NOPR Collection:

Reddish brown pigments from Alternaria alternata for textile dyeing and printing

Tue, 01 Sep 2015 00:00:00 GMT

Title: Reddish brown pigments from Alternaria alternata for textile dyeing and printing Authors: Devi, Sagarika; Karuppan, Perumal Abstract: Reddish brown pigment has been extracted from dry mycelium of Alternaria alternata in methanol and then evaluated for dyeing efficacy on cotton fabrics. The pigment producing fungus A. alternata is grown in maize grain broth maintained at pH 6. Shade of Sienna is obtained on cotton. Dyed cotton fabric has recorded a grey scale rating of 2-3 and 4-5 for colour fastness and multi fibre staining respectively. Maximum dye absorption of 63% has been observed on cotton fabrics. The antimicrobial property of dyed fabric is also tested. Potent antimicrobial activity is observed against Staphylococcus epidermis (42 mm) and Streptococcus pyogenes (39 mm). Page(s): 315-319

Predicting the intermingled yarn number of nips and nips stability with neural network models

Tue, 01 Sep 2015 00:00:00 GMT

Title: Predicting the intermingled yarn number of nips and nips stability with neural network models Authors: Özkan, İlkan; Kuvvetli, Yusuf; Baykal, Pinar Duru; Şahin, Cenk Abstract: This study aims at predicting the effects of selected process parameters on nips stability and number of nips by using different artificial intelligence methods. Partially oriented polyester yarn with 283 dtex linear density and different numbers of filaments are intermingled with different speed and pressure levels. The feed forward neural network with multi-hidden layers (ML-FFNN) and general regression neural networks (GRNN) have been selected as artificial intelligence methods. The number of filaments, intermingling speed and pressure values are used as input variables on the artificial neural networks. The effects of number of hidden layers on the ML-FFNN and number of nodes in the hidden layer are investigated. Based on comparative results, the ML-FFNN is found to give better performance (at most 6%) than by GRNN in terms of prediction accuracy on train and test data sets. It can be concluded from this study that the neural networks has great ability to predict intermingling process parameters. Page(s): 267-272

Effect of finishing on performance characteristics of woven and warp-knitted terry fabrics

Tue, 01 Sep 2015 00:00:00 GMT

Title: Effect of finishing on performance characteristics of woven and warp-knitted terry fabrics Authors: Akaydin, M; Yilmaz, K; Yilmaz, N D Abstract: The influence of some finishing processes has been studied on the performance characteristics of woven and warp-knitted terry fabrics with open-end pile warp. Terry fabrics of similar structural parameters have been produced by weaving or warp knitting and then subjected to finishing processes which are commonly applied by the textile industry. Samples are extracted at different stages of the finishing processes. Water absorption behavior, structural parameters, and mechanical properties are evaluated and the results are compared by statistical analysis of the obtained data. It is observed that compared to greige terry fabrics, the finishing treatment increases basis weight and dimensional stability due to shrinkage occurred with relaxation, water absorption rate due to the removal of size and other hydrophobic substances, and elongation ratio because of the elimination of size film during pretreatment processing. Woven terry fabrics give higher strength values and warp-knitted terry fabrics show higher elongation. Page(s): 301-307

Optimization of spinning parameters influencing the tensile properties of polyester/cotton vortex yarn

Tue, 01 Sep 2015 00:00:00 GMT

Title: Optimization of spinning parameters influencing the tensile properties of polyester/cotton vortex yarn Authors: Senthilkumar, P; Kuthalam, E Sankara Abstract: The influence of vortex spinning parameters on the tensile properties of polyester/cotton vortex yarn has been studied. Polyester/cotton yarn of 50:50 blend ratio have been produced in two different counts (Ne 20s and Ne 40s) each with four different spinning parameters (delivery speed, spindle size, feed ratio and nozzle pressure). Experiments are designed with the aid of response surface method. Accordingly different samples are produced with three levels of each parameter. The tenacity and elongation-at-break have been evaluated from the samples produced with these combinations. It is found that the tenacity of coarser count vortex yarn is influenced by feed ratio and the medium count vortex yarn is influenced by all the spinning parameters considered for this study. Elongation-at-break of coarser count vortex yarn is influenced by the feed ratio and nozzle pressure while that of the medium count vortex yarn is influenced by the spindle size, feed ratio and nozzle pressure. The interactions of spinning parameters have significant influence on the tenacity and elongation-at-break of medium count vortex yarn. On the other hand the interactions have significant influence on the coarser count vortex yarn elongation-at-break, but they do not have any influence on its tenacity. Page(s): 256-266