Big Data Utilization and Analysis to Improve Operational Performance of Hybrid Straddle Carrier in Container Terminal

Abstract

Big data analytics has triggered various advances in marine terminal research and information technology implementation. Specifically, for container terminals, big data technology has much to offer in understanding and consolidating information between port users and operators. One of the clear advantages for port operators is the opportunity to exploit the operational potential of cargo handling machinery. In 2015, we developed and introduced a method to effectively measure the performance of a hybrid straddle carrier (HSC) utilizing big data collection and analysis. Since 2017, this method has been used in the form of the Eco-Lamp prototype installed on HSCs at a medium-size container terminal in Japan. This study will analyze the effectiveness of that implementation, present the result achieved from the big data analytic point-of-view, and discuss the challenges and possible improvement of the system toward cost savings and efficient operation of port equipment.