In this study, we analyzed how the revenue water ratio(RWR) is affected by changes in conditions of the water supply area, such as the ratio of aging pipes, maintenance conditions, and revenue water. As a result of analyzing the impact of pipe aging and maintenance conditions on the RWR, it was confirmed that the RWR could be decreased if the pipe replacement project to improve the aging pipe ratio was not carried out and proper maintenance costs were not secured. It was also confirmed that an increase in the revenue water could be operated to facilitate the achievement of the project’s target RWR. In contrast, a decrease in the revenue water due to a population reduction could affect the failure of the target RWR. In addition to analyzing the causes of variation in the RWR, the calculation of estimated project costs was considered by using leakage reduction instead of RWR from recent RWR improvement project cost data. From this analysis, it was reviewed whether the project costs planned to achieve the target RWR of the RWR improvement project in A city were appropriate. In conclusion, the RWR could be affected by variations in the ratio of aging pipes, maintenance conditions, and revenue water, and it was reasonable to consider not only the construction input but also the input related to RWR improvement, such as leakage reduction, when calculating the project cost.

PURPOSES : Construction cost estimates are important information for business feasibility analysis in the planning stage of road construction projects. The quality of current construction cost estimates are highly dependent on the expert's personal experience and skills to estimate the arithmetic average construction cost based on past cases, which makes construction cost estimates subjective and unreliable. An objective approach in construction cost estimation shall be developed with the use of machine learning. In this study, past cases of road projects were analyzed and a machine learning model was developed to produce a more accurate and time-efficient construction cost estimate in teh planning stage. METHODS : After conducting case analysis of 100 road construction, a database was constructed including the road construction's details, drawings, and completion reports. To improve the construction cost estimation, Mallow's Cp. BIC, Adjusted R methodology was applied to find the optimal variables. Consequently, a plannigs-stage road construction cost estimation model was developed by applying multiple regression analysis, regression tree, case-based inference model, and artificial neural network (ANN, DNN). RESULTS : The construction cost estimation model showed excellent prediction performance despite an insufficient amount of learning data. Ten cases were randomly selected from the data base and each developed machine learning model was applied to the selected cases to calculate for the error rate, which should be less than 30% to be considered as acceptable according to American Estimating Association. As a result of the analysis, the error rates of all developed machine learning models were found to be acceptable with values rangine from 17.3% to 26.0%. Among the developed models, the ANN model yielded the least error rate. CONCLUSIONS : The results of this study can help raise awareness of the importance of building a systematic database in the construction industry, which is disadvantageous in machine learning and artificial intelligence development. In addition, it is believed that it can provide basic data for research to determine the feasibility of construction projects that require a large budget, such as road projects.

A disposal of radioactive wastes is one of the critical issues in our society. Considering upcoming plans for dismantling of nuclear power plants, this problem is inevitable and should be discussed very carefully. There are variety of methods to handle with radioactive wastes, including Incineration, conventional gasification and plasma gasification. Among them, plasma gasification process is in the limelight due to its eco-friendly & stable operation, and large volume reduction effects. However, a fatal disadvantage is that it consumes more electric power than other methods, this leaves us a question of whether this process is indeed economical. Within the scope of this paper, I would like to introduce 4 cases which plasma facilities were evaluated economically in worldwide, and reach the conclusion on the economic feasibility of plasma process.

When decommissioning nuclear power plant (NPP), the first task performed is cost estimation. This is an important task in terms of securing adequate decommissioning funds and managing the schedule. Therefore, many countries and institutions are conducting continuous research and also developing and using many programs for cost estimation. However, the cost estimated for decommissioning an NPP typically differs from the actual cost incurred in its decommissioning. This is caused by insufficient experience in decommissioning NPPs or lack of decommissioning cost data. This uncertainty in cost estimation can be in general compensated for by applying a contingency. However, reflecting an appropriate standard for the contingency is also difficult. Therefore, in this study, data analysis was conducted based on the contingency guideline suggested by each institution and the actual cost of decommissioning the NPP. Subsequently, TLG Service, Inc.’s process, which recently suggested specific decommissioning costs, was matched with ISDC (International Structure for Decommissioning Costing)’s work breakdown structure (WBS). Based on the matching result, the guideline for applying the contingency for ISDC’s WBS Level 1 were presented. This study will be helpful in cost estimation by applying appropriate contingency guidelines in countries or institutions that have no experience in decommissioning NPPs.

