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首页> 外文期刊>Journal of Cleaner Production >A novel Fuzzy Bayesian Network approach for safety analysis of process systems; An application of HFACS and SHIPP methodology
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A novel Fuzzy Bayesian Network approach for safety analysis of process systems; An application of HFACS and SHIPP methodology

机译：用于过程系统安全性分析的新型模糊贝叶斯网络方法; HFACS和SHIPP方法论的应用

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摘要

Chemical process industries (CPI) are inherently hazardous complex systems where large inventory of extremely flammable and explosive chemicals are processed and stored in a highly congested process area. A reliable safety analysis method plays a significant role to measure risks and to develop preventive strategies in process industries. This paper proposed a novel Fuzzy Bayesian Network for dynamic safety analysis of process systems by incorporating Bayesian network (BN) with Fuzzy Best Worst Method (Fuzzy-BWM). In the proposed approach a comprehensive and in-depth analysis of human and organizational factors (HOFs) involving in the accident scenario occurrence was also provided by integrating Human Factor Analysis and Classification System (HFACS) and System Hazard Identification, Prediction and Prevention (SHIPP) methodology into the model. An ethylene storage tank was selected to verify the applicability of the proposed approach and its application potential. The study also explained a comparison between the results of the proposed Fuzzy-BWM approach with the conventional BN approach and a quantitative risk assessment (QRA) conventional technique such as bow-tie (BT). The findings revealed the capability of the proposed Fuzzy-BWM approach to provide high reliable results and to detect risks that using the BT and BN approaches were not identified. (C) 2019 Elsevier Ltd. All rights reserved.
机译：化学过程工业（CPI）是本质上有害的复杂系统，在该系统中，大量易燃易爆化学品的大量库存被处理并存储在高度拥挤的过程区域中。可靠的安全分析方法在过程工业中衡量风险和制定预防策略中起着重要作用。本文提出了一种新颖的模糊贝叶斯网络，将贝叶斯网络（BN）与模糊最佳最差方法（Fuzzy-BWM）相结合，用于过程系统的动态安全分析。在拟议的方法中，还通过将人为因素分析和分类系统（HFACS）与系统危害识别，预测和预防（SHIPP）集成在一起，对涉及事故场景发生的人为因素和组织因素（HOF）进行了全面，深入的分析。方法论纳入模型。选择了一个乙烯储罐来验证所提出方法的适用性及其应用潜力。该研究还解释了拟议的Fuzzy-BWM方法与常规BN方法的结果与定量风险评估（QRA）传统技术（例如领结（BT））之间的比较。研究结果表明，所提出的Fuzzy-BWM方法具有提供高可靠结果并检测未确定使用BT和BN方法的风险的能力。 （C）2019 Elsevier Ltd.保留所有权利。

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  • 来源
    《Journal of Cleaner Production》 |2020年第2期|118761.1-118761.18|共18页
  • 作者

  • 作者单位

    Arak Univ Med Sci Ashtian Hlth Care Ctr Dept Occupat Hlth Engn Arak Iran|Shiraz Univ Med Sci Sch Hlth Student Res Comm Shiraz Iran;

    Shiraz Univ Med Sci Sch Hlth Dept Occupat Hlth Res Ctr Hlth Sci Inst Hlth Shiraz Iran;

    Mashhad Univ Med Sci Fac Hlth Dept Occupat Hlth & Safety Engn Mashhad Razavi Khorasan Iran;

    Shiraz Univ Fac Econ Management & Social Sci Dept Management Shiraz Iran;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Bayesian network; Fuzzy best worst method; Process industries; Safety analysis;

    机译：贝叶斯网络;模糊最佳最差方法;加工工业;安全分析;

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