Autor: Markus Kreutz

3D printing has established itself as a production process and has also found its way into the fashion industry. Individualised shoes can be 3D printed, but this poses significant challenges for automated quality control, as defects are rare. Autoencoders enable to train a system with defect-free data so that detected deviations from this state can be evaluated as defects. Our research shows a ROC AUC score of 0.87, proving that this method is suitable for anomaly detection in 3D-printed shoes.

The digital twin is well on the way to becoming an elementary part of the corporate world. Corporate leaders hope that these intelligent images of an increasingly dynamic corporate reality will significantly reduce complexity. Ideally, model-based analyses and (partially) automated decisions using methods of simulation technology and artificial intelligence based on optimized IoT data management can make their contribution to corporate agility. In addition to the definition of terms/concepts, the paper will discuss current challenges and present various examples of their application. Based on these ideas, a process model for the introduction of digital twins in terms of technology migration will be presented.