| Fabric hand is an important characteristic to the textile industry. Fabric hand is influenced by fiber parameters including flexural rigidity and friction. It is also influenced by yarn parameters such as count, twist, CV%, hairiness, stiffness and softness. This study deals primarily with predicting the hand of knitted T-shirts from yam quality parameters. The work consists of a short literature review on the existing yarn parameters as well as fabric hand evaluation and prediction techniques. Roughness measurement and the latest development in measuring the roughness of textile material surfaces are also covered. Additionally, the two main components of softness, bulk and surface softness, are discussed. Subjective and objective hand evaluations are clarified and reviewed.; A device named the Mechanical Stylus Surface Analyzer (MSSA) that was previously developed to test the surface of paper tissues is discussed. In this work, the MSSA is modified to measure yarn surface characteristics. Using the surface profile as tested by the MSSA a novel yarn surface analysis parameter named Surface Response Average (SRA) was developed. A model for the fiber stylus-tip interaction was also developed. Ten T-shirts were produced from 10 different yarn samples and the T-shirts were ranked based on their hand by a panel of judges. The yarns used to make these T-shirts were tested by Uster III and MSSA.; The T-shirts were classified based on yarn parameters using linear and tree modeling techniques. The result shows that SRA has a correlation of 0.6 with fabric hand. When classifying the T-shirts to 3 classes of low, medium and high hand, the linear model has a classification rate of 69%. However using tree modeling it is possible to obtain a classification rate of 93% which is considered a significant result. It is therefore concluded that SRA is an important yarn surface parameter that can be used to predict fabric hand. |
