliding. A normally bolted high-tension bolt joint and deduction of bolt tension were also analyzed with the finite element analysis of bridge-sliding behavior.