Application of decision support models in asset management of sewer networks: Framework and case study

Tran, H, Marlow, D and May, R 2010, 'Application of decision support models in asset management of sewer networks: Framework and case study', in George Ruchti; Tom Roode, P.E (ed.) Proceedings of the Pipelines 2010: Climbing New Peaks to Infrastructure Reliability, Renew, Rehab, and Reinvest, Colorado, United States, 28 August -1 September 2010, pp. 846-856.


Document type: Conference Paper
Collection: Conference Papers

Title Application of decision support models in asset management of sewer networks: Framework and case study
Author(s) Tran, H
Marlow, D
May, R
Year 2010
Conference name Pipelines 2010: Climbing New Peaks to Infrastructure Reliability, Renew, Rehab, and Reinvest
Conference location Colorado, United States
Conference dates 28 August -1 September 2010
Proceedings title Proceedings of the Pipelines 2010: Climbing New Peaks to Infrastructure Reliability, Renew, Rehab, and Reinvest
Editor(s) George Ruchti; Tom Roode, P.E
Publisher American Society of Civil Engineers
Place of publication United States
Start page 846
End page 856
Total pages 11
Abstract This paper presents a framework for application of modelling tools in an integrated approach to deal with the probabilistic manner of deterioration processes. The framework will assist industry towards implementation of integrated asset management approaches by addressing research and practical challenges such as (1) which assets should be inspected with high priority? and (2) how decision support models can be used to provide important information for various levels of asset management. The framework is applied to a case study relating to asset management of sewers and manholes. A preliminary result of statistical analysis on sewer data of the case study is also presented.
Subjects Infrastructure Engineering and Asset Management
Keyword(s) Assets
Case studies
Decision support systems
Sewers
DOI - identifier 10.1061/41138(386)81
Copyright notice © 2010 ASCE
ISBN 9780784411384
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