Abstract
Infrastructure asset managers are often faced with the challenges of utilizing restricted budgets and making use of limited data to manage their assets. These problems are often further exacerbated by the need to meet the needs and aspirations of a diverse range of stakeholders.
To address these issues, this paper proposes an integrated asset and risk management framework which considers data uncertainty within the decision-making process. A probabilistic risk based approach is formulated to examine maintenance costs taking into consideration the uncertainty associated with asset deterioration and the cost and impact of maintenance and inform stakeholders.
This approach is demonstrated using a study of the UK’s canal system. The analysis found large maintenance cost uncertainties for a number of canal assets due to the large percentage of assets at risk of needing repair, the large difference in costs between preventive maintenance and major repairs and the greater uncertainty of assets requiring preventative maintenance. The analysis also demonstrates the necessity of adopting a plausible range analysis framework to improve long-term investment and whole lifecycle costing.
To address these issues, this paper proposes an integrated asset and risk management framework which considers data uncertainty within the decision-making process. A probabilistic risk based approach is formulated to examine maintenance costs taking into consideration the uncertainty associated with asset deterioration and the cost and impact of maintenance and inform stakeholders.
This approach is demonstrated using a study of the UK’s canal system. The analysis found large maintenance cost uncertainties for a number of canal assets due to the large percentage of assets at risk of needing repair, the large difference in costs between preventive maintenance and major repairs and the greater uncertainty of assets requiring preventative maintenance. The analysis also demonstrates the necessity of adopting a plausible range analysis framework to improve long-term investment and whole lifecycle costing.
Original language | English |
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Article number | 04016014 |
Number of pages | 12 |
Journal | ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering |
Volume | 3 |
Issue number | 1 |
Early online date | 25 Jul 2016 |
DOIs | |
Publication status | Published - Mar 2017 |
Keywords
- Asset management
- Risk Management
- Deterioration rate
- Cost analysis