AI Summary & Key Takeaways
AI InsightIn the content of the study, it was revealed that the fabric comfort specialties can be predicted successfully before manufacture via established ANN Models
📌 3 Key Takeaways
Abstract
In the content of the study, it was investigated that the effects of various production parameters on the fabric comfort properties of clothing aimed woven fabrics by statistical analyze and it was tried to predict the comfort properties of fabrics by using production parameters. In the scope of the study, it was analyzed by using statistical methods that the effects of selected production parameters which were weft fiber type, weft density, weft yarn count, weaving pattern, fabric thickness and fabric weight on the fabric comfort properties which were fabric air permeability, stiffness and relative water vapor permeability(RWVP).Also it was established suitable Artificial Neural Network (ANN) Models by using MATLAB® programme for predicting fabric air permeability, fabric stiffness and fabric relative water vapor permeability with using selected production parameters as inputs. As a consequence, the statistical models established for each one of the comfort specialties was seen to be meaningful with the value of p<0.0001. Also the production parameters examined in the study were defined to be meaningful on the comfort specialties statistically. In the content of the study, it was revealed that the fabric comfort specialties can be predicted successfully before manufacture via established ANN Models
Özet
Çalışma kapsamında giysi amaçlı dokunmuş kumaşlarda farklı üretim parametrelerinin kumaş konfor özellikleri üzerine etkileri istatistiksel olarak incelenmiş, üretim parametrelerinden yola çıkılarak kumaş konfor özelliklerinin tahmin edilmesine çalışılmıştır. Çalışma kapsamında üretim parametresi olarak atkı elyaf cinsi, atkı sıklığı, atkı iplik numarası, dokuma örgüsü, kumaş kalınlığı ve kumaş gramajının kumaş hava geçirgenliği, kumaş yumuşaklığı ve bağıl su buharı geçirgenliği (RWVP) üzerine etkileri istatistiksel olarak incelenmiş ve bu üretim parametreleri girdi olarak kullanılarak kumaş hava geçirgenliği, kumaş yumuşaklığı ve bağıl su buharı geçirgenliğinin tahmin edilmesi için uygun Yapay Sinir Ağı (YSA) modelleri MATLAB® paket programı kullanılarak kurulmuştur. Sonuç olarak; her bir konfor özelliği için ayrı ayrı kurulan istatistiksel modellerin p