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Effect of Pretreatment on the Smoothness Behaviour of Cotton Fabric

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Effect of Pretreatment on the Smoothness Behaviour of Cotton Fabric Nidhi Sisodia*, M.S. Parmar, Effect of Pretreatment on the Smoothness Saurbh Jain Behaviour of Cotton Fabric DOI: 10.5604/01.3001.0013.2901 Northern India Textile Research Abstract Association Ghaziabad, Before dyeing, woven cotton fabrics have been passed through different pretreatments like Ghaziabad, India, desizing, scouring, bleaching and mercerising to enhance quality. In every treatment cotton * e-mail: [email protected] fabric is treated with different chemicals and mechanical processes. After these treatments, the feel of the fabric has been changed. The change in feel or in terms of the hand value of treated fabrics were analysed by determining the bending length, crease recovery angle, SEM, FTIR, surface roughness and smoothness properties. Other physical properties viz. the tear and tensile strength were also evaluated. Fabric surface roughness and smoothness were determined using the Kawabata Evaluation System (KES) and digital image proces- sing method. Using MATLAB software, digital image processing techniques were used to evaluate the roughness index. The study revealed that the pretreatment process alters the fabric surface. Statistical analysis (ANOVA) was carried out using SPSS software in order to establish the relationship between the pretreatment process effect on the bending length, smoothness and crease recovery angle. Key words: dyeing, pretreatment, desizing, scouring, bleaching, statical analysis. Introduction purposes a commercial desizing enzyme Tegewa test drop test method, spray test was used. method, and whiteness index. At the present time the garment indus- try and fabric producers are confronting Pretreatment a great deal of issues with respect to the Analysis of fabric samples The cotton fabric was pretreated by de- hand feel of material. There is no stand- sizing, scouring, bleaching & merceri- The cotton fabrics (woven) were pre- ard method available using which the sation as per the sequence given in Fig- treated (singed, desizing, scouring, smoothness of fabric can be measured. ure 1 using a standard recipe, shown in bleaching and mercerisation) as per the Just subjective evaluation is completed to Table 1. standard recipe. The test standards used judge the feel of the fabric. When a fabric for the study are given in Table 1. or garment of clothing is purchased, the Singeing and desizing consumer constantly attempts to pick it based on his own evaluation technique Singeing removed loose and unwant- for a specific end use [1]. ed fibres from the fabric surface to get a smooth surface. Enzymatic desizing Grey fabric The surface of any wearable material was done after singeing. can be modified by chemical or mechan- ical procedures. Fabric smoothness is Scouring specifically related to the fabric surface Desized fabric was treated with alkaline friction. Fabric surface smoothness be- solution to scour it. This process im- Singeing haviour depends upon the yarn qualities, proved the absorbency of the fabric by weave points of interest, and finally on removing impurities. the sort of chemical treatment. The use of chemical treatment makes a fabric Bleaching Desizing rough or smooth. Chemical or mechani- Woven cotton fabric was bleached using cal treatment modifies the surface prop- hydrogen peroxide to remove the natural erties of fabric. The chemical treatment colouring [3]. of cotton to alter the physical properties of fibres without changing their shape is Mercerisation Scouring a common practice in the textile indus- Chain mercerisation was used to merce- try [2]. rise the cotton fabric. The concentration of sodium hydroxide was 52° Tw [4]. Material Bleaching In this study plain weave (1/1) cotton This work centered around the treatment fabric of 128 g/m2 mass and 120 and of cotton with various pretreatments: 70 ends and picks per inch, respective- the cotton texture was successively pre- ly, was procured from surya processors treated as shown in Figure 1, utilising in the grey stage. All the chemicals, like the standard formula given in Table 1. Mercerization sodium hydroxide, sodium carbonate, After every pretreatment process the hydrogen peroxide etc., used in the study treated sample was tested for its qual- were of commercial grade. For desizing ity using standard test methods viz. the Figure 1. Flow chart of process sequence. Sisodia N, Parmar MS, Jain S. Effect of Pretreatment on the Smoothness Behaviour of Cotton Fabric. 