• Title/Summary/Keyword: 유지관리비용모델

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A Study on Survivability Management Model for Information Systems Over Internet (인터넷에서 정보시스템의 생존성 관리 모델)

  • Kim, Hwang-Rae;Park, Jin-Sub
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.7 no.6
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    • pp.1185-1193
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    • 2006
  • The next generation networked information system over unbounded internet is open to various network attacks and incidents, so many users suffer from damage and financial loss. In this paper we propose a survivability management model to evaluate the tradeoffs between the cost of defence mechanisms for information systems with weighted service and the resulting expected survivability after a network attack or occurrence of incidents. By varying the level of defence in the simulation, we examine how survivability changes according to the defense level. We derive a cost/survivability and weighted service/survivability curve that managers can use to decide on the appropriate level of defense for the network system of their organizations.

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Predicting Highway Concrete Pavement Damage using XGBoost (XGBoost를 활용한 고속도로 콘크리트 포장 파손 예측)

  • Lee, Yongjun;Sun, Jongwan
    • Korean Journal of Construction Engineering and Management
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    • v.21 no.6
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    • pp.46-55
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    • 2020
  • The maintenance cost for highway pavement is gradually increasing due to the continuous increase in road extension as well as increase in the number of old routes that have passed the public period. As a result, there is a need for a method of minimizing costs through preventative grievance Preventive maintenance requires the establishment of a strategic plan through accurate prediction old Highway pavement. herefore, in this study, the XGBoost among machine learning classification-based models was used to develop a highway pavement damage prediction model. First, we solved the imbalanced data issue through data sampling, then developed a predictive model using the XGBoost. This predictive model was evaluated through performance indicators such as accuracy and F1 score. As a result, the over-sampling method showed the best performance result. On the other hand, the main variables affecting road damage were calculated in the order of the number of years of service, ESAL, and the number of days below the minimum temperature -2 degrees Celsius. If the performance of the prediction model is improved through more data accumulation and detailed data pre-processing in the future, it is expected that more accurate prediction of maintenance-required sections will be possible. In addition, it is expected to be used as important basic information for estimating the highway pavement maintenance budget in the future.

Application of Framework Data Model for Road Management (도로관리를 위한 기본지리정보 데이터모델 응용 연구)

  • Ji Jeong-Kuk;Lim Seung-Hyeon;Choi Young-Taek;Cho Gi-Sung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.23 no.1
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    • pp.31-38
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    • 2005
  • Importance of road that is country base equipment is occupying fair part. Therefore, establishment of road and maintenance expense for road management are increasing continuously. These problem can manage efficiently through data model construction that take advantage of framework data. But, because of difference of method of study in research institution, framework data research was constructed being overlapped until current. This is because framework data research was no access of application side. Therefore, National Geographic Information Institute presented subject framework data model guide through framework data model standardization business. This research constructed road management data model that take advantage of traffic framework data. Therefore, we can check equal data construction and reduce expense accordingly. Also, because there are not data model development instances by framework data model, it is difficult that judge whether is suitable to apply framework data model guide. Hence, in this study, the extended road management data medel and the suitability of framework data is presented.

Application of probabilistic VE/LCC Analysis Models for Quay Wall Structures (안벽구조물의 확률론적 VE/LCC 분석모델 적용방안)

  • Ahn, Jong-Pil;Lee, Cheung-Bin;Park, Ju-Won;Yu, Deog-Chan
    • Korean Journal of Construction Engineering and Management
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    • v.8 no.5
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    • pp.71-79
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    • 2007
  • It is common that the analysis of VE/LCC is performed in design phase of quay wall structures. The analysis is mainly executed based on experience and engineering sense of expert considering the selection of construction method, construction and maintenance cost. Recently there are increasing demands on the analysis that includes uncertainty and vulnerability of input parameters, for this purpose, fuzzy reliability based probabilistic VE/LCC analysis model for quay wall structures is suggested. In VE/LCC analysis for quay wall structures, the application of probabilistic analysis method give very similar results compare with those of deterministic analysis method. It is anticipated that the methodology proposed in this paper can also be utilized in the design and maintenance phase of other facilities where decision making is made for the probabilistic life cycle cost and value analysis.

