Modeling and optimization of dyeing process of polyamide 6 and woolen fabrics with plum-tree leaves using artificial intelligence

• Published in: Scientific reports Vol. 14; no. 1; pp. 15067 - 17
• Main Authors: Shahmoradi Ghaheh, Fatemeh, Razbin, Milad, Tehrani, Majid, Zolfipour Aghdam Vayghan, Leila, Sadrjahani, Mehdi
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 02.07.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 639/301/357/551; 639/705/1042; Artificial intelligence; Artificial neural network; Dyeing process; Dyes; Fabrics; Fixatives; Genetic algorithm; Humanities and Social Sciences; Leaves; multidisciplinary; Neural networks; Optimization; pH effects; Plum-tree leaves; Polyamides; Response surface methodology; Science; Science (multidisciplinary); Water quality; Wool fabrics; Artificial neural network; Response surface methodology; Dyeing process; Genetic algorithm; Plum-tree leaves
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-64761-7

The dyeing process of textile materials is inherently intricate, influenced by a myriad of factors, including dye concentration, dyeing time, pH level, temperature, type of dye, fiber composition, mechanical agitation, salt concentration, mordants, fixatives, water quality, dyeing method, and pre-treatment processes. The intricacy of achieving optimal settings during dyeing poses a significant challenge. In response, this study introduces a novel algorithmic approach that integrates response surface methodology (RSM), artificial neural network (ANN), and genetic algorithm (GA) techniques for the precise fine-tuning of concentration, time, pH, and temperature. The primary focus is on quantifying color strength, represented as K/S, as the response variable in the dyeing process of polyamide 6 and woolen fabric, utilizing plum-tree leaves as a sustainable dye source. Results indicate that ANN (R 2  ~ 1) performs much better than RSM (R 2  > 0.92). The optimization results, employing ANN-GA integration, indicate that a concentration of 100 wt.%, time of 86.06 min, pH level of 8.28, and a temperature of 100 °C yield a K/S value of 10.21 for polyamide 6 fabric. Similarly, a concentration of 55.85 wt.%, time of 120 min, pH level of 5, and temperature of 100 °C yield a K/S value of 7.65 for woolen fabric. This proposed methodology not only paves the way for sustainable textile dyeing but also facilitates the optimization of diverse dyeing processes for textile materials.