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Predicting the air permeability of polyester/cotton blended woven fabrics


The aim of this study was to model the air permeability of polyester cotton blended woven fabrics. Fabrics of varying construction parameters i.e. yarn linear densities and thread densities were selected and tested for air permeability, fabric areal density and fabric thickness. A total of 135 different fabric constructions were tested among which 117 were allocated for development of prediction model while the remaining were utilized for its validation. Four variables were selected as input parameters on basis of statistical analysis i.e. warp yarn linear density, weft yarn linear density, ends per 25 mm and picks per 25 mm. Response surface regression was applied on the collected data set in order to develop the prediction model of the selected variables. The model showed satisfactory predictability when applied on unseen data and yielded an absolute average error of 5.1 %. The developed model can be effectively used for prediction of air permeability of the woven fabrics.

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Correspondence to Noman Haleem.

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Haleem, N., Malik, Z.A., Malik, M.H. et al. Predicting the air permeability of polyester/cotton blended woven fabrics. Fibers Polym 14, 1172–1178 (2013).

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  • Air permeability
  • Modeling
  • Response surface regression
  • Cover factor
  • Woven fabric