UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Predictive Health Analysis for Future Maintenance Planning in Aging Containership Hull Structures Within Digital Healthcare Engineering Systems

Kim, Hyeong Jin; Xie, Yuheng; Paik, Jeom Kee; (2025) Predictive Health Analysis for Future Maintenance Planning in Aging Containership Hull Structures Within Digital Healthcare Engineering Systems. In: ASME 2025 44th International Conference on Ocean, Offshore and Arctic Engineering. (pp. V001T02A036). ASME: Vancouver, British Columbia, Canada. Green open access

[thumbnail of Predictive Health Analysis for Future Maintenance Planning.pdf]
Preview
Text
Predictive Health Analysis for Future Maintenance Planning.pdf - Accepted Version

Download (1MB) | Preview

Abstract

Aging ships and offshore structures face significant risks from corrosion, fatigue cracking, and mechanical damage, worsened by harsh marine environments and remote operations. Ensuring their safety and sustainability requires innovative solutions, leveraging automated technologies, digital solutions and advanced communication systems. This paper introduces the Digital Healthcare Engineering (DHE) system, a proactive, real-time monitoring and artificial intelligence (AI)-driven framework for managing the structural health of aging vessels and the well-being of seafarers. The AI-enhanced DHE system includes five modules: (1) Module 1: On-site real-time monitoring and digitalization of structural health parameters, (2) Module 2: Transmission of collected data to a land-based analytics center via low Earth orbit (LEO) satellites, (3) Module 3: Advanced analytics and simulations through digital twin technology, (4) Module 4: AI-driven diagnostics with automated maintenance recommendations, and (5) Module 5: Predictive health analysis for future maintenance planning. This study focuses on Module 5, which uses damage data to predict corrosion wastage and fatigue crack propagation, assess structural strength reduction, and optimize maintenance schedules. A case study on a hypothetical 25,800 TEU containership powered by small modular reactors (SMRs) demonstrates the system’s practical benefits in enhancing the safety and operational sustainability.

Type: Proceedings paper
Title: Predictive Health Analysis for Future Maintenance Planning in Aging Containership Hull Structures Within Digital Healthcare Engineering Systems
Event: ASME 2025 44th International Conference on Ocean, Offshore and Arctic Engineering
Dates: 22 Jun 2025 - 27 Jun 2025
ISBN-13: 978-0-7918-8890-2
Open access status: An open access version is available from UCL Discovery
DOI: 10.1115/OMAE2025-157144
Publisher version: https://doi.org/10.1115/omae2025-157144
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: AI-enhanced digital healthcare engineering (DHE) system, aging containership hull structures, digital twins, predictive health analysis, age-related degradation
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering
URI: https://discovery.ucl.ac.uk/id/eprint/10213955
Downloads since deposit
10Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item