Configuration of an AVS/RS Using a Data-Driven Queueing Network Model

Ensuring a short response time is pivotal in automated warehousing systems, such as the autonomous vehicle storage and retrieval system (AVS/RS). AVS/RSs are blooming in modern companies as much as research interest in warehousing system performance estimation (e.g., cycle time and throughput). This study aims to introduce a novel data-driven approach based on an open queueing network model. The purpose is to estimate the waiting and response times of the storage and retrieval transactions in a deep-lane tier-captive AVS/RS. The arrival and service times of storage and retrieval transactions depend on real system dynamics (e.g., seasonal trends of material flows), overcoming unrealistic assumptions such as Exponential or Poisson distributions. The adopted Java Modelling Tool supports the estimation of the system performance throughout the modelling lifts, shuttles, satellites, and conveyors in the JSIM web-based simulation environment. This application-oriented environment is an open-source Java suite where users can easily modify or add new modules to design different AVS/RSs. The proposed approach is applied to a real case study of a deep-lane AVS/RS in the food and beverage industry, highlighting the relevance of the waiting times on the total handling time and the effectiveness of the proposed data-driven assessment.