• 한국안전학회지
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• 제38권2호
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• pp.104-111
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• 2023

Rolling stock maintenance, which focuses on preventive maintenance, is typically implemented considering the potential harm that may be inflicted to passengers in the event of failure. The cost of preventive maintenance throughout the life cycle of a rolling stock is 60%-75% of the initial purchase cost. Therefore, ensuring stability and reducing maintenance costs are essential in terms of economy. In particular, private railroad operators must reduce government support budget by effectively utilizing railroad resources and reducing maintenance costs. Accordingly, this study analyzes the reliability characteristics of components using field data. Moreover, it resolves the problem of determining an economical replacement interval considering the timing of scrapping railroad vehicles. The procedure for determining the optimal replacement interval involves five steps. According to the decision model, the optimal replacement interval for the onboard signal device components of the "A" line train is calculated using field data, such as failure data, preventive maintenance cost, and failure maintenance cost. The field data analysis indicates that the mileage meter is 9 years, which is less than the designed durability of 15 years. Furthermore, a life cycle in which the phase signal has few failures is found to be the same as the actual durability of 15 years.

• 한국컴퓨터정보학회논문지
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• 제24권7호
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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.

• 시스템엔지니어링학술지
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• 제18권1호
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• pp.99-104
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• 2022

In this paper, to increase the maintenance efficiency of the urban railway train control system and to build a standard data system, we collect as much as possible structured, unstructured, and semi-structured data, and collect data by sensing and monitoring the system status and system status and monitoring. pre-process function data(Identification, purification, integration, transformation) through effective data classification and maintenance activities business classification system was studied. The purpose of this is to define the data matrix model by considering the relationship with the data generated and managed in the O&M stage of the train control system operated by the urban railway together with the WBS model, and to reflect and utilize it in practice.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.221-232
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• 2023

Recently, due to the expansion of the logistics industry, demand for logistics automation equipment is increasing. The modern logistics industry is a high-tech industry that combines various technologies. In general, as various technologies are grafted, the complexity of the system increases, and the occurrence rate of defects and failures also increases. As such, it is time for a predictive maintenance model specialized for logistics automation equipment. In this paper, in order to secure the operational reliability of the ICT/Cold-Chain Unmanned Storage, a predictive maintenance system was implemented based on the LSTM model. In this paper, a server for data management, such as collection and monitoring, and an analysis server that notifies the monitoring server through data-based failure and defect analysis are separately distinguished. The predictive maintenance platform presented in this paper works by collecting data and receiving data based on RabbitMQ, loading data in an InMemory method using Redis, and managing snapshot data DB in real time. The predictive maintenance platform can contribute to securing reliability by identifying potential failures and defects that may occur in the operation of the ICT/Cold-Chain Unmanned Storage in the future.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2003년도 춘계학술발표회 논문집
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• pp.443-450
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• 2003

Our country is constructed the digital map in the first NGIS plan. Through digital map construction, it was had the potentiality that can more easily activate GIS. But these data included numerous problems from user's view. In the second NGIS plan, our government try to construct the framework data for the maximization of GIS utilization. This paper is showed a step of update that considered relationship between the national framework data themes, suggested the structure of maintenance activity for national framework data.

• 한국구조물진단유지관리공학회 논문집
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• 제12권3호
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• pp.183-190
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• 2008

국가 중요시설물인 터널에 대한 유지관리업무는 관리주체별, 용도별, 터널 규모별로 각각 상이하게 수행되고 있다. 현재 각 관리주체별로 운영중인 국내 터널유지관리시스템을 분석해보면 수기 또는 초보적인 전산화만이 되어 활용도가 매우 저조한 것이 현 상태이다. 이에 본 연구에서는 터널의 계획, 설계, 시공 단계의 관련자료 뿐 아니라 보수 보강 이력 자료 등의 유지관리단계에서 조사된 여러 현장조사와 터널 스캐너에 의한 결과를 통합한 새로운 터널유지관리시스템을 구축하여 국내 여러 터널 현장에 적용한 후, 이의 적용성을 분석하였고, 터널 유지관리방법의 개선안을 제안하였다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2002년도 가을 학술발표회 논문집
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• pp.219-226
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• 2002

To systematic maintenance and record 10,000 port structures, under Ministry of Maritime and Fisheries, data base management system is required. In this study, POMIS(Port Maintenance and Information System) program is developed for this Purpose. In this program, records for inspection and repair for the various type of port structures can be maintained and operated through internet. Thus ministry can efficiently maintenance and repair port structures and systematically manage computerized maintenance and repair data.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.312-317
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• 1998

Reliable maintenance scheduling of main equipments is a crucial problem in thermal power stations in order to skirt overall losses of power generation resulted from severe failures of the equipments. A reasonable method was proposed to determine the maintenance scheduling of whole pump system in thermal power stations in order to reduce the maintenance cost by keeping the present avail-ability of the pump system throughout the operation. The dimensional reduction method was used to solve problems encountered due to few data which involved many operational factors in failure rate of pumps. The problem of bandlimited nature of data with time was solved by extrapolating future failures from presently available actual data with an aid of Weibull distribution. The results of the analysis identified the most suitable maintenance intervals of each pump type accordingly and hence reduce the cost of unnecessary maintenance with an acceptable range in the overall system availability.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2014년도 춘계 학술논문 발표대회
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• pp.56-57
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• 2014

As school facilities have been expanding quantity better than quality, efficient school facility management has been focused on from 2001 in domestic. Due to obsolescence of school facility, objective management and maintenance cost of school facility is very important. However LCC(Life cycle cost) analyst, owner, engineer, contractor and facility manager have a difficulty to obtain and facilitate the basic analyzed data required to analyze LCC of school facility and establish maintenance plan. Therefore this research presents muti-dimensional analysis method through data warehouse technique for supplying maintenance cost information of school facility that can trace and accumulate the scattered LCCing data in the perspective of life cycle of school facility.

• KNOM Review
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• 제24권1호
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• pp.13-19
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• 2021

최근 산업 분야에서는 공장 자동화 뿐만 아니라 장애 진단/예측을 통해 고장/사고를 사전에 방지하여 생산량을 극대화하기 위한 연구가 진행되고 있으며, 이를 구성하기 위해 많은 양의 데이터 축적을 위한 클라우드 기술, 데이터 처리를 위한 빅 데이터 기술, 그리고 데이터 분석을 쉽게 진행하기 위한 AI(Artificial Intelligence)기술이 도입되고 있다. 또한 최근에는 장애 진단/예측의 발전으로 인해 설비 유지보수(PM: Productive Maintenance) 방식도 정기적으로 설비를 유지보수 하는 방식인 TBM(Time Based Maintenance)에서 설비 상태에 따라 유지보수 하는 방식인 CBM(Condition Based Maintenance)을 조합하는 방식으로 발전하고 있다. CBM 기반 유지보수를 수행하기 위하여 설비의 상태(condition)의 정의와 분석이 필요하다. 따라서 본 논문에서는 머신 러닝(Machine Learning) 기반의 장애 진단을 위한 시스템 및 데이터 모델(Data Model)을 제안하며, 이를 기반으로 장애를 사전 예측한 사례를 제시하고자 한다.