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Analysis of accident risk factors in chemical industry based on ISM-BN

Author

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  • Yiming Ma
  • Mingguang Zhang
  • Mingliang Wang

Abstract

The chemical industry involves the production, storage, and use of many flammable, explosive, toxic, and other hazardous chemicals. Once an accident occurs, it will cause serious harm to human and economic activities. In order to prevent chemical accidents, this paper combines Interpretive Structural Modeling (ISM) and Bayesian network (BN) to quantitatively study the relationship and interaction strength among accident risk factors in chemical industry. Through the analysis of accident cases and questionnaire survey, 21 accident risk factors in chemical industry are selected. According to the decision of experts, the influence relationship between risk factors is determined, and a multi-level directed graph of ISM is obtained. And the ISM model is transformed into a quantitative BN model. The BN model is applied to forward reasoning, sensitivity analysis, and reverse reasoning. The results indicate that there is a positive correlation between various risk factors and chemical accidents, and the supervision mechanism has the highest probability of occurrence in production activities. Illegal operation has the highest sensitivity and the greatest impact on chemical accidents. Inherent hazards of materials and products is the most likely cause of accidents. Based on the research results, feasible measures have been proposed to improve safety management in the chemical industry.

Suggested Citation

  • Yiming Ma & Mingguang Zhang & Mingliang Wang, 2024. "Analysis of accident risk factors in chemical industry based on ISM-BN," Journal of Risk and Reliability, , vol. 238(6), pages 1209-1223, December.
    • Handle: RePEc:sae:risrel:v:238:y:2024:i:6:p:1209-1223
    DOI: 10.1177/1748006X231205382
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    1. Lee Cronbach, 1951. "Coefficient alpha and the internal structure of tests," Psychometrika, Springer;The Psychometric Society, vol. 16(3), pages 297-334, September.
    2. Yunmeng Lu & Tiantian Wang & Tiezhong Liu, 2020. "Bayesian Network-Based Risk Analysis of Chemical Plant Explosion Accidents," IJERPH, MDPI, vol. 17(15), pages 1-20, July.
    3. Pfohl, Hans-Christian & Gallus, Philipp & Thomas, David, 2011. "Interpretive structural modeling of supply chain risks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 55230, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. Huang, Wencheng & Zhang, Yue & Kou, Xingyi & Yin, Dezhi & Mi, Rongwei & Li, Linqing, 2020. "Railway dangerous goods transportation system risk analysis: An Interpretive Structural Modeling and Bayesian Network combining approach," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    5. Sushil, 2018. "How to check correctness of total interpretive structural models?," Annals of Operations Research, Springer, vol. 270(1), pages 473-487, November.
    6. Hongfu Mi & Xiaomei Zhang & Wenhe Wang & Wenjing Yang & Xinsheng Jiang & J Santos Reyes, 2022. "A Risk Analysis Method of Cable Fire in Utility Tunnel Based on a Bayesian Network," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-13, July.
    7. Wang, Zengkai & Zeng, Shengkui & Guo, Jianbin & Che, Haiyang, 2021. "A Bayesian network for reliability assessment of man-machine phased-mission system considering the phase dependencies of human cognitive error," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    8. Yang, Zhisen & Yang, Zaili & Yin, Jingbo, 2018. "Realising advanced risk-based port state control inspection using data-driven Bayesian networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 38-56.
    9. Nandal, Vinod & Kumar, Raj & Singh, S.K., 2019. "Barriers identification and analysis of solar power implementation in Indian thermal power plants: An Interpretative Structural Modeling approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    10. Wu, Wei-Shing & Yang, Chen-Feng & Chang, Jung-Chuan & Château, Pierre-Alexandre & Chang, Yang-Chi, 2015. "Risk assessment by integrating interpretive structural modeling and Bayesian network, case of offshore pipeline project," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 515-524.
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