Collaborative platforms, algorithms, smart sensors and machine learning in the world of maritime transport.
Free trade agreements, reducing customs tariffs, relocating production sites and container transportation costs falling have led to a huge increase in logistics flows and opened up to globalization.
However, these technological advances have not been enough to address the challenges and complexity of shipping which requires more coordination and collaboration than other modes of transportation.
The complexity of maritime transport is due to the large number of players: carriers, freight forwarders, brokers, bankers, ports and customs. It is also explained by the considerable quantity of documents, such as the bill of lading, which are exchanged and often crucial for goods to be delivered. Finally, there are also the flows of economic transactions which are never far behind when goods are moved from point A to point B.
Wherever they are based, shipping companies are known for their lack of reactivity when communicating the position and status of containers in real time. Real-time communication and coordination are strategically important because of the impact they have on supply chain costs and the quality of customer service.
Shippers could take advantage of many technologies to gain more visibility, but logistics managers are afraid to buy into technological changes because they are uncertain about the potential gains while being asked to guarantee a reliable supply chain. On the other hand, they do not know which solution to choose. What is certain is that the decision not to make a choice and the existing issues on their supply chain lead to a negative competitiveness gap compared to front runners who decide to equip their supply chain with the latest technologies.
Incurring fees for demurrage and detention perfectly illustrate how improper coordination and visibility can be in logistics. Containers often remain at the dock beyond the deadline set by the carrier. These delays are due to poor coordination and could be avoided if consignees were informed about when containers arrive to prevent them from getting blocked at the dock.
These problems could easily be solved through increased collaboration, i.e. by transmitting real-time information about logistics flows between the parties involved: shippers, freight forwarders, carriers and consignees. Then, the IoT (internet of things) can provide more accurate real-time monitoring of containers via smart sensors connected to the cloud which collects real time data about logistics.
“Logistics managers are keen on supply chain data and want to know why containers spend a lot of time at the dock. Our goal is to move them on”, says Tim Baker, Traxens Marketing Manager. We also want our containers to move at a consistent pace, reduce their time of arrival and check how effective the measures put in place to achieve these objectives are. This is why we have sensors and collect all this DATA.”
Benoit Fichefeux, Co-founder of BuyCo, has just come back from Berlin where he attended the AI Talk forum on artificial intelligence in the supply chain industry.
Regarding the relationship between professionals and machines, he says “Machine learning and automation will enable logistics professionals to free supply chain operators from lower value-added tasks. Nonetheless, humans will remain essential in managing exceptions or for activities which require creativity, strategic thinking and leadership, qualities that technology will not be replacing. We are still a long way from autonomous transport management. ”
Regarding the evolution of BuyCo, “At the moment, artificial intelligence provides us with some basics functionalities and will undoubtedly give us the opportunity to optimize slot booking on vessels. Machines would replace human beings to choose vessels better by taking constraints, previous patterns and users’ booking history into account. An AI application could pre-fill booking parameters based on all this information”, Benoît Fichefeux adds.
Port terminals are already making use of the benefits of artificial intelligence and machine learning. The latest edition of the Assise on Port of the Future has rewarded the start-up Blue Cargo for its innovative solution on container storage management at terminals.
Blue Cargo is proof that data and machine learning can optimize a cargo terminal and benefit the entire supply chain.
Blue cargo uses DATA and machine learning to provide terminal managers with plans for storing containers at terminal docks by taking their destination, category (refrigerated, dry storage, etc.) as well as other DATA into account. This solution reduces unnecessary movements, especially when moving one container means having to move every other container stacked on top of it.
The Blue Cargo solution offers productivity gains to all players in the supply chain while strengthening the competitiveness of a port infrastructure and all its stakeholders.
The port of Rotterdam is already using these new technologies. It is equipped with plenty of sensors and the IoT (Internet of Things) that enable logistics and port operators to acquire accurate and granular information about all performance issues.
BuyCo uses the latest technologies to simplify, secure and optimize container shipping management. BuyCo’s solution is cloud-based and simplifies container shipping by increasing the visibility of transportation records and fostering collaboration.
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