Storage Space Efficiency in Deep-Lane Autonomous Vehicle Storage and Retrieval System

Autonomous vehicle storage and retrieval systems (AVS/RSs) ensure high productivity and storage density in production and distribution networks. The focus of this study is a tier-captive deep-lane AVS/RS equipped with multiple lifts, shuttles, and satellites. The system has n independent tiers connected by one or more lifts, with bays and conveyors in each tier. A generic lane contains unit loads of the same stock-keeping unit (SKU) and production batches. Space efficiency (SE), which is defined as the ability to exploit the storage capacity, is a major concern for AVS/RSs. Existing literature has focused on controlling the system productivity (e.g., throughput) without considering the impact on storage efficiency. Because an AVS/RS is an expensive storage solution, the strategies and rules to manage the storage capacity are critical along with ensuring high productivity rates. This study proposes a data-driven space efficiency control system (SECS) that measures and controls the storage capacity of an AVS/RS through a set of SE indicators. The SECS can also monitor the impact of alternative storage/retrieval dispatching strategies and lane-depth configurations on the system performance. A comparative and competitive multiscenario analysis is conducted in a case study of a deep-lane AVS/RS operating in the food and beverage industry.