{"id":143420,"date":"2021-05-12T04:37:00","date_gmt":"2021-05-12T04:37:00","guid":{"rendered":"https:\/\/alliedtelesisprod.smmile.com\/gestion-intelligente-des-actifs-surfer-sur-la-vague-de-la-maintenance-predictive\/"},"modified":"2026-05-29T17:23:29","modified_gmt":"2026-05-29T17:23:29","slug":"intelligent-asset-management-riding-wave-predictive-maintenance","status":"publish","type":"post","link":"https:\/\/alliedtelesisprod.smmile.com\/fr\/intelligent-asset-management-riding-wave-predictive-maintenance\/","title":{"rendered":"Gestion intelligente des actifs : Surfer sur la vague de la maintenance pr\u00e9dictive"},"content":{"rendered":"<p>Les op\u00e9rations de maintenance et de r\u00e9paration (MRO) comptent parmi les activit\u00e9s les plus importantes des organisations industrielles modernes. Elles permettent aux entreprises de fonctionner sans heurts et ont un impact significatif sur la productivit\u00e9 et les r\u00e9sultats. Une partie importante des op\u00e9rations de maintenance et de r\u00e9paration concerne la gestion et la maintenance des actifs physiques tels que les machines et les outils utilis\u00e9s dans les op\u00e9rations de production. C&#8217;est pourquoi les entreprises investissent massivement dans des m\u00e9thodes nouvelles et intelligentes de gestion de leurs actifs.<\/p>\n<p>L&#8217;approche la plus simple de la maintenance des actifs est la maintenance r\u00e9active. Dans le cadre de la maintenance r\u00e9active, les actifs sont r\u00e9par\u00e9s ou remplac\u00e9s lorsqu&#8217;ils tombent en panne. La maintenance r\u00e9active n&#8217;est pas tr\u00e8s efficace : elle entra\u00eene souvent des arr\u00eats de production car les op\u00e9rations doivent \u00eatre interrompues pendant le remplacement de l&#8217;actif. C&#8217;est pourquoi la plupart des entreprises utilisent un autre mod\u00e8le de maintenance pour les actifs cl\u00e9s, appel\u00e9 maintenance pr\u00e9ventive. Cette m\u00e9thode consiste \u00e0 remplacer ou \u00e0 entretenir les actifs avant leur fin de vie nominale. En \u00e9tant proactive, elle permet d&#8217;\u00e9viter les temps d&#8217;arr\u00eat catastrophiques, car la fin de vie des actifs n&#8217;est jamais atteinte. Ce n&#8217;est pas la m\u00e9thode la plus rentable, car la dur\u00e9e de vie du produit peut \u00eatre r\u00e9duite, c&#8217;est pourquoi la maintenance conditionnelle est \u00e9galement une option.<\/p>\n<p>La maintenance conditionnelle remplace ou entretient un bien en fonction de son \u00e9tat r\u00e9el. Elle est utilis\u00e9e pour entretenir le bien avant qu&#8217;une panne ne se produise. L&#8217;un des types de maintenance conditionnelle les plus populaires est la maintenance pr\u00e9dictive. Elle s&#8217;appuie sur les pr\u00e9visions relatives \u00e0 la dur\u00e9e de vie utile restante (RUL) et \u00e0 la fin de vie (EoL) de l&#8217;actif pour programmer la maintenance au moment le plus opportun. La maintenance pr\u00e9dictive permet d&#8217;\u00e9viter les temps d&#8217;arr\u00eat catastrophiques, tout en optimisant l&#8217;efficacit\u00e9 globale de l&#8217;\u00e9quipement (OEE). N\u00e9anmoins, la mise en \u0153uvre d&#8217;une approche de maintenance pr\u00e9dictive est un d\u00e9fi, car il n&#8217;existe pas de moyen facile de pr\u00e9dire et d&#8217;anticiper les d\u00e9faillances des actifs industriels.<\/p>\n<p>Ces derni\u00e8res ann\u00e9es, l&#8217;av\u00e8nement de l&#8217;industrie 4.0 permet aux entreprises de collecter de grandes quantit\u00e9s de donn\u00e9es num\u00e9riques sur leurs syst\u00e8mes de production. Cela facilite la mise en \u0153uvre de la maintenance pr\u00e9dictive et entra\u00eene des avantages \u00e9conomiques tangibles. La maintenance pr\u00e9dictive est l&#8217;une des applications les plus populaires de l&#8217;industrie 4.0 pour deux raisons : son retour sur investissement (ROI) av\u00e9r\u00e9 et sa large applicabilit\u00e9 dans presque tous les secteurs industriels, y compris la fabrication, le p\u00e9trole et le gaz, l&#8217;exploitation mini\u00e8re, les b\u00e2timents intelligents et plus encore.