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A simulation study on the robotic mobile fulfillment system in high-density storage warehouses
Simulation Modelling Practice and Theory ( IF 3.5 ) Pub Date : 2021-06-11 , DOI: 10.1016/j.simpat.2021.102366
Xiaowen Li , Xiuqing Yang , Canrong Zhang , Mingyao Qi

The robotic mobile fulfillment system (RMFS) is a parts-to-picker material handling system that has emerged in e-commerce warehouses and aims to save labor costs and achieve higher picking efficiency. This study investigates an RMFS in high-density storage warehouses with limited space or high rental costs. Supposing that the incoming orders have been preprocessed, we focus on how to carry specific storage pods to given workstations and then return to the storage area, which are called tasks. We elaborate on the task fulfillment process, which includes three modules: task assignment, path planning, and traffic control. We characterize the unique nature of high-density warehouse systems by introducing some definitions, rules, and propositions. To evaluate the system performance, a simulation platform is implemented to compare the traditional and high-density storage warehouse layouts with different robot numbers. The results show that the RMFS with a high-density storage layout can save approximately 10% storage space on average while maintaining the same level of robot deployment and energy consumption. The results also show that we can achieve a higher warehouse space utilization while maintaining comparable efficiency by adopting more robots. We also observe that a large lane depth, for example, with four unit spaces, is not appealing due to high throughput time and energy consumption.



中文翻译:

高密度仓储仓库机器人移动履约系统仿真研究

机器人移动履行系统(RMFS)是电子商务仓库中出现的一种从零件到拣货员的物料搬运系统,旨在节省人工成本并实现更高的拣货效率。本研究调查了空间有限或租赁成本高的高密度存储仓库中的 RMFS。假设传入的订单已经过预处理,我们重点讨论如何将特定的存储吊舱运载到给定的工作站,然后返回存储区域,这称为任务。我们详细阐述了任务执行过程,它包括三个模块:任务分配、路径规划和流量控制。我们通过引入一些定义、规则和命题来描述高密度仓库系统的独特性质。为了评估系统性能,实现了一个仿真平台,以比较具有不同机器人数量的传统和高密度存储仓库布局。结果表明,采用高密度存储布局的RMFS在保持相同水平的机器人部署和能源消耗的情况下,平均可以节省约10%的存储空间。结果还表明,通过采用更多机器人,我们可以实现更高的仓库空间利用率,同时保持可比的效率。我们还观察到,例如,具有四个单位空间的大车道深度由于高吞吐量时间和能源消耗而没有吸引力。结果表明,采用高密度存储布局的RMFS在保持相同水平的机器人部署和能源消耗的情况下,平均可以节省约10%的存储空间。结果还表明,通过采用更多机器人,我们可以在保持可比效率的同时实现更高的仓库空间利用率。我们还观察到,例如,具有四个单位空间的大车道深度由于高吞吐量时间和能源消耗而没有吸引力。结果表明,采用高密度存储布局的RMFS在保持相同水平的机器人部署和能源消耗的情况下,平均可以节省约10%的存储空间。结果还表明,通过采用更多机器人,我们可以实现更高的仓库空间利用率,同时保持可比的效率。我们还观察到,例如,具有四个单位空间的大车道深度由于高吞吐量时间和能源消耗而没有吸引力。

更新日期:2021-06-17
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