Optimisation of bending and shear rigidities of woven fabrics using hybrid DOE-NSGA-II approach

Abstract

Bending and shear rigidities of woven fabrics depend on various materials and structural parameters. Achieving low bending rigidity and high shear rigidity in woven fabrics is a challenging and complicated task. In this work, engineering design of woven fabrics was optimised with respect to bending and shear rigidities using design of experiments (DOE) and non-dominated sorting genetic algorithm II (NSGA-II). The relationships between input parameters (proportion of fibre, yarn count and fabric sett) and rigidities of fabrics were obtained using Box-Behnken DOE method. The NSGA-II was used to determine the Pareto optimal front for low bending rigidity and high shear rigidity. The user can choose any option from the Pareto optimal front based on the end-use requirement. For the validation of the proposed approach, two engineered fabrics were produced using the optimised values of input parameters. The results demonstrated that target values and achieved values of rigidities are reasonably close to each other with average error of 6.24% and 3.33%, respectively. The proposed method can pave the way for intelligent manufacturing of woven fabrics in industrial scale.