{"id":3824,"date":"2025-10-16T14:21:10","date_gmt":"2025-10-16T14:21:10","guid":{"rendered":"https:\/\/aselcom.cl\/web\/?p=3824"},"modified":"2025-11-17T20:39:51","modified_gmt":"2025-11-17T20:39:51","slug":"prueba","status":"publish","type":"post","link":"https:\/\/aselcom.cl\/web\/2025\/10\/16\/prueba\/","title":{"rendered":"IA al servicio de la continuidad operativa"},"content":{"rendered":"<p><strong>De la auditor\u00eda el\u00e9ctrica al mantenimiento predictivo, con foco en uptime y seguridad<\/strong><\/p>\n<p>\u201cLa IA es la nueva electricidad.\u201d \u2014 <em>Andrew Ng<\/em> (pionero de Google Brain) \u2014 una manera precisa de explicar c\u00f3mo esta tecnolog\u00eda est\u00e1 permeando procesos cr\u00edticos y elevando los est\u00e1ndares de disponibilidad en infraestructuras el\u00e9ctricas y de data center. <a href=\"http:\/\/gsb.stanford.edu\/\"><strong>gsb.stanford.edu<\/strong><\/a><\/p>\n<p><strong>\u00bfPor qu\u00e9 ahora?<\/strong><\/p>\n<p>La demanda de cargas de trabajo de IA y las restricciones de capacidad el\u00e9ctrica est\u00e1n presionando a las operaciones cr\u00edticas para ser m\u00e1s eficientes y resilientes. Como resume <strong>Andy Lawrence<\/strong> (Uptime Institute): los operadores deben \u201canticipar m\u00faltiples cambios tecnol\u00f3gicos\u2026 y prepararse para una demanda impredecible de IA\u201d, manteniendo la continuidad del negocio. <a href=\"http:\/\/datacenterdynamics.com\/\"><strong>datacenterdynamics.com<\/strong><\/a><\/p>\n<p>Los n\u00fameros acompa\u00f1an: programas anal\u00edticos y de mantenimiento predictivo (PdM) han demostrado <strong>reducir costos de mantenimiento en 18\u201325%<\/strong> y <strong>recortar downtime no planificado hasta 50%<\/strong>, adem\u00e1s de <strong>extender la vida \u00fatil de activos<\/strong>. Estas mejoras, reportadas en investigaciones de McKinsey y an\u00e1lisis industriales recientes, muestran el salto de valor al pasar de mantenimiento reactivo a predictivo. <a href=\"https:\/\/www.mckinsey.com\/capabilities\/operations\/our-insights\/establishing-the-right-analytics-based-maintenance-strategy?utm_source=chatgpt.com\"><strong>McKinsey &amp; Company+1<\/strong><\/a><a href=\"https:\/\/www.iiot-world.com\/predictive-analytics\/predictive-maintenance\/predictive-maintenance-cost-savings\/?utm_source=chatgpt.com\"><strong>IIoT World<\/strong><\/a><\/p>\n<p><strong>\u00bfC\u00f3mo lo aplicamos en Aselcom?<\/strong><\/p>\n<p><strong>1) Auditor\u00edas el\u00e9ctricas potenciadas por IA<\/strong><\/p>\n<ul>\n<li><strong>An\u00e1lisis de calidad de energ\u00eda<\/strong> (THD, flicker, arm\u00f3nicos, transitorios): la IA detecta patrones an\u00f3malos y <em>drift<\/em> en perfiles de carga que, a simple vista, se pierden.<\/li>\n<li><strong>Gemelos digitales<\/strong> para planificaci\u00f3n y operaci\u00f3n: el ecosistema Schneider Electric + NVIDIA avanza en \u201cdigital twins\u201d de centros de datos para optimizar uso de energ\u00eda y operaci\u00f3n, acelerando dise\u00f1o y decisiones de mantenimiento. Esto reduce riesgos y tiempos de intervenci\u00f3n. <a href=\"https:\/\/www.barrons.com\/articles\/nvidia-schneider-data-centers-stock-d21c3569?utm_source=chatgpt.com\"><strong>Barron&#8217;s<\/strong><\/a><\/li>\n<li><strong>Priorizaci\u00f3n de riesgos<\/strong>: modelos que cruzan severidad el\u00e9ctrica, criticidad del proceso y probabilidad de fallo para priorizar mitigaciones con mayor impacto en continuidad.<\/li>\n<\/ul>\n<p>\u201cLa IA es genial, pero solo si se adapta al negocio, no al rev\u00e9s.\u201d \u2014 <em>Kevin Brown, Schneider Electric<\/em> (sobre c\u00f3mo la tecnolog\u00eda debe servir a la operaci\u00f3n). <a href=\"http:\/\/datacenterdynamics.com\/\"><strong>datacenterdynamics.com<\/strong><\/a><\/p>\n<p><strong>2) Mantenimiento predictivo en UPS y distribuci\u00f3n<\/strong><\/p>\n<ul>\n<li><strong>Salud de bater\u00edas<\/strong> (impedancia, temperatura, ciclos, <em>state of health<\/em>): modelos de degradaci\u00f3n anticipan capacidad remanente y ventanas \u00f3ptimas de recambio.