• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.826-828
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• 1996

Genetic Algorithm(GA) is a searching or optimizing algorithm based on natural evolution principle. GA has demonstrated considerable success in providing good solutions to many nonlinear, multi-dimensional optimization problems. The preventative maintenance scheduling is a kind of dynamic optimization problem with constraints. This paper applies GA to the preventative maintenance scheduling problem. In the case study, we can get the preventative maintenance scheduling of 3-generators during 8 weeks using GA. It is shown that GA can be available to the preventative maintenance scheduling problem.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.9
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• pp.1331-1338
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• 2010

Recently, the need for improving the economical efficiency of pumped-storage power plants has increased because of the decrease in the availability of electricity caused by an increase in the consumption of electricity at night. Therefore, a preventative maintenance cycle, especially an overhaul cycle, is required. Unconditional extension cannot be implemented because it may cause unanticipated failures due to insufficient maintenance. Therefore, in this study, a methodology for optimizing the preventative maintenance cycle by taking into account both reliability and economical efficiency is presented; this methodology has been developed by reviewing previous studies on reliability and considering the characteristics of pumped-storage power plants. Finally, an extended overhaul cycle is derived by applying this methodology to a domestic pumped-storage power plant.

• The monthly packaging world
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• s.323
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• pp.77-82
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• 2020

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.359-360
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• 2008

765kV변전소의 운전 조건을 고려하여 유지보수(CBM) 기법을 활용한 예방진단시스템을 이용해 변전기기를 정비한 사례를 통하여 예방진단시스템의 운영실태를 살펴보고, 고장원인 및 고장설비를 더욱 정확히 구분할 수 있어 관계자에게 보다 신뢰성있는 시스템이 될 수 있도록 대안을 모색하며 향후 진단 및 감시항목을 더 발굴하기 위한 예방진단 시스템을 제도화 할 필요가 있다.

• Journal of Welding and Joining
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• v.29 no.2
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• pp.13-20
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• 2011

• Journal of Applied Reliability
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• v.16 no.3
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• pp.224-230
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• 2016

Purpose: Military maintenance involves corrective and preventive actions carried out to keep a system in or restore it to a predetermined condition. This research develops an optimal maintenance cycle for aviation oil testing equipment with acceptable reliability level and minimum maintenance cost. Methods: The optimal maintenance policy in this research aims to satisfy the desired reliability level at the lowest cost. We assume that the failure process of equipment follows the power law non-homogeneous Poisson process model and the maintenance system is a minimal repair policy. Estimation and other statistical procedures (trend test and goodness of fit test) are given for this model. Results: With time varying failure rate, we developed reliability-based maintenance cost optimization model. This model will reduce the ownership cost through adopting a proactive reliability focused maintenance system. Conclusion: Based on the analysis, it is recommended to increase the current maintenance cycle by three times which is 0.5 year to 1.5 years. Because of the system's built-in self-checking features, it is not expected to have any problems of preventative maintenance cycle.

• Smart Structures and Systems
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• v.30 no.6
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• pp.571-582
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• 2022

Optimal life-cycle management is a challenging issue for deteriorating regional bridges. Due to the complexity of regional bridge structural conditions and a large number of inspection and maintenance actions, decision-makers generally choose traditional passive management strategies. They are less efficiency and cost-effectiveness. This paper suggests a deep reinforcement learning framework employing double-deep Q-networks (DDQNs) to improve the life-cycle management of deteriorating regional bridges to tackle these problems. It could produce optimal maintenance plans considering restrictions to maximize maintenance cost-effectiveness to the greatest extent possible. DDQNs method could handle the problem of the overestimation of Q-values in the Nature DQNs. This study also identifies regional bridge deterioration characteristics and the consequence of scheduled maintenance from years of inspection data. To validate the proposed method, a case study containing hundreds of bridges is used to develop optimal life-cycle management strategies. The optimization solutions recommend fewer replacement actions and prefer preventative repair actions when bridges are damaged or are expected to be damaged. By employing the optimal life-cycle regional maintenance strategies, the conditions of bridges can be controlled to a good level. Compared to the nature DQNs, DDQNs offer an optimized scheme containing fewer low-condition bridges and a more costeffective life-cycle management plan.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.6
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• pp.421-428
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• 2015

