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

Abstract

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.

KEYWORDS:

• Order picking methods
• automated guided vehicle
• facility design
• warehouse design
• robotic mobile fulfilment systems
• expected travel distance

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Francisco J. Aldarondo

Francisco J. Aldarondo Valle is an analyst in the National Security Analysis Department at JHU/APL. Prior to joining JHU/APL, he worked at General Electric as a Supply Chain Data Analyst and as an independent contractor for manufacturing and logistics industries. He holds a B.S. in Industrial Engineering from the University of Puerto Rico and a Ph.D. in Industrial and Operations Engineering from the University of Michigan.

Yavuz A. Bozer

Bozer’s work focuses on developing quantitative models and Operations Research (OR) tools to design and analyze the logistics operations of production and service organisations, including manufacturing, warehousing, distribution, and e-commerce. He is also a leading researcher in facility logistics and design, including manufacturing plants, fulfilment centres, and supply chain facilities such as cross-docks. He has also studied the application of Lean techniques and value stream analysis in the above fields. Professor Bozer's professional experience includes his employment as a consultant with the SysteCon Division of Pricewaterhouse-Coopers, and his work as a Research Engineer at the Material Handling Research Center at Georgia Tech. He received the 1987 IISE Outstanding Dissertation Award, and in 1988 was named a Presidential Young Investigator by the National Science Foundation. He was inducted into the Council of Outstanding Young Engineering Alumni at Georgia Tech in 1995, and he received the Technical Innovation Award in Industrial Engineering from IISE in 1999. He is the cofounder of the Lean Manufacturing Certificate Program offered through Nexus at the U-M College of Egineering where he trained or consulted with a long list of well-known companies in various sectors spanning manufacturing, defense, and healthcare.