• Journal of Information Technology Applications and Management
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• v.19 no.2
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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.

• Journal of the Korean housing association
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• v.21 no.2
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• pp.59-67
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• 2010

The maintenance cost plays a important role to plan the scale of the apartment housing such as a number of household, building area and building type. Therefore, it is required to forecast the cost considering various maintenance characteristics. The maintenance characteristics are floor area, number of household, heating type, site area and etc.. In addition, the maintenance cost are classified into 5 area. These are a personal expense, facility maintenance cost, energy and water cost, insurance and sanitary cost. These five cost area are related with various characteristics and brought up the estimation model using the stepwise multiple regression analysis. The energy and heating cost share over the 50% in the total cost and the personal expense cost shares about 40%. The personal expense cost per area is 5,272 won/$m^2{\cdot}yr$ irregardless of heating type and the district heating type is a higher cost than other type. In facility maintenance cost, the central heating type is 2,015 won/$m^2{\cdot}yr$ and higher than other type. The estimation models have good statistics in each model. Most of the model have a determination coefficient over 0.7 and Durbin Watson value between 1.5 and 2.5.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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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.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.353-360
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• 2009

Most information systems are component-based and developed by outsourcing, and developed software is maintained integrative. However, studies on cost measurement indicators and cost estimation model have not been performed sufficiently, which are foundational to enhance the productivity and efficiency of maintenance. This study suggests indicators to measure maintenance cost for component-based software and examines maintenance cost estimation model of component software by the measurement indicators suggested. In order to generate the indicators to measure the component-based maintenance cost, the previously proposed indicators are summarized comparatively. To estimate the measurement indicators of component-based software, it makes a comparison of the previously proposed indicators and arranges them. We classify the measurement indicators by how to apply according to maintenance types of component software and then we propose the cost measurement indicators. Moreover, we propose the cost estimation model according to the maintenance types of component software using the suggested measurement indicators suggested. With the suggested estimation model, a case study is performed and its validity is verified.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.77-85
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• 2013

In this paper, we present the cost measurement metrics for the operation management and service improvement besides the general maintenance. The cost measurement metrics of the operation management and service improvement are based on the metrics that are classified and summarized precedent studies and complemented by empirical measuring indicators, and we propose the maintenance cost estimation model based on this metrics. The maintenance costs can be calculated detailedly, because the proposed metrics can be used selectively, depending on the scope of the information system maintenance. The effectiveness of the proposed maintenance cost measurement metrics and cost estimation model is verified by comparison between existing studies and our research.

• 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 Information Technology Services
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• v.14 no.3
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• pp.67-84
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• 2015

Software is more diverse and complex and the level of importance for the maintenance of application software to securely operate software is also gradually increasing in proportion. The calculation method for maintenance cost of application software applied in Korea public enterprises is involved in the range of 10 to 15% of development cost, depending on the Software Project Cost Estimation Guide. Moreover, as most software maintenance cost estimation procedures do not take into consideration of the risk factors related of maintenance, it can be seen as a main cause for the occurrence of maintenance related accidents. This study proposes a maintenance cost estimate model that takes into consideration of the risks related to the software maintenance activities to improve and resolve issues arising from the estimation of maintenance cost. In doing so, maintenance risk factors are analyzed and a risk index is derived through the analysis of risk levels based on the risk factors. Based on such analysis, a maintenance cost estimate method which reflects the maintenance risk index was established.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.287-295
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• 1995

This paper is concerned with cost analysis model in periodic maintenance policy. Generally periodic maintenance policy in which item is repaired periodic interval times. And in the article minimal repair is considered. Mimimal repair means that if a unit fails, unit is instantaneously restored to same hazard rate curve as before failure. In the paper periodic maintenance policy with minimal repair is as follows; Operating unit is periodically replaced in periodic maintenance time, if a failure occurs between minimal repair and periodic maintenance time, unit is replaced by a new item until tile periodic maintenance time comes. Also unit undergoes minimal repair at failures in minimal-repair-for-failure interval. Then total expected cost per unit time is calculated according to scale parameter of failure distribution. Maintenance cost factors are included operating, fixed, minimal repair, periodic maintenance and new item replacement cost. Numerical example is shown in which failure time of system has weibull distribution.

• 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 the Korea institute for structural maintenance and inspection
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• v.11 no.6
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• pp.131-142
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• 2007

The road user cost in indirect costs as well as direct costs such as the inspection/ diagnosis cost and the repair/reinforcement cost should be considered as one of the important items in the life-cycle cost-effective design and maintenance of the bridges. To estimate the road user cost, this paper formulates the road user cost as a sum of the user delay cost and the vehicle operating cost considering the detour effect. A numerical traffic simulation and a regression analysis are performed to develop a regression model due to a time delay. The proposed regression model is applied to the generation of the maintenance strategy based on the life-cycle cost and performance, and its effectiveness and applicability is investigated. The road user cost has a great influence on establishing the maintenance strategy, and the proposed regression model could be successfully utilized to estimate the road user cost of a bridge.