• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• autumn
• /
• pp.450-453
• /
• 2003

It is very important to examine and compare initial plan with earned value repeatedly in construction. For this purpose, progress measurement, which reflects the actual progress correctly, is required and it is necessary that accurate field data should be offered. To measure the progress, the entire project mutt be divided into unit works that have an accurate scope of work, and required information must be distributed to the all parties. Under the circumstances of domestic construction industry which focus on the specifications, progress measurement needs to reflect the information of schedule as well as cost that includes the quantity of unit work and construction expenses. Therefore this research proposes weighted method of progress measurement based on the information of cost and schedule.

• Korean Journal of Construction Engineering and Management
• /
• v.4 no.4 s.16
• /
• pp.182-191
• /
• 2003

The material lift-up and procurement management for high-rise buildings is complex and critical key to the success of projects. It has been hardly managed by the heuristic or rule-of-thumb techniques which are adapted in usual construction building sites. Especially in downtown high-rise residential building project sites, the limit of heuristic management techniques is critical. It has space constraint for materials loading and site transportation especially in finish work phases in which construction period diverse work trades struggle for their own material and manpower transportation. Hence, it is essential to adapt JIT(Just-In-Time) concept in these particular types of building construction project sites. According to the analysis of the case project sites, the communication and flow of relevant information regarding material lift-up and transportation in project sites is the key factor for successful performance. Therefore, this study analyzes the flow and site transportation of the key materials and provides the system, PLUTO(Procurement & Lift-Up for material Transport Optimizing system). This study also applies the system in the case site and verifies the model validation in actual project.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 2004.11a
• /
• pp.317-322
• /
• 2004

As a construction project in urban area tends to be high-rise and huge, the importance of the project's underground work, in terms of the cost and the schedule, is gradually increasing. It's extremely significant to choose a proper filing method, at the stage of underground work. However, in piling work many change orders have been occurred since a piling method is experientially selected based on uncertain information and many earth factors to consider. It has effects on the cost and the schedule of the project. In this study, we have suggested a decision model for piling method that can be used to determine and verify the suitable piling method in design and pre-construction phase of a project. Based on historical data, a neural network model has already proven to be efficient. The tests of the model for selecting a suitable piling method have progressed exactly with the data of 150 piling works which were done room 2000 to 2004 in Korea. The optimization or the developed neural network model has progressed with the data for teaming. The validity of the neural network model has been verified.

• Korean Journal of Construction Engineering and Management
• /
• v.7 no.2 s.30
• /
• pp.127-137
• /
• 2006

Productivity is important to evaluate an efficiency of performed work and organization in construction industry. The productivity should be defined as activity level rather than macro level in order to effectively use productivity data and manage a project. The primary objective of this study is to develop a construction productivity management system using data warehouse, OLAP and data mining technologies which enables to easily accumulate the construction productivity data and perform multi layer analysis. Finally, it is anticipated that the effective use of the developed system would be able to measure the result of project and make a plan of the similar project with reliability.

• The Journal of Bigdata
• /
• v.5 no.2
• /
• pp.17-27
• /
• 2020

District heating system supplies heat from low-cost high-efficiency heat production facilities to heat demand areas through a heat pipe network. For efficient heat supply system operation, it is important to accurately predict the heat demand within the region and optimize the heat production plan accordingly. In this study, a heat demand forecasting model is proposed considering real-time calorimeter information from local heat demands. Previous models considered ambient temperature and heat demand history data to predict future heat demands. To improve forecast accuracy, the proposed heat demand forecast model added big data from real-time calorimeters installed in the heat demands within the target region. By employing calorimeter information directly in the model, it is expected that the proposed forecast model is to reflect heat use pattern of each demand. Computational experiemtns based on the actual heat demand data shows that the forecast accuracy of the proposed model improved when the calorimeter big data is reflected.

• Journal of Korea Port Economic Association
• /
• v.37 no.4
• /
• pp.1-11
• /
• 2021

Port hinterland has been experiencing difficulty in generating new cargo volume and high value-added activity. It will be able to contribute to create new cargo volume and high added-value if transshipment cargo can be switched to trusted processing and then attract to port hinterland. This paper estimates items and volume size that can be the appropriate to attract in port hinterland and also be able to switch to trusted processing based on the trade data and manifest of transshipment container. The 50 items were classified from the result of trusted processing trade and the 33 items of them were suggested as the appropriate to attract in the port hinterland. The result shows that the 3.2 times transshipment cargo volume which is large than the total volume of trusted processing trade in Korea is transshipped at Busan port. This study is the first research to compare trade data and manifest of transshipment container, and thus it contributes to attracting firms in the port hinterland for the port authorities and the government.