Economic Analysis on the Maintenance Management of Riparian Facilities against Flood Damage (침수피해를 고려한 하천이용시설 유지관리의 경제성 분석)

  • Lee, Seung Yeon;Yoo, Hyung Ju;Lee, Sang Eun;Lee, Seung Oh
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.198-198
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    • 2021
  • 최근 자연적, 사회적, 정책적 관점에서 하천관리의 중요성이 증대되면서 국가하천 정비를 통한 하천시설 관리의 책임이 증대되고 있다. 국가하천 5대강 본류의 친수지구 이용도 변화를 살펴보면 2015년에 비해 2019년에 면적당 이용객 수가 630,813(명/km2)이 증가하였음을 알 수 있었고(국토교통부, 2020) 본 연구에서는 이용자 수 증가율이 높은 편인 한강 내 하천이용시설을 대상으로 선정하여 해당 지역을 기계학습 기반의 수위예측 알고리즘에 적용하였다. 하천이용시설은 하천이용자가 편리하게 하천을 이용하기 위하여 설치한 시설로 공원시설(강서, 난지, 양화, 망원, 여의도, 이촌, 반포, 잠원, 뚝섬, 잠실, 광나루, 구리)을 위주로 분석하였다. 해당 시설의 침수피해를 고려하기 위해 시계열 자료에 특화된 LSTM(Long Short-term Memory)기법을 활용하여 수위예측 알고리즘을 개발하였고 이를 통해 도출된 홍수 예보로 재난을 대비하고 시설물을 체계적으로 관리하는 유지관리의 효과를 분석하고자 하였다. 입력 자료(input data)는 수위 (EL.m), 팔당댐 방류량 (m3/s), 강화대교의 조위(EL.m)를 사용하였으며 수위예측 알고리즘을 통해 6시간 후 예측 수위값을 도출하여 기존 2단계(주의보, 경보)였던 홍수 예보 단계에서 4단계(관심, 보행자통제, 차량통제, 경계)로 구축하였다. 기존과 세분화된 홍수예보를 적용했을 경우의 유지관리 비용과 편익을 산정하여 하천이용시설의 경제성을 비교·분석한 결과, 유지관리 비용이 기존 대비 약 5% 이상 절감되었고 편익은 약 1.5배 이상 증가하였으며 관리등급은 평균 C등급(보통) 이상 달성하였다. 이는 수위예측 알고리즘의 적용으로 하천이용 활성화 및 투자의 효율성에 목적을 두었으며 향후 분석결과를 토대로 경제성모델을 개발하여 국가하천 내 관리그룹에 적용하면 효율적인 유지관리체계를 제시할 수 있을 것으로 기대된다.

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PMG : Project Management Negotiating Model and Process among Stakeholders in Project Development Phase (PMG : 프로젝트 개발단계에서 Stakeholder 간의 문제점 협상모델 및 프로세스)

  • Moon, Jae-Hyun;Kim, Jin-Hyung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2008.05a
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    • pp.300-303
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    • 2008
  • IT 관련 프로젝트를 진행 시 프로젝트 진행 도중 예상치 못한 많은 문제에 봉착하게 된다. 본 논문에서는 IT 프로젝트 대부분이 도입, 사용하는 요구사항분석-설계-개발-테스트-배포-유지보수단계 중 개발단계 및 유지보수 단계에서 발생할 수 있는 문제점에 초점을 맞추었다. PMG 란 Project Management Negotiator 의 약자로서 개발 시 고객의 요구사항이 변경되면 고객과 개발자 간의 개발에 소요되는 난이도, 일정, 비용에 따른 관점이 다를 수 있으므로, 이러한 차이점을 서로 이해 할 수 있는 범위 내에서 감소시킬 수 있는 모델을 제시한다. 또한 제시한 모델에 근거한 매핑테이블과 프로세스를 개발하고 실제 pilot 시스템을 구축하여 효용성을 검증한다. 제시한 프로젝트 관리 협상 모델을 통하여 일정에 차질 없는 프로젝트가 수행 가능하며 비용절감 및 고객만족 효과를 거둘 수 있다. 결과적으로 일정, 비용 측면 및 고객 만족 세 가지 측면에서 기존의 프로젝트 개발 방법론보다 더 나은 일정준수, 효율성, 정확성 등의 정량적, 정성적 만족을 확보할 수 있다.

Decision Making Model for Widening Bridges Using Decision Tree Technique (의사결정수 기법을 이용한 교량확폭에 관한 의사결정모델 개발)

  • Cho, Hyo Nam;Park, Jin-Hyung;Sun, Jong-Wan;Youn, Man-Keun
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.12 no.4
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    • pp.187-194
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    • 2008
  • Recently, the constructions of widening bridges or new bridges are often undergoing as a part of road widening because traffic volumes are rapidly increasing caused by fast-growing population and urbanization. But in general, there is no rational decision process and specification to justify the validity of the bridge widening. Moreover, there are also numerous events including various uncertainties involved in widening bridges. In this paper, therefore, a decision making model is proposed for widening bridges using decision tree based on quantitative LCC analysis considering a variety of uncertainties for the rational and practical approach to a quantitative decision making for alternatives.

