• Title/Summary/Keyword: operation costs

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A Study on the Performance Prediction Model for Life Cycle Maintenance of Reservoir (저수지 생애주기 유지관리를 위한 성능저하예측 모델 연구)

  • Lee, Huseok;Kim, Ran-Ha;Cho, Choong-Yuen
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.1
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    • pp.568-574
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    • 2021
  • According to the Framework Act on Sustainable Infrastructure Management, which has been enforced since 2020, reservoirs should be managed to minimize life cycle costs caused by aging through preemptive management such as systematic maintenance and performance improvement. For maintenance in consideration of the life cycle, it is essential to derive the end of life due to continuous performance degradation as the common period increases. For this purpose, it is necessary to develop a performance-predicting model for reservoirs. In this study, a reservoir was divided into main complex facilities to develop a model for the maintenance of the life cycle. A model was developed for each facility. For model development, maintenance information data were collected under management by the Rural Community Corporation. The data available for model development were selected by analyzing the collected data. The developed model was used to predict the expected life expectancy of the reservoir in the current maintenance system and the expected life expectancy in the case of no action. By using the developed model, it is expected that it will be possible to support decision making in operation management and maintenance while considering the life cycle of the reservoir.

A TBM data-based ground prediction using deep neural network (심층 신경망을 이용한 TBM 데이터 기반의 굴착 지반 예측 연구)

  • Kim, Tae-Hwan;Kwak, No-Sang;Kim, Taek Kon;Jung, Sabum;Ko, Tae Young
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.23 no.1
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    • pp.13-24
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    • 2021
  • Tunnel boring machine (TBM) is widely used for tunnel excavation in hard rock and soft ground. In the perspective of TBM-based tunneling, one of the main challenges is to drive the machine optimally according to varying geological conditions, which could significantly lead to saving highly expensive costs by reducing the total operation time. Generally, drilling investigations are conducted to survey the geological ground before the TBM tunneling. However, it is difficult to provide the precise ground information over the whole tunnel path to operators because it acquires insufficient samples around the path sparsely and irregularly. To overcome this issue, in this study, we proposed a geological type classification system using the TBM operating data recorded in a 5 s sampling rate. We first categorized the various geological conditions (here, we limit to granite) as three geological types (i.e., rock, soil, and mixed type). Then, we applied the preprocessing methods including outlier rejection, normalization, and extracting input features, etc. We adopted a deep neural network (DNN), which has 6 hidden layers, to classify the geological types based on TBM operating data. We evaluated the classification system using the 10-fold cross-validation. Average classification accuracy presents the 75.4% (here, the total number of data were 388,639 samples). Our experimental results still need to improve accuracy but show that geology information classification technique based on TBM operating data could be utilized in the real environment to complement the sparse ground information.

A Study on Economic Evaluation Modeling of MVDC Distribution System for Hosting Capacity of PV System (태양광전원 수용을 위한 MVDC 배전망의 경제성평가 모델링에 관한 연구)

  • Lee, Hu-Dong;Kim, Ki-Young;Kim, Mi-Sung;Rho, Dae-Seok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.3
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    • pp.1-12
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    • 2021
  • Technologies for an MVDC(medium voltage direct current) distribution system are being considered as an effective alternative to overcome the interconnection delay issues of PV systems. However, the implementation of a DC distribution system might lead to economic problems because of the development of DC devices. Therefore, this paper deals with the scale of a PV plant based on its capacity and proposes hosting-capacity models for PV systems to establish a network to evaluate the feasibility of an MVDC distribution system. The proposed models can be classified as AC and DC distribution systems by the power-supply method. PV systems with hundreds of MW, dozens of MW, and a few MW can be categorized as large-scale, medium-scale, and small-scale models, respectively. This paper also performed modeling for an economic evaluation of MVDC distribution system by considering both the cost of AC and DC network construction, converter replacement, operation, etc. The profit was composed of the SMP and REC rate of a PV plant. A simulation for economic evaluation was done for the MVDC distribution system using the present worth and equal-principal costs repayment method. The results confirmed that the proposed model is a useful tool to evaluate economic issues of a DC distribution system.

