Title: Predictive Maintenance with Experts in the loop
Approval Date:  Oct. 2021


The objective is to design an AI able to anticipate the drifts of electronic components in complex embedded systems. The AI will learn from existing data to be properly selected and processed while considering the feedbacks of human experts and will evolve continuously to provide new maintenance schemes

Related roadmap thrusts and axis

– Thrust 2: New Algorithms for Energy-Efficient and Human Based AI

    • Axis 2.1 Cross Learning Between Humans and Machines

Project Members

Name Organisation Role
M. Jean-Victor AUTRAN  Ariane Group  PhD Student
Prof. Cedric BUCHE  CNRS / ENIB  Primary PhD Supervisor
Dr. Jean-Philippe DIGUET  CNRS  Primary PhD Supervisor
Dr. Véronique Kuhn  Ariane Group Technical Industry PhD Advisor 

Project Funding 

  • Ariane Group

Start / Duration 

  • Jan. 22 / 3 years