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Intelligent Manufacturing for the Process Industry Driven by Industrial Artificial Intelligence
Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Peoples R China..
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0003-4299-0471
Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Peoples R China..
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-9940-5929
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2021 (English)In: ENGINEERING, ISSN 2095-8099, Vol. 7, no 9, p. 1224-1230Article in journal (Refereed) Published
Abstract [en]

Based on the analysis of the characteristics and operation status of the process industry, as well as the development of the global intelligent manufacturing industry, a new mode of intelligent manufacturing for the process industry, namely, deep integration of industrial artificial intelligence and the Industrial Internet with the process industry, is proposed. This paper analyzes the development status of the exist-ing three-tier structure of the process industry, which consists of the enterprise resource planning, the manufacturing execution system, and the process control system, and examines the decision-making, control, and operation management adopted by process enterprises. Based on this analysis, it then describes the meaning of an intelligent manufacturing framework and presents a vision of an intelligent optimal decision-making system based on human-machine cooperation and an intelligent autonomous control system. Finally, this paper analyzes the scientific challenges and key technologies that are crucial for the successful deployment of intelligent manufacturing in the process industry.

Place, publisher, year, edition, pages
Elsevier BV , 2021. Vol. 7, no 9, p. 1224-1230
Keywords [en]
Industrial artificial intelligence, Industrial Internet, Intelligent manufacturing, Process industry
National Category
Computer Sciences Production Engineering, Human Work Science and Ergonomics Computer Systems
Identifiers
URN: urn:nbn:se:kth:diva-305620DOI: 10.1016/j.eng.2021.04.023ISI: 000719871700007Scopus ID: 2-s2.0-85116422946OAI: oai:DiVA.org:kth-305620DiVA, id: diva2:1617154
Note

QC 20211206

Available from: 2021-12-06 Created: 2021-12-06 Last updated: 2022-06-25Bibliographically approved

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Yi, XinleiJohansson, Karl H.

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CiteExportLink to record
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