Reducing the global carbon footprint in increasingly complex and volatile markets requires new ways of thinking, a willingness to change, and the use of disruptive technologies. SMS already offers not only new processes and equipment for the production of high-performance materials in the field of metallurgy but also digitalized and connected processes as part of Industry 4.0 aimed at realizing the fully autonomous steel plant. In the following, we will look at three use case examples of the DataXpert platform and outline the opportunities this presents for predictive asset optimization and why the interaction of different disciplines is essential for developing modern digital solutions.
Digital applications provide the leverage for resource-efficient and sustainable production processes, which are now playing an increasingly important role in the manufacturing industry. They enable plant operators to make accurate, machine learning-based predictions about production processes, product quality, and the plant’s condition. Similarly, energy consumption can be predicted and optimized through the targeted calculation of raw materials. The possibility of making accurate process predictions means that raw materials and feedstock are used according to demand, thus reducing waste, downtime, and costs. By relying on digitalization, companies can generate enormous added value from the possibilities offered by new technologies such as machine learning for the holistic optimization of production processes.
Another important topic, however, is occupational safety, and machine learning methods provide an opportunity to make important further developments. Today, for example, camera systems allow problems to be detected without humans having to enter hazardous areas. New sensor technology helps to assess the state of the production line with ever-greater precision. Condition and process monitoring systems combine data from multiple sources to provide plant operators with meaningful information and recommendations. Predictive asset management and automation will be instrumental in improving safety and mitigating risks in steel production facilities. Digital tools enable us to anticipate, respond to, and solve problems before they occur. The aim is to create next-generation steel plants that operate fully autonomously, efficiently, and safely.
SMS group developed the DataXpert platform to facilitate the collaboration between interdisciplinary teams of software developers, experts with process and hardware knowledge, and data engineers and data scientists. So, what are the specific possibilities for using platforms for efficient plant management?