Investigation and prediction of chosen comfort properties on woven fabrics for clothing

In the content of the study,it was investigated that the effects of various production parameters on the fabric comfort properties of clothing aimed woven fabrics by statistical analyze and it was tried to predict the comfort properties of fabrics by using production parameters. in the scope of the study,it was analyzed by using statistical methods that the effects of selected production parameters which were weft fiber type,weft density,weft yarn count,weaving pattern,fabric thickness and fabric weight on the fabric comfort properties which were fabric air permeability,stiffness and relative water vapor permeability (rwvp).also it was established suitable artificial neural network (ann) models by using matlab® programme for predicting fabric air permeability,fabric stiffness and fabric relative water vapor permeability with using selected production parameters as inputs. as a consequence,the statistical models established for each one of the comfort specialties was seen to be meaningful with the value of p<0.0001. also the production parameters examined in the study were defined to be meaningful on the comfort specialties statistically. in the content of the study,it was revealed that the fabric comfort specialties can be predicted successfully before manufacture via established ann models.