• 품질경영학회지
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• 제25권1호
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• pp.31-43
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• 1997

In this study, the pros and cons of TPM and RCM were comparatively evaluated at various aspects : a, pp.ication process, objectives, maintenance items, organizations, analysis of maintenace methods, etc. It is found that TPM can be considered as a management discipline. However, in TPM, there seldom exist concrete rules or guidelines to select a maintenance scheme. RCM, which is a widely used maintenance scheme for aircrafts or power plants, has a good analysis and decision logic for maintenance planning. In the paper, similar decision rules are adopted to TPM deployment to get an effective and effecient maintenance Planning.

• 대한전기학회논문지
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• 제41권1호
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• pp.9-17
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• 1992

Proper resource allocation is also a very important topic in power system problems, especially in operation and planning. One such is optimal maintenance problem in operation and planning. Least cost and highest reliability should be the subjects to be pursued. A probabilistic operation simulation model developed recently by authors is applied to the proboem of optimal maintenance scheduling. Three different methods are compared, marginal maintenance cost, levelized risk and maintenance space. The method by the marginal maintenance costs shows the least cost, the highest reliability and the highest maintenance outage rates. This latter characteristics may considerably influence the results of genetation planning, because the usual maintenance outages obtained from the other methods have shown to be lower.

• 풍력에너지저널
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• 제13권2호
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• pp.5-12
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• 2022

Operations and maintenance (O&M) in offshore wind farms accounts for a substantial portion of the life cycle cost due to harsh weather conditions and vessel dispatching. In this regard, it is crucial to expedite O&M technologies in South Korea, which is in the early stage of harnessing wind resources from the ocean. This contribution investigates an O&M planning and scheduling model for floating offshore wind farms with a literature review and use case study. We introduce the development of a long- and short-term maintenance planning framework as part of an integrated O&M platform. This contains a single vessel and fleets routing composition along with technicians and a maintenance job list based on numerical algorithms. Additionally, the routing search presents the basis of decision support for economic trade-offs regarding smooth operation corresponding to ever-changing wind farm situations. The maintenance planning simulator will ultimately contribute to support yearly and day-to-day power-related decisions in a cost-effective manner.

• 전기학회논문지
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• 제67권4호
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• pp.505-511
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• 2018

Long term capacity expansion planning has to be carried out to satisfy pre-defined system reliability criterion. For purpose of assessing system reliability, probabilistic simulation technique has been widely adopted. However, the way how to approximate generator outage, especially maintenance outage, in probabilistic simulation scheme can significantly influence on reliability assessment. Therefore, in this paper, 3 different maintenance approximation methods are applied to investigate the quantitative impact of maintenance approximation method on long term capacity expansion planning.

• Industrial Engineering and Management Systems
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• 제7권2호
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• pp.113-125
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• 2008

This paper presents a model for designing cellular manufacturing systems (CMS) by integrating system cost, machine reliability, and preventive maintenance (PM) planning. In a CMS, a part is processed using alternative process routes, each consisting of a sequence of visits to machines. Thus, a level of 'system reliability' is associated with the machines along the process route assigned to a part type. Assuming machine reliabilities to follow the Weibull distribution, the model assigns the machines to cells, and selects, for each part type, a process route which maximizes the overall system reliability and minimizes the total costs of manufacturing operations, machine underutilization, and inter-cell material handling. The model also incorporates a reliability based PM plan and an algorithm to implement the plan. The algorithm determines effective PM intervals for the CMS machines based on a group maintenance policy and thus minimizes the maintenance costs subject to acceptable machine reliability thresholds. The model is a large mixed integer linear program, and is solved using LINGO. The results point out that integrating PM in the CMS design improves the overall system reliability markedly, and reduces the total costs significantly.

• 한국통신학회:학술대회논문집
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• 한국통신학회 1986년도 추계학술발표회 논문집
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• pp.59-63
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• 1986

This paper presents a basic planning of CMDSS(Centrallized Maintenance Decision Support System)for future operation and maintenance of telecommunication network, the main components of CMDSS are MDB, MMB, DSDB, MDBMS, MMAMS, and IGMS. ANd the efficiency and the effectiveness depend on the adequate design of the decision procedure to assisy operation and maintenance persinnels.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2007년도 춘계학술대회 논문집
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• pp.328-333
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• 2007

Traditional maintenance planning is based on a constant maintenance interval for equipment life. In order to consider economic aspect for tm based preventive maintenance, preventive maintenance is desirable to be scheduled by RCM(Reliability-Centered Maintenance) evaluation. The main objective of RCM is to reduce the maintenance cost, by focusing on the most important functions of the system and avoiding or removing maintenance actions that are not strictly necessary. So, Markov state model is utilized considering stochastic state in RCM In this paper, a Markov state model much can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by the stepwise Markov model in detail. Also, because the system is not continuously monitored, the inspection is considered. In case study, simulation results about RCM will be shown using the real historical data of combustion turbine generating unit in Korean power systems.

• KIEAE Journal
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• 제3권3호
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• pp.67-74
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• 2003

The repair and maintenance planning is the principal transaction to prevent from the degradation of apartment buildings to prolong their lives. Various building components as part of living area should be maintained properly and timely before critical defects are realized, then the building life might be extended until the limit of its usability. In other words, various building components such as utilities, finishes and structural members are needed to be repaired and replaced in different time interval after completion. To do this systematically, a maintenance management system for Long-Range Planning (LRP) needs developing. The LRP should be figured out based on the forecast of repairing and replacing cycle of building components according to work trades. And the precise forecast of repairing and replacing time of the components helps to enhance the usability of the developed system. The purpose of this paper is to suggest a system with which apartment building managers carry out the tasks of periodical check, diagnosis and replacement of building components based on the maintenance calendar. By using the system, they can easily forecast repairing and replacing time of the components with the consideration of life cycle of building materials and build the LRP.

• 교육시설 논문지
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• 제18권4호
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• pp.69-77
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• 2011

The purpose of this study is to provide the school planning factors as emergency shelter after disaster. The school functions as the evacuation space areas could be classified into the evacuation center, education maintenance, and dwelling. Among these functions, the scopes of our study are limited to the functions of evacuation center and education maintenance. To carry out this purpose, we were comparative analyzed the shelter space problems of Korea and Japan's survey in the existing literatures. In results of our study, the evacuation center's functions are difficult to depending on the disaster types, such as the earthquake, tornado, and hurricane. On the other hand, the education maintenance functions are difficult to deepening on the victims occupied times in the school as emergency shelters. Based on these findings, the Korea school planning as the emergency shelters are desired to reflect that the evacuation's functions based on the disaster type of the damage from storms, and the education maintenance's functions based on the victim's occupied times in school for their safety.

• Smart Structures and Systems
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• 제26권4호
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• pp.533-544
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• 2020

Effective bridge maintenance reduces bridge operation costs and extends its service life. The possibility of storing bridge life-cycle data in a 3D parametric model of the bridge through Bridge Information Modeling (BrIM) provides new opportunities to enhance current practices of bridge maintenance management. This study develops a Decision Support System (DSS), namely BrDSS, which employs BrIM and an efficient optimization model for bridge maintenance planning. The BrIM model in BrDSS extracts basic data of elements required for the optimization process and visualizes the inspection data and the optimization results to the user to help in decision makings. In the optimization module of the DSS, the specifically formulated Genetic Algorithm (GA) eliminates the chances of producing infeasible solutions for faster convergence. The practicality of the presented DSS was explored by utilizing the DSS in the maintenance planning of a bridge under operation in the southwest of Iran.