• IE interfaces
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• v.16 no.1
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• pp.27-33
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• 2003

The maintenance cost in K Steelworks has been continuously increased in proportion to the production cost. However, there seems to be a possibility of reducing cost through the optimization of maintenance actions. The failure types of the equipment in steelworks ate various with different failure cost. Thus the failure rate and cost of each type of failures should be considered simultaneously when the optimum maintenance period is to be determined. It is considered that the equipment undergoes periodic replacement and a specified number of incomplete preventive maintenance actions are performed during a replacement period. Assuming that the time to failure follows a Weibull distribution, the parameters of the failure rate are estimated using the maximum likelihood estimation. The optimal replacement period is determined to minimize the average cost per unit time. As the result of analysis it is suggested that the existing maintenance period for a hot-rolling equipment can be extended significantly.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.1545-1546
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• 2011

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.2
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• pp.248-253
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• 2007

Traditional time based preventive maintenance is used to constant maintenance interval for equipment life. In order to consider economic aspect for time based preventive maintenance, preventive maintenance is scheduled by RCM(Reliability-Centered Maintenance) evaluation. So, Markov state model is utilized considering stochastic state in RCM. In this paper, a Markov state model which can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by a Markov model. In case study, simulation results about RCM are used to the real historical data of combustion turbine generating units in Korean power systems.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.357-361
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• 2022

Employing the available technologies and utilizing the advanced means to improve the level of health care provided to citizens in their various locations. Citizens have the right to get a proper health care services despite the location of their residency or the distance from the health care delivery centers, a goal that can be achieved by utilizing air ambulance systems. In such systems, aircrafts and their life spans are the essential component, the flight duration of the aircraft during its life span is determined by the maintenance schedule. This research, enhances the air ambulance systems by presenting a proposal that maximizes the aircraft flight duration during its life span. The enhancement will be reached by developing a set of algorithms that handles the aircraft maintenance problem. The objective of these algorithms is to minimize the maximum completion time of all maintenance tasks, thus increasing the aircraft operation time. Practical experiments performed to these algorithms showed the ability of these algorithms to achieve the desired goal. The developed algorithms will manage the maintenance scheduling problem to maximize the uptime of the air ambulance which can be achieved by maximizing the minimum life of spare parts. The developed algorithms showed good performance measures during experimental tests. The 3LSL algorithm showed a higher performance compared to other algorithms during all performed experiments.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.651-656
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• 2006

Wu and Clements-Croome (2005) investigate the optimization problem of PM policies for situations where the quality of PM is a random variable with a certain probability distribution. However, they assume that the cost of preventive maintenance is constant, not depending on the quality of PM. Thus, this paper considers a periodic PM model when PM cost depends on the quality of PM activity. The optimal PM policy are presented for the extended PM model and the numerical examples are presented for illustrative purpose.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.3
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• pp.507-512
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• 2017

Recently, more electric power facilities have been miniaturized and it is noted that the facilities maintenance will be essential through operation optimization. In this paper we applied and examined the operation optimization of electric power facilities by applying Matrix system which can improve reliability to minimize outage and recover failure rapidly when blackouts happen at 25.8kV Gas Insulated Switchgear(GIS). The fundamental problem for facilities maintenance of GIS can happen due to indeterminable internal state in real time. Matrix optimization organizes action states in all containers which contain pressurized $SF_6$ Gas such as circuit breaker, disconnector switch, bus for utilizing them each area. Then, we connect it with power system to monitor and control internal state remotely in real time, and we can minimize blackout zone or outage. Considering above process, we improved stability of overall facilities.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.4
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• pp.217-224
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• 2003

The objective of this paper is to suggest the technique of program to perform structural optimization design after reliability analysis to consider the uncertainties of structural reponses. AFOSM method is used for reliability analysis then, structural optimization design is developed for 10-bar truss and 3 span 10 stories planar frame model is subject to reliability indices and probability of failure by reliability analysis. SQP method is used for optimization design method, this method has many attractions. As a result of analyzing with having and not having constraints and uncertainty, the minimum weight of truss and planar frame increased respectively 20.92% and average 8.08%.

• Proceedings of the Korean Nuclear Society Conference
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• 1999.05a
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• pp.197-197
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• 1999

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.357-359
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• 2006

Traditional time based preventive maintenance is used to constant maintenance interval for equipment life. In order to consider economic aspect for time based preventive maintenance, preventive maintenance is scheduled by RCM(Reliability-Centered Maintenance) evaluation. So, Markov state model is utilized considering stochastic state in RCM. In this paper, a Markov state model which can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by a Markov model. In case study, simulation results about RCM are used to the real historical data of combustion turbine generating units in Korean power systems.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.8
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• pp.477-483
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• 2004

In competitive electricity markets, maintenance schedule is submitted by generation companies (GENCOs) and transmission companies (TRANSCOs), and coordinated by Independent System Operator (ISO) with the adequacy criterion. This paper presents an alternative coordination procedure by ISO on the maintenance schedule. In this paper, it is focused on modeling a coordination algorithm by ISO for the maintenance schedule based on the Simulated Annealing algorithm. The proposed model employs the minimum information such as generator capacity, forced outage rate and generator maintenance schedules. The objective function of this model represents minimization of adjustment on schedules submitted by GENCOs.