Research & Development
      Focus on Sustainability

      The focus on sustainability encompasses all R&D activities aimed at increasing resource, energy, and general process efficiency, circular economy projects and the development of materials and components for sustainable products, e.g., for lightweight automotive construction or renewable energy generation.

      Digitalization can go a long way towards increasing efficiency. Robots, data-based algorithms, model-based controls, state-of-the-art sensor technology in combination with machine learning and artificial intelligence (AI) help to optimize processes and support employees at the plants in such a way that product quality can be increased significantly.

      Optical systems are already being used successfully in many voestalpine companies, using AI to detect defects. This allows surface defects such as cracks on the product or component to be detected at an early stage. OCR (Optical Character Recognition), i.e., algorithms for optical character recognition supported by artificial intelligence (AI), enables parts to be clearly identified and their path tracked. These are two development examples for the application of innovative key technologies which are used to ensure the outstanding quality of voestalpine products.

      Artificial intelligence (AI) is also being used successfully in condition monitoring, to enable predictive maintenance of voestalpine systems using forecasting models (lean smart maintenance). The improvements in plant availability and capacity utilization as well as optimization of the process chain also lead to a reduction in energy requirements and therefore CO2 emissions.

      However, the use of artificial intelligence (AI) is not just limited to production processes, but also enables intelligent product solutions. The latest generation of turnouts, for instance, uses AI to assess their condition from the data collected and to decide whether there is a risk of a turnout failure and therefore a line closure. The flawless functionality of this essential system component can be ensured with a high degree of accuracy, and predictive maintenance can be initiated.