Comparison of Fuel Consumption Estimation for Passenger Cars (승용차 유류소모량 산정 방법의 비교 연구)

  • Yoo, In-Kyoon;Kim, Je-Won;Lee, Su-Hyeong;Ko, Kwang-Ho
    • International Journal of Highway Engineering
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    • v.13 no.4
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    • pp.167-175
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    • 2011
  • Evaluation of fuel consumption for the various road condition and vehicle type is necessary to perform the economic analysis of road construction which is important for the efficient design and management of road. Economic analysis of road should consider the social cost which can be divided into agency cost including initial construction expense, maintenance cost, and so on, and user cost consisting of vehicle operating cost, congestion cost, etc. Since vehicle operating cost depends on the traffic volume, fuel consumption that is a major part of vehicle operating cost will change by traffic volume as well. Fuel consumption is significantly affected by vehicle speed and road condition, especially the roughness. Thus, fuel consumption should be evaluated in terms of road condition, which is not currently considered. In this study, the estimation model of fuel consumption for the passenger cars in Korea has been developed by considering the road condition. First, the relationship between vehicle speed and fuel consumption that is used to calculate the vehicle operating cost for investment evaluation of transportation facility and the initial feasibility study of road construction was investigated. Second, with the consideration of road roughness, fuel consumption of the passenger car was measured. From the measurement, it was found that fuel consumption increased by $80m{\ell}$ per 100km driving as the roughness increased by 1m/km. Therefore, it is recommended that for the economic analysis of road design and management, the fuel consumption should be a function of road roughness.

Research on the Development of Automatic Damage Analysis System for Railway Bridges using Deep Learning Analysis Technology Based on Unmanned Aerial Vehicle (무인이동체 기반 딥러닝 분석 기술을 활용한 철도교량 자동 손상 분석 기술 개발 연구)

  • Na, Yong-Hyoun;Park, Mi-Yeon
    • Proceedings of the Korean Society of Disaster Information Conference
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    • 2022.10a
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    • pp.347-348
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    • 2022
  • 본 연구에서는 무인이동체를 활용한 철도교량의 외관조사 점검을 보다 효율적이고 객관성 있게 수행하기 위하여 무인이동체를 통해 촬영된 이미지를 딥러닝 기반 분석기술을 활용하여 손상 자동으로 분석 하기위한 기술을 연구하였다. 철도교량의 외관 손상 중 균열, 콘크리트 박리·박락, 누수, 철근노출에 대한 손상 이미지를 추출하여 딥러닝 분석 모델을 생성하고 학습한 분석 모델을 적용한 시스템을 실제 현장에 적용 테스트를 수행하였으며 학습 구현된 분석모델의 검측 재현율을 검토한 결과 평균 95%이상의 감지성능을 검토할 수 있었다. 개발 제안된 자동손상분석 기술은 기존 육안점검 결과 대비 보다 객관적이고 정밀한 손상 검측이 가능하며 철도 유지관리 분야에서 무인이동체를 활용한 외관조사 업무를 수행함에 있어 기존 대비 객관적인 결과도출과 소요시간, 비용저감이 가능할 것으로 기대된다.

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Condition Estimation of Facility Elements Using XGBoost (XGBoost를 활용한 시설물의 부재 상태 예측)

  • Chang, Taeyeon;Yoon, Sihoo;Chi, Seokho;Im, Seokbeen
    • Korean Journal of Construction Engineering and Management
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    • v.24 no.1
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    • pp.31-39
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    • 2023
  • To reduce facility management costs and safety concerns due to aging of facilities, it is important to estimate the future facilities' condition based on facility management data and utilize predictive information for management decision making. To this end, this study proposed a methodology to estimate facility elements' condition using XGBoost. To validate the proposed methodology, this study constructed sample data for road bridges and developed a model to estimate condition grades of major elements expected in the next inspection. As a result, the developed model showed satisfactory performance in estimating the condition grades of deck, girder, and abutment/pier (average F1 score 0.869). In addition, a testbed was established that provides data management function and element condition estimation function to demonstrate the practical applicability of the proposed methodology. It was confirmed that the facility management data and predictive information in this study could help managers in making facility management decisions.