%0 Journal Article %1 james_geisbush_2024_13691676 %A Geisbush, James %A Ariaratnam, Samuel T. %D 2024 %J Global Journal of Engineering and Technology Advances %K Reliability-centered maintenance %N 2 %P 069–080 %R 10.30574/gjeta.2024.19.2.0047 %T Determining a Reliability Centered Maintenance (RCM) analysis model for large diameter prestressed concrete water pipelines %U https://gjeta.com/content/determining-reliability-centered-maintenance-rcm-analysis-model-large-diameter-prestressed %V 19 %X Which maintenance task to perform on an asset is generally known but the schedule of when to perform the task may not be well defined. If the task is performed early, while it may benefit the asset, it may also be expending resources that could be better used elsewhere. If the task is not performed soon enough, the asset may fail, or the asset may require more extensive maintenance be performed. Reliability Centered Maintenance (RCM) is an analysis process used to determine the most effective maintenance strategies. RCM analysis can help an agency establish the most cost effective maintenance strategies for an asset and help establish the best schedule for implementing those strategies. The ultimate goal of an RCM is to determine the required function of an asset with the required reliability at the lowest operation and maintenance costs by identifying revealing indicators of potential failures to establish a condition based strategy; essentially, predicting failures and identifying procedures to minimize the risk of the failure. This paper reviews potential models for predicting the progression of distress of prestressed concrete pipe segments for use in an RCM analysis and proposes a regression model operators can use to forecast when to perform maintenance activities. The paper further considers the condition of the drinking water infrastructure in the United States, developing the case for evaluating predictive models to forecast when a pipeline may reach a specified limit state. The results of this study suggest that RCM analyses for large diameter water pipelines can improve reliability, reduce maintenance costs, and extend the useful life of a pipeline regardless of age or material. Further, using a regression style model with gathered data can be used to forecast when specific maintenance thresholds may be reached, prompting predictive maintenance actions.

@article{james_geisbush_2024_13691676, abstract = {Which maintenance task to perform on an asset is generally known but the schedule of when to perform the task may not be well defined. If the task is performed early, while it may benefit the asset, it may also be expending resources that could be better used elsewhere. If the task is not performed soon enough, the asset may fail, or the asset may require more extensive maintenance be performed. Reliability Centered Maintenance (RCM) is an analysis process used to determine the most effective maintenance strategies. RCM analysis can help an agency establish the most cost effective maintenance strategies for an asset and help establish the best schedule for implementing those strategies. The ultimate goal of an RCM is to determine the required function of an asset with the required reliability at the lowest operation and maintenance costs by identifying revealing indicators of potential failures to establish a condition based strategy; essentially, predicting failures and identifying procedures to minimize the risk of the failure. This paper reviews potential models for predicting the progression of distress of prestressed concrete pipe segments for use in an RCM analysis and proposes a regression model operators can use to forecast when to perform maintenance activities. The paper further considers the condition of the drinking water infrastructure in the United States, developing the case for evaluating predictive models to forecast when a pipeline may reach a specified limit state. The results of this study suggest that RCM analyses for large diameter water pipelines can improve reliability, reduce maintenance costs, and extend the useful life of a pipeline regardless of age or material. Further, using a regression style model with gathered data can be used to forecast when specific maintenance thresholds may be reached, prompting predictive maintenance actions.}, added-at = {2024-10-02T17:16:07.000+0200}, author = {Geisbush, James and Ariaratnam, Samuel T.}, biburl = {https://www.bibsonomy.org/bibtex/21ffcbe1c9a6b8f7c9c8aae87f09c604c/gjetajournal}, doi = {10.30574/gjeta.2024.19.2.0047}, interhash = {35eed20a2085a5b0d5be6f893f4e99b9}, intrahash = {1ffcbe1c9a6b8f7c9c8aae87f09c604c}, issn = {2582-5003}, journal = {{Global Journal of Engineering and Technology Advances}}, keywords = {Reliability-centered maintenance}, month = sep, number = 2, pages = {069–080}, timestamp = {2024-10-02T17:16:07.000+0200}, title = {Determining a Reliability Centered Maintenance (RCM) analysis model for large diameter prestressed concrete water pipelines}, url = {https://gjeta.com/content/determining-reliability-centered-maintenance-rcm-analysis-model-large-diameter-prestressed}, volume = 19, year = 2024 }