Effects of yarn, fabric and machine parameters on the dimensional

properties of weft knitted single jersey fabric

ABSTRACT
Weft Knit fabrics are famous for traditional wear due to their elastic and light structures with gentle
smoothness and low production cost with high productivity. But few of those fabrics, especially single
jersey create quality problems in dimensional change and deformation after the production process.
Spirality is a most severe problem for single jersey knitted fabrics due to their asymmetrical loop
formation. This work focuses on causes of spirality of the knitted fabrics as crucial aspects. The study
investigates the different parameters such as yarn count, yarn tension, tightness factor, stitch length,
fabric weight per unit area, machine speed, machine gauge, number of feeders and their effect on the
spirality of single jersey knitted fabrics. Hence, 100% Z-twisted, combed cotton yarns were used to knit
plain single jersey knitted fabric. All the fabrics were subjected to scouring, bleaching followed by
whitening by optical brightening agent then dried through the same condition. The results conclude
that the fabric spirality increases with increasing stitch length, number of feeders, yarn count, number
of twists per unit length in yarn. On the other hand, it was observed from the study that tightness factor
and machine gauge inversely affect spirality. However, machine speed and yarn tension do not affect
spirality.

Keywords: Spirality, single jersey, shrinkage, stitch length, tightness factor, knitting speed, yarn tension

1. Introduction
Knitted fabrics, especially ready-made knitted garments, T-shirts, underwear, and lingerie, are essential
basic items in the textile sector. The reasons for this usage can be explained in various ways: firstly, it
has an elastic and light structure; secondly, single jersey fabrics are easily and quickly produced; thirdly,
they have lighter weight and lower production cost, and finally, because of their smooth surface, they
are convenient for printing (Bueno & Camillieri, 2019). However, besides all the advantages, these
fabrics have quality problems like dimensional change and deformations.

Spirality is a dimensional distortion in circular, plain knitted fabrics. One of the sources of spirality is
twist stress in the constituent yams that causes loops to distort and throwing the fabric wales and courses
into an angular relationship other than 90 degrees as shown in fig 1(a) and (b). There are four significant
sources of spirality: fiber parameters, yarn parameters, knitting parameters, and finishing parameters.
Fiber parameters include fiber types, fiber fineness, fiber maturity, fiber quality, torsional rigidity,
flexural rigidity, fiber mix, and fiber length. Spinning type, fiber arrangement in yarn, twist level, twist
direction, linear yarn density, number of plies, yarn voluminosity, yarn conditioning, and yarn
mechanical characteristics are all yarn parameters. Knitting parameters include the number and type of
feed systems, direction of cylinder rotation, needle gauge, knitting structure types, tightness factor, loop
density, yarn input tension, and fabric takedown tension. Finishing parameters include wet processing,
drying and stentering, fabric calendaring, and other treatments such as enzyme, resin, mercerizing,
softener treatment. (Kalkanci, 2019).

a b

Fig 1. Wales and course position in knit fabric. (a). without spirality, (b). with spirality

Spirality has a definite influence on both the functional and aesthetic performance of knitted fabrics and
garments. Displacements of seams during the garment make-up, mismatched patterns due to wale
skewness, sewing difficulties are significant realistic difficulties due to spirality (Kalkanci, 2019). As
the dimensional properties of the fabrics are affected by spirality it is essential to accurately findout the
sources and minimize or eliminate it rather than solely leaving it to be corrected in finishing process by
imposing distortion to fabrics.

Spinning process involves application of constant torque to every twisted. The strands begin to snarl on
themselves as soon as they are removed from the twisting force. When yarn is liberated of its tensions,
it reacts inversely to rotation, called yarn liveliness. The snarling propensity rises as the twist coefficient
of the yarns increases, and the yarn becomes thicker. Rotor yarns has the lowest snarling tendency,
whereas compact yarns has the highest values positively relating the degree of spirality to the number
of twists per unit length in the yam. Şehit and Kadoğlu investigated the effect of the spinning system,
twist coefficient and yarn count on the yarn liveliness and observed their significant impacts on spirality.
(Şehit & Kadoǧlu, 2020). Chu & Choi et al. compared the performance of fabrics made from torque-
free ring-spun yarns and conventional ring-spun yarns with three cotton types. They found that the
torque-free ring spun yarns outperformed the conventional ones in spirality (Chu et al., 2021).
Similarly, Tao et al. developed a torque-balanced spun yarn and discovered that fabric produced from
this yarn showed a remarkable reduction of spirality (Lau & Tao, 1997). Unlike similarly constructed
yams produced from thermoplastic fibres, heat setting in yarn or fabric form to eliminate spirality
proved insufficient for cotton fabrics (Pavko-Čuden, 2015)..

