Most risk assessment methods have problems such as uncertainty, static structure, and lack of validation. Also, in most of these studies, less attention has been paid to human, managerial, and organizational issues. Therefore, this study proposes a risk assessment method based on the Fuzzy Bayesian Network (FBN) to prevent failure of firefighting systems (FFSs) in the atmospheric Storage Tanks of a Petrochemical Industry. The first stage of the study is the development of a fault tree (FT) and investigation of basic events (BEs). In this study, content validity indices and brainstorming technique were used to validate the FT structure and reduce the uncertainties of Completeness, Modeling, and Parameter. After determining the probability of basic events (BEs) by the expert team opinions and fuzzy logic, events were transmitted to the Bayesian Network (BN) and then analyzed with deductive and inductive reasoning, followed by sensitivity analysis in the GeNIe software. Finally, results of a case study in the Atmospheric Storage Tanks of the Methanol Floating Roof of a Petrochemical Industry showed that FBN simulation and FT validation could provide a practical way to determine FFSs probabilities, identify impactful events, and reduce the above uncertainties. Also, taking account of hidden factors of events, such as organizational and managerial factors, can help managers to prevent FFSs in tanks.

大多数风险评估方法都存在诸如不确定性，静态结构和缺乏验证之类的问题。同样，在大多数这些研究中，对人，管理和组织问题的关注较少。因此，本研究提出了一种基于模糊贝叶斯网络（FBN）的风险评估方法，以防止石化行业大气储罐中消防系统（FFS）的故障。研究的第一阶段是故障树（FT）的开发和基本事件（BE）的调查。在这项研究中，内容有效性指标和集思广益技术被用来验证FT结构并减少完整性，建模和参数的不确定性。通过专家组的意见和模糊逻辑确定基本事件（BE）的概率后，事件被传输到贝叶斯网络（BN），然后通过演绎和归纳推理进行分析，然后在GeNIe软件中进行敏感性分析。最后，在石化行业甲醇浮顶的大气储罐中的案例研究结果表明，FBN模拟和FT验证可以提供一种确定FFS概率，识别有影响的事件并减少上述不确定性的实用方法。同样，考虑到事件的隐性因素，例如组织和管理因素，也可以帮助管理人员预防坦克中的FFS。在石化行业的甲醇浮顶的大气储罐中进行的案例研究结果表明，FBN模拟和FT验证可以为确定FFS概率，识别有影响的事件并减少上述不确定性提供一种实用的方法。同样，考虑到事件的隐性因素，例如组织和管理因素，也可以帮助管理人员预防坦克中的FFS。在石化行业的甲醇浮顶的大气储罐中进行的案例研究结果表明，FBN模拟和FT验证可以为确定FFS概率，识别有影响的事件并减少上述不确定性提供一种实用的方法。同样，考虑到事件的隐性因素，例如组织和管理因素，也可以帮助管理人员预防坦克中的FFS。