HIGH-PERFORMANCE COMPUTING BASED BIG DATA ANALYTICS FOR SMART MANUFACTURING

被引:0
|
作者
Yang, Yuhang [1 ]
Cai, Y. Dora [2 ]
Lu, Qiyue [2 ]
Zhang, Yifang [2 ]
Koric, Seid [2 ]
Shao, Chenhui [1 ]
机构
[1] Univ Illinois, Dept Mech Sci & Engn, Urbana, IL 61801 USA
[2] Univ Illinois, Natl Ctr Supercomp Applicat, Urbana, IL 61801 USA
关键词
High-Performance Computing; Parallel Computing; Genetic Algorithm; Data Analytics; Smart Manufacturing; Dynamic Sampling Design; Big Data; SYSTEM-DESIGN;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
With the rapid development of sensing, communication, and computing technologies and infrastructure, today's manufacturing industry is marching towards a big data era and a new generation of digitalization and intelligence. The availability of big data provides us with a golden opportunity to promote smart manufacturing. Nevertheless, the deployment and popularization of big data analytics in manufacturing is still at its nascent stage. One critical challenge results from the lack of high-performance computing (HPC) capability, which is crucial for responsive and intelligent decision -making in the modern manufacturing industry. To address this challenge, this paper proposes a framework and some general guidelines for implementing big data analytics in an HPC environment. The details of the whole workflow, from the prototype to the final application, are highlighted. A case study for intelligent 3D sensing with real-world manufacturing data is presented to demonstrate the effectiveness of the proposed framework.
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页数:8
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