Big data analytics for smart factories of the future
Big data analytics for smart factories of the future
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DOI：
10.1016/j.cirp.2020.05.002
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发表时间：
2020-01-01
影响因子：
4.1
通讯作者：
Teti, Roberto
中科院分区：
文献类型：
--
作者：
Gao, Robert X.;Wang, Lihui;Teti, Roberto
传感器的不断进步导致了从生产线上获取的各种物理性质的数据量不断增加。随着丰富的与机器和工艺相关的信息嵌入其中，如何有效、高效地发现大数据中的模式，以提高生产率和经济性，既成为挑战，也成为机遇。本文讨论了数据科学的基本要素和有前景的解决方案，这些解决方案对于处理大容量、高速度、多种多样和低准确性的数据至关重要，有助于在未来的智能工厂中创造附加值。(C)2020年CIRP。爱思唯尔有限公司出版。保留所有权利。
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. (C) 2020 CIRP. Published by Elsevier Ltd. All rights reserved.