2
Impact of production parameters on spirality have been studied by many researchers. Ceken and
Kayacan studied the influence of the direction of cylinder rotation and number of feeding system. They
concluded that feeder number has a positive relation and direction of rotation against twist direction in
the yarn has a negative relation with the magnitude of spirality.. (Ceken & Kayacan, 2007). According
to Kothari et al. lower stitch length, higher machine gauge and coarser count reduce the spirality
(Kothari et al., 2011). impact of machine gauge and tightness factor have also been studied by Banerjee
and Alaiban (Banerjee & Alaiban, 1988). Their study concluded that the knitted fabric with the finest
possible gauge at a fabric tightness factor value ≥14.0 reduces the spirality in the fabric. Tao and
Dinghra et al. opined out of other sources, yarn twist and tightness factors are the main factors
influencing spirality(Tao et al., 1997). whereas Singh and Roy et al. with their mathematical model
expressed that the stitch length is the most crucial factor determining fabric dimensional characteristics
(Singh et al., 2011).

Other than the machine parameters, inclusion of secondary strand in the knitting system and its impact
on spirality have also been studied by several researchers suggesting that, cotton/spandex knitted fabrics
if properly heat set shows less spirality(Marmarali, 2003) (Khalil et al., 2021). The result is also
acknowledged by Zaman & Weber et al. with a conclusion that the spirality starts to reduce with the
increasing rate of elastomeric yarn feeding (ZAMAN & WEBER, 2012).
Ceken et al. states that, wet processing and finishing in open width form rather that tubular form shows
higher spirality (Ceken, 2010). According to Banerjee and Alaiban (Banerjee & Alaiban, 1988), fabric
mercerization reduces loop asymmetry more than yarn mercerization and thereby influences resultant
spirality. Another study revealed that spirality decreases with the increasing gsm of fabric and the
completion of the dyeing process (Değirmenci & Topalbekiroğlu, 2010). Addition of crosslinking
agents in the finishing line contributes in setting and reducing the spirality of knitted fabric (Ahmed et
al., 2019).

As one of the most disturbing properties developed in knit fabrics, several researchers have
developed hypothesis, models and tools to explain and predict the amount of spirlaty. Araujo
and Smith created a hypothesis to describe the mechanics of knitted fabric spirality and the causes and
solutions (de Araujo & Smith, 1989). Celik and Ucar et al. developed an algorithm to calculate spirality
angle using image analysis, claiming that the suggested method achieved quick and accurate results
(Celik et al., 2005). Murrells and Tao et al. estimated the degree of spirality of completely relaxed single
jersey fabrics using an artificial neural network model. They discovered a pretty high agreement
between the predictions and actual measured values of fabric spirality with a correlation coefficient of
0.976 (Murrells et al., 2009). Besides these, other researchers used ANN, regression models,
mathematical formulation, genetic programming, and image analysis approaches to predict the fabric
spirality that may develop during manufacturing. (Shahid & Hossain, 2015)(Mezarcıöz, 2021)(Mavruz
Mezarciöz & Oǧulata, 2011)(ka Fai Choi & Tin Yee lo, 2006) (Chen et al., 2012).

3
 Although many parameters of spirality have been explored, no researcher has before investigated or not
reported the effect of yarn tension and cylinder rpm on spiraltiy, which is one of our work's distinctive
aspects. This research will benefit knitwear companies and designers with a compact spun yarn knitted
fabric and garments. The spirality angle of single cotton jersey fabrics and garments can be easily
predicted using the factors defined before starting production in a factory.