<\/p>\n<h2>Estimation de la dur\u00e9e de vie utile restante \u00e0 l&#8217;aide de l&#8217;analyse pr\u00e9dictive<\/h2>\n<p>Le d\u00e9veloppement de solutions de maintenance pr\u00e9dictive s&#8217;appuie sur de grands volumes de donn\u00e9es num\u00e9riques provenant de capteurs, de syst\u00e8mes de production et d&#8217;applications d&#8217;entreprise. Ces donn\u00e9es sont trait\u00e9es par des algorithmes d&#8217;analyse avanc\u00e9s tels que l&#8217;apprentissage automatique (ML) et l&#8217;intelligence artificielle (IA), afin d&#8217;aider \u00e0 \u00e9valuer l&#8217;\u00e9tat de l&#8217;\u00e9quipement. Les algorithmes d&#8217;analyse pr\u00e9dictive sont appliqu\u00e9s aux donn\u00e9es provenant de divers dispositifs tels que les capteurs de vibration, les capteurs de temp\u00e9rature, les capteurs de consommation d&#8217;\u00e9nergie, les capteurs acoustiques, les dispositifs \u00e0 ultrasons et les dispositifs d&#8217;imagerie thermique. Des informations suppl\u00e9mentaires provenant de syst\u00e8mes d&#8217;information commerciale (par exemple, des syst\u00e8mes ERP (Enterprise Resource Planning)) sont exploit\u00e9es, y compris, par exemple, des informations sur la qualit\u00e9 de la production et des donn\u00e9es d&#8217;analyse de l&#8217;huile des machines. Les \u00e9l\u00e9ments d&#8217;information susmentionn\u00e9s fournissent des informations utiles sur le fonctionnement et l&#8217;\u00e9tat de l&#8217;actif.<\/p>\n<p>Un syst\u00e8me int\u00e9gr\u00e9 de maintenance pr\u00e9dictive comprend les sous-syst\u00e8mes suivants :<\/p>\n<ul>\n<li><strong>Un sous-syst\u00e8me de collecte de donn\u00e9es<\/strong>, qui assure la collecte fiable de donn\u00e9es provenant de capteurs et de syst\u00e8mes de production. Dans la plupart des cas, le syst\u00e8me de collecte de donn\u00e9es est un syst\u00e8me Big Data qui traite les donn\u00e9es en continu avec une forte ingestion et des donn\u00e9es au repos. Le syst\u00e8me est dot\u00e9 d&#8217;une infrastructure r\u00e9seau robuste, configur\u00e9e pour r\u00e9pondre aux besoins en bande passante des diff\u00e9rents flux de donn\u00e9es.<\/li>\n<li><strong>Un sous-syst\u00e8me d&#8217;analyse pr\u00e9dictive<\/strong>, qui traite les donn\u00e9es des capteurs pour fournir des estimations de temps pour la maintenance. Ce sous-syst\u00e8me comprend des algorithmes d&#8217;analyse avanc\u00e9s tels que l&#8217;analyse statistique et les techniques d&#8217;exploration de donn\u00e9es comme l&#8217;apprentissage automatique et l&#8217;apprentissage profond (DL). Ces derni\u00e8res ann\u00e9es, les techniques d&#8217;apprentissage profond sont pr\u00e9f\u00e9r\u00e9es aux techniques de ML conventionnelles en raison de leur pr\u00e9cision. Cependant, l&#8217;utilisation de mod\u00e8les DL n\u00e9cessite plus de donn\u00e9es que les algorithmes ML traditionnels.<\/li>\n<li><strong>Un sous-syst\u00e8me de visualisation<\/strong>, qui pr\u00e9sente des informations pr\u00e9dictives aux ing\u00e9nieurs et techniciens de maintenance. Par exemple, les pr\u00e9visions concernant l&#8217;\u00e9tat de sant\u00e9 des actifs sont visualis\u00e9es dans des tableaux de bord appropri\u00e9s. Les informations peuvent \u00eatre visualis\u00e9es sous la forme de cyber-repr\u00e9sentations de r\u00e9alit\u00e9 augment\u00e9e (RA) et de r\u00e9alit\u00e9 virtuelle (RV).<\/li>\n<li><strong>Un sous-syst\u00e8me d&#8217;actionnement et de contr\u00f4le<\/strong>, qui exploite des informations pr\u00e9dictives pour programmer des op\u00e9rations de maintenance ou pour configurer le fonctionnement de syst\u00e8mes de production. Ce sous-syst\u00e8me peut interagir avec les applications de l&#8217;entreprise (par exemple, les syst\u00e8mes ERP et de gestion des actifs) pour identifier le meilleur moment pour programmer la maintenance. Dans cette optique, l&#8217;\u00e9tat des ordres de production en attente est pris en compte. De m\u00eame, le sous-syst\u00e8me de commande et de contr\u00f4le configure les op\u00e9rations des machines en vue de prolonger leur dur\u00e9e de vie.<\/li>\n<\/ul>\n<h2>L&#8217;essor des actifs en tant que services<\/h2>\n<p>Au-del\u00e0 de la r\u00e9duction des temps d&#8217;arr\u00eat et de l&#8217;augmentation de l&#8217;efficacit\u00e9 \u00e9nerg\u00e9tique, la maintenance pr\u00e9dictive permet une s\u00e9rie de nouveaux mod\u00e8les commerciaux de maintenance d&#8217;entreprise bas\u00e9s sur le paradigme &#8220;Asset-as-a-Service&#8221; (AaaS). Ce paradigme permet aux \u00e9quipementiers de facturer leurs produits en fonction de leur utilisation, plut\u00f4t que sur la base d&#8217;un prix initial fixe. \u00c0 cette fin, ils exploitent les informations relatives \u00e0 l&#8217;\u00e9tat et \u00e0 la sant\u00e9 des actifs pour planifier les op\u00e9rations de maintenance, de r\u00e9paration et de service sur le terrain. De m\u00eame, ils offrent une visibilit\u00e9 sur l&#8217;\u00e9tat des actifs et les op\u00e9rations de maintenance qui doivent \u00eatre effectu\u00e9es sur eux. Dans ce contexte, il est \u00e9galement possible de mettre en \u0153uvre des mod\u00e8les de maintenance en tant que service (MaaS), qui facturent aux clients la fourniture d&#8217;informations sur la maintenance et la r\u00e9paration des actifs.