• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2007.05a
• /
• pp.224-228
• /
• 2007

It is focused on a methodology to establish a optimal inspection cycle of electrical facility of railroad Decision method of optimal inspection cycle is a process which establishes maintenance plan for facilities' immanent function as using reliability theory in operation term In order to ensure normal operation in a given condition, the decision method is logical for selecting effective maintenance plan to consider characteristic of system In estimation of failure rate, critical facility is selected firstly. After that, proper distribution function on each facility is decided to investigate distribution function for extraction of failure rate. Next, cost produced by the case that facility's failure is occurred is surveyed. Finally, maintenance method developed until now is investigated, before suitable model for the facility applying maintenance method is developed, and that maintenance decision is made. Therefore, this process is the method to find optimal inspection cycle for reasonable cost and effective reliability on facility.

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.559-561
• /
• 1995

The cogeneration system has a strong merit in providing thermal and electrical energy simultaneously. Nowadays, cogeneration system is widely used in the point of efficient use of the energy resources And the installation of the system is expected to be greatly increased in each year. So, we need to develop an optimal operation planning for those systems. In this paper, we are used to result what studed at the my power system of room because it is in order to solve maintenance scheduling problem. Also we added a constraints to the proposed maintenance model for optimal maintenance rate. In the case study, we construct an multi-machine generated example system which operated in topping cycle, and calculate the yearly optimal production cost, marginal maintenance cost, and maintenance scheduling of the example system respectively.

• Journal of Applied Reliability
• /
• v.17 no.3
• /
• pp.246-255
• /
• 2017

Purpose: This study proposes the optimal PM (preventive maintenance) policy of leased equipment for lessee's decision-making using two types of reliability condition. Methods: We consider reliability threshold based PM model. Equipment reliability is estimated and used as condition variable. The effect of repair for maintenance is imperfect and represented by age reduction factor. Results: We provide two PM policies. Policy 1 is focused on minimized total cost. This policy guarantees reliability threshold until last maintenance action. Policy 2 focus on maintaining reliability threshold during leased period. The proposed approach provides optimal reliability threshold under number of PM. Through result, we finally construct decision-making process for lessee using reliability threshold and end of reliability. Conclusion: This study provides two PM policy for lessee's decision-making. Through numerical example, we get a result of optimal reliability threshold, number of PM, optimum alternative under lessee's reliability condition.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.3
• /
• pp.1853-1862
• /
• 2015

Naval maintenance system carries out repairs of battle ships. Korean Navy has four maintenance stations to maximize the readiness of the battle ships. Since each station can provide different services according to characteristics(specific size of ships, type of maintenances) and the maintenance ability of stations is predetermined, it has been one of complex problems for the Korean Navy to find the optimal resource allocation. We investigate the operation of the stations from the perspective of the human resource allocation which plays crucial role in the performance of the maintenance stations. Using a queueing model and optimization technique, we present a way to derive the optimal personnel allocation which minimize the waiting number of battle ships at each station, leading to the improvement of the military readiness in the Korean Navy.

• Proceedings of the Korean Reliability Society Conference
• /
• 2005.06a
• /
• pp.115-120
• /
• 2005

This paper introduces models for preventive maintenance policies and considers periodic preventive maintenance policy with minimal repair when the failure of system occurs. It is assumed that minimal repairs do not change the failure rate of the system. The failure rate under prevention maintenance received an effect by a previously prevention maintenance and the slope of failure rate increases the model where it considered. Also the start point of failure rate under prevention maintenance considers the degradation of system and that it increases quotient, it assumed. Per unit time it bought an expectation cost from under this prevention maintenance policy. We obtain the optimal period time and the number for the periodic preventive maintenance by using Nakagawa's Algorithm, which minimizes the expected cost rate per unit time. Finally, it suppose that the failure time of a system has a Weibull distribution as an example and we obtain an expected cost rate per unit time the optimal period time and the number when cost of replacement and cost of minimal repair change.

