• International conference on construction engineering and project management
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• 2009.05a
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• pp.1140-1147
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• 2009

Productivity measurement of construction machinery is a significant issue faced by many contractors especially those involved in earthwork projects. Traditionally, equipment production rate has been estimated using data available in manufacturers' catalogues, results of previous construction projects, or personal experience and assessments of the site personnel. Actual production rates obtained after the completion of a project demonstrate the fact that most of these methods fail to provide accurate results and as a direct consequence, may lead to unrealistic project cost estimations prepared by the contractors. What makes this more critical is that in most cases, inadequate cost estimations lead the entire project to exceed the initial budget or fall behind the schedule. In this paper, a linear regression method to estimate bulldozer productivity is introduced. This method has been developed using SPSS-16 software package. The presented method is used to estimate the productivity of Komatsu D-155A1 series which is commonly used in many earthmoving operations in Iran. The data required for the numerical analysis has been collected from actual site observation and productivity measurement of 60 pieces of D-155A1 series currently being used in several earthmoving projects in Iran. Comparative analysis of the output data of the presented regression method and the existing productivity tables provided by the manufacturer shows that when compared to the actual productivity data collected on the jobsite, a significant increase in accuracy and a remarkable reduction of data variance can be achieved by using the presented regression method.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.231-234
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• 2013

According to the recent development of USN technology, it has been applied in various fields of construction management. In particular, the concrete curing management using the wireless measurement system is actively being conducted. However, the existing method has limitations such as the reinstallation of temperature sensors and repositioning of repeaters. It is also not easy to acquire the measured data. Thus, this study focuses on the concrete curing management. This study proposes data acquisition method using the smartphone on construction site and tests applicability of the data measuring device and the smartphone. The test allows us to suggest the actual communication distance on construction site and to determine the correction value that is applied to the measured temperature. The data acquisition method proposed in this study is intended to enable appropriate management on construction site and will be able to be applied effectively to a variable construction site. It can also be used in all fields of construction management.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.488-493
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• 2013

Accurate initial cost estimates are essential to effective management of construction projects where many decisions are made in the course of project management by referencing the estimates. In practice, the initial estimates are frequently derived from historical actual cost data, for which standard distribution-based techniques are widely applied in the construction industry to account for risk associated with the estimates. This approach assumes the same probability distribution of estimate errors for any selected estimates. This assumption, however, is not always satisfied. In order to account for the probabilistic nature of estimate errors, an alternative method for measuring the risk associated with a selected initial estimate is developed by applying the Bayesian probability approach. An application example include demonstrates how the method is implemented. A hypothesis test is conducted to reveal the robustness of the Bayesian probability model. The method is envisioned to effectively complement cost estimating methods that are currently in use by providing benefits as follows: (1) it effectively accounts for the probabilistic nature of errors in estimates; (2) it is easy to implement by using historical estimates and actual costs that are readily available in most construction companies; and (3) it minimizes subjective judgment by using quantitative data only.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.153-160
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• 2009

The demand for super tall building construction is increasing worldwide. There has been a constant request for achieving early payback on investment by shortening the construction time. This pertains especially for the case of huge investment projects such as super tall building construction. It is very important to shorten the construction time for the building framework, which requires substantial construction time and cost, and this is directly related to the establishment of an optimum lift plan for construction. When there is a problem in the selection of the lift equipment, it is almost impossible to revise the selection, resulting in a possible failure of the project. Thus, the purpose of this study is to analyze the function and logic for the development of the process for the selection of lift equipment for super tall building projects and further development of making the analyzed process into a system. In line with this research objective, the process of selecting the optimum lift equipment by domestic construction company was investigated and analyzed as well as collecting the actual field data. The actual data were obtained by sensors installed on tower cranes at three construction sites with the help from the construction company.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.05b
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• pp.171-174
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• 2009

The standard estimation system, used to estimate the predetermined cost of construction work, is measured by the standard and typical construction methods and field conditions. And the standard estimation system is applied to basic data for the measuring of construction cost, such as the consumed quantity of material, labor hours, and machinery cost. However it does not reflect sufficiently for the diversity and reality of constructions work Therefore, this study is recognized the necessity of new cost estimation models for the rational construction cost estimation. To improve estimation technique and construction ability, it was analyzed labor hours, production volume based on the work crew in construction work.

