• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1714-1721
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• 2007

TECA (Terminal Cabin), the terminal device which offers the information to the driver about the condition of High Speed Train(KTX), analyzes the system of train and plays a role of corrective maintenance guideline to a driver when a breakdown occurs. It also supports the driver to decide the situation of the train by offering a necessary information, in communicating with MPU(Main Processor Unit). For Localization of TECA, it is necessary to analyze communication protocol between TECA and MPU. As a part of analysis, communication protocol between OBCS(on-board computer system) and add-on devices has analyzed for the first step. Also with protocol analyzer appropriate method was offered for TECA and MPU protocol analysis. Finally, by appling proposed method to the drivers consol suitability was verified.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1018-1020
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• 2008

Since radio communications based train control system requires considerable amount of information than track circuits based signalling system and these information have significant effects on train control system safety, it is essential to ensure information integrity. In addition, when track information has to be added or changed due to track installation, track maintenance (both corrective and preventive), any information changes must be reported to train control system as soon as possible. In this paper, we provide explanation on the equipment and its data structure. Also, we represent the results of a simulator application to check the information integrity generated by the equipment.

• Journal of Drive and Control
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• v.9 no.2
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• pp.28-38
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• 2012

Monitoring of system cleanliness levels and counting of particulate contaminant are fundamental to achieving hydraulic system reliability as any departure from the specified cleanliness level is often a precursor to future failures. On-line monitoring of cleanliness levels has the advantage of giving data both very quickly and accurately as environmental influences are eliminated. In this way, corrective actions can be promptly implemented. Most on-line instruments are sensitive to system conditions to a greater or lesser extent, but Automatic Particle Counters (APCs) working on light extinction principles are especially sensitive to the presence of optical interfaces caused by such conditions as fluid mixtures, emulsions, free water and air bubbles. These conditions give erroneous data and can result in drawing incorrect conclusions, wasting maintenance time and ultimately, reduced user confidence in cleanliness monitoring. This paper describes such conditions and shows how the correct selection of the analysis technique can result in reliable cleanliness level data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.51
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• pp.211-220
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• 1999

The purpose of this study is the necessity of collaboration, equilibrium or the differences of examination items about certification system which is focused on products, such as KS, formal approval, and ISO 9000 family, QS 9000, etc, for Quality management system. We make expert group control this problem. Also we make examination items to be united. And the differences of certification body and personnel necessary is dissolved by proper instruction. Examination process and corrective maintenance should be improved by clarity, fairness and reliability. Problems through preparation for certification and certified company should be focused on reform of consciousness of top management and continuous instruction. And desirable solution for mutual certification problem and others should be found by information interchange system of international cooperation.

• Journal of the Korean Society of Mechanical Technology
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• v.13 no.2
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• pp.9-19
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• 2011

Most real world design evaluation and risk-based decision support combine quantitative and qualitative (linguistic) variables. Decision making based on conventional mathematics that combines qualitative and quantitative concepts always exhibit difficulty in modelling actual problems. The successful selection process for choosing a design/procurement proposal is based on a high degree of technical integrity, safety levels and low costs in construction, corrective measures, maintenance, operation, inspection and preventive measures. In this paper, a design decision support framework using a composite structure methodology grounded in approximate reasoning approach and evidential reasoning method is suggested for design evaluation of machinery space of a ship engine room at the initial stages. An illustrative example is used to demonstrate the application of the proposed framework.

• Journal of Applied Reliability
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• v.13 no.3
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• pp.217-227
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• 2013

Reliability growth is defined as the positive improvement in a reliability parameter over a period of time due to implementation of corrective actions to system design, operation or maintenance procedures, or the associated manufacturing process. In recent, the importance of reliability growth management has emerged in the military authority and industries. For effective application of reliability growth models, it is necessary to understand their characteristics and differences. This paper presents the concepts of reliability growth management and compares the features of reliability tracking and projection models centered on MIL-HDBK-189C for selecting the appropriate model for an one-shot system under development.

