A study of multi-quality processing parameter optimization for sueded fabric

Sueded fabric quality control depends on the processing parameter settings. The quality characteristics considered in this study are surface softness and color difference. The Taguchi method was combined with gray relational analysis (GRA) to optimize the multi-quality sueding processing parameter combinations. First, an orthogonal array is designed by using the design of experiments of the Taguchi method for the major processing parameters of the sueding machine. The signal/noise ratio and analysis of variance are calculated from the measured fabric surface softness and color difference data, significant factors influencing the quality characteristics obtained, and GRA used to remedy the deficiency in the Taguchi method, which is only applicable to single-quality characteristics. The optimum processing parameters of multiple-quality characteristics are obtained from the response table and response diagram of GRA. The quality of suede fabric can be controlled effectively by using the optimum processing parameters to set the processing parameters, and the 95% confidence interval validates the reliability and reproducibility of the experiment.