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Pregled bibliografske jedinice broj: 1028013

Neural network-based UV adjustment of the photopolymer surface for modification of coating properties printed in flexography


Mahović Poljaček, Sanja; Tomašegović, Tamara; Leskovac, Mirela; Jakovljević, Suzana
Neural network-based UV adjustment of the photopolymer surface for modification of coating properties printed in flexography // Journal of coatings technology and research, 17 (2019), 1-14 doi:10.1007/s11998-019-00270-x (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1028013 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Neural network-based UV adjustment of the photopolymer surface for modification of coating properties printed in flexography

Autori
Mahović Poljaček, Sanja ; Tomašegović, Tamara ; Leskovac, Mirela ; Jakovljević, Suzana

Izvornik
Journal of coatings technology and research (1945-9645) 17 (2019); 1-14

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Flexography ; Surface properties ; Coating thickness ; Optical density ; Neural network

Sažetak
Processes of coating deposition often rely on printing techniques, with flexography being the most common one because of its ability to adjust the medium for the coating transfer (printing plate) to the specific type of coating and substrate by using photopolymer materials with different properties. Qualitative requirements for many types of coatings, especially in the printing industry, include uniformity, achieving desired thickness, definition of the edges of printed coating and optical density of colored coatings. This research was focused on the modification of the mechanical and surface properties of the common styrene–diene-based photopolymer materials in order to optimize the properties of the deposited coating— flexographic ink—by applying the UV post- treatment of the photopolymer. After the analyses of modified photopolymers, neural networks were built with the aim of finetuning of the photopolymer’s surface properties by the UV post-treatment. The results of the research enabled the analysis of the influence of changes that occur in the modified photopolymer material’s mechanical and surface properties on the coating thickness, optical density and printed element edge definition. Once the neural network was built, it enabled fast adjustment of the UV post-treatment of the photopolymer with the aim of optimizing the properties of the specific coating.

Izvorni jezik
Engleski

Znanstvena područja
Grafička tehnologija, Kemijsko inženjerstvo



POVEZANOST RADA


Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb,
Fakultet kemijskog inženjerstva i tehnologije, Zagreb,
Grafički fakultet, Zagreb

Citiraj ovu publikaciju

Mahović Poljaček, Sanja; Tomašegović, Tamara; Leskovac, Mirela; Jakovljević, Suzana
Neural network-based UV adjustment of the photopolymer surface for modification of coating properties printed in flexography // Journal of coatings technology and research, 17 (2019), 1-14 doi:10.1007/s11998-019-00270-x (međunarodna recenzija, članak, znanstveni)
Mahović Poljaček, S., Tomašegović, T., Leskovac, M. & Jakovljević, S. (2019) Neural network-based UV adjustment of the photopolymer surface for modification of coating properties printed in flexography. Journal of coatings technology and research, 17, 1-14 doi:10.1007/s11998-019-00270-x.
@article{article, year = {2019}, pages = {1-14}, DOI = {10.1007/s11998-019-00270-x}, keywords = {Flexography, Surface properties, Coating thickness, Optical density, Neural network}, journal = {Journal of coatings technology and research}, doi = {10.1007/s11998-019-00270-x}, volume = {17}, issn = {1945-9645}, title = {Neural network-based UV adjustment of the photopolymer surface for modification of coating properties printed in flexography}, keyword = {Flexography, Surface properties, Coating thickness, Optical density, Neural network} }
@article{article, year = {2019}, pages = {1-14}, DOI = {10.1007/s11998-019-00270-x}, keywords = {Flexography, Surface properties, Coating thickness, Optical density, Neural network}, journal = {Journal of coatings technology and research}, doi = {10.1007/s11998-019-00270-x}, volume = {17}, issn = {1945-9645}, title = {Neural network-based UV adjustment of the photopolymer surface for modification of coating properties printed in flexography}, keyword = {Flexography, Surface properties, Coating thickness, Optical density, Neural network} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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