The quality assessment of reprints by means of fuzzy logic

Author(s) Collection number Pages Download abstract Download full text
Repeta V. B., Ryvak P. M., Senkivskyi V. M. № 2 (51) 64-71 Image Image

The problem of complex evaluation of quality reprints has been examined in the article. According to the analysis conducted, the basic parameters of the prints offset sheet quality, such as optical density, dot gain, excretory capacity, accuracy of color combination, gray balance have been set. In accordance with the terms «low», «satisfactory», «high», the fuzzy logic basic parameters of quality prints with performance conditions «if-then» have been formed. Based on this knowledge base there have been built fuzzy logical equations to calculate the options for quality imprints, and the difuzzyfication of the «center of gravity», allowing to obtain a quantitative indication of the quality of imprints, as a result of observance of the appropriate mode of the printing process, has been conducted.

Keywords: quality of imprints, linguistic variable, knowledge base, fuzzy logic.

  • 1. Ryvak P., Shablіy І., Repeta V. and Rybka R. (2014), Evaluation of the quality of prints with ‘‘desirable feature’’ to formalize the complex index of competitiveness of a printing house, Qualіology of a book, Vol. 26, No. 2. рр. 3–9.
  • 2. Krylov A. (2009), Quality control in strict mode, Journal Compuart, No. 9, Avaliable at: (Accessed 27 December 2014).
  • 3. Standardization of multi-color printing (2012), Journal Publish, No.10,12, avaliable at:; (Accessed 27 December 2014).
  • 4. International Standard ISO 12647-2:2004 (2004), Graphic technology – Process control for the production of half-tone colour separations, proof and production prints Part 2, Offset lithographic processes, Geneva.
  • 5. Sekerin V. D. (2005), The choice of material using the Harrington (desirability function), Methodical instructions, Moscow.
  • 6. Velychko O. M. (2005), Processing information flow of elements printing contact, Kyiv University publishing center, Kyiv.
  • 7. Rothstein A. P., Lariushkin Ye. I. and Mityushkin Yu. I. (2008), Soft Computing in biotechnology: multivariate analysis and diagnostics, Universum-Vinnytsja.