• 산업공학
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• 제17권spc호
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• pp.122-130
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• 2004

Since the cost of software maintenance occupies about 50~75% in a general successful organization, the software maintenance plays an important role in software life cycle. In particular, if the managed system needs to be operated in a long term or the system is very large and complex, then the maintenance is especially more important. Software maintenance is defined as software modification activities after customer delivery, such as improvement of performance or functionality, error correction, adaptation to environmental changes, etc. In this paper, software cost estimation models are proposed, that is based on productivity of manpower in maintenance projects. In order to do this, the activities of maintenance are classified into function change, non-function change, user support and application operation. The proposed models are constructed and verified based on the real size and cost information of projects in the real world. The approach in this paper is to discriminate the heterogeneous activities in maintenance projects, and then to calculate the respective cost of each discriminated activity. By using the proposed models, the total cost of maintenance project is summed from the costs of four activities. In addition the number of conflicts between owner and order receiver about the amount of cost will be reduced and the reasonable cost estimation system will be established.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2008년도 학술발표회 논문집
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• pp.2244-2248
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• 2008

This study was focused on estimated Stream Maintenance Flow and performed for simulate securing Stream Maintenance Flow in New town development area. Tributary streams were made of 6 small streams, joined Gong-ji Stream and Eu-am lake finally. For estimate Stream Maintenance Flow used Kajiyama and SWAT models for calculate available flow in study area. As a result the annual average stream flow dry years were $2,300{\sim}136,000\;m^/day3$, the annual average stream flow wet years were $4,800{\sim}136,031\;m^3/day$. The coefficient of determination($R^2$) and Nash-sutcliffe coefficient(EI) for comparison between Kajiyama and SWAT models were 0.88, 0.78 respectively.

• Structural Monitoring and Maintenance
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• 제10권2호
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• pp.175-190
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• 2023

This article aims to quantitatively predict the snowmelt in extreme cold regions, considering a combination of grayscale and neural models. The traditional non-equidistant GM(1,1) prediction model is optimized by adjusting the time-distance weight matrix, optimizing the background value of the differential equation and optimizing the initial value of the model, and using the BP neural network for the first. The adjusted ice forecast model has an accuracy of 0.984 and posterior variance and the average forecast error value is 1.46%. Compared with the GM(1,1) and BP network models, the accuracy of the prediction results has been significantly improved, and the quantitative prediction of the ice sheet is more accurate. The monitoring and maintenance of the structure by quantitative prediction model by gray models was clearly demonstrated in the model.

• 한국철도학회논문집
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• 제8권6호
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• pp.544-549
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• 2005

Nowadays, most of bridge networks are complete or close to completion. The biggest challenge railroad./highway agencies and departments of transportation face is the maintenance of these networks, keeping them safe and serviceable, with limited funds. To maintain the bridges effectively, there is an urgent need to predict their remaining life from a system reliability viewpoint. And, it is necessary to develop the maintenance models based on system reliability concept. In this paper, maintenance models are developed for preventive maintenance and essential maintenance by using system reliability and lifetime distributions. The proposed model is applied to an existing railroad bridge. The optimal maintenance strategy of this bridge is obtained in terms of services life extension and cumulative maintenance cost.

• International Journal of Reliability and Applications
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• 제8권2호
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• pp.183-197
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• 2007

There is a growing trend for asset intensive industries to outsource maintenance services of their complex assets since outsourcing through service contract reduces upfront investments in infrastructure, expertise and specialised maintenance facilities. Estimation of costs for such contracts is complex and it is important to the user and the service providers for economic variability. The service provider's profit is influenced by many factors such as the terms of the contract, reliability of asset, and the servicing strategies, costs of resources needed to carryout maintenance. There is a need to develop mathematical models for understanding future costs to build it into the contract price. Three policies for service contracts are proposed in this paper considering the concepts of outsourcing maintenance service of assets to the service providers. Conceptual models are developed for estimating servicing costs of outsourcing through service contracts by considering time dependent failure mode.

