摘要
随着工业4.0的推进,智能工厂作为现代制造业的重要发展方向,对大数据处理与分析的需求也日益增加。提出了一种适用于智能工厂的大数据处理与分析架构,旨在提升智能工厂的数据融合与处理能力。然后,研究了数据分析预处理的层级结构,其包含数据采集层、数据预处理层、数据融合层、数据存储层、数据分析层、数据可视化层和数据共享与接口层等。通过对数据进行系统化的处理与分析,该架构能够实现对企业数据、工业数据和外部数据的有效融合与管理,为智能工厂的优化和决策提供了科学依据。
With the advancement of Industry 4.0,smart factories,as an important development direction of modern manufacturing,have increasing demands for big data processing and analysis.This paper proposes a big data processing and analysis architecture suitable for smart factories,aiming to improve data fusion and processing capabilities in smart factories.Then,the hierarchical structure of data analysis preprocessing was studied,including data acquisition layer,data preprocessing layer,data fusion layer,data storage layer,data analysis layer,data visualization layer,and data sharing and interface layer.Through systematic processing and analysis of data,the architecture realizes the effective integration and management of enterprise data,industrial data and external data,providing a scientific basis for the optimization and decision-making of smart factories.
作者
张海森
ZHANG Haisen(Guangzhou Henkel Surface Technologies Co.,Ltd.,Guangzhou,Guangdong 511431,China)
出处
《自动化应用》
2025年第6期110-112,共3页
Automation Application
