Predicting the unevenness of polyester/viscose/acrylic-blended open-end rotor spun yarns

ERBİL Y., BABAARSLAN O., İLHAN İ.

JOURNAL OF THE TEXTILE INSTITUTE, cilt.106, sa.7, ss.699-705, 2015 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 106 Sayı: 7
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1080/00405000.2014.936138
  • Dergi Adı: JOURNAL OF THE TEXTILE INSTITUTE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.699-705
  • Anahtar Kelimeler: yarn unevenness, statistical analysis, mixture spinning, ternary blends, OE-rotor yarn, ARTIFICIAL NEURAL-NETWORK, ELONGATION PROPERTIES, HAIRINESS, MODEL, STRENGTH
  • Çukurova Üniversitesi Adresli: Evet

Özet

Mixture spinning aims to bring together the best properties of two or more fiber types into one single yarn. In mixture spinning, while some fiber types have impacts to increase the yarn strength, the other fiber types may have impacts to improve the yarn unevenness values. In this study, it is aimed to obtain a regression model that predicts the unevenness (CVm%) of polyester/viscose/acrylic (PES/CV/PAN)-blended OE-rotor spun yarns. For this purpose, the methods of statistical analysis as analysis of variance and Combined Analysis were used. In the context of experimental design, basic parameters affecting the yarn unevenness were selected as: the type of fiber mixture (by carding machine or drawframe), blend ratio (from 0 to 100% at five different rates), and the yarn count (24, 30 and 36 tex). As a result, a statistically significant (p = 0.05) model has been established to estimate the unevenness of PES/CV/PAN blended OE-rotor yarns. In addition, two-dimensional surface graphics have been created to view CVm% values according to the fiber ratios in ternary mixtures. For all of the yarn samples, the increase in acrylic ratio has been found to have positive impact on the CVm% values.