We belong together - A system-level investigation regarding AGV-assisted order picking performance
研究了在仓储环境中，自动导引车（AGV）与人工拣货员共享工作空间时，AGV比例对订单拣选时间的U形影响，发现并非AGV越多越好，为混合自动化场景下的系统设计提供经济分析视角。
Automation technologies are currently being introduced in many warehouse intralogistics operations to support human workers in manual order picking. Robotic systems supporting manual order picking are therefore receiving increasing attention in the production economics literature. One related concept is human–robot collaboration, in which automated guided vehicles (AGV) and human pickers collaborate in the same work space. As these automation technologies still represent a minority in a larger manual order picking setting, we propose a role-model opportunity for analyzing the system level of joint operations from an economic perspective. We empirically investigate a pilot test of a new industrial truck deployed as an AGV that automatically follows order pickers in their travel direction within one specific warehouse of a brick-and-mortar grocery retailer. Our data set comprises 140,991 pick location visits performed in one dedicated warehouse aisle between 01 February 2023 and 30 June 2023, with an average of 31.89% of picks involving human–robot and 68.11% human–manual order pickers, with both groups sharing the identical aisle work space. We find that an increasing share of AGVs in the system has a U-shaped impact on order picking time. Therefore, the intuitive assumption of “the more, the better” for introducing AGVs and their impact on order picking performance is not confirmed for the context under investigation. Our findings can guide researchers and managers on how to analyze and economically design system-level order picking in scenarios in which the complete transition to automation remains a distant reality or requires long-term transition windows, a real-life operations management challenge for most order picking contexts.