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

被引:0
|
作者
Bischoff, Peter [1 ,2 ,3 ]
Carreiro, Andre V. [4 ]
Schuster, Christiane [1 ]
Haertling, Thomas [1 ,2 ,3 ,5 ]
机构
[1] Fraunhofer Inst Ceram Technol & Syst IKTS, Maria Reiche Str 2, D-01109 Dresden, Germany
[2] Tech Univ Dresden, Inst Solid State Elect, D-01069 Dresden, Germany
[3] Senodis Technol GmbH, Manfred Von Ardenne Ring 20, D-01099 Dresden, Germany
[4] Fraunhofer Portugal Ctr Assist Informat & Commun S, P-1649003 Lisbon, Portugal
[5] Fraunhofer Portugal Ctr Smart Agr & Water Manageme, Rua Alfredo Allen 455-461, P-4200135 Porto, Portugal
关键词
data matrix; pattern recognition; drop deviation; code recognition; quality assessment; predictive maintenance;
D O I
10.3390/jimaging9070125
中图分类号
TB8 [摄影技术];
学科分类号
0804 ;
摘要
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.
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页数:12
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