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Autex Research Journal

The Journal of Association of Universities for Textiles (AUTEX)

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2300-0929
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Use of Taguchi Method and Grey Relational Analysis to Optimize Multiple Yarn Characteristics in Open-End Rotor Spinning

Tanveer Hussain
  • Faculty of Engineering & Technology, National Textile University Faisalabad (37610) Pakistan
/ Farooq Ahmed Arain
  • Department of Textile Engineering, Mehran University of Engineering & Technology, Jamshoro Pakistan
/ Zulfiqar Ali Malik
  • Corresponding author
  • Faculty of Engineering & Technology, National Textile University Faisalabad (37610) Pakistan
  • Email:
Published Online: 2017-03-09 | DOI: https://doi.org/10.1515/aut-2015-0046

Abstract

Rotor speed and twist per metres (tpm) are two key parameters in open-end rotor spinning of cotton yarns. High spinning productivity can be obtained by keeping the rotor speed high and twist level as low as possible. However, too high rotor speed may result in yarn imperfections and too low twist level may result in lower tenacity yarns. This study aimed at optimising the multiple yarn characteristics in open-end rotor spinning using the Taguchi method and the grey relational analysis. Cotton yarn samples of 30 tex were produced on rotor spinning machine with different twist levels (i.e. 500, 550, 600 and 700 tpm) at different rotor speeds (i.e. 70,000, 80,000, 90,000 and 100,000 rpm) according to the Taguchi design of experiment. Optimal spinning process parameters were determined using the grey relational grade as the performance index. It was concluded that for the cotton fibres and yarn count used in this study, optimum properties of the yarns could be obtained at 90,000 rpm rotor speed and 700 tpm.

Keywords: Rotor yarn; open-end spinning; Taguchi’s method; grey relational analysis and optimisation

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About the article

Published Online: 2017-03-09

Published in Print: 2017-03-01


Citation Information: Autex Research Journal, ISSN (Online) 2300-0929, DOI: https://doi.org/10.1515/aut-2015-0046.

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© 2017 Autex Research Journal. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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