{"id":205902,"date":"2024-08-08T04:00:56","date_gmt":"2024-08-08T03:00:56","guid":{"rendered":"https:\/\/www.artefact.com\/?post_type=blog&#038;p=205902"},"modified":"2024-10-28T17:28:14","modified_gmt":"2024-10-28T17:28:14","slug":"michelin-forvia-celonis-at-ai-for-industry-by-artefact-ai-for-automotive-state-of-the-art-use-cases","status":"publish","type":"blog","link":"https:\/\/www.artefact.com\/br\/blog\/michelin-forvia-celonis-at-ai-for-industry-by-artefact-ai-for-automotive-state-of-the-art-use-cases\/","title":{"rendered":"MICHELIN, FORVIA &amp; CELONIS na AI for Industry by Artefact - AI for Automotive: Estado da arte e casos de uso"},"content":{"rendered":"<p><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-1 fusion-flex-container nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--link_color: var(--awb-color6);--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-background-color:var(--awb-color1);--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:calc( 1440px + 20px );margin-left: calc(-20px \/ 2 );margin-right: calc(-20px \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-0 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:10px;--awb-margin-bottom-large:0px;--awb-spacing-left-large:10px;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:10px;--awb-spacing-left-medium:10px;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:10px;--awb-spacing-left-small:10px;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-1 description\" style=\"--awb-text-color:var(--awb-color5);--awb-text-font-family:&quot;PT Serif&quot;;--awb-text-font-style:normal;--awb-text-font-weight:400;\"><p>AI for Industry Summit by Artefact - 17 de setembro de 2024 - Paris<\/p>\n<p>Principais aprendizados do painel de discuss\u00e3o com Jean-Vianney Chiron, Gerente de Transforma\u00e7\u00e3o de IA da Michelin, Caroline Connan, Diretora do Grupo Data e Transforma\u00e7\u00e3o Digital da Forvia, e Prashant Dhanraj, Engenheiro L\u00edder de IA - Automotivo da Celonis.<br \/>\nModerado por Florence Benezit, diretora de consultoria da Artefact.<\/p>\n<\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-2 fusion-flex-container nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-background-color:var(--awb-color1);--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:calc( 1440px + 20px );margin-left: calc(-20px \/ 2 );margin-right: calc(-20px \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-1 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:10px;--awb-margin-bottom-large:0px;--awb-spacing-left-large:10px;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:10px;--awb-spacing-left-medium:10px;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:10px;--awb-spacing-left-small:10px;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div style=\"text-align:center;\"><a class=\"fusion-button button-flat fusion-button-default-size button-default fusion-button-default button-1 fusion-button-default-span fusion-button-default-type button-primary-medium\" style=\"--awb-margin-bottom:40px;--button_text_transform:var(--awb-custom_typography_2-text-transform);--button_font_size:var(--awb-custom_typography_2-font-size);--button_line_height:var(--awb-custom_typography_2-line-height);--button_typography-letter-spacing:var(--awb-custom_typography_2-letter-spacing);--button_typography-font-family:var(--awb-custom_typography_2-font-family);--button_typography-font-weight:var(--awb-custom_typography_2-font-weight);--button_typography-font-style:var(--awb-custom_typography_2-font-style);\" target=\"_self\" data-hover=\"text_slide_down\" href=\"https:\/\/marketing.artefact.com\/l\/597421\/2024-10-23\/j35tm6\" rel=\"noopener\"><div class=\"awb-button-text-transition  awb-button__hover-content--centered\"><span class=\"fusion-button-text awb-button__text awb-button__text--default\">Relat\u00f3rio de IA para o setor<\/span><span class=\"fusion-button-text awb-button__text awb-button__text--default\">Relat\u00f3rio de IA para o setor<\/span><\/div><\/a><\/div><\/div><\/div><\/div><\/div><article class=\"fusion-fullwidth fullwidth-box fusion-builder-row-3 fusion-flex-container nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--link_color: var(--awb-color6);--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-background-color:var(--awb-color1);--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-justify-content-center fusion-flex-content-wrap\" style=\"max-width:calc( 1440px + 20px );margin-left: calc(-20px \/ 2 );margin-right: calc(-20px \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-2 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:10px;--awb-margin-bottom-large:0px;--awb-spacing-left-large:10px;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:10px;--awb-spacing-left-medium:10px;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:10px;--awb-spacing-left-small:10px;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-video fusion-youtube\" style=\"--awb-max-width:670px;--awb-max-height:377px;--awb-align-self:center;--awb-width:100%;\"><div class=\"video-shortcode\"><div class=\"fluid-width-video-wrapper\" style=\"padding-top:56.27%;\" ><iframe title=\"Reprodutor de v\u00eddeo do YouTube 1\" src=\"https:\/\/www.youtube.com\/embed\/9WGhKTptW5I?wmode=transparent&autoplay=0\" width=\"670\" height=\"377\" allowfullscreen allow=\"autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture;\"><\/iframe><\/div><\/div><\/div><div class=\"fusion-title title fusion-title-1 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:var(--awb-color6);--awb-margin-bottom-small:8px;--awb-font-size:30px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"font-family:&quot;PT Serif&quot;;font-style:normal;font-weight:700;margin:0;letter-spacing:1.6px;font-size:1em;--fontSize:30;line-height:1.47;\">Introdu\u00e7\u00e3o \u00e0 IA para o setor automotivo<\/h2><\/div><div class=\"fusion-text fusion-text-2\" style=\"--awb-font-size:20px;--awb-line-height:1.6;--awb-letter-spacing:var(--awb-typography4-letter-spacing);--awb-text-transform:var(--awb-typography4-text-transform);--awb-text-color:var(--awb-color5);--awb-text-font-family:var(--awb-typography4-font-family);--awb-text-font-weight:var(--awb-typography4-font-weight);--awb-text-font-style:var(--awb-typography4-font-style);\"><p>A sess\u00e3o \u201cAI for Automotive\u201d contou com representantes importantes da Michelin, Forvia e Celonis, destacando como a IA est\u00e1 revolucionando o setor automotivo. A IA est\u00e1 transformando especialmente a otimiza\u00e7\u00e3o de processos, a manuten\u00e7\u00e3o preditiva e o controle de qualidade, por meio de aplica\u00e7\u00f5es reais de aprendizado de m\u00e1quina, vis\u00e3o computacional e IA generativa, remodelando as opera\u00e7\u00f5es automotivas.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-2 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:var(--awb-color6);--awb-margin-bottom-small:8px;--awb-font-size:30px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"font-family:&quot;PT Serif&quot;;font-style:normal;font-weight:700;margin:0;letter-spacing:1.6px;font-size:1em;--fontSize:30;line-height:1.47;\">O potencial transformador da IA na otimiza\u00e7\u00e3o de processos<\/h2><\/div><div class=\"fusion-text fusion-text-3\" style=\"--awb-font-size:20px;--awb-line-height:1.6;--awb-letter-spacing:var(--awb-typography4-letter-spacing);--awb-text-transform:var(--awb-typography4-text-transform);--awb-text-color:var(--awb-color5);--awb-text-font-family:var(--awb-typography4-font-family);--awb-text-font-weight:var(--awb-typography4-font-weight);--awb-text-font-style:var(--awb-typography4-font-style);\"><p>Prashant Dhanraj, da Celonis, enfatizou o potencial da IA para transformar os processos de neg\u00f3cios, como o desenvolvimento de produtos e o gerenciamento da cadeia de suprimentos. Ele explicou como os g\u00eameos digitais, modelos virtuais de processos f\u00edsicos, permitem que as empresas obtenham insights de grandes datasets e otimizem as opera\u00e7\u00f5es. Um exemplo \u00e9 o uso de IA generativa para estimativas de custo de novas pe\u00e7as, analisando desenhos t\u00e9cnicos, identificando pe\u00e7as semelhantes e sugerindo fornecedores. A IA tamb\u00e9m auxilia no gerenciamento de pedidos, usando LLMs para avaliar bloqueios de cr\u00e9dito em pedidos de vendas e fornecer recomenda\u00e7\u00f5es com base em data anteriores, aprimorando a tomada de decis\u00f5es.