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Guest Editorial Special Issue on Deep Integration of Artificial Intelligence and Data Science for Process Manufacturing.

Authors :
Qian, Feng
Jin, Yaochu
Qin, S. Joe
Sundmacher, Kai
Source :
IEEE Transactions on Neural Networks & Learning Systems. Aug2021, Vol. 32 Issue 8, p3294-3295. 2p.
Publication Year :
2021

Abstract

Process manufacturing serves as the pillar of the continuous manufacturing industry such as oil, gas, chemicals, nonferrous metals, iron, and steel, and thus is closely related to almost every aspect of human life. On the one hand, in order to meet several urgent but challenging demands of increasing profits, reducing materials consumption, enhancing safety, and protecting the environment, it is necessary to facilitate the development of process manufacturing with the usage of some novel and advanced techniques such as artificial intelligence (AI) and computation intelligence (CI). On the other hand, with the increasing scale of process manufacturing, another challenge is how to effectively deal with a huge amount of industrial big data in the process industry for environmental perception, modelling, optimization, decision-making, autonomous intelligent control, fault detection, and risk analysis. Therefore, it is of fundamental importance to deeply integrate AI, CI, and data sciences to achieve accurate control and optimal decision-making for process industries. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2162237X
Volume :
32
Issue :
8
Database :
Academic Search Index
Journal :
IEEE Transactions on Neural Networks & Learning Systems
Publication Type :
Periodical
Accession number :
153127774
Full Text :
https://doi.org/10.1109/TNNLS.2021.3092896