• Journal of the Society of Disaster Information
• /
• v.12 no.1
• /
• pp.10-18
• /
• 2016

This study presented a new NOS model through the following suggestions to apply the construction work planing and management to NOS(Network Operating System). First, This study presented CIMS(construction information classification system) reflected the characteristics of facility classification - functional component classification - functional component classification - work classification - resource classification. Based on this system. this study presented how to establish PMMB(performance measurement management baseline) with proposed master target equation which analyzed the trend of performance measurement management baseline and proposed work target equation which analyzed the execution results. Finally, this study presented NOS model that can be applied to fixed price method and cost plus fee method through the theoretical verification of executive performance analysis method.

• Korean Journal of Construction Engineering and Management
• /
• v.14 no.3
• /
• pp.42-52
• /
• 2013

The aim of this study is to present a prediction model of construction cost for a bridge that has a high reliability using historical data from the planning phase based on a CBR (Case-Based Reasoning) method in order to overcome limitations of existing construction cost prediction methods, which is linearly estimated. To do this, a reasoning model of bridge construction cost by a spreadsheet template was suggested using complexly both CBR and GA (Genetic Algorithm). Besides, this study performed a case study to verify the suggested cost reasoning model for bridge construction projects. Measuring efficiency for a result of the case study was 8.69% on average. Since accuracy of the suggested prediction cost is relatively high compared to the other analysis methods for a prediction of construction cost, reliability of the suggested model was secured. In the case that information for detailed specifications of each bridge type in an initial design phase is difficult to be collected, the suggested model is able to predict the bridge construction cost within the minimized measuring efficiency with only the representative specifications for bridges as an improved correction method. Therefore, it is expected that the model will be used to estimate a reasonable construction cost for a bridge project.

• Korean Journal of Construction Engineering and Management
• /
• v.9 no.6
• /
• pp.235-243
• /
• 2008

Construction projects have unique characteristics that these may be carried out by contractors thus, cost should be estimated before execution. The importance of cost estimation and cost check has become increasingly emphasized in all phases of construction project that would be performed numerously. It is needed that owner have to estimate reasonable budget, and contractor should predict the bid price. However, there are lack of standard cost estimation method before quantity takeoff, cost analysis method, and cost database thus, the method of area cost, such as square foot method, is as used as ever in Korea. Therefore, this research suggested standard cost database structure CUBE, and analysis method of item quantity per one household categorized by area type. Whereafter, database of all item quantity of finish work has been built with 90 building cost data, and validated it's availability. In this respect, the suggested method and the findings from this research are expected to help enhancing the efficiency and productivity of cost estimation in Korea.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2006.05a
• /
• pp.115-118
• /
• 2006

빙축열 시스템과 같은 열교환 시스템을 이용하여 심야의 전력 경부하 시 주간에 이용할 냉방부하를 축열하였다가 주간에 공급함으로써 전력의 평준화와 전력 설비의 효율적 운용을 기할 수 있어 전력의 안정적인 수급과 에너지의 효율을 극대화할 수 있다. 하지만 빙축열 시스템의 제어 운전을 전적으로 운전자의 경험에 의존하는 경우에 충분한 냉방 부하를 공급하기 위한 잉여축열에너지가 비경제적으로 많아져서 빙축열 시스템의 경제성이 저하되고 사용 효과가 낮아지는 문제점이 많이 발생되고 있다. 경제적인 활용 효과를 고려하여 빙축열 시스템을 효율적으로 운용하기 위해서는 냉방부하량이 기후 특성에 의해 결정되므로 기후를 정확하게 예측하고 이를 토대로 다음날의 시간별 냉방부하를 예측하여 적정한 축열량을 결정하여야 하는 어려움이 따른다. 이러한 문제를 해결하기 위해 본 연구에서는 신경망을 이용하여 기상 데이터를 토대로 다음날의 온도와 습도를 예측하고 예측된 온도와 습도 및 냉방부하 실적 자료를 기반으로 신경망을 이용하여 시간별 냉방부하를 예측하는 알고리즘을 제시하였다. 제안된 냉방 부하예측 알고리즘에 의해 구축된 한국전력공사 속초생활연수원의 부하예측모델을 이용하여 온도, 습도, 냉방부하를 예측한 결과 기존 방법에 의한 것보다 우수한 예측 성능을 보였다.