{"id":171404,"date":"2023-12-06T12:16:12","date_gmt":"2023-12-06T12:16:12","guid":{"rendered":"https:\/\/www.aviationbusinessnews.com\/?p=171404"},"modified":"2024-01-26T14:32:28","modified_gmt":"2024-01-26T14:32:28","slug":"pam-2023-ais-role-in-making-material-difference-to-engine-operational-efficiency","status":"publish","type":"post","link":"https:\/\/www.aviationbusinessnews.com\/industry-news\/pam-2023-ais-role-in-making-material-difference-to-engine-operational-efficiency\/","title":{"rendered":"PAM 2023: AI&#8217;s role in making material difference to engine operational efficiency"},"content":{"rendered":"<p>Artificial Intelligence can be used to drive greater engine operational efficiency and to maximise time on the wing, the Predictive Aircraft Maintenance (PAM) Conference was told last week.<\/p>\n<p>Guillaume Limouzy, airline sales director EMEA at StandardAero, told delegates at the event in London that collecting data to enable preventative maintenance is nothing new.<\/p>\n<p>But he said the question today is what should operators do with the data, to take advantage of all the information they collect.<\/p>\n<p>\u201cAt the end of the day delivering costs reduction is what really needs to be done. There are so many items that can be applied to the data and this is where collaboration works, with certain conditions.<\/p>\n<p>\u201cYou get a report based on the data you can get from the engine. Then the question is what should I do with it? What can I do to really make use of this data?\u201d<\/p>\n<p>Limouzy said AI is \u201cbasically based on data\u201d and the value it can bring is to maximise time on wing and reduce the need for engines to be removed for maintenance.<\/p>\n<p>However, he said this has to be done with data scientists, engineering experts and airline operators working together to determine when the best time is to remove an engine.<\/p>\n<p>OEM\u2019s have an advantage, added Limouzy, because they have access to raw data and knowledge of the conditions and location of where the engines are operating.<\/p>\n<p>Once issues have been identified operators then have the challenge of supply chain issues and access to parts which is seeing OEM turnaround times of up to two years for some older engines.<\/p>\n<p>\u201cWe are always coming back to the data and to the data availability. Who is holding the data? This is always the question we are asking.<\/p>\n<p>\u201cTo be able to use this wonderful tool [AI] there is a need for this data and to work with data scientists and operations to really bring value.\u201d<\/p>\n<p>StandardAero says it is working to \u201cclosed the loop\u201d with data so it has much greater visibility of the MRO requirement of engines before they arrive in their workshops.<\/p>\n<p>Limouzy said the firm is \u201cfine tuning\u201d is algorithms and performance in wing to take account of the engine lifecycle looking at both the impact on costs and operation.<\/p>\n<p>\u201cIt gives the operator and the MRO the possibility of cooperating to take advantage of what needs to be done to keep the engine flying with the right parts at the right cost,\u201d said Limouzy.<\/p>\n<p>David Crowly, StandardAero director of technical development, said: \u201cI have a team of really smart engineers and statisticians.<\/p>\n<p>\u201cOur goal is to build reliable models for engines that forecast when they are going to fail, when they are going to require their next shop.<\/p>\n<p>\u201cWe are using it to workscope optimise our engines when they come in while they are still flying. It\u2019s important to understand when those next shops do occur what type of material they are going to need.<\/p>\n<p>\u201cOnce we build this reliability model we can apply it with a software wrapper where we can apply that to decision logic tools and maintenance planning and all functions around the MRO value chain.\u201d<\/p>\n<p>\u201cA lot of parts have a two to four-year lead time. You need to be planning out into the future what you are going to need.\u201d<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Artificial Intelligence can be used to drive greater engine operational efficiency and to maximise time on the wing, the Predictive Aircraft Maintenance (PAM) Conference was&hellip;<\/p>\n","protected":false},"author":120,"featured_media":171241,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[29,30,1131,28,267,4177,31,4172,32,4041],"tags":[],"class_list":["post-171404","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-aircraft-mro-management","category-engines_apus","category-industry-news","category-mro","category-latest-news-mro","category-on-stage","category-parts-components","category-pam","category-tech","category-tech-digitisation"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.0 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