IZAR
Hacia una fábrica proactiva basada en conocimiento experto
Industry
Artificial Intelligence
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KK-2026/00055
Goals
IZAR aims to capture and evaluate the expert knowledge in factories without assuming it is perfect or that it remains valid over time, and allow the factory, relying on this knowledge, to continuously explore new hypotheses and opportunities for improvement.
What was our contribution?
In this project, we offer a perspective focused on lower technology readiness levels (TRLs) and the generation of scientific knowledge in advanced artificial intelligence. Its strategy centres on the autonomy of artificial intelligence, the training of experts, and international scientific impact. At IZAR, it leads the development of new multifidelity optimisation techniques and contributes to areas such as physics-informed machine learning, reinforcement learning, and multi-agent systems.
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