{"id":3182,"date":"2025-04-07T12:59:40","date_gmt":"2025-04-07T12:59:40","guid":{"rendered":"https:\/\/www.autfactory.com\/solidair-promoting-ai-and-robotics-for-sustainable-european-manufacturing\/"},"modified":"2025-04-28T06:59:57","modified_gmt":"2025-04-28T06:59:57","slug":"solidair-promoting-ai-and-robotics-for-sustainable-european-manufacturing","status":"publish","type":"post","link":"https:\/\/www.autfactory.com\/en\/solidair-promoting-ai-and-robotics-for-sustainable-european-manufacturing\/","title":{"rendered":"SoliDAIR: Promoting AI and robotics for sustainable European manufacturing"},"content":{"rendered":"\n
<\/div>\n
\n \n \n
\n \n \n\n
\n
\n

The SoliDAIR project: accelerating AI and robotics adoption in manufacturing<\/h3>\n\n\n\n

The SoliDAIR project aims to promote the widespread introduction of artificial intelligence (AI), data and robotics in the European manufacturing industry. Despite the promising potential of these technologies, their use has so far been limited – only around 15% of manufacturing companies use AI-based solutions <\/strong>to optimize their production processes. <\/p>\n\n\n\n\n\n\n\n

SoliDAIR aims to close this gap by developing advanced AI and robotics solutions and dividing them into three customizable technology areas that can be widely used in industry. The aim is to increase <\/strong>the competitiveness <\/strong>of European manufacturing companies, reduce costs and improve the sustainability of production processes. <\/p>\n<\/div>\n\n\n\n

<\/div>\n\n\n\n
\n
\"\"<\/figure>\n<\/div>\n<\/div>\n\n\n <\/div>\n\n <\/div>\n
\n \n \n
\n \n \n\n
\n
\n
\"\"<\/figure>\n<\/div>\n\n\n\n
<\/div>\n\n\n\n
\n

Predictive quality control in automotive production<\/h3>\n\n\n\n

As part of SoliDAIR, we play a key role in Use Case 4, which focuses on predictive quality control<\/strong> in automotive transmission assembly. <\/p>\n\n\n\n

Here, the traditional end-of-line inspection process for 50% of products is replaced by AI-supported quality control<\/strong>. The aim of this use case is to optimize the production process through preventive defect identification and to implement proactive corrective measures<\/strong> through AI and human collaboration. <\/p>\n\n\nMehr zu den Use Cases erfahren<\/a>\n<\/div>\n<\/div>\n\n\n <\/div>\n\n <\/div>\n

\n \n \n
\n \n \n\n
\n
\n

Challenges and solutions<\/h3>\n\n\n\n

This use case presents us with a number of challenges, particularly when dealing with unbalanced data sets that make it difficult to train the AI models. We have already further developed the AI so that it is able to precisely identify the causes of production errors and initiate targeted measures to rectify them. <\/p>\n\n\n\n

With these innovations, we are not only increasing production efficiency, but also creating greater collaboration between man and machine – an important step towards more sustainable and higher-quality production.<\/p>\n\n\nmehr zu Predictive Quality erfahren<\/a>\n<\/div>\n\n\n\n

<\/div>\n\n\n\n
<\/div>\n<\/div>\n\n\n <\/div>\n\n <\/div>\n
\n \n \n
\n \n \n\n
\"\"<\/figure>\n\n\n\n

This project has received funding from the European Union under GA n 101120276. However, the views and opinions expressed are those of the authors only and do not necessarily reflect those of the European Union or the European Climate, Infrastructure and Environment Executive Agency (CINEA). Neither the European Union nor the granting authority can be held responsible for them. <\/p>\n\n\n <\/div>\n\n <\/div>\n","protected":false},"excerpt":{"rendered":"

The SoliDAIR project: accelerating AI and robotics adoption in manufacturing The SoliDAIR project aims to promote the widespread introduction of artificial intelligence (AI), data and robotics in the European manufacturing industry. Despite the promising potential of these technologies, their use has so far been limited – only around 15% of manufacturing companies use AI-based solutions […]<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[14],"tags":[],"class_list":["post-3182","post","type-post","status-publish","format-standard","hentry","category-general"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.autfactory.com\/en\/wp-json\/wp\/v2\/posts\/3182","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.autfactory.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.autfactory.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.autfactory.com\/en\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/www.autfactory.com\/en\/wp-json\/wp\/v2\/comments?post=3182"}],"version-history":[{"count":2,"href":"https:\/\/www.autfactory.com\/en\/wp-json\/wp\/v2\/posts\/3182\/revisions"}],"predecessor-version":[{"id":3192,"href":"https:\/\/www.autfactory.com\/en\/wp-json\/wp\/v2\/posts\/3182\/revisions\/3192"}],"wp:attachment":[{"href":"https:\/\/www.autfactory.com\/en\/wp-json\/wp\/v2\/media?parent=3182"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.autfactory.com\/en\/wp-json\/wp\/v2\/categories?post=3182"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.autfactory.com\/en\/wp-json\/wp\/v2\/tags?post=3182"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}