• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.11
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• pp.476-484
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• 2006

The failure prediction and preventive maintenance for the equipment of nuclear power plant area using reliability-centered maintenance have been grown. On the other hand, the maintenance for power distribution system consists of time-based maintenance mainly. In this paper, the new maintenance algorithms for power distribution system are developed considering reliability indices. First of all, Time-varying failure rates are extracted from data accumulated at KEPCO using exponential distribution function and weibull distribution function. Next, based on the extracted failure rate, reliability for real power distribution system is evaluated for applying the effective maintenance algorithm which is the analytic method deciding the maintenance point of time and searching the feeder affecting the specific customer. Also the algorithm deciding the maintenance priority order are presented based on sensitivity analysis and equipment investment plan are analyzed through the presented algorithm at real power distribution system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.7
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• pp.869-874
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• 2019

Performing preventive maintenance on a system reduces unexpected downtime caused by system aging and increases its availability. In general, preventive maintenance can be largely divided into two broad categories: time-based maintenance policy and condition-based maintenance policy. In the time-based maintenance policy the preventive maintenance is triggered at scheduled time epochs with fixed time intervals, while in the condition-based maintenance policy the preventive maintenance is performed when system state is checked to satisfy a specific condition. Condition-based maintenance has some benefits in improving maintenance efficiency, compared to time-based one. This paper presents a stochastic model for analyzing a system with condition-based preventive maintenance, where the preventive maintenance is performed after a random time since the system aging occurs, and provides an analytical solution for the steady-state availability and the corresponding profit.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.6 no.1
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• pp.1-8
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• 2010

The existing maintenance program is focused on time-based maintenance to inspect and repair components according to maintenance period, rather than condition-based maintenance or predictive maintenance. The preventive maintenance template of the steam turbine has been developed for optimizing maintenance procedure and improving reliability and availability of the steam turbine of nuclear power plants based on EPRI PM template methodology and EPRI technical reports about preventive maintenance.

• Journal of the Korean Society of Safety
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• v.21 no.4 s.76
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• pp.25-32
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• 2006

LonWorks over IP(LonWorks-IP) virtual device network(VDN) is an integrated form of LonWorks device network and IP data network. In especially real-time distributed servo applications on the factory floor, timely response is essential for predictive and preventive maintenance. The time delay in servo control on LonWorks-IP based VDN has highly stochastic nature. LonWorks-IP based VDN induced transmission delay deteriorates the performance and stability of the real-time distributed control system and can't give an effective preventive and predictive maintenance. In order to guarantee the stability and performance of the system, and give an effective preventive and predictive maintenance, LonWorks-IP based VDN induced time-varying uncertain time delay needs to be predicted and compensated. In this paper new Pill control scheme based on Smith predictor, disturbance observer and band pass filter is proposed and tested through computer simulation about position control of DC servo motor. It is shown that how can the proposed control scheme be designed to minimize the effects of uncertain varying time delay and model uncertainties. The validity of the proposed control scheme is compared and demonstrated with the comparison of internal model controllers(IMC) based on Smith predictor with and without disturbance observer.

• International Journal of Safety
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• v.5 no.2
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• pp.6-11
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• 2006

The time delay in servo control on LonWorks/IP Virtual Device Network (VDN) is highly stochastic in nature. LonWorks/IP VDN induced time delay deteriorates the performance and stability of the real-time distributed control system and hinders an effective preventive and predictive maintenance. Especially in real-time distributed servo applications on the factory floor, timely response is essential for predictive and preventive maintenance. In order to guarantee the stability and performance of the system for effective preventive and predictive maintenance, LonWorks/IP VDN induced time delay needs to be predicted and compensated for. In this paper position control simulation of DC servo motor using Zero Phase Error Tracking Controller (ZPETC) as a feedforward controller, and Internal Model Controllers (IMC) based on Smith predictor with disturbance observer as a feedback controller is performed. The validity of the proposed control scheme is demonstrated by comparing the IMC based on Smith predictor with disturbance observer.

