Monitoring and Control of Unstructured Manufacturing Big Data

被引：0
|
作者：
Cui, Yesheng [1 ]
Kara, Sami [1 ]
Chan, Ka C. [1 ,2 ]
机构：
[1] Univ New South Wales, Sch Mech & Mfg Engn, Sydney, NSW, Australia
[2] Univ Southern Queensland, Sch Management & Enterprise, Springfield, Australia
来源：
2020 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT (IEEE IEEM) | 2020年
关键词：
Big data; unstructured data; Industry; 4.0;
D O I：
10.1109/ieem45057.2020.9309975
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Unstructured manufacturing big data silos are challenging for enabling various data-driven applications such as digital threads and digital twins in manufacturing. The management of big data silos requires to address the issues of large volume, data inconsistency, data redundancy, information silos and data security. This research developed a systematic approach to managing data silos using the state of art big data software. Applying this approach in the product life cycle can control data silos, data consistency, redundancy, timely update and enable the automatic workflow of each system.
引用
收藏
页码：928 / 932
页数：5
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