• Journal of the Korea Institute of Building Construction
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• v.8 no.1
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• pp.97-102
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• 2008

The report of the Korean Board of Audit and Inspection(BAI) on May 2007 indicates the problems of Life Cycle Cost (LCC) analysis and evaluation in the Design-Build(Turn-Key) and alternative bidding system. The point which the report indicates is that the cost estimation system for LCC analysis has nothing in common each other and there's no consistency among the repair cycle and ratio per facilities parts. For solving these problems, BAI demands the establishment of the guidelines for LCC analysis and evaluation from the competent authority Korean Ministry of Construction And Transportation(MOCT). The objective of this study is to develop the improvement directions for LCC analysis and evaluation which are suitable to the public construction projects especially for the Design-Build and alternative bidding system in Korea. For this study, the LCC related raws and regulations, LCC analysis guidelines of public cooperations, actual condition of LCC analysis and evaluation which include, the elements of LCC, the estimation rules of the initial cost and the maintenance cost, the analysis standards of time value of money, etc. are investigated to provide the improvement directions for LCC analysis and evaluation.

• Journal of the Korea Institute of Building Construction
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• v.8 no.2
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• pp.53-61
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• 2008

It is expected that the market of residential facility for retired seniors will be a new investment field for construction firms. This study describes the questionnaire survey analysis results of potential customers' demand for the facility. For comparison purpose, direct construction cost was estimated by estimation experts. In addition, a case analysis was conducted to compare direct cost and indirect project cost with the experts' estimation. According to the questionnaire survey analysis, it is observed that there were significant differences in demand between groups which are classified by the regions, living expenditures, the level of property ownership and the scales of residence. From an investor's perspective, investment decision on residential facility for retired seniors should be made considering bothe the level of returns which can be generated from the investment and the customers' needs.

• Journal of the Korea Institute of Building Construction
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• v.12 no.5
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• pp.518-527
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• 2012

This study uses a hybrid estimation tool for effective cost data management of building projects, and develops a realistic cost estimation model. The method makes use of newly available information as the project progresses, and project cost and percentage progress are analyzed and used as inputs for the developed system. For model development, case-based reasoning (CBR) is proposed, as it enables complex nonlinear mapping. This study also investigates analytic hierarchy process (AHP) for weight generation and applies them to a real project case. Real case studies are used to demonstrate and validate the benefits of the proposed approach. By using this method, an evaluation of actual project performance can be developed that appropriately considers the natural variability of construction costs.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.597-598
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• 2015

In order to improve the reliability of cost estimation results using CBR, there has been a continuous issue on similarity measurement to accurately compute the distance among attributes and cases to retrieve the most similar singular or plural cases. However, these existing similarity measures have limitations in taking the covariance among attributes into consideration and reflecting the effects of covariance in computation of distances among attributes. To deal with this challenging issue, this research examines the weighted Mahalanobis distance based similarity measure applied to CBR cost estimation and carries out the comparative study on the existing distance measurement methods of CBR. To validate the suggest CBR cost model, leave-one-out cross validation (LOOCV) using two different sets of simulation data are carried out. Consequently, this research is expected to provide an analysis of covariance effects in similarity measurement and a basis for further research on the fundamentals of case retrieval.

• Journal of the Korean Society for Advanced Composite Structures
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• v.6 no.4
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• pp.24-29
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• 2015

Bridge construction cost estimates have generally been conducted by using historial unit-price(per meter or square meter). The traditional estimating method based on unit-price references can never completely reflect the specialty of cable supported bridge. In this paper, we have developed the system for supporting the approximate construction cost and the quantity estimation based on 3D model information in the pre-project planning phase of 3-span continuous suspension bridge with 2-pylons. First of all, we'd analyzed the design information (such as structural design report, blueprint and quantity) and the real cost data from the existing suspension bridges and derived the design variables of the bridges. We developed the BIM wizard that generates a suspension bridge model parametrically based on derived design variables. The principle material quantities of suspension bridge are calculated directly from 3-dimensional bridge model built by using the BIM wizard. We have established the system that the construction cost can be estimated more specific than the traditional estimating method.

