{"id":157111,"date":"2026-07-20T07:33:19","date_gmt":"2026-07-20T06:33:19","guid":{"rendered":"https:\/\/univga.org\/intelligence-artificielle-alliages-metallurgie\/"},"modified":"2026-07-20T07:33:19","modified_gmt":"2026-07-20T06:33:19","slug":"artificial-intelligence-metal-alloys-metallurgy","status":"publish","type":"post","link":"https:\/\/univga.org\/en\/intelligence-artificielle-alliages-metallurgie\/","title":{"rendered":"How does artificial intelligence help metallurgists?"},"content":{"rendered":"<div class=\"veille-intro\">\n<p>Imagine that, in a small and medium-sized industrial enterprise in Moanda, a maintenance team replaces parts exposed to dust, shocks, and heat every month. Downtime is costly. The manager hesitates: should he import standard parts again or test new metal alloys designed with artificial intelligence (AI)?<\/p>\n<p>In a university, a laboratory wants to train its students in this approach. Not to replace engineers, but to better select tests, reduce trial and error, and prepare materials useful for mines, furnaces, and metallurgical workshops.<\/p>\n<\/div>\n<aside class=\"veille-oneminute\">\n<p class=\"veille-oneminute__label\">What to remember in 1 minute<\/p>\n<ul>\n<li>On July 13, 2026, the University of Toronto announced six new 3D printable metal alloys.<\/li>\n<li>These alloys based on nickel, cobalt, and chromium are aimed at very high-temperature environments.<\/li>\n<li>For mining, the focus is on parts that are more resistant to wear, heat, and oxidation.<\/li>\n<li>Before the factory, it is necessary to validate costs, standards, safety, and actual conditions.<\/li>\n<\/ul>\n<\/aside>\n<h2>What is it, concretely?<\/h2>\n<p>The subject is simple: use AI to accelerate the discovery of new metal alloys. Instead of randomly testing thousands of mixtures, software analyzes known results and proposes some promising recipes. Machines then produce small samples, researchers measure their hardness, heat resistance, or oxidation resistance, and these results are used to improve the next choice. The University of Toronto has applied this method to nickel-cobalt-chrome alloys suitable for metal printing. The key point: AI helps guide the tests, but it does not replace the laboratory, the engineer, or industrial validation.<\/p>\n<h2>Concrete case: what to do and what not to do<\/h2>\n<aside class=\"veille-case-study\">\n<p class=\"veille-case-study__intro\">Let's take the Compagnie mini\u00e8re de l\u2019Ogoou\u00e9 (COMILOG) in Moanda, Gabon. The case is educational and hypothetical; it has not been announced by the company. COMILOG is involved in the manganese supply chain, while the country wants to strengthen the local processing of its ores with ERAMET and COMILOG.<\/p>\n<p class=\"veille-case-study__intro\">The business problem is very concrete: certain parts of furnaces, conveyors, grinders, or equipment exposed to heat, abrasion, and oxidation are expensive to replace. The temptation would be to quickly launch an AI project, new alloys, and metal printing. What is lacking before deciding: reliable maintenance data, tests under real conditions, a cost-benefit analysis, local skills, and hygiene, safety, and environment (HSE) validation.<\/p>\n<div class=\"veille-case-study__grid\">\n<div class=\"veille-case-study__col veille-case-study__col--do\">\n<p class=\"veille-case-study__label\">What can be done<\/p>\n<ul>\n<li>Target three to five critical parts that cause the most downtime.<\/li>\n<li>Build a clean database: lifespan, supplier, temperature, dust, humidity, downtime cost.<\/li>\n<li>Plan a laboratory test, then a limited pilot before any production.<\/li>\n<li>Bring together metallurgists, maintenance, purchasing, finance, and HSE around the decision.<\/li>\n<li>Train local teams in AI applied to materials and quality control.<\/li>\n<\/ul>\n<\/div>\n<div class=\"veille-case-study__col veille-case-study__col--dont\">\n<p class=\"veille-case-study__label\">What not to do<\/p>\n<ul>\n<li>Present AI as a machine that independently invents a ready-to-use material.<\/li>\n<li>Move from a laboratory result to a critical part without field tests.<\/li>\n<li>Neglect the availability of nickel, cobalt, or chrome, nor their cost.<\/li>\n<li>Purchase a closed solution that transfers no skills to the teams.<\/li>\n<li>Omit the risks of welding, recycling, dust, toxicity, or end-of-life.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/aside>\n<h2>Questions to Ask Before Acting<\/h2>\n<ul>\n<li>What specific problem do we want to solve: wear, heat, corrosion, breakage, lead time, or supply cost&nbsp;?