Life Cycle Cost Analysis based Optimal Maintenance and Rehabilitation for Underground Infrastructure Management

This study presents a sanitary sewer management decision-making framework incorporating demand forecasting and life cycle cost analysis. The framework provides the asset managers with an alternative approach in sewer management. It is designed to allow asset managers to better allocate limited funds...

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Bibliographic Details
Published in:KSCE journal of civil engineering 2006, 10(4), , pp.243-253
Main Authors: Chung, Seung-Hyun, Hong, Tae-Hoon, Han, Seung-Woo, Son, Jae-Ho, Lee, Sang-Youb
Format: Article
Language:English
Subjects:
Artificial neural networks
Cost analysis
Decision analysis
Decision making
Demand
Dynamic programming
Forecasting
Life cycle
Life cycle analysis
Life cycle costs
Life cycles
Maintenance
Managers
Markov chains
Mathematical models
Neural networks
Rehabilitation
Sanitary sewers
Sewer maintenance
Sewers
Studies
Waste management
토목공학
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Summary:This study presents a sanitary sewer management decision-making framework incorporating demand forecasting and life cycle cost analysis. The framework provides the asset managers with an alternative approach in sewer management. It is designed to allow asset managers to better allocate limited funds for maintenance and rehabilitation by identifying possible problematic sewers and devising a maintenance plan to prevent costly sewer failures. Sewer demand forecasting model is developed using an artificial neural network. The forecasted sewer demand is then used to identify “critical” areas, where the current hydraulic capacity is less than the forecasted sewer demand. In such areas, an optimal maintenance and rehabilitation strategy is developed through the application of probabilistic dynamic programming in conjunction with Markov chain deterioration modeling.
ISSN:1226-7988
1976-3808
DOI:10.1007/BF02830778