2. Materials and Methods

2.1. Preparation of knit fabrics
Thirty different types of plain knitted single jersey fabrics were produced in a Fukuhara circular knitting
machine having cylinder diameter 30 inches, 90 positive feed system, needle gauge 24 and automatic
fabric takedown system. Fabrics were produced in GMS composite knitting Industries Ltd, Kashimpur,
Gazipur. Detailed knitting strategy has been shown in table 1.

Table 1: Detailed strategy of knitting

Type of
Sample used for Varying parameters Test performed
samples
Effect of yarn count, 6 6 different count: 24, 26, 28, Shrinkage and
tightness factor 30, 34, 40 Ne spirality, cpi
Effect of the number of 5 Numer of feeds: 30, 45, 60, Spirality
feeders 75, 90
Effect of yarn twist 4 Twist per inch: 17, 18.5, 20, Spirality
21.5
Effect of needle gauge 4 Needle gauge 16, 20, 24, 28 Spirality

Effect of yarn tension 6 Yarn tension: 6.5, 7.5, 8, 8.5, Spirality

9 & 10 cN
Effect of knitting speed 6 Cylinder rotation speed: 20, Spirality
26, 30, 35, 40, 45

All the knitting yarns have been collected from Square Textiles Ltd, Kashimpur, Gazipur. The
quality parameters of yarns are listed in table 2.

Table 2: Yarn properties

Imperfection/1000 mSingle
Yarn
Unevenness CV yarn Elg.
Count Thin Thick Neps Hairiness
U% m% strength (%)
(Ne) (+50%/km) (+50%/km) (+200%/km) (RKM)
24 9.02 11.40 0 18 23 19 5.85 4.91
26 8.91 11.23 0 9 15 18.9 5.75 4.63
28 9.50 11.98 0 14.3 25 18.8 5.7 4.96
30 9.07 11.43 0 13.0 29 18.75 5.6 4.89
34 8.97 11.30 0 8.1 30 18.7 5.5 3.24
40 9.59 12.10 0 18.8 35.5 18.5 5.4 3.79

4
2.2. Wet processing of the samples
Wet processing of all the samples were carried out in the same bath, with combined scouring,
bleaching followed by whitening and enzyme wash (M:L 1:7). Chemicals and auxiliaries used
for the process were - detergent (1.0 gm/l), anti-creasing agent (2.0 gm/l), sequestering agent
(1.0 gm/l), anti-foaming agent (0.1 gm/l), stabilizer (0.4 gm/l), sodium hydroxide (3.0 gm/l),
hydrogen peroxide (8.0 gm/l) and max bright 4BK (0.3%). The batch was neutralized by hot
and cold wash before enzyme wash. Enzyme (Bio polish LC) (0.3%) was used for enzyme
wash, and acetic acid was used to bring the pH to required level. After successive cold wash,
the samples were dewaterd and dried at 180°C in industrial dryer.

3. Test methods
BS EN 14970 was used to measure stitch length, BS EN 14971 was used to measure course density and
wales density, and ASTM D3776 / D3776M-09a was used to quantify GSM. The yarn tension during
knitting was determined according to ASTM D 2256-02, ISO 2061:2010 for the number of twist
measurements, ISO 16322 for measuring the spirality of single jersey fabrics, and ISO 139 was followed
for fabric conditioning before test works. Several measurements were taken and recorded against each
type of samples and the average value of the recorded readings have been used for statistical analysis.

4. Results and Discussion

4.1. Effect of yarn count and tightness factor

Physical properties of the single jersey includes the courses density, wales density, tightness factor, loop
shape factor, areal density etc. stitch density has been calculated by multiplying courses and wales per
unit length. The dimensional constants (K values: Kc, Kw, and Ks) established by Doyle and Munden
(Munden, 1959) were used to calculate the physical parameters (shown in table 3) of the produced
samples.

