فصلنامه علوم و فناوری نساجی
سال پنجم شماره 1 (بهار 1394)

In this research the effect of yarn characteristics such as yarn count, different percent of polyester/cotton fiers in blend yarn, yarn twist and average of the weft yarn tension at different supplied air pressures and weaving machine speed on the weft yarn speed, and weft arrival time were investigated. Blend polyester-cotton yarns (45 samples(were produced by ring spinning method and the percentage of cotton in the composition changed as 0, 25, 50,7 5, and 100%. The samples were used as weft yarn in an air-jet weaving machine for measuring the weft yarn arrival time and its tension. In order to fid a correlation between the yarn properties and the experimental results, the back-propagation neural network model was adapted. The results showed that all of the parameters have a signifiant inflence on the weft arrival time. However, the most important parameter was found to be the loom speed and consequently the applied air pressure on the weft yarn. The presented neural network model can be used to predict the weft yarn velocity for cotton, polyester and cottonpolyester blend yarns on an air-jet loom with a regression coeffiient as high as R2= 0.98.

There is a high demand in the textile industries for environment friendly processes with minimum wastewater generation. In addition, the reduction of oil reservoirs has led to an increased interest in production of biodegradable polymers from renewable natural recourses like plants. Poly lactic-acid (PLA), the fist synthetic fier produced from renewable materials, combines ecological advantages with excellent performance for textile application. PLA actually fils the gap between synthetic and natural fiers and has found a wide range of applications, from medical and pharmaceutical applications to environmentally benign fim and fiers for packaging, and clothing. In recent research studies, PLA nanofiers have been used as a new system for drug delivery. PLA has found a growing demand in textile industries as a result of its renewable source origin, ease of melt spinning and process-ability and ease of composting and recycle-ability. This review provides an up-to-date information about production, properties, performance and applications of PLA fiers.

Selection of the best dyeing recipe for yarn dyeing is one of the major concerns for the dyers in handmade carpet and textile industries. The purpose of this work is to develop expert system software for selection of the most appropriate dyeing recipe for handmade woolen carpet with natural dyes. Knowledge based data in this expert system is collected from different sources such as reference books, papers and experienced dyers. After forming the corresponding data-base and surveying the inference engine, Natural Dyes Expert System (NDES(was developed as artifiial intelligent software. The system was designed using C #. net programming software in the Visual Studio platform and graphical methodology of WPF & Direct X. Knowledge data base of the system was created using SQL Server 2014 and also, LINQ technology was employed for connecting the system to the data-base. The system can advise users to choose the best initial dyeing recipe for dyeing wool fiers with natural dyes. The outcomes of the present research can be listed as helping inexperienced dyers, providing extensive information of natural dyes and also presentation of the dyeing recipe alongside with their fial expected color fastness and properties.

In this research, silicon softener was used on untreated and corona treated cotton fabrics. Cotton fabrics were treated at different concentrations of silicon softener. The bending length, crease recovery angle and wetting time were determined. By increasing the concentration of softener, the bending length decreased while the wetting time and crease recovery angle increased. Scanning electron microscopy (SEM(was used for investigation of surface morphology. The SEM micro-graphs from the samples showed etching effect on the cotton fabric samples treated with corona discharge which could be a reason for better absorption of the softener into the fiers. The silicon softener was also observed on the surface of treated and untreated cotton fabrics. The FTIR/ATR analysis confimed the chemical change on the surface of treated cotton fabric which could be due to the increase of hydrophilic groups. The results also showed that the presence of the silicon softener on the surface of corona treated cotton fabric enhanced the hydrophilicity. These results are in agreement with the results of bending length, wetting time and crease recovery angle. The results showed the orientation of silicon softener on the surface of untreated cotton and absorption of softener into the cotton fabrics treated with corona discharge.

Considering the cultural diversity, understanding consumer behavior and evaluating the customer buying decision process are very important. In this research, the factors affecting customer buying process of clothing were investigated. To attain this objective, a questionnaire about the parameters involved in the purchase of clothing was prepared. The questionnaires were distributed and filed by shoppers and retailers in Isfahan and Tehran grand bazar. The statistical analysis of the responses showed that the affecting factors on purchase of garments were mainly quality, price, aesthetic, brand, design and discounts. The results showed that the most important factor for purchase of coats was its quality; while aesthetic and fashion design had a higher degree of importance in purchase of casual night dress. Based on this survey, some suggestions are proposed to increase local clothing sale and brand. Branding is one of the most important aspects of any large or small business or retail.

The rise of China and other Asian countries with cheap labor, led to a massive transfer of textile industry to these countries. Despite the higher labor wages in the North America and European countries, some textile groups adapted a Fast-Fashion business model and competed with low-cost Asian textile products successfully. The clothing industry in Iran suffered from Chinese cheap imported textile goods during last years, but following the Fast-Fashion model is a strategic approach to recover it. This can lead to increased competitiveness and growth of the garment industry in the country.