IK4-AZTERLAN part of the PREMIERE Project, focused on the development of predictive analytics for manufacturing processes
Within the project, the Metallurgy Research Centre IK4-AZTERLAN develops an advanced data capture and artificial intelligence system for the company Fagor Ederlan.
With the aim of driving the digital transformation of manufacturing plants, the consortium of the PREMIERE Project is working on the development of intelligent systems that will allow applying advanced techniques of predictive analysis to optimize industrial productive processes.
The project aims at helping industrial companies to achieve more adaptable, flexible and efficient means with machine learning capabilities, that will improve their processes by decreasing manufacturing defects, increasing production ratios and minimizing levels of energy consumption.
Framed within Basque Government’s HAZITEK Program to promote and develop R&D projects among companies, the PREMIERE Project is led by Spyro and it is participated by the companies Vixion, Ingeteam Power Technology, Fagor Arrasate, Fagor Ederlan, Sidenor and RPK, as well as the technology centers and research entities Koniker, Tecnalia, Edertek, IK4-Ikerlan, an IK4-Azterlan.
As a part of this outstanding consortium, IK4-AZTERLAN Metallurgy Research Centre develops an advanced data capture and Artificial Intelligence system for Fagor Ederlan.
Projects for the implementation of 4.0 technologies in metallic transformation processes
The PREMIERE Project is part of the extensive research work of the Technology Center, developing as well specific applications in other projects like EFFORT 4.0 or DIGIMAT, to develop control systems based on 4.0 technologies related to metallic transformation technologies.
Regarding the project EFFORT 4.0, besides the iron foundry technology, IK4-AZTERLAN also approaches the development and implementation of predictive software for aluminum High Pressure Die Casting (HPDC) and for forging processes. In addition, the DIGIMAT project is focused on the application of predictive control systems oriented towards the development of components with optimized metallurgic properties for the automotive sector.