Dual cycle time modelling and design optimisation for the bidirectional flow-rack AS/RS

Abstract

This article discusses the problem of evaluating performance and optimising the design of Automated Storage/Retrieval Systems (AS/RS) in a steady state, with a focus on the dual cycle in the bidirectional flow-rack (BFR) AS/RS. To accomplish this, two well-known approaches (discrete and continuous) are utilised to model the dual cycle time. The developed models reveal that the system is near optimal when designed to be square in time. Furthermore, the continuous models are shown to be relatively accurate compared to the discrete counterparts, with discrepancies under 6%. Subsequently, the optimal dimensions of the system are identified through design optimisation aimed at minimising the cycle time. The findings indicate the optimal depth decreases as load rate increases, while optimal height and length follow a cubic root function of system volume. Approximate formulas are derived, allowing for direct calculation of optimal dimensions based on the system size and its load rate. Finally, the article evaluates the system's overall performance by calculating its throughput, providing a tool to estimate capacity. These findings provide an essential tool for optimising the system's performance in a steady state during the upstream design and installation phase, prior to making significant investments.

KEYWORDS:

• Automated storage/retrieval systems
• bi-directional flow-rack AS/RS
• material handling
• warehousing
• mathematical models
• design optimization

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data available on request from the authors.

Additional information

Notes on contributors

Hamzaoui Mohammed Adel

Mohammed Adel Hamzaoui presently holds a position as a teacher-researcher at the Lab-STICC laboratory, affiliated with the Southern Brittany University in France. In 2020, he was conferred with a Ph.D. in Industrial and Production Engineering, a programme jointly supervised by the University of Tlemcen in Algeria and the University of Technology of Troyes in France. His scholarly pursuits are primarily concentrated in the domain of automated storage/retrieval systems and material handling. Moreover, he is actively involved in emerging research avenues related to Industry 4.0 technologies, with a particular emphasis on cyber-physical systems and digital twins.

Sari Zaki

Zaki Sari is currently a freelance senior consultant and expert for industry and services. Before, he was a Manufacturing Engineering Professor at Aboubekr Belkaid University of Tlemcen (UABT), Algeria; the founder and past Director of the Manufacturing Engineering Laboratory of Tlemcen (MELT), and the founder and past head of the National Curriculum of Manufacturing Engineering. He obtained his Engineer degree in electrical engineering from the National Institute of Electrical Engineering, Boumerdes, Algeria in 1987; his Magister degree in power engineering from the National Polytechnic School of Algiers, Algeria in 1990; and his Doctorate degree in manufacturing engineering from Tlemcen University in 2003. He obtained also a certificate in system engineering management from University of Missouri Rolla, USA, in 2003. His main domain of interest concerns the Design, Modelling, Optimisation, Simulation and Control of Automated Storage and Retrieval System, he made several investigations on non-conventional AS/RS systems like flow rack systems but employed for different uses than the ones designed for. Other domains that he is interested in include Flexible Manufacturing Systems, Scheduling, Supply Chain Management … 

Belghoul Leila

Leila Belghoul is an Industrial Engineer specialising in supply chains. She completed her Master's degree in 2022, following her Bachelor of Science in Industrial Engineering with a focus on automation at Aboubekr Belkaid University of Tlemcen (UABT), Algeria. Leila has worked on supply chain optimisation, bioenergy, genetic algorithms, and production planning, with a strong interest in improving efficiency and sustainability within supply chains.