Study on the Applicability of Muography Exploration Technology in Underground Space Development (지하공간개발에서 뮤오그래피 탐사기술의 적용성에 관한 연구)

  • Seo, Seunghwan;Lim, Hyunsung;Ko, Younghun;Kwak, Kiseok;Chung, Moonkyung
    • Explosives and Blasting
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    • v.39 no.4
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    • pp.22-33
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    • 2021
  • Recently, the frequent occurrence of ground subsidence in urban areas has caused increasing anxiety in residents and incurred significant social costs. Among the causes of ground subsidence, the rupture of old water and sewer pipes not only halts the operation of the buried pipes, but also leads to ground and water pollution problems. However, because most pipes are buried after construction and cannot be seen with the naked eye, the importance of maintenance has underestimated compared to other structures. In recent years, integrated physical exploration has been applied to the maintenance of underground pipes and structures. Currently, to investigate the internal conditions and vulnerable portions of the ground, consolidated physical surveys are executed. Consolidated physical surveys are analysis techniques that obtain various material data and add existing data using multiple physical surveys. Generally, in geotechnical engineering, consolidated physical surveys including electrical and surface wave surveys are adopted. However, it is difficult to investigate time-based changes in under ground using these surveys. In contrast, surveys using cosmic-ray muons have been used to scan the inner parts of nuclear reactors with penetration technology. Surveys using muons enable real-time observation without the influence of vibration or electricity. Such surveys have great potential for available technology because of their ability to investigate density distributions without requiring as much labor. In this paper, survey technologies using cosmic ray muons are introduced, and the possibilities of applying such technologies as new physical survey technologies for underground structures are suggested.

Improvement Mechanism for Automatic Web Vulnerability Diagnosis (웹취약점 자동진단 개선방안)

  • Kim, Tae-Seop;Jo, In-June
    • The Journal of the Korea Contents Association
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    • v.22 no.2
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    • pp.125-134
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    • 2022
  • Due to the development of smartphone technology, as of 2020, 91.9% of people use the Internet[1] to frequently acquire information through websites and mobile apps. As the number of homepages in charge of providing information is increasing every year, the number of applications for web vulnerability diagnosis, which diagnoses the safety of homepages, is also increasing. In the existing web vulnerability check, the number of diagnostic personnel should increase in proportion to the number of homepages that need diagnosis because the diagnosticians manually test the homepages for vulnerabilities. In reality, however, there is a limit to securing a web vulnerability diagnosis manpower, and if the number of diagnosis manpower is increased, a lot of costs are incurred. To solve these problems, an automatic diagnosis tool is used to replace a part of the manual diagnosis. This paper explores a new method to expand the current automatic diagnosis range. In other words, automatic diagnosis possible items were derived by analyzing the impact of web vulnerability diagnosis items. Furthermore, automatic diagnosis identified possible items through comparative analysis of diagnosis results by performing manual and automatic diagnosis on the website in operation. In addition, it is possible to replace manual diagnosis for possible items, but not all vulnerability items, through the improvement of automatic diagnosis tools. This paper will explore some suggestions that can help improve plans to support and implement automatic diagnosis. Through this, it will be possible to contribute to the creation of a safe website operating environment by focusing on the parts that require precise diagnosis.

A Study on the Scheme of Implementing Meta-data Based Applications for Enterprises (메타 데이터 기반의 기업용 애플리케이션 구축 방안에 관한 연구)

  • Jang, Gil-Sang
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.9
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    • pp.135-145
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    • 2009
  • Generally, the phases of constructing information systems are consisted of systems planning and selection, system analysis, system design, and system implementation and operation. These systems require many efforts and costs for additional development of modification requirements due to a frequent changes of business environments and business processes. Especially, inconsistencies between system design and system implementation usually happen during development steps because of the difficulties of program developments due to difficulties of capturing exact user requirements and frequent changes of user requirements. This paper proposes a scheme of implementing meta-data based applications for enterprises in order to reduce inconsistencies between system design and system implementation and to overcome limits of the existing coding-based development methods of applications which must use until disuse if they are developed once. Also, this paper presents a framework of repository system to systematically manage and utilize meta-data. The core concept of the proposed scheme makes outputs generated in the phases of system analysis and design into meta-data and is to easily develop and customize application programs using meta-data repository. Also, to show the applicability of the proposed scheme, it is applied to implement ERP system of 'H' automotive part manufacturer. As a result, the proposed scheme can gain improvements such as easiness and productivity of program development, easiness of maintenance, reusability of program components, etc.

A Study on the Fiscal Efficiency of the Early Scrappage Support System for Aged Diesel Vehicles (노후 경유차 조기폐차 지원제도의 재정 효율성에 관한 연구)

  • Sung Hoon Kang
    • Environmental and Resource Economics Review
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    • v.32 no.2
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    • pp.107-126
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    • 2023
  • This study analyzes the financial efficiency of the early scappage support system using the benefit and cost analysis. To do so, we use comprehensive administrative data on the early scrappage of old diesel vehicles. The result shows that the benefit-cost ratio was greater than 1 before 2020, but it appeared to be less than 1 after 2020. This indicates that despite recent reforms to increase the subsidy of early scrappage of old diesel vehicles, the rate of the benefit of air quality improvement is not as fast as the increase in system operation cost of this system. The benefit of air quality improvement depends on how much the operating period is shortened due to early scrappage support system. The earlier this period is brought forward, the more likely it is that the benefits of early scrappage will exceed the costs. Upon examining the results of this study, it was found that when the scrappage timing is brought forward by 5 years, the B/C for 98% of the samples becomes 1, greatly securing financial efficiency. Therefore, it is important for the government to reform the system so that it can influence the decision of old diesel vehicle owners on the timing of scrappage.

