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Communication dans un congrès

Overcoming the Barriers in Diagnostics and Prognostics of the Circular Industrial System by Hidden Markov Model

Akash Basia 1 E. Gascard 1 Zineb Simeu-Abazi 1 Peggy Zwolinski 2
1 G-SCOP_GCSP [2016-2019] - Gestion et Conduite des Systèmes de Production [2016-2019]
G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production
2 G-SCOP_CPP [2016-2019] - Conception Produit Process [2016-2019]
G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production
Abstract : In this paper, a novel method has been proposed to overcome the difficulty of handling technical heterogeneity and varying operating condition, while designing Prognostics and Health Management (PHM) systems. The motivation towards this work is to facilitate better decision making on repurposing, in the context of Circular economy. In the case of re-purposing, there are multiple second life applications of a product. It is utterly important to know the state of health in prior for sorting the product efficiently into the above-said applications. However, estimating the health state of products with complex degradation mechanism, particularly electronic devices, is difficult, due to technical heterogeneity and varying operating conditions. The method proposed, is based on the black box modeling of the system, relying on the real-time data acquired through the sensors installed to monitor the component. A data-driven stochastic method based on hidden Markov model is proposed. A region based model database has been created to provide versatility to the overall system.
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https://hal.univ-grenoble-alpes.fr/hal-02372138
Contributeur : Eric Gascard <>
Soumis le : mercredi 20 novembre 2019 - 11:36:19
Dernière modification le : mardi 6 octobre 2020 - 16:30:21

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  • HAL Id : hal-02372138, version 1

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Akash Basia, E. Gascard, Zineb Simeu-Abazi, Peggy Zwolinski. Overcoming the Barriers in Diagnostics and Prognostics of the Circular Industrial System by Hidden Markov Model. 3rd International Conference on Control, Automation and Diagnosis (ICCAD’19), Jul 2019, Grenoble, France. ⟨hal-02372138⟩

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