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Processing, Dyeing & Finishing
  Effect of steaming process on elastic denim yarns

In elastic denim yarns, the spandex linear density is an influential and considerable parameter especially in the variation of the RKM, elongation at break and twist, find B Jaouachi and M Sahnoun.

The elastic yarns are complex structures that are not easily controllable especially at the time of the severe requests because of their heterogeneous compositions. Elastic yarns are known as the sheath and spandex or Lycra® as the core or the central part of the stretch yarn structure [3]. The external part is often cotton or another different fibre (PET/Viscose, PET, jute, etc). These core spun yarns are frequently used especially like a wrap of screen in weaving.

The elastic yarns were studied in 1970 by Balasubramanian and Bhatnagar [1]. They examined the effect of the conditions of production on the tensile strength of core spun yarns. The provision of the filament of Spandex in the total structure of the thread (PET/Viscose) has been recently the subject of interest of Babaarslan and Osman [2]. In this study, statistical methods are necessary to find out the important parameters, which are most influent on mechanical and physical properties.

Materials and methods


Two elastic yarns of 59 tex linear density, but with two different linear density of Spandex -- 156 dtex and 78 dtex -- are used. The formation of elastic yarns is made on continuous slip while adding on this one two rollers in the form of metal tube turning in the same direction located under the reels of wick. The value of desired draft (drawing) is fixed using an electronic system, Amsler Spandex®, and this value is in connection with the percentage of the elastic filament in the yarn. The elastic yarn has physical properties (breaking strength, RKM, elongation at fracture, torsion, hairiness etc), which are unverifiable and frequently change value during later processes of transformation. The authors stipulate that this is due to several parameters such as the drawing of the filament spandex during the formation of the core spun yarns, with conditioning (temperature of transformation and realization and moisture) and especially with the steaming process. To study the influence of the steaming process on the characteristics of core spun yarn, the authors proposed to study only one linear density of 17 Nm with spandex filament counts 78 dtex and 156 dtex by applying the method of experimental designs.

The equipment used for the study of resistance and elongation at break is Uster Tensorapid 3, which ensures a tensile test until the rupture and functions according to the principle of the gradient of constant lengthening. For a rack of 24 reels, the authors carried out 10 tests for each reel or spindle. They used a total of 240 tests for each elastic yarn. For the control of twist we used Zweigle twist machinery which ensures automatic untwisting and twisting of the yarn. The length of each specimen measured is 500 mm. According to the selected linear density, they applied the suitable claim.

Finally, the hairiness was measured using Uster Tester 3. The percentage of cotton fibre component: Micronaire=4.23, length = 28.85 mm, Tenacity = 29.1 CN/tex, elongation = 7.6 mm, short fibre percentage= 9.6% and maturity= 0.87.The composition of the cotton used is given by Table 1. The physical properties studied are four: breaking strength expressed by RKM, elongation at break, twist and hairiness. In order to have a better idea on the effect of the steaming process, the authors carried out tests on the same core spun yarn (Nm 17 (78) and Nm 17 (156)). Before steaming process, the corresponding mean values of RKM, elongation at break, hairiness and twist are given in the Table 2.

Table 1. Cotton mixed percentages.

Fibre origins Syrien fibre Spain fibre Togolian fibre Senegal fibre Grec fibre
Percentage (%) 21 11 25 17 26

Table 2. Mean values of physico-mechanical properties of core spun yarns before steaming.

Ls (dTex) RKM (KgNm) Elongation (%) Twist (T/m) Hairiness
78 15,61 9,16 158,52 7,02
156 15,96 12,04 160,87 7,29

Method of experimental designs, Tagauchi

It is a strategy used to facilitate the progressive organization of the acquisition of knowledge. It can also minimize the number of experiments as much as possible but it should not sacrifice the quality of the results, on the contrary, the authors seek the best possible precision [4]. Four parameters were used as data base of orthogonal Table 3 presented in order to study their impact on mechanical properties of core spun yarn after and before steaming process: duration of steaming process (Ds), duration of relaxation (Dr), temperature of steaming (Ts) and spandex linear density (Ls). Table 4 shows the combinations of the regulation points and the factors and levels used in the mixed orthogonal analysis. The study consists in testing the input parameters chosen to be the most probable influential on the mechanical behaviour of core spun yarns. Table 5 shows the results of each test.

