Framework of the approximate cost estimating model for river dredging construction

Abstract

Enhancing the accuracy of an approximate cost estimate is a critical issue since the estimate ordinarily predicts the total cost of a project with insufficient project information. In order to facilitate the approximate cost estimate process, this paper proposes a computer-based integrated system that enables the flexibility to varying amount and accuracy of available information, higher accuracy by using several different adjustment factors at the same time, and decision supporting feature by fast manipulation of the profits and contingencies in determining the final bid price. Proposed methodology has been implemented for a steel mill construction company in Korea, and its viability was validated. Findings and practical implications are outlined. Keywords: approximate estimate, historical database, adjustment factors, information system 1. INTORDUCTION Preliminary estimating, especially for the design-build contracts, is a critical process predicting the total cost of a project with insufficient project information. In order to enhance the accuracy of a preliminary or an approximate estimate, several methodologies have been developed and utilized. Approximate cost estimating methods ordinarily utilize parameters, factors, and indices. In addition, the advanced applications including probability and statistics, neural networks (NN), and relational database management systems (RDBMS) have been employed for the purpose of improving the accuracy. Findings of previous studies [1][2][3][4] indicate that the accuracy of the estimate using these advanced applications can be increased up to 20%. The approxi mate cost estimating method based on historical cost records is a frequently used one as well. When using this method, the quality of the historical cost data from the previously performed projects is a crucial factor determining the quality of the estimate result. The purpose of this research was to develop an estimating methodology and a computerized system for an engineering and construction firm in Korea, that has abundant experience in planning, designing, procurement, construction, inspection, and test operation of the Pohang and Kwangyang steelworks of the world's second largest steel company. The estimating system developed as a result of this research is integrated with the project management information system (PMIS) of the company in order to obtain quality information in a timely manner. 2. SYSTEM DEVELOPEMENT The system developed in this research, named CEDA (Capital cost Estimate Data Analysis), uses relational database management systems (RDBMS) that manipulate all relevant estimate data and the historical database as well. CEDA consists of two subsystems; one for the estimate of construction cost and the other for the estimate of equipment cost. In estimating the cost of construction, the system mainly utilizes the shared historical construction performance database focused on actual labor productivity. For the cost estimate of major equipment to be installed in the steel mill, this system provides a...

Environmental management for dredging sediments – The requirement of developing nations

“…For example, Lee (2011) attempted to create a framework for dredging cost, analysing the construction operation process, type of river section, and the combination of equipment employed for river dredging. This analysis was based on historical data of river dredging projects conducted in South Korea (Lee et al, 2011). (Briffett et al, 2004) -Difficult to enforce EIA 1987 Order (Emang, 2006) -Lack of cumulative impact analysis (Briffett et al, 2004) -Illegal sand dredging -Environment aspect was not included during pre-planning stage (Briffett et al, 2004) -Lack of baseline data/evidence based documents (Briffett et al, 2004) Despite the fact that developing countries were estimated to become the largest dredging markets in the world over the next few years, stiff competition from foreign dredging contractors heightens the need to lower costs for local dredging contractors (George, 2011, Thacker, 2007.…”