Metallurgy Research Centre

Applied Research


investigación investigación investigación

  • By means of Artificial Intelligence, performs a multivariable analysis of the 600 parameters that take part of the metallic transformation process.
  • Predicts the quality of the component manufactured and sends alerts 
  • In real time, analises data captured during the metallic transformation process to improve relevant areas.

  • Based on the cooling curves register, it allows controlling the alloy quality in real time and predict the resultant microstructure in the castings regarding its thermal modulus.
  • Spheroidal casting graphite density, matrix microestructure (%Ferrite/Pearlite), risk of shrinkage and cementite formation, necessary time for shake out, risk of Chunky graphite formation (big part), determination of C and Si and analysis of free Mg content.
  • Compacted graphite casting: spheroidization index, risk of shrinkage and cementite formation and determination of C and Si.
  • Gray cast iron: percentage of graphite distribution type A, graphite size classification, strength (T.S.) and hardness (HB) in a bar with 30mm of diameter, risk of shrinkage and cementite formation and determination of C and Si.
  • Aluminium alloy: grain size refinement, SDAS, modification rate, solid fraction evolution depending on the time and fraction of the main phases in a standard sample and in real castings.
  • New simulation system which includes the metallurgical quality in the defects prediction.
  • Simple and fast software, whose concept is not oriented to the feeding system design but verifies the behaviour of this reference with the alloy quality of that moment.
  • Simulations in the production plant, with an initial calculation estimation lower than 10 minutes.
  • With practice, it allows reducing the number and size of the feeding systems and increase the yield of the casting pattern when considering the feeding and solid fraction times of the different zones of the part.
  • Extensive knowledge on metallurgy and phase transformations, with the available equipment, allow encompassing complex projects to obtain alloys with optimized properties.
  • Azterlan shares the intellectual property of three patents that are exploited by the companies with which they have been developed.
  • IPRO system (Intelligent Process Control System) encompasses advanced computing tools (multivariable analysis, sensitivity analysis, acquisition and modeling of the knowledge and predictive system) that allow managing large volumes of information, which enables a variable output link (defect, mechanical properties, etc.) with all those which may be measurable with some precision in any section of the production process.
  • It is possible to predict in real time possible non compliance of the demanded requirements and therefore able to take immediate corrective actions, reducing the problematic drastically.
  • The use of optimized risers (Riser 2D, patented) allows obtaining castings without defects.
  •  The yield of the casting pattern is optimized and it is ensured that the riser works duly.
Contact

Ramón Suarez
Metallurgy Processes R&D Director

Susana Méndez
Metallurgy Processes R&D Coordinator

Aitor Loizaga
Industry and Foundry Projects

Fernando Santos
Institutional Projects

Jon Garay
Steel research area

Enara Mardaras
Corrosion research area

Asier Bakedano
Aluminium research area

Lucía Unamunzaga
Evironment research area

Garikoitz Artola
Forming research area

Argoitz Zabala
Artificial Intelligence research area

Jose Manuel Gutiérrez
Calculus Center