3D modeling is a technology for representing real objects in a virtual 3D space or modeling and reproducing the physical environment. 2D drawings for viewing the existing building structure have limitations that make it difficult to understand the structure. By implementing this 3D modeling, specific visualization became possible. 3D technology is being applied in a wide range of preevaluation work required for nuclear decommissioning. In Slovakia, 3D modeling was applied to determine the optimal cutting strategy for the primary circuit before dismantling the VVER type Bohunice V1. In Japan, the Decommissioning Engineering Support System (DEXUS) program has been developed that incorporates VRDose, a decommissioning engineering support system based on 3D CAD models. Through this, the cutting length of the work object and the quantity of containers for packaging waste are calculated, exposure dose calculations in various dismantling scenarios, and cost estimation are performed. Korea also used 3D technology to evaluate the decommissioning waste volume for Kori Unit 1 and to evaluate the optimal scenario of the decommissioning process procedure for the research reactor Unit 1. 3D technology is currently being used in various pre-decommissioning evaluations for VVER, PWR, and research reactors. Overseas, a program that matches various decommissioning pre-evaluation tasks with cost estimation has also been developed. However, most 3D technologies are mainly used as a support system for dose evaluation and amount of decommissioning waste calculation. In this study, 3D modeling was performed on the PHWR structure, and physical and radiological information about the structure was provided. The information on the structure can present the unit cost for the work object by confirming the standard of the applied unit cost factor (UCF). The UCF presents the unit cost for repeated decommissioning operations. The decommissioning cost of the work object can be obtained by multiplying the UCF by the number of repetitions of the work. If the results of this study are combined with the process evaluation and waste quantity estimation performed in previous studies, it is judged that it will be helpful in developing an integrated NPP decommissioning program that requires preliminary evaluation of various tasks. In addition, it is judged that a clear cost estimation of the object to be evaluated will be possible by matching the 3D work object with the UCF.

본 연구는 국내 항구도시 인천, 목포, 광양, 부산, 울산의 대기오염물질 배출특성, 대형선박 배기가스 배출량 및 사회적 비 용을 산정하여 배출가스 저감방안의 필요성을 제시하였다. 부산은 선박 입항수가 많고 목포는 선박 입항수는 적지만 선박 배기가스에 의한 배출기여도는 두 항구도시 모두 높았다. 울산은 세계적 수준의 중화학공업, 광양은 제철소, 인천은 제조업과 선박 입항수가 목포 보다 많았지만 배출기여도는 낮았다. 선박 배기가스 배출량 산정 결과, CO2의 배출량이 가장 많고 다음으로는 NOx, SOx으로 배출량이 많았다. 선종별로는 부산, 울산, 인천은 유조선, 광양은 일반화물선, 목포는 여객선에서 각각 많았다. 사회적 비용 결과, 부산은 배출량 이 많은 영향으로 사회적 비용이 높았으며, 항목별로는 PM이 높았다. 저황유 사용으로 PM, SOx 배출량을 직접적으로 줄이고, NOx의 배출량을 간접적으로 줄 일수 있다. 하지만 선박 배기가스 중 가장 많은 배출량을 보인 CO2를 저감하기 위해서는 저황유의 보급만으 로는 부족하다. CO2 배출량 감축을 위해서는 육상전원공급장치(Alternative Maritime Power)를 사용하는 등 화석연료를 사용하지 않는 저 감방안 수립의 필요성을 제기하였다.

NDF (No Defect Found) is a phenomenon in which defects have been found in the manufacturing, operation and use of a product or facility, but phenomenon of defects is not reproduced in the subsequent investigation system or the cause of the defects cannot be identified. Recently, with the development of the fourth industrial revolution, convergence of hardware and software technologies in various fields is spreading to products such as aircraft, home appliances, and mobile devices, and the number of parts is increasing due to functional convergence. The application of such convergence technologies and the increase in the number of parts are major factors that lead to an increase in NDF phenomena. NDF phenomena have a significant negative impact on cost, reliability, and reliability for both manufacturers, service providers and operators. On the other hand, due to the nature of NDF phenomena such as difficult and intermittent cause identification and ambiguity in judgment, it is common to underestimate the cost of NDF or fail to take appropriate countermeasures in corporate management. Therefore, in this paper, we propose a methodology for estimating NDF costs by the PAF model which is a quality cost analysis model and ABC (Activity Based Costing) technique. The methodology of this study suggests a detailed procedure and the concept to accurately estimate the NDF costs, using ABC analysis, accounting system information, and IT system data. In addition case studies have validated the methodology. We think this could be a valid methodology to refer to when estimating the cost of other parts. And, it is meaningful to provide important judgment information in the decision-making process based on quality management and ultimately reduce NDF costs by visualizing them separately by major variable factors.

