Prediction of Fabric Stiffness Based On Fabric Construction | ||
| Industrial Technology Journal | ||
| Article 2, Volume 1, Issue 1 - Serial Number 300, 2023, Pages 21-32 PDF (554.83 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/itj.2023.219376.1005 | ||
| Authors | ||
| Eman Mustafa* 1; abdel Salam Malek1; Sherwet El Gholmy2; Adel EL Geiheini2; Sherien El kateb2 | ||
| 1Textile Department, Faculty of Technology and Education, Suez University, Cairo, Egypt | ||
| 2Textile Engineering Department, Faculty of Engineering, Alexandria University, Cairo, Egypt | ||
| Abstract | ||
| This research presents a statistical tool to predict fabric stiffness based on fabric construction to avoid material waste, effort and time consuming in laboratories testing. Three different blended material of fabric were used that made from wool and polyester with different percentages of material yarns, counts and type (single/ply) of weft yarn, and fabric weave pattern (plain, twill and satin). Quantitative and qualitative variables were used in prediction by applying regression analysis and Artificial Neural Network (ANN) with a suitable coding system for different variables. Three independent models were derived to predict fabric stiffness by using regression analysis and compared to ANN model. Model (3) is the best prediction tool depending on regression analysis to predict fabric stiffness due to higher interpretation of the relation between variables used in prediction of fabric stiffness. Whereas, ANN achieved higher performance of validation (MSE = 7.41E-05) and total value of (R2= 0.967) when comparing to regression analysis model. | ||
| Keywords | ||
| Regression analysis; Artificial Neural Network; Worsted fabric; Prediction performance; Correlation | ||
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