{"title":"基于ISM-BN的化工事故风险因素分析","authors":"Yiming Ma, Mingguang Zhang, Mingliang Wang","doi":"10.1177/1748006x231205382","DOIUrl":null,"url":null,"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.","PeriodicalId":51266,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of accident risk factors in chemical industry based on ISM-BN\",\"authors\":\"Yiming Ma, Mingguang Zhang, Mingliang Wang\",\"doi\":\"10.1177/1748006x231205382\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":51266,\"journal\":{\"name\":\"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2023-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/1748006x231205382\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1748006x231205382","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
Analysis of accident risk factors in chemical industry based on ISM-BN
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.
期刊介绍:
The Journal of Risk and Reliability is for researchers and practitioners who are involved in the field of risk analysis and reliability engineering. The remit of the Journal covers concepts, theories, principles, approaches, methods and models for the proper understanding, assessment, characterisation and management of the risk and reliability of engineering systems. The journal welcomes papers which are based on mathematical and probabilistic analysis, simulation and/or optimisation, as well as works highlighting conceptual and managerial issues. Papers that provide perspectives on current practices and methods, and how to improve these, are also welcome