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Additive Manufacturing Blog

Immersive Learning for Additive Manufacturing

May 27, 2021 | Reading time: 2 min
Augmented Virtuality breaks down the walls between learning and working. Learning comes to the place where it is needed in the moment of need. Not everything that is possible has been implemented yet, but we are taking big steps in this direction. The German eLearning Journal awarded EOS and netTrek with the eLearning Award 2021 for Augmented Reality. This gives me and the Additive Minds Academy team at EOS the motivation to continue working on better learning and knowledge worlds.

eLearning Award 2021 goes to Additive Minds Academy

The combination of Augmented Reality with 3D printers and the intuitive usability convinced the jury to award the Eagle5 EOS KI AR project. Together with netTrekAdditive Minds Academy, has developed an app that helps with the commissioning and maintenance of industrial 3D printers. It recognizes the type of machine and superimposes three-dimensional learning content on machine operators in real time so that errors can be corrected with the help of live instructions. 

Augmented reality (AR) technology allows us to bring product training directly to the user. Through three-dimensionality and context sensitivity, we want to make it easier for employees, customers, and service technicians to work on the system and increase the motivation to learn. This is a very efficient approach to apply knowledge intuitively on site.

The low training requirement exemplifies the potential for increasing efficiency that AR applications offer especially for technology companies. The app is laying the groundwork for this, to be expanded with further functions in the future.

After the digital transformation from classroom training to blended learning paths and modules, we are now reaching the next stage with augmented and mixed reality, which allows us to interact with the digital printers in a context-sensitive manner, using the industrial internet of things (IIoT) to display vital data and, in the case of necessary intervention, to show how to solve the task at hand. In the future, the knowledge database will be searched automatically by machine type and error code, and solutions or learning programs will be displayed.