Article (Scientific journals)
Multi-agent deep reinforcement learning based Predictive Maintenance on parallel machines
Ruiz Rodriguez, Marcelo Luis; Kubler, Sylvain; de Giorgio, Andrea et al.
2022In Robotics and Computer-Integrated Manufacturing
Peer reviewed
 

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Keywords :
Predictive Maintenance; Scheduling; Reinforcement learning; Multi-agent systems; Industry 4.0
Abstract :
[en] In the context of Industry 4.0, companies understand the advantages of performing Predictive Maintenance (PdM). However, when moving towards PdM, several considerations must be carefully examined. First, they need to have a sufficient number of production machines and relative fault data to generate maintenance predictions. Second, they need to adopt the right maintenance approach, which, ideally, should self-adapt to the machinery, priorities of the organization, technician skills, but also to be able to deal with uncertainty. Reinforcement learning (RL) is envisioned as a key technique in this regard due to its inherent ability to learn by interacting through trials and errors, but very few RL-based maintenance frameworks have been proposed so far in the literature, or are limited in several respects. This paper proposes a new multi-agent approach that learns a maintenance policy performed by technicians, under the uncertainty of multiple machine failures. This approach comprises RL agents that partially observe the state of each machine to coordinate the decision-making in maintenance scheduling, resulting in the dynamic assignment of maintenance tasks to technicians (with different skills) over a set of machines. Experimental evaluation shows that our RL-based maintenance policy outperforms traditional maintenance policies (incl., corrective and preventive ones) in terms of failure prevention and downtime, improving by ≈75% the overall performance.
Disciplines :
Computer science
Author, co-author :
Ruiz Rodriguez, Marcelo Luis ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SerVal
Kubler, Sylvain ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SerVal
de Giorgio, Andrea;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SerVal
Cordy, Maxime  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SerVal
Robert, Jérémy;  Cebi Luxembourg S.A.
Le Traon, Yves ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SerVal
External co-authors :
no
Language :
English
Title :
Multi-agent deep reinforcement learning based Predictive Maintenance on parallel machines
Publication date :
2022
Journal title :
Robotics and Computer-Integrated Manufacturing
Publisher :
Elsevier
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
FnR Project :
FNR16756339 - Robust Predictive Maintenance For Industry 4.0, 2021 (01/06/2022-31/05/2025) - Yves Le Traon
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