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Communication Dans Un Congrès Année : 2020

Predictive maintenance based on decentralized CPS and convolution’s neural network

Résumé

The massive ingest of non-intrusive sensors on manufacturing processes lifecycle allows to collect and monitor the health state of machines and serve maintenance programmes. In this research paper, we use machines’ monitoring data in a decentralised Cyber Physical System (CPS) architecture implementing Convolution’s Neural Network algorithms to influence the future behaviour of manufacturing equipment in a predictive maintenance perspective. This research contributes to extend the remaining useful life (RUL) of equipment and was implemented in an industrial use case supported by TARDY partner for the predictive maintenance of metal transformation machines.
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Dates et versions

hal-03059679 , version 1 (12-12-2020)

Identifiants

  • HAL Id : hal-03059679 , version 1

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Baudouin Dafflon, Mohand Lounes Bentaha, Néjib Moalla, Alexandre Benbouriche. Predictive maintenance based on decentralized CPS and convolution’s neural network. 13ème Conférence Internationale de Modélisation, Optimisation et Simulation - MOSIM 2020, Nov 2020, Agadir, Morocco. ⟨hal-03059679⟩
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