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Développement d’un outil à base de connaissances pour l’aide à la décision dans le contexte de l’Industrie 4.0 : application au diagnostic des machines d’usinage à grande vitesse

Abstract : Within the context of its fourth revolution, the industrial world is undergoing a strong digitalization in all sectors. This research work is integrated in a context of transition towards the industry of the future, specifically in the mechanical machining industries. These studies answer the problematic of industrial data and knowledge integration, to sustain the functioning of decision-support systems. The proposed approach is used to diagnose the failure of connected machining machines. This thesis proposes, in a first step, a conceptual framework for the structuring of heterogeneous knowledge and data bases, necessary to implement the DSS. Through a first traceability function, the system capitalizes the description of the characteristics of all particular events and malicious phenomena that may appear during machining. The diagnostic function allows to understand the causes of these failures and to propose improvement solutions, through the reuse of knowledge stored in the ontology and a rule-based reasoning. The proposed knowledge-based system is implemented in a global Decision Support Framework, developed as part of the ANR collaborative project called Smart Emma. A practical application has been made on two real databases from two different industrials.
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https://theses.hal.science/tel-03789795
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Submitted on : Tuesday, September 27, 2022 - 4:34:48 PM
Last modification on : Sunday, November 20, 2022 - 2:59:07 PM

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  • HAL Id : tel-03789795, version 1

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Oussama Meski. Développement d’un outil à base de connaissances pour l’aide à la décision dans le contexte de l’Industrie 4.0 : application au diagnostic des machines d’usinage à grande vitesse. Intelligence artificielle [cs.AI]. Université de Nantes (UN), FRA., 2021. Français. ⟨NNT : ⟩. ⟨tel-03789795⟩

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