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首页> 外文期刊>International Journal of Production Research >Travel time models for deep-lane unit-load autonomous vehicle storage and retrieval system (AVS/RS)
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Travel time models for deep-lane unit-load autonomous vehicle storage and retrieval system (AVS/RS)

机译:深车道单载自动驾驶车辆存储和检索系统(AVS / RS)的旅行时间模型

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摘要

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.
机译:自主车辆存储和取回系统使用的车辆可在存储架内沿导轨水平移动,而垂直运动则由升降机提供。本文提出的解决方案针对一种特殊的系统配置,该配置可与在食品和饮料行业广泛使用的多个深层存储通道配合使用,其特点是大量产品种类有限。通用深层通道是单个项目,即一个库存单位,而单个批次,即一个生产批次,从而在存储容量利用率和吞吐量方面影响系统的性能。确定通道的数量和深度对于帮助设计和控制此类存储系统至关重要。本文的目的是通过一套原始的分析模型来支持AVS / RS的设计,这些模型可以确定给定替代布局配置的单指令和双指令周期的行进距离和时间。这些模型通过仿真进行了验证,并以实际仓储案例研究为例。本文为系统布局的配置提出了有用的指导,包括确定最佳形状比和车道长度。

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