TY  - JOUR
AB  - In this study, the response surface methodology is used to predict the mechanical properties of yarn, their unevenness and hairiness by using the high-volume instrument (HVI) properties of raw cotton and the parameters of the spinning process. Therefore, five different blends of cotton are processed and spun into ring yarns (Nm13, Nm19, Nm 21, Nm31 and Nm37). Each count is spun at five twist levels (450, 500, 650, 750 and 850 trs/m).The models that are developed by using response surface regression with many iterations on a Minitab16 statistical software predict very well the different yarn properties since the R2 values obtained are very important. In addition, these models show that metric number and twist have the highest effect on the four studied parameters
VL  - 19
IS  - 4
SN  - 1560-6074
DO  - 10.1108/RJTA-19-04-2015-B001
UR  - https://doi.org/10.1108/RJTA-19-04-2015-B001
AU  - Ghanmi Hanen
AU  - Ghith Adel
AU  - Benameur Tarek
PY  - 2015
Y1  - 2015/01/01
TI  - Response Surface Regression Models for Prediction of Ring Spun Yarn Properties
T2  - Research Journal of Textile and Apparel
PB  - Emerald Group Publishing Limited
SP  - 1
EP  - 10
Y2  - 2024/04/24
ER  -