电池充电条件下自动导引车(agv)最小数量的计算

H. R. Shaukat, Bruce Gunn, Michael Johnstone, Doug Creighton
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引用次数: 0

摘要

该研究有助于研究自动导引车(AGV)的利用率,特别是不同工业时间间隔所涉及的AGV数量。agv数量的计算取决于不同时间间隔分配的任务,如装卸行程时间、装卸次数、回程行程、完成周期等。已经努力管理现有研究中的当前研究差距,并帮助工业部门估计agv的最低数量。现代化也对该行业产生了影响;这项研究为制造业提供了额外的知识,特别是如何以最小的努力轻松部署自动引导车辆,因为它们很灵活,可以轻松地在各种路径上移动。本研究描述了一种基于运输时间因素的AGV配方算法,可以在任何行业中执行不同的任务。当前的COVID大流行也凸显了机器人和数字化在应对此类灾难方面的重要性,很少有人致力于使用基于代理的模拟计算,将结果与计算值进行比较。我们解决了困难,并展示了需要多少agv才能满足行业需求。
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Computation of Minimum Number of Automated Guided Vehicles (AGVs) with Battery Charging
The research contributes to the study of the automated guided vehicle (AGV) utilisation, specifically the number of AGVs involved with different industrial time intervals. Computation of the number of AGVs depends upon the assigned tasks of different time intervals such as loaded and unloaded travel times, loading, and unloading times, return travel, and the completion period. There has been an effort to manage the current research gap in existing studies and help the industry sector to estimate the minimum number of AGVs. Modernisation left an impact on the industry too; this research offers additional knowledge toward the manufacturing sector, particularly how automated guided vehicles can easily deploy with minimum effort, as they are flexible and easily can move on a variety on paths. This research study describes an algorithm for AGV formulation based on the transport time factors, to perform different jobs in any industry. The current COVID pandemic also highlights the importance of robots and digitalisation to compete with such disasters, little effort has been devoted to computing with agent-based simulation, to compare the finding with calculated values. We address the difficulties and demonstrate how many AGVs are required to meet the industry requirement.
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