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-3 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:var(--awb-color6);--awb-margin-bottom-small:8px;--awb-font-size:30px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"font-family:&quot;PT Serif&quot;;font-style:normal;font-weight:700;margin:0;letter-spacing:1.6px;font-size:1em;--fontSize:30;line-height:1.47;\">Inova\u00e7\u00f5es baseadas em IA na Michelin<\/h2><\/div><div class=\"fusion-text fusion-text-4\" style=\"--awb-font-size:20px;--awb-line-height:1.6;--awb-letter-spacing:var(--awb-typography4-letter-spacing);--awb-text-transform:var(--awb-typography4-text-transform);--awb-text-color:var(--awb-color5);--awb-text-font-family:var(--awb-typography4-font-family);--awb-text-font-weight:var(--awb-typography4-font-weight);--awb-text-font-style:var(--awb-typography4-font-style);\"><p>Jean-Vianney Chiron, da Michelin, explicou como a IA melhora a fabrica\u00e7\u00e3o com vis\u00e3o computacional e an\u00e1lise de s\u00e9ries temporais. Na produ\u00e7\u00e3o de pneus, as c\u00e2meras com tecnologia de IA detectam defeitos na borracha, que s\u00e3o dif\u00edceis de inspecionar manualmente. A tecnologia garante maior qualidade do produto e agiliza o processo. Al\u00e9m disso, a IA correlaciona o data da m\u00e1quina, como temperatura e press\u00e3o, com a qualidade do produto final, melhorando a efici\u00eancia ao permitir que os trabalhadores resolvam problemas cr\u00edticos em vez de monitorar o data manualmente.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-4 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:var(--awb-color6);--awb-margin-bottom-small:8px;--awb-font-size:30px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"font-family:&quot;PT Serif&quot;;font-style:normal;font-weight:700;margin:0;letter-spacing:1.6px;font-size:1em;--fontSize:30;line-height:1.47;\">IA generativa para captura de conhecimento na Michelin<\/h2><\/div><div class=\"fusion-text fusion-text-5\" style=\"--awb-font-size:20px;--awb-line-height:1.6;--awb-letter-spacing:var(--awb-typography4-letter-spacing);--awb-text-transform:var(--awb-typography4-text-transform);--awb-text-color:var(--awb-color5);--awb-text-font-family:var(--awb-typography4-font-family);--awb-text-font-weight:var(--awb-typography4-font-weight);--awb-text-font-style:var(--awb-typography4-font-style);\"><p>Jean-Vianney Chiron destacou como a IA generativa ajuda a capturar d\u00e9cadas de conhecimento das f\u00e1bricas globais da Michelin. A equipe de manuten\u00e7\u00e3o pode inserir sintomas de m\u00e1quinas e receber sugest\u00f5es de diagn\u00f3stico com base em casos anteriores. O sistema aprende continuamente com o feedback do usu\u00e1rio, criando uma base de conhecimento robusta e em evolu\u00e7\u00e3o, acess\u00edvel em todo o mundo, melhorando o tempo de resposta aos problemas de manuten\u00e7\u00e3o.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-5 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:var(--awb-color6);--awb-margin-bottom-small:8px;--awb-font-size:30px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"font-family:&quot;PT Serif&quot;;font-style:normal;font-weight:700;margin:0;letter-spacing:1.6px;font-size:1em;--fontSize:30;line-height:1.47;\">Manuten\u00e7\u00e3o e controle de qualidade baseados em IA na Forvia<\/h2><\/div><div class=\"fusion-text fusion-text-6\" style=\"--awb-font-size:20px;--awb-line-height:1.6;--awb-letter-spacing:var(--awb-typography4-letter-spacing);--awb-text-transform:var(--awb-typography4-text-transform);--awb-text-color:var(--awb-color5);--awb-text-font-family:var(--awb-typography4-font-family);--awb-text-font-weight:var(--awb-typography4-font-weight);--awb-text-font-style:var(--awb-typography4-font-style);\"><p>Caroline Connan, da Forvia, compartilhou casos de uso semelhantes, incluindo IA para manuten\u00e7\u00e3o preditiva para evitar paradas na linha de produ\u00e7\u00e3o. Ao analisar o hist\u00f3rico data e os par\u00e2metros da m\u00e1quina em tempo real, a IA alerta os operadores sobre poss\u00edveis problemas, reduzindo o dispendioso tempo de inatividade. Um sistema baseado em LLM gera planos de manuten\u00e7\u00e3o e ajuda a priorizar as a\u00e7\u00f5es. Al\u00e9m disso, os sistemas de vis\u00e3o computacional alimentados por IA nas f\u00e1bricas da Forvia detectam defeitos de qualidade em interiores automotivos, reduzindo erros e melhorando a qualidade do produto.