Prediction of Fabric Stiffness

Abstract

Abstract:In this research it is aimed to predict fabric stiffness by ANNs (artificial neural networks) using inputs like some fabric parameters and finishing treatments. For this aim 27 various fabrics were weaved with using 3 different weft densities, 3 different weft yarn sizes, 3 different weaving patterns. The fabrics were produced of using 100% Pes on the warp yarn and 100% cotton on the weft yarn. And 3 concentrations of 2 finishing treatments were applied on the 27 various fabrics. The stiffness properties of fabrics were tested by stiffness tester with using ASTM (American society for testing and materials) D 4032-94 circular bending test method. Then prediction models were tried to be established with using production parameters for inputs and measured stiffness values for outputs by ANN techniques at MATLAB ® programme. ANN models were established to predict fabric stiffness with the selected 5 inputs such as weft yarn number, weft density, weaving pattern, finishing treatments and concentrations. While the network models were established, it was used feed-forward and back propagation network. While the network models were established with the aim of determining optimum network, 10 alternative models were established by changing of transfer function, neuron numbers and number of hidden layers. The best results whose regression degree is R = 0.96, were obtained with two hidden layer networks with 30 neurons.

Artificial-Neural-Network-Based Predicted Model for Seam Strength of Five-Pocket Denim Jeans: A Review

“…Moreover, using AI techniques such as artificial neural networks, models have been developed that accurately predict fabric stiffness based on various fabric parameters such as weft yarn number and its density, weaving pattern, finishing treatments, and concentrations. ANN-based models accurately predict fabric stiffness before production using these parameters [34].…”

Prediction of Mechanical Properties of Woven Fabrics by ANN

“…Artificial neural networks (ANNs) have a wide range of application in the textile industry as they are powerful in many prediction-related problems in the textile sector, such as the prediction of textile properties like identification, pattern recognition, classification and defect analysis 8 . Figure 1 represents the network structure for the prediction of six mechanical properties: (tensile strength (N), bending length (m) and elongation %) in both the warp and weft directions.…”

Prediction of air permeability properties with artificial neural network models of fabrics which applied softness and water repellent finishing treatments

“…6 At the studies of Erenler and Oğulata in 2013, it is defined that fabric stiffness can be successfully predicted via ANN Models by using the fabric parameters at which finishing processes are applied. 7,8 Militký and the others have carried a study on the air permeability of the woven fabrics with different weft yarn counts and they revealed that the success of the NN model was more likely successful than regression model which were established with fabric constructions as inputs and the NN model established with fabric porosity as input. 9 In this study air permeability features of the fabrics which were weaved at different characteristics were tried to be guessed at preproduction stage.…”