{"id":64571,"date":"2020-07-14T10:13:36","date_gmt":"2020-07-14T14:13:36","guid":{"rendered":"https:\/\/mayahtt.com\/siemens?content=blog"},"modified":"2020-12-08T09:41:05","modified_gmt":"2020-12-08T14:41:05","slug":"siemens","status":"publish","type":"post","link":"https:\/\/www.mayahtt.com\/fr\/blog\/siemens\/","title":{"rendered":"Siemens"},"content":{"rendered":"<h2>Application \u00e0 auto-apprentissage pour d\u00e9terminer les param\u00e8tres optimaux d\u2019une machine industrielle dans un environnement complexe<\/h2>\n<p>Les fabricants font face \u00e0 des d\u00e9fis importants en ce qui concerne le fonctionnement des machines de nos jours. Les machines de production complexes sont tr\u00e8s sensibles au changement des conditions de production et peuvent produire des pi\u00e8ces non conformes tr\u00e8s rapidement. Par exemple, la temp\u00e9rature ambiante, l\u2019humidit\u00e9 de l\u2019air et la qualit\u00e9 des mati\u00e8res premi\u00e8res provenant de diff\u00e9rents fournisseurs ont une grande incidence sur la qualit\u00e9 de la production. Souvent, ces facteurs peuvent \u00eatre mesur\u00e9s tout au long du processus de production et la qualit\u00e9 de la pi\u00e8ce fabriqu\u00e9e peut \u00eatre automatiquement qualifi\u00e9e. <\/p>\n<p>Toutefois, les processus de production ne sont pas tous enti\u00e8rement automatis\u00e9s, et des r\u00e9glages fins doivent \u00eatre effectu\u00e9s manuellement, conform\u00e9ment aux changements des conditions de production. Cela n\u00e9cessite une tr\u00e8s grande expertise de la part de l\u2019op\u00e9rateur de la machine. Avec un accroissement du nombre de facteurs ayant une influence, il est difficile pour l\u2019op\u00e9rateur d\u2019\u00e9tablir des corr\u00e9lations et de r\u00e9agir ad\u00e9quatement aux conditions de production changeantes.<\/p>\n<p>  En raison de la main-d\u2019\u0153uvre vieillissante, de plus en plus d\u2019op\u00e9rateurs de machine chevronn\u00e9s prennent leur retraite. Le transfert de tout ce savoir-faire sera bient\u00f4t un d\u00e9fi de taille.<\/p>\n<p>  L\u2019assistant de machine intelligent a \u00e9t\u00e9 con\u00e7u pour appuyer les op\u00e9rateurs \u00e0 trouver les bons param\u00e8tres sur leurs machines en vue de produire des pi\u00e8ces conformes de qualit\u00e9 dans des conditions de production changeantes. <\/p>\n<h2>L\u2019assistant de machine intelligent fournit les param\u00e8tres optimaux \u00e0 vos op\u00e9rateurs.<\/h2>\n<p>Cette solution est le fruit d\u2019une application normalis\u00e9e et de services personnalis\u00e9s afin qu\u2019elle soit adapt\u00e9e \u00e0 vos besoins. L\u2019application utilise des capacit\u00e9s d\u2019apprentissage machine pour d\u00e9terminer les relations inconnues des param\u00e8tres de la machine et des IRC. Elle formule des recommandations concr\u00e8tes \u00e0 l\u2019op\u00e9rateur de la machine pour le r\u00e9glage des param\u00e8tres de production pendant le fonctionnement afin d\u2019accro\u00eetre la qualit\u00e9 globale du produit et l\u2019efficacit\u00e9 de la machine.<\/p>\n<p>  Vous pouvez, gr\u00e2ce \u00e0 l\u2019assistant de machine intelligent, optimiser votre production en ayant sous la main le bon param\u00e9trage. <\/p>\n<p>Les visualisations intuitives vous aident \u00e0 identifier rapidement les mauvaises configurations des param\u00e8tres de la machine. Les recommandations fournies et les donn\u00e9es disponibles dans MindSphere vous aident \u00e0 d\u00e9terminer les causes profondes des baisses de production.<\/p>\n<p>  Lors de la premi\u00e8re \u00e9tape, les actifs concern\u00e9s de l\u2019atelier sont reli\u00e9s \u00e0 MindSphere et l\u2019assistant de machine intelligent sera configur\u00e9 par les experts de MindSphere. Par la suite, l\u2019assistant de machine intelligent recueillera les donn\u00e9es du processus de production, et apr\u00e8s un certain temps, les composantes d\u2019apprentissage machine feront leurs propres recommandations aux op\u00e9rateurs de machine. \u00c0 partir de ce moment, l\u2019assistant de machine intelligent assurera le recyclage continu du mod\u00e8le d\u2019apprentissage machine et fournira des recommandations \u00e0 l\u2019op\u00e9rateur de la machine au moyen de l\u2019interface utilisateur pr\u00e9fabriqu\u00e9e. <\/p>\n<h3>Caract\u00e9ristiques<\/h3>\n<ul>\n<li>La normalisation des donn\u00e9es sert \u00e0 cr\u00e9er des ensembles de donn\u00e9es coh\u00e9rentes relativement \u00e0 la configuration de la machine, \u00e0 l\u2019information de production et les donn\u00e9es de s\u00e9ries chronologiques d\u2019IdO.<\/li>\n<li>Les modules ax\u00e9s sur les r\u00e9seaux neuronaux cr\u00e9ent p\u00e9riodiquement des ensembles de donn\u00e9es de proposition et les enregistrent dans le plan de valeur d\u2019IdO.<\/li>\n<li>Visualisation intuitive des ensembles de donn\u00e9es de proposition dans une application normalis\u00e9e<\/li>\n<\/ul>\n<h3>Avantages<\/h3>\n<ul>\n<li>Permet aux op\u00e9rateurs industriels d\u2019am\u00e9liorer la productivit\u00e9 de la machine et des processus<\/li>\n<li>Am\u00e9liore la boucle de qualit\u00e9 des processus de production qui m\u00e8nent \u00e0 la r\u00e9duction des d\u00e9chets et l\u2019augmentation du traitement efficient des commandes<\/li>\n<li>Acc\u00e9l\u00e8re le processus d\u2019apprentissage exp\u00e9rimental pour les op\u00e9rateurs menant \u00e0 des am\u00e9liorations de productivit\u00e9 et une confiance aux op\u00e9rations de la machine<\/li>\n<li>Permet une \u00e9volutivit\u00e9 rapide et facile de multiples machines dans plusieurs r\u00e9seaux de production globale<\/li>\n<\/ul>\n<p><a href=\"\/brochures\/Siemens-MindSphere-MindAccess-IoT-Value-Plan-fs-66303-A20_tcm38-20913_tcm76-19173.pdf\" target=\"_blank\" rel=\"noopener noreferrer\"><strong>T\u00e9l\u00e9chargez la brochure<\/strong><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Application \u00e0 auto-apprentissage pour d\u00e9terminer les param\u00e8tres optimaux d\u2019une machine industrielle dans un environnement complexe<\/p>\n","protected":false},"author":1,"featured_media":63827,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[616,304,615],"tags":[],"class_list":["post-64571","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-developpement-dapplications-a-code-faible","category-histoires-de-reussites","category-ido-et-analyses"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - 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