Table 3. Factors and levels used in mixed orthogonal analysis.

Factor level Ds (min) Ts (°C) Dr (hours) Ls (dtex)
1 20 60 3 78
2 30 70 5 156
3 40 80 7  

Table 4. Experimental mixed design:

N° test Ls (dtex) Ds (min) Ts (°C) Dr (hours)
1 78 20 60 3
2 78 20 70 5
3 78 20 80 7
4 78 30 60 3
5 78 30 70 5
6 78 30 80 7
7 78 40 60 5
8 78 40 70 7
9 78 40 80 3
10 156 20 60 7
11 156 20 70 3
12 156 20 80 5
13 156 30 60 5
14 156 30 70 7
15 156 30 80 3
16 156 40 60 7
17 156 40 70 3
18 156 40 80 5

Principal Components Analysis (PCA)

In order to quantify input and output parameters as well as the correlations between them, we worked on MATLAB 7.01 and Excel software to show the influence of input/output parameters. The Principal Component Analysis (PCA) method makes it possible to summarize in a graph the importance of the inputs and outputs basis (Mahdi, 2002). The Principal Component Analysis is a statistical method of description and reduction of parameters. Its goal is to find correlations between the data by:

  • An assessment of semblance between the data: it is a question of seeking the points of resemblance (or of opposition) between the data input as well as the homogeneous groups of data.

  • An assessment of the connections between the variables: one seeks to find the variables which are positively dependent, the variation (increase or reduction).

The goal under consideration by the PCA is to gather all the variables (input, output) presented in the form of a cloud in a trigonometrically circle. The variables which are set in one of the rounds are variables known as correlated positively because they evolve/move in the same way. A variation by one parameter will cause the variation in the same way of the others. Then the groups of variables which are opposed by one of the axes of the trigonometrically circle are correlated negatively.

Indeed, the increase in a variable results causes the reduction in the other. The importance of the variables is all the more significant as the corresponding points move away from the centre. Thus, the variables in the central group do not have a very significant influence for the correlations. In principal figure of axial vectors determined by PCA method, correlated groups of dots will be defined on these graphs in the following way:

Results and discussion

Figures 2, 3 and 4 prove that the spandex linear density is an influential and considerable parameter especially in the variation of the RKM, elongation at break and twist. This seems to be logical when we accept that an elastic yarn is only one composite structure and the thicker the inside filament is made up, the better physical properties it will have. A linear density of 156 dtex, a low temperature of steaming process (60°C) and duration of relaxation of 4 hours form a good database to obtain the best physical properties of an elastic core spun yarn intended for hosiery. If the elastic yarn is intended in weaving, nonporous, the method of the experimental designs shows that it is necessary to reach a temperature of 80°C with respect of the other parameters like above.

Figure 4 shows that the porosity increases each time the temperature is decreased. Table 6 shows the contribution values of each input parameter on the physical properties. These different values were calculated between high and low levels of each output parameters. The increase in the twist of elastic yarn after steaming process is about 31.59 T/m (Table 6). If we change the elastic yarn instead of 17 Nm (78 dtex) another yarn 17 Nm (156 dtex).

Twist is well in narrow correlation with the spandex linear density used. This is in agreement with the result found by the PCA method (Figure 6) where the authors announced that twist is in positive correlation with Ls since they are in the same group E. On the other hand, the increase in the temperature of steaming process of 60°C with 80°C decreases the value of the twist of 12,9T/m. The temperature releases the elastic yarn and acts primarily on the level of stability by minimizing its twist.

Elongation at break is in remarkable growth when duration of relaxation Dr, linear density of the spandex Ls, and the duration of steaming process Ds, take the high levels in our experimental design. On the other hand, one can notice that elongation at break and the temperature of steaming process are inversely proportional. Therefore, a deficiency in temperature of steaming process increases the elastic yarn elongation.

