Scrap Management Suite

Raw materials account for the highest costs by far in producing one ton of crude steel. Implementing the right strategy for using these charge materials can generate the most significant potential for cost savings during production. Producers in the electric steelmaking industry are facing a particular challenge here: They need to maximize the amount of low-priced scrap in a melt while at the same time ensuring that it has the quality needed to meet the requisite production goals. In terms of the scrap, special emphasis is placed here on unwanted tramp elements such as copper or tin. In many cases, only an analysis that is carried out after the feedstock has been melted can show how high the proportion of these tramp elements in the scrap actually is.

The Metallics Optimizer makes up for this deficit. This application uses artificial intelligence techniques to forecast the amount of undesired tramp elements in the scrap before it is melted. The Metallics Optimizer uses this forecast to calculate the lowest-cost composition for the melt's charge mix utilizing an optimization algorithm. Here, the Metallics Optimizer takes account not only of the costs of the material but also of all costs related to the production of the melt, such as component wear and tear or energy consumption during the melting.

The charging of the scrap container and thus the crane operator play an essential part in the scrap handling process: scrap containers must be filled with the specified recipes for the charge materials in the correct order and weight within the shortest possible time. SMS group’s Scrap Yard Management system provides assistance here by recording the key events in the crane's movements. This allows scrap handling within the scrap yard to be tracked and the set recipes to be compared in real-time with the scrap that is actually charged. The crane driver can use an operator panel in the crane to check the loads he has already carried out any time he chooses and, if necessary, adapt the scheduled loading process. For outdoor scrap yards, there is also the possibility of tracking all vehicles and any completed process steps via an app and instructing and guiding the operators to ensure complete transparency in outdoor working areas too.

The detailed recording of all sequences significantly improves stock level documentation. What's more, the scrap heap volume can be captured by means of laser scanners on the crane beam and a precise volume model can be created to calculate the exact stock level down to just a few kilograms. This allows orders to be placed more precisely and any ordered materials no longer have to be stored for an indefinite period at considerable cost. Here SMS collaborates with the experienced laser-based application provider LASE Industrielle Lasertechnik.  Short storage times also reduce the oxidation of the material, which in turn increases yield and reduces CO₂ emissions. The laser scanner also provides a precise calculation of the fill level of the scrap container - down to a few centimeters - and thus ensures optimal filling of the container. Using a laser scanner for material detection is the first important step towards autonomous crane operation.

At present, optimization algorithms aimed at cutting costs for charging raw materials are only rarely employed in the global steel industry. Instead, standard operating procedures (SOPs) are followed. To minimize the risk of not achieving the target analysis, high-quality scrap and products from direct reduction are predominantly used for charging. Severe fluctuations in the chemical composition of individual batches can be compensated in this way, but they result in safety margins that do not take account of considerable savings potential. Currently, optimization algorithms are barely used at all – there is too much uncertainty regarding the chemical composition of the scrap.

SMS digital designed and built AI applications specifically to address this problem. Using historical chemical analyses of the melt, these machine-learning models are able to make predictions on the chemical composition of those scrap types currently stored in the scrap yard. The prediction of the chemical composition of the scrap type is used for an optimization algorithm that calculates the most cost-effective scrap mix for the target analysis and reduces the proportion of direct reduced iron to a minimum. In addition to cutting raw material costs, reducing CO₂ emissions is a further positive side effect.

In the past, scrap yard management often played only a minor role in the manufacture of metal products. Due to the growing cost pressure faced by the manufacturers and the shift towards more sustainable production processes, scrap yard management is increasingly becoming a significant distinguishing feature that makes a company stand out from its competitors. With its Scrap Management Suite, SMS digital is taking an essential step in this direction. In particular, the interaction between scrap handling tracking and scrap characterization increases the recycling rate while at the same time ensuring more efficient use of the material. Just a few measures are enough, therefore, to reduce CO₂ emissions significantly. In no other stage of the value chain in an existing plant such a positive effect on the CO₂ balance can be achieved at reasonable cost.