Multi-response optimization in the development of oleo-hydrophobic cotton fabric using Taguchi based grey relational analysis

Abstract Present study under takes multi-response optimization of water and oil repellent finishing of bleached cotton fabric under Taguchi based grey relational analysis. We considered three input variables, viz. concentrations of the finish (Oleophobol CP-C) and cross linking agent (Knittex FEL), and curing temperature. The responses included: water and oil contact angles, air permeability, crease recovery angle, stiffness, and tear and tensile strengths of the finished fabric. The experiments were conducted under L 9 orthogonal array in Taguchi design. The grey relational analysis was also included to set the quality characteristics as reference sequence and to decide the optimal parameter combinations. Additionally, the analysis of variance was employed to determine the most significant factor. The results demonstrate great improvement in the desired quality parameters of the developed fabric. The optimization approach reported in this study could be effectively used to reduce expensive trial and error experimentation for new product development and process optimization involving multiple responses. The product optimized in this study was characterized by using advanced analytical techniques, and has potential applications in rainwear and other outdoor apparel.

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