{"id":10801,"date":"2024-03-11T15:08:23","date_gmt":"2024-03-11T15:08:23","guid":{"rendered":"https:\/\/novelis.io\/?post_type=research-lab&p=10801"},"modified":"2025-07-07T12:54:14","modified_gmt":"2025-07-07T12:54:14","slug":"ia-dans-les-infrastructures-industrielles","status":"publish","type":"research-lab","link":"https:\/\/novelis.io\/fr\/research-lab\/ia-dans-les-infrastructures-industrielles\/","title":{"rendered":"IA dans les infrastructures industrielles"},"content":{"rendered":"\n

D\u00e9couvrez les avanc\u00e9es r\u00e9centes dans l’application de l’IA aux infrastructures industrielles<\/p>\n\n\n\n

Aper\u00e7u de la maintenance pr\u00e9dictive des pompes dans les infrastructures civiles gr\u00e2ce \u00e0 l’IA<\/h3>\n\n\n\n
<\/div>\n\n\n\n
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La maintenance pr\u00e9dictive (PdM) est une strat\u00e9gie proactive qui utilise des analyses bas\u00e9es sur les donn\u00e9es, des m\u00e9thodes d’intelligence artificielle (IA) et des technologies avanc\u00e9es pour pr\u00e9dire les d\u00e9faillances potentielles d’\u00e9quipements. Par exemple, dans les infrastructures civiles, la maintenance des pompes peut b\u00e9n\u00e9ficier des techniques de PdM.<\/p>\n\n\n\n

Trois strat\u00e9gies principales de maintenance s’appliquent aux pompes dans les infrastructures civiles : la maintenance corrective, la maintenance pr\u00e9ventive et la maintenance pr\u00e9dictive (PdM). La maintenance corrective consiste \u00e0 diagnostiquer et r\u00e9parer les d\u00e9faillances apr\u00e8s leur apparition. La maintenance pr\u00e9ventive respecte un calendrier pr\u00e9d\u00e9fini, rempla\u00e7ant les pi\u00e8ces \u00e0 intervalles r\u00e9guliers, qu’elles soient us\u00e9es ou non. En revanche, la PdM utilise l\u2019analyse des donn\u00e9es en temps r\u00e9el pour anticiper les probl\u00e8mes. Gr\u00e2ce \u00e0 des capteurs, des informations comme les vibrations et la temp\u00e9rature sont collect\u00e9es et analys\u00e9es par des algorithmes de machine learning pour identifier des sch\u00e9mas annonciateurs de d\u00e9faillances.<\/p>\n\n\n\n

Une avanc\u00e9e technologique r\u00e9cente est le cadre de maintenance pr\u00e9dictive (PdM) activ\u00e9 par ADT, con\u00e7u sp\u00e9cifiquement pour les pompes des stations de traitement des eaux us\u00e9es (WWTP).<\/p>\n\n\n\n

Pourquoi est-ce essentiel ?<\/strong> Cette technologie est cruciale pour \u00e9viter les pannes inattendues, am\u00e9liorer la fiabilit\u00e9 du syst\u00e8me, r\u00e9duire les temps d’arr\u00eat et optimiser l’allocation des ressources. L’analyse des donn\u00e9es permet de d\u00e9tecter les probl\u00e8mes en amont, garantissant des op\u00e9rations efficaces et r\u00e9silientes pour les infrastructures essentielles.<\/p>\n\n\n\n

<\/div>\n\n\n\n

LCSA – Mod\u00e8le bas\u00e9 sur le Machine Learning<\/h3>\n\n\n\n

Intelligence artificielle pour une conception de b\u00e2timents plus intelligente et durable<\/p>\n\n\n\n

<\/div>\n\n\n\n
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Ces derni\u00e8res ann\u00e9es, l’intelligence artificielle (IA) s’est r\u00e9pandue dans de nombreux secteurs, de la sant\u00e9 \u00e0 la finance, en passant par la construction.<\/p>\n\n\n\n

Ce mois-ci, nous nous concentrons sur l’application de l’IA aux infrastructures industrielles, et notamment sur la construction. En particulier, nous explorons comment l’IA et le machine learning (ML) contribuent \u00e0 la conception de b\u00e2timents plus durables et \u00e0 la r\u00e9\u00e9valuation de l’impact environnemental des b\u00e2timents existants.<\/p>\n\n\n\n

