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Central Composite Design Matrix (CCDM) for Phthalocyanine Reactive Dyeing of Nylon Fiber: Process Analysis and Optimization

  • Textile Coloration and Finishing
  • Abbr : Text. Color. and Finish.
  • 2008, 20(2), pp.19-28
  • Publisher : The Korean Society Of Dyers And Finishers
  • Research Area : Engineering > Fiber Engineering > Dyeing Engineering

K. Ravikumar 1 Young-A Son 1 KIM BYUNG-SOON 1

1충남대학교

Accredited

ABSTRACT

The objective of this study was to apply the statistical technique known as design of experiments to optimize the % exhaustion variables for phthalocyanine dyeing of nylon fiber. In this study, a three-factor Central Composite Rotatable Design (CCRD) was used to establish the optimum conditions for the phthalocyanine reactive dyeing of nylon fiber. Temperature, pH and liquor ratio were considered as the variable of interest. Acidic solution with higher temperature and lower liquor ratio were found to be suitable conditions for higher % exhaustion. These three variables were used as independent variables, whose effects on % exhaustion were evaluated. Significant polynomial regression models describing the changes on % exhaustion and % fixation with respect to independent variables were established with coefficient of determination, R2, greater than 0.90. Close agreement between experimental and predicted yields was obtained. Optimum conditions were obtained using surface plots and Monte Carlo simulation techniques where maximum dyeing efficiency is achieved. The significant level of both the main effects and interaction was observed by analysis of variance (ANOVA) approach. Based on the statistical analysis, the results have provided much valuable information on the relationship between response variables and independent variables. This study demonstrates that the CCRD could be efficiently applied for the empirical modeling of % exhaustion and % fixation in dyeing. It also shows that it is an economical way of obtaining the maximum amount of information in a short period of time with least number of experiments.

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