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Let’s turn the learning
steel plant into reality.

SMS digital GmbH

Digital transformation and innovation are our DNA

We are taking up the challenges of digital transformation and Industry 4.0 and develop innovative solutions that boost your business. Benefiting from state-of-the-art development methods, our software solutions for predictive asset health, product quality, production planning and energy management contribute in actively saving money, increase profitabiliy and conserve resources. 

Use our digital technologies to turn data into information and information into value. 

The digital future has already begun.

Streamlining your maintenance 

 

Decrease quality deviations

 

Optimize your plant utilization

Achieve 6 - 8% EBITDA margin improvement by digital transformation.


The first Learning Steel Plant

Our vision comes true

Big River Steel produces pipe grades for pipelines, silicon steels for electrical steel and AHSS grades for the automotive industry on SMS group equipment. As systems supplier for the steel mill complex, SMS group supplied all the equipment, process know-how and automation technology and supported BRS during commissioning. 

From the combination with SMS digital's innovative solutions for data infrastructure, digital products and machine learning resulted in the world's first learning steel mill. 

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Solutions

We combine digitalization expertise with 150 years of metallurgical know-how.

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Reduce your carbon footprint
Predictive Energy Management

The demand for energy and resources is steadily increasing. Intelligent solutions are needed to achieve a sustainable balance between economic growth and environmental responsibility. Effective energy and sustainability management is therefore of central importance for the metals and process industry and has a decisive effect on its cost efficiency and carbon footprint.

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Solutions for optimized production planning
Predictive Production Planning

The dynamic changes in market demands, triggered by the Internet of Things, require considerably shorter modernization cycles as we head towards Industry 4.0. Increasing volumes of data and new means of exchanging information are resulting in closer collaboration between integrated plant and automation system suppliers and plant owners/operators and end users.

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Software solutions for quality optimization
Predictive Product Quality

Even today, quality management is not an automated process in most rolling mills. A great deal of time and effort is invested in quality monitoring by plant personnel, for example to determine the exact cause of defects. Deviations in the quality data require the monitoring personnel to take decisions and any relevant action, such as redirecting or, in the worst case, scrapping a coil, which leads to losses.

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PREDICTIVE PROCESS CONDITION MONITORING
Predictive Asset Health

Many plant processes in companies have already been digitalized. However, the evaluation of the generated data is very time-consuming. Our smart maintenance solutions make it possible to carry out automatic system-wide analyses, thus improving quality and efficiency. These products and solutions focus on aspects such as plant availability, inventory management, and maintenance planning.

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REAL TIME CONNECTIVITY AND PROCESS TRANSPARENCY
Digital Twin

The Digital Twin is a virtual representation of a material or immaterial object of the real world that not necessarily exists, e.g. in the design phase of a machine. As the concept of Digital Twins is universal, it can thus be applied to almost everything: to machines, tools, processes, human capital, production, and quality KPI, and so on.

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TURN DATA INTO INFORMATION AND INFORMATION INTO VALUE
INFRASTRUCTURE SOLUTIONS

In order to create a basis for all digitalization applications and to finally obtain added value from data, the plant data must be available in a structured, well-organized form. For this purpose, we offer the cloud-based "SMS Data Factory" which is used to convert araw data such as relational data, process data, time codes or files into usable data.