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Comment l’Intelligence Artificielle dompte la traçabilité des processus Supply Chain ? Application à NOZ France

Author

Listed:
  • Hind Aboussikine

    (LIRSA - Laboratoire interdisciplinaire de recherche en sciences de l'action - CNAM - Conservatoire National des Arts et Métiers [CNAM])

  • Sonia Bendimerad

    (ESLI - École supérieure de logistique industrielle)

  • Thierry Sauvage

    (LIRSA - Laboratoire interdisciplinaire de recherche en sciences de l'action - CNAM - Conservatoire National des Arts et Métiers [CNAM])

  • Mohamed Haouari

    (ESLI - École supérieure de logistique industrielle)

Abstract

L'intelligence artificielle est devenue incontournable dans la mise en œuvre d'une supply chain efficace [Derrouiche, 2022] et les entreprises n'ont d'autres choix que de s'adapter pour bénéficier d'une logistique rentable, fiable et fluide. Dans ce contexte, la chaîne de magasin de déstockage généraliste-NOZ- souhaite renforcer sa présence en France en augmentant son nombre de magasins (de 322 à 450) et en améliorant la traçabilité de sa supply chain. Dans cette recherche, nous identifierons les différentes phases du projet pour mettre en place un système de traçabilité basée sur une application prédictive d'Intelligence Artificielle, puis, nous constaterons les retombées positives liées à ces actions et leurs impacts sur la stratégie logistique de Noz France.

Suggested Citation

  • Hind Aboussikine & Sonia Bendimerad & Thierry Sauvage & Mohamed Haouari, 2023. "Comment l’Intelligence Artificielle dompte la traçabilité des processus Supply Chain ? Application à NOZ France," Post-Print hal-04536092, HAL.
    • Handle: RePEc:hal:journl:hal-04536092
    Note: View the original document on HAL open archive server: https://cnam.hal.science/hal-04536092
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    References listed on IDEAS

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