Custom equipment. No off-the-shelf solution. Plan maintenance before downtime hits.
Predict wear, loads & operating modes for custom offshore and heavy industrial equipment.
Our engineering physics-based models leverage your existing data to provide actionable
health insights.
We verify if your data is ready for
Physics-ML. No cost, expert review.
Why EA
Multus for Predictive Maintenance?
Tailored to Your
Equipment
Custom offshore and heavy industrial assets require custom
solutions. We deliver ML models specific to your equipment's physics and operational conditions.
Works with Sparse Data
Physics-Informed ML means you don't need massive datasets. We
embed engineering knowledge directly into models to work with your existing sensor data.
100% Code Ownership
No vendor lock-in. You receive the complete working product with
full source code, documentation, and retraining procedures. Delivered in 12 weeks.
Technical Insights & Engineering Solutions
Physics-Informed Machine Learning for Custom
Assets
Physics-Informed Machine
Learning (PIML)
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.
Predictive Maintenance for
Custom Assets
From cutter-tooth wear estimation in turbid water to mud-pump seal failure state
segmentation using MS-TCN architectures. We handle non-standard equipment where OEM monitoring doesn't provide
the insights you need.
Anomaly detection for variable operational conditions
Virtual sensing for unmeasurable parameters
Remaining Useful Life (RUL) estimation
Failure prediction before critical events
Structural Health & Heavy
Lifting
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.
Our
Process
Step 1: Free Data
Feasibility Check (2 Weeks)
We review your sensor data (open to NDA), confirm physics-based
solvability, and provide a Go/No-Go recommendation. Zero cost & no obligation.
Step 2: Model
Development (8 Weeks)
Physics-ML model creation with weekly sync meetings. We embed
domain knowledge and validate against your operational data.
Step 3: Integration &
Handoff (2 Weeks)
Deployment to your infrastructure, full documentation, and team
training. You own the complete solution.
Are You
Ready to Reduce Downtime?
✓
Custom equipment where OEM monitoring doesn't give the needed insights
You want a free expert technical assessment to de-risk the solution
Don't start with a contract.
Start with proof.
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.