Performance evaluation of two-depth deep lane automatic storage and retrieval system

Abstract

This thesis deals with a two-depth deep lane system which is a variation of unitload automatic storage and retrieval system (AS/RS). Compared with typical one lane AS/RS, the deep lane system has several advantages such as savings of the storage and retrieval machine and aisle space. Utilizing Markov properties, we propose methods to evaluate the system throughput under two kinds of system operation rule; random order sequencing rule and the nearest neighbor heuristic rule. It is observed that the throughput under the nearest neighbor rule is more efficient than the other. Also, the system is compared with equivalent one lane AS/RS.