• Journal of Applied Reliability
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• v.18 no.2
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• pp.184-191
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• 2018

Purpose: The purpose of this study is to propose a method to calculate the optimal preventive maintenance cycle of radar used in the aviation weapon system of ROKAF. Methods: A hybrid model is used to estimate the optimal preventive maintenance cycle in a system that can perform condition based predictive maintenance (CBPM) through continuous diagnosis. The failure data of the radars operating in the military were used to calculate the reliability. Results: According to the research results, the reliability threshold of the radar began to decrease after 5 flights, and decreased rapidly after 12 flights. Since the second check, costs have continued to decline. Conclusion: A method is proposed to determine the cycle of optimal preventive maintenance of radar within operational budget through modeling results between reliability limit and cost for radar. The results can be used to determine the optimal preventive maintenance cycle and frequency of various avionics equipment.

• Smart Structures and Systems
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• v.4 no.5
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• pp.641-653
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• 2008

This paper proposes a practical and realistic method to establish an optimal lifetime maintenance strategy for deteriorating bridges by considering the life-cycle performance as well as the life-cycle cost. The proposed method offers a set of optimal tradeoff maintenance scenarios among other conflicting objectives, such as minimizing cost and maximizing performance. A genetic algorithm is used to generate a set of maintenance scenarios that is a multi-objective combinatorial optimization problem related to the lifetime performance and the life-cycle cost as separate objective functions. A computer program, which generates optimal maintenance scenarios, was developed based on the proposed method using the life-cycle costs and the performance of bridges. The subordinate relation between bridge members has been considered to decide optimal maintenance sequence and a corresponding algorithm has been implemented into the program. The developed program has been used to present a procedure for finding an optimal maintenance scenario for steel-girder bridges on the Korean National Road. Through this bridge maintenance scenario analysis, it is expected that the developed method and program can be effectively used to allow bridge managers an optimal maintenance strategy satisfying various constraints and requirements.

• 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.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.167-174
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• 2007

This study proposes a practical and realistic method to establish an optimal lifetime maintenance strategy for deteriorating bridges by considering the life-cycle performance as well as the life-cycle cost. The proposed method offers a set of optimal tradeoff maintenance scenarios among other conflicting objectives, such as minimizing cost and maximizing performance. A genetic algorithm is used to generate a set of maintenance scenarios that is a multi-objective combinatorial optimization problem related to the and the life-cycle cost and performance as separate objective functions. A computer program, which generates optimal maintenance scenarios, was developed based on the proposed method. The subordinate relation between bridge members has been considered to decide optimal maintenance sequence. The developed program has been used to present a procedure for finding an optimal maintenance scenario for steel-girder bridges on the Korean National Road. Through this bridge maintenance scenario analysis, it is expected that the developed method and program can be effectively used to allow bridge managers an optimal maintenance strategy satisfying various constraints and requirements.

• 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.

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

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.61-69
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• 2020

Systems such as database and socal network systems have been broadly used, and their unexpected failure, with great losses and sometimes a social confusion, has received attention in recent years. Therefore, it is an important issue to find optimal maintenance plans for such kind of systems from the points of system reliability and maintaining cost. However, it is difficult to maintain a system during its working cycle, since stopping works might incur users some troubles. From the above viewpoint, this paper discusses minimal repair maintenance policy with periodic replacement, while considering the random working cycles. The random working cycle and periodic replacement policies with minimal repair has been discussed in traditional literatures by usually analyzing cases for the nonstopping works. However, maintenance can be more conveniently done at discrete time and even during the working cycle in real applications. So, we propose that periodic replacement is planned at discrete times while considering the random working cycle, and moreover provide a model in which system, with a minimal repair at failures between replacements, is replaced at the minimum of discrete times KT and random cycles Y. The average cost rate model is used to determine the optimal number of periodic replacement.

• International Journal of Reliability and Applications
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• v.12 no.1
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• pp.41-48
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• 2011

This paper considers the maintenance model suggested by Jung and Park (2010) to adopt the Bayesian approach and obtain an optimal replacement policy following the expiration of NFRRW. As the criteria to determine the optimal maintenance period, we use the expected cost during the life cycle of the system. When the failure times are assumed to follow a Weibull distribution with unknown parameters, we propose an optimal maintenance policy based on the Bayesian approach. Also, we describe the revision of uncertainty about parameters in the light of data observed. Some numerical examples are presented for illustrative purpose.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.765-771
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• 2008

After the KTX operation Korail has been making great effort to reliability settlement through RCM. Also maintenance cycle and method optimization for normal speed rolling stock field are lively same as high-speed rolling stock. In this paper maintenance techniques for new model electric locomotive are introduced. To find the optimal maintenance method, locomotive inspection cycle for advanced country are examined and other electric locomotive inspection cycle are compared. As a result the present time inspection cycle is totally focusing on safety aspect so the economical efficiency is quite low. Through this research optimal maintenance technique will be accomplished in the end of year 2008.