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

Feng QIAN , Yaochu JIN, S. Joe QIN, Kai SUNDMACHER

Research output: Journal PublicationsEditorial/Preface (Journal)

5 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)3294-3295
Number of pages2
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume32
Issue number8
DOIs
Publication statusPublished - Aug 2021
Externally publishedYes

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