Live Sensor Based Risk Based Inspection Planning for Floating Offshore Structures

Abstract Risk Based Inspection (RBI) planning for offshore floating structures optimizes inspections and maintenance costs by managing risks related to degradation. This paper presents an innovative approach integrating live sensor data and digital twin technology into the RBI planning process for Floating Production Storage and Offloading (FPSO) units. Developed by DNV and SBM Offshore, the methodology covers key degradation mechanisms such as fatigue, corrosion, and coating degradation. Real-time operational data dynamically updates inspection plans, ensuring timely identification of potential issues and optimized maintenance activities. Endorsed by DNV, ABS and BV class societies, this approach improves the structural integrity and operational efficiency of FPSO units and is adaptable to other offshore structures. Future improvements could include enhanced data analytics and machine learning algorithms for predictive maintenance.

Authors

Publication Details

Journal
Offshore Technology Conference
Published
2025-04-28
DOI
https://doi.org/10.4043/35609-ms
Primary Topic
Structural Integrity and Reliability Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Live Sensor Based Risk Based Inspection Planning for Floating Offshore Structures

Stefan Marion, François-Xavier Siréta, Frode Bratbak, Giles H. Brown et al.
Offshore Technology Conference
Structural Integrity and Reliability Analysis
article

Live Sensor Based Risk Based Inspection Planning for Floating Offshore Structures

Stefan Marion, François-Xavier Siréta, Frode Bratbak, Giles H. Brown, Amine El Gharbaoui, Anja Siems
article en

Abstract

Abstract Risk Based Inspection (RBI) planning for offshore floating structures optimizes inspections and maintenance costs by managing risks related to degradation. This paper presents an innovative approach integrating live sensor data and digital twin technology into the RBI planning process for Floating Production Storage and Offloading (FPSO) units. Developed by DNV and SBM Offshore, the methodology covers key degradation mechanisms such as fatigue, corrosion, and coating degradation. Real-time operational data dynamically updates inspection plans, ensuring timely identification of potential issues and optimized maintenance activities. Endorsed by DNV, ABS and BV class societies, this approach improves the structural integrity and operational efficiency of FPSO units and is adaptable to other offshore structures. Future improvements could include enhanced data analytics and machine learning algorithms for predictive maintenance.

Offshore Technology Conference
Openalex Percentile: Top 82%
Structural Integrity and Reliability Analysis
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