• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.41-52
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• 2020

This paper investigates the stress-reducing preventive maintenance model through numerical experiments. The preventive maintenance model is used to analyze the relationship between related conditions and variables to gain insight into the efficient operation of the system when performing preventive maintenance in real-world situations. Various preventive maintenance models have been developed over the past decades and their complexity has increased in recent years. Increasing complexity is essential to reflect reality, but recent models can only be interpreted through numerical experiments. The stress-reducing preventive maintenance is a newly introduced preventive maintenance concept and can only be interpreted numerically due to its complexity, and has received little attention because the concept is unfamiliar. Therefore, for information purposes, this paper investigates the characteristics of the stress-reducing preventive maintenance and the relationship between parameters and variables through numerical experiments. In particular, this paper is focusing on the economic feasibility of stress-reducing preventive maintenance by observing changes in the optimal preventive maintenance period in response to changes in environmental stress and the improvement factor. As a result, when either the environmental stress or the improve effect of stress-reducing preventive maintenance is low, it is not necessary to carry out the stress-reducing preventive maintenance at excessive cost. In addition, it was found that the age reduction model is more economical than the failure rate reduction model.

• Journal of Applied Reliability
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• v.18 no.2
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• pp.104-113
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• 2018

Purpose: This paper proposes the non-periodic preventive maintenance policy based on the level of cumulative hazard intensity. We aim to construct a cost-effectiveness on the proposed model with relaxing the constraint on reliability. Methods: We use the level of cumulative hazard intensity as a condition variable, instead of reliability. Such a level of cumulative hazard intensity can derive the reliability which decreases as the frequency of preventive maintenance action increases. We also model the imperfect preventive maintenance action using the proportional age setback model. Conclusion: We provide a numerical example to illustrate the proposed model. We also analyze how the parameters of our model affect the optimal preventive maintenance policy. The results show that as long as high reliability is guaranteed, the inefficient preventive maintenance action is performed reducing the system operation time. Moreover, the optimal value of the proposed model is sensitive to changes in preventive maintenance cost and replacement cost.

• Journal of Applied Reliability
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• v.12 no.2
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• pp.57-66
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• 2012

In this paper, we consider the periodic preventive maintenance model for a repairable system following the expiration of replacement-repair warranty. Under this preventive maintenance model, we derive the expressions for the expected cycle length, the expected total cost and the expected cost rate per unit time. Also, we determine the optimal preventive maintenance period and the optimal preventive maintenance number by minimizing the expected cost rate per unit time. Finally, the optimal periodic preventive maintenance policy is given for Weibull distribution case.

• International Journal of Reliability and Applications
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• v.9 no.1
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• pp.113-122
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• 2008

In this paper, we consider a periodic preventive maintenance policy in which each preventive maintenance reduces the hazard rate of amount proportional to the failure intensity, which increases since the system started to operate. And the effect of preventive maintenance at each preventive maintenance epoch is different. The expected cost rate per unit time for the proposed model is obtained. We discuss the optimal number N of the periodic preventive maintenance and the optimal period x, which minimize the expected cost rate per unit time and obtain the optimal preventive maintenance schedule for given cost structures of the model. A numerical example is given for the purpose of illustrating our results when the failure time distribution is Weibull distribution.

• Journal of Applied Reliability
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• v.16 no.4
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• pp.313-322
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• 2016

Purpose: We introduce ways to employ Markov chain model to evaluate the effect of preventive maintenance process. While the preventive maintenance process decreases the failure rate of each subsystems, it increases the downtime of the system because the system can not work during the maintenance process. The goal of this paper is to introduce ways to analyze this trade-off. Methods: Markov chain models are employed. We derive the availability of the system consisting of N repairable subsystems by the methods under various maintenance policies. Results: To validate our methods, we apply our models to the real maintenance data reports of military truck. The error between the model and the data was about 1%. Conclusion: The models developed in this paper fit real data well. These techniques can be applied to calculate the availability under various preventive maintenance policies.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1305-1310
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• 2008

