Our Solutions · Pillar 04
Powered by ECON Tech · Applied AI for Industry
Mathematical models meet machine learning — empowering industrial teams to make faster, smarter, data-driven decisions that optimize processes, predict failures, and reduce costs in real time.
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Smart Metrix is ECON Tech's applied AI platform — built specifically for industrial environments. Unlike generic data tools, every Smart Metrix model is a hybrid of machine learning and process-specific mathematical models developed with domain engineers who know your industry.
The result: AI that doesn't just find patterns in data — it understands why they exist. Models that generalize correctly to new operating conditions. Predictions that plant operators can trust and act on. Decision support that empowers people, not replaces them.
Explore Our AI Solutions →Neural networks, regression models, and pattern recognition trained on your historical process data
Physics-based models and expert process knowledge that constrain and guide the AI — ensuring predictions make physical sense
Data-driven decisions that empower your people and optimize your processes — in real time
Smart Metrix models are deployed across four high-value domains where AI consistently delivers measurable ROI in industrial operations.
Closed-loop AI optimization that continuously tunes process variables — reducing variability, improving yield, and cutting energy consumption.
Machine health monitoring that detects anomalous patterns and forecasts failures days in advance — before they become costly breakdowns.
ML models that discover hidden process factors affecting final product quality — enabling proactive adjustments before defects occur.
AI-driven energy management that models consumption patterns, optimizes demand, and tracks CO₂ emissions in real time — turning sustainability targets into measurable, daily operational results.
Industry-specific AI models — each one a hybrid of machine learning and process engineering expertise, deployed inside your existing SCADA and MES environment.
Non-Linear Model Predictive Control (NMPC) that combines AI with physics-based process models for closed-loop optimization. Continuously calculates the optimal set of manipulated variables to keep your process at peak performance — automatically.
AI-based asset health monitoring that learns the normal behavior of your equipment and detects anomalous patterns that precede failures. Forecast breakdowns days in advance — schedule maintenance on your terms, not the machine's.
Machine learning models combined with digital process models that identify the hidden process variables driving quality outcomes. Predict final product quality in real time during production — adjust before defects occur, not after.
An AI layer on top of energy monitoring that models how production decisions affect energy consumption — today and tomorrow. Optimize demand, reduce peak charges, and understand the true energy cost of every product, shift, and machine state.
Intelligent temperature and heat prediction for steelmaking and metallurgical processes. AutoHeat models the thermal state of liquid metal across each stage — predicting tap temperature with high accuracy and recommending optimal energy inputs to hit target temperature first time.
AI-powered alloy addition optimization for secondary metallurgy. Calculates the precise quantity and sequence of additions — aluminum, calcium, ferroalloys — to hit chemical composition targets at minimum cost, accounting for recovery rates and bath conditions in real time.
Intelligent optimization of vacuum degassing processes (VD/VOD/RH). VacuumAI models the degassing kinetics using a hybrid ML + thermodynamic approach — predicting final hydrogen and nitrogen content and recommending optimal vacuum cycle parameters to achieve target cleanliness.
Real-time prediction of hydrogen content in liquid steel throughout the steelmaking process. H2Predictor uses a thermodynamic model combined with machine learning to estimate hydrogen pickup and predict the result after degassing — enabling operators to take proactive action before casting.
AI-powered real-time monitoring and prediction of strand geometry and shape in continuous casting. ShapeSense correlates casting machine parameters with product geometry — detecting shape deviations as they develop and recommending corrective actions before they become rejects.
Every Smart Metrix model combines machine learning with mathematical process models. Your engineers understand why the AI makes each recommendation — and can trust the output.
We don't apply general-purpose AI tools to industrial problems. Smart Metrix models are built with metallurgical, chemical, and mechanical process knowledge baked in from day one.
Smart Metrix is decision-support AI. Our models surface insights, recommend actions, and explain predictions — so your operators and engineers make better decisions, faster.
Smart Metrix runs inside your existing SCADA, MES, and control systems — not as an external dashboard. AI recommendations appear where operators already work, in context.
Book a free 45-minute consultation with one of our AI & analytics engineers. We'll assess your process data environment and outline a Smart Metrix implementation path — at no cost.