The ETHPRIN project consortium, made up of Ceit, Azterlan, Lortek, Tecnun, Tubacex Innovación and Hispavista Labs, develops technologies and new modeling capabilities that will favor the digitization of industrial production. To this end, the project will address one of the most critical stages in achieving this goal: the lack of new product and process models..
To this day, the demand for parts made from cast iron has increased due to its technological properties, and above all, its great economic competitiveness. This fact, together with the crisis situation in Europe and the threat from countries like China or India, causes a greater need to optimize the physical properties of these materials and/or develop new types of iron alloys with innovative characteristics. These new materials, especially those with a high resistance to corrosion at high temperatures, have the potential to be applied in the manufacture of parts in which, up to now, steels or other alloys with higher production costs have been used.
To this end, the ETHPRIN project consortium, made up of Ceit, Azterlan, Lortek, Tecnun, Tubacex Innovación and Hispavista Labs, develops technologies and new modeling capabilities that will favor the digitization of industrial production. To this end, the project will address one of the most critical stages in achieving this goal: the lack of new product and process models.
Within ETHPRIN, physical-based models, data-based models and hybrid models will be executed in order to:
- Provide intelligence in processes.
- Increase predictive capacity.
- Have extensive applicability to a set of steels, alloys, castings and/or ranges of process settings.
- Give an online response during the industrial processing stages and predict the behavior in service conditions in a hostile environment.
Main objectives of the project:
- Advanced simulation of casting processes.
- Advanced modeling of hot forming processes and heat treatments.
- Advanced modeling of the hardfacing process of CRA alloys.
- Verification of corrosion behavior in service of nodular cast iron with CRA overlay.
- Design of distributed algorithms for monitoring and prediction of degradation processes.
- Development of pipeline methodology in machine learning and improvements of the federated learning system.
- Evaluation of the anisotropic behavior in mechanical properties and collapse of CRAs alloys.
Real-time forecasting software for cast iron:
Within ETHPRIN, AZTERLAN develops the KASANDRA® software, a real-time predictive simulation tool for cast iron that predicts the risk of shrinkage defects in spheroidal, laminar, and compact graphite cast iron.
