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Seam performance: Analysis and Modelling
[Thesis]. Manchester, UK: The University of Manchester; 2011.
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Abstract
Seam quality is affected by various fabric mechanical properties with a combination of their sewing parameters. Previously, a lot of research has been done on identifying the parameters that influencing seam quality by looking into correlation between fabric properties and sewing parameters. The purpose of this current study was to investigate the performance of seam quality in terms of seam appearance and strength constructed with different sewing parameters. Another aim was to identify parameters that influence the seam quality using the Structural Equation Modelling (SEM) by AMOS and leads to the development of multivariable predictive equations using SPSS. Finally, the validation between experimental and predicted results using newly developed equations was examined using a new set of fabrics. The investigation was done for five different fabric categories, namely light, light to medium, medium, medium to heavy and heavy weight. A total of 45 fabrics with different weave densities, fibre types and structures were used. Seams were produced using various sewing parameters such as threads with different fibre types and structures, needle sizes and stitch densities. All fabrics were tested for their mechanical properties using two established items of equipment known as Kawabata Evaluation System for Fabrics (KES-F) and Fabric Assurance by Simple Testing (FAST). Seam evaluations together with thread and fabric mechanical properties obtained from KES-F and FAST were used as input for modelling. From the experimental work, it was concluded that the usage of thicker threads did not always give better strength and the seam appearance was also poor. A combination of finer thread with moderate strength and a medium level of stitch density according to fabric weight category provided an effective result for both seam appearance and strength. From the modelling work, it was found that the extensibility, bending and shearing properties, together with thread properties including extensibility, tensile strength and size, were among the properties selected by SEM to be included in the predictive equations. The validation results showed that the standard deviation between fabric properties used to develop the equations and new fabric properties used for validation plays an important role. The principal conclusion was that the prediction equations developed using SEM and SPSS possible to be used and gave a strong validation between experimental and predicted results when the new fabric properties were within one standard deviation.