Improving Throughput Capacity in Multi-tier Warehouse Systems using Autonomous Vehicles


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Abstract

To improve flexibility and responsiveness in order fulfillment operations, several distribution centers are implementing autonomous vehicle-based storage and retrieval (AVS/R) system in their high-density storage areas. Systems based on autonomous vehicle technologies present significant potential to improve throughput and efficiency of unit load operations in a warehouse. In such systems, vehicles are self-powered to travel in horizontal directions (x- and y- axes), but typically use lifts for vertical motion (z-axis). Since all transactions use lifts for vertical transfer, a lift-based system may limit the overall throughput capacity. In this research, we analyze alternate conveyor-based system for vertical transfer using stylized queuing network models. By using a combination of parametric decomposition and embedded Markov chain analysis, the queuing network is solved, and the effect of conveyors on system throughput capacity and transaction cycle times is determined. Insights from such studies can be useful during the conceptualization stage of warehouses with autonomous vehicles.
 
Contact information:
Prof.dr.ir. René de Koster
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