Modeling the consumption of sewing thread for stitch class 301 through image analysis by using Fourier series. Issue 15 (August 2022)

• Record Type: Journal Article
• Authors: Javed, Zafar; Ahmad, Fayyaz; Khan, Qammar; Naeem, M Salman; Javaid, M Usman; Jabbar, Abdul; Hassan, Zameerul; Karahan, Mehmet
• Is Part Of: Textile research journal. Volume 92:Issue 15/16(2022)
• Page Start: 2792
• Page End: 2799
• Publication Date: 2022-08
• Subjects: Stitch class 300 -- Fourier series -- mathematical model -- sewing thread consumption; Textile industry -- Periodicals; Textile fabrics -- Periodicals; Textile research -- Periodicals; Textiles et tissus -- Industrie et commerce -- Périodiques; Textiles et tissus -- Périodiques; Textiles et tissus -- Recherche -- Périodiques; Electronic journals; 677.005
• DOI: 10.1177/00405175211017400
• Languages: English
• ISSNs: 0040-5175

Abstract

This research work aims at modeling the sewing thread consumption for stitch class 301 through image analysis by using Fourier series. A mathematical model was developed by using the geometry of stitch class 301 for calculating sewing thread consumption. The modeling of stitch class 301 was conducted by changing the stitch density and thickness of the stitched fabric. The stitch density was adjusted by varying the stitch length (2, 3 and 4 mm) and the thickness of stitched fabric (2, 3 and 4 plies of fabric).The interlacement of sewing thread between the needle and bobbin was used for the measurement of arc length of one stitch. The total consumption of sewing thread was determined by multiplying the arc length by 4. The developed model was verified by using nine different stitched samples for comparing the predicted and measured values of sewing thread consumption. This model predicted the sewing thread consumption with 95% accuracy. Error percentages were also calculated for determining the major influencing factors that affected the sewing thread consumption. The proposed model can effectively be employed in garment industries for determining sewing thread consumption.