<\/li>\n<li>Are the data on parts, failures, and production stoppages reliable&nbsp;?<\/li>\n<li>Can a local or partner laboratory test the material before a pilot line&nbsp;?<\/li>\n<li>Do the teams understand the limits of AI and metal printing&nbsp;?<\/li>\n<li>Does the total cost remain better with material, energy, maintenance, training, and certification&nbsp;?<\/li>\n<li>Who owns the data and results: the company, the supplier, the laboratory, or a foreign platform&nbsp;?<\/li>\n<li>Does the project strengthen local processing and national skills, or does it create a new dependency&nbsp;?<\/li>\n<\/ul>\n<h2>UNIVGA Viewpoint<\/h2>\n<aside class=\"veille-univga-voice\">\n<p>For Gabon, this news goes beyond scientific curiosity. The country is a major player in manganese: the United States Geological Survey (USGS) attributes 25% of global production to it in 2024. The public goal of local manganese processing by 2029 thus changes the question. It is not just about extraction, but mastering material testing, industrial maintenance, furnaces, quality control, and investment choices.<\/p>\n<p>UNIVGA must view AI as a tool for industrial sovereignty. Data on failures, ores, processes, alloys, and costs are not just simple technical files. They tell the real performance of a mine or a factory. If this data goes uncontrolled to external suppliers, the country loses part of its ability to learn.<\/p>\n<p>For the School of Mines &amp; Metallurgy, the message is clear: future executives will need to speak metallurgy, management, purchasing, HSE, data, and strategy. AI does not replace this foundation. It makes the right profiles even more valuable.<\/p>\n<\/aside>\n<aside class=\"veille-univga-encart\">\n<p class=\"veille-univga-encart__label\">Training at UNIVGA<\/p>\n<p>UNIVGA offers professional certifications in many fields. Browse the complete catalog of our schools and training programs to find the path that suits your project.<\/p>\n<p><a href=\"https:\/\/univga.org\/en\/our-training-courses\/\">Discover our training programs<\/a><\/aside>\n<h2>Sources<\/h2>\n<ol>\n<li><a href=\"https:\/\/news.engineering.utoronto.ca\/self-driving-lab-leverages-ai-to-develop-tough-new-3d-printable-metal-alloys-for-aerospace-and-advanced-manufacturing\/\">University of Toronto Engineering News, announcement of July 13, 2026<\/a><\/li>\n<li><a href=\"https:\/\/www.mines.gouv.ga\/9-actualites\/1196-transformation-locale-du-manganese-le-gabon-accelere-avec-erametcomilog\/?utm_source=openai\">Ministry of Mines of Gabon, local transformation of manganese with ERAMET and COMILOG<\/a><\/li>\n<li><a href=\"https:\/\/www.nature.com\/articles\/s44334-026-00098-5\">npj Advanced Manufacturing, scientific article on NiCoCr alloys<\/a><\/li>\n<li><a href=\"https:\/\/www.usgs.gov\/centers\/national-minerals-information-center\/gabon?utm_source=openai\">U.S. Geological Survey, Gabon fact sheet<\/a><\/li>\n<li><a href=\"https:\/\/www.mines.gouv.ga\/9-actualites\/1059-tout-est-mis-en-oeuvre-pour-viser-la-transformation-integrale-du-manganese-dici-2029-\/?utm_source=openai\">Ministry of Mines of Gabon, goal of complete transformation of manganese by 2029<\/a><\/li>\n<li><a href=\"https:\/\/knowridge.com\/2026\/07\/ai-powered-robot-lab-discovers-six-new-metal-alloys-that-thrive-in-extreme-heat\/\">Knowridge Science Report, popularized summary<\/a><\/li>\n<li><a href=\"https:\/\/www.metaltechnews.com\/\">Metal Tech News, sector watch<\/a><\/li>\n<\/ol>","protected":false},"excerpt":{"rendered":"<p>Researchers have used artificial intelligence to identify six heat-resistant alloys. Here\u2019s what this means for mining.<\/p>","protected":false},"author":6945,"featured_media":157112,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1969],"tags":[1980,2040,2038,2039,1983],"offerexpiration":[],"class_list":["post-157111","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-veille-technologique","tag-intelligence-artificielle","tag-materiaux","tag-metallurgie","tag-mines","tag-technologie"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.9 (Yoast SEO v27.9) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Comment l\u2019intelligence artificielle aide les m\u00e9tallurgistes ?<\/title>\n<meta name=\"description\" content=\"Des chercheurs ont utilis\u00e9 l\u2019intelligence artificielle pour rep\u00e9rer six nouveaux alliages. 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