Estimation Of Screen Density According To Different Screening Methods With Artificial Neural Network Method In Flexo Printing System

Year 2018, Volume: 21 Issue: 3, 575 - 580, 01.09.2018

Mustafa Batuhan Kurt Yelda Karatepe Mumcu , Lütfi Özdemir

https://doi.org/10.2339/politeknik.386932

Cited By: 3

Abstract

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.

Keywords

Packaging, flexo printing, screening methods, flexo plate, artificial neural networks

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