Since gas plants are progressively increasing near urban areas, a comprehensive tool to plan maintenance and reduce the risk arising from their operations is required. To this end, a comparison of three Risk-Based Maintenance methodologies able to point out maintenance priorities for the most critical components, is presented in this paper. Moreover, while the literature is mostly focused on probabilistic analysis, a particular attention is directed towards consequence analysis throughout this study. The first developed technique is characterized by a Hierarchical Bayesian Network to perform the occurrence analysis and a Failure Modes, Effects and Criticality Analysis to assess the magnitude of the adverse outcomes. The second approach is a Quantitative Risk Analysis carried out via a software named Safeti. Finally, another software called Synergi Plant is adopted for the third methodology, which provides a Risk-Based Inspection plan, through a semiquantitative risk analysis. The proposed study can assist asset manager in adopting the most appropriate methodology to their context, while highlighting priority components. To demonstrate the applicability of the approaches and compare their rankings, a Natural Gas Regulating and Measuring Station is considered as case study. The results showed that the most suited method strongly depends on the available data.

由于城市附近的天然气厂正在逐渐增加，因此需要一种综合的工具来计划维护并降低其运营所带来的风险。为此，本文对三种基于风险的维护方法进行了比较，这些方法能够指出最关键组件的维护优先级。此外，尽管文献主要集中在概率分析上，但在整个研究过程中，都特别关注结果分析。最早开发的技术的特征在于，进行事件分析的层次贝叶斯网络和评估不良结果的严重程度的失效模式，影响和临界度分析。第二种方法是通过名为Safeti的软件进行定量风险分析。最后，第三种方法采用了另一种名为Synnergi Plant的软件，该软件通过半定量风险分析提供了基于风险的检查计划。拟议的研究可以帮助资产管理者根据自己的情况采用最合适的方法，同时强调优先事项。为了证明这些方法的适用性并比较其排名，将天然气调节和测量站作为案例研究。结果表明，最合适的方法在很大程度上取决于可用的数据。为了证明这些方法的适用性并比较其排名，将天然气调节和测量站作为案例研究。结果表明，最合适的方法在很大程度上取决于可用的数据。为了证明这些方法的适用性并比较其排名，将天然气调节和测量站作为案例研究。结果表明，最合适的方法在很大程度上取决于可用的数据。