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AN ASSET MANAGEMENT PLANNING TOOL FOR SCHEDULING REPAIR AND REPLACEMENT PROJECTS

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Abstract:

In recent years, the water and wastewater industry has become increasingly involved in developing asset management programs to identify the timing and costs of upcoming repair and replacement (R&R) projects. To assist in this effort, Carollo Engineers has developed the Water/Wastewater Asset Manager™ (WAM), an asset management software program designed specifically for use in the development of a long-term capital improvement plan (CIP). The WAM software incorporates fundamental concepts of asset management, such as existing condition, desired level of service goals, criticality, vulnerability, risk and remaining useful life, with cost information to identify future R&R projects, as well as the associated implementation costs and timing for replacement.

Before WAM can be used to identify and prioritize future R&R projects, the agency must identify which criteria will be used to evaluate whether a project should be included in their CIP. These criteria are specific to each agency; however, typical evaluation criteria include risk, condition, replacement cost, or repair cost. Once these criteria have been identified, WAM can be used to filter the asset tree to identify those assets that meet the specified criteria. WAM can then prioritize those assets based on these criteria, and can also be used to identify the predicted timing for the implementation of these future R&R projects.

In addition to its use as a planning tool, WAM can be used to aid an agency in the overall process of converting asset data into knowledge. A variety of reports can be generated, from asset specific reports to facility summary reports, based on user-customized queries. WAM is also able to store numerous databases so that asset information can be tracked over time. This feature provides WAM the ability to develop graphs that can be used to develop customized condition decay curves for each asset. This knowledge enables agencies to make better, more informed decisions regarding implementation of future R&R projects by predicting the deterioration of their assets over time.

Document Type: Research Article

DOI: https://doi.org/10.2175/193864705783856866

Publication date: 2005-01-01

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