Matching of manual operation trajectories and warehouse operation information: A data chain Construction method based on indoor positioning technology

Yunhai Xiang, Kun Wang, Xinru Wu

Abstract: Accurate data collection in manual warehouses faces significant challenges due to the reliance on singular information collection method and the operators’ flexibility, which impedes data-driven, intelligent decision-making in warehouse operations. This paper addresses this problem to construct the data chain using indoor positioning technology (DCC-IPS). A unique feature of the proposed approach is the integration of the operators’ positioning data with the layout, operations, and tasks in the warehouse, facilitating a deep fusion of new external data and internal business data. Experiments conducted at Southwest Jiaotong University’s laboratory have demonstrated that the DCC-IPS achieves a matching accuracy exceeding 80%. Compared to traditional scanning with PDA, DCC-IPS reduces the delay in operation recognition by 20 s in the experimental scenario. Furthermore, by utilizing the data chain for evaluating operators’ capability and optimizing task assignments, our numerical experiments showed a 22.13% increase in efficiency over random assignments. These results highlight the accuracy and effectiveness of DCC-IPS in enhancing operational efficiency in warehouses.