Choice of dot shape is the most important factors that
affect the printing quality in the flexographic printing system. The aim of the
operations performed by the machine operator during the printing process
(densitometric measurements, ink settings, etc.) is to achieve the same quality
from the first printing to last printing. This study attempts to estimate
screen density values obtained from the same polymer structure (DFR), 175 Lpi
screening and 10 different screen structures using the Artificial Neural
Networks method (ANN). Data necessary for calculations were obtained from real
values as a result of experimental studies. The correlation coefficient of the
data obtained from the model created with ANN for screen density values was
found to be 98,902% and this value was found to be consistent with scientific
values. According to the results, the neural network model used in flexographic
printing systems of different screening methods predictable effect on the
printing result.
Choice of dot shape is the most important factors that
affect the printing quality in the flexographic printing system. The aim of the
operations performed by the machine operator during the printing process
(densitometric measurements, ink settings, etc.) is to achieve the same quality
from the first printing to last printing. This study attempts to estimate
screen density values obtained from the same polymer structure (DFR), 175 Lpi
screening and 10 different screen structures using the Artificial Neural
Networks method (ANN). Data necessary for calculations were obtained from real
values as a result of experimental studies. The correlation coefficient of the
data obtained from the model created with ANN for screen density values was
found to be 98,902% and this value was found to be consistent with scientific
values. According to the results, the neural network model used in flexographic
printing systems of different screening methods predictable effect on the
printing result.
Subjects | Engineering |
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Journal Section | Research Article |
Authors | |
Publication Date | September 1, 2018 |
Submission Date | April 25, 2017 |
Published in Issue | Year 2018 Volume: 21 Issue: 3 |
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