• International conference on construction engineering and project management
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• 2005.10a
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• pp.1112-1117
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• 2005

Construction cost index is generally used to estimate the new project cost based on past construction data and to adjust contract cost when the price change of various articles and items of expenditure composing the contract occurs. In Korea, it is mostly used for adjustment of construction contract cost due to fluctuation of prices. However index adjustment rate which is used for adjustment of construction contract cost had some problems in calculating cost index of each expenditure item that could not reflect properly the change of construction cost. For supplementing these problems, the research of developing construction cost index has been executed. Through the precedent research, these problems were partially resolved but still remain. Therefore this research proposes method of making cost index that utilizes representative items of labor, material, and equipment by analyzing bill of quantity of road construction, through analysis and comparison of precedent study. By using this method, it is expected to solve problems which were not reflected in precedent studies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.5
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• pp.527-534
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• 2020

A significant factor in construction work is cost. At early- and advanced-stage design, costs should be calculated to derive realistic cost estimates according to unit price calculation. Based on these estimates, the economic feasibility of construction work is assessed, and whether to proceed is determined. Through the Korea Institute of Civil Engineering and Building Technology, the construction cost index has been calculated by indirect methods after both the producer price index and construction market labor have been reprocessed to easily adjust the price changes of construction costs in Korea, and the Institute has announced it since 2004. As of January 2000, however, the construction cost index was released, and this has a time constraint on the correction and use of past construction cost data to the present moment. Variables were calculated to compute a rough construction cost that utilized past construction costs through surveys of the producer price index and the construction market labor force consisting of the construction cost index. After significant independent variables among the many variables were selected through correlation analysis, the construction cost index from 1970 to 1999 was calculated and presented through multiple regression analysis. This study therefore has prominent significance in terms of proposing a method of calculating rough construction costs that utilize construction costs that pre-date the 2000s.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.908-912
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• 2005

Construction Cost Indices are values for measuring fluctuations in direct construction costs which include material costs, labor costs, and equipment costs for construction operations. In Korea, Korea Institute of Construction Technology (KICT) has been assessing and announcing these indices since January, 2004. The main goals of this paper are to look over the calculation process for those indices and then present the trend in construction costs according to the types of facilities with the past construction cost index data. Also, this paper traces the origin of the occurrence of significant changes on those indices through the further analysis of the trend. In addition, this paper shows the practicality of the indices and the way how to put them to practical use. An alternative estimate method using the indices is suggested for compensating the changes of construction costs caused by price fluctuations.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.11a
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• pp.291-292
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• 2012

Progress in the construction project, the estimated cost of the measure is very important. Use preliminary estimate cost data for the prediction of construction cost. But, preliminary estimate cost data a clear calculation, there is no way. it is rely on the historical data and the past construction data. As a result, a significant difference in the actual construction cost and the predicted cost of the problem occurs. In this study, taking advantage of BIM Cost Prediction for efficient and rapid preliminary estimate BIM for building database through the study preliminary estimate cost data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6D
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• pp.829-837
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• 2011

Construction cost estimation in planning phase which calculates the cost for performing construction tasks is used for various ways. Meanwhile, in the case of road construction, the existing cost estimating method in early phase based on numerical mean value of the past is not accurate to be used. This paper propose neural network model for estimating road construction cost in planning phase to solve the limit of current cost estimating method. The model was designed using past road construction bidding records, and variables of model were optimized through trial and error. The estimation result of the model was compared with regression analysis and government's standard and it was verified that the model is better in accuracy. It is expected that the proposed model will be used for road cost estimation in planning phase.

• Geomechanics and Engineering
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• v.28 no.1
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• pp.65-75
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• 2022

Time and cost of construction are key factors in decision-making during a tunnel project's planning and design phase. Estimations of time and cost of tunnel construction projects are subject to significant uncertainties caused by uncertain geotechnical and geological conditions. The Gaussian Process Regression (GPR) technique for predicting ground condition and construction time and cost of mountain tunnel projects is used in this work. The GPR model is trained with data from past mountain tunnel projects. The model is applied to a case study in which the predicted time and cost of tunnel construction using the GPR model are compared with the actual construction time and cost for model validation and reducing the uncertainty for the future projects. In addition, the results obtained from the GPR have been compared with to other models of artificial neural network (ANN) and support vector regression (SVR) that the GPR model provides more accurate results.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2011.11a
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• pp.17-18
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• 2011

Over the past 20 years, Researchers have tried to develop "Integration Model of Cost and Schedule" in construction industry. They suggested various models and techniques, however, it is still required to develop new methodology for AL Form Work in Public Multi-Housing Projects. Accordingly, this research focused on measuring quantity take-offs of on-going projects and analysing the basic process of using the resources(Labor, Material, Plant) related to cost and time data. There are 3 steps of this research : 1) The literature review of previous studies about Integration Model of Cost and Schedule was conducted. 2) Model for integration between cost and schedule was developed. 3) the accuracy of developed model was verified. The results are expected to improve in integrated managing the cost and schedule data of AL form work.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2010.05a
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• pp.143-147
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• 2010

Due to the diversification and complication of construction projects, controlling risks from the early design-planning phase gives huge impact on success of the construction project. As a part of managing uncertainties it is also important to estimate the project cost several times. Especially, estimating project cost in the early stage gives effects on making a budget for projects. This study estimated the apartment project cost using case-based reasoning(CBR), which is the process of solving new problems based on the past problems. For this, we deduced the apartment cost influence factors which can be gathered in the early stage of project. Based on the factors we established the database for apartment project and calculated the attribute value, attribute similarity and case similarity. Although we retrieve the most similar case from the database, it is very hard to utilize it directly due to the uniqueness of each project. So, Genetic Algorithm(GA) was applied in revising the cost of the retrieved-case. Therefore, the accuracy of the prediction was improved by GA optimization.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1707-1718
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• 2013

Historical cost data estimating system has been introduced since 2004 in the construction industry. Based on contract prices of past projects, this estimating system estimates construction cost according to work types. The Korea Institute of Construction Technology (KICT) announces the historical cost data twice a year annually. The unit price of a small construction project is higher than large construction project due to the increase on production cost per work unit, equipment and labor cost, etc. However, the historical cost data estimating system is applied to project estimation uniformly regardless the construction project's size. This study compared and analyzed the historical cost data of large and small construction project to indicate the problem of historical cost date estimating system. The study derived that the unit price of a small construction project is 21.8% higher than that of large construction project.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.105-113
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• 2006

Construction cost index is generally used to estimate the new project cost based on past construction data and to adjust the contract cost when the price change of various articles and items of expenditure composing the contract occurs. In Korea, it is mostly used for modulation of construction contract cost due to fluctuation of prices. However the method for making cost index had some problems in calculating cost index of each expenditure item that could not properly reflect the change of construction cost. To supplement these problems, the research of developing construction cost index has been executed. Through the precedent research, these problems were partially resolved but still remain. Therefore this research proposes the method for making cost index that utilizes representative items of labor, material, equipment by analyzing bill of quantity of road construction, through analysis and comparison of precedent studies. By using this method, it is expected to solve the problems which were not reflected in preceeding studies.