CorrosionVision

Anticipate corrosion risks prior to manufacturing through Artificial Intelligence and digital twins. By leveraging historical test data, CorrosionVision identifies critical areas, reduces physical prototyping, and accelerates design and validation processes.

Corrosion Prediction via Digital Twin and AI

Physical corrosion testing often requires prototypes and extended evaluation periods, increasing both time and costs during design and validation.

CorrosionVision utilizes predictive models and digital twins to forecast corrosion behavior before manufacturing a new part, enabling engineering teams to target physical testing where it is most critical.

From Historical Testing to Predictive Insights

The solution integrates each component’s 3D model with technical documentation, imagery, and historical test results to identify key performance patterns related to corrosion behavior.

The output is projected directly onto the model through a visual risk map, allowing teams to:

Identify high-probability corrosion zones.
Detect design flaws or critical areas requiring revision.
Reduce physical prototyping requirements and focus testing on high-risk areas.
Streamline validation timeframes and operational costs.
Capitalize on historical test data for future evaluations.
Accelerate the development and validation cycle of new designs.

Implementation can begin with a Proof of Concept (PoC) on a specific component and scale progressively across new product lines.

CorrosionVision brings predictive intelligence into the engineering workflow to mitigate risks prior to manufacturing and decrease reliance on physical testing throughout development.