首页> 外文期刊>Journal of Engineered Fibers and Fabrics >Application of Taguchi and Full Factorial Experimental Design to Model the Color Yield of Cotton Fabric Dyed with Six Selected Direct Dyes
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Application of Taguchi and Full Factorial Experimental Design to Model the Color Yield of Cotton Fabric Dyed with Six Selected Direct Dyes

机译:田口和全因子实验设计在六种直接染料染色棉织物色产量建模中的应用。

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This paper describes the modeling of the color yield (Fk) of 100% cotton fabric dyed with six selected direct dyes (two from each groups of A, B and C) using Taguchi and factorial experimental designs as well as a response surface regression method. The factors chosen were dye concentration, electrolyte (sodium chloride) concentration, temperature and time of dying. To conduct the tests using the Taguchi approach, two levels were chosen for each factor. After obtaining the data (Fk), the significant factors were determined by an analysis of variance (ANOVA). Then, the level of significant factors was increased from two to three and the supplementary tests were carried out using full factorial design. ANOVA was applied again and, finally, the initial response surface regression model was produced considering the significant factors. After verifying the validity of the initial models, the BOX-COX transformation was implemented until the models achieved validity.
机译:本文介绍了使用Taguchi和阶乘实验设计以及响应表面回归方法对用6种选定的直接染料(A,B和C各两组中的两种)染色的100%棉织物的色率(Fk)进行建模的方法。选择的因素是染料浓度,电解质(氯化钠)浓度,染色温度和染色时间。为了使用田口方法进行测试,为每个因素选择了两个级别。获得数据(Fk)后,通过方差分析(ANOVA)确定重要因素。然后,将重要因素的水平从两个增加到三个,并使用全因子设计进行补充测试。再次应用方差分析,最后,考虑了重要因素,建立了初始响应表面回归模型。在验证初始模型的有效性之后,进行BOX-COX转换,直到模型达到有效性为止。

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