Digitization and Analysis Framework for Warehouse Truck Berth

In distribution warehouses, various forms of data transformation are underway, such as the conversion of data related to receiving and inventory management. Distribution warehouses have designated areas known as truck berths, where trucks are parked for loading/unloading. While data collection is expected to enhance work efficiency at these truck berths, there is no data regarding the status of work in progress in the unloading space, and no system is in place to analyze the work. Consequently, it is unclear which tasks are problematic and how to enhance efficiency. To address this issue, this paper proposes a framework for analyzing the loading/unloading situation at truck berths with the objective of enhancing berth utilization efficiency and work efficiency. Specifically, we employed a fixed camera for object detection through instance segmentation. This approach enables us to understand the situation of trucks, unloading spaces, and workers. The training data were annotated using a large amount of real-world data, allowing for the measurement and analysis of the efficiency of loading/unloading operations. By calculating the amount of cargo based on the floor space, we assessed the efficiency of unloading operations per truck. Through the analysis of both efficient and inefficient operations, insights for enhancing work efficiency were provided.