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Risk-based asset integrity indicators

Citation

Hassan, J and Khan, FI, Risk-based asset integrity indicators, Journal of Loss Prevention in the Process Industries, 25, (3) pp. 544-554. ISSN 0950-4230 (2012) [Refereed Article]

DOI: doi:10.1016/j.jlp.2011.12.011

Abstract

Asset integrity is a major concern of process facilities. Monitoring and assessing asset integrity is a challenging task due to the involvement of various dependent and independent parameters. Monitoring and assessing asset performance through indicators is one easily doable option. Lack of an appropriate set of indicators quantification technique and measurement cohesion limits the use of an indicator system. To overcome this, in the present paper a hierarchical framework is prepared to for asset integrity monitoring and assessment. The hierarchical structure is used to characterize the asset and relate it to an organization's strategic goal. The hierarchical structure is based on three major areas of asset integrity, namely: mechanical, personnel and process. Further, it provides an opportunity to follow a bottom-up perspective for identifying multilevel level indicators. The proposed approach uses a risk metric to classify asset integrity through the integration of leading and lagging indicators' outcome. The analytical hierarchy process is used to determine the weights, or for prioritization of each level indicator and for the aggregation of the indicators to classify risk. To test the proposed model, a benchmark study is conducted. The estimated asset integrity index value provides a tangible asset's performance index. The system of indicators and their integration provide a comprehensive view of the process facility's status and also reveal which sections of the facility need more attention. © 2012 Elsevier Ltd.

Item Details

Item Type:Refereed Article
Keywords:Asset integrity; Hierarchical structure; Lagging indicator; Leading indicator; Risk index; Sensitivity; Asset integrity; Hierarchical structures; Lagging indicators; Leading indicators; Risk index; Sensitivity; Industrial engineering; Gages
Research Division:Engineering
Research Group:Maritime Engineering
Research Field:Ocean Engineering
Objective Division:Energy
Objective Group:Renewable Energy
Objective Field:Renewable Energy not elsewhere classified
Author:Khan, FI (Professor Faisal Khan)
ID Code:84992
Year Published:2012
Web of Science® Times Cited:14
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2013-06-11
Last Modified:2017-11-03
Downloads:0

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