Analytical models for cycle time and throughput evaluation of multi-shuttle deep-lane AVS/RS

The increased need for just-in-time delivery of finite goods has pulled the development of novel automation solutions to manage warehouse activities. Among the available technologies, autonomous vehicle storage and retrieval systems (AVS/RS) rely on light vehicles able to travel independently and to perform different tasks at the same time, thus exhibiting enhanced flexibility and increased throughput level. Nonetheless, techniques to evaluate the performance of such systems still exhibit some gaps and are mainly focused on simple configurations. This paper aims to extend the state of the art by introducing novel analytical models capable to assess the performance of a tier-to-tier, multi-shuttle AVS/RS feeding a deep-lane rack. The proposed approach enables to evaluate the expected cycle time and throughput by (i) enabling the possibility to consider the real criteria adopted to store and retrieve items, and (ii) taking into account the ability of the vehicles to simultaneously perform different tasks. The model is validated against simulations performed on different rack layouts, on AVS/RS with different fleet compositions, for different types of cycle. The developed model aims to support both the design and the deployment phases of AVS/RS by enabling quick and accurate performance estimation in a wide variety of scenarios.