Comparison of risk-based maintenance approaches applied to a natural gas regulating and metering station
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In the last decades many researchers have directed their efforts towards safety improvement of plants where hazardous substances are processed or handled. This attitude has led to develop strategic plans for minimizing risk and costs arising from the operations. Accidents related to hazardous substances can indeed pose a threat for human beings and the surrounding environment, therefore a reliable tool for engineering maintenance is required. This work presents the comparison of three different Risk-Based Maintenance (RBM) approaches for prioritizing maintenance actions. In the first technique, Hierarchical Bayesian Network (HBN) is adopted to estimate the probability of failure components, while the severity is assessed via Failure, Mode, Effects and Criticality Analysis (FMECA). Subsequently costs related to each component are evaluated and a Cost Risk Priority Number (C-RPN) is obtained. The second approach consists on a classic Quantitative Risk Analysis (QRA), where standard probabilities from literature are exploited for the modelling of the different scenarios. In this study the catastrophic rupture and three sizes of leakage have been chosen as reference scenarios for each component. The analysis is carried out through a software named Safeti (by Den Norske Veritas – German Lloyds DNV-GL), which performs calculations based on standard source, dispersion and consequence models. Safeti provides a risk metric of components that is used to rank their criticality. At last, another software by DNV-GL (Synergi-Plant) is adopted for the third methodology, by which a Risk-Based Inspection (RBI) plan is obtained and Future Risk Total Cost curves are studied. The three approaches are compared based on the component rankings obtained and heir susceptibility to variations of input parameters. This comprehensive review can help maintenance engineers to reduce risks resulting from operations and pinpoint the most critical components, by using the methodology that is more suitable for their case. To demonstrate the three different methodologies and compare their results a Natural Gas Regulating and Metering Station (NGRMS) is considered as case of study. The results show that applying the three methods to the same plant gives different component rankings, due to their different sensitivities and settings.