Color Strength Modeling of Viscose/Lycra Blended Fabrics Using a Fuzzy Logic Approach

Abstract

The aim of this study was to model the color strength of viscose/lycra (95:5) blended knitted fabrics using a fuzzy logic approach where color strength is a function of dye concentration, salt concentration, and alkali concentration. Dye concentration, salt concentration, and alkali concentration are the most important factors affecting color strength of viscose/lycra blended knitted fabrics. Moreover, these factors behave nonlinearly and interact: hence, it is very difficult to develop an exact functional relationship between the input variables and color strength using mathematical models, statistical models, or empirical models. Conversely, artificial neural network models are trained using large amounts of experimental data which is a time consuming process. One possible approach to deal with such a complex process is by using a fuzzy logic expert system (FLES), which perform remarkably well in non-linear and complex systems with minimum experimental data. In this study a laboratory scale experiment was conducted to validate the developed fuzzy model. The model was assessed by analyzing various numerical error criteria. The mean relative error was found to be 3.80%, the correlation coefficient was 0.992, and goodness of fit was 0.986 from the actual and predicted color strengths of the fabrics. The results show that the model developed performed well.