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-6 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-text-color:var(--awb-color6);--awb-margin-bottom-small:8px;--awb-font-size:30px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"font-family:&quot;PT Serif&quot;;font-style:normal;font-weight:700;margin:0;letter-spacing:1.6px;font-size:1em;--fontSize:30;line-height:1.47;\">Redu\u00e7\u00e3o do consumo de energia com IA na Michelin e na Forvia<\/h2><\/div><div class=\"fusion-text fusion-text-7\" style=\"--awb-font-size:20px;--awb-line-height:1.6;--awb-letter-spacing:var(--awb-typography4-letter-spacing);--awb-text-transform:var(--awb-typography4-text-transform);--awb-text-color:var(--awb-color5);--awb-text-font-family:var(--awb-typography4-font-family);--awb-text-font-weight:var(--awb-typography4-font-weight);--awb-text-font-style:var(--awb-typography4-font-style);\"><p>A Michelin e a Forvia usam IA para rastrear e reduzir o consumo de energia em suas f\u00e1bricas. Os modelos de aprendizado de m\u00e1quina analisam o sensor data em tempo real para monitorar o uso de eletricidade e \u00e1gua. Esses insights permitem que as empresas estabele\u00e7am metas, prevejam o consumo e ajustem as opera\u00e7\u00f5es para reduzir o impacto ambiental e os custos operacionais. A capacidade da IA de fornecer feedback em tempo real \u00e9 fundamental para atingir as metas de sustentabilidade.<\/p>\n<\/div><\/div><\/div><\/div><\/article><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-4 fusion-flex-container nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-background-color:var(--awb-color1);--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:calc( 1440px + 20px );margin-left: calc(-20px \/ 2 );margin-right: calc(-20px \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-3 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:10px;--awb-margin-bottom-large:0px;--awb-spacing-left-large:10px;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:10px;--awb-spacing-left-medium:10px;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:10px;--awb-spacing-left-small:10px;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div style=\"text-align:center;\"><a class=\"fusion-button button-flat fusion-button-default-size button-default fusion-button-default button-2 fusion-button-default-span fusion-button-default-type button-primary-medium\" style=\"--awb-margin-top:20px;--button_text_transform:var(--awb-custom_typography_2-text-transform);--button_font_size:var(--awb-custom_typography_2-font-size);--button_line_height:var(--awb-custom_typography_2-line-height);--button_typography-letter-spacing:var(--awb-custom_typography_2-letter-spacing);--button_typography-font-family:var(--awb-custom_typography_2-font-family);--button_typography-font-weight:var(--awb-custom_typography_2-font-weight);--button_typography-font-style:var(--awb-custom_typography_2-font-style);\" target=\"_self\" data-hover=\"text_slide_down\" href=\"https:\/\/marketing.artefact.com\/l\/597421\/2024-10-23\/j35tm6\" rel=\"noopener\"><div class=\"awb-button-text-transition  awb-button__hover-content--centered\"><span class=\"fusion-button-text awb-button__text awb-button__text--default\">Relat\u00f3rio de IA para o setor<\/span><span class=\"fusion-button-text awb-button__text awb-button__text--default\">Relat\u00f3rio de IA para o setor<\/span><\/div><\/a><\/div><\/div><\/div><\/div><\/div><\/p>","protected":false},"excerpt":{"rendered":"<p>Principais li\u00e7\u00f5es aprendidas no painel de discuss\u00e3o com Jean-Vianney Chiron, gerente de transforma\u00e7\u00e3o em IA da Michelin; Caroline Connan, diretora-geral de Data e transforma\u00e7\u00e3o digital do Grupo Forvia; e Prashant Dhanraj, engenheiro-chefe de IA \u2013 setor automotivo da Celonis, na C\u00fapula \u201cIA para a Ind\u00fastria\u201d organizada pela Artefact.<\/p>","protected":false},"featured_media":205903,"parent":0,"template":"","meta":{"_acf_changed":false,"ep_exclude_from_search":false},"blog-category":[21932],"blog-language":[2991],"class_list":["post-205902","blog","type-blog","status-publish","has-post-thumbnail","hentry","blog-category-industrial-energy-utilities","blog-language-en"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.artefact.com\/br\/wp-json\/wp\/v2\/blog\/205902","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.artefact.com\/br\/wp-json\/wp\/v2\/blog"}],"about":[{"href":"https:\/\/www.artefact.com\/br\/wp-json\/wp\/v2\/types\/blog"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.artefact.com\/br\/wp-json\/wp\/v2\/media\/205903"}],"wp:attachment":[{"href":"https:\/\/www.artefact.com\/br\/wp-json\/wp\/v2\/media?parent=205902"}],"wp:term":[{"taxonomy":"blog-category","embeddable":true,"href":"https:\/\/www.artefact.com\/br\/wp-json\/wp\/v2\/blog-category?post=205902"},{"taxonomy":"blog-language","embeddable":true,"href":"https:\/\/www.artefact.com\/br\/wp-json\/wp\/v2\/blog-language?post=205902"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}