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.1-9
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• 2001

To keep an enterprise's competitiveness on the condition of the automatic manufacturing system such as FA, FMS and CIM, all the maintenance problems should be considered seriously In not only in production and maintenance but also in related industrial safety. As we analyze in the surveys the maintenance management of domestic enterprises and the causes of Industrial accident, there will be necessity of drawing up countermeasures for preventing industrial accidents and for ensuring expertise maintenance technologies. Based on these analyses, the safety information system, maintenance management information system, and the machinery condition diagnosis technique are studied by using of the knowledge-based system under the real-time computer-operating environment and using fuzzy linguistic variable. This computer system based knowledge-based diagnosis can easily provide not only the knowledge of expert system about deterioration phenomenon of industrial robots, but also the knowledge of relating safety and facility all the time. Therefore, it is expected to improve the efficiency of business processes in the production and safety when we use this system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.30
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• pp.73-79
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• 1994

This paper propose Adaptive Maintenance as a new type of maintenance for machine failures which are unpredictable. A purpose of adpative maintenance is to decrease inconsistency. In order to pick up some of problems the traditional maintenance policy, We discussed Time Based Maintenance(TBM) and Condition Based Maintenance(CBM) with Bath-Tub Curve. By using Machine Condition Diagnosis Technique (CDT), Monitored condition maintenance deals with the dynamic decision making for diagnosis procedures at maintenance and caution level. Adaptive Maintenance is a powerful tool for Total Production Maintenance(TPM).

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1989-1992
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• 2009

Maintenance is classified preventive maintenance before performing equipment failure and corrective maintenance after performing equipment failure. In preventive maintenance, we may analyze the failure data to end from beginning of equipment and allocate maintenance method and calculate maintenance cycle quantitatively by the failure data analysis. So, it has a merit to reduce system maintenance cost and to operate effectively but, it require high cost in system introducing and continuous operation to end of system. In corrective maintenance, we may calculate MTTR(mean time to repair) quantitatively based on function failure time. it can be based on establishing maintenance system for operation efficiency. In this paper, we may reflect the MTTR for the onboard equipped in Tilting train to establish maintenance system for Tilting train operation efficiency.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1177-1183
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• 2013

In this paper, the analysis of inspection period bases on reliability is suggested in the field of traction power system. Even though there are several maintenance models, the most commonly used maintenance assessment has been focused on time based maintenance in real traction power systems. The maintenance intervals are selected on the basis of long-time experience. It ensures high availability and exact planning of staff. Reliability centered maintenance, which evaluates criticality and severity of each failure mode, achieves the operation, maintenance, and cost-effective improvement that will manage the risks of equipment. This paper deals with electrification in railway inspection frequency and applied reliability based inspection frequency instead of constant intervals. The distribution function of failure rate in traction power system belongs to Weibull function. Also, the fault data and the number of installed equipments for electrifications are collected. The failure history is investigated and classified in detail. Though these complicated procedures, it contribute to extend equipment lifetime and to reduce maintenance costs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.12-23
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• 2014

The O&M (Operation and Maintenance) phase of offshore plants with a long life cycle requires heavy charges and more efforts than the construction phase, and the occurrence of an accident of an offshore plant causes catastrophic damage. So previous studies have focused on the development of advanced maintenance system to avoid unexpected failures. Nowadays due to the emerging ICTs (Information Communication Technologies) and sensor technologies, it is possible to gather the status data of equipment and send health monitoring data to administrator of an offshore plant in a real time way, which leads to having much concern on the condition based maintenance policy. In this study, we have reviewed previous studies associated with CBM (Condition-Based Maintenance) of offshore plants, and introduced an algorithm predicting the next failure time of the compressor which is one of essential mechanical devices in LNG FPSO (Liquefied Natural Gas Floating Production Storage and Offloading vessel). To develop the algorithm, continuous time Markov model is applied based on gathered vibration data.