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Risk-based and predictive maintenance planning of engineering infrastructure: existing quantitative techniques and future directions

Citation

Abbassi, R and Arzaghi, E and Yazdi, M and Aryai, V and Garaniya, V and Rahnamayiezekavat, P, Risk-based and predictive maintenance planning of engineering infrastructure: existing quantitative techniques and future directions, Process Safety and Environmental Protection, 165 pp. 776-790. ISSN 0957-5820 (2022) [Refereed Article]

Copyright Statement

2022 Institution of Chemical Engineers.

DOI: doi:10.1016/j.psep.2022.07.046

Abstract

Engineering infrastructure incorporate complex systems, hazardous materials and often operated by human beings, making them prone to catastrophic accidents. Continuously improving system safety of the facilities and their operations requires a well-established asset management practices. The history of hazardous events in some domains such as process facilities suggest that many accidents have occurred due to ineffective maintenance planning strategies. Thus, to ensure an acceptable level of system safety and availability, it is essential to adopt optimal programs and practical procedures in maintenance planning engineering assets. The lessons learnt from previous accidents have helped operators, classification societies and regulators to develop viable standards and guidelines for employing quantitative methods in Operation and Maintenance (O&M) planning. The current work aims to present the existing attempts and identify the gaps, needs, and challenges of maintenance planning in engineering facilities. It then integrates the empirical and theoretical conclusions, highlighting the capabilities and drawbacks of the state-of-the-arts and explaining research opportunities and challenges. The decision-makers, operators, and managers in engineering infrastructure can exploit the present work from theoretical and practical perspectives.

Item Details

Item Type:Refereed Article
Keywords:maintenance operations, process industry, risk analysis, system safety, decision-making
Research Division:Engineering
Research Group:Maritime engineering
Research Field:Marine engineering
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Abbassi, R (Dr Rouzbeh Abbassi)
UTAS Author:Arzaghi, E (Dr Ehsan Arzaghi)
UTAS Author:Aryai, V (Dr Vahid Aryai)
UTAS Author:Garaniya, V (Associate Professor Vikram Garaniya)
ID Code:154239
Year Published:2022
Web of Science® Times Cited:2
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2022-11-15
Last Modified:2022-12-08
Downloads:0

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