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Volume 11
Issue 6
10.3390/pr11061608
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Review

Abnormal Situation Management in Chemical Processes: Recent Research Progress and Future Prospects

by
Shangzhi Liu
1,2,
Fangyi Lei
3,
Dongfeng Zhao
2,3,* and
Qinglong Liu
2
1
College of Mechanical and Electronic Engineering, China University of Petroleum (East China), Qingdao 266580, China
2
Center for Safety, Environmental & Energy Conservation Technology, China University of Petroleum (East China), Qingdao 266580, China
3
College of Chemistry and Chemical Engineering, China University of Petroleum (East China), Qingdao 266580, China
*
Author to whom correspondence should be addressed.
Processes 2023, 11(6), 1608; https://doi.org/10.3390/pr11061608
Submission received: 23 April 2023 / Revised: 22 May 2023 / Accepted: 23 May 2023 / Published: 25 May 2023
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Abstract

In the chemical process, abnormal situations are precursor events of incidents and accidents. Abnormal situation management (ASM) can effectively identify abnormalities and prevent them from evolving into incidents or accidents, ensuring the safe and smooth operation of chemical plants. In recent years, ASM has attracted extensive attention from the process industry and from academia, and a lot of research work has been conducted. However, the intelligence level of ASM in actual chemical plants is still relatively low, and industrial applications still face many difficulties and challenges. This review first summarizes the concepts and involved in the contents of ASM. Then, the latest research progress in various aspects of ASM is systematically reviewed. Finally, the challenges and future research directions of ASM are analyzed based on the perspective of industrial application. This review aims to provide the most cutting-edge reference for follow-up research on ASM, and to promote the intelligent development and practical industrial application of ASM in the chemical process.
Keywords: chemical process; abnormal situation management; fault detection and diagnosis; early prediction and warning; root cause analysis; dynamic risk assessment; intelligence; industrial application; digital twin system chemical process; abnormal situation management; fault detection and diagnosis; early prediction and warning; root cause analysis; dynamic risk assessment; intelligence; industrial application; digital twin system

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MDPI and ACS Style

Liu, S.; Lei, F.; Zhao, D.; Liu, Q. Abnormal Situation Management in Chemical Processes: Recent Research Progress and Future Prospects. Processes 2023, 11, 1608. https://doi.org/10.3390/pr11061608

AMA Style

Liu S, Lei F, Zhao D, Liu Q. Abnormal Situation Management in Chemical Processes: Recent Research Progress and Future Prospects. Processes. 2023; 11(6):1608. https://doi.org/10.3390/pr11061608

Chicago/Turabian Style

Liu, Shangzhi, Fangyi Lei, Dongfeng Zhao, and Qinglong Liu. 2023. "Abnormal Situation Management in Chemical Processes: Recent Research Progress and Future Prospects" Processes 11, no. 6: 1608. https://doi.org/10.3390/pr11061608

APA Style

Liu, S., Lei, F., Zhao, D., & Liu, Q. (2023). Abnormal Situation Management in Chemical Processes: Recent Research Progress and Future Prospects. Processes, 11(6), 1608. https://doi.org/10.3390/pr11061608

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