Response Surface Methodology and Genetic Algorithms Applied to Model and Optimize the Dyeing of Cotton Process with the Reactive Black 5 Dyestuff
Keywords:Response surface methodology, Modelling, genetic algorithms, dyeing of cotton, financial impact, environmental impact
This work aimed to combine response surface methodology and genetic algorithms to model and optimize the dyeing process to show the influences of each component in the dyeing of cotton knit to optimize its dyeing conditions. A 26 design of central composite and rotational (DCCR) was used as support to execute seventy-eight dyeings with Reactive Black 5 dyestuff (RB5) on 100% knitted cotton substrate. The impacts of various dyeing process parameters were also investigated. The concentrations of [RB5] (percent), [NaCl] (g/L), [Na2CO3] (g/L), and [NaOH] (mL/L), as well as processing time (min) and temperature (°C), were employed. The K S-1 coefficient and the costs of each experiment were calculated as a result. The objective function was derived from the fitting of the experimental points using the least-squares method and analysis of variance (ANOVA). The findings revealed that both techniques can be efficiently applied to model and optimize the cotton dyeing, with the goal of lowering the cost and environmental impact.
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