• Journal of Information Technology Applications and Management
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• 제19권2호
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• pp.181-196
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• 2012

The cost of software maintenance occupies about two thirds in the software lifecycle. However, it is not easy to estimate the cost of software maintenance because of various viewpoints about software maintenance, unclear estimation methods, and complex procedures. Until now, the cost estimation model has used compensation factors for software characteristic and environment on the basis of program size. Especially, most of existing models use maintenance rate of total software cost as a main variable. This paper suggests the software maintenance cost estimation model that uses the result of calculating real maintenance efforts. In this paper, we classify functional maintenance and non-functional maintenance as software maintenance activity type. For functional maintenance, present function point of target software is needed to evaluate. The suggested maintenance cost evaluation model is applied to a software case in public sector. This paper discusses some differences between our model and other modes.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권2호
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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.

• 전기학회논문지P
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• 제58권4호
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• pp.410-415
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• 2009

With the implementation of electric power industry reform, the utilities are looking for effective ways to improve the economic efficiency. One area in particular, the equipment maintenance, is being scrutinized for reducing costs while keeping a reasonable level of the reliability in the overall system. Here the conventional RCM requires the tradeoff between the upfront maintenance costs and the potential costs of losing loads. In this paper we describe the issues related to applying so-called the "Reliability-centered Maintenance" (RCM) method in managing electric power distribution equipment. The RCM method is especially useful as it explicitly incorporates the cost-tradeoff of interest, i.e. the upfront maintenance costs and the potential interruption costs, in determining which equipment to be maintained and how often. In comparison, the "Time-based Maintenance" (TBM) method, the traditional method widely used, only takes the lifetime of equipment into consideration. In this paper, the modified Markov model for maintenance is developed. First, the existing Markov model for maintenance is explained and analyzed about transformer and circuit breaker, so on. Second, developed model is introduced and described. This model has two different points compared with existing model: TVFR and nonlinear customer interruption cost (CIC). That is, normal stage at the middle of bathtub curve has not CFR but the gradual increasing failure rate and the unit cost of CIC is increasing as the interruption time is increasing. The results of case studies represent the optimal maintenance interval to maintain the equipment with minimum costs. A numerical example is presented for illustration purposes.

• 산업경영시스템학회지
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• 제43권3호
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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.

• 한국국방경영분석학회지
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• 제22권1호
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• pp.142-155
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• 1996

In this research, our objective is to develop a model which could evaluate the maintenance capability for a maintenance battalion in the mechanized division. To analyze the maintenance system, we obtained various data related to maintenance capability and described the maintenance process as a network type. This network type model is then translated to SLAM-II network model to simulate the system. The simulation model can be operated by using appropriate input data and simulation results are obtained. The simulation model can be applied in various way. Through the simulation we could find the bottle neck point in the maintenance process. Also the maximum capability of maintenance with on hand asset and the wartime supportability can be evaluated. The mode provides sensitivity analysis by changing various imput data such as the number of repairmen, repair time, failure rate and so on.

• 한국BIM학회 논문집
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• 제14권3호
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• pp.31-45
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• 2024

This study proposes a BIM-based space model generation framework for managing maintenance history in apartments. While BIM adoption in design and construction phases is increasing, its use in operation and maintenance remains limited, particularly in the continuous utilization of as-built BIM models. To address this, the study introduces a methodology for automated space model generation using DYNAMO, analyzing 1,875 maintenance records and long-term repair plans from two apartment projects over two years. The framework was applied to case projects, achieving a 100% space model creation rate for dedicated spaces and 108.91% for public spaces, proving its applicability. This suggests that the automated space model generation process proposed in this study is applicable. The significance of this study is that it presents a model transition framework for the operation and maintenance phase of the as-built BIM model. In addition, it is of research value that a simplified BIM space model is proposed to overcome the limitation of not being able to manage the history of each part in the current maintenance phase. This study can be utilized as a basis for future BIM guidelines applicable to operation and maintenance phases and delivery guidelines for as-built BIM models.

• 한국BIM학회 논문집
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• 제8권4호
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• pp.34-40
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• 2018

As the number of aged bridges increases, the development of efficient bridge maintenance techniques is becoming more important. Particularly, there have been many studies on digital-twin models of bridges for maintenance and SHM (Structure Health Monitering). However, in order to use the digital-twin model for maintenance of the bridge, the model updating process that matches the structural response between the real bridge and the digital-twin bridge model must be done. This study presents a model updating method that adjusts bridge's stiffness and boundary condition with genetic algorithm (GA) using static displacements and verified proposed updating method through field test on PSC girder bridge. This study also proposes a conceptual idea to construct an efficient bridge maintenance system by applying the updated numerical analysis model to the digital-twin model.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.105-117
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• 2003

The purpose of this research aimed at performing the easy design. and also the easy on-the-job application or the maintenance interval determination methodology by presenting the determining model or the optimizing maintenance interval in TBM for the preventive maintenance or facility TBM(time-based maintenance) as the preventive maintenance requires the adequate determination or the maintenance interval. The maintenance interval or TBM shall be applied differently for the each interval such as He patrol inspection, maintenance, overhaul inspection. exchange. And it is based on the composition level of equipment. The already informed theories or interval determination methodology for the patrol inspection. repair. and overhaul inspection are difficult for adopting because or the several restriction problems in applying the maintenance schemes as the theory So, the model for determining the optimizing exchange interval or part, maintenance interval of auxiliary machine, unit equipment etc. was presented to apply in the maintenance easily and appropriately.

• 산업경영시스템학회지
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• 제42권4호
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• pp.145-152
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• 2019

All machines deteriorate in performance over time. The phenomenon that causes such performance degradation is called deterioration. Due to the deterioration, the process mean of the machine shifts, process variance increases due to the expansion of separate interval, and the failure rate of the machine increases. The maintenance model is a matter of determining the timing of preventive maintenance that minimizes the total cost per wear between the relation to the increasing production cost and the decreasing maintenance cost. The essential requirement of this model is that the preventive maintenance cost is less than the failure maintenance cost. In the process mean shift model, determining the resetting timing due to increasing production costs is the same as the maintenance model. In determining the timing of machine adjustments, there are two differences between the models. First, the process mean shift model excludes failure from the model. This model is limited to the period during the operation of the machine. Second, in the maintenance model, the production cost is set as a general function of the operating time. But in the process mean shift model, the production cost is set as a probability functions associated with the product. In the production system, the maintenance cost of the equipment and the production cost due to the non-confirming items and the quality loss cost are always occurring simultaneously. So it is reasonable that the failure and process mean shift should be dealt with at the same time in determining the maintenance time. This study proposes a model that integrates both of them. In order to reflect the actual production system more accurately, this integrated model includes the items of process variance function and the loss function according to wear level.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권3호
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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.