Prediction of viscosity, density and solids content in inks employed in printing industry production chain combining infrared and neural models

Autores

  • Camila Proni UNESP - Universidade Estadual Paulista “Júlio de Mesquita Filho"
  • Eduardo Hideki Oshiro Senai “Fundação Zerrener“
  • Edenir Rodrigues Pereira-Filho UFSCAR - Universidade Federal de São Carlos
  • Érica Regina Filletti UNESP - Universidade Estadual Paulista “Júlio de Mesquita Filho“

DOI:

https://doi.org/10.21167/cqdv23n12023082098

Palavras-chave:

Inks, Viscosity, Density, Solids content, Artificial neural networks.

Resumo

In this work, some characteristics of the black and whiteinks that are part of the graphic printing processes,calledrotogravure, were evaluated. In this process, the ink playsa decisive role in the quality of the material produced,therefore, its properties must be evaluated and guaranteedin order to obtain a product that works properly in theprinting process.Thus, an analytical method was devel-oped that combines infrared spectroscopy with ArtificialNeural Networks (ANN) to estimate the viscosity, densityand solids content of inks, having the advantage of provid-ing highly accurate results very quickly and with littlecomputational effort. The best models were those devel-oped for density, with average percentage errors of: 1% intraining and validation, and 2% in testof the black andwhite inks together; 1% in training and validation, and0.7% in test of theblack ink; 0.2% in training, 0.8% invalidation and 0.7% in test of white ink. The method de-veloped has the potential to be applied in printing indus-tries as an improvement for the production of high qualityrotogravure printed material

Biografia do Autor

Camila Proni, UNESP - Universidade Estadual Paulista “Júlio de Mesquita Filho"

Instituto de Química

Érica Regina Filletti, UNESP - Universidade Estadual Paulista “Júlio de Mesquita Filho“

Instituto de Química

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Publicado

31-07-2023 — Atualizado em 31-07-2023

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Como Citar

PRONI, C.; OSHIRO, E. H.; PEREIRA-FILHO , E. R.; FILLETTI, Érica R. Prediction of viscosity, density and solids content in inks employed in printing industry production chain combining infrared and neural models. C.Q.D. - Revista Eletrônica Paulista de Matemática, Bauru, v. 23, n. 1, p. 82–98, 2023. DOI: 10.21167/cqdv23n12023082098. Disponível em: https://sistemas.fc.unesp.br/ojs/index.php/revistacqd/article/view/359. Acesso em: 4 maio. 2024.

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Artigos de Pesquisa