Yokogawa Electric Corporation has announced that its subsidiary, Yokogawa Digital Corporation, has successfully completed a proof-of-concept (PoC) test of a proprietary AI solution designed to automate outbound shipment loading planning for Hokuetsu Logistics Corporation, a subsidiary of Hokuetsu Corporation.
By replicating expert-level decision-making, this AI-powered system drastically reduces planning time while optimizing load efficiency based on product shape and destination region. Following the PoC’s success, Hokuetsu Corporation and Hokuetsu Logistics Corporation will officially adopt and begin using the solution in July 2025.
Hokuetsu Corporation’s main business is the manufacturing and sales of paper and pulp products. The outbound shipment of paper and pulp products is subject to various constraints, such as the shape of the products, the vehicles in which they are to be transported, and specific requirements at the shipment destination. It is also important to reduce the burden on truck drivers by limiting shipments whenever possible to single destinations and, when there must be multiple destinations, arranging for them to be as close together as possible.
With conventional combinatorial optimization techniques, increased complexity in objectives and constraints makes it more difficult to devize loading plans, and the necessary calculations take longer to complete. Efforts to automate the loading planning process have proven difficult, and the training of loading planning specialists has also been a challenge.
Development of AI Solution and Implementation of PoC Test
With the aim of developing an AI solution that could automate this loading planning process, Yokogawa’s AI consultants interviewed Hokuetsu Corporation’s highly skilled planning specialists to understand their thinking processes and gain a clear understanding of site operations. Based on these insights, Yokogawa developed a proprietary AI-driven loading planning solution that replicated the decision-making expertise of specialists. A PoC test was then implemented that confirmed the following outcomes.
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- Quick completion of loading planning
It was confirmed that the AI loading planning tool is capable of generating accurate loading plans, in a significantly reduced timeframe of less than 10 seconds for individual planning, even while taking into account complex conditions such as shipped items, vehicles, and specific requirements at delivery destinations.
- Quick completion of loading planning
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- Successful incorporation of expert-level capability to reduce burden on delivery personnel
It was also confirmed that the planning tool mimics the capabilities of specialists to decrease the burden on personnel by consolidating the number of delivery destinations to one or two. When multiple arrival points are required, the system prioritizes the nearest destinations and generates plans that also take load capacity into account.
- Successful incorporation of expert-level capability to reduce burden on delivery personnel
Future Plans
Yokogawa will contribute to the improvement of operational efficiency and the construction of a sustainable operation system at the Group’s logistics sites by providing an AI loading planning solution that factors in individual circumstances at each company and mimics the reasoning of expert personnel.
