TRANSPORTATION FRAMEWORK IN PANELIZED CONSTRUCTION FOR RESIDENTIAL BUILDING

Abstract

Transportation operations, in connecting the factory with the construction site through the delivery of prefabricated building components (e.g., panel) using transportation equipment (e.g., trucks and trailers), play a significant role in determining the efficiency of overall panelized construction operations. However, several issues surrounding transportation operations have been identified, including the fact that operations planning and decision making are typically carried out in an experience-based manner in the absence of a systematic approach to transportation management, while existing construction transportation planning approaches are based on a material flow and information flow that are ineffective for offsite construction. Thus, this research proposes the development of an automated transportation planning approach tailored to panelized construction, the framework for which can provide better transportation planning and decision making based on collected data from actual logistics operations. In developing the framework, various tools for logistics planning are considered. First, a projection based augmented reality (AR) is applied to improve potential transportation quality issue during panel manufacturing processes at offsite facility. Second, an extensive data collection system using quick response (QR) codes and global positioning system (GPS) is proposed to improve the transparency of logistics operations as well as to validate the optimized fleet-dispatching plan from the simulation. Third, machine learning (e.g., SVM) and rule-based algorithms are utilized to extract key information the collect data and perform estimations on durations and costs. Fourth, fleet-dispatching discrete-event simulation (DES) is established in order to determine the optimum fleet management schedule and construction job schedule based on construction site locations. The proposed framework addresses existing issues while providing optimized, data-driven planning and decision support. Potential contributions include efficiency improvement in transportation operations for panelized construction, reduced transportation costs, and improved transportation data collection and utilization.