Right-first-time dyeing: a design of experiments approach for the optimisation of dyeing-processes using hard water. Issue 5 (2nd September 2019)

• Record Type: Journal Article
• Authors: Faisal, Saira; Tronci, Aurelio; Ali, Muhammad; Bashir, Erum; Lin, Long
• Is Part Of: Pigment & resin technology. Volume 48:Issue 5(2019)
• Page Start: 449
• Page End: 455
• Publication Date: 2019-09-02
• Subjects: Optimisation -- 32 full factorial design -- Colorimetric properties -- Reactive dyeing -- Right-first-time dyeing -- Water hardness; Protective coatings -- Periodicals; 667.62305
• DOI: 10.1108/PRT-05-2019-0045
• Languages: English
• ISSNs: 0369-9420

Abstract

Abstract : Purpose: The purpose of this study was to optimise the dyeing conditions to achieve right-first-time dyeing in hard water. Owing to the persistent water scarcity for more than two decades now, the textile industry in Pakistan is forced to rely on high-mineral-content ground water for use in textile wet processing. Furthermore, the limited amount of municipal water that is at the disposal of the textile industry is also high in mineral content. Thus, on the large scale, water hardness has become an acute problem for the textile processor. In particular, in the dyeing process, water hardness is known to have crucial effects. However, to-date, no systematic study has been conducted on this aspect of textile dyeing. Design/methodology/approach: In this study, 3 2 full factorial design was used to optimise the dyeing conditions to achieve right-first-time dyeing in hard water. Thus, cotton fabric was dyed with Red Reactive dye (of dyebath concentration at 5, 10 and 15 g/L) in prepared hard water (of hardness at 10, 40 and 70°dH), respectively. Analysis of variance, coefficient of determination ( R 2 ) and p -values for the models were used to evaluate the adequacy of the predictive models. The surface plots of the effects were studied to further examine the interactions of two independent variables. Derringer's desirability function was used to determine the optimum levels of each variable. Findings: Three levels for both independent variables generate second-order polynomial models to predict the colour strength, lightness, red/green, yellow/blue and total colour difference values of dyed cotton. The obtained predictive models point out the considerable influence of both water hardness and dye concentration on right-first-time dyeing. Originality/value: Such a finding enabled the dye-mill to produce the correct shade at water hardness of 10°dH and 15 g/L dye concentration, without the need for corrective reprocessing.