Articles | Volume 11, issue 2
J. Sens. Sens. Syst., 11, 277–285, 2022
J. Sens. Sens. Syst., 11, 277–285, 2022
Regular research article
16 Sep 2022
Regular research article | 16 Sep 2022

En route to automated maintenance of industrial printing systems: digital quantification of print-quality factors based on induced printing failure

Peter Bischoff et al.

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Cited articles

Bischoff, P., Zeh, C., Schuster, C., Härtling, T., and Kroh, C.: D5.1 Image-Based Predictive Maintenance Concept for Inkjet Printing of Ceramic Inks, in: SMSI 2021 – Measurement Science, AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany, 262–263,, 2021. a
Chang, T., Mukherjee, S., Watkins, N. N., Benavidez, E., Gilmore, A. M., Pascall, A. J., and Stobbe, D. M.: Millimeter-wave electromagnetic monitoring for liquid metal droplet-on-demand printing, J. Appl. Phys., 130, 144502,, 2021. a
Choi, I. H., Kim, Y. K., Lee, S., Lee, S. H., and Kim, J.: A Pneumatic Drop-on-Demand Printing System With an Extended Printable Liquid Range, J. Microelectromech. S., 24, 768–770,, 2015. a
Dickey, D. A. and Fuller, W. A.: Distribution of the Estimators for Autoregressive Time Series with a Unit Root, J. Am. Stat. Assoc., 74, 427–431,, 1979. a
Dong, H., Carr, W. W., and Morris, J. F.: An experimental study of drop-on-demand drop formation, Phys. Fluids, 18, 072102,, 2006. a
Short summary
Tracking individual parts in manufacturing processes helps to lower production cost by assigning a full record of production steps to each part, and therefore enabling targeted quality control. A novel approach is presented, which shows that the printing quality can be monitored using images of the printed result only. Analysing data from long-term tests shows which characteristics of the part marking are suitable to be used as indicators for maintenance needs.