• Journal of Applied Reliability
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• v.10 no.2
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• pp.93-105
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• 2010

The following thesis provides an explanation for the definition of the MIL-HDBK-2155 : Failure Reporting, Analysis and Corrective Action System (FRACAS), which systemizes the collection and analysis of failure data and the feedback process of the results. It also presents a plan based on MIL-HDBK-2155 for the collection and analysis of operating specifications on weapon systems. The collection and analysis of failure data and the feedback process utilizing FRACAS contributes to identifying improvement requirements during equipment operation as well as finding and eliminating the root cause of the failures. The objective of applying FRACAS to weapon systems is to receive source data feedback for reliability enhancements and performance improvements during operation. This is done by recognizing weaknesses in the design or operation by identifying the type of failures that might occur, and by performing Failure Modes, Effects and Criticality Analysis(FMECA) and Failure Tree Analysis(FTA).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.3
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• pp.174-182
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• 2007

There are not many studies on the maintenance and replacement for the ITS equipments. Most of ITS center has no comprehensive regulation on the equipment replacement. This study was focusing on estimation of equipment replacement period and the number of spare parts in stock using the actual failure data of Road Side Equipment (RSE) by Dedicated Short Range Communication (DSRC). The failure data showed a type of bath-tub curves. The data, however, did not fit to any probability distribution curve, which means that the preventive replacement cannot be strongly applied for the RSE. In the aspect of practical strategy, this study suggest that repairing cost and failure frequency be used for decision of replacement of RSE after the 1 or 2 year warrant period. The future study needs to include more RSE failure data as well as other equipments of the ITS.

• Journal of Navigation and Port Research
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• v.30 no.6 s.112
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• pp.525-531
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• 2006

In the port, the yard crane is very important. If a container crane or a transfer crane is broken down, it costs a lot because of the delay of work during the period of repair or reorder. But, we don't have enough spare parts because of the high cost. It is necessary to maintain high reliability of the crane through effective preventive maintenance and failure analysis. In this paper, we analyse the function and failure mechanism of the transfer crane which is a main equipment in the yard Also, we standardize failures and maintenance works using the historical data of failure and maintenance. This study which is a basic work for effective equipment operation and maintenance will support reliability engineers to decide the optimal design of the next generation equipment and operational policy of equipment.

• Journal of the Korean Society of Safety
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• v.20 no.3 s.71
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• pp.1-8
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• 2005

The industrial induction motor is widely used in the rotating electrical machine for the transmission of power. It is very reliable equipment, but it could lead to the loss of production and lift when failure occurs. Therefore, the failure data is acquired and analyzed by attaching an exclusive instrument to existing induction motor. However, these instruments could lead to side effects, increasing the production costs, because they are very expensive. The purpose of this study is the development of an induction motor bearing failure diagnosis system constructed using LabVIEW which can be supplied the kernelled function, process monitoring and current signature analysis. In addition, the availability and reasonability of the constructed system was examined for an induction motor with failure defects in outer raceway and ball bearing. From the results, it shows that failure diagnosis system constructed is useful for real-time monitoring with detection of bearing defects over the web.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2209-2214
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• 2010

The purpose of Reliability Centered Maintenance(Hereafter, RCM) is to enhance the effectiveness and efficiency of preventive maintenance by applying the improvement plan after analysis of existing preventive maintenance. To accomplish this, it is required to collect the failure data for equipments during operation, and to carry out the quantitative criticality analysis for each equipment. This paper shows that the case study of RCM criticality analysis based on the accumulative failure data and following improvement activity for KORAIL AIRPORT RAILROAD's E&M system.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.109-119
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• 2010

FRACAS (Failure Reporting, Analysis and Corrective Action System) is intended to provide management visibility and control for reliability and maintainability improvement of hardware and associated software by timely and disciplined utilization of failure and maintenance data to generate and implement effective corrective actions to prevent failure recurrence and to simplify or reduce the maintenance tasks. This process applies to acquisition for the design, development, fabrication, test, and operation of military systems, equipment, and associated computer programs. This paper shows the FRACAS development process and developed FRACAS system for a defense equipment.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.10a
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• pp.223-226
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• 2009

Various database and analysis system has been used for the cost effective maintenance of distribution facility but it is not effective because of the lack of interconnection among these systems. In order to overcome this problem this paper proposes reliability centered maintenance system based on the on-line monitoring of distribution system through intelligent distribution equipment. This system is made by the interconnection of distribution automation system, asset management system, failure analysis system and failure mode effect analysis system.

• The Journal of Bigdata
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• v.7 no.1
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• pp.113-124
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• 2022

Various methods using machine learning and big data have been applied to prevent failures in Data Centers. However, there are many limitations to referencing individual equipment-based performance indicators or to being practically utilized as an approach that does not consider the infrastructure operating environment. In this study, the performance indicators of individual infrastructure equipment are integrated monitoring and the performance indicators of various equipment are segmented and graded to make a single numerical value. Data pre-processing based on experience in infrastructure operation. And an ensemble of RRCF (Robust Random Cut Forest) analysis and Prophet analysis model led to reliable analysis results in detecting anomalies. A failure analysis system was implemented to facilitate the use of Data Center operators. It can provide a preemptive response to Data Center failures and an appropriate tuning time.

• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.125-133
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• 2019

Because military weapons systems for special purposes are small and complex, they are not easy to maintain. Therefore, it is very important to maintain combat strength through quick maintenance in the event of a breakdown. In particular, naval ships are complex weapon systems equipped with various equipment, so other equipment must be considered for maintenance in the event of equipment failure, so that skilled maintenance personnel have a great influence on rapid maintenance. Therefore, in this paper, we analyzed maintenance data of defense equipment maintenance information system through text mining and social network analysis(SNA), and tried to identify the naval ship maintenance expertise. The defense equipment maintenance information system is a system that manages military equipment efficiently. In this study, the data(2,538cases) of some naval ship maintenance teams were analyzed. In detail, we examined the contents of main maintenance and maintenance personnel through text mining(word cloud, word network). Next, social network analysis(collaboration analysis, centrality analysis) was used to confirm the collaboration relationship between maintenance personnel and maintenance expertise. Finally, we compare the results of text mining and social network analysis(SNA) to find out appropriate methods for finding and finding naval ship maintenance expertise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1386-1390
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• 2007

This paper presents the equipment condition monitoring technology for the process or the equipment using statistical techniques. The equipment condition monitoring system consists of an empirical model to estimate the expected sensor values of process variables and a diagnose model to detect the abnormal condition and to identify the root source of the problem. The empirical model is constructed by the analysis of historic data. The diagnose model uses the sequential probability ratio test (SPRT) technique. The monitoring system was tested with real operating data acquired from the Reactor Coolant Pump Seal in the Nuclear Power Plant. It can detect the system degradation or failure at the early stage since it is able to catch the subtle deviation of process variables from normal condition.