Prognosticating the Shade Change after Softener Application using Artificial Neural Networks

• Autorzy: Farooq Assad , Irshad Farida , Azeemi Rizwan , Iqbal Nadeem

Identyfikatory

DOI

10.2478/aut-2020-0019

• Języki publikacji: EN

Abstrakty

EN

Softener application on fabric surface facilitates the process and wear abilities of the fabric. However, the application of softeners and other functional finishes influence the color of dyed fabrics, which results in shade change in the final finished fabrics. This article presents the method of intelligent prediction of the shade change of dyed knitted fabrics after finishing application by using artificial neural networks (ANNs). Individual neural networks are trained for the prediction of delta values (ΔL, Δa, Δb, Δc, and Δh) of finished samples with the help of reflectance values of the knitted dyed samples along with color, shade percentage, and finishing concentrations, which were selected as input parameters. The trained ANNs were validated through “holdout” and “cross-validation” techniques. The trained ANNs were combined to develop the model for shade prediction. The developed system can predict the shade change with >90% accuracy and help to decrease the rework and reprocessing in the wet processing industries.

Słowa kluczowe

EN

textile finishing; softeners; artificial neural networks; shade change

PL

wykończenie tekstyliów; zmiękczacze; sztuczne sieci neuronowe

• Wydawca: Lodz University of Technology, Faculty of Material Technologies and Textile Design
• Czasopismo: Autex Research Journal
• Rocznik: 2021
• Tom: Vol. 21, no. 1
• Strony: 79--84
• Opis fizyczny: Bibliogr. 27 poz.

Twórcy

autor

Farooq Assad

• Department of Fibre and Textile Technology, University of Agriculture, Faisalabad, Pakistan

autor

Irshad Farida

• Department of Fibre and Textile Technology, University of Agriculture, Faisalabad, Pakistan

autor

Azeemi Rizwan

• Kays & Emms Pvt. Ltd., Faisalabad, Pakistan

autor

Iqbal Nadeem

• Kays & Emms Pvt. Ltd., Faisalabad, Pakistan

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).