Traditional maintenance planning is based on a constant maintenance interval for equipment life. In order to consider economic aspect for time based preventive maintenance, preventive maintenance is desirable to be scheduled by RCM(Reliability-Centered Maintenance) evaluation. The main objective of RCM is to reduce the maintenance cost, by focusing on the most important functions of the system and avoiding or removing maintenance actions that are not strictly necessary. 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 the stepwise Markov model in detail. Also, because the system is not continuously monitored, the inspection is considered. In case study, simulation results about RCM will be shown using the real historical data of combustion turbine generating unit in Korean power systems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.24-31
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• 2018

As a system complexity increases and technology innovation progresses rapidly, leasing the equipment is considered as an important issue in many engineering areas. In practice, many engineering fields lease the equipment because it is an economical way to lease the equipment rather than to own the equipment. In addition, as the maintenance actions for the equipment are costly and need a specialist, the lessor is responsible for the maintenance actions in most leased contract. Hence, the lessor should establish the optimal maintenance strategy to minimize the maintenance cost. This paper proposes two periodic preventive maintenance policies for the leased equipment. The preventive maintenance action of policy 1 is performed with a periodic interval, in which their intervals are the same until the end of lease period. The other policy is to determine the periodic preventive maintenance interval minimizing total maintenance cost during the lease period. In addition, this paper presents two decision-making models to determine the preventive maintenance strategy for leased equipment based on the lessor's preference between the maintenance cost and the reliability at the end of lease period. The structural properties of the proposed decision-making model are investigated and algorithms to search the optimal maintenance policy that are satisfied by the lessor are provided. A numerical example is provided to illustrate the proposed model. The results show that a maintenance policy minimizing the maintenance cost is selected as a reasonable decision as the lease term becomes shorter. Moreover, the frequent preventive maintenance actions are performed when the minimal repair cost is higher than the preventive maintenance cost, resulting in higher maintenance cost.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.99-106
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• 1999

This paper considers an imperfect repair model for which the repairable system is maintained preventively at periodic times and is replaced by a new system when a predetermined number of preventive maintenance has been applied. our main objective of this is to determine the optimal number of preventive maintenances before the system is replaced and the optimal length of interval between two consecutive preventive maintenances under a new repair model which is referred to as an ineffective preventive maintenance. Such a model assumes a periodic preventive maintenance in which the system is effectively maintained with a certain probability. Otherwise the system is not improved at all after each maintenance and thus the failure rate remains the same as before. The criteria to determine the optimal number of preventive maintenances and length of period is the expected cost rate per unit time for an infinite time span. We give the explicit expressions for the expected cost rate per unit time. Some numerical examples are presented for illustrative purposes.

• Korean Management Science Review
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• v.13 no.3
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• pp.163-172
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• 1996

According to flying hours, aircraft engines require regular overhaul for preventive maintenance. Because of hostile defense environment of Republic of Korea, the aircraft of republic of Korea Air Force(ROKAF) have been operated at the maximum level of availability and have similar overhaul schedule in several months. The concentration of overhaul schedule in a short period demands additional spare engines far exceeding the spare engines for corrective maintenance. If ROKAF decides to purchase extra engines for the preventive maintenance, the extra engines will be used only for the preventive maintenance and will be excess inventory for the most of aircraft life ccle. Also, the procurement of extra engines is significant investment for ROKAF. To help ROKAF schedule the preventive maintenance without significant spending, this study develops a dynamic programming model that is solvable using an integer programming algorithm. The model provides the number of engines that should be overhauled for a month for multiple periods under given constraints. ROKAF actually used this model to solve a T-59 engine overhaul problem and saved about three billion won at one time. ROKAF plans to use this model continuously for T-59 and other weapon systems. Thus, saving for long term will be significant to ROKAF. Finally, with minor modification, this model can be applied to deciding the minimum number of spare engines for preventive maintenance.