While basing itself on the study of experimental designs and the PCA method presented by Figure 6, we can minimize the study on a fewer number of input and output parameters. The study with these two methods enabled the authors to target the most influential parameters on the most interesting physical properties. Figure 6 shows that the assembly in groups informs us about the degree of importance of one or more parameters and also of the nature of correlation between them: positive or negative. Each time the group of parameters approaches zero, for example group A, the whole of parameters is considered of low importance and can be repealed. As much the group approaches the ends (1 or -1), it is considered very significant, example: groups E, D and B. The PCA method shows that the two physical properties (RKM and twist) are gathered in the same group. Indeed, the variation of a physical property of this group informs us on the variation of the other. When Ls increases, the two properties increase, the contrary case, when Ls decreases, the two properties decrease.

The duration of Ds steaming process does not contribute enormously in the physical properties since this parameter forms a group in the centre. Indeed, the authors conclude that only Ts, Dr and Ls are significant and contribute enormously in the elastic yarn physical properties. The hairiness of yarn is related principally to only one parameter, which is the time of steaming process. If a yarn is intended for knitting then the temperature must be weak conversely in the case of weaving where it is to better increase Ts.

Figure 5 shows that the Ts is the most influential parameter on hairiness. To increase the temperature of steaming process intuitively amounts minimizing porosity and thereafter a use of the elastic yarn in weaving. In the opposite case, the elastic yarn will be intended in knitting. In the case of elastic yarn, the steaming process is in general recommended if the destination of the latter is weaving according to DuPont; the steaming process decreases hairiness and in the majority of case the results of a steaming process depends on time and the temperature.


The studied parameters are not all influential. Indeed, the present study enabled the authors to analyze the input parameters and their influence degrees subjectively by the means of the PCA method and objectively by experimental Tagauchi designs method. Both methods show that the linear density is the most influential parameter followed by the temperature of steaming process and the duration of relaxation.

The PCA method proved that the authirs can minimize the data basis of their study especially when two or several input/output parameters follow the same evolution, case of twist and the RKM. To manufacture elastic core spun yarn intended for weaving, it is necessariy to steam yarn at low temperatures, eg: 60°C. On the other hand, when the elastic yarn is that of a warp thread or screen and thus with high hairiness level, it is advised to steam at high temperature so that the yarn is with high hairiness level. As the elastic yarns are generally used in weaving as being a screen, then we ask for certain extensibility during insertion it is better to increase the temperature of steaming process Ts.

The PCA is a method of optimization of the experimental design and it makes it possible to consolidate the deductions approved by the statistical method, Tagauchi experimental designs.


  1. Balasubramanian N and Bhatnagar V K (1970): The Effect of Spinning Conditions on the Tensile Properties of Core-spun Yrans, J Text Inst 61(11), : 65-67, 148-157.

  2. Babaarslan and Osman (2001): Method of Producing a Polyester/Viscose Core-Spun Yarn Containing Spnadex Using a Modified Ring Spinning Frame, Text, Res J. 71(4): 367-371.

  3. Mahdi SAHNOUN (2002): Thesis, Caractérisation et modélisation de l'influence des paramètres de structure des étoffes sur l'évaluation mécanique et sensorielle de leur toucher: Lycra DuPont, 1999, Producing Core Spun Yarns Containing LYCRA®, Technical Bulletin L120, Nov: 1-3. Books

  4. Gilles Sado et Marie-Christine Sado, 2000, Les plans d'expériences de l'expérimentation à l'assurance qualité, Nouvelle édition, pp 83-87.

Note: For detailed version of this article please refer the print version of The Indian Textile Journal November 2007 issue.

B Jaouachi
Textile Research Unit of ISET Ksar Hellal,
Institut Supérieur des Etudes Technologiques de Ksar Hellal,
Rue El Hadj Ali Soua 5070 Ksar Hellal Tunisia.
Tel: (00 216) 22 92 18 04/ (00 216) 73 47 59 00.
E-mail: boubaker_jaouachi@ yahoo.fr.

M Sahnoun
Textile Research Unit of ISET Ksar Hellal,
Institut Supérieur des Etudes Technologiques de Ksar Hellal,
Rue El Hadj Ali Soua 5070 Ksar Hellal Tunisia.
Tel: (00 216) 22 92 18 04/ (00 216) 73 47 59 00.

published November , 2007
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