Human-centric investigation of a robotic forward–reserve warehouse

Abstract

Order picking has long been identified as a time- and cost-intensive task in almost every supply chain. One interesting approach to accelerate the picking process is to separate the warehouse into forward and reserve areas, where the forward area holds a limited amount of inventory for fast picking that is replenished by the stock in the reserve area. To date, the replenishment operation is often conducted manually or using goods-to-person technologies such as automated storage/retrieval systems. Recently, a newly developed market-ready technology called picking robots, which are a kind of autonomous mobile robots, was implemented in e-commerce warehouses. They can be integrated into existing manual order picking systems without modifying the warehouse layout. In this study, we simulate a case wherein picking robots are applied for replenishment tasks to avoid stock shortages in fast-picking areas, thereby supporting the picking activities of humans. The aim is to reduce the human workload during the order picking process. We investigate various scenarios with different human–robot team configurations and demand patterns. The results indicate that such a setting can improve working conditions by simultaneously reducing human energy expenditure and costs per pick. The contribution of this study is to introduce these robots to forward–reserve warehouses, obtain preliminary results regarding system performance, and discuss related opportunities for future work.