An article about the LOGISTAR project was recently published on the Community Research and Development Information Service (CORDIS) website. In the article, you can read how automation, artificial intelligence, and data could be the key to optimizing logistics operations within the global supply chain. Find the part of the article below.
The main outcome of the LOGISTAR project is an end-to-end architecture that can automatically capture and harmonize data, send the corresponding messages to the modules in charge of executing different algorithms, and gather results to be displayed to stakeholders.
“This solution takes real-time available data and feeds it to AI-based algorithms,” explains Enrique Onieva who serves as the project coordinator. “These algorithms are then used to run a number of services, each of which is geared towards optimising supply chain operations.”
For example, one service uses the precise estimated time of arrival prediction and incident detection to optimise warehouse operations. “By helping warehouses use their available resources more efficiently, this service reduces wait times and the supply chain bottlenecks such delays cause,” adds Onieva.
Another service improves how freight is routed and load capacity optimised. “By taking advantage of different modes of transportation, such as trucks, trains, and ships, we’re able to both optimise the use of all available infrastructure while also reducing the overall costs of logistics transport,” he notes.
On this note, the project also developed a tool for horizontal collaborative planning. “By helping different supply chain stakeholders share available resources, we can reduce the number of kilometers traveled by empty trucks, which in turn reduces greenhouse gas emissions,” says Onieva.
Read the full article “AI to future-proof the global supply chain” on the CORDIS website.
