Investigation of interactions between fabric performance, sewing process parameters and seam pucker of shirt fabric

Seam pucker is a common problem in sewing. It not only affects the appearance of product, but also affects product performance. The purpose of this study is to quantify the complex dynamic interactions between fabric performance, sewing process parameters and seam pucker. In order to solve the problem of shirt seam pucker, this study selected four kinds of shirt fabrics, three kinds of polyester sewing threads, three kinds of stitch density and four kinds of seam types for experiments. Through unitary regression analysis, the subjective and objective evaluation results are consistent. Further analysis the results of objective experiment revealed that fabric performances, seams type, sewing thread and stitch densities all have impact on seam pucker. Meanwhile also find out the sewing process parameters for the four fabrics when the seam shrinkage’s were smallest, so it’s helpful for the apparel enterprises to improve seam quality. Multiple linear regression analysis of experimental results show that fabric performances has the greatest influence on seam pucker, thickness, weight and warp density of fabric properties significantly affect seam pucker. And as the breaking elongation of sewing thread increases, seam pucker also increases. Stitch densities and seam type has the least affected on seam pucker, they affect the seam pucker by changing the extension of stitch and thickness of fabric at the seam, respectively. Seam type has greater impact on fabrics that are prone to seam pucker, seam type T1 get larger seam shrinkage than T4. Finally, the complex dynamic interactions was quantified and expressed through mathematical models.

The impact of sewing thread's tensile behavior and laundering process on the seam puckering of elastic and normal fabrics

PurposeThe aim of the present study is to consider the influence of the tensile behavior of fabric and sewing thread on the seam appearance.Design/methodology/approachIn this study, the formation of seam puckering on two elastic and normal woven fabrics was explored. In order to prepare samples, various sewing threads were applied. Test specimens were sewn under five different thread tension levels. Then the appearance of samples was evaluated subjectively to determine their seam puckering grade before and after the laundering process.FindingsThe obtained outcomes of this study present that although sewing thread tension increment decreases the seam pucker ranking in the similar sewing condition, elastic fabrics have a greater seam pucker grade compared to the normal fabric due to the fabric extension and contraction during sewing and after sewing process, respectively. In addition, the elastic strain of the sewing thread is the key factor that determined sewing thread's tendency to make seam puckering. Moreover, the laundry process due to the relaxation of the sewing thread decreases the seam pucker grade.Originality/valueThe consistency of the tensile property of fabric and sewing thread is a crucial parameter in improving the seam appearance and obtaining a smooth seam.

Investigation of sewing and water repellent performance of outdoor clothing

Purpose Durability of textile materials under wet conditions has become very important in recent years. The water repellency performance of fabrics should be maintained in the seam areas. The purpose of this paper is to analyze the effect of water repellent agents and sewing threads on the seam and water repellency performance properties of woven fabrics. Design/methodology/approach 100 percent polyester woven fabrics were treated with three different water repellent finishing agents (silicone, fluorocarbons with 6 and 8 carbons) and then sewn with different sewing threads (unfinished/water repellent finished polyester/cotton corespun and polyamide filament). Afterwards, mechanical properties, seam performance and water repellency properties of these materials were measured. Findings The effect of finishing which was statistically significant on seam strength only in warp direction was significant on seam elongation and efficiency in both warp and weft directions. Seam strength, seam efficiency, seam slippage and seam pucker of fabrics sewn with polyamide threads were higher than others. The fluorocarbons applied to the fabrics gave higher water repellency values than silicones. In addition, as the chain length increased in fluorocarbons, water repellency performance increased. Sewing process reduced water resistance of fabrics; however, water repellent finish applied to the threads increased water resistance of fabrics. Originality/value As a result of the literature review, it was seen that water repellency property of a wear were studied in only seamless areas of fabrics. Originality of this study is that the water repellency properties are also analyzed in the seam areas of the fabrics and evaluated together with the seam performance characteristics.

Automatic seam pucker evaluation using support vector machine classifiers

Purpose The purpose of this paper is to propose a novel method using support vector machine (SVM) classifiers for objective seam pucker evaluation. Features are extracted using wavelet analysis and gray-level co-occurrence matrix (GLCM), and the samples are evaluated using SVM classifiers. The study aims to solve the problem of inappropriate parameters and large required samples in objective seam pucker evaluation. Design/methodology/approach Initially, seam pucker image was captured, and Edge detection and Hough transform were utilized to normalize the seam position and orientation. After cropping the image, the intensity was adjusted to the same identical level through histogram specification. Then, the standard deviations of the horizontal image and diagonal image, reconstructed using wavelet decomposition and reconstruction, were calculated based on parameter optimization. Meanwhile, GLCM was extracted from the restructured horizontal detail image, then the contrast and correlation of GLCM were calculated. Finally, these four features were imported to SVM classifiers based on genetic algorithm for evaluation. Findings The four extracted features reflected linear relationships among five grades. The experimental results showed that the classification accuracy was 96 percent, which catches up to the performance of human vision, and resolves ambiguity and subjective of the manual evaluation. Originality/value There are large required samples in current research. This paper provides a novel method using finite samples, and the parameters of the methods were discussed for parameter optimization. The evaluation results can provide references for analyzing the reason of wrinkles during garment manufacturing.

Development of a Sewing Machine Controller for Seam Pucker Reduction using Online Measurement Feedback System

An automated sewing machine controller and a three-dimensional measurement system have been developed to find the optimum sewing condition that minimizes seam pucker. It is already known that there are various factors affecting the seam pucker. However, the selection of sewing conditions for reducing seam pucker has relied on the experience of skilled workers. In this study, thread tension, presser foot pressure, and stitch length were chosen as the parameters. Parameter settings were controlled by a computer, which enabled the automatic generation of samples with various combinations of sewing conditions. The seam pucker grade was determined from the scanned three-dimensional sample using a fractal dimension calculation. The optimum sewing conditions for a given sample can be determined from this result. The efficiency of the system was verified by comparing the newly developed method with the existing subjective evaluation method.