D5.1 Image-Based Predictive Maintenance Concept for Inkjet Printing of Ceramic Inks
- SMSI 2021
2021-05-03 - 2021-05-06
- SMSI 2021 - Measurement Science
- D5 Deep Learning and Artificial Intelligence in Measurement
- P. Bischoff, C. Zeh, C. Schuster, T. Härtling - Fraunhofer Institute IKTS, Dresden (Germany), C. Kroh - Senodis Technologies GmbH, Dresden (Germany)
- 262 - 263
Ceramic inks can be used to mark metal sheets in hot forming for track-and-trace purposes. However, the ceramic pigments in the inks can lead to clogging of printer nozzles which results in loss of print quality. Here we report on a predictive maintenance concept including different machine- and deeplearning models as the basis of a print quality assurance strategy. Pixelwise image segmentation leads to detailed information about the printing results. The information is used to train a model, classifying the remaining useful lifetime until insufficient printing results.