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    Evaluation of Maintenance Decisions to Optimize Navigable Inland Waterway Lock Conditions

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    JITSE4.ISENG-2435.pdf (1021.Kb)
    Date
    2024
    Author
    Bukola Oni
    Katherine Madson
    Cameron MacKenzie
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    Abstract
    An investment gap in America’s inland waterways (IWWs) has been fueled by decades of low investments, which has negatively impacted the reliability of the waterway’s locks. US IWWs, which transport commodities and support the nation’s economy, are aging rapidly, exacerbated by decades of underinvestment. Many of these infrastructure systems now need to address a substantial maintenance backlog to increase their life span and improve functionality. Optimizing the decision-making process for effective and efficient planning and policymaking is essential to perform this requisite maintenance. Recognizing the robust scope of this maintenance, long-term maintenance strategies are needed in order to optimize investments across these waterway systems to improve their condition. Currently, limited research exists on decision making on IWW transportation assets, and there is a lack of requisite guidance for optimally performing maintenance activities on a single lock on the IWW system. Therefore, this study focuses on developing a decision-making model that considers several uncertainties toward optimizing the maintenance of locks on IWWs. The model evaluates maintenance decisions on an IWW lock using data obtained via expert elicitation. Results obtained from compiling the influence diagram (ID) and performing sensitivity analysis on the model support the need for periodic inspection of the locks to assess the condition before making any maintenance decision. The study presents a novel approach for enhancing maintenance decisions on IWW assets by considering key uncertainties beyond the physical condition of the assets. This research sets the stage for further studies on how fiscal constraints affect infrastructure asset maintenance decisions.
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    http://yetl.yabesh.ir/yetl1/handle/yetl/4299107
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