• 산업경영시스템학회지
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• 제38권3호
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• pp.100-107
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• 2015

Recently as the manufacturers want competitiveness in dynamically changing environment, they are trying a lot of efforts to be efficient with their production systems, which may be achieved by diminishing unplanned operation stops. The operation stops and maintenance cost are known to be significantly decreased by adopting proper maintenance strategy. Therefore, the manufacturers were more getting interested in scheduling of exact maintenance scheduling to keep smooth operation and prevent unexpected stops. In this paper, we proposedan integrated maintenance approach in injection molding manufacturing line. It consists of predictive and preventive maintenance approach. The predictive maintenance uses the statistical process control technique with the real-time data and the preventive maintenance is based on the checking period of machine components or equipment. For the predictive maintenance approach, firstly, we identified components or equipment that are required maintenance, and then machine parameters that are related with the identified components or equipment. Second, we performed regression analysis to select the machine parameters that affect the quality of the manufactured products and are significant to the quality of the products. By this analysis, we can exclude the insignificant parameters from monitoring parameters and focus on the significant parameters. Third, we developed the statistical prediction models for the selected machine parameters. Current models include regression, exponential smoothing and so on. We used these models to decide abnormal patternand to schedule maintenance. Finally, for other components or equipment which is not covered by predictive approach, we adoptedpreventive maintenance approach. To show feasibility we developed an integrated maintenance support system in LabView Watchdog Agent and SQL Server environment and validated our proposed methodology with experimental data.

• 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.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 춘계학술대회 논문집
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• pp.1481-1498
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• 2007

As railroad industry face the new Renaissance era, effective and efficient maintenance methods for rolling stock operation are required with advanced railroad technology. All kinds of railroad systems such as high speed long distance train, metropolitan mass transit and light rail require systematic maintenance technology in order to maintain the safe railroad operation. Simulation models for detailed operations of the sample maintenance center are developed. In this study, standard maintenance procedures, layout, equipments and number of workers of Siheung Metropolitan Railroad Maintenance Rolling Stock Depot are considered. The proposed simulation models are developed using simulation package ARENA. Three simulation analysis using the developed simulation model are done. First, the bottleneck operation is identified. Second, the relationship between maintenance center size, number of workers and cycle time is analyzed. Lastly, the scheduling performances between PERT/CPM and Critical Chain Project Management(CCPM) are compared.

• Nuclear Engineering and Technology
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• 제56권2호
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• pp.526-535
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• 2024

This paper proposes a safety-critical standby component unavailability model that contains aging effects caused by the elapsed time from installation, component degradation due to surveillance tests, and imperfect maintenance actions. An application of the model to a Motor-Operated Valve and a Motor-Driven Pump involved in the HPIS of a VVER/1000-V446 nuclear power plant is demonstrated and compared with other existing models at component and system levels. In addition, the effects of different unavailability models are reflected in the NPP's risk criterion, i.e., core damage frequency, over five maintenance periods. The results show that, compared with other models that do not simultaneously consider the full effects of degradation and maintenance impacts, the proposed model realistically evaluates the unavailabilities of the safety-related components and the involved systems as a plant age function. Therefore, it can effectively reflect the age-dependent CDF impact of a given testing and maintenance policy in a specified time horizon.

• Asian-Australasian Journal of Animal Sciences
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• 제8권1호
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• pp.59-66
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• 1995

Energy obtained by grazing cattle in oil palm plantations is usually used for maintenance of body functions, the construction of body tissues and pregnancy, the synthesis of milk and the conversion to mechanical energy used for activities such as walking, eating and others. In this study, attempt was made to estimate metabolizable energy (ME) requirement of grazing cattle. Models of ME requirement (MER) for maintenance, gain, pregnancy, lactation and activities were developed. ME system and units were used because of wide recognition. Estimation of ME intake in grazing cattle was expressed as MEVI = $14.58{\times}VI{\times}DMD$, and under grazing condition MEVI = $MER_i$. MER was expressed as a function of net energy(NER, MJ) required for the i'th body function. Coefficient of efficiency for conversion of ME into net energy(ki) was adopted from literatures. Quantifying of ME requirement for Kedah-Kelantan cattle under grazing condition was made by using equation MERM = NEM / kn. The estimated values of MER for Kedah-Kelantan cattle is quite reasonable if compared with other estimates as reported in literatures from stall-fed animals. Dynamic MER models for grazing herd was developed in order to estimate ME requirement for maintenance and productions. These ME requirement models can be used for prediction of energy utilization pattern of the herd in the grazing systems.