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Big Data Analytics for Smart Factories of the Future

Published

Author(s)

Robert Gao, Lihui Wang, Moneer Helu, Roberto Teti

Abstract

Continued advancement of sensors has led to an ever-increasing amount of data of various physical nature to be acquired from production lines. As rich information relevant to the machines and processes are embedded within these "big data," how to effectively and efficiently discover patterns in the big data to enhance productivity and economy has become both a challenge and an opportunity. This paper discusses essential elements of and promising solutions enabled by data science that are critical to processing data of high volume, velocity, variety, and low veracity, towards the creation of added-value in smart factories of the future.
Citation
CIRP Annals-ManufacturingTechnology
Volume
69
Issue
2

Keywords

Digital Manufacturing System, Information, Learning

Citation

Gao, R. , Wang, L. , Helu, M. and Teti, R. (2020), Big Data Analytics for Smart Factories of the Future, CIRP Annals-ManufacturingTechnology, [online], https://doi.org/10.1016/j.cirp.2020.05.002, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=929090 (Accessed October 24, 2021)
Created June 17, 2020, Updated October 12, 2021