• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.4
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• pp.172-178
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• 2006

In this paper, an advanced demand clustering algorithm which can explore the planned maintenance outage of generators in changed electricity industry is proposed. The major contribution of this paper can be captured in the development of the long-term estimates for the generation availability considering planned maintenance outage. Two conflicting viewpoints, one of which is reliability-focused and the other is economy-focused, are incorporated in the development of estimates of maintenance outage based on the advanced demand clustering algorithm. Based on the advanced clustering algorithm, in each demand cluster, conventional effective outage of generators which conceptually capture maintenance and forced outage of generators, are newly defined in order to properly address the characteristic of the planned maintenance outage in changed electricity markets. First, initial market demand is classified into multiple demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the initial demand. Then, based on the advanced demand clustering algorithm, the planned maintenance outages and corresponding effective outages of generators are reevaluated. Finally, the conventional demand clusters are newly classified in order to reflect the improved effective outages of generation markets. We have found that the revision of the demand clusters can change the number of the initial demand clusters, which cannot be captured in the conventional demand clustering process. Therefore, it can be seen that electricity market situations, which can also be classified into several groups which show similar patterns, can be more accurately clustered. From this the fundamental characteristics of power systems can be more efficiently analyzed, for this advanced classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.

• Journal of Information Technology Services
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• v.12 no.2
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• pp.335-348
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• 2013

Vessel PMS (Planned Maintenance System) is a paper and/or software based system to monitor vessel engine equipment including main propulsion, steering, auxiliary machinery and cargo handling information. This is one of mandatory survey for vessel introduced by IMO (International Maritime Organization). The planned maintenance as well as documentation must be performed according to a system to be approved by classification agencies. Recently, vessel owners have preferred software based systems to collect and preserve accurate data. However, not ship specific and not taking into account the user are said by end users as operational difficulties. To relieve these concerns, this research analyzes vessel PMS data, suggests a middleware to support automatic collection and design consideration of user interface.

• International Journal of Quality Innovation
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• v.7 no.3
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• pp.15-23
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• 2006

A spare ordering policy is considered for planned maintenance. Introducing the ordering, uptime, downtime, inventory costs and salvage value, we derive the expected cost effectiveness. The problem is to determine jointly the ordering time for a spare and the preventive replacement time for the operating unit which maximize the expected cost effectiveness. Some properties regarding the optimal policy are derived, and a numerical example is included to explain the proposed model.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.66-73
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• 2011

With rapid industrialization, electric power consumption has been increasing every year in Korea and in other countries. The provision of additional power stations to produce more electricity is one possible response to this steady increase in consumption. Another alternative is to improve the efficiency of existing stations through timely and effective maintenance works. Since the construction of a new power plant involves a large amount of capital as well as difficulties in the selection of sites, the improvement of existing power stations' efficiencies is often a preferred solution. Therefore, this paper focuses on maintenance project management to address this issue. Among several types of maintenance works, this paper concentrates on planned outage maintenance (POM). This focus arises from the critical impact of POM on other maintenance work, as well as the entire process of electricity production. Unlike other maintenance work, POM is done on the basis of mid and long-term plans. In addition, only POM works are conducted during the outage of all power plants. To evaluate the efficiency of POM works, budget data relating to 164 POM projects between 2001 and 2008 was collected from 7 sites in South Korea. Data envelopment analysis (DEA) was selected as a methodology for evaluation. From this analysis, comparative study was used to determine the categories of projects that had performed well, and those with the most optimized budget structures. Moreover, through discussion with industry, this research develops a feasible proposed method by which to enhance the efficiency of POM projects.

• Journal of Aerospace System Engineering
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• v.17 no.5
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• pp.1-10
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• 2023

This research sought to determine the optimal cycle of Planned Depot Maintenance (PDM) for Unmanned Aerial Vehicle (UAV), and PDM through Reliability and Maintainability-based simulation and Operating and Support (O&S) cost analysis using Reliability and Maintainability analysis results. The effectiveness of the PDM was verified economically, and the optimal PDM interval that balances UAV effective operations and sustaining engineering costs was presented.

