Multi-objective Optimization of Woven Fabric Parameters Using Taguchi–Grey Relational Analysis

Abstract

ABSTRACT Optimization technique is mainly used to find out the optimal value of control factors which yield the best response variables. In the case of more than one response variable, the optimization process using the Taguchi approach will give a different set of optimal level for each response variable. Consolidating Taguchi method with grey relation analysis will give optimal levels of control factors for all response variables. In the present study, multi-response optimization based on Taguchi-grey relational analysis was conducted to maximize tensile strength, breaking extension and air permeability of cotton woven fabrics. Cotton woven fabric parameters such as weft yarn count, weave structure, weft yarn density with three levels, and twist factor of the weft yarn with two levels were used as control factors. Using full factorial design, 81 experiments will be conducted. Whereas, using the Taguchi approach and L18 orthogonal array in particular, these experiments will be reduced to 16 experiments. Using Taguchi-grey relational method, optimal combination of the control factors which yield the best-woven fabric properties under study were obtained.