基于光通讯的军工车间物流调度技术研究与应用
Research and Application of Logistics Scheduling Technology in Ordnance Workshop Based on Optical Communication
尹健 1邱枫 1柏志彬 1梁海洋 1孙科星1
作者信息
- 1. 中国兵器装备集团自动化研究所有限公司,四川绵阳 621000
- 折叠
摘要
为解决军工车间物AGV和立体库之间物流流转率低,数据交互困难等问题,采用红外光超短距离无线通讯的光通讯方式进行车间物流数据交互和安全传输.阐述了典型军工车间物流流传方式和主要物流约束,构建了基于光通讯的数据传输网络,基于改进Dijkstra算法进行AGV线路寻优和多车共线调度,进行了软件开发与实现,并在某装配车间进行了部署应用,应用结果表面,该技术采用的光通讯方式传输安全、可靠,采用的多车共线优化调度机制可靠,实现了装配车间传统被动式物流配送模式提升为基于状态触发的主动式物流配送模式,有效降低了装配车间物料不及时送达造成的时间浪费,提升了车间物流流转效率,提升了装配车间数字化水平,有效助推企业数字化转型.
Abstract
In order to solve the problems of low logistics flow rate and difficult data interaction between the AGV and the three-dimen-sional warehouse in the military workshop,the optical communication method of infrared ultra-short-distance wireless communication is used for the exchange and safe transmission of workshop logistics data.The logistics flow mode and main logistics constraints in typical mili-tary workshops are expounded,a data transmission network based on optical communication is constructed,AGV route optimization and multi-vehicle co-line scheduling are carried out based on Dijkstra greedy algorithm,software development and implementation are carried out,and in a certain assembly The workshop has been deployed and applied,and the application results show that the optical communica-tion method adopted by this technology is safe and reliable for transmission,and the multi-vehicle collinear optimization scheduling mecha-nism is reliable,which realizes the upgrading of the traditional passive logistics distribution mode in the assembly workshop to an active one based on state triggering.The logistics distribution mode effectively reduces the time waste caused by the untimely delivery of materials in the assembly workshop,improves the efficiency of workshop logistics flow,improves the digital level of the assembly workshop,and effectively promotes the digital transformation of enterprises.
关键词
光通讯/军工车间/物流调度Key words
Optical communication/Ordnance workshop/Logistics scheduling引用本文复制引用
出版年
2024
NETL
NSTL
万方数据