• Nuclear Engineering and Technology
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• v.40 no.7
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• pp.615-624
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• 2008

In this paper, the contribution of task types and error types involved in the human-related unplanned reactor trip events that have occurred between 1986 and 2006 in Korean nuclear power plants are analysed in order to establish a strategy for reducing the human-related unplanned reactor trips. Classification systems for the task types, error modes, and cognitive functions are developed or adopted from the currently available taxonomies, and the relevant information is extracted from the event reports or judged on the basis of an event description. According to the analyses from this study, the contributions of the task types are as follows: corrective maintenance (25.7%), planned maintenance (22.8%), planned operation (19.8%), periodic preventive maintenance (14.9%), response to a transient (9.9%), and design/manufacturing/installation (6.9%). According to the analysis of the error modes, error modes such as control failure (22.2%), wrong object (18.5%), omission (14.8%), wrong action (11.1 %), and inadequate (8.3%) take up about 75% of the total unplanned trip events. The analysis of the cognitive functions involved in the events indicated that the planning function had the highest contribution (46.7%) to the human actions leading to unplanned reactor trips. This analysis concludes that in order to significantly reduce human-induced or human-related unplanned reactor trips, an aide system (in support of maintenance personnel) for evaluating possible (negative) impacts of planned actions or erroneous actions as well as an appropriate human error prediction technique, should be developed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.279-289
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• 1998

This study deals with the schemes of design, plan and operate maintenance management support systems and with the engineering approach for the solutions to build the maintenance management for the production efficiency. Maintenance Management Information System(MMIS) is the task that must focus on machinery historical data and planned maintenance action. Also the efficient supporting system in a maintenance management is achieved by database which is based on process of machinery's failure history. Designing method of maintenance management information system, maintenance modules are consisted of six factors ; machinery's historical data, lubrication control, check sheet, repair work, availability report, and performance report(control board and detailed reports), and then operators can rapidly utilize data in work place. In the implementation of designed model, program coding has been developed by Visual Basic 3.0. Data insertion, deletion and updating which perform menu screen is implemented by reading data from database. Implementation model based on LAN environment and related data is stored in Microsoft DBMS.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.261-267
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• 2010

Present maintenance of a high speed railway is after the fack maintenance that executes a task when measured value goes over threshold value except some planned maintenance. It is difficult from efficient management of maintenance human resource and equipment commitment because it is difficult to predict quantity of maintenance targets. Corrective maintenance is pushed back on the repair priority of other target to need repair and it is exceeded repair cost potentially. For safety and dependable track management because track deterioration prediction is linked directly with track's life and safety of train service, it is very important that track management be based on preventive maintenance. In this study, we propose statistics model of track quality to use track inspection data and forecast model for track deterioration prediction.

• Journal of Korean Critical Care Nursing
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• v.15 no.3
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• pp.88-100
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• 2022

Purpose : This study aimed to identify risk factors for unplanned reintubation after planned extubation and to analyze the clinical outcomes in patients admitted to the intensive care unit after cardiac surgery. Methods : The study examined patients who underwent intubation and planned extubation admitted to the intensive care unit after cardiac surgery between January 1, 2017, and December 31, 2021. The reintubation group comprised 58 patients underwent unplanned reintubation within 7 days of planned extubation. The maintenance group comprised 116 patients who did not undergo reintubation and were matched with the reintubation group using the rational for matching criteria. Data were collected retrospectively from electronic medical records. We used the independent t-test, Mann-Whitney U test, 𝑥²-test, Fisher's exact test, and logistic regression analysis with SPSS/WIN 27.0. Results : The multivariate logistic regression analysis demonstrated that albumin (odds ratio [OR]=0.38, 95% confidence interval [CI]=0.20-0.72), surgery time (OR=1.54, 95% CI=1.20-1.97), PaO₂ before extubation (OR=0.85 per 10 mmHg, 95% CI=0.75-0.97), postoperative arrhythmia (OR=2.82, 95% CI=1.22-6.51), reoperation due to bleeding (OR=4.65, 95% CI=1.27-17.07), and postoperative acute renal failure (OR=2.97, 95% CI=1.09-8.04) were risk factors for unplanned reintubation. The reintubation group had a higher in-hospital mortality rate (𝑥²=33.74, p<.001), longer intensive care unit stay (Z=-7.81, p<.001), and longer hospital stay than the maintenance group (Z=-8.29, p<.001). Conclusion : These results identified risk factors and clinical outcomes of unplanned reintubation after planned extubation after cardiac surgery. These findings should be considered when developing and managing an intervention program to prevent and reduce the incidence of unplanned reintubation.

• Korean Journal of Computational Design and Engineering
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• v.20 no.3
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• pp.281-290
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• 2015

The specific goal of the SMS (Ship Management System) is to increate ship safety and decrease maintenance fee. Equipment of ship is managed by PMS (Planned Management System), subsystem of SMS. But hull has not managed by ship manager. So, the Classes have developed the system for hull maintenance. Recently, the ship maintenance system has been developed for satisfying operator's requirements such as managing maintenance data as integrated platform, intuitive manipulation and design for ease of use. To reflect such requirement, 3D Model based maintenance system was introduced for ship in operation stage. Hull items that have to be inspected, repaired, replaced, are stored in integrated data platform with drawing, reports, and etc. and completely linked to 3D product Model. This system is specially developed for measurement and maintenance of hull thickness.