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首页> 外文期刊>International Journal of Production Research >Travel-time models and fill-grade factor analysis for double-deep multi-aisle AS/RSs
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Travel-time models and fill-grade factor analysis for double-deep multi-aisle AS/RSs

机译：双深多通道AS / RS的行程时间模型和填充等级因子分析

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Double-deep multi-aisle automated storage/retrieval systems are increasingly applied for storing and retrieving unit loads, with advantages of increased space utilisation, reduced number of aisles and improved efficiency of storage rack (S/R) machines. In such systems, the retrieval process may consist of the rearrangement of blocking loads, based on the assumptions of uniformly distributed storage locations and random storage policy. We formulate analytical travel-time models of both single-and dual-command cycles under three rearrangement rules. We validate the analytical travel-time models by simulation and conduct numerical experiments to analyse the effect of the number of aisles an S/R machine serves, the fill-grade factor and the command cycles on the expected travel time of the S/R machine. The results show that the expected travel time of the S/R machine is increasing with the increase in the number of aisles an S/R machine serves and the increase in the fill-grade factor, and dual command cycle outperforms single-command cycle in terms of cycle time. To deal with the trade-off between the storage space cost and the operational cost of the S/R machine, we develop a decision model for finding an optimal fill-grade factor to minimise the total cost. We find the condition when an optimal fill-grade factor exists and show how to calculate it. Based on the decision model, we compare the performance of double-deep multi-aisle automated storage/retrieval system (AS/RSs) and single-deep single-aisleAS/RSs. The results show that double-deep multi-aisleAS/RSs outperform single-deep single-aisle AS/RSs in terms of total cost, although double-deep multi-aisle AS/RSs need more storage locations.
机译：双深多通道自动存储/检索系统越来越多地用于存储和检索单元负载，具有增加空间利用率，减少过道数量和提高存储机架（S / R）机器效率的优势。在这样的系统中，基于均匀分布的存储位置和随机存储策略的假设，检索过程可能包括阻塞负载的重新排列。我们在三个重排规则下制定了单命令周期和双命令周期的分析行程时间模型。我们通过仿真验证了分析行程时间模型，并进行了数值实验，以分析S / R机服务的过道数量，填充等级因子和指令周期对S / R机预期行程时间的影响。结果表明，S / R机器的预期行进时间随着S / R机器服务的过道数量的增加和填充等级因子的增加而增加，并且双指令周期优于单指令周期。周期时间。为了解决S / R机器的存储空间成本和运营成本之间的折衷，我们开发了一个决策模型，用于寻找最佳的填充等级因子以最小化总成本。我们找到存在最佳填充等级因子时的条件，并说明如何计算。基于决策模型，我们比较了双深度多通道自动存储/检索系统（AS / RS）和单深度单通道单通道AS / RS的性能。结果表明，尽管双深度多通道AS / RS需要更多的存储位置，但在总成本方面，双深度多通道AS / RS优于单深度单通道AS / RS。

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