본 논문에서는 고리 1호기 해체 비용 추정을 위해 외국 원자력발전소 해체 비용 데이터를 현가화한 후 원자력발전소 해체 비용 추정 회귀 분석모델을 개발하였다. 이 모델 개발에 사용된 데이터는 해체 또는 진행 중인 BWR 13기, PWR 16기의 해체 비용 데이터이다. 회귀 분석모델 도출을 위해, 해체 비용을 종속변수로 정하고, 해체 원전의 운전 특성을 반영할 수 있게 고 안된 Contamination factor와 해체 기간을 독립변수로 선정하였다. 빅데이터 분석 도구인 R language의 통계패키지를 이용 하여 회귀 분석모델을 도출하였다. 이 회귀 분석 모델을 적용하여 고리 1호기 해체 비용을 예측한 결과, 미화 663.40~928.32 백만 달러, 한화 약 7,828.12억~1조 954.18억 원이 소요될 것으로 예측되었다.

The estimation of heat source model is very important for heat transfer analysis with finite element method. Part I of this study used adaptive simulated annealing which is one of the global optimization algorithm for anticipating the parameters of the Goldak model. Although the analysis with 3D model which depicted the real situation produced the correct answer, that took too much time with moving heat source model based on Fortran and Abaqus. This research suggests the procedure which can reduce time with maintaining quality of analysis. The lead time with 2D model is reduced by 90% comparing that of 3D model, the temperature distribution is similar to each other. That is based on the saturation of heat transfer among the direction of heat source movement. Adaptive simulated annealing with 2D model can be used to estimate more proper heat source model and which could enhance to reduce the resources and time for experiments.

북베트남의 컨테이너 터미널을 주제로 한 연구는 다수 있지만, 선박의 대기시간이나 화물처리에 관련한 비용 측면에서의 경쟁을 다룬 연구는 거의 없다. 이 논문은 북 베트남에 입지한 컨테이너 터미널의 TEU당 평균대기비용을 추산해 본 연구다. 우선 대기 행렬이론을 적용하여 평균대기시간을 추산한 뒤, 불확실성 이론을 적용하여 선박의 일당 비용을 추산할 것이다. 그리고 각 터미널의 하역능력 내지 물동량 처리율과 관련하여 TEU당 일련의 대기시간을 산정하기 위해 시뮬레이션을 실시하였다. 추산된 일련의 대기시간을 근거로 하여 각 항만의 평균대기시간과 물동량 처리율 / 하역률 간의 관계를 제시하기 위한 함수를 추정하기 위해 비선형회귀법을 적용하였다. 연구 결과는 북베트남의 컨테이너 터미널간의 경쟁상황에 관한 후속 연구에서 게임이론을 적용하는 데 이용될 수 있을 것 이다.

본 연구는 BIM 도입 효과를 극대화할 수 있는 현장 적용성 확보에 중점을 둔 철근콘크리트 골조공사의 BIM 견적모델 작성과 BIM기반 견적 업무 프로세스를 표준화한 가이드라인을 제시하는 것을 목적으로 한다. 이를 위하여 기존 지침 및 가이드라인의 BIM 견적모델 작성 범위 및 방식을 고찰하고, 철근콘크리트공사 수량산출·견적 지침 및 기준을 분석하며, 기존 견 적 방식과 BIM기반 견적 방식에 대해 비교분석한다. 이를 통하여 BIM기반 견적 업무의 표준 프로세스를 수립하고, 콘크리 트/거푸집/철근 견적모델의 작성 및 수량산출 기준을 도출하며, 철근콘크리트공사 BIM기반 수량산출 및 견적 업무의 성과 물 목록 및 양식을 제시한다. 본 연구를 통해 작성된 BIM 견적 가이드라인은 BIM기반의 새로운 기술환경에 대한 진입장벽 을 낮추고, 견적의 정확성 극대화를 통한 원가절감을 실현하며, BIM 업무와 건설산업의 생산성과 부가가치를 증대시켜, 궁 극적으로 건설사업 전 생애주기에서 생산되는 정보를 통합 관리할 수 있는 기반을 구축하고 BIM 생태계를 조성하는데 기여 할 것으로 기대한다.

