• 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.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.11
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• pp.757-764
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• 2013

The estimation of maintenance cost of information system so far has been conducted centered on the ordering body, so the problem of provider's having to cover the cost due to small cost compared to the amount of work is not solved. This study is a base study for estimating the maintenance cost of information system centered on provider, and it deduces cost items of maintenance and suggests adjustment factors for adjusting the gap between the ordering body and provider regarding the maintenance cost. In order to deduce the cost items of maintenance, this study adds the activities of the provider for maintenance to the base study of cost factors regarding the existing maintenance activity, divides, and classifies them into the fixed cost and variable cost. In order to adjust the gap between the ordering body and provider regarding the maintenance cost, this study found the adjustment factors such as the code, utility, and components created by the automatic tool that was not included when estimating the maintenance cost centered on the ordering body. After examining and analyzing K Company's data of maintenance performance for three years, it confirmed that the gap regarding the adjustment factors was about 13% in case of K Company.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.651-656
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• 2006

Wu and Clements-Croome (2005) investigate the optimization problem of PM policies for situations where the quality of PM is a random variable with a certain probability distribution. However, they assume that the cost of preventive maintenance is constant, not depending on the quality of PM. Thus, this paper considers a periodic PM model when PM cost depends on the quality of PM activity. The optimal PM policy are presented for the extended PM model and the numerical examples are presented for illustrative purpose.

• Journal of Applied Reliability
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• v.15 no.1
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• pp.6-11
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• 2015

Maintenance plays an important role in keeping product availability, reliability and quality at an appropriate level. In this paper, two-types of maintenance policies are studied following the expiration of two-dimensional (2D) free replacement warranty. Both the fixed-maintenance-period policy and the variable-maintenance-period policy are based on a specified region of the warranty defined in terms of age and usage where all failures are minimally repaired. An accelerating failure time (AFT) model is used to allow for the effect of usage rate on product degradation. The maintenance model that arises following the expiration of 2D warranty is discussed. The expected cost rates per unit time from the user's point of view are formulated and the optimal maintenance policies are determined to minimize the expected cost rate to the user. Finally numerical examples are given to illustrate the optimal maintenance polices.

• 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 Architectural Institute of Korea Structure & Construction
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• v.34 no.2
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• pp.41-48
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• 2018

Carbonation is one of the major detrimental factors to the reinforced concrete structures owing to penetration of atmospheric CO2 through the micro pores, thereby it reduces the durability of the concrete. The maintenance periods and cost for concrete according to the coefficient variation of different finishing materials is documented in literature. However, it is required to carry out the systematic and well planned studies. Therefore, keeping them in mind, surface repair was carried out to the carbonated concrete and the maintenance cost was calculated to measure the durability life after repair with different variable. The deterministic and probabilistic methods were applied for durability and repair cost of the concrete. In the existing deterministic model, the cost of repair materials increases significantly when the concrete structure reaches its service life. In present study using a stochastic model, the maintenance period and cost was evaluated. According to obtained results, there was no significant difference in the number of maintenance of the coefficient variation. The initial durability has a great influence on the maintenance time and cost of the structure. Unlike the deterministic model, the probabilistic cost estimating model reduces the number of maintenance to the target service life expectancy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2724-2731
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• 2014

As the future national defense plan of government focus on advanced weapon system, military maintenance facility becomes more important. However, military maintenance facility has been managed by director's experience and simple mathematical calculation until now. Thus, the optimization for the management of military maintenance facility is suggested by more scientistic and logical methods in this study. The study follows the procedure below. First, simulation is designed according to the analysis of military maintenance facility. Second, independent variable and dependent variable are defined for optimization. Independent Variable includes the number of maintenance machine, transportation machine, worker in the details of military maintenance facility operation, and dependent variable involves total maintenance time affected by independent variable. Third, warmup analysis is performed to get warmup period, based on the simulation model. Fourth, the optimal combination is computed with evolution strategy, meta-heuristic, to enhance military maintenance management. By the optimal combination, the management of military maintenance facility can gain the biggest effect against the limited cost. In the future, the multipurpose study, to analyze the military maintenance facility covering various weapon system equipments, will be performed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.173-183
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• 1995

Life cycle cost has been one of the key criteria in design or purchasing of systems, particularly in the flying weapon system. Unexpected cost increase or system breakdown during the system life can be reduced by controlling maintenance cost A system should be designed for maintainability in early stage of product life cycle. The design should be insensitive to its environmental, organizational, and human factors in the stage of customer's utilization. This paper presents LCC as a controllable variable and also suggests a new control model for LCC analysis. The estimation of maintenance cost based upon maintenance scenario, design of maintainability followed by minimizing maintainability loss function in the beginning stage of design, and increase of useful life of systems are among the factors to control LCC.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.26-35
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• 2007

The vehicle of urban transit is a complex system that consists of various electric, electronic, and mechanical equipments, and the maintenance cost of this complex and large-scale system generally occupies sixty percent of the LCC (Life Cycle Cost). For reasonable establishing of maintenance strategies, safety security and cost limitation must be considered at the same time. The concept of system reliability has been introduced and optimized as the key of reasonable maintenance strategies. For optimization, three preceding studies were accomplished; standardizing a maintenance classification, constructing RBD (Reliability Block Diagram) of VVVF (Variable Voltage Variable Frequency) urban transit, and developing a web based reliability evaluation system. Historical maintenance data in terms of reliability index can be derived from the web based reliability evaluation system. In this paper, we propose applying inverse problem analysis method and hybrid neuro-genetic algorithm to system reliability optimization for using historical maintenance data in database of web based system. Feed-forward multi-layer neural networks trained by back propagation are used to find out the relationship between several component reliability (input) and system reliability (output) of structural system. The inverse problem can be formulated by using neural network. One of the neural network training algorithms, the back propagation algorithm, can attain stable and quick convergence during training process. Genetic algorithm is used to find the minimum square error.

• Smart Structures and Systems
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• v.22 no.2
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• pp.151-159
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• 2018

Maintenance activities are regarded as a key part of the repairable deteriorating system because they maintain the equipment in good condition. In practice, many maintenance policies are used in engineering fields to reduce unexpected failures and slow down the deterioration of the system. However, in traditional maintenance policies, maintenance activities have often been assumed to be performed at the same time interval, which may result in higher operational costs and more system failures. Thus, this study presents two non-periodic preventive maintenance (PM) policies for repairable deteriorating systems, employing the failure rate of the system as a conditional variable. In the proposed PM models, the failure rate of the system was restored via the failure rate reduction factors after imperfect PM activities. Operational costs were also considered, which increased along with the operating time of the system and the frequency of PM activities to reflect the deterioration process of the system. A numerical example was provided to illustrate the proposed PM policy. The results showed that PM activities performed at a low failure rate threshold slowed down the degradation of the system and thus extended the system lifetime. Moreover, when the operational cost was considered in the proposed maintenance scheme, the system replacement was more cost-effective than frequent PM activities in the severely degraded system.