47 FIBRES & TEXTILES in Eastern Europe 2019; 27, 5(137): 47-52. DOI: 10.5604/01.3001.0013.2901 Table 1. Test standard. Statistical analysis S. no. Test name Test standard Experimental data were analysed using 1 GSM IS 1964:2001 SPSS (version 20). One-way ANOVA and 2 Thread density (EPI/PPI) IS:1963-1981(reaffirmed:2004 ) Multivariate Anova were used to compare 3 Count (IS 3442:1980) means. The null hypothesis (Ho) is that 4 Crease recovery IS 4681-1968 there is no relationship between the types 5 Bending length IS6490-1971 of processing treatment of the fabric and 6 Tear strength ISO-13937-1 the coefficient of friction (smoothness), 7 Tensile strength ISO 13934-1 bending length and crease recovery when using a digital image processing system. In the alternative hypothesis, there is a re- The change in fabric surface roughness face plot in Matlab. The colour of indi- lationship between the types of processing or smoothness after the pretreatment pro- vidual pixels was plotted as the height treatment of the fabric and the coefficient cess was determined using the ‘Digital in the graph. As there is a difference of friction (smoothness), bending length Image Processing (DIP)’ method using between the colour of different regions and crease recovery of fabrics when us- MATLAB software and the Kawabata of the fabric, this causes a variation in ing a digital image processing system. Ho Evaluation System (KES-F), a scanning the height of the plot. This difference is will be rejected when the p-value turns electron microscope from 30 Kv = JEOL used to determine the surface roughness. out to be less than a pre-determined sig- (JAPAN) model JSM-6360. These meth- An appropriate computer programme nificance level, i.e. 0.05. ods are described below. was written with due consideration of the various parameters of the three dimen- Result and discussion Digital image processing method sional surface plot of the scanned fabric The DIP method is based on the theory of images, and simulation was finished uti- The physical properties of fabric like the surface height variation measurement. In lising Matlab programming to obtain the mass, ends per inch/picks per inch, bend- accordance with this method, fabric sam- fabric surface roughness index [6]. ing length, crease recovery angle and ples were scanned using a 600 dpi digital tensile strength along with the surface smoothness in terms of the coefficient of image processing scanner [5]. After scan- Kawabata evaluation system friction (MIU) and surface roughness in ning, the images obtained were cropped Coefficients of friction (MIU) were de- terms of the peak height, using a digital so as to have a uniform and regular fig- termined using the Kawabata system. image processing system for all 6 fabrics ure. Using Matlab software, the simula- MIU was determined in the warp and treated along with gray fabric, are as- tion and surface roughness were plotted. weft directions for fabric samples on the sessed in Tables 2 and 3. The images obtained were first inverted sides that would be in contact with the so that the lighter areas represented the skin during wearing [7]. From the table it is clear that the mass of densely populated part of the fabric and the samples varies from 118 to 128 g/m2. the dark parts – the sparsely populated re- The frictional coefficient MIU is calcu- The mass of the grey fabric (128 g/m2) gion [6]. The images were transformed to lated by averaging the output over the is found to be higher than the others gray scale and then loaded into Matlab. distance between 0 to 20 mm using an due to the presence of the sizing agent. To remove noise, Gaussian filters were integrator [8]. Ends/inch and picks/inch of the treated applied. The degree of smoothening was fabric samples i.e. samples having un- determined by the standard deviation of The frictional coefficient is defined as: dergone mercerisation treatments, were the Gaussian, which is generally taken found to be higher than those of the grey MIU = F/P as 5 [6]. A surface plot is three dimen- due to wet shrinkage during processing. sional, connecting a set of data points. Where F – frictional force, N, P – sensor The increase in ends/inch and picks/inch The images were then converted to a sur- load, N. also increase the tear strength of the treat- Table 2. Physical properties of fabric. Crease recovery Coefficient Tensile strength, N Tear strength, g Bending length, cm Sample Mass, Ends Picks angle of friction-Kawabata code g/m2 per cm per cm (warp + weft ) Warp Weft Warp Weft degree Warp Weft Warp Weft Grey 128 48 28.8 576 259 1138 569 106 2.45 1.75 0.15 0.152 Singed 124 48.8 28.8 560 270 1112 536 110 2.40 2.80 0.158 0.161 Desized 118 50.4 31.2 520 230 1150 720 140 1.58 1.46 0.167 0.171 Scoured 124 51.2 32 580 240 1064 676 144 1.55 1.42 0.156 0.158 Bleached 126 53.6 32.8 700 271 897 640 146 1.56 1.40 0.153 0.152 Mercerised 127 54.4 32 681 258 977 670 156 1.40 1.38 0.149 0.136 Table 3. Roughness index measured by DIP method. Maximum decrease Fabric sample Grey Desized Scoured Bleached Mercerised in roughness index, % Maximum height of peaks 28 30 50 60 16 42% 48 FIBRES & TEXTILES in Eastern Europe 2019, Vol.
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