UnityStep AI and Rengo have launched a field trial to optimise product storage locations using shipment performance data. They aim to establish data-based decision-making criteria, shorten waiting and cargo-handling times, and reduce the burden on drivers.
UnityStep AI, a startup originating from the Matsuo Lab at the University of Tokyo, and Rengo announced on 23 October that they had launched a field trial to optimise product storage locations, with the aim of shortening loading times when shipping containerboard. The trial will begin by analysing and forecasting shipment trends for each product using shipment performance data.
The trial will combine UnityStep AI’s demand forecasting and mathematical optimisation technology with Rengo’s operational expertise to develop storage allocation proposals based on information obtained from shipment performance data. The proposals will be implemented at Rengo sites, where their actual effectiveness will be assessed.
Against the backdrop of the 2024 logistics issue, Rengo is promoting White Logistics, which enables drivers to work more easily while improving productivity. This initiative is positioned as part of those efforts. Depending on the trial results, the companies will consider expanding the range of products covered, reviewing product storage locations, and eventually linking the system with production planning and vehicle dispatching, as well as rolling it out horizontally to other sites.
The company plans to continue working to optimise the entire supply chain using AI and data. Attention will focus on how the results of the field trial are reflected in operations going forward.