Navigating progress in s-X-AIPI steel use-case

MSI Grupo, Sidenor, and BFI, the s-x-AIPI experts who comprise the steel team, have achieved promising progress. In s-X-AIPI, steel use case focuses on optimising the use of scrap to produce high-quality steel products, while avoiding downstream surface quality problems and reducing process energy intensity. This will be achieved through the use of self-X AI technologies (i.e., AI technologies capable of adapting and evolving on their own) .

Over the past few months, Sidenor and BFI successfully defined and calculated the first set of metadata. This crucial step puts metadata monitoring processes in place for assessing the performance of each selected variable entering into the machine learning models for the self-healing proposed approach.

In close collaboration with BFI and Sidenor, MSI Grupo's most notable contribution has been to develop the initial prototype for raw data ingestion, establishing a connection between metadata generated by an advanced artificial intelligence model developed by BFI. This model accurately predicts copper content in liquid steel, by relying on input data associated with scrap in the production process.

Furthermore, MSI Grupo facilitated the seamless connectivity of metadata generated by the model to an Orion Context Broker hosted in the cloud. This innovative step opens avenues for improved data management and accessibility.

As the project progresses, the road ahead will involve processing and analysing these metadata in the cloud. This marks a significant milestone towards optimizing steel production. The collaboration of Sidenor, BFI, and MSI Grupo exemplifies the impactful outcomes achievable through collaborative research and innovation.