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Dürr receives award for deploying artificial intelligence

According to a current study by the RWTH Aachen University, Dürr has been attested a leading position in the deployment of artificial intelligence (AI) in research and development

According to a current study by the RWTH Aachen University, Dürr has been attested a leading position in the deployment of artificial intelligence (AI) in research and development. In a benchmark comparison carried out by the university, Dürr was distinguished as one of five successful practice enterprises in Germany. 145 technology and industrial corporations took part in the study “Artificial Intelligence in R&D”. It was carried out by the Complexity Management Academy, which is part of the Laboratory for Machine Tools and Production Engineering (Werkzeugmaschinenlabor – WZL) of the RWTH Aachen University.

The study examined how artificial intelligence (AI) is used in research and development work by businesses and where it has already featured in the creation of new products. First of all, 145 questionnaires on the use of AI were evaluated and 30 top performers identified. From this group, the Complexity Management Academy of the RWTH Aachen University selected the five leading companies. The four other corporations in addition to Dürr were 3M, ABB, Airbus and Wacker Chemie.

Ralf W. Dieter, CEO of Dürr AG: “Digitization – in combination with artificial intelligence – is the key future trend in industrial production. As a mechanical and plant engineering firm, our approach is to combine software skills with our expertise concerning the production processes of our customers. This enables us to offer customers near-production software and AI solutions.”

As part of the evaluation criterion “Portfolio Applications”, Dürr managed to score e.g. with its DXQplant.analytics software for quality assurance in automotive paint shops. The application uses artificial intelligence to identify systematically occurring quality deviations, to discover the causes in the painting process and to derive optimization solutions in doing so. This is possible thanks to self-learning data models that search for recurring patterns in the quality data measured and associate these with special features of the painting process. A further argument in Dürr’s favor was the ADAMOS platform jointly established with partner companies for the Industrial Internet of Things. Special importance was assigned to it as part of the criterion “Technical requirements”.

SOURCE: Dürr

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