A Study on the Improvement of the Logistics System for Heavy-goods Maintenance in Navy Ship (해군함정 중량형 정비품 물류체계 개선에 관한 연구)

  • Jang, Ji-Hwan;Kim, Hwan-Seong
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2020.11a
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    • pp.163-164
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    • 2020
  • Along with the increase in global volume of goods, logistics companies are trying to reduce costs by increasing the size of ships carrying cargo, increasing the efficiency of quantitative equipment at ports, and unmanned electric vehicles on land. Korean naval ports are also facing the same situation as the global trend. In the past, small and medium-sized ships such as FF, PCC, and beheaded eagles are being retired for their longevity, and their positions are being replaced by large ships such as KDX, FFG, and LST-II. In particular, large ships such as Dokdo and the next light aircraft carriers are also being prepared. Unlike general merchant ships, naval ships require periodic inspections and preventive maintenance, so repair piers such as maintenance depots are in operation. The naval maintenance depot mainly uses trailers, trucks, and truck-type cranes to carry out loading and unloading of heavy ships, and the application or development of automation and unmanned equipment performed by the private sector is inadequate, and self-improvement cases are also very weak. This study aims to improve the efficiency of the military logistics system through research on the logistics system such as transport, storage and unloading of heavy goods and maintenance products of naval ships.

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Outlier Detection and Labeling of Ship Main Engine using LSTM-AutoEncoder (LSTM-AutoEncoder를 활용한 선박 메인엔진의 이상 탐지 및 라벨링)

  • Dohee Kim;Yeongjae Han;Hyemee Kim;Seong-Phil Kang;Ki-Hun Kim;Hyerim Bae
    • The Journal of Bigdata
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    • v.7 no.1
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    • pp.125-137
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    • 2022
  • The transportation industry is one of the important industries due to the geographical requirements surrounded by the sea on three sides of Korea and the problem of resource poverty, which relies on imports for most of its resource consumption. Among them, the proportion of the shipping industry is large enough to account for most of the transportation industry, and maintenance in the shipping industry is also important in improving the operational efficiency and reducing costs of ships. However, currently, inspections are conducted every certain period of time for maintenance of ships, resulting in time and cost, and the cause is not properly identified. Therefore, in this study, the proposed methodology, LSTM-AutoEncoder, is used to detect abnormalities that may cause ship failure by considering the time of actual ship operation data. In addition, clustering is performed through clustering, and the potential causes of ship main engine failure are identified by grouping outlier by factor. This enables faster monitoring of various information on the ship and identifies the degree of abnormality. In addition, the current ship's fault monitoring system will be equipped with a concrete alarm point setting and a fault diagnosis system, and it will be able to help find the maintenance time.

Multi-objective Genetic Algorism Model for Determining an Optimal Capital Structure of Privately-Financed Infrastructure Projects (민간투자사업의 최적 자본구조 결정을 위한 다목적 유전자 알고리즘 모델에 관한 연구)

  • Yun, Sungmin;Han, Seung Heon;Kim, Du Yon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.1D
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    • pp.107-117
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    • 2008
  • Private financing is playing an increasing role in public infrastructure construction projects worldwide. However, private investors/operators are exposed to the financial risk of low profitability due to the inaccurate estimation of facility demand, operation income, maintenance costs, etc. From the operator's perspective, a sound and thorough financial feasibility study is required to establish the appropriate capital structure of a project. Operators tend to reduce the equity amount to minimize the level of risk exposure, while creditors persist to raise it, in an attempt to secure a sufficient level of financial involvement from the operators. Therefore, it is important for creditors and operators to reach an agreement for a balanced capital structure that synthetically considers both profitability and repayment capacity. This paper presents an optimal capital structure model for successful private infrastructure investment. This model finds the optimized point where the profitability is balanced with the repayment capacity, with the use of the concept of utility function and multi-objective GA (Generic Algorithm)-based optimization. A case study is presented to show the validity of the model and its verification. The research conclusions provide a proper capital structure for privately-financed infrastructure projects through a proposed multi-objective model.