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Regression Model for the Bagging Fatigue of Knitted Fabrics Produced from Viscose/Polyester Blended Rotor Yarns

Abstract

The aim of this work was to predict the bagging fatigue percentage of knitted fabrics produced from viscose/polyester blended rotor yarns using blend ratios and structural cell stitch lengths as predictor variables. A simplex lattice design was used to determine the combinations of blend ratios of the fiber types. Knitted fabrics with three different structures were produced from viscose/polyester blended rotor yarns. Mixture-process crossed regression models with two mixture components and one process variable (structural cell stitch lengths, blend ratio) were built to predict the bagging fatigue percentage. All statistical analysis steps were implemented using Design-Expert statistical software. The correlation coefficient between the bagging fatigue percentage predicted and the bagging fatigue percentage observed was 0.983, indicating the strong predictive capability of the regression model built.

 


 

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