Genetic Algorithm Based Multi-Objective Optimization of Process Parameters in Color Fast Finish Processes - A Textile Case Study

K.L. Jeyaraj, C. Muralidharan, T. Senthilvelan, S.G. Deshmukh

Abstract


This study describes the application of intelligent control systems in color fast finish (CFF) process as well as to use these approaches for optimizing processing conditions. A multi-objective optimization method based on genetic algorithm (GA) has been proposed for the design and control of color fast finish process. The processing parameters including temperature of the pre-dryer, bath liquor pickup, machine speed and padder pressure were used as design variables and were mathematically related to the five quality characteristics; shade variation to the standard, color fastness to washing, center to selvedge variation, color fastness to light and fabric residual shrinkage using response surface methodology (RSM) technique. Nonlinear mathematical functions were derived based on the processing parameters. Afterward, using a multi-objective optimization technique based on genetic algorithm, optimal conditions were found in such a way that, mean color fast finish process parameters were optimized.

Full Text: PDF