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Type: Journal article
Title: Ref: EATJ-D-19-00148 - prediction of remaining useful life of naval structures using a covariate-base hazard model
Author: Gorjian, N.
Rameezdeen, R.
Gorjian Jolfaei, N.
Chow, C.
Jin, B.
Citation: Australian Journal of Structural Engineering, 2020; 21(3):208-217
Publisher: Taylor & Francis
Issue Date: 2020
ISSN: 1328-7982
Statement of
Nima Gorjian, Rameez Rameezdeen, Neda Gorjian Jolfaei, Chris Chow and Bo Jin
Abstract: Maintenance cost effectiveness, usability, reliability, safety and the remaining life of engineering assets are key factors for asset management decision-making. Management of an individual or groups of structures requires a systematic approach such that reliability and condition could be maintained within both budget and resource availability. This means maintenance and inspection activities should be planned optimally to ensure operation of structures is safe and economical. Hence, methodologies surrounding the modelling and analysis of data representing the time until the occurrence of an event become crucial to asset managers. This study uses the Explicit Hazard Model (EHM) to demonstrate the modelling of hazard, reliability and Remaining Useful Life (RUL) prediction of naval structures using a quasi-experiment. Amongst the existing covariate-based hazard models, EHM is selected as this model jointly utilises three available asset health data including failure event data, condition data and operating environment data in the modelling effort which provides effective outcomes. The hazard and reliability estimate of these structures using EHM are compared to the traditional Weibull model. Results show that the individual’s hazard and reliability closely follow the population’s hazard and reliability. The predicted RUL of these structures using EHM is compared to the actual RUL. Results validate the performance and accuracy of this model in reliability and RUL calculation of engineering assets.
Keywords: Prognostics; remaining useful life; hazard function; reliability; covariate; structural assets
Description: Published online: 30 Apr 2020.
Rights: © 2020 Engineers Australia
RMID: 1000021158
DOI: 10.1080/13287982.2020.1758375
Appears in Collections:Chemical Engineering publications

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