Rework during construction is often required due to errors and omissions contained in the engineering documentation that is produced. If errors and omissions go undetected, they may become embedded within the ‘as-built’ documents that are provided to an asset owner at practical completion. In the specific case of instrumentation and control systems (ICSs), errors and omissions are often found in as-builts. This adversely impacts productivity and safety during the operations and maintenance process, as information is not readily available. In the case of liquefied natural gas (LNG) plants, for example, shutdown periods may have to be extended, which can jeopardise the production and supply of gas and therefore place a strain on energy markets. The research presented in this paper aims to address this issue by proposing a novel digital system information model which can be used to improve the robustness of an LNG operator’s asset information management system. The creation of a digital model provides a platform for future-proofing LNG assets and minimising the duration of shutdown periods. The research provides the LNG sector with an innovative solution for digitising their ICSs so that assets can efficiently and effectively be maintained and operated.
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19 March 2020
Research Article|
July 19 2019
Digital system information model: future-proofing asset information in LNG plants Available to Purchase
Peter E. D. Love, D.Sc., PhD
;
School of Civil and Mechanical Engineering, Curtin University, Perth, Australia
(corresponding author: p.love@curtin.edu.au)
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Jingyang Zhou, PhD
;
Jingyang Zhou, PhD
Senior Research Fellow
School of Civil and Mechanical Engineering, Curtin University, Perth, Australia
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Jane Matthews, PhD
;
Jane Matthews, PhD
Professor
School of Architecture and Building, Deakin University, VIC, Australia
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Giorgio Locatelli, PhD
Giorgio Locatelli, PhD
Professor
School of Civil Engineering, University of Leeds, Leeds, UK
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(corresponding author: p.love@curtin.edu.au)
Publisher: Emerald Publishing
Received:
February 10 2019
Accepted:
July 04 2019
Online ISSN: 2053-0250
Print ISSN: 2053-0242
ICE Publishing: All rights reserved
2020
Infrastructure Asset Management (2020) 7 (1): 46–59.
Article history
Received:
February 10 2019
Accepted:
July 04 2019
Citation
Love PED, Zhou J, Matthews J, Locatelli G (2020), "Digital system information model: future-proofing asset information in LNG plants". Infrastructure Asset Management, Vol. 7 No. 1 pp. 46–59, doi: https://doi.org/10.1680/jinam.19.00050
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