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

• Korean Journal of Construction Engineering and Management
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• v.10 no.3
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• pp.139-147
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• 2009

Accurate construction cost estimation in the initial stage of building project plays a key role for project success and for mitigation of disputes. Total construction cost(TCC) estimation of apartment projects in Vietnam has become more important because those projects increasingly rise in quantity with the urbanization and population growth. This paper presents the application of artificial neural networks(ANNs) in estimating TCC of apartment projects. Ninety-one questionnaires were collected to identify input variables. Fourteen data sets of completed apartment projects were obtained and processed for training and generalizing the neural network(NN). MATLAB software was used to train the NN. A program was constructed using Visual C++ in order to apply the neural network to realistic projects. The results suggest that this model is reasonable in predicting TCCs for apartment projects and reinforce the reliability of using neural networks to cost models. Although the proposed model is not validated in a rigorous way, the ANN-based model may be useful for both practitioners and researchers. It facilitates systematic predictions in early phases of construction projects. Practitioners are more proactive in estimating construction costs and making consistent decisions in initial phases of apartment projects. Researchers should benefit from exploring insights into its implementation in the real world. The findings are useful not only to researchers and practitioners in the Vietnam Construction Industry(VCI) but also to participants in other developing countries in South East Asia. Since Korea has emerged as the first largest foreign investor in Vietnam, the results of this study may be also useful to participants in Korea.

• Korean Journal of Construction Engineering and Management
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• v.21 no.6
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• pp.113-124
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• 2020

Social movements to improve the performance of buildings through remodeling of aging apartment houses are being captured. To this end, the remodeling construction cost analysis, structural analysis, and political institutional review have been conducted to suggest ways to activate the remodeling. However, although the method of analyzing construction cost for remodeling apartment houses is currently being proposed for research purposes, there are limitations in practical application possibilities. Specifically, In order to be used practically, it is applicable to cases that have already been completed or in progress, but cases that will occur in the future are also used for construction cost analysis, so the sustainability of the analysis method is lacking. For the purpose of this, we would like to suggest an automated estimating method. For the sustainability of construction cost estimates, Deep-Learning was introduced in the estimating procedure. Specifically, a method for automatically finding the relationship between design elements, work types, and cost increase factors that can occur in apartment remodeling was presented. In addition, Monte Carlo Simulation was included in the estimation procedure to compensate for the lack of uncertainty, which is the inherent limitation of the Deep Learning-based estimation. In order to present higher accuracy as cases are accumulated, a method of calculating higher accuracy by comparing the estimate result with the existing accumulated data was also suggested. In order to validate the sustainability of the automated estimates proposed in this study, 13 cases of learning procedures and an additional 2 cases of cumulative procedures were performed. As a result, a new construction cost estimating procedure was automatically presented that reflects the characteristics of the two additional projects. In this study, the method of estimate estimate was used using 15 cases, If the cases are accumulated and reflected, the effect of this study is expected to increase.

• Korean Journal of Construction Engineering and Management
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• v.15 no.1
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• pp.3-10
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• 2014

High-rise buildings need thorough cost management because of large size and high risk. Cost management makes a budget by establishing and analyzing detail element at planning phase, needs cost control as each design phase, then reflected to next design. This research develops a schematic estimation model based on vertical and horizontal elements at design phase for structure cost of high-rise buildings to reduce error range and use data as design management. Usability of the model is confirmed by case study. The estimation model is expected to contribute to making the cost model more effective and satisfactory to concerned in construction or budget department and manage keeping track of the cost.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.823-830
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• 2022

The risk of project execution increases due to the enlargement and complexity of Engineering, Procurement, and Construction (EPC) plant projects. In the fourth industrial revolution era, there is an increasing need to utilize a large amount of data generated during project execution. The design is a key element for the success of the EPC plant project. Although the design cost is about 5% of the total EPC project cost, it is a critical process that affects the entire subsequent process, such as construction, installation, and operation & maintenance (O&M). This study aims to develop a system using machine-learning (ML) techniques to predict risks and support decision-making based on big data generated in an EPC project's design and construction stages. As a result, three main modules were developed: (M1) the design cost estimation module, (M2) the design error check module, and (M3) the change order forecasting module. M1 estimated design cost based on project data such as contract amount, construction period, total design cost, and man-hour (M/H). M2 and M3 are applications for predicting the severity of schedule delay and cost over-run due to design errors and change orders through unstructured text data extracted from engineering documents. A validation test was performed through a case study to verify the model applied to each module. It is expected to improve the risk response capability of EPC contractors in the design and construction stage through this study.