The use of ETA in prediction of pick-up of containerized goods at port
Typ
Examensarbete för masterexamen
Master's Thesis
Master's Thesis
Program
Maritime management (MPMAR), MSc
Publicerad
2022
Författare
Ringborg, Johannes
Svanborg, Erik
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
Increased global trade combined with logistical disturbances due to COVID – 19 as well as Ever
Given blockade of the Suez Canal have generated increased pressure on the global supply chain
during the recent years. With the global trading predicted to grow during the upcoming period, partly
due to increased e-commerce and consumption, the situation within the intermodal transportation
chain is more pressured than ever. At the same time, the goods – owners still desire to track their
cargo as well as receive precise information regarding the predicted arrival time. This kind of
transparency could be difficult to address during the current state of the world, especially within a
dynamic environment, such as the maritime domain. This thesis addresses the possibilities as well as
difficulties in predicting the arrival time for container vessels, based on the Estimated Time of Arrival
(ETA) retrieved from the Automatic Identification System (AIS). The aim is to present a verified
process model for import containerised cargo, based on the ETA from the AIS, which could simplify
the pick-up process of containers at container terminals.
By utilizing a mixed methods approach, through a literature review, interviews and a questionnaire
survey, data, information, and opinions were collected from stakeholders within the supply chain.
The result showed that there was an overall interest for the subject, and that it was a highly relevant
research area due to the ongoing situation within the global supply chain. Three main interfaces were
recognized, with different stakeholders interfering with each other alongside the physical movement
of containers. By utilizing the AIS and retrieving a reliable ETA, through preferably machine
learning, a seamless information exchange regarding the predicted arrival time for container vessel
could be possible. If the ETA is reliable enough, it can provide valuable information through all three
interfaces, which could simplify different processes for the included stakeholders. It could also serve
as a solid foundation for a verified process model, which could simplify the pick-up process for
containerised cargo at port container terminals.
Beskrivning
Ämne/nyckelord
AIS, ETA Prediction, Maritime trade routes, Maritime logistics, ICT, Supply chain, Containerized transport, Intermodal transport, Machine learning