Materials Degradation AI
AI-Powered Corrosion & Degradation Prediction for Refinery Equipment
Predict corrosion rates, remaining useful life, and inspection intervals for pressure vessels, piping, and heat exchangers — using AI that learns from your actual inspection history rather than generic industry tables.
Corrosion Intelligence That Learns From Your Plant
Generic corrosion allowance tables from API 510/570 are conservative by design — they don’t know your specific crude slate, process chemistry, or inspection history. Materials Degradation AI builds facility-specific corrosion models by training on your actual thickness measurement data, inspection records, and process conditions — delivering predictions that are accurate to your plant, not an industry average.
Corrosion Rate Modeling
Machine learning corrosion rate models trained on your plant’s actual inspection data. Accounts for process chemistry variations, seasonal crude changes, and inhibitor effectiveness over time.
Remaining Life Prediction
Calculates remaining useful life for individual equipment items based on actual measured degradation trends — not conservative code minimums. Supports API 510/570/653 fitness-for-service assessments.
Inspection Interval Optimization
Risk-based inspection interval recommendations that satisfy API 580/581 requirements while reducing unnecessary inspections on low-risk, stable equipment.
Damage Mechanism Mapping
Identifies active and potential damage mechanisms for each equipment item based on process conditions, materials of construction, and industry damage mechanism databases (API RP 571).
Thickness Alert System
Automated alerts when measured thickness approaches calculated minimum — with enough lead time for scheduled repair vs. emergency shutdown. Integrates with your CMMS work order system.
MI Program Dashboard
Full visibility into your mechanical integrity program health — overdue inspections, approaching minimum thickness, high-risk equipment, and upcoming budget requirements for the next inspection cycle.
What Materials Degradation AI Tracks
- High-temperature hydrogen attack (HTHA) — Nelson curve monitoring for high-pressure circuits
- Sulfidic corrosion — crude unit and vacuum pipework at elevated temperatures
- Amine stress corrosion cracking — treating unit equipment inspection management
- Chloride stress corrosion cracking — austenitic stainless in wet environments
- CO2 and H2S corrosion — sour service equipment under NACE MR0175
- Erosion-corrosion — high-velocity services and catalyst-bearing streams in FCC units
Mechanical Integrity Is the Most-Cited PSM Element
OSHA 29 CFR 1910.119(j) — Mechanical Integrity — consistently generates the highest number of citations in PSM inspections. The most common finding: inspection intervals that can’t be justified, or thickness records that don’t support the continued service of equipment.
Materials Degradation AI doesn’t just predict corrosion. It builds the documented, justified, traceable MI program records that turn a potential citation into a demonstration of best practice.
Stop managing mechanical integrity on spreadsheets.
Materials Degradation AI is in development. Mechanical integrity engineers, inspection coordinators, and PSM managers can contact us to discuss early access and data integration requirements.