Investigation of a Digital Twin for the Transformation of Composite Component Manufacturing in an Intelligent, Automated, Sensed, and Connected Industry.

01

Integration of sensors and data acquisition.

We integrate new cameras and optical sensors into the production process to monitor it in real time, from data capture to its exploitation.

02

Artificial intelligence for inspection and process control.

We develop models that relate process parameters to quality indicators, capable of functioning in environments where data on critical phenomena is scarce.

03

Artificial vision for the detection of surface defects.

We design vision algorithms to automatically detect defects in manufactured parts and reduce reliance on manual inspection.

01

Anticipating defects and deviations.

Predictive models relate process parameters to the final quality of the part to anticipate deviations before they become defects. Acting during the process, rather than at the end, reduces rejection and rework.

02

Data-driven maintenance.

Anticipating downtimes based on precise measurements of critical tool wear extends their lifespan and reduces unplanned downtimes.

03

An interoperable plant.

Connecting sensors, algorithms, and ERP/MES systems through industrial standards facilitates decision-making on the shop floor.