Steel is mainly produced via two process routes, the primary route (Blast Furnace - Basic Oxygen Furnace), and the secondary electric arc furnace (EAF) route. Both routes require steel scrap as an important secondary raw material, with the proportion of scrap continuing to increase in the future. Compared to steel production from primary raw materials, the utilization of scrap as a feedstock in crude steel production not only contributes to resource conservation, but it also reduces CO2 emissions and induces other environmental benefits, such as reduced acidification and photochemical oxidation. Efforts to decarbonize the steel industry to achieve the established CO2 reduction target (50% decrease in CO2 from steel production by 2030 compared to 1990 levels, and no net emissions by 2050 according to the European Green Deal) increase the shares of the lower CO2 primary route and the secondary route. This allows steel production to contribute significantly to the circular economy.
Efficient scrap recycling requires precise knowledge of the composition since a required steel grade demands a certain scrap quality. This depends on the characteristics of the scrap pieces (shape, dimensions, weight, volume) as well as on the material (chemical) composition (proportions of iron and foreign metals, as well as impurities such as plastics). Impurities and accompanying elements of the scrap delivered to the steel mill influence the process control of steel production and therefore the process costs. The increasing share of available scrap in total scrap (currently around 60% in the EU) already leads to a surplus of lower-quality scrap, which will increase in the future.
Regarding the achievement of climate targets in the steel industry, concrete and urgent action is required with an efficient analysis of the scrap composition. InSpecScrap provides an important contribution to significantly reduce costs and CO2 emissions in steel production. This is achieved by implementing suitable technologies for improved scrap characterization. Furthermore, it enables a more efficient use of scrap in the steel mill through an optimized charging mix for the converter or the EAF. The objectives of InSpecScrap are defined as follows:
- Innovative image analysis and detection of impurities by intelligent coupling of Artificial Intelligence (IR) with sensor technology
- Scrap characterization with focus on the analysis of industrially used scrap samples and application of an infrared-based sensor concept
- Improving the scrap charge mix for specific steel grades and investigating its impact on the metallurgical reactions occurring during the process
- Preparation of a roadmap that includes all technically relevant aspects along the scrap value chain
1 April 2023 – 31 March 2025
This project is funded by the Province Styria (Zukunftsfonds Steiermark) (Grant Agreement no. PN 1510)
Beginning with the project coordinator, the consortium is formed as follows:
- JOANNEUM RESEARCH Forschungsgesellschaft mbH
- Graz University of Technology - Institute for Computer Graphics and Vision
- K1-MET GmbH
- Know-Center GmbH – Research Center for Data-Driven Business & Big Data Analytics