Performance Analysis of a Robotized H-AMR Warehousing System by Considering Different Product Turnover

This paper investigates the performance of a warehouse system based on heterogeneous autonomous mobile robots, where two types of robots collaborate in storage and retrieval operations. The first type, called bin pickers, operates exclusively within aisles, retrieving and storing bins, while the second type, called bin movers, transports bins between storage locations and picking stations. Product turnover is considered by dividing bins into high-turnover and low-turnover classes: high-turnover bins are stored at the first level of the racks and handled only by bin movers, whereas low-turnover bins are stored at higher levels and require the combined action of both robot types. The proposed configuration partially allocates the first level to high-turnover products, reducing lead times as these are managed exclusively by bin movers. A simulation study was conducted by varying aisle length, fleet size, and the share of high-turnover products. Results show that throughput increases significantly with higher proportions of high-turnover products, reaching values above 450 bins per hour in favorable scenarios. The findings highlight how bin allocation and warehouse design choices strongly influence efficiency, supporting more effective industrial applications.