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Dynamic Semi-Quantitative Risk Research in Chemical Plants

Department of Control Science and Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
Quzhou Special Equipment Inspection Center, Quzhou 324000, China
Zhejiang Transit Fluorine Silicon Limited Company, Quzhou 324000, China
Author to whom correspondence should be addressed.
Processes 2019, 7(11), 849;
Received: 26 August 2019 / Revised: 7 November 2019 / Accepted: 8 November 2019 / Published: 12 November 2019
(This article belongs to the Special Issue Industry 4.0 and Sustainable Supply Chain Management)
When a major accident occurs in a chemical industry park, it directly affects the personal safety of operators and neighboring residents and causes major losses; therefore, we should take measures to strengthen the management of chemical industry parks. This article proposes and analyzes a new dynamic semi-quantitative risk calculation model for chemical plants that can be applied digitally. This model provides a sustainable, standardized, and comprehensive management strategy for the safety management of chemical plants and chemical industry park managers. The model and its determined parameters were applied to the safety management of chemical companies within the chemical industry park of Quzhou, Zhejiang Province. From the point of view of the existing semi-quantitative model, the existing problems of the current model are analyzed, the current model is optimized, and a new dynamic semi-quantitative calculation model scheme is proposed. The new model uses an analytical hierarchy process targeting the factors affecting the risks in chemical plants, and chemical plant semi-quantitative dynamic calculation system consisting of the operator, process/equipment, risk, building environment, safety management, and domino effect, and the comprehensive risk of the chemical plant was calculated. The model is ultimately a real-time quantitative value, but its calculation process can compare and analyze the causes of high risk in a chemical plant as they relate to these six factors. Its implementation requires only software, which will greatly help chemical plant safety management. View Full-Text
Keywords: analytical hierarchy process; chemical plants; dynamic semi-quantitative calculation; risk value analytical hierarchy process; chemical plants; dynamic semi-quantitative calculation; risk value
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MDPI and ACS Style

Song, Q.; Jiang, P.; Zheng, S.; Kong, Y.; Zhao, Y.; Shen, G. Dynamic Semi-Quantitative Risk Research in Chemical Plants. Processes 2019, 7, 849.

AMA Style

Song Q, Jiang P, Zheng S, Kong Y, Zhao Y, Shen G. Dynamic Semi-Quantitative Risk Research in Chemical Plants. Processes. 2019; 7(11):849.

Chicago/Turabian Style

Song, Qiusheng, Peng Jiang, Song Zheng, Yaguang Kong, Ye Zhao, and Gang Shen. 2019. "Dynamic Semi-Quantitative Risk Research in Chemical Plants" Processes 7, no. 11: 849.

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