摘要
工业大数据是智能制造的核心,然而工业数据治理面临数据资源不丰富、数据标准不统一等问题。结合工业数据的隔离性、多模态、强关联以及高通量等特点,搭建了一套面向工业生产的数据治理体系,充分利用人工智能、大数据等先进技术,打通工业生产系统间的数据链条,实现数据融合共享,提升数据质量,以满足智能化生产过程管控需求,并为此提供高效的分析决策支持。通过数据治理应用实践案例,全方位体现数据治理对工业智能化和数字化的促进作用,为工业数字化转型提供技术支持。
Industrial Big Data is the core of intelligent manufacturing,but industrial data governance faces problems such as insufficient data resources and inconsistent data standards.Combining the characteristics of isolation,multi-modality,strong correlation and high throughput of industrial data,this paper builds a data governance system for industrial production,making full use of advanced technologies such as artificial intelligence and Big Data to get through the data chain between industrial production systems,realizes data fusion and sharing,improves data quality to meet the needs of intelligent production process management and control,and provides efficient analysis and decision support.Through its data governance practice cases,it fully reflects the role of data governance in promoting industrial intelligence and digitalization,and provides technical support for industrial digital transformation.
作者
汪洋
王柯
张桃宁
韩蕊
彭艳兵
汤国强
Wang Yang;Wang Ke;Zhang Taoning;Han Rui;Peng Yanbing;Tang Guoqiang(Nanjing Fiber Home World Communication Technology Limited Liability Company,Nanjing 210000,China;Nanjing Xhunter Software Limited Liability Company,Judicial Identification,Nanjing 210000,China)
出处
《信息技术与网络安全》
2022年第4期25-31,共7页
Information Technology and Network Security
关键词
工业大数据
数据治理
数据质量
应用实践
industrial Big Data
data governance
data quality
application practice
