• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.20 no.4
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• pp.45-48
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• 2016

• Journal of Applied Reliability
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• v.17 no.3
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• pp.256-263
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• 2017

Purpose: This article provides the efficiency test results of conducting depot maintenance. Method: ANOVA (analysis of variance) and ANCOVA (analysis of covariance) tests are conducted using data obtained from Defense Logistics Integrated Information System (DELIIS). Results: The result shows that although the effect of the depot maintenance is significant, some parts do not follow the overall effect of the depot maintenance. In order to solve the problem we provide some suggestions to be improved. Conclusion: For improving the combat readiness condition of K-1 main battle tank, the maintenance policies and regulation must be revised for the parts of the weakness. In addition, the collection way of the operation and maintenance data must be redesigned.

• Journal of the Korea institute for structural maintenance and inspection
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• v.5 no.4
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• pp.205-213
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• 2001

The condition assessment of bridges is one of the important procedures in the safety evaluation of the structures. The current inspection guideline is rather ambiguous and vague so that the inspection results based on the existing guidelines are highly subjective and varing from person to person and even day to day for a given person. It is therefore, necessary to improve the current inspection criteria in order to provide consistent results in safety assessment. To circumvent possible inconsistencies in inspection and rating of bridge components, the revised criteria have been proposed in this study. The proposed guideline and criteria may be efficiently used for the realistic and consistent assessment of bridge structures.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.4
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• pp.693-700
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• 2024

This study aims to analyze the concept and application of AI-based predictive maintenance in the railroad industry and draw implications from it. Focusing on the adoption of AI-based maintenance systems by the Korea Railroad Corporation and Seoul Metro, we examined how AI technology can improve the efficiency and safety of railroad operations. We also compared and analyzed the application of AI technology in the European railroad industry through the cases of Deutsche Bahn in Germany and SNCF in France. The study found that AI-powered predictive maintenance contributes to reducing the frequency of breakdowns, reducing maintenance costs, and increasing the reliability of railroad operations.

• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.1998-2008
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• 2020

Solenoid operated valves (SOV) play important roles in industrial process to control the flow of fluids. Solenoid valves can be found in so many industries as well as the nuclear plant. The ability to be able to detect the presence of faults and predicting the remaining useful life (RUL) of the SOV is important in maintenance planning and also prevent unexpected interruptions in the flow of process fluids. This paper proposes a fault diagnosis method for the alternating current (AC) powered SOV. Previous research work have been focused on direct current (DC) powered SOV where the current waveform or vibrations are monitored. There are many features hidden in the AC waveform that require further signal analysis. The analysis of the AC powered SOV waveform was done in the time and frequency domain. A total of sixteen features were obtained and these were used to classify the different operating modes of the SOV by applying a machine learning technique for classification. Also, a deep neural network (DNN) was developed for the prediction of RUL based on the failure modes of the SOV. The results of this paper can be used to improve on the condition based monitoring of the SOV.

• Journal of the Korean Society of Systems Engineering
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• v.12 no.1
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• pp.41-58
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• 2016

Reliability Centered Maintenance (RCM) introduces a systematic method and decision logic tree for utilizing previous operating experience focused on reliability and optimization of maintenance activities. In this paper RCM methodology is applied on safety injection system for APR-1400. Functional Failure Mode Effects and Criticality Analysis (FME&CA) are applied to evaluate the failure modes and the effect on the component, system and plant. Logic Tree Analysis (LTA) is used to determine the optimum maintenance tasks. The results show that increasing the condition based maintenance will reduce component failure and improve reliability and availability of the system. Also the extension of the surveillance test interval of Safety Injection Pumps (SIPs) would lead to an improved pump's availability, eliminate the unnecessary maintenance tasks and this will optimize maintenance activities.

• Journal of Applied Reliability
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• v.18 no.2
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• pp.184-191
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• 2018

Purpose: The purpose of this study is to propose a method to calculate the optimal preventive maintenance cycle of radar used in the aviation weapon system of ROKAF. Methods: A hybrid model is used to estimate the optimal preventive maintenance cycle in a system that can perform condition based predictive maintenance (CBPM) through continuous diagnosis. The failure data of the radars operating in the military were used to calculate the reliability. Results: According to the research results, the reliability threshold of the radar began to decrease after 5 flights, and decreased rapidly after 12 flights. Since the second check, costs have continued to decline. Conclusion: A method is proposed to determine the cycle of optimal preventive maintenance of radar within operational budget through modeling results between reliability limit and cost for radar. The results can be used to determine the optimal preventive maintenance cycle and frequency of various avionics equipment.

• Journal of Applied Reliability
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• v.18 no.2
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• pp.104-113
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• 2018

Purpose: This paper proposes the non-periodic preventive maintenance policy based on the level of cumulative hazard intensity. We aim to construct a cost-effectiveness on the proposed model with relaxing the constraint on reliability. Methods: We use the level of cumulative hazard intensity as a condition variable, instead of reliability. Such a level of cumulative hazard intensity can derive the reliability which decreases as the frequency of preventive maintenance action increases. We also model the imperfect preventive maintenance action using the proportional age setback model. Conclusion: We provide a numerical example to illustrate the proposed model. We also analyze how the parameters of our model affect the optimal preventive maintenance policy. The results show that as long as high reliability is guaranteed, the inefficient preventive maintenance action is performed reducing the system operation time. Moreover, the optimal value of the proposed model is sensitive to changes in preventive maintenance cost and replacement cost.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.451-452
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• 1999

• Structural Engineering and Mechanics
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• v.64 no.3
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• pp.347-352
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• 2017

The poor maintenance practice increases the possibility of system failure. Subsequently, the consequences of failure fall on the aspects of output, safety and healthy, environmental integrity, system quality, and customer satisfaction. Conditionbased maintenance is seen as a potential strategy to improve performance. Whereby, the key success factor of this maintenance strategy is identified as the system inspection. This study aims to investigate the association between system breakdown rate and frequency of inspection. A mixed method approach is implemented by distributing questionnaire and interviewing for data collection. Subsequently, descriptive analysis, correlation analysis and regression are adopted to analyse the collected data from 100 respondents and the results are validated with interview data of 10 interviewees. The research result establishes significant relationship between the system breakdown rate and the frequency of inspection. Additionally, the result of regression analysis confirms that the frequency of inspection is the significant predictor of system breakdown rate. Planning of accurate inspection frequency is crucial to secure the system performance. Hence, the research signifies the importance to carry out regular inspection towards the building systems and components. As a recommendation, the maintenance personnel should assess the risk criticality of the building systems. Then, continuously monitor the condition of critical building systems; regularly inspect the condition of non-critical building systems and randomly inspect all of them.