Abstract
Nowadays, modeling is used for evaluating and controlling the weft crimp percentage before and after manufacturing plain woven fabrics. Also, modeling assists in estimating and evaluating crimp percentage without complex and time-consuming experimental procedures. The purpose of this study is to develop a linear regression model that can be employed for the prediction and evaluation of the weft crimp percentage of plain woven fabric. For this study, nine plain woven fabrics of 100% cotton were produced with three different wefts thread densities and weft yarn linear densities. From the findings, the effects of weft count and weft density on the weft crimp percentage of the fabrics were found to be statistically significant with a confidence interval of 95%. The weft crimp percentage showed a positive correlation with weft count and weft density. The weft count and weft density have multicollinearity in the model because the variance inflation factors (VIFs) values are greater than one, which are 1.70 & 1.20, respectively. The model was tested by correlating measured crimp percentage values obtained with a crimp tester instrument to the crimp percentage values calculated by a developed linear model equation. The result disclosed that the model was strongly correlated, with a confidence interval of 95% (R² of 0.9518). Furthermore, the significance value of the t-test is not significant for both the measured weft crimp percentage values and the calculated weft crimp percentage values, which means that they do not differ significantly. Crimp percentage is impacted by fiber, yarn, fabric structural parameters and machine setting parameters. This makes the crimp percentage difficult to control and study, but this developed model can be easily used by manufacturers or researchers for controlling and studying purposes. Thus, the model can be used to produce a fabric with a pre-controlled weft crimp percentage. It can also be used to evaluate and predict the weft crimp percentage before and after fabric production.
Highlights
The purpose of this study is to develop a linear regression model that can be employed for the prediction and evaluation of the weft crimp percentage of plain woven fabric
As the tightness or compactness of the fabrics increases, the weft yarn properly bends over the warp yarn, which results in an increase in the weft crimp percentage
The weft yarn count and weft density were used for the extraction of a weft crimp percentage model equation
Summary
There are various types of weave structures that are manufactured nowadays, such as plain, twill, honeycomb, satin and other derivatives. Crimp percentage could be affected by various factors, such as thread density of the warp and weft, loom setting, fabric structure and yarn count, amongst others. A theory can be proposed that the crimp percentage of the yarn of the woven fabric is directly related to the tension that is applied during weaving. The crimp of warp and weft yarn in woven fabrics is an important parameter that influences several fabric properties such as fabric mass per unit area (GSM), surface roughness, strength, extensibility, thickness, compressibility, stress-strain relations, handle, and creasing. Predictive modeling has nowadays become a powerful tool that can deliver real value through its application and innovation to different textile industries It forms an essential part of the research and development effort of many of the world’s leading organizations and can be incredibly valuable for textile industries. Since crimp percentage is one of the main parameters of woven fabric construction, yarn crimp has a practical significance for designers; in particular, this parameter can be exploited to define fabric behavior during
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