Name: ML for Quality Management
Start: 2022-10-12T19:00:00+02:00
End: 2022-10-12T20:30:00+02:00
Location: Cluster Produktionstechnik

**Safe the Date!**

🎉 We are happy to announce the upcoming ML Meetup on October 12, starting at 19:00 o'clock (07:00pm).

🗣️**Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University** \- Real or Fake? \- How Generative Deep Learning Methods contribute to the dissemination of Deep Learning in industrial machine vision
*Deep Learning (DL) expands the toolbox of industrial machine vision for tasks in which the quality characteristics are not known or cannot be described analytically. However, DL introduces new challenges: The data must be available in sufficient quantity and quality, and the underlying decision criteria remain untransparent to users. These deficits in combination with technical and infrastructural challenges prevent the utilization of the full potential DL promises for industrial machine vision.*
*In contrast to discriminative methods, generative DL methods learn the distribution of a dataset. After a successful training, they can be used to synthesize photorealistic images that appear indistinguishable from the images within the original dataset. This makes them suitable, for example, to enlarge the database for training discriminative Deep Learning models. Certain variants allow the manipulation of distinct properties of the synthesized images and thus enable an interpretation of the learned features. The potential of these abilities of generative Deep Learning methods for image-based quality assurance applications is demonstrated for several industrial use-cases.*

🗣️**Fraunhofer Institute for Production Technology IPT** \- Battery cell production \- Potentials of AI applications for quality assurance and quality management
*The presentation will give insights into the battery cell production. Beyond that, the concept of an AI toolbox for the application in quality assurance and quality management of battery cell production will be presented. Therefore the different methods as well as the basic structure and utility of the AI toolbox will be explained. The concrete benefit will be demonstrated by real-life use cases in production. Finally, the intersections with the concept of a digital twin will be shown.*

🚨Please note that there has been a change in location from previous events.

🎉 We look forward to seeing you again!

Nils Klasen

Maik Frye

Aachen Digital

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