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

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.