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Optimisation of maintenance interventions for railway bridges

conference contribution
posted on 06.12.2017, 00:00 by Dwayne Nielsen, Richard Egelstaff, Timothy Mcsweeney
Maintenance of aging infrastructure is a burden on many organisational budgets. Life Cycle Cost Analysis (LCCA) is accepted as an effective method to reduce these costs and keep within budgets. However, LCCA becomes extremely complex when applied at an individual component level. This is particularly so when there is a large population of bridges, because owners need to consider multiple maintenance strategies, varying deterioration rates and intervention intervals. To address this concern, a decision support framework is presented in this paper that proposes maintenance actions for future interventions based on a selection of maintenance strategies, while at the same time keeping within organisational budget constraints. In addition, the remaining value of surrounding bridge components is considered when assessing the most appropriate maintenance actions. Asset managers are encouraged to apply one of three strategies (refurbish, upgrade or renew) to estimate future network budgets and align with existing budgets. An important outcome from this research is a decision support framework that allows decision makers to conduct “what-if” maintenance scenarios. This framework calculates life cycle costs from life gained due to maintenance actions, maintenance costs, maintenance strategy, discount rate, intervention trigger time and minimum intervention intervals.

Funding

Category 4 - CRC Research Income

History

Start Page

1

End Page

9

Number of Pages

9

Start Date

01/01/2014

Finish Date

01/01/2014

Location

Brisbane, Australia

Publisher

Informa

Place of Publication

Sydney, NSW

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

Centre for Railway Engineering; Institute for Resource Industries and Sustainability (IRIS); School of Engineering and Technology (2013- );

Era Eligible

Yes

Name of Conference

International Congress of Condition Monitoring and Diagnostic Engineering