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RISS 인기검색어
- 검색키워드
- 저자 : Fahmida Siddiqa (검색결과 2 건)
- 무료
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Efficacy of whip roller setting on physical attributes of denim fabric
Farial Islam Farha,Fahmida Siddiqa,Md. Rashedul Islam 한국의류학회 2017 Fashion and Textiles Vol.4 No.1
Whip roller settings in a weaving machine is one of the vital factor to adjust warp yarn tension properly as well as delivering fault free fabric. The present study was undertaken with an aim to explore the influence of whip roller settings on various physical and mechanical properties of both grey and finished 100% cotton denim fabric in order to select suitable position of whip roller for producing particular (3/1 twill) denim fabric. For this purpose total eight positions of whip roller were selected keeping constant depth with variable height in five cases and constant height with variable depth in three cases. The samples were produced in an air jet loom and some prominence like EPcm, PPcm, areal density, tensile strength, dimensional stability, air permeability, crimp% and skewness were checked. Data analysis of all the results showed that with the ascendance of whip roller, crimp% of warp yarn was decreased whereas crimp% of weft yarn was increased both in grey and finished state. Decreasing the depth of whip roller caused increment of both warp and weft crimp% in both state. Tensile strength in warp way direction was found to increase gradually up to a certain roller height and then decreased whereas air permeability showed reverse trend in both state. Warp density, Weft density as well as areal density was also affected by the alteration in settings of whip roller. Due to reduction of roller depth, warp way tensile strength and lengthwise shrinkage were reduced but air permeability had improved.
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Prediction of whiteness index of cotton using bleaching process variables by fuzzy inference system
Abu Naser Md Ahsanul Haque,Shamima Akter Smriti,Manwar Hussain,Nawshin Farzana,Fahmida Siddiqa,Md. Azharul Islam 한국의류학회 2018 Fashion and Textiles Vol.5 No.1
A fuzzy prediction model has been built based on hydrogen peroxide concentration, temperature and time of bleaching as the input variables and knitted fabric whiteness index as the output variable. The process parameters affecting the whiteness index of cotton knitted fabrics are very non-linear. Fuzzy inference system is a prospective modeling tool as it can map effectively in nonlinear domain with minimum investigational data. Triangular-shaped membership functions were considered for the variables and total 48 rules were created in this study. It was found that the sole effect of the concentration of hydrogen peroxide on whiteness is pretty low, but is affected by temperature noticeably even in a fixed concentration of hydrogen peroxide. The model proposed in the present study has been verified by additional experimental data set. The root mean square, mean absolute error percentage and coefficient of determination (R 2 ) between the predicted and experimental values were found to be 0.536, 0.798 and 0.959 respectively. The results validate that the model can be applied suitably for the prediction of fabric whiteness index in textile industries.
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