An important trend in the sustainment of military aircraft is the transition from preventative maintenance to condition based maintenance (CBM). For CBM, it is essential that the actual system condition can be measured and the measured condition can be reliably extrapolated to a convenient moment in the future in order to facilitate the planning process while maintaining flight safety. Much research effort is currently being made for the development of technologies that enable CBM, including structural health monitoring (SHM) systems. Great progress has already been made in sensors, sensor networks, data acquisition, models and algorithms, data fusion/mining techniques, etc. However, the transition of these technologies into service is very slow. This is because business cases are difficult to define and the certification of the SHM systems is very challenging. This paper describes a possibility for fielding a SHM system on legacy military aircraft with a minimum amount of certification issues and with a good prospect of a positive return on investment. For appropriate areas in the airframe the application of SHM will reconcile the fail-safety and slow crack growth damage tolerance approaches that can be used for safeguarding the continuing airworthiness of these areas, combining the benefits of both approaches and eliminating the drawbacks.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.325-336
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• 2005

Mobile ad hoc networks (MANET) are composed of moving wireless hosts which, within range of each other, form wireless networks. For communication to occur between hosts that are not within each other's range, routes involving intermediate nodes must be established; however, since the hosts may be in motion, a host that was part of a route may move away from its upstream and downstream partners, thus breaking the route. In this paper, we propose anticipated route maintenance (ARM) protocol with two extensions to route discovery based routing scheme: Extend the route when nodes on a link move apart from each other and they have common neighbor that can be 'inserted' in the path, and shrink route when a node discovers that one of its neighbor which is not the next hop is also on the same route several hops later on. By utilizing only local geographic information (now a part of some route finding algorithms), a host can anticipate its neighbor's departure and, if other hosts are available, choose a host to bridge the gap, keeping the path connected. We present a distributed algorithm that anticipates route failure and performs preventative route maintenance using location information to increase a route lifespan. The benefits are that this reduces the need to find new routes (which is very expensive) and prevents interruptions in service. As the density of nodes increases, the chance to successfully utilize our route maintenance approach increases, and so does the savings. We have compared the performance of two protocols, pure dynamic source routing (DSR) protocol and DSR with ARM. The simulation results show how ARM improves the functionality of DSR by preventing the links in the route from breaking. Packets delivery ratio could be increased using ARM and achieved approximately $\100%$ improvement. The simulations clarify also how ARM shows a noticeable improvement in dropped packets and links stability over DSR, even though there is more traffic and channel overhead in ARM.

• International Journal of Railway
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• v.1 no.3
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• pp.83-88
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• 2008

Since the 1990's the fleet of the Dutch Railways showed a dramatic decrease in wheel tyre life. This lifetime reduction led to an unacceptable increase in life cycle costs. Therefore Lloyd's Register Rail has proposed to NedTrain to investigate the possibilities of improving the wheel tyre life. Three improvements were determined as most promising and relatively easy to achieve: - Profile optimisation for Rolling Contact Fatigue (RCF) reduction - a new wheel profile has been developed with a better resistance against rolling contact fatigue of the wheel tread. The profile has been implemented on single deck intercity trains and shows an increase in wheel tyre life of 30%. - Selection of improved wheel tyre materials - combining information from literature and experiences of manufacturers five alternative wheel tyre materials have been selected and are now being tested in practice. - Optimisation of the maintenance strategy - an alternative, preventative maintenance regime has been developed. With this Scraping regime, during short term maintenance every wheel is reprofiled. Higher mileages are reached and savings on life cycle costs up to 50% and more have been achieved. Unplanned maintenance goes down with $30{\sim}60%$. The results from field tests, using a reference group for comparison, and preliminary results after implementation show that the increase in wheel tyre life that is achieved with this project is significant. The results will continue to be monitored using the asset management tool 'Wheel Watch', that was specially developed for this project and is also described in this paper.