• Journal of Korean Society for Quality Management
• /
• v.47 no.1
• /
• pp.87-96
• /
• 2019

Purpose: The purpose of this paper is to determine an optimal production time for economic production quantity model with preventive maintenance and random defective rate as the function of a machinery deteriorates. Methods: If a machinery shifts from "in-control" state to "out-of-control" state, a proportion of defective items being produced increases. It is assumed that time to state shift is a random variable and follows an arbitrary distribution. The elapsed time until process shift decreases stochastically as a production cycle repeats and quasi-renewal process is used to implement for production facilities to deteriorate. Results: When the exponential parameter for exponential distribution increases, the optimal production time increases. When Weibull distribution is considered, the optimal production time is closely affected by the shape parameter of Weibull distribution. Conclusion: A mathematical model is suggested to find optimal production time and optimal number of production cycles and numerical examples are implemented to validate the patterns for changes of optimal times under different parameters assumptions. The real application is implemented using the proposed approach.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1997.10a
• /
• pp.193-196
• /
• 1997

In this paper we consider a Bayesian theoretic approach to periodic incomplete preventive maintenance with minimal repair at failure. We assume that the system failure rate is increasing as the frequency of PM increases and that the system is replaced at the K-th PM under this maintenance strategy. The optimal policies which minimize the expected cost rates are discussed. We seek the optimal periodic PM interval x and replacement time K under a Weibull failure intensity. Assuming suitable prior distribution for the Weibull parameters, we derive the posterior distribution incorporating failure data and obtain the updated optimal replacement strategies.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.2
• /
• pp.338-346
• /
• 2016

In order for the optimal solution of generators’ annual maintenance scheduling to be applicable to the actual power system it is crucial to incorporate the constraints related to the equivalent operation hours (EOHs) in the optimization model. However, most of the existing researches on the optimal maintenance scheduling are based on the assumption that the maintenances are to be performed periodically regardless of the operation hours. It is mainly because the computation time to calculate EOHs increases exponentially as the number of generators becomes larger. In this paper an efficient algorithm based on demand grouping method is proposed to calculate the approximate EOHs in an acceptable computation time. The method to calculate the approximate EOHs is incorporated into the optimization model for the maintenance scheduling with consideration on the EOHs of generators. The proposed method is successfully applied to the actual Korean power system and shows significant improvement when compared to the result of the maintenance scheduling algorithm without consideration on EOHs.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.45 no.3
• /
• pp.18-30
• /
• 2022

Predicting remaining useful life (RUL) becomes significant to implement prognostics and health management of industrial systems. The relevant studies have contributed to creating RUL prediction models and validating their acceptable performance; however, they are confined to drive reasonable preventive maintenance strategies derived from and connected with such predictive models. This paper proposes a data-driven preventive maintenance method that predicts RUL of industrial systems and determines the optimal replacement time intervals to lead to cost minimization in preventive maintenance. The proposed method comprises: (1) generating RUL prediction models through learning historical process data by using machine learning techniques including random forest and extreme gradient boosting, and (2) applying the system failure time derived from the RUL prediction models to the Weibull distribution-based minimum-repair block replacement model for finding the cost-optimal block replacement time. The paper includes a case study to demonstrate the feasibility of the proposed method using an open dataset, wherein sensor data are generated and recorded from turbofan engine systems.

• Journal of the Korean Society for Railway
• /
• v.12 no.2
• /
• pp.291-301
• /
• 2009

This paper presents the optimal design and analysis method of the train overhaul maintenance facility based on the simulation. Because the train is composed of a coach or more, we design the simulation model after analyzing the operation of train into train, coach, coach's body parts and wheel parts and soon. In simulation analysis, we consider the critical (dependent) factors and design (independent) parameters for the selection of alternatives and optimal design. Therefore, Multi Criteria Decision Making (MCDM) is proposed for the selection of alternatives and optimal method in order to find the optimal design factors. The case study for the above approach is used for the electronic locomotive overhaul maintenance facility. This paper provides a comprehensive framework for the train overhaul maintenance facility design using the simulation, MCDM and optimal methods. Therefore, the method developed for this research can be adopted for other enhancements in different but comparable situation.