Viscoelastic Behavior and Wrinkle Formation in Cotton- Polyester Garments: A Data-Driven Approach for Textile Care

Year : 2025 | Volume : 13 | Issue : 04 | Page : 50 60
    By

    Patil Naomi Sachin,

  • Vrishti Garg,

  • Manoj Soni,

  • Khushi Kumari,

  • Aliza,

  1. Scholars, Department of Mechanical and Automation Engineering, Indira Gandhi Delhi Technical University for Women, Delhi, India
  2. Scholars, Department of Mechanical and Automation Engineering, Indira Gandhi Delhi Technical University for Women, Delhi,
  3. Professor, Department of Mechanical and Automation Engineering, Indira Gandhi Delhi Technical University for Women, Delhi, India
  4. Scholars, Department of Mechanical and Automation Engineering, Indira Gandhi Delhi Technical University for Women, Delhi, India
  5. Scholars, Department of Mechanical and Automation Engineering, Indira Gandhi Delhi Technical University for Women, Delhi, India

Abstract

This study investigates the wrinkle behavior of cotton-polyester blended fabrics by analyzing data from over 1,200 store-handled garments. Integrating concepts from polymer chemistry and computer vision, it aims to establish a smart textile care framework based on fiber-specific wrinkle characteristics. The research identifies how cotton’s hydrophilic and non-elastic structure results in increased wrinkling, while polyester’s thermoplastic and crystalline properties enhance wrinkle resistance. Elastomeric fibers like Lycra contribute to wrinkle recovery through reversible elastic deformation. A visual scoring rubric was developed to assess wrinkle severity, frequency, and surface coverage, which was then combined with YOLO-based image analysis to automate wrinkle detection. This process enabled the generation of a composite wrinkle score by correlating visual wrinkle patterns with fiber compositions. To systematically examine the impact of different fiber blends, Central Composite Design (CCD) was employed to create an experimental matrix covering seven polymer types. This facilitated the development of a temperature prediction model capable of recommending optimal ironing temperatures between 130–175°C for each fabric type. The results show a consistent inverse correlation between polyester content and wrinkle formation, offering data-driven insights for designing more efficient garment care protocols. The study presents a significant advancement in intelligent fabric management, enabling the development of fiber-aware ironing systems that optimize energy usage, preserve fabric integrity, and improve user convenience. By bridging material science with machine learning, this research contributes a scalable solution for personalized garment care in both domestic and industrial settings.

Keywords: Wrinkle formation, viscoelasticity, cotton-polyester blends, polymer chemistry, ironing temperature prediction.

[This article belongs to Journal of Polymer & Composites ]

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How to cite this article:
Patil Naomi Sachin, Vrishti Garg, Manoj Soni, Khushi Kumari, Aliza. Viscoelastic Behavior and Wrinkle Formation in Cotton- Polyester Garments: A Data-Driven Approach for Textile Care. Journal of Polymer & Composites. 2025; 13(04):50-60.
How to cite this URL:
Patil Naomi Sachin, Vrishti Garg, Manoj Soni, Khushi Kumari, Aliza. Viscoelastic Behavior and Wrinkle Formation in Cotton- Polyester Garments: A Data-Driven Approach for Textile Care. Journal of Polymer & Composites. 2025; 13(04):50-60. Available from: https://journals.stmjournals.com/jopc/article=2025/view=213271


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Regular Issue Subscription Original Research
Volume 13
Issue 04
Received 16/04/2025
Accepted 28/04/2025
Published 06/06/2025
Publication Time 51 Days
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