Production prediction of conventional and global positioning system–based earthmoving systems using simulation and multiple regression analysis

Accurate estimation of construction production, which is composed of productivity and unit costs, allows construction planners and managers to have excellent control over current processes and to correctly predict the production of similar projects in the future. Due to the need for accurate production estimation, selection of the appropriate construction technology is a critical factor in the success of a project. This paper presents a methodology for developing a model capable of predicting productivity and unit costs using several procedures, such as actual data collection, input data generation using construction simulation, and multiple regression analysis. An earthmoving operation was analyzed to estimate the proposed methodology’s prediction of construction production. A global positioning system (GPS)–based earthmoving system was selected as the new construction technology to be compared with the conventional system, to evaluate the decision-making process at a jobsite. The proposed methodology is expected to provide users with a basis for selecting appropriate technology. The case study presented in this paper demonstrates how to utilize the proposed methodology and analyze its predicted results.