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Risk-based inspection on highway assets with category 2 defects

Risk-based inspection on highway assets with category 2 defects

Ekpiwhre, E.O., Tee, K. F., Aghagba, S. A.. and Bishop, K. (2016) Risk-based inspection on highway assets with category 2 defects. International Journal of Safety and Security Engineering, 6 (2). pp. 372-382. ISSN 2041-9031 (Print), 2041-904X (Online) (doi:10.2495/SAFE-V6-N2-372-382)

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Abstract

This paper presents a study piloted on highway assets Category 2 defects. Imminent hazards on high-way road networks are significantly accelerated by structural deterioration of highway infrastructures. The inspection and maintenance strategy for highway infrastructure requires continuous improvements to reduce high occurrence of defective highway assets. Combined risk-based inspection (RBI) and stochastic (STOC) techniques is considered in this investigation to give an in-depth understanding of highway asset maintenance response. Appropriate data information is extracted from Network Maintenance Management System and complementary information elicited from maintenance experts as well as recommended standards. Safety inspections piloted within the period of 5 years is evaluated using the projected RBI-STOC approach. The RBI incorporates the consequences and likelihood of the defects and the combined STOC techniques utilised defines the actual maintenance interval operated. The RBI-STOC approach proposes reclassification of highway asset defect repair intervals, appropriate maintenance task response and efficient maintenance prioritisation of highway assets in equivalence with contribution to system average mean time to repair and downtime.

Item Type: Article
Uncontrolled Keywords: Category 2 defects, Probability distribution, Risk-based highway assets management, Risk based inspections, Safety inspection
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Faculty / Department / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Department of Engineering Science
Last Modified: 31 Aug 2017 10:55
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/17442

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