Use of artificial neural networks for modelling the drape behaviour of woollen fabrics treated with dry finishing processes

Senem Kursun Bahadir*, Fatma Kalaoglu, Simona Jevsnik, Selin Hanife Eryuruk, Canan Saricam

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

The relationship between fabric drape, low stress mechanical properties and finishing processes is relatively complex. This paper demonstrates the possibility of using artificial neural networks to identify the fabric drape of woollen fabrics treated with different dry finishing processes (stenter, decatising, superfinish, formula, KADE strong/weak - autoclave decatizing). The mechanical and surface properties of woollen fabrics were measured by both the KES-FB and FAST systems, and then the results obtained were applied to artificial neural network (ANN) modelling. ANN models were compared by verifying the Mean Square Error (MSE) and Correlation coefficient (R-value). The results indicated that each model is capable of making quantitatively accurate drape behaviour predictions for wool fabrics (Rmin = 0.92, MSEmin = 0).

Original languageEnglish
Pages (from-to)90-99
Number of pages10
JournalFibres and Textiles in Eastern Europe
Volume23
Issue number2
Publication statusPublished - 2015

Bibliographical note

Publisher Copyright:
© 2015, Institute of Biopolymers and Chemical Fibres. All rights reserved.

Keywords

  • Artificial neural network
  • FAST
  • Fabric drape
  • Finishing processes
  • KES
  • Wool fabrics

Fingerprint

Dive into the research topics of 'Use of artificial neural networks for modelling the drape behaviour of woollen fabrics treated with dry finishing processes'. Together they form a unique fingerprint.

Cite this