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                <title xml:lang="fr">Vers l’aide au choix des paramètres de fabrication additive : application au procédé arc-fil (WAAM)</title>
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                <term xml:lang="fr">Fabrication Additive</term>
                <term xml:lang="fr">Optimisation multi critères</term>
                <term xml:lang="fr">Industrialisation</term>
                <term xml:lang="fr">paramètres de fabrication</term>
                <term xml:lang="fr">Aide Décision</term>
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              <p>Directed Energy Deposition (DED) processes are not widely used in industry. To contribute to their integration, it appears essential to handle both the quality of the produced parts and the sustainability of the manufacturing process. This paper presents a methodological framework to support the implementation of these technologies through the choice of relevant manufacturing parameters according to the targeted performances. It combines a genetic algorithm, suited to the optimisation of manufacturing parameters, the Nondominated Sorting Genetic Algorithm II (NSGA II) with a multi-criteria ranking algorithm. Thus, it brings the necessary interaction with the decision-maker, a high computational power and a simplicity of use for the decision maker. The proposed model has been developed for the optimisation of manufacturing parameters of the Wire Arc Additive Manufacturing (WAAM) process according to both mechanical characteristics (load bearing capacity and dimensional accuracy) and industrial criteria (cost and environmental impact). As this model aims to participate to the industrialisation of DED processes, it has therefore been designed to be transferable to a broad range of cases integrating various geometries, materials and DED processes.</p>
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              <p>Pour contribuer à l’intégration industrielle des procédés de fabrication additive métallique, la maitrise des performances relatives à la qualité des pièces produites et relatives au procédé de fabrication est impérative. Cet article propose un cadre méthodologique outillé pour faciliter la mise en œuvre de ces technologies via le choix de paramètres de fabrication pertinents. Il combine un algorithme génétique, adapté à l’optimisation de paramètres de fabrication, le Nondominated Sorting Genetic Algorithm II (NSGA II) à un algorithme de classement multicritères permettant ainsi une interaction avec le décideur, une puissance de calcul élevée et une simplicité d’utilisation pour le décideur. Le modèle proposé a été développé pour l’optimisation des paramètres de fabrication du procédé additif arc-fil (Wire Arc Additive Manufacturing - WAAM) en fonction de critères mécaniques (force maximale admissible et précision dimensionnelle) et industriels (coût et impact environnemental). Ce modèle vise à participer à l’industrialisation des procédés dits de dépôt de matière sous flux d’énergie dirigé (Directed Energy Deposition – DED). Ainsi, il a été conçu pour être applicable à des cas d’études variés intégrant diverses géométries, matériaux et procédés DED.</p>
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