<\/p>\n<p>\u00c0 l&#8217;avenir, MaaS et AaaS offriront aux entreprises industrielles une plus grande flexibilit\u00e9 pour la planification de leurs op\u00e9rations de MRO. Par exemple, les fabricants n&#8217;auront plus \u00e0 se d\u00e9barrasser de contrats de maintenance co\u00fbteux. Ils pourront au contraire payer les services de maintenance en fonction de l&#8217;utilisation de l&#8217;actif.<\/p>\n<p>Les infrastructures et technologies num\u00e9riques telles que les infrastructures de r\u00e9seau \u00e0 haut d\u00e9bit, les plateformes Big Data et les technologies d&#8217;analyse avanc\u00e9e sont les principaux piliers des solutions de maintenance pr\u00e9dictive. Les solutions d&#8217;Allied Telesis offrent de solides propositions de valeur lorsqu&#8217;il s&#8217;agit de mettre en \u0153uvre des plateformes d&#8217;acquisition de donn\u00e9es fiables pour la maintenance pr\u00e9dictive. Par exemple, la solution Total Autonomous Networking d&#8217;Allied Telesis permet aux entreprises manufacturi\u00e8res de centraliser le contr\u00f4le et la gestion de plusieurs appareils, tout en prenant en charge les services de r\u00e9cup\u00e9ration et de provisionnement, toujours importants. La solution offre des capacit\u00e9s de configuration r\u00e9seau polyvalentes bas\u00e9es sur l&#8217;analyse du trafic sans fil. Plus pr\u00e9cis\u00e9ment, l&#8217;analyse du trafic permet de comprendre comment configurer au mieux le r\u00e9seau pour r\u00e9pondre \u00e0 la demande. Elle facilite \u00e9galement la mise en place de solutions WAN hautes performances, qui garantissent que les donn\u00e9es de maintenance provenant de diff\u00e9rents appareils peuvent \u00eatre diffus\u00e9es de mani\u00e8re fiable vers le nuage.<\/p>\n<p>Une autre option est la <a data-entity-substitution=\"canonical\" data-entity-type=\"node\" data-entity-uuid=\"b1b43f5a-c4ee-4cf5-abca-3ef0bf4f6fdc\" href=\"https:\/\/alliedtelesisprod.smmile.com\/solutions\/cybersecurity\/\">solution de s\u00e9curit\u00e9 Self-Defending Networks<\/a> d&#8217;Allied Telesis, qui automatise la configuration et l&#8217;application de politiques de s\u00e9curit\u00e9 complexes au niveau de la p\u00e9riph\u00e9rie et du nuage des solutions de maintenance pr\u00e9dictive. Cette solution peut consid\u00e9rablement renforcer la confiance et la fiabilit\u00e9 des d\u00e9ploiements de maintenance pr\u00e9dictive, ce qui est tr\u00e8s important pour prot\u00e9ger les entreprises industrielles contre les dispositifs non fiables et les attaques adverses.<\/p>\n<p>Dans l&#8217;ensemble, Allied Telesis fournit les bases d&#8217;une infrastructure de r\u00e9seau industriel robuste, s\u00e9curis\u00e9e et de haute performance, qui garantit le flux appropri\u00e9 des donn\u00e9es de maintenance de l&#8217;atelier au nuage. Il s&#8217;agit l\u00e0 d&#8217;une base solide pour un d\u00e9ploiement r\u00e9ussi et rentable de la maintenance pr\u00e9dictive.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Maintenance and Repair Operations (MRO) are among the most important activities of modern industrial organizations.<\/p>\n","protected":false},"author":3,"featured_media":116854,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"location":[],"markets":[7278],"partners":[],"posttype":[7993],"products":[8012],"services":[],"solutions":[8174,8168,8175],"site_tags":[8154,8151],"technologies":[],"class_list":["post-143420","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","markets-manufacturingindustrial","posttype-blogpost","products-industrialswitches","solutions-industrialsolutions","solutions-networkautomation","solutions-smartbuilding","site_tags-manufacturing","site_tags-self-defendingnetworks"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Gestion intelligente des actifs : Surfer sur la vague de la maintenance pr\u00e9dictive - Allied 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