The data collected by sensors installed on structures, machinery and mechanical systems in the offshore industry hold huge potential in terms of structural health monitoring, performance evaluation and real-time integrity management. However, the huge amount and complexity of the data acquired pose great challenges for data processing and analysis.
DNV GL wishes to bring together key industry stakeholders and data specialists to identify and address the unique challenges associated with Big Data and adaptive, data-driven offshore asset management and condition monitoring. The focus of this joint industry project will be on machine learning tools and their potential positive impact on the offshore industry.
A guideline for state-of-the-art implementation of machine learning in data management for offshore assets.
- Accurate fatigue and corrosion evaluation
- Predictive maintenance
- Early damage detection
- Structural system identification
- Reduced inspection costs and downtime