Simulation based experimental design to identify factors affecting performance of AVS/RS

Abstract

We perform a simulation based experimental design for automated unit-load (UL) storage and retrieval systems based on autonomous vehicle technology to identify factors affecting their performance. First, we select the best combination of numbers of lifts and vehicles from pre-defined scenarios that are the key components of the system. Then, we apply design of experiment (DOE) for a system with this combination of lifts and vehicles and for various arrival rates. The factors considered in the DOE include: dwell point policy, scheduling rule, input/output (I/O) locations and interleaving rule. Three different responses, the average cycle time for storage and retrieval transactions, average vehicle utilization, and average lift utilization, are considered. However, because the ANOVA assumptions are not met for the average cycle time response, an inverse transformation method is applied on this response. The results show that there is three-way interaction effect on each response at a 95% confidence level. After determining the main and the interaction effects, a Tukey’s test analysis is completed on the responses. We utilize data from a warehouse in France that utilizes the autonomous vehicle storage and retrieval system.

Introduction

Autonomous vehicle storage and retrieval system (AVS/RS) is a relatively new technology for automated unit-load, storage and retrieval (S/R) systems. Autonomous vehicles function as S/R devices. Within the storage aisle, the key distinction of an AVS/RS relative to a traditional, crane-based, automated S/R system (AS/RS) pertains to the movement patterns of the S/R device. In an AS/RS, aisle-captive storage cranes capable of simultaneous movement in the horizontal and vertical dimensions store or retrieve unit-loads. In an AVS/RS, vehicles share a fixed number of lifts for vertical movement and follow rectilinear flow patterns for horizontal travel. While the travel patterns in an AS/RS is generally more efficient within the storage aisles, an AVS/RS has a significant potential advantage in the adaptability of system throughput capacity to transactions demand. This can be accomplished by simply changing the number of vehicles operating in a fixed storage configuration. For example, increasing the number of vehicles decreases, to a certain extent, the transaction cycle times and therefore the warehouse throughput capacity.

It is important to design an AVS/RS in such a way that it can efficiently handle the current and future demand requirements while avoiding bottlenecks and overcapacity. Due to the relative inflexibility of the physical layout and the equipment, it is important to design it right the first time. The purpose of this study is to first determine a near-optimal, AVS/RS-based, warehouse design configuration and then to evaluate the effects of various pre-defined design parameters on the key performance measures of this configuration via simulation-based DOE.