ERO develops an AI system based on deep learning for quality control in paper converting, reducing waste and improving production efficiency even on cases with complex graphics.
ERO Srl
Università degli Studi di Brescia
ERO Srl operates in the paper converting and packaging industry, specializing in advanced solutions for adhesive quality control. The company serves a demanding market that requires precision, reliability, and high levels of automation in production processes.
In the paper converting sector, manufacturers face increasing demands for quality and accuracy. Traditional glue inspection systems struggle to function properly on cartons with complex graphics, leading to production errors, waste, and downtime. The lack of reliable solutions limits productivity and the ability to meet modern quality standards.
The project developed an artificial intelligence system using deep learning techniques capable of accurately detecting adhesive presence—even on printed cartons with intricate designs. The system enables fully automated inspection adaptable to any type of carton, improving line efficiency and minimizing manual intervention.
Deep learning
Artificial Intelligence
Machine Vision
This solution eliminates current limitations in adhesive quality control, enabling a more flexible, accurate, and streamlined production process. Companies using the system can produce cartons with unrestricted graphic designs without compromising inspection reliability. Large-scale adoption will lead to reduced waste, enhanced quality, and optimized production resources.
With this innovative system, ERO strengthens its market position by offering a highly intuitive and versatile solution. Clients will benefit from significantly improved product quality, reduced time-to-market, and lower production waste. This innovation also opens opportunities for expansion into international markets.
