Analytical models for the evaluation of deep-lane autonomous vehicle storage and retrieval system performance

• Published in: International journal of advanced manufacturing technology Vol. 94; no. 5-8; pp. 1811 - 1824
• Main Authors: D’Antonio, Gianluca, Maddis, Manuela De, Bedolla, Joel Sauza, Chiabert, Paolo, Lombardi, Franco
• Format: Journal Article
• Language: English
• Published: London Springer London 01-02-2018; Springer Nature B.V
• Subjects: Automated storage retrieval systems; Autonomous vehicles; CAE) and Design; Computer simulation; Computer-Aided Engineering (CAD; Criteria; Cycle time; Engineering; Industrial and Production Engineering; Light duty vehicles; Logistics; Mathematical models; Mechanical Engineering; Media Management; Original Article; Performance evaluation; Racks; Retrieval; Warehouses; Autonomous vehicle storage and retrieval system (AVS/RS); Performance analysis; Automated storage; Warehousing systems; Logistics
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-017-0313-2

In the last decades, huge efforts have been made to develop innovative solutions supporting the automation of logistics activities. Among the available technologies, autonomous vehicle storage and retrieval systems (AVS/RS) are very promising: they use light vehicles able to independently travel on different axes, and thus perform different tasks at the same time. Despite the increasing diffusion of such systems, there is still a lack of performance evaluation techniques. Furthermore, there are no standards available to provide performance evaluation criteria. In this paper, novel analytical models to assess the performance of AVS/RS pertaining to deep-lane racks. These models extend the state of the art by (i) taking into account the real criteria related to the storage and retrieval of items, (ii) considering the capability of the shuttle and the satellite to simultaneously perform different tasks, and (iii) evaluating the standard deviation of the cycle time, beside its average value. The presented models are validated through simulations performed on different warehouse layouts, in different deployment scenarios. The ultimate aim of such models is to support warehouse equipment designers in evaluating the performance of their systems, considering a multiplicity of realistic scenarios.