• 한국국방경영분석학회지
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• 제26권1호
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• pp.70-88
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• 2000

In this research we consider a statistical model to estimate the optimal maintenance manpower of aircraft which we use at present. We design a multiple regression model, apply to three types of aircraft to estimate the optimal maintenance manpower of aircraft. This paper provides reasonable results about maintenance manpower of aircraft, and contributes accomplishment of mission for air and air support operations.

• 경영과학
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• 제13권3호
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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.

• 한국도로학회논문집
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• 제19권3호
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• pp.65-70
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• 2017

PURPOSES : Pavement Management System contains the data that describe the condition of the road. Under limited budget, the data can be utilized for efficient plans. The objective of this research is to develop a mixed integer program model that maximizes remaining durable years (or Lane-Kilometer-Years) in road maintenance planning. METHODS : An optimization model based on a mixed integer program is developed. The model selects a cluster of sectors that are adjacent to each other according to the road condition. The model also considers constraints required by the Seoul Metropolitan Facilities Management Corporation. They select two lanes at most not to block the traffic and limit the number of sectors for one-time construction to finish the work in given time. We incorporate variable cost constraints. As the model selects more sectors, the unit cost of the construction becomes smaller. The optimal choice of the number of sectors is implemented using piecewise linear constraints. RESULTS : Data (SPI) collected from Pavement Management System managed by Seoul Metropolitan City are fed into the model. Based on the data and the model, the optimal maintenance plans are established. Some of the optimal plans cannot be generated directly in existing heuristic approach or by human intuition. CONCLUSIONS:The mathematical model using actual data generates the optimal maintenance plans.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권4호
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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.

• International Journal of Reliability and Applications
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• 제9권1호
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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.

• 한국정보처리학회논문지
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• 제3권4호
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• pp.846-854
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• 1996

본 연구에서는 소프트웨어 위기의 주요 원인인 유지보수 문제를 해결하기 위한 방안을 제시하기 위한 것으로, 국내의 유지보수 문제점과 현황을 설문으로 기초 조 사·분석하고 면담과 문헌을 참고하여 문제점을 해결하고자 하였다. 연구의 결과로 유지보수 생명주기를 정의하고 유지 보수를 효율적으로 수행하기 위한 기본 전략을 수립하고, 수립된 기본 전략을 구현하기 위한 유지보수 지원 시스템을 개략 설계하여 유지보수 시스템의 자동화 설계를 위한 기반을 구축하였다.

• International Journal of Railway
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• 제1권2호
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• pp.59-63
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• 2008

The maintenance effect is a peculiar factor applied to repairable systems such as rolling stocks. Conventional statistical analysis for failure times takes into account one of the two following extreme assumptions, namely, the state of the system after maintenance is either as "good as new" (GAN, perfect maintenance model) or as "bad as old" (BAO, minimal maintenance model). Most of the papers concerning the stochastic behavior of railroad systems assume two types of maintenance: perfect and minimal maintenance. However, Lee, Kim & Lee (2008) analyzed the failure data of a door system in Metro EMU and the effect of preventive maintenance was imperfect. It is seen that the imperfect maintenance is of great significance in practice. This article describes how to deal with the maintenance effect in reliability studies of rolling stocks. Maintenance policies under imperfect maintenance are described and the method is proposed to evaluate their performance.

• 대한산업공학회지
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• 제30권4호
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• pp.261-266
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• 2004

In this paper, the software reliability growth model which incorporates the periodic maintenance after the release is proposed. Using the proposed model, the debugging and periodic maintenance cost subject to the required level of the software reliability are investigated. An optimal software release time is derived for a fixed interval of periodic maintenance. To validate the proposed model, release times obtained in this study are compared with examples. The proposed investigation is expected to be served as one of factors in determining the release time of the software where periodic maintenance is considered.

• 산업공학
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• 제13권3호
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• pp.521-527
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• 2000

A simulation model is developed for planning maintenance, and it can be used in the procedure of Reliability-Centered Maintenance. System availability and the total cost of system operation are predicted by discrete event simulation. These two kinds of output are useful to determine the interval of preventive maintenance. This paper describes simulation logic, and focuses on modeling the maintenance effects and the relations of maintenance works. An example is described for illustrating the simulation model.

• Industrial Engineering and Management Systems
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• 제7권1호
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• pp.51-56
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• 2008

With growing demand for zero defects, predicting reliability of software systems is gaining importance. Software reliability models are used to estimate the reliability or the number of latent defects in a software product. Most reliability models to estimate the reliability of software in the literature are based on the development lifecycle stages. However, in the maintenance phase, the software needs to be corrected for errors and to be enhanced for the requests from users. These decrease the reliability of software. Software Reliability Growth Models (SRGMs) have been applied successfully to model software reliability in development phase. The software reliability in maintenance phase exhibits many types of systematic or irregular behaviors. These may include cyclic behavior as well as long-term evolutionary trends. The cyclic behavior may involve multiple periodicities and may be asymmetric in nature. In this paper, SGRM has been adapted to develop a reliability prediction model for the software in maintenance phase. The model is established using maintenance data from a commercial shop floor control system. The model is accepted to be used for resource planning and assuring the quality of the maintenance work to the user.