Scroll Top

Resources

Publications

Public deliverables

Scientific papers

Research paper written by our coordinator ENSAM and our consortium partner Simula and published at ICAART 2024. This paper presents a method that utilizes explainability techniques to amplify the performance of machine learning (ML) models in forecasting the quality of milling processes, as demonstrated in this paper through a manufacturing use case.

This paper published in open access journal Sensors, was produced among others by our consortium partners from MTL NTUA and focuses on the need for advanced machine learning-based process monitoring in smart manufacturing.

Newsletters

resources
This is the inaugural edition of “Empowering Tomorrow’s Manufacturing,” the official newsletter dedicated to keeping you informed about the latest updates, advancements, and achievements of the Manufacturing Architecture for Resilience and Sustainability (MARS) project. Stay tuned for the latest updates and stories that highlight the remarkable progress of the Manufacturing Architecture for Resilience and Sustainability project.

This is the second edition of “Empowering Tomorrow’s Manufacturing,” the official newsletter dedicated to keeping you informed about the latest updates, advancements, and achievements of the Manufacturing Architecture for Resilience and Sustainability (MARS) project.

Highlights of this edition include: Global meeting in Pamplona at the head quarters of AIN – Navarra Industrial Association, Arts et Métiers ParisTech – École Nationale Supérieure d’Arts et Métiers‘s participation at the TriboBR 2023, the third article of the series “Closer look on…Federated Learning methods” and upcoming events in march.

 

;