Travel time models for deep-lane unit-load autonomous vehicle storage and retrieval system (AVS/RS)

Riccardo Manzini, Riccardo Accorsi, Giulia Baruffaldi, Teresa Cennerazzo and Mauro Gamberi

International Journal of Production Research, 2016, vol. 54, issue 14, 4286-4304

Abstract: Autonomous vehicle storage and retrieval systems use vehicles that move horizontally along rails within the storage racks, while vertical movements are provided by lifts. The solution proposed in this paper addresses a particular system configuration that works with multiple deep storage lanes that are widely used in the food and beverage industry, characterised by large volumes of products of limited variety. The generic deep lane is single item, i.e. one stock keeping unit, and single batch, i.e. one production lot, thereby affecting the performance of the system in terms of storage capacity utilisation and throughput. Determining the number and depth of the lanes is crucial to aid the design and control of such a storage system. The aim of this paper was to support the design of AVS/RSs though a set of original analytic models for the determination of the travelled distance and time for single-command and dual-command cycles given alternative layout configurations. The models are validated by simulation and exemplified with a real-warehousing case study. The paper presents useful guidelines for the configuration of the system layout including the determination of the optimal shape ratio and the length of the lanes.

Date: 2016
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DOI: 10.1080/00207543.2016.1144241

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