Une technique pour r\u00e9duire les impacts environnementaux n\u00e9gatifs de l’industrie de la construction est l’\u00e9valuation des impacts d’un projet en amont gr\u00e2ce \u00e0 l’approche Life Cycle Sustainable Assessment (LCSA). Cette m\u00e9thode prend en compte les performances environnementales (Life Cycle Assessment, LCA), \u00e9conomiques (Life Cycle Costing, LCC) et sociales (Social Life Cycle Assessment, SLCA) sur l’ensemble du cycle de vie d’un b\u00e2timent, offrant ainsi une meilleure \u00e9valuation de sa durabilit\u00e9.<\/p>\n\n\n\n

Gr\u00e2ce \u00e0 un mod\u00e8le ML, les performances \u00e9nerg\u00e9tiques des b\u00e2timents peuvent \u00eatre pr\u00e9dites, simplifiant le calcul des indices LCA, LCC et SLCA. Ce qui est souvent une t\u00e2che longue et complexe devient ainsi plus simple et rapide.<\/p>\n\n\n\n

Pourquoi est-ce essentiel ?<\/strong> Cette m\u00e9thodologie permet d’\u00e9valuer et de rejeter rapidement les projets ayant des impacts d\u00e9favorables, tout en acceptant plus rapidement ceux qui sont plus durables, pour un avenir plus vert.<\/p>\n\n\n\n

<\/div>\n\n\n\n

Inspection de qualit\u00e9 intelligente<\/h3>\n\n\n\n

Inspection de qualit\u00e9 bas\u00e9e sur l’IA pour la fabrication<\/p>\n\n\n\n

<\/div>\n\n\n\n
\"\"<\/figure>\n\n\n\n

L’inspection de qualit\u00e9 est un processus critique pour garantir un syst\u00e8me de fabrication optimal et \u00e0 faible co\u00fbt. La pr\u00e9cision des inspections r\u00e9alis\u00e9es par des op\u00e9rateurs humains atteint environ 80 %. Une approche bas\u00e9e sur l’IA peut augmenter cette pr\u00e9cision jusqu’\u00e0 99,86 %.<\/p>\n\n\n\n

Le processus d’inspection de qualit\u00e9 intelligente (SQI) comprend six \u00e9tapes. La premi\u00e8re \u00e9tape consiste \u00e0 acheminer le produit vers la zone d’inspection et \u00e0 le placer \u00e0 un endroit sp\u00e9cifique. Une cam\u00e9ra haute r\u00e9solution capture des images du produit, et les conditions d’\u00e9clairage et la distance sont ajust\u00e9es. Ensuite, une architecture de r\u00e9seau neuronal convolutif (CNN) sur mesure d\u00e9tecte les d\u00e9fauts. Ce mod\u00e8le de d\u00e9tection de d\u00e9fauts est int\u00e9gr\u00e9 dans une application utilis\u00e9e sur le lieu de production. Lors de l’inspection, l’op\u00e9rateur utilise l’algorithme pour d\u00e9cider d’accepter ou de rejeter le produit. Les r\u00e9sultats sont ensuite stock\u00e9s automatiquement, facilitant le suivi et l’analyse.<\/p>\n\n\n\n

Pourquoi est-ce essentiel ?<\/strong> Cette technologie est cruciale pour surveiller l’\u00e9tat de l’environnement de production, pr\u00e9venir les r\u00e9parations impr\u00e9vues et d\u00e9tecter les produits d\u00e9fectueux, r\u00e9duisant ainsi les pertes potentielles.<\/p>\n","protected":false},"featured_media":10767,"template":"","categories":[510],"custom_tag":[],"class_list":["post-10801","research-lab","type-research-lab","status-publish","has-post-thumbnail","hentry","category-lab-news-2"],"acf":{"externel_link":"","summary":"","filter_opacity":"70","subtitle":"","reading_time":"","authors":"","document_to_download":{"upload_a_file":false,"download_without_form":false,"file":false,"url":""},"show_recent_block_on_the_bottom_of_the_page":false},"yoast_head":"\nIA dans les infrastructures industrielles<\/title>\n<meta name=\"description\" content=\"D\u00e9couvrez les avanc\u00e9es r\u00e9centes dans l'application de l'IA aux infrastructures industrielles\" \/>\n<meta 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