ITcon Vol. 21, pg. 39-56,

Productivity based method for forecasting cost & time of earthmoving operations using sampling GPS data

submitted:May 2015
revised:March 2016
published:March 2016
editor(s):Turk Ž
authors:Dr. Adel Alshibani, (corresponding author)
Department of Architectural Engineering , College of Environmental Design, KFUPM, Dhahran, 31261, Kingdom of Saudi Arabia,

Dr. Osama Moselhi, Professor
Department of Building, Civil and Environmental Engineering, Concordia University, 1455 De Maisonneuve Blvd. W. Montreal, QC H3G 1M8, Canada
summary:Accurate estimate of onsite productivity of earthmoving operations is essential for successful delivery of this class of projects. Estimating onsite productivity is a difficult task that requires tracking heavy and costly equipment and requires collecting, managing, and analyzing a considerable amount of data from construction sites on daily bases. Despite the fact that there are many systems available to carry out such process, those systems are expensive and require collection of large volume of data. This paper introduces a newly automated web based system for estimating actual productivity and for forecasting cost and time of earthmoving operations in near real time. The developed system integrates Global Positioning System (GPS) and Geographical Information System (GIS) in addition to four developed algorithms. The proposed system makes use of limited samples of GPS data for tracking and control purpose instead of collecting large volume of data from construction sites. The proposed system considers uncertainties associated with activity durations and cost. The results obtained from the application of the proposed system to two actual projects, indicates that the proposed system can be used as an effective tool for tracking and control of earthmoving operations.
keywords:Cost, Forecasting, GPS, Productivity, Time, Uncertainties
full text: (PDF file, 1.444 MB)
citation:Alshibani A, Moselhi O (2016). Productivity based method for forecasting cost & time of earthmoving operations using sampling GPS data, ITcon Vol. 21, pg. 39-56,