<\/li>\n<li><strong>Activos de potencia<\/strong> (IGBT, ventilaci\u00f3n, contactores, STS, transformadores y tableros): detecci\u00f3n temprana de sobrecalentamientos, vibraciones y desbalances de carga.<\/li>\n<li><strong>Ecosistema Schneider EcoStruxure&#x2122;<\/strong>: plataformas como <strong>IT Expert<\/strong> y <strong>Asset\/Advisor<\/strong> habilitan monitoreo avanzado, recomendaciones data-driven y PdM a nivel sistema. <a href=\"https:\/\/www.se.com\/us\/en\/product-range\/65972-ecostruxure-it-expert\/?utm_source=chatgpt.com\"><strong>Schneider Electric+2Schneider Electric+2<\/strong><\/a><\/li>\n<li><strong>Resultados de referencia<\/strong>: casos recientes reportan <strong>-40% intervenciones on-site<\/strong> y <strong>-20% OPEX<\/strong> al transitar hacia modelos de servicio predictivos. <a href=\"https:\/\/www.compassdatacenters.com\/news\/compass-and-schneider-electric-utilize-ai-to-transform-data-center-maintenance\/?utm_source=chatgpt.com\"><strong>Compass Datacenters<\/strong><\/a><\/li>\n<\/ul>\n<p><strong>3) Monitoreo continuo (NOC) + gesti\u00f3n de tickets<\/strong><\/p>\n<ul>\n<li>Integraci\u00f3n de eventos el\u00e9ctricos, sensores ambientales y telemetr\u00eda de UPS\/PDUs en una <strong>plataforma de tickets con manejo de incidencias<\/strong>.<\/li>\n<li>La IA filtra ruido, correlaciona eventos y sugiere <strong>acciones prescriptivas<\/strong>; el equipo t\u00e9cnico valida y ejecuta, cerrando el ciclo con lecciones aprendidas.<\/li>\n<\/ul>\n<p><strong>Casos de uso t\u00edpicos<\/strong><\/p>\n<ul>\n<li><strong>Auditor\u00edas con IA<\/strong>: identifica arm\u00f3nicos de 5.\u00ba\/7.\u00ba que elevan p\u00e9rdidas y temperatura en barras; recomienda filtros\/redistribuci\u00f3n de carga.<\/li>\n<li><strong>PdM de UPS<\/strong>: alerta por incremento an\u00f3malo de impedancia en cadenas VRLA\/Li-ion tras picos t\u00e9rmicos; agenda recambio selectivo antes del punto de inflexi\u00f3n.<\/li>\n<li><strong>Clima y contenci\u00f3n<\/strong>: correlaci\u00f3n de <em>hotspots<\/em> con cargas AI\/ML; simulaci\u00f3n r\u00e1pida con gemelos digitales para ajustar flujo de aire o considerar <em>liquid cooling<\/em> (tendencia acelerada por cargas de IA). <a href=\"https:\/\/www.networkworld.com\/article\/967974\/data-center-liquid-cooling-to-gain-momentum.html?utm_source=chatgpt.com\"><strong>Network World<\/strong><\/a><\/li>\n<\/ul>\n<p><strong>Metodolog\u00eda de implementaci\u00f3n (4 pasos pr\u00e1cticos)<\/strong><\/p>\n<ol>\n<li><strong>Baseline &amp; datos<\/strong>: puntos de medici\u00f3n PQ, inventario de activos cr\u00edticos, histograma de fallas, SLA\/SLI.<\/li>\n<li><strong>Modelado<\/strong>: elegir variables sensibles (THD, PF, temp., vibraci\u00f3n, ciclos bater\u00eda), entrenar modelos con <em>labels<\/em> de incidentes reales.<\/li>\n<li><strong>Automatizaci\u00f3n<\/strong>: umbrales din\u00e1micos, alarmas inteligentes y creaci\u00f3n autom\u00e1tica de tickets con runbooks.<\/li>\n<li><strong>Mejora continua<\/strong>: <em>post-mortems<\/em> y <em>feature engineering<\/em> (nuevas variables\/umbrales) para reducir falsos positivos y tiempo medio de reparaci\u00f3n (MTTR).<\/li>\n<\/ol>\n<p><strong>KPIs esperados (con respaldo de la literatura)<\/strong><\/p>\n<ul>\n<li><strong>-18\u201325%<\/strong> en costos de mantenimiento (optimizaci\u00f3n de intervenciones\/stock). <a href=\"https:\/\/www.mckinsey.com\/capabilities\/operations\/our-insights\/establishing-the-right-analytics-based-maintenance-strategy?utm_source=chatgpt.com\"><strong>McKinsey &amp; Company<\/strong><\/a><\/li>\n<li><strong>-25\u201350%<\/strong> en downtime no planificado en activos cr\u00edticos. <a href=\"https:\/\/www.mckinsey.com\/capabilities\/operations\/our-insights\/transforming-advanced-manufacturing-through-industry-4-0?utm_source=chatgpt.com\"><strong>McKinsey &amp; Company<\/strong><\/a><a href=\"https:\/\/www.iiot-world.com\/predictive-analytics\/predictive-maintenance\/predictive-maintenance-cost-savings\/?utm_source=chatgpt.com\"><strong>IIoT