MULTIPLE LINEAR REGRESSION APPROACH FOR PRODUCTIVITY ESTIMATION OF BULLDOZERS

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.