• Journal of the Korean Society for Railway
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• v.13 no.2
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• pp.159-165
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• 2010

In this paper the TRMS (Tilting Rolling-stock Maintenance System) that applies the concept of RAM (Reliability, Availability, and Maintainability) and RCM (Reliability Centered Maintenance) to Preventive and Corrective Maintenance Policy for TTX (Tilting Train Express) will be discussed. We will briefly introduce the RCM concepts and discus show these concepts and procedures are implemented in the TRMS S/W. In the TRMS S/W there are four modules, System and Operations Information Module, FMECA(Failure Modes, Effects, and Criticality Analysis)module, RAM Information Module, and RCM Analysis Module. The System and Operations Information Module provides the user interface for collection of systems and operations related data and the FMECA module provides a groundwork for the RCM analysis. The algorithms to calculate the reliability and failure rate for Weibull distribution and formulae to calculate the task intervals and task costs are proposed in the RAM and RCM Analysis Module respectively. There is a good possibility of applying RCM to other rolling stock maintenance systems if the benefit that RCM can brings to the maintenance world is fully recognized.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.611-620
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• 2021

The maintenance industry is mainly progressing based on condition-based maintenance after corrective maintenance and preventive maintenance. In condition-based maintenance, maintenance is performed at the optimum time based on the condition of equipment. In order to find the optimal maintenance point, it is important to accurately understand the condition of the equipment, especially the remaining useful life. Thus, using simulation data (C-MAPSS), a prediction model is proposed to predict the remaining useful life of a turbofan engine. For the modeling process, a C-MAPSS dataset was preprocessed, transformed, and predicted. Data pre-processing was performed through piecewise RUL, moving average filters, and standardization. The remaining useful life was predicted using principal component analysis and the k-NN method. In order to derive the optimal performance, the number of principal components and the number of neighbor data for the k-NN method were determined through 5-fold cross validation. The validity of the prediction results was analyzed through a scoring function while considering the usefulness of prior prediction and the incompatibility of post prediction. In addition, the usefulness of the RUL prediction model was proven through comparison with the prediction performance of other neural network-based algorithms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.190-196
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• 2020

FRACAS(Failure Reporting, Analysis and Corrective Action System) has been applied in various industries to improve the reliability of the systems. FRACAS is effective in improving reliability by repeating failure analysis, proper corrective action, and result verification for identified failures. However, FRACAS has many limitations in terms of process, data collection and management to be integrated into the existing development environment. In the domestic defense industry, studies on the development of FRACAS system and process improvement have been conducted to solve the difficulties of applying FRACAS, but most of them are concentrated in the operation/maintenance phase. Since FRACAS should be conducted in consideration of TLCSM(Total Life Cycle System Management), it is necessary to study the reference architecture so that FRACAS can be applied from the early design phase. In this paper, we studied the TLCSM-based integrated architecture considering the system life cycle phases, FRACAS closed-loop process, and FRACAS essentials in order to effectively apply FRACAS throughout the life cycle of defense systems. The proposed architecture was used as a reference model for FRACAS in a shipboard combat system.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.2
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• pp.81-88
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• 2023

SHM (Structural Health Monitoring) technique for monitoring aircraft structural health and damage, EHM (Engine Health Monitoring) for monitoring aircraft engine performance, and APM (Application Performance Management) is used for each function. APMS (Airplane Performance Monitoring System) is a program that comprehensively applies these techniques to identify the difference between the performance manual provided by the manufacturer and the actual fuel mileage of the aircraft and reflect it in the flight plan. The main purpose of using APMS is to understand the performance of each aircraft, to plan and execute flights in an optimal way, and consequently to reduce fuel consumption. First, it is to check the fuel efficiency trend of each aircraft, check the correlation between the maintenance work performed and the fuel mileage, find the cause of the fuel mileage increase/decrease, and take appropriate measures in response. Second, it is to find the cause of fuel mileage degradation in detail by checking the trends by engine performance and fuselage drag effect. Third, the APMS is to be used in making maintenance work decisions. Through APMS, aircraft with below average fuel mileage are identified, the cause of fuel mileage degradation is identified, and appropriate corrective actions are determined. Fourth, APMS data is used to analyze the economic analysis of equipment installation investment. The cost can be easily calculated as the equipment installation cost, but the benefit is fuel efficiency improvement, and the only way to check this is the manufacturer's theory. Therefore, verifying the effect after installation and verifying the economic analysis is to secure the appropriateness of the investment. Through this, proper investment in fuel efficiency improvement equipment will be made, and fuel efficiency will be improved.