摘要
在分析智能工厂国内外研究现状基础上,对基于大数据的智能工厂数据平台架构技术展开研究,为智能生产的运行分析、预测、决策调控以及数字孪生信息物理融合提供技术参考。探讨了智能工厂定义与内涵,以及智能工厂大数据来源和特征,采用Hadoop、Spark、Storm热门开源大数据计算引擎,提出了数据来源层、数据传输层、数据存储层、资源管理层、处理分析层以及业务应用层构成的智能工厂大数据平台技术架构,有效解决智能工厂大数据多源复杂性和实时性的要求和难点。所提数据平台技术架构将对智能制造和智能工厂的实现具有重要的借鉴价值。
Based on the analysis of the existing research status of intelligent factories at home and abroad,this paper studies the data platform architecture technology for intelligent factories based on big data,providing technical reference for the operation analysis,prediction,decision control and the fusion of information and physics of digital twins of intelligent production.The paper not only discusses the definition and connotation of intelligent factory,intelligent factory big data source and characteristics,but also puts forward by using Hadoop+Spark+Storm the big data platform technology architecture of intelligent factory which includes the data source layer,the data transfer layer,the data storage layer,the resource management layer,the processing and analysis layer,and the business application layer.The technology architecture of the data platform will have important reference value for the realization of intelligent manufacture and intelligent factories.
作者
常镜洳
CHANG Jingru(Department of Software Engineering,Dalian Neusoft University of Information,Dalian 116023,China)
出处
《软件工程》
2019年第12期34-36,共3页
Software Engineering
关键词
大数据
智能工厂
数字孪生
big data
intelligent factory
Digital Twin
