Rapid Metal Corrosion Detection with Vision-Based AI for Industrial Alloys

Quick Summary

Challenge

Field technicians relied on lab testing to detect corrosion in metal tanks. This meant a week-long delay that slowed maintenance and risked costly failures.

Solution

Tatras Data built a deep learning solution that analyzes images of metal coupons from customer sites and provides instant corrosion classification with actionable insights.

Result

98% accuracy
7-day inspection process → 7 minutes.

Tech Stack

AI: Transfer learning on vision models Image-based risk scoring | ML: CNNs for corrosion classification Score generation algorithm | Data & Retrieval: On-site image capture and upload | Dev: TensorFlow PyTorch Keras OpenCV | Ops: Mobile app integration Edge-ready inference | Security: Local device processing Data sanitization pipeline

The Challenge

Tank corrosion often hides in plain sight. Until it becomes a problem.

For a global water treatment provider, inspecting RO tanks meant retrieving metal coupons from field sites, sending them to a lab, and waiting 7+ days for results. During that time, degradation could spread unnoticed.

Worse, missed corrosion cues led to reactive fixes and unplanned downtime.

The client needed an AI system that could match lab precision from a single image.

A Day in the Life: Before Our Solution

Every inspection started with a field visit.

Technicians would extract metal coupons, note basic visual observations, and send the samples for lab testing. Results took a week. Sometimes longer. Meanwhile, the tank continued running, even if corrosion was worsening.

If an issue was confirmed, another team would be dispatched to take corrective action. Delays mounted. Maintenance became reactionary. Clients lost confidence.

All because no one could act fast.

Pain Points:

Lab-based detection delayed responses by 7+ days
Field teams had no real-time decision support
Subtle corrosion cues were often missed visually
High cost of manual inspections and repeat site visits
Scaling the process across geographies was impractical

Solution

1. Core Innovation

Tatras Data built a mobile-compatible, vision-based system that diagnoses corrosion with AI:

Collected diverse images across metal types and corrosion forms
Used pre-trained image recognition models with transfer learning for accuracy
Created a custom algorithm that assigns corrosion risk scores based on visual patterns
Linked visual indicators (e.g. color, pitting, spread) to severity levels
Delivered rapid results through an edge-deployable mobile interface

2. Key Features

98% accuracy in metal alloy corrosion detection
Visual risk scoring aligned with lab-grade standards
Image-to-insight pipeline optimized for mobile capture
End-to-end diagnosis in under 7 minutes
Interpretable visual reports for field and central teams

3. Workflow Integration

Technicians now capture images on-site using a mobile app.

Within minutes, the system returns coupon composition, corrosion severity, and action recommendations.

Outcomes

✅ 7-day inspection cycle reduced to 7 minutes

📸 Field teams empowered with real-time insights

🧠 AI models continuously improve with labeled data

💰 Cost and time savings at scale for preventive maintenance

🏭 Improved SLA performance with proactive corrosion detection