AI System Advisor for Steel Operations
SteelSense™ is a next-generation industrial AI platform that transforms steel operations from experience-driven to data-driven and predictive. It delivers a unified intelligence layer across furnaces, combustion systems, and rolling processes to improve efficiency, reliability, and decarbonization.
Why SteelSense™?
- AI-native platform that predicts, optimizes, and continuously learns from steel plant operations.
- Real-time visibility into energy performance, process efficiency, and carbon emissions.
- Proactive anomaly detection to identify fuel inefficiencies, temperature drift, and losses.
- Carbon-verified, audit-ready data supporting CBAM, ESG reporting, and regulatory governance.
- What-if simulation and digital twins to evaluate operational changes and decarbonization.
- Modular, industry-ready deployment integrating seamlessly with PLC/DCS, ERP, and systems.
How it works
SteelSense™ converts plant data into verified actions through analytics, advisory intelligence, and compliance layers.
- Data Acquisition & Integration: Collects real-time operational data from PLC, DCS, sensors, MES, ERP, energy meters, and laboratory systems continuously reliably.
- Unified Data Lake & Contextualization: Cleanses, contextualizes, and aggregates multi-system plant data to create a single, trusted operational data foundation.
- AI-Driven Analytics: Applies predictive, prescriptive, and anomaly detection models across energy efficiency, RUL, yield, and emissions performance.
- Advisory Intelligence Modules: Converts analytics into actionable recommendations for energy optimization, maintenance planning, quality improvement, carbon management, and value.
- Visualization, Action & Verification: Dashboards enable informed decisions, execution tracking, MRV-based verification, audit trails, and regulatory-compliant reporting.
Key Modules of SteelSense™
Integrated AI modules for operational optimization and carbon compliance.
Intelligent Energy Optimization
• Optimize fuel, oxygen balance, and zone temperatures continuously. • Reduce specific energy consumption through AI-driven setpoint tuning. • Stabilize furnace efficiency across varying loads and conditions. • Detect abnormal combustion behavior and excess air losses early. • Simulate what-if scenarios using digital furnace twin models. • Minimize CO₂ emissions through energy efficiency improvements. • Deliver measurable fuel savings with verified performance outcomes.
Proactive Asset Reliability Intelligence
• Detect early anomalies in fans, pumps, burners, and blowers. • Predict remaining useful life using equipment health indicators. • Reduce unplanned downtime through proactive maintenance insights. • Improve maintenance planning with AI-based failure probability insights. • Optimize spare inventory using data-driven asset condition trends. • Enhance safety by preventing sudden equipment failures. • Integrate alerts with CMMS and maintenance workflows seamlessly.
Thermal Quality and Yield Control
• Monitor temperature uniformity across furnace zones in real time. • Predict yield losses caused by overheating or underheating conditions. • Optimize soak temperature and dwell time automatically. • Reduce scale loss and rework through thermal control insights. • Correlate process parameters with rolling quality outcomes. • Visualize heat-level quality deviations using uniformity heat maps. • Improve product consistency across shifts and operating teams.
Carbon Intelligence and Regulatory Assurance
• Automatically calculate plant-level emissions from fuel and electricity. • Reconcile activity data with verified emission factors accurately. • Generate product-level CO₂e ledgers with full audit traceability. • Support CBAM, SBTi, and GHG compliance reporting requirements. • Reduce manual reporting effort through automated data pipelines. • Ensure audit-ready emissions data validated for regulatory reviews. • Enable green steel readiness for buyers and sustainable financiers.
Features of SteelSense™
Capabilities designed for operational efficiency, reliability, and carbon compliance.
Data Exploration & Quality
Transforms raw furnace data into trusted, validated operational intelligence for analytics and carbon accounting.
Engineering Layer
Converts raw process signals into standardized, traceable energy, quality, and carbon performance indicators.
AI Models & Intelligence
Predicts performance trends, detects anomalies, and delivers prescriptive recommendations for optimization.
KPI Dashboards
Provides real-time, role-based visibility into energy efficiency, quality performance, throughput, and emissions.
Predictive Maintenance
Predicts equipment health and failures using RUL analytics to reduce downtime and maintenance costs.
What-If Simulation Engine
Simulates operational scenarios using digital twins to optimize setpoints without production risk safely offline.
Inspirational Insights Client Stories
Case studies that connect progress with performance goals.
FAQs on SteelSense™ Platform
How soon can a steel plant realistically expect measurable outcomes after implementing SteelSense™?
Once data integration is completed, plants usually begin seeing meaningful operational insights within a few weeks. Early value comes from visibility into energy behavior, anomalies, and emissions baselines. Optimization, predictive maintenance, and carbon benefits increase steadily as the system learns from ongoing operations.
Does SteelSense™ change how operators control furnaces or interfere with existing automation systems?
No. SteelSense™ does not replace PLCs, DCS, or operator control logic. It works as a decision-support layer, providing recommendations, alerts, and simulations while leaving full control with operators and existing automation systems.
What happens if plant data quality is inconsistent or sensors are unreliable?
SteelSense™ includes steel-specific data quality validation to detect missing values, sensor issues, and invalid ranges. This ensures unreliable data is flagged early, preventing incorrect insights and maintaining confidence in analytics, recommendations, and compliance reporting.
Can SteelSense™ adapt to different furnace types, fuels, and operating practices across plants?
Yes. The platform is designed to learn from plant-specific data rather than relying on generic assumptions. It adapts to different furnace designs, fuel mixes, load patterns, and operating philosophies while maintaining consistent performance metrics.
How does SteelSense™ help justify operational or decarbonization investments to leadership?
SteelSense™ links operational improvements to quantified outcomes such as fuel savings, downtime reduction, efficiency gains, and emissions impact. This enables data-backed justification for optimization initiatives, maintenance planning, and decarbonization investments.
Is SteelSense™ prepared to support future regulatory changes and evolving sustainability requirements?
Yes. SteelSense™ is built with audit-ready traceability and structured data pipelines, allowing it to adapt to changing regulations, reporting frameworks, and sustainability standards without requiring system redesign.