Kc = course per cm × stitch length (cm)

Kw = course per cm × stitch length (cm)

Ks= Kc × Kw

√590.6/Ne
Tightness factor = Stitch length(cm)

𝐾𝑐
Loop shape factor = 𝐾𝑤

𝐾𝑠 ×590.6
Areal density =
Stitch length(cm)×Ne

5
 Table 3: Test results of the physical properties of the produced samples
Yarn Stitch Stitch Loop Areal
Sample Courses Wales Tightness
count length density Kc Kw Ks shape density Spirality
no per cm per cm factor
(Ne) cm per cm2 factor gm/m2
1 24 0.282 22.00 15.00 330.00 6.20 4.23 26.24 17.59 1.47 229.01 2.54
2 26 0.275 21.00 15.00 315.00 5.78 4.13 23.82 17.33 1.40 196.77 2.60
3 28 0.273 20.00 14.00 280.00 5.46 3.82 20.87 16.82 1.43 161.23 2.67
4 30 0.269 20.00 14.00 280.00 5.38 3.77 20.26 16.49 1.43 148.28 2.59
5 34 0.264 19.00 14.00 266.00 5.02 3.70 18.54 15.79 1.36 121.98 3.00
6 40 0.251 18.00 14.00 252.00 4.52 3.51 15.88 15.31 1.29 93.39 3.43

The shrinkage and spirality were determined at a fully relaxed state. Spirality and shrinkage were
recorded for different counts, which are presented in the following figure 2.

5 0
4.5 4 -0.5
4 -1
3.4
3.5 -1.5

Shrinkage, %
Spirality, %

2.67 2.8
3 2.5 2.6 -2
2.5 -2.5
-3.23 -3.27 -3.13
2 -3.41 -3
-2.85 -3.8
1.5 -3.2 -3.13 -3.12 -3.5
1 -4.29 -4
-3.88
0.5 -4.5
-4.71
0 -5
22 24 26 28 30 32 34 36 38 40 42
Yarn count, Ne

Spirality Length-wise shrinkage Width-wise shrinkage

Figure 2. Shrinkage and spirality for different yarn count

The shrinkage and spirality data were plotted against the yarn counts 24, 26, 28, 30, 34, and 40 in the
graph. The tightness factors for corresponding fabrics were 17.59, 17.33, 16.82, 16.49, 15.79, and 15.31.
therefore, the chart shows the results for both the yarn count and the tightness factor, where the yarn
count and tightness factor are inversely connected. The figure shows that fabric with higher count yarn
shows higher shrinkage and spirality, whereas fabric with lower count shows less shrinkage and
spirality. The fabric of 40 Ne shows length-wise – 4.29%, width-wise shrinkage – 4.71%, and 4%
spirality, whereas fabric of 24 Ne shows length-wise – 3.23%, width-wise shrinkage – 2.85%, and 2.5%
spirality. Spirality and shrinkage increase with the increase of yarn fineness, and yarn tends to twist
back more after fabric relaxation.

6
Results of the Pearson correlation indicated that there was a significant positive relationship between
spirality and count, r(58) = .506, p<.001; a significant negative associattion between spirality and width-
wise shrinkage, r(58) = -.188, p =.150; a significant negative associattion between spirality and length-
wise shrinkage, r(58) = -.319, p = .013; a significant negative associattion between count and length-
wise shrinkage, r(58) = -.456, p<.001; ; a significant negative associattion between count and width-
wise shrinkage, r(58) = -.471, p<.001; a significant positive association between length-wise and width-
wise shrinkage, r(58) = .0328, p =.011.

4.2. Effect of number of feeders

30 Ne yarn was used to determine the impact of the number of feeders on spirality, and the fabric was
knitted with the knitting machine of 24 gauges. On this occasion, the number of yarn feeding units was
gradually raised. Five samples were prepared using 30, 45, 60, 75, and 90 feeding units in the same
machine keeping other parameters constant. It was found that, the number of feeders positively
influenced the spirality of knitted fabrics. The scatter chart with the error bar has been demonstrated in
figure 3.

y = 0.0347x + 1.3884
5 R² = 0.8888

4
Spirality, %

0
20 30 40 50 60 70 80 90 100
Number of feeders

Figure 3. Spirality for different number of feeders

A simple regression was used to predict the spirality percentage from the different number of feeders.
The number of feeders explained significant variance in the spirality, F (1,23) = 183.83, p<.001, R2=.88,
R2adjusted =.88. The regression coefficient, B=25.63, indicated that an increase in the number of feeders
correspond, on average, to the rise in spirality of 25.63 points.

