TY - GEN
T1 - High-performance computing based big data analytics for smart manufacturing
AU - Yang, Yuhang
AU - Cai, Yandong Dora
AU - Lu, Qiyue
AU - Zhang, Yifang
AU - Koric, Seid
AU - Shao, Chenhui
N1 - Publisher Copyright:
Copyright © 2018 ASME.
PY - 2018
Y1 - 2018
N2 - 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 highperformance 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.
AB - 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 highperformance 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.
KW - Big Data
KW - Data Analytics
KW - Dynamic Sampling Design
KW - Genetic Algorithm
KW - High-Performance Computing
KW - Parallel Computing
KW - Smart Manufacturing
UR - http://www.scopus.com/inward/record.url?scp=85054988564&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85054988564&partnerID=8YFLogxK
U2 - 10.1115/MSEC2018-6602
DO - 10.1115/MSEC2018-6602
M3 - Conference contribution
AN - SCOPUS:85054988564
SN - 9780791851371
T3 - ASME 2018 13th International Manufacturing Science and Engineering Conference, MSEC 2018
BT - Manufacturing Equipment and Systems
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2018 13th International Manufacturing Science and Engineering Conference, MSEC 2018
Y2 - 18 June 2018 through 22 June 2018
ER -