Your equipment operates in constantly changing conditions. Off-the-shelf solutions don't adapt. We build models that understand your equipment and your conditions.
Physics-Informed ML means you don't need massive datasets. We embed engineering knowledge directly into models to work with your existing sensor data.
No vendor lock-in. You receive the complete working product with full source code, documentation, and retraining procedures. Delivered in 12 weeks.
Physics-Informed Machine Learning for Changing Conditions
We solve the 'reality gap' in deep-sea digital twins by embedding physical laws (Navier-Stokes, Hertzian Contact, thermal dynamics) directly into the learning loop. This approach enables accurate predictions even with limited historical failure data.
From cutter-tooth wear estimation in turbid water to mud-pump seal failure prediction. We handle equipment operating in conditions that standard monitoring systems can't predict.
Real-time FEM surrogates for ladder fatigue analysis and multi-physics PINNs for deep-water winch drum integrity monitoring and thermal fade prediction. Specialized solutions for offshore cranes, pipelay tensioners, and heavy lifting systems.
We review your sensor data (open to NDA), confirm physics-based solvability, and provide a Go/No-Go recommendation. Zero cost & no obligation.
Physics-ML model creation with weekly sync meetings. We embed domain knowledge and validate against your operational data.
Deployment to your infrastructure, full documentation, and team training. You own the complete solution.
Your offshore equipment operates in changing, unpredictable conditions
You have specific recurring failure problems
Standard monitoring systems aren't giving you the insights you need
You want to test if this works before investing
Every engagement begins with a 2-week feasibility assessment. We analyze your data, map the physics, and give you a Go/No-Go recommendation for development.
REQUEST FEASIBILITY ASSESSMENT →EA MULTUS B.V.
Serving Netherlands, Norway, and Northern Europe offshore equipment sector
Contact: erduan@eamultus.com