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

• 한국주거학회논문집
• /
• 제21권2호
• /
• pp.59-67
• /
• 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.

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

• 정보처리학회논문지D
• /
• 제16D권3호
• /
• pp.353-360
• /
• 2009

대부분의 정보시스템은 컴포넌트 기반으로 아웃소싱에 의해 개발되고 있으며, 개발된 소프트웨어들은 통합되어 유지보수 되고 있다. 그러나 유지보수의 생산성과 효율성 제고를 위한 기반 연구인 비용 측정지표 및 비용 추정 모델에 관한 연구가 부족하다. 본 연구는 컴포넌트 기반의 소프트웨어에 대한 유지보수의 비용에 대한 측정지표를 제안하고, 제안한 측정지표의 의한 컴포넌트 소프트웨어의 유지보수 비용 추정 모델을 연구한다. 컴포넌트 기반의 유지보수 비용 측정지표를 추정하기 위하여 기존에 제시된 지표들을 비교 정리하고, 정리된 측정지표가 컴포넌트 소프트웨어 유지보수 유형에 따라 어떻게 적용되는지를 분류하고 유형별 비용 측정지표를 제안한다. 또, 제안한 측정지표를 이용한 컴포넌트 소프트웨어 유지보수 유형에 따른 비용 추정 모델을 제안한다. 제안한 추정 모델의 사례연구를 실시하여 유효성을 검증한다.

• 한국컴퓨터정보학회논문지
• /
• 제18권5호
• /
• pp.77-85
• /
• 2013

본 연구는 소프트웨어의 변경을 가하는 순수 유지보수 비용 외에 운영 관리 및 서비스 향상을 위한 비용 측정지표를 도출하고 이를 기반으로 정보시스템유비보수 비용 추정 모델을 제안한다. 운영 관리 및 서비스 향상 측정지표는 선행연구를 요약 분류하여 지표의 기반으로 도출하고 경험적인 측정지표를 추가 보완하였으며, 이를 근거로 유지보수 비용 추정 모델을 제안한다. 제안한 측정지표는 정보시스템 유지보수 범위에 따라 선택적으로 사용할 수 있어 상세한 유지보수 비용 산정이 가능하다. 제안한 유지보수 비용 측정지표와 비용 추정 모델의 유효성을 검증하기 위하여 기존의 연구와 비교 검증하여 유효성을 입증하였다.

• 한국신뢰성학회지:신뢰성응용연구
• /
• 제12권2호
• /
• pp.57-66
• /
• 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.

• 한국IT서비스학회지
• /
• 제14권3호
• /
• pp.67-84
• /
• 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.

• 산업경영시스템학회지
• /
• 제18권36호
• /
• pp.287-295
• /
• 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.

• 한국신뢰성학회지:신뢰성응용연구
• /
• 제18권2호
• /
• pp.104-113
• /
• 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.

• 한국구조물진단유지관리공학회 논문집
• /
• 제11권6호
• /
• pp.131-142
• /
• 2007

생애주기비용을 고려한 교량의 설계 및 유지관리에 있어서, 점검진단, 보수보강 등에 소요되는 직접적인 비용뿐만 아니라 간접적인 비용인 도로이용자비용은 중요한 비용항목으로 고려되고 있다. 직접비용과 비교하여 상대적으로 추정이 곤란한 도로이용자비용의 추정을 위하여 우회도로의 효과를 고려한 이용자지연비용과 차량운행비용의 정식화를 수행하고, 시간지체에 따른 도로이용자비용의 추정을 위한 회귀모델 개발을 위하여 교통해석과 회귀분석을 수행하였다. 개발된 회귀모델을 생애주기 비용 및 성능 기반 유지관리 전략 수립에 적용하여 도로이용자비용이 생애주기분석에 미치는 영향을 분석하고, 개발된 모델의 적용성에 대해서 고찰하였다. 도로이용자비용은 생애주기분석에 기초한 유지관리전략수립에 큰 영향을 미치며, 개발된 회귀모델은 교량의 도로이용자비용의 추정에 실용적으로 활용될 수 있을 것으로 판단된다.