Europe’s leading logistics software supplier is researching into the benefits of AI and machine learning for Slotting, Picking & Putaway.
Consafe Logistics is now investing in several areas to help its customers be at the forefront of machine learning to increase efficiencies while reducing costs.
“We expect that in the near future, artificial intelligence will be used both to optimize certain processes in warehouse logistics, and improve general warehouse performance,” says Sofie Travessét, Group Marketing and Communication Manager at Consafe Logistics.
Consafe Logistics is running proof of concepts on AI/Machine learning to optimize pick efficiency based on analyzing pick patterns and goods placement in the Warehouse. The basis for machine learning is the collection of sufficient data that can be analysed to capture learnings and take actions based on that to improve efficiency.
These initiatives include:
Slotting: Examining ways to look at more than just frequency when placing goods in the warehouse. Areas Consafe Logistics is working on include slotting for A, B, and C goods, and even predicting what goods are ordered together and how often they are sold.
Picking and Putaway: Positioning data is already available from Consafe Logistics’ flagship product Astro WMS®. Using algorithms to plan which routes to choose will streamline picking and putaway even further.
“By using algorithms to proactively predict which products that will be bought together, we can plan placements of products in the warehouse not only by frequency of purchase but also how products correlate to one another. Companies can then better prepare what will be delivered, making forecasting smarter and customer deliveries faster – even predicting what customers will order in the future based on past purchases,” says Patrik Olsson, CPO, Consafe Logistics.
For more information about how AI and machine learning can bring positive results to your logistics processes, contact: email@example.com