Sindi, Abdulaziz;
Kim, Hyeong Jin;
Yang, Young Jun;
Thomas, Giles;
Paik, Jeom Kee;
(2024)
Advancing digital healthcare engineering for aging ships and offshore structures: an in-depth review and feasibility analysis.
Data-Centric Engineering
, 5
, Article e18. 10.1017/dce.2024.14.
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Abstract
Aging ships and offshore structures face harsh environmental and operational conditions in remote areas, leading to age-related damages such as corrosion wastage, fatigue cracking, and mechanical denting. These deteriorations, if left unattended, can escalate into catastrophic failures, causing casualties, property damage, and marine pollution. Hence, ensuring the safety and integrity of aging ships and offshore structures is paramount and achievable through innovative healthcare schemes. One such paradigm, digital healthcare engineering (DHE), initially introduced by the final coauthor, aims at providing lifetime healthcare for engineered structures, infrastructure, and individuals (e.g., seafarers) by harnessing advancements in digitalization and communication technologies. The DHE framework comprises five interconnected modules: on-site health parameter monitoring, data transmission to analytics centers, data analytics, simulation and visualization via digital twins, artificial intelligence-driven diagnosis and remedial planning using machine and deep learning, and predictive health condition analysis for future maintenance. This article surveys recent technological advancements pertinent to each DHE module, with a focus on its application to aging ships and offshore structures. The primary objectives include identifying cost-effective and accurate techniques to establish a DHE system for lifetime healthcare of aging ships and offshore structures—a project currently in progress by the authors.
| Type: | Article |
|---|---|
| Title: | Advancing digital healthcare engineering for aging ships and offshore structures: an in-depth review and feasibility analysis |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1017/dce.2024.14 |
| Publisher version: | http://dx.doi.org/10.1017/dce.2024.14 |
| Language: | English |
| Additional information: | This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. Copyright © The Author(s), 2024. Published by Cambridge University Press |
| Keywords: | aging ships, aging offshore structures, digital healthcare engineering, AI-driven diagnosis with machine learning, data analysis, digital twins |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10193058 |
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