7
The result is in alignment with the theoretical explanation of the construction of single jersey
knit fabric. By nature, the courses in a knit fabric, as illustrated in fig 4 follow a spiral path
when it is produced. Thereby an angle (α) is produced between actual course line and the
horizontal line when wale line is kept vertical. With the increase of feeder density, the value of
α increases gradually. For producing garments, it is essential to align the course line to
horizontal line and the wale line to vertical line, in other words, the value of α needs to be 00.
If the value of α is not permanently set to 00 through appropriate finishing process, the spirality
may reappear after subsequent washing and relaxation of the garments.

a b

Fig 4. Spiral path of courses during knitting. (a). needle action, (b). fabric view

4.3. Effect of twist per unit length in yarn

30 Ne yarns with four different twist levels: 17 TPI, 18.5 TPI, 20 TPI, and 21.5 TPI were used to
investigate the influence of twist amount on spiriality. It should be mentioned that the twist amount for
30 Ne combed yarn ranges from 17 to 21 twists per inch. The scatter chart showing the relation between
twist levels and spirality with the error bar has been demonstrated in figure 5.

5 y = 0.5032x - 6.3696
R² = 0.8904

4
Spirality, %

0
16 17 18 19 20 21 22
Twist per inch

Figure 5. Relation between twist amount in yarn and spirality

8
The higher twisted yarn has a more untwisting tendency in fabric than that of lower twisted yarn. When
the fabric undergoes wet processing and finishing process, the twist liveliness reappears. As a result of
this untwisting, the fabric with more TPI yarn showed more spirality.

A simple regression was used to predict the spirality percentage from the different twist levels of the
yarn. Twists per inch explained a significant amount of the variance in the spirality, F (1,18) = 146.28,
p<.001, R2= .89, R2adjusted =.88. The regression coefficient, B= -6.4, indicated an increase in the number
of twists per inch, on average, to a decrease in spirality of 6.4 points.

4.4. Effect of machine gauge

Four cylinders with the same diameter (30 inches) but different needle gauges (needles per inch, NPI)
were used to find the relation with the spirality. The selective NPI were 16, 20, 24, and 28. The number
of needles in the four cylinders varied, as the finer gauge cylinder can contain more needles than the
coarser gauge cylinder. In that order, the cylinders' actual needle numbers were 1500, 1880, 2260, and
2630 needles. The number of wales is equivalent to the number of needles. As a result, fabrics having
more wales with the same tubular diameter displayed reduced spirality. NPI-24 as shown in fig 6
showed the least spirality of the four gauges, and it's commonly known that NPI-24 or G24 is widely
employed in the knitting sector.

5
4.5
y = -0.466x + 4.375
4 4
3.5 3.5
Spirality, %

3
2.75
2.5 2.59

2
1.5
1
0.5
0
16 20 24 28
Needle gauge

Figure 6: Effect of machine gauge on spirality

A simple regression was used to predict the spirality percentage from the different NPI of the cylinder.
NPI explained significant variance in the spirality, F (1,18) = 91.62, p<.001, R2= .84, R2adjusted =.83. The
regression coefficient, B= -.12, indicated that an increase in the needle gauge corresponds, on average,
to a decrease in spirality of 0.12 points.

9
4.5. Effect of yarn tension on spirality
The tension of the yarn while knitting is a significant factor in determining the quality of fabric. The
yarn tensions were altered in this case to determine the relationship with spirality. The tensions were
6.5, 7.5, 8, 8.5, 9, and 10 cN, respectively. The position determining screws were adjusted to modify
the position of the needle bed, i.e., the cylinder. The yarn tension increases when the cylinder is slightly
lowered.

6
y = 0.2857x + 2.0667
5

4
Spirality, %

4.5
2 4
3.4
3
1 2
1.5

0
6.5 7.5 8 8.5 9 10
Yarn tension, cN

Figure 7. Spirality against different yarn tension

The optimal knitting tension in dimensional quality was 7.5 to 8 cN, which caused less spirality. A
simple regression was used to predict the spirality percentage from the different knitting tensions. Yarn
tensions as shown in fig 7 did not show any significant relations with the variance in the spirality, F
(1,4) = .76, p=.98, R2= .16, R2adjusted =-.05 andhe regression coefficient, B=.38.

