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Hindi Research Article, J Fashion Technol Textile Eng Vol: 2 Issue: 3
Modeling the Performance Properties on Woolen Handknotted Carpets using Response Surface Methodology
| Seyed Mahmoud Tabatabaei1*, Mohammad Ghane1, Ali Zeinal Hamadani2 and Hossein Hasani1 | |
| 1Department of Textile Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran | |
| 2Department of Industrial Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran | |
| Corresponding author : Seyed Mahmoud Tabatabaei Department of Textile Engineering, Isfahan University of Technology, Isfahan 84156-83111 E-mail: m.tabatabaei@tx.iut.ac.ir |
|
| Received: August 12, 2014 Accepted: September 27, 2014 Published: October 01, 2014 | |
| Citation: Tabatabaei SM, Ghane M, Hamadani AZ, Hasani H (2014) Modeling the Performance Properties on Woolen Hand-knotted Carpets using Response Surface Methodology. J Fashion Technol Textile Eng 2:3. doi:10.4172/2329-9568.1000113 |
Abstract
Modeling the Performance Properties on Woolen Handknotted Carpets using Response Surface Methodology
In this study, the main purpose is to predict the performance properties of woolen hand-knotted carpets using response surface methodology (RSM). We have considered the thickness loss of surface pile yarns (TL) and compression toughness index (TI) as representative of the compression properties, and color difference index of pile yarns (ΔE), tuft size index (TS) and evenness of texture index (ET) as representative of the appearance characteristics. Eighteen woolen hand-knotted carpet samples with different structural specifications were produced. The carpet samples were subjected to 4000, 8000 and 12000 drum revolutions (wear factor) using a Hexapod tumbler tester. Meanwhile, performance properties of samples were investigated in original and worn out carpet samples. Factorial experimental design and response surface method were applied for modeling of each performance property. To optimize some initial models, the Box-Cox transformation was used. In addition, contribution of different variables was determined. The models showed a desirable fit and high adjusted R2 values were resulted. The ANOVA test showed that the obtained models are valid at 5% significant level.
