Thesis Details


Thesis Title: Development of a practical method for measuring heat history of textured polyester at-line using NIRA
Thesis Author: Kamesha Owens
Abstract: Currently, there are two common methods for determining the quality of yarn exiting the false-twist texturing frame. The first method is a dyed knitted sock test, and the second is an on-line tension monitoring system. The cost of the dyed knitted sock test is high because it requires fabric to be knit and dyed, and needs operators to visually compare shades. The on-line tension monitoring system does a good job of detecting mechanical faults in the process, but recent studies show that on-line methods fail to detect yarn defects which are related to thermal history of filaments. Heat related defects are the main cause of poor quality yarn, resulting in dyeability and bulk problems. Currently, there is no method of measuring heat history at-line to quickly detect heat-related defects. The purpose of this thesis was to develop a practical method for measuring heat history of polyester at-line using NIRA to quickly detect heat-related defects. For this thesis research, two different NIRA technologies were calibrated using yarn produced at different temperatures on a high-speed commercial false-twist texturing machine. Heat history differences were established by altering primary heater temperatures in the texturing process in increments of 8°C. Temperatures ranged from 404°C to 596 DC. Samples not used in the calibration were used to validate prediction equations. Plant trials were then conducted in which doffs were analyzed using the two NIRA technologies. It was then determined to what degree NIRA could detect packages produced with heat-related defects. The research showed that NIR systems are sensitive to changes induced by thermal treatments and thus, are useful tools for determining heat history of textured PET yarn. NIR systems were able to identify heat defective packages during inplant trials, and calibrations were improved through optimal usage of package presentation, sampling method, and advanced mathematical modeling techniques.