The RCM and AHP hybrid model for road network maintenance prioritization
Author(s): |
Ena E. Orugbo
Babakalli M. Alkali Anjali DeSilva David K. Harrison |
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Medium: | journal article |
Language(s): | English |
Published in: | The Baltic Journal of Road and Bridge Engineering, June 2015, n. 2, v. 10 |
Page(s): | 182-190 |
DOI: | 10.3846/bjrbe.2015.23 |
Abstract: |
Category1 defects such as potholes significantly accelerate structural deterioration and pose imminent hazards on trunk road networks. Frequent occurrences of category1 defects have increased service disruptions on trunk road networks. Road maintenance agencies are now required to effectively prioritize trunk road network category1 defects maintenance works. However, existing road maintenance prioritization methods such as value engineering and traditional expert judgment methods have limitations. Value engineering is resource and time intensive thus best suited for project level prioritization and traditional expert judgments are subjective and lack audit trails. In an attempt to address the limitations of above methods, this study presents a Reliability Centered Maintenance and Analytical Hierarchy Process based hybrid model for trunk road network maintenance prioritization. The proposed hybrid model is used to establish failure diagnostic and Multi-criteria Decision Making respectively. As a case study, the hybrid model is implemented on a trunk road network in the United Kingdom. Relevant category1 defect failure information linked to trunk road network subassets are extracted from databases and relevant information elicited from maintenance experts. The criticality analysis results presented show the risk priority numbers of category1 defect related failures and cost effective preventative maintenance tasks are proposed. The Analytical Hierarchy Process results are used to address the complex prioritization process. The proposed hybrid model facilitates a systematic prioritization of a large number of trunk road network category1 defect failure maintenance activities consistently. |
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data sheet - Reference-ID
10084662 - Published on:
09/10/2018 - Last updated on:
09/10/2018