TOWARDS A PROACTIVE FACTORY BASED ON EXPERT KNOWLEDGE

In recent years, many models and algorithms have been developed for use in manufacturing, with objectives such as machine parameter configuration and production planning. However, their actual adoption in industrial settings remains limited, and they are often relegated to the role of support tools. The aim is to capture and evaluate expert knowledge and enable the factory, drawing on that knowledge, to continuously explore new hypotheses and opportunities for improvement.

In short, the IZAR project aims to capture and evaluate the expert knowledge present in factories, without assuming that it is perfect or that it will remain valid over time, and to enable the factory, drawing on this knowledge, to continuously explore new hypotheses and opportunities for improvement. In this approach, unlike traditional artificial intelligence approaches based exclusively on data, expert knowledge forms the starting point upon which improvements are built and validated.