An open queuing network-based tool for performance estimations in a shuttle-based storage and retrieval system

Recently, growth in e-commerce has resulted in substantially increased investment in robotic technologies in warehouses, especially for storage and retrieval devices. A shuttle-based storage and retrieval system (SBS/RS) is one of the robotic automated storage and retrieval technologies mostly used for a miniload material handling system in e-commerce warehouses. This new technology has been developed as an alternative to the traditional miniload crane-based automated storage and retrieval system. Because it has an autonomous order picker robot in each tier of the racking system, the process rate for this new technology is very high. To evaluate several design options for an SBS/RS warehouse quickly, we have developed analytical models for estimating important performance outputs of these systems. Specifically, this study presents an open queuing network-based software tool that can quickly estimate some important performance metrics for a predefined SBS/RS warehouse design. Once the user enters the required input data values in the tool (e.g., the arrival rate of transactions in the system, warehouse metrics, number of tiers, aisles, and bays, and velocity profiles of devices), the performance metric estimates can be obtained in terms of the mean cycle time of a transaction, the mean energy consumption and energy regeneration per transaction, the mean waiting time of a transaction, the mean number of transactions waiting in a server (lift/shuttle) queue, and the mean utilization of servers. (C) 2020 Elsevier Inc. All rights reserved.