Energy- and Quality-Optimized Production through AI-Driven Process Analysis (EKOPRO)

Purpose and goal

The project´s purpose is Energy- and Quality-Optimized Production (EKOPRO) through AI-Driven Process Analysis. The core aim is to fundamentally reduce scrap and energy consumption in steel and specialty metals production by applying AI to combine process data and inspection results. The key goals include developing and validating real-time AI warning systems to identify risky process parameters and demonstrating a measurable reduction in scrap, CO₂ emissions, and resource losses.

Expected effects and result

The expected results and effects include the delivery of a validated prototype AI decision system for the early detection of quality deviations in production. This system will enable real-time process adjustment to prevent scrap. This improves resource efficiency (e.g., critical alloying elements) and strengthens the security of material supply. The project also delivers a robust, scalable data infrastructure and guidelines for industry-wide application.

Planned approach and implementation

The approach shifts quality control from reactive inspection to proactive, real-time AI optimization using CRISP-DM. Implementation relies on establishing end-to-end traceability by linking individual product process history to final Ultrasonic Testing, leveraging automatic ID code reading. Advanced AI models will be developed to create real-time warning systems. The project also addresses data integration and ensures operator trust through explainable AI. Scalability is assessed in WP4.