Side by Side or “Get Out of My Way!”—Examining the Impact of Picker Blocking and AGV Assistance in Picker-to-Parts Order-Picking Systems
研究仓库中拣货员阻塞对任务时间的影响，发现自动导引车（AGV）能减轻阻塞带来的延迟，对优化仓库运营有参考价值。
Manual order picking remains a labor- and cost-intensive warehouse process. Automation technologies have gained traction, with automated guided vehicles (AGVs) assisting human pickers by handling transport tasks and optimising workflows. However, due to high cost levels and infrastructural constraints, AGVs are often introduced incrementally, resulting in mixed-technology scenarios in which workers with a prior-generation technology and workers with the new (AGV) generation technology operate side by side, for example, in the same warehouse aisle. One challenge in such settings is picker blocking, which occurs when the actions of one picker impede or delay the movements of another. This study empirically examines pick-column blocking and within-aisle blocking with respect to their impact on task performance time. Using a mixed-effects regression model, we analyse 490,398 pick events from a German retailer during 2023. This approach accounts for repeated observations and individual heterogeneity in picker performance over time. Our results show that both types of blocking significantly increase task performance time. AGV assistance mitigates these negative effects, reducing the additional delay by 3.4% for pick-column blocking and 2.1% for within-aisle blocking. Our results demonstrate that AGVs do more than provide transport assistance, reducing congestion and ensuring smoother, more efficient movement. The study provides valuable theoretical and management insights to optimise warehouse operations and contributes to the growing literature on human–AGV collaboration in logistics.