{"id":25889,"date":"2021-04-05T06:00:00","date_gmt":"2021-04-05T13:00:00","guid":{"rendered":"https:\/\/insidebigdata.com\/?p=25889"},"modified":"2021-04-06T09:43:41","modified_gmt":"2021-04-06T16:43:41","slug":"at-john-deere-hard-iron-meets-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2021\/04\/05\/at-john-deere-hard-iron-meets-artificial-intelligence\/","title":{"rendered":"At John Deere, \u2018Hard Iron Meets Artificial Intelligence\u2019"},"content":{"rendered":"\n
\"\"<\/figure><\/div>\n\n\n\n

What\u2019s New:<\/strong> John Deere<\/a> is leveraging Intel\u2019s artificial intelligence (AI) technology to help solve a costly, age-old problem in the manufacturing welding process. Deere is piloting a solution that uses computer vision to automatically spot common defects in the automated welding process in its manufacturing facilities.<\/p>\n\n\n\n

\u201cWelding is a complicated process. This AI solution has the potential to help us produce our high-quality machines more efficiently than before. The introduction of new technology into manufacturing is opening up new opportunities and changing the way we think about some processes that haven\u2019t changed in years.\u201d \u2013Andy Benko, quality director, John Deere Construction & Forestry Division<\/em><\/p><\/blockquote>\n\n\n\n

Why It Matters:<\/strong> At 52 factories around the world, John Deere uses the Gas Metal Arc Welding (GMAW) process to weld mild- to high-strength steel to create machines and products. In these factories, hundreds of robotic arms consume millions of weld wire pounds annually.<\/p>\n\n\n\n

With this volume of welding, Deere has experience finding solutions to welding issues \u2014 and is always looking for new ways to deal with potential problems. One common welding challenge felt across the industry is porosity, in which cavities in the weld metal are caused by trapped gas bubbles as the weld cools. The cavities weaken the weld strength.<\/p>\n\n\n\n

Traditionally, GMAW defect detection has been a manual process requiring highly skilled technicians. Past attempts throughout the industry to deal with weld porosity issues during the welding process haven\u2019t always been successful. If these flaws are found later in the manufacturing process, they require re-work or even scrapping of full assemblies, which can be disruptive and expensive to manufacturers.<\/p>\n\n\n\n

How it Works:<\/strong> The opportunity to work with Intel to leverage AI to address weld porosity was a chance to bring together two of John Deere\u2019s core values \u2014 innovation and quality. \u201cWe wanted to drive technology to make John Deere\u2019s weld quality better than it\u2019s ever been. That\u2019s the commitment we have to our customers, and that\u2019s what they expect from John Deere,\u201d said Benko.<\/p>\n\n\n\n

Intel and Deere combined expertise to develop an integrated, end-to-end system of hardware and software that can generate insights in real time at the edge, at levels beyond the human sense\u2019s capability. When using a neural network-based inference engine, the solution logs defects in real time and automatically stops the welding process. The automated system allows Deere to correct the issue in real time and produce the quality products that Deere is known for.<\/p>\n\n\n\n

\u201cDeere is leveraging AI and machine vision to solve a common challenge with robotic welding,\u201d said Christine Boles, vice president in Intel\u2019s Internet of Things Group and general manager of Industrial Solutions Group. \u201cBy leveraging Intel technology and smart infrastructure in their factories, Deere is positioning themselves well to capitalize not only on this welding solution, but potentially others that emerge as part of their broader Industry 4.0 transformation.\u201d<\/p><\/blockquote>\n\n\n\n

About the Solution:<\/strong> The AI defect detection at the edge solution is powered by Intel\u00ae Core\u2122 i7 processors and uses Intel\u00ae Movidius\u2122 VPUs and the Intel\u00ae Distribution of OpenVINO\u2122 toolkit, implemented with an industrial-grade ADLINK Machine Vision Platform<\/a> and a MeltTools welding camera.<\/p>\n\n\n\n

Sign up for the free insideBIGDATA newsletter<\/a>.<\/em><\/p>\n\n\n\n

Join us on Twitter: @InsideBigData1 \u2013 https:\/\/twitter.com\/InsideBigData1<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Intel and John Deere developed an integrated, end-to-end system of hardware and software that can generate insights in real-time, at levels beyond human capability. When using a neural network-based inference engine, the solution logs defects in real-time and automatically stops the welding process. <\/p>\n","protected":false},"author":10513,"featured_media":22304,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"footnotes":""},"categories":[526,115,87,180,210,56,1],"tags":[437,324,284,96],"acf":[],"yoast_head":"\nAt John Deere, \u2018Hard Iron Meets Artificial Intelligence\u2019 - insideBIGDATA<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/insidebigdata.com\/2021\/04\/05\/at-john-deere-hard-iron-meets-artificial-intelligence\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"At John Deere, \u2018Hard Iron Meets Artificial Intelligence\u2019 - insideBIGDATA\" \/>\n<meta property=\"og:description\" content=\"Intel and John Deere developed an integrated, end-to-end system of hardware and software that can generate insights in real-time, at levels beyond human capability. 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