Let’s turn the learning
steel plant into reality.

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.

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.

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.

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.

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.

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 DataFactory" which is used to convert araw data such as relational data, process data, time codes or files into usable data.