The project aims to improve visibility and control over the quality of the assembly process through the use of advanced analytics and Artificial Intelligence. Based on the information generated by sensors installed on the manufacturing equipment, the aim is to anticipate potential geometric deviations during the process, enabling early intervention and optimising final production outcomes.

To this end, an approach has been defined combining the integration and preparation of various industrial data sources, the analysis of the relationship between process signals and quality indicators, and the development of predictive models capable of estimating the behaviour of the assembly throughout the operation. This approach is complemented by the definition of a technological framework geared towards its future implementation in a production environment, including visualisation tools and interfaces designed for plant operators.

In this way, the project facilitates the interpretation of process data and provides comprehensible indicators that support decision-making during manufacturing, helping to improve the efficiency and quality of the process.