In the defense acquisition, a company’s goal is to maximize profits, and the government’s goal is to allocate budgets efficiently. Each year, the government estimates the ratio of indirect cost sector to defense companies, and estimates the ratio to be applied when calculating cost of the defense articles next year. The defense industry environment is changing rapidly, due to the increasing trend of defense acquisition budgets, the advancement of weapon systems, the effects of the 4th industrial revolution, and so on. As a result, the cost structure of defense companies is being diversifying. The purpose of this study is to find an alternative that can enhance the rationality of the current methodology for estimating the ratio of indirect cost sector of defense companies. To do this, we conducted data analysis using the R language on the cost data of defense companies over the past six years in the Defense Integrated Cost System. First, cluster analysis was conducted on the cost characteristics of defense companies. Then, we conducted a regression analysis of the relationship between direct and indirect costs for each cluster to see how much it reflects the cost structure of defense companies in direct labor cost-based indirect cost rate estimates. Lastly a new ratio prediction model based on regularized regression analysis was developed, applied to each cluster, and analyzed to compare performance with existing prediction models. According to the results of the study, it is necessary to estimate the indirect cost ratio based on the cost character group of defense companies, and the direct labor cost based indirect cost ratio estimation partially reflects the cost structure of defense companies. In addition, the current indirect cost ratio prediction method has a larger error than the new model.

SCM activities in a company are considered as total innovation through synchronizing supply and demand while maintaining appropriate inventory level and reducing the business operating costs. Until now, even several researches are carried out on the SCM performance of the companies which have introduced and been operating SCM, the research on the cost analysis for the inventory which occurs frequently on supply chain is still insufficient. Especially, for the electronics industry in which the product depreciation is sharp caused by the short product life cycle and the complexity of distribution channels, even the inventory related costs are a major factor in business management, since the current estimated criteria of inventory costs are limited to the interest and maintenance management costs, the criteria do not reflect the total influence of the product depreciation and lost opportunity cost which are related to the business management. Furthermore, even though the rapid price drops of the distributor inventory caused by the frequent new model launch can be covered by the product manufacturers, the scale of total costs related to the inventory has not been conceived because the price compensation is traditionally considered as a market costs.In this research, we analyzed the inventory characteristics of electronics industry in which the price depreciation happens frequently, newly defining the estimated criteria of the product total inventory cost which includes price depreciation from the product manufacturers’ view. Finally we focus on the case study of a representative electronics company and verify the scale of the influence on management performance.

Price quotations for SOR / RFQ from OEM clients is a very important process in the automotive parts industry. However, OEM clients are demanding a price quote on short duration but it takes long delivery time due to sales, research and development, purchasing, production and cost management departments role and jobs focused on detail and responsibility. And to provide a reasonable alternative with eliminating the waste of non-value processes is to achieve OEM clients satisfaction through standardized and parallel processing, IT system based on the systems and processes of global benchmark companies.

PURPOSES: This study aimed to evaluate the performance of pavement management works and to develop a function for estimating the level of service (LOS) and cost of service (COS) for the systematic and quantitative management of pavement performance in the public sector. METHODS: The International Roughness Index (IRI) was used as the performance index for pavement management. Long-term pavement performance data for a period of 7 years (2007-2014) collected by the National Highway Pavement Management System and historical maintenance budget data published by the South Korean government were used to develop the LOS-COS function. Based on the function, a model for estimating the appropriate budget as well as the network conditions was suggested. RESULTS : There was high degree of correlation between pavement performance and the investment level (R = - 0.74). The developed LOS-COS function suggested that the unit cost to improve the network IRI to 1 m/km was 32.6 billion KRW. Further, the maintenance costs normalized with respect to the LOS levels were LOS-A = 88.2 billion KRW, LOS-B = 55.6 billion KRW, and LOS-C = 23.0 billion KRW. CONCLUSIONS: This study proposes a simple way of developing a LOS-COS function. It also shows how to develop a network budget demand and condition estimation model using the LOS-COS function. In addition, it is the first attempt to evaluate the road maintenance budget in South Korea. It is expected that these results will help in the negotiations between the road managers and budget makers.