Skip to Main Content (Press Enter)

Logo UNIECAMPUS
  • ×
  • Home
  • Degrees
  • Courses
  • Jobs
  • People
  • Outputs
  • Organizations
  • Third Mission
  • Expertise & Skills

UNI-FIND
Logo UNIECAMPUS

|

UNI-FIND

uniecampus.it
  • ×
  • Home
  • Degrees
  • Courses
  • Jobs
  • People
  • Outputs
  • Organizations
  • Third Mission
  • Expertise & Skills
  1. Outputs

On risk-based maintenance: A comprehensive review of three approaches to track the impact of consequence modelling for predicting maintenance actions

Academic Article
Publication Date:
2021
abstract:
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.
Iris type:
1.1 Articolo in rivista
Keywords:
Risk-based maintenance; Hierarchical bayesian approach; Quantitative risk analysis; Natural gas distribution network
List of contributors:
Leoni, Leonardo; De Carlo, Filippo; Paltrinieri, Nicola; Sgarbossa, Fabio; Bahootoroody, Ahmad
Authors of the University:
LEONI LEONARDO
Handle:
https://iris.uniecampus.it/handle/11389/80783
Published in:
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
Journal
  • Overview

Overview

URL

https://www.sciencedirect.com/science/article/pii/S0950423021001637?dgcid=author
  • Use of cookies

Powered by VIVO | Designed by Cineca | 26.9.2.0