Port of Chittagong Rides Out the Storm

Nov. 27, 2019

 |  Insights

While the peak of the 2019 tropical storm season has passed, Cyclone Bulbul hit Bangladesh on November 10. In anticipation of the severe storm, the country suspended its port operations, resulting in a 36-hour closure of Port of Chittagong, the main port of Bangladesh. We studied the impact on vessel waiting times and arrivals at the port. While we expected it to lead to a longer queue of pending ships, the delays were actually not much longer than normal for the vessels that did not skip the port.

The port often has heavy congestion due to various problems, including port operations inefficiency, a lack of truckers, and traffic jams. Prolonged waiting time for arriving vessels are also quite common.

We expected to find that the storm and port closure would further worsen the conditions and lead to an even longer queue of pending ships. However, after analyzing container vessel arrivals and departures based on Automatic Information System (AIS) data about vessels' actual locations, we did not find a severe impact compared to normal operations.

Chittagong Study Scope

Duration:  October 26 - November 26, 2019
Total Vessel Arrivals:  92
Average Vessel Waiting Time:  70 Hours



As shown in the figure below, no vessels arrived on November 9, vessel arrivals jumped on November 10, and operations returned to normal by November 11.

When looking at the vessel waiting time, we found that vessels that arrived on November 8, waited to berth outside the immediate port area over four days on average. In contrast, vessels that arrived before November 8, waited under two days on average. Following the storm, vessels waited around three days, closer to the average waiting time before the developing storm.

Using the power of the Internet of Things to track real-time container movements enables us to see beyond basic shipping milestones. Analyzing the AIS data revealed that vessel waiting times were not much longer than the lengthy waiting times before the storm.

Tags: analytics , big data , vessel waiting time , port congestion , sailing schedules , insights