• Journal of the Society of Disaster Information
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• v.9 no.1
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• pp.11-21
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• 2013

This study proposed cost prediction equation model by considering duration, construction, size, actual cost with the subway construction started by the actual cost system which was introduced since 2004. Costs - scale exponent n(confidence range: 0.5 to 0.7) for cost prediction of subway construction was drawn total cost(0.713), net cost(0.77) in point of the 11 subway construction data. The cost prediction equation model of the subway construction which was presented in this study is able to effectively apply to business planning, preliminary investigation, feasibility study, basic design stage to estimate the approximate cost in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.497-502
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• 2020

For the Navy to acquire the desired vessels in time, it is necessary to plan the schedule accurately for warships. On the other hand, until now, there has been only a subjective prediction of the period of warship construction through a survey by a group of experts. No academic studies have been conducted based on actual data. Therefore, this study presents a model for predicting the construction period of a warship through linear regression based on actual data. Experts first identified the factors that can affect the warship construction period. Actual data of the factors were collected, and regression analysis was performed to estimate the ship construction period. As a result, the key factors selected that influence the construction period of a ship were the number of operational test items, number and type of equipment, and the number and type of R&D equipment. The resulting regression model revealed 96.5% accuracy in terms of internal validity.

• Journal of the Korea Institute of Building Construction
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• v.16 no.2
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• pp.133-140
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• 2016

The amount of labor input in a construction project is used as source data to estimate construction cost and to understand the productivity of the construction industry. However, there is a significant difference between the standard of estimation and the actual amount of labor input, and a plan is needed to resolve this problem. For this reason, to establish a system with which the actual amount of labor input can be inputted in a more accurate and simpler manner, a new method is proposed in this study. In the new method, a digital pen is used to minimize the difference from traditional handwriting on paper using a pen, and eliminate the redundant input of information. This study is expected not only to reduce the actual amount of labor input but also to contribute to the productivity of construction cost estimate through the sharing or utilization of the information on the web.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.250-251
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• 2021

A subcontract work order is the basis of the construction process and consists of the root and trunk of the construction industry. The construction process through a subcontract work order is an important element of project success, and it is the basic unit of creating profit in the construction industry. Therefore, correct analysis and forecasting of subcontract work orders allow correct estimation of construction cost and profit which is the foundation of corporate decision making. This study has started to provide predictions of subcontractor's bidding-ratio for decision-making. Since the actual project data has been used in this study, the contribution level of the model is highly expected in actual field. The statistical confidential level of adjusted decision coefficient is concluded low because of limited sample numbers. However, its accuracy and confidence level can be increased through increasing sample numbers, considering more variables, and studying of reducing error.

• Journal of Environmental Science International
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• v.22 no.5
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• pp.533-542
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• 2013

In this study, estimation methods for actual evapotranspiration have been studied using the concept of potential and actual evapotranspiration. Among the diverse estimation methods, SWAT-K application is chosen for hydrological modeling. For Jeju island we have characterized annual and monthly evapotranspiration using SWAT-K. In the results, simulated potential evapotranspiration reached to the 91% of small pan evaporation. With respect to the temperature lapse rate($-6^{\circ}C/km$) depending on the altitude of Halla mountain, evapotranspiration rate decreased by 7.5% compared to the status when the temperature data from the Jeju weather station were applied to the watershed. As the average of annual rainfall increased, potential evapotranspiration was increased, actual evapotranspiration was, however, decreased.