Modelling the properties of pigment‐dyed polyester/cotton sheeting fabrics by response surface methodology

Abstract

The aim of this study was to model the effect of pigment, binder and fixer concentrations on the rubbing fastness, crease recovery, tear strength and stiffness of pigment‐dyed polyester/cotton sheeting fabrics. The design and analysis of experiments were carried out using Minitab® statistical software according to the central composite design of response surface methodology. It was found that an increase in the binder concentration significantly improves the dry rubbing fastness, crease recovery and stiffness of the fabric, with a corresponding decrease in fabric tear strength, without significantly affecting the wet rubbing fastness. An increase in the fixer concentration significantly improves both the dry and wet rubbing fastness and crease recovery, with a decrease in fabric tear strength and stiffness. The effect of binder and fixer concentrations on crease recovery was not linear and there was significant negative interaction between these factors for dry rubbing fastness. The effect of pigment concentration was not found to be statistically significant for the types and range of concentrations of pigment, binder and fixer used in this study.

Coloration of cellulose nanofibres with pigments

“…This may be because when the CEL ENM was creased the molecular chains in the amorphous region slipped past each other, breaking the weak hydrogen bonds of the stretched chains 30 . Pigment‐ coloured CEL ENMs demonstrated increased WRAs as the coloured ENMs became stiffer, providing better wrinkle resistance 31 . Increases in the stiffness of coloured ENMs were attributed to crosslinking of the binder used with the cellulose polymer structure during heat treatments.…”

Optimization of the cationizing condition in salt‐free reactive dyeing of cotton fabric with the pad‐irradiate‐pad‐steam process using response surface methodology

“…RSM is typically employed to model the relationship between multiple experimental variables and one or more responses by modelling linear and nonlinear relationships between experimental variables and responses, as well as their interactions. Conventional one‐factor experiments always fail in modeling the nonlinear relationships between experimental variables and responses and in considering their interactions . Two important types of experimental designs used in RSM are CCD and Box–Behnken design (BBD).…”

“…It uses the relevant data obtained from experiments to fit the functional relationship between variables and response values by means of multivariate quadratic regression equation and to seek the optimal process parameters by analyzing the regression equation (response surface plots and contour plots). The main characteristic of RSM is less test times and higher test precision …”

Modelling the properties of pigment‐printed polypropylene nonwoven fabric using the Box–Behnken technique

“…More than 80% of printed goods are pigment based owing to its obvious advantages, such as versatility, print quality, applicability to almost every kind of fibre or mixture, and no washing processes required after fixation. Insoluble pigments, which have no affinity for any fibre, are used in a finely dispersed form, and film‐forming binders are used to fix these pigments onto the substrate by adhesion .…”