Port of Hamburg is using machine learning (ML) to predict the dwell time of a container at the terminal, with the first two projects successfully integrated and implemented into the IT landscape at Container Terminals Altenwerder (CTA) and Burchardkai (CTB).
The goal of this initiative is to predict the exact pickup time of a container. Processes are substantially optimised when a steel box does not need to be unnecessarily restacked during its dwell time in the yard. When a container is stored in the yard, its pickup time is frequently still unknown. In future, the computer will calculate the probable container dwell time. It uses an algorithm based on historic data which continually optimises itself using state-of-the-art machine learning methods.
Angela Titzrath, Chairwoman of the Executive Board of HHLA during the World Artificial Intelligence Conference (WAIC) stated that
Advancing digitalisation is changing the logistics industry and our port business with it. Machine learning solutions provide us with many opportunities to increase productivity and capacity rates at the terminals.
It is added that a similar technology is taking place at the CTB, where a conventional container yard is used alongside an automated one.
Already both terminals are experiencing the advantage of these technology, since the containers are stored based on their predicted pickup time and must therefore be moved less frequently. The projects were driven forward by teams from HHLA and its consulting subsidiary HPC Hamburg Port Consulting.
