Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Institute of Textiles and Clothing | en_US |
| dc.creator | Mandal, Sumit | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/5330 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Studies on seam quality with sewing thread size, stitch density and fabric properties | en_US |
| dcterms.abstract | Different sewing threads sewn on different woven fabric will provide different effects on seam quality. The expectation on seam quality for various apparel products will also be different. For example, sportswears focus on seam performance, whereas shirts focus more on seam appearance. However, the definition of seam quality is still ambiguous. As a result, analysis of seam quality can provide a more realistic study. The purpose of this study was to analyse the seam quality with commercial sewing threads in woven fabric. This study focused on four major objectives: 1) to study the critical dimensions for measuring seam quality; 2) to study the effect of sewing thread size on each critical dimension for seam quality evaluation under various fabrics and sewing conditions; 3) to evaluate the effectiveness of modelling techniques for each critical dimension of seam quality evaluation; 4) to study each dimension for seam quality evaluation in various apparel products using proposed model. In this study, seven different sizes of spun polyester sewing threads were sewn on 20 cotton, 15 cotton-polyester and 15 cotton-spandex woven fabrics respectively. To study the effect of sewing thread size, stitch density and fabric properties on seam quality, the multiple regression models were selected in this study. They were- linear and logarithmic models. To compare the performance of these two models, the coefficient of determination (R2), standard error and the mean square error (MSB) were used to identify which model fits for measuring seam quality. Based on the proposed model, each dimension of seam quality evaluation could be integrated in five apparel products- blouse, shirt, denim trousers, T-shirt and lingerie. Through evaluation table, a total of 10 professional researchers were distributed a weightage in percentage to each dimension of seam quality in these five apparel products. In this study, through subjective ranking, there were three critical dimensions for measuring seam quality- seam efficiency, seam puckering and seam boldness. Models of seam efficiency, seam puckering and seam boldness for cotton, cotton-polyester and cotton-spandex woven fabrics were formulated. The result revealed that the logarithmic modelling technique was best fitted for seam efficiency, seam puckering and seam boldness. Through a validation process, the result also found that the proposed model could be effectively applied in various apparel products. The outcomes of this study could provide in-depth analysis of seam quality through different multiple regression modelling technique. The success of this modelling could help apparel manufacturers to evaluate seam quality more effectively when a particular sewing thread size and stitch density are applied on a particular type of fabric. It would facilitate apparel engineers in the production planning and quality control. | en_US |
| dcterms.extent | xix, 258 leaves : ill. (some col.) ; 30 cm. | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2009 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Phil. | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations. | en_US |
| dcterms.LCSH | Seams (Sewing) | en_US |
| dcterms.LCSH | Stitches (Sewing) | en_US |
| dcterms.LCSH | Sewing. | en_US |
| dcterms.LCSH | Textile fabrics. | en_US |
| dcterms.accessRights | open access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b23071746.pdf | For All Users | 3.05 MB | Adobe PDF | View/Open |
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