Comexi Leads Innovative MADAM Project for Improved Packaging Production

The MADAM (Automatic Model for Anomaly Detection and Error Prevention with Machine Learning) project focuses on modernizing production processes to increase efficiency. This innovative project, involving a consortium with Synaptik, Dribia, RotorPrint and coordinated by the Packaging Cluster, aims to use machine learning to detect and prevent errors in laminating machines.

Our goal is to gain new knowledge in anomaly detection and develop solutions to anticipate and minimize defects. The success of MADAM will significantly reduce waste, improve product quality, optimize machines, and increase productivity. These improvements will translate into increased customer satisfaction and an improved brand image.

Throughout the development of MADAM, we will define the requirements and variables to monitor the health of various modules and components in our machines. The data obtained will be analyzed to build a cause-and-effect model that anticipates machine stops. A data visualization model will be implemented, followed by an evaluation of the system through machine testing.

The MADAM project is supported by a €219,438 grant from the Ministry of Industry, Trade and Tourism, contributing to a total budget of €284,385. This funding will facilitate the development of an automated model for anomaly detection and error prevention, promoting collaboration across the sector.

Comexi’s involvement in the MADAM project is a testament to our commitment to innovation and our dedication to advancing the flexible packaging industry. By embracing machine learning, we aim to set new standards in production quality and efficiency.

Stay tuned for more updates on this exciting venture into the future of packaging technology!