Optimising Maintenance Planning and Integrity in Offshore Facilities Using Machine Learning and Design Science: A Predictive Approach DOI Creative Commons
Marina Polonia Rios, Rodrigo Goyannes Gusm�ão Caiado, Yiselis Rodríguez Vignon

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(23), P. 10902 - 10902

Published: Nov. 25, 2024

This research presents an innovative solution to optimise maintenance planning and integrity in offshore facilities, specifically regarding corrosion management. The study introduces a prototype for on oil platforms, developed through the Design Science Research (DSR) methodology. Using 3D CAD/CAE model, integrates machine learning models predict progression, essential effective strategies. Key components include damage assessment, regulatory compliance, asset criticality, resource optimisation, collectively enabling precise efficient anti-corrosion plans. Case studies gas platforms validate practical application of this methodology, demonstrating reduced costs, lower risks associated with corrosion, enhanced efficiency. Additionally, opens pathways future advancements, such as integrating IoT technologies real-time data collection applying deep improve predictive accuracy. These potential extensions aim evolve system into more adaptable powerful tool industrial maintenance, applicability beyond other environments, including onshore facilities.

Language: Английский

Towards Good Practice In Engaging Users In Evaluation Of Computer Model Software: Introducing The Critical Appraisal Approach (CAA) DOI Creative Commons
Caroline Rosello, Joseph H. A. Guillaume, Peter Taylor

et al.

Environmental Modelling & Software, Journal Year: 2025, Volume and Issue: unknown, P. 106469 - 106469

Published: April 1, 2025

Language: Английский

Citations

0
Optimising Maintenance Planning and Integrity in Offshore Facilities Using Machine Learning and Design Science: A Predictive Approach DOI Creative Commons
Marina Polonia Rios, Rodrigo Goyannes Gusm�ão Caiado, Yiselis Rodríguez Vignon

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(23), P. 10902 - 10902

Published: Nov. 25, 2024

This research presents an innovative solution to optimise maintenance planning and integrity in offshore facilities, specifically regarding corrosion management. The study introduces a prototype for on oil platforms, developed through the Design Science Research (DSR) methodology. Using 3D CAD/CAE model, integrates machine learning models predict progression, essential effective strategies. Key components include damage assessment, regulatory compliance, asset criticality, resource optimisation, collectively enabling precise efficient anti-corrosion plans. Case studies gas platforms validate practical application of this methodology, demonstrating reduced costs, lower risks associated with corrosion, enhanced efficiency. Additionally, opens pathways future advancements, such as integrating IoT technologies real-time data collection applying deep improve predictive accuracy. These potential extensions aim evolve system into more adaptable powerful tool industrial maintenance, applicability beyond other environments, including onshore facilities.

Language: Английский

Citations

0