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  4. Quantifying the Displacement of Data Matrix Code Modules: A Comparative Study of Different Approximation Approaches for Predictive Maintenance of Drop-on-Demand Printing Systems
 
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2023
Journal Article
Title

Quantifying the Displacement of Data Matrix Code Modules: A Comparative Study of Different Approximation Approaches for Predictive Maintenance of Drop-on-Demand Printing Systems

Abstract
Drop-on-demand printing using colloidal or pigmented inks is prone to the clogging of printing nozzles, which can lead to positional deviations and inconsistently printed patterns (e.g., data matrix codes, DMCs). However, if such deviations are detected early, they can be useful for determining the state of the print head and planning maintenance operations prior to reaching a printing state where the printed DMCs are unreadable. To realize this predictive maintenance approach, it is necessary to accurately quantify the positional deviation of individually printed dots from the actual target position. Here, we present a comparison of different methods based on affinity transformations and clustering algorithms for calculating the target position from the printed positions and, subsequently, the deviation of both for complete DMCs. Hence, our method focuses on the evaluation of the print quality, not on the decoding of DMCs. We compare our results to a state-of-the-art decoding algorithm, adopted to return the target grid positions, and find that we can determine the occurring deviations with significantly higher accuracy, especially when the printed DMCs are of low quality. The results enable the development of decision systems for predictive maintenance and subsequently the optimization of printing systems.
Author(s)
Bischoff, Peter  
Fraunhofer-Institut für Keramische Technologien und Systeme IKTS  
Carreiro, André V.
Fraunhofer Center for Assistive Information and Communication Solutions AICOS  
Schuster, Christiane
Fraunhofer-Institut für Keramische Technologien und Systeme IKTS  
Härtling, Thomas  
Fraunhofer-Institut für Keramische Technologien und Systeme IKTS  
Journal
Journal of imaging  
Open Access
DOI
10.3390/jimaging9070125
Language
English
Fraunhofer-Institut für Keramische Technologien und Systeme IKTS  
Keyword(s)
  • data matrix

  • pattern recognition

  • drop deviation

  • code recognition

  • quality assessment

  • predictive maintenance

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