4.6. Effect of knitting speed

Up to a certain level, cylinder speed is related to optimized knitting production above which it creates
excessive tension on the yarn causing increased rate of yarn breakage. Spirality was measured after a
particular amount of fabric was produced at six different cylinder speeds. The cylinder was rotated
clockwise in this case. The relation between machine speed or cylinder rpm during knitting and spirality
has been shown in fig 8.

10
 6
y = 0.4643x + 1.4167
5 5

4 4

Spirality, % 3 3
2.5
2 2
1.75

0
20 26 30 35 40 45
Cylinder rpm

Figure 8: Changes of spirality for different machine speed

A simple regression was used to predict the spirality percentage from the cylinder rpm variations.
Cylinder speed did not show any significant relations with the variance in the spirality, F (1,4) =3.52,
p=.99, R2= .47, R2adjusted =.33. and the regression coefficient, B=.09.

Conclusions
This study was aimed to identify and analyze the impact and extent of the factors coming from yarn
properties and production parameters on spirality to forecast the individual parameters on spirality.
Spirality increases with TPI increases with yarn counts and yarn tends to twist back more after fabric
relaxation. No significant relation has been found between yarn tension and spirality. Machine speed
should not be so high that it might cause frequent yarn breakage and high spirality of the fabric.

References

Ahmed, T., Irshad, F., Farooq, A., Ashraf, M. A., & Mahmood, N. (2019). Effect of cross linker
treatment on dimensional and mechanical properties of knitted fabrics. Pakistan Journal of
Scientific and Industrial Research Series A: Physical Sciences, 62(1), 48–51.
https://doi.org/10.52763/PJSIR.PHYS.SCI.62.1.2019.48.51

Banerjee, P. ., & Alaiban, T. . (1988). Geometry and Dimensioanl Properties of Plain Loops Made of
Rotor Spun Cotton Yarns. Textile Research Journal, 58(5), 287–290.
https://doi.org/10.1177/004051758805800507

Bueno, M. A., & Camillieri, B. (2019). Structure and mechanics of knitted fabrics. In Structure and
Mechanics of Textile Fibre Assemblies (2nd ed.). Elsevier Ltd. https://doi.org/10.1016/B978-0-
08-102619-9.00003-1

11
Ceken, F. (2010). The effect of wale spirality of single jersey circular knit fabrics on seam distortions.
Tekstil, 59(5), 186–192.

Ceken, F., & Kayacan, O. (2007). The effects of some machine parameters on the spirality in single
jersey fabrics. Fibers and Polymers, 8(1), 89–97. https://doi.org/10.1007/BF02908165

Celik, O., Ucar, N., & Ertugrul, S. (2005). Determination of spirality in knitted fabrics by image
analyses. Fibres and Textiles in Eastern Europe, 13(3), 47–49.

Chen, Z. H., xu, B. G., Chi, Z. ru, & Feng, D. G. (2012). Mathematical formulation of knitted fabric
spirality using genetic programming. Textile Research Journal, 82(7), 667–676.
https://doi.org/10.1177/0040517511435011

Chu, P. yee, Choi, K. fai, Chuang, Y. chun, & Kan, C. wai. (2021). Comparison of Performance of
Fabrics made of Torque-free and Conventional Ring Spun Yarn with Different Varieties of
Cotton Fibres. Fibers and Polymers, 22(7), 2036–2043. https://doi.org/10.1007/s12221-021-
1024-8

de Araujo, M. D., & Smith, G. W. (1989). Spirality of Knitted Fabrics: Part I: The Nature of Spirality.
Textile Research Journal, 59(5), 247–256. https://doi.org/10.1177/004051758905900501

Değirmenci, Z., & Topalbekiroğlu, M. (2010). Effects of weight, dyeing and the twist direction on the
spirality of single jersey fabrics. Fibres & Textiles in Eastern Europe, 18(3), 81–85.

