Abstract-Digital textile printing(DTP) is becoming more important because the production trend of textile printing goods is adapting to small-lot multiple items. Recently enhanced use of DTP is closely connected with production of high value-added products in fashion industry, which is also appropriate for quick response system(QRS). Quality of DTP depends on pre-treatment, after-treatment, ink, media, printer, etc. One of these parameters, Selection of good media is very important to obtain high quality of DTP products. Especially, the effects of media on printing quality of DTP according to yarn twist and structure of knitting fabric were examined in this study.Two types of yarn twist of 830 t.p.m and 1630 t.p.m for cotton knit were used and five types of media structures were knitted with single circular knitting machine. First, MIU, MMD, SMD's values are closely related with surface roughness of sample as well as printing quality. The hard twist samples were higher values than normal twist samples in the same media structure. In case of SMD, the values increased from plain to corduroy types. Second, aspect of line sharpness, line area, and line width values of hard twist samples decreased from plain to corduroy than those of normal twist samples. Third, line deviation values of hard twist samples, blurriness of line, also decreased than those of normal twist samples.

Digital textile printing (DTP) is widely used because it is more efficient and simpler than conventional textile printing methods. Digital transfer textile printing (DTTP) is one of the most efficient and simplest DTP methods. In this study, the optimum process conditions for DTTP have been investigated, to minimize the distortion of printed images and maximize the color reproducibility. First, a novel measurement method for fabric shrinkage and image distortion was developed. Then 9 characteristic values were defined and a series of experiments were designed and performed using the Taguchi method. Finally, two different multiple-characteristic value analyses were performed on the results. In one method, 9 characteristic values were converted into a single value. In the other method, the characteristic values were divided into 3 groups for analysis. Finally, results from the two methods were compared to determine which method was more suitable.