Abstract
This paper describes the main features of a modelling framework that sets out a systematic approach to railway infrastructure asset management enabling decisions to be made based not only on costs but on service performance and safety. First, the framework structure is briefly described, then the main focus is on the discussion of the modelling capabilities that will support decisions on the asset interventions that have an impact in reducing the risk related to the use of the railway infrastructure. Standard industrial techniques such as event trees can be used to lay out all the possible paths leading from an initiating event to a given outcome through a series of success and failure events. Only the probability of the intermediate events related to failures of the infrastructure can be controlled by the Infrastructure Operator through maintenance. State-based stochastic models using Petri nets are developed for each asset type to predict the asset response to maintenance, including the probability of the different failure modes. Such predictions can support the selection of the most effective maintenance strategies that contribute to reduce the risk related to the use of the infrastructure. An example is provided for evaluating the risk of train derailment due to track geometry faults.
Original language | English |
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Number of pages | 12 |
Publication status | Published - 1 Jan 2018 |
Externally published | Yes |
Event | 14th Probabilistic Safety Assessment and Management, PSAM 2018 - Los Angeles, United States Duration: 16 Sept 2018 → 21 Sept 2018 |
Conference
Conference | 14th Probabilistic Safety Assessment and Management, PSAM 2018 |
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Country/Territory | United States |
City | Los Angeles |
Period | 16/09/18 → 21/09/18 |
Keywords
- Degradation and maintenance modelling
- Derailment
- Petri nets
- Railway asset management