Application of Taguchi and Full Factorial Experimental Design to Model the Color Yield of Cotton Fabric Dyed with Six Selected Direct Dyes

This paper describes the modeling of the color yield (F _k ) 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 (F _k ), 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.