Application of central composite design to model the color yield of six diazo direct dyes on cotton fabric

Abstract

This paper describes the modeling of the color yield of six direct diazo dyes on cotton fabric through central composite design, which is an efficient experimental design. The factors chosen for the model were dye concentration, electrolyte (sodium chloride) concentration, dye bath temperature, dyeing time, and liqor ratio. Five levels were considered for each factor. Color yield ( F k ) was taken as the response. Box-Cox transformation was employed to optimize the models. Each dye was represented by a model. The models showed a good fit. Finally a series of conditions of the factors leading to optimum response ( F k ) were identified.

Dyeing process parameters optimisation and colour strength prediction for viscose/lycra blended knitted fabrics using Taguchi method

“…Additionally, based on many years of experience in the textile dyeing occupation, it has been seen that notwithstanding all other qualities within the acceptable limit, buyer do not accept any piece of export quality garment in a minor deviation of colour shade. Various research have been reported on the factors affecting the colour properties of knitted fabric including dye concentration, temperature, time, pH, salt concentration and liquor ratio (Ashraf et al, 2014;Fezeli, Tavanai, & Hamadani, 2012;Kuo & Pietras, 2010;Zavareh, Hamadani, & Tavanai, 2010;Zeydan & Toga, 2011). Moreover, all these factors act non-linearly and interact with one another; hence, it is very complicated to control the dyeing process and consequently not easy to create an exact functional relationship between process parameters and quality characteristics (Majumdar & Ghosh, 2008;Kuo & Pietras, 2010).…”

“…To meet the customers increasing demand, the manufacturers are applying more competent machinery, new process technologies and new improved quality raw materials (Fezeli et al, 2012;Zavareh et al, 2010). Alternatively, process optimisation is one of the most feasible but competent technique for efficient control of the critical factors, which has a substantial impact on the reduction of process time and production cost as well as productivity improvement (Fezeli et al, 2012;Kuo & Pietras, 2010;Kuo, Chang, Su, & Fu, 2008;Zavareh et al, 2010;Zeydan, 2008).…”

“…Alternatively, process optimisation is one of the most feasible but competent technique for efficient control of the critical factors, which has a substantial impact on the reduction of process time and production cost as well as productivity improvement (Fezeli et al, 2012;Kuo & Pietras, 2010;Kuo, Chang, Su, & Fu, 2008;Zavareh et al, 2010;Zeydan, 2008).…”

“…Conventional trial-and-error approaches and single factor variable at a time for optimisation did not succeed to present an overall design of parameters due to the large volume of works and very tough to find the interactive effects. Moreover, full-factor experimental design in this regard is also time consuming, involving with huge raw material availability and more expensive as well as complicated to control the process conditions (Chary & Dastidar, 2010;Fezeli et al, 2012;Kuo et al, 2008;Zavareh et al, 2010).…”

Modeling the functional compression properties of hand-knotted carpets using factorial design and response surface methodology

“…In order to do this, the Box-Cox power transformation searches from lambda = −5 to +5 until the best value is found (for any λ, a model is fitted to the data so that the λ related to the model with lowest MSE is chosen). The selected λ is used to modify the original model and led to the presentation of the final model [17,20]. D) Relative importance of proper variables using extra sum of squares For determining the relative importance of proper variables in each models, one has to use the extra sum of squares method [19,21].…”