Expected distances and alternative design configurations for automated guided vehicle-based order picking systems

Automated Guided Vehicle (AGV)-based order picking (OP) systems, also known as Robotic Mobile Fulfilment Systems, continues to receive attention in industry and academia since their introduction as Kiva systems. A key component of AGV-based OP systems is the 'robots' (or AGVs) that pick up...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of production research Vol. 60; no. 4; pp. 1298 - 1315
Main Authors Aldarondo, Francisco J., Bozer, Yavuz A.
Format Journal Article
LanguageEnglish
Published London Taylor & Francis 16.02.2022
Taylor & Francis LLC
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Automated Guided Vehicle (AGV)-based order picking (OP) systems, also known as Robotic Mobile Fulfilment Systems, continues to receive attention in industry and academia since their introduction as Kiva systems. A key component of AGV-based OP systems is the 'robots' (or AGVs) that pick up the 'pods' and transport them to the appropriate pick station (PS), where a picker picks the items ordered by customers. The performance of such systems depends on the shape of the forward area (FA) and the number of AGVs, which in turn depends on the time it takes an AGV to retrieve a pod. To aid system designers, we explore alternative shapes for the FA and we derive closed-form expressions for the expected AGV travel distances under two possible order assignment rules. Under the random assignment rule, an order is assigned to any PS with equal probability. Under the closest assignment rule, the order is assigned to the closest PS. We also examine the impact of alternative PS configurations for different shapes of the FA. The results offer valuable insights concerning expected travel distances under alternative design configurations. The results would also be useful when building design and performance evaluation models for AGV-based OP systems.
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2020.1856438