Intelligent production in the steel industry: revolutionary technologies for a sustainable and efficient future

Artificial Intelligence
Image: Pixabay

The steel industry is facing a huge transformation: in future, companies around the world will have to produce and process steel in a climate-friendly, energy-efficient and resource-saving manner if they want to meet the challenges of the 21st century. The key enabler for this is intelligent production, which enables completely new levels of efficiency in production, further processing and, for example, heat treatment through the combination of artificial intelligence (AI), big data digital twins and highly integrated process automation. Technological progress with the help of advancing digitalization is making the future of steel production smarter and more connected than ever.

All experts now agree that the vision of climate-neutral steel production can no longer just be an ambitious idea on the drawing board - it is an urgent necessity. Nevertheless, in the case of the steel industry, it is a long and arduous road from realizing the necessity to actually implementing it, because switching to climate-friendly production is a Herculean task. Just to convert one of Thyssenkrupp's four blast furnaces in Duisburg to a direct reduction plant with hydrogen operation, for example, would require more than twelve times the hydrogen capacity of the neighboring gasometer in Oberhausen every day. This in turn would require 3,200 windmills of the highest performance class in continuous operation to produce this amount of green hydrogen, because only green hydrogen is climate-neutral. These enormous requirements illustrate how radically the energy supply must change if companies in primary steel production want to reduce their emissions and become more climate-friendly. But these new production methods are just the beginning: the vision is to convert the entire sector to sustainable and recycling-based production methods in order to make steel production virtually CO₂-free in the long term.

Image: ArcelorMittal Bremen

Digitalization as a driver for efficiency and cost reduction

The key to the green transformation lies above all in the digital transformation of companies. Smart Steel Technologies is a pioneer in this discipline. The company specializes in developing the right tools to ensure that end-to-end digital production control and planning not only significantly increases efficiency, but also enables significant savings in energy costs. This is urgently needed in Germany, but also in almost all of Europe, as energy prices in steel production are high by international standards, putting European manufacturers under severe pressure. With hybrid AI approaches that combine physics-based and machine-learning models, solutions are now being developed that promise a drastic improvement in efficiency and sustainability. Hybrid models are so promising precisely because they understand and optimize complex production processes better than traditional planning ever could - they are more precise, faster and capable of learning.

The example of the German medium-sized company BGH Edelstahl illustrates very well how the digital AI-based revolution is also finding its way into traditional companies. Collaboration with AI specialist gapzero has resulted in the so-called “heat treatment planner”, software for the automated optimization of heat treatment processes. What used to be a purely manual and time-consuming planning process can now be optimized within seconds at the click of a mouse. This solution goes far beyond traditional planning software: it minimizes the duration of production runs, reduces energy consumption and provides production managers with a powerful tool with which they can dynamically and agilely control the operation of furnaces and quenching tanks. This is a paradigm shift in traditional stainless steel production, which until now has relied primarily on the experience and intuition of its skilled workers.

The view shows the optimized processes in the planning software
Image: BGH Edelstahl Siegen

Big data and AI: a new era for the steel industry

“We use perhaps 10% of the data we collect in steelworks today.” This statement by Andreas Dalchow, Chief Technology Officer at ArcelorMittal, illustrates the huge untapped potential that lies dormant in the steel industry's processes. In the digital age, data is the “new oil” and AI-supported systems are the refineries. ArcelorMittal is working hard to efficiently evaluate the remaining 90% of available data and use it to optimize processes. For example, AI can predict unplanned plant shutdowns by detecting potential defects and anomalies in real time and initiating maintenance measures at an early stage. The use of such predictive maintenance and prognostic foresight technologies not only increases efficiency, but also makes it possible to sustainably reduce energy consumption and emissions - crucial steps on the way to climate-friendly production.

However, before using artificial intelligence in production, it is often first necessary to dispel fears and concerns among the workforce and plant operators. This is because it is initially an unpredictable “black box” for them, which can cause great uncertainty in critical production environments such as a steel mill. Primetals has therefore developed a system of “explainable AI” (xAI) that overcomes the lack of transparency of traditional models. The idea: not only the result of an AI-based analysis should be understandable, but also the way in which this result was achieved. By combining machine learning with detailed knowledge of metallurgy and thermodynamics, models can be developed that are easy to understand and can be controlled efficiently. This transparency is invaluable, especially in safety-critical processes such as blast furnaces and sintering plants, and helps to increase the acceptance of AI solutions in production.

Image: Primetals

Sustainability through life cycle analyses and material simulation

The Institute of Ferrous Metallurgy at RWTH Aachen University goes one step further and combines life cycle analyses (LCA) with data-driven material simulation, for example to increase the sustainability of new steel alloys and processes. These approaches are particularly important as material compositions are constantly changing due to the increased use of recycled scrap. The digital simulation of material properties and data-driven modeling offer valuable insights here and make it possible to develop more climate-friendly and robust steels right from the start. Especially in the automotive industry, which relies on high-strength steels, this capability will be indispensable in the future.

Conclusion

Intelligent production is not a dream of the future, but the next big wave that will revolutionize the steel industry worldwide. The combination of big data, AI and automation is making it possible to achieve long-held goals of efficiency and sustainability that seemed unattainable until a few years ago. Companies such as Smart Steel Technologies, BGH Edelstahl and ArcelorMittal as well as research institutions such as RWTH Aachen University are consistently driving change and using the new AI-based technologies to make their production processes fundamentally more (energy) efficient and economical. The steel industry is not only becoming more environmentally friendly and profitable, but also more resilient and agile, which puts it in an optimal position to meet the challenges of the future.

You can find out more about intelligent production in the steel industry at the next wire & Tube, which will take place in Düsseldorf from April 13 to 17, 2026. The latest industry and product information is available on the Internet portal at www.wire-tradefair.com.

Sources

„Intelligente Produktion: Interview mit Dr. Falk-Florian Henrich von Smart Steel Technologies“.

Goderbauer, Sebastian, Hippenstiel, Frank, Metzger, Jonas, & Müller, Michael: „Automatisierte Planungsoptimierung der Wärmebehandlung bei BGH Edelstahl Siegen“.

Lutter, Pascal & Hartmann, Marc: „Künstliche Intelligenz in der Metallindustrie: Kann KI die Planung revolutionieren?“.

Bettinger, Dieter, Fritschek, Harald, Klinger, Angelika, et al.: „Erfolgreiche KI-Anwendungen in der Eisenerzeugung: Transparenz-Ansatz mit erklärbarer KI“.

Naber, Hannah, Jeyaraj, Vinola, Krupp, Ulrich & Gramlich, Alexander: „Stahldesign im Spannungsfeld der Digitalisierung: Integrative Werkstoffsimulation und LCA“.

ArcelorMittal: „Künstliche Intelligenz in der Stahlherstellung: Viele Chancen - aber auch noch einige offene Fragen“.