AI supported machine data acquisition and control



Horizon 2020


01.03.2022 - 31.05.2023


Nejc Bat
EU flag
This project has indirectly received funding from the European Union’s Horizon 2020 research and innovation programme, via an Open Call issued and executed under project KITT4SME (grant agreement No 952119).

Accurate prediction of machining time is essential for planning and optimizing production and business processes. Computer Aided Manufacturing solutions estimate job execution times based on CNC part programs, but these vary drastically from real processing times.

The CNCSmart service predicts the real execution times of CNC part programs for metal-working industry cutting machines. It uses machine learning techniques to analyse CNC part programs and accurately estimate execution times based on historical data and various cutting parameters such as machine type (e.g., oxyfuel, plasma, laser cutting), material type and thickness, operation (e.g., cutting, marking, drilling, piercing, bevel cutting), and tools handling.

CNCSmart provides a baseline to build prediction services for any CNC-enabled machinery that provides data through OPC/UA, ADS, or other standards.

The project was selected for funding via an Open Call issued under project KITT4SME that invited technical developers to describe solutions addressing problems for EU SME manufacturers.

XLAB’s role

XLAB is responsible for the development of the complete CNCSmart solution and its validation in real-world environments.