Duration of concrete pouring task is typically considered from the arrival time of the first Ready Mixed Concrete (RMC) truck until the end of the pouring process of the last truck. In practice, the concrete pouring duration does not only depend on site features. In fact, the duration is also affected by other parameters such as supply process, location of the project and traffic conditions, particularly in cities with heavy traffic. This paper investigates impacts of supply chain parameters on predicting concrete pouring duration that have been typically excluded from such analyses. Unlike other studies which are limited to construction site parameters in predicting concrete pouring duration, this study not only considers construction site factors at a general level but also investigates the impact of supply related parameters. To test the effectiveness of considered variables a field dataset of an active RMC in Adelaide, Australia with four batch plants and around 40 trucks is used. The dataset covers a period of a month which includes 2,658 deliveries to more than 500 locations. In terms of the modeling practice of this study, first a preliminary linear regression is developed and then it is modified to satisfy crucial assumptions of heteroscedasticity and residuals normality. Finally, a hazard-based model where the assumption of residual normality is relaxed, is developed. The results show that severe bias occurs when assumptions associated with linear regression are overlooked. Moreover, in the developed models the supply parameters are found to have significant impacts on concrete pouring duration.

Keywords