ka Fai Choi, & Tin Yee lo. (2006). The Shape and Dimensions of Plain Knitted Fabric: A Fabric
Mechanical Model. Textile Research Journal, 76(10), 777–786.
https://doi.org/10.1177/0040517507069030

Kalkanci, M. (2019). Investigation into fabric spirality in various knitted fabrics and its effect on
efficiency in apparel manufacturing. Fibres and Textiles in Eastern Europe, 27(1), 59–66.
https://doi.org/10.5604/01.3001.0012.7509

Khalil, A., Těšinová, P., & Aboalasaad, A. R. R. (2021). Thermal comfort properties of
cotton/spandex single jersey knitted fabric. Industria Textila, 72(3), 244–249.
https://doi.org/10.35530/IT.072.03.1760

Kothari, V. K., Singh, G., Roy, K., & Varshney, R. (2011). Spirality of cotton plain knitted fabrics
with respect to variation in yarn and machine parameters. Indian Journal of Fibre and Textile
Research, 36(3), 227–233.

Lau, Y. M., & Tao, X. M. (1997). Torque-Balanced Singles Knitting Yarns Spun by Unconventional
Systems Part II: Cotton Friction Spun DREF III Yarn. Textile Research Journal, 67(11), 815–
828. https://doi.org/10.1177/004051759706701106

12
Marmarali, A. B. (2003). Dimensional and Physical Properties of Cotton/Spandex Single Jersey
Fabrics. Textile Research Journal, 73(1), 11–14. https://doi.org/10.1177/004051750307300102

Mavruz Mezarciöz, S., & Oǧulata, R. T. (2011). The use of the taguchi design of experiment method
in optimizing spirality angle of single jersey fabrics. Tekstil ve Konfeksiyon, 21(4), 374–380.

Mezarcıöz, S. (2021). Statistical Modeling of Spirality and Thickness Values in Plain Knitted Fabrics.
Journal of Natural Fibers, 00(00), 1–12. https://doi.org/10.1080/15440478.2021.1915912

Munden, D. L. (1959). 26—The geometry and dimensional properties of plain-knit fabrics. Journal of
the Textile Institute Transactions, 50(7), T448–T471.
https://doi.org/10.1080/19447025908659923

Murrells, C. M., Tao, X. M., Bin Gang xu, & Cheng, K. po S. (2009). An Artificial Neural Network
Model for the Prediction of Spirality of Fully Relaxed Single Jersey Fabrics. Textile Research
Journal, 79(3), 227–234. https://doi.org/10.1177/0040517508094091

Pavko-Čuden, A. (2015). Skewness and Spirality of Knitted Structures. Tekstilec, 58(2), 108–120.
https://doi.org/10.14502/tekstilec2015.58.108-120

Primentas, A., & Iype, C. (2003). Spirality of weft knitted fabrics: Part III - An innovative method for
the reduction of the effect. Indian Journal of Fibre and Textile Research, 28(2), 202–208.

Şehit, H., & Kadoǧlu, H. (2020). A study on the parameters effecting yarn snarling tendency. Tekstil
ve Konfeksiyon, 30(1), 42–49. https://doi.org/10.32710/tekstilvekonfeksiyon.587866

Shahid, M., & Hossain, M. (2015). Modeling the Spirality of Cotton Knit Fabric Using Fuzzy Expert
System. Turkish Journal of Fuzzy Systems (TJFS), 6(2), 56–67.

Singh, G., Roy, K., Varshney, R., & Goyal, A. (2011). Dimensional parameters of single jersey cotton
knitted fabrics. Indian Journal of Fibre and Textile Research, 36(2), 111–116.

Tao, J., Dhingra, R. C., Chan, C. K., & Abbas, M. S. (1997). Effects of Yarn and Fabric Construction
on Spirality of Cotton Single Jersey Fabrics. Textile Research Journal, 67(1), 57–68.
https://doi.org/10.1177/004051759706700112

ZAMAN, M., & WEBER, M. (2012). Efect of feeding speeds of elastomeric yarn with 100% cotton
yarn on knit fabric spirality. Proceedings of 46th Interantional Congress IFKT, Sinaia, 903–909.

13