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.