World<\/strong><\/a><\/li>\n<li><strong>+20\u201340%<\/strong> de vida \u00fatil de activos seleccionados (bater\u00edas\/equipos rotativos). <a href=\"https:\/\/www.iiot-world.com\/predictive-analytics\/predictive-maintenance\/predictive-maintenance-cost-savings\/?utm_source=chatgpt.com\"><strong>IIoT World<\/strong><\/a><\/li>\n<\/ul>\n<p><strong>Gobernanza, seguridad y personas<\/strong><\/p>\n<p>La adopci\u00f3n responsable importa: algunos operadores a\u00fan desconf\u00edan del \u201cpiloto autom\u00e1tico\u201d total. Uptime Institute ha observado una <strong>ca\u00edda en la confianza<\/strong> de usar IA directamente en operaciones, a pesar de sus beneficios: la clave es mantener <strong>al humano en el loop<\/strong>, con trazabilidad de decisiones y ciberseguridad reforzada. <a href=\"http:\/\/upsite.com\/\"><strong>upsite.com<\/strong><\/a><\/p>\n<p><strong>Conclusi\u00f3n (y propuesta de valor)<\/strong><\/p>\n<p>En continuidad operativa, <strong>la IA no reemplaza al equipo t\u00e9cnico: lo potencia<\/strong>. Combinada con auditor\u00edas el\u00e9ctricas rigurosas y mantenimiento predictivo, permite <strong>ver antes de que ocurra<\/strong>, priorizar lo que impacta el negocio y sostener SLAs exigentes con costos controlados. En Aselcom \u2014<strong>ISO 9001<\/strong> y <strong>partner de Schneider Electric (APC)<\/strong>\u2014 integramos estas pr\u00e1cticas en proyectos llave en mano para data centers, laboratorios, telecom y entornos industriales, con un enfoque simple: <strong>menos fallas, menos sorpresas, m\u00e1s disponibilidad<\/strong>.<\/p>\n<p>\u00bfConversamos? Podemos evaluar en una visita t\u00e9cnica:<\/p>\n<ol>\n<li>tu l\u00ednea base de riesgos el\u00e9ctricos,<\/li>\n<li>el potencial de PdM en UPS y distribuci\u00f3n, y<\/li>\n<li>un <em>roadmap<\/em> de 90 d\u00edas para empezar con <em>quick wins<\/em> medibles.<\/li>\n<\/ol>\n<p><strong>Referencias seleccionadas<\/strong><\/p>\n<ul>\n<li>Andrew Ng, \u201cAI is the New Electricity\u201d (Stanford GSB). <a href=\"http:\/\/gsb.stanford.edu\/\"><strong>gsb.stanford.edu<\/strong><\/a><\/li>\n<li>McKinsey, estrategias de mantenimiento basadas en anal\u00edtica y casos de PdM. <a href=\"https:\/\/www.mckinsey.com\/capabilities\/operations\/our-insights\/establishing-the-right-analytics-based-maintenance-strategy?utm_source=chatgpt.com\"><strong>McKinsey &amp; Company+1<\/strong><\/a><\/li>\n<li>IIoT-World, s\u00edntesis 2025 de ahorros y reducciones de downtime con PdM. <a href=\"https:\/\/www.iiot-world.com\/predictive-analytics\/predictive-maintenance\/predictive-maintenance-cost-savings\/?utm_source=chatgpt.com\"><strong>IIoT World<\/strong><\/a><\/li>\n<li>Uptime Institute \/ Andy Lawrence, retos de operaci\u00f3n con cargas de IA (2025). <a href=\"http:\/\/datacenterdynamics.com\/\"><strong>datacenterdynamics.com<\/strong><\/a><\/li>\n<li>Barron\u2019s, alianza <strong>NVIDIA\u2013Schneider Electric<\/strong> para \u201cdigital twins\u201d de data centers. <a href=\"https:\/\/www.barrons.com\/articles\/nvidia-schneider-data-centers-stock-d21c3569?utm_source=chatgpt.com\"><strong>Barron&#8217;s<\/strong><\/a><\/li>\n<li>Schneider Electric, <strong>EcoStruxure&#x2122; IT\/Asset Advisor<\/strong> y soluciones de mantenimiento predictivo. <a href=\"https:\/\/www.se.com\/us\/en\/product-range\/65972-ecostruxure-it-expert\/?utm_source=chatgpt.com\"><strong>Schneider Electric+2Schneider Electric+2<\/strong><\/a><\/li>\n<\/ul>\n<p><em>La IA bien aplicada no es un costo; es un multiplicador de continuidad.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>IA aplicada a auditor\u00edas el\u00e9ctricas y mantenimiento predictivo mejora continuidad, reduce fallas, optimiza activos y asegura mayor disponibilidad operativa.<\/p>\n","protected":false},"author":3,"featured_media":3994,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"image","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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