Introduction

Recently, the dissemination of condition monitoring equipment and the development of methods for deterioration prognosis and residual life estimation have shifted the interest of most practitioners towards predictive maintenance techniques. Predictive maintenance seeks to anticipate system failures in order to plan timely interventions on the system.

Available Theses

• Anomaly detection for time series
• GAN for time series
• Cyber-physical attack detection

Theses In progress

• None at the moment

Project & Collaborations

In progress 

References

• Vincenzo Moscato, Associate Professor (This email address is being protected from spambots. You need JavaScript enabled to view it.)
• Antonio Galli, PhD student (This email address is being protected from spambots. You need JavaScript enabled to view it.)