Determining the loop length during knitting and dyeing processes

Abstract

Loop length is one of the most relevant variables to control while producing knitted fabrics because the final characteristics of the finished fabric depend on it to a great extent. The procedure followed to calculate it is based on standard UNE-EN 14970, and it is cumbersome, time-consuming and requires yarn-measuring equipment. This study investigated several single jersey and 1 × 1 rib structures produced with different yarn counts and 100% cotton yarns, and a 1 × 1 rib structure that was half-plated in alternating courses by defining four relaxation states of the different fabrics: two knits (knitting and dry relaxation and knitting and wet relaxation) and two dyed (dyed and dry relaxation and dyed and wet relaxation). The most significant dimensional variables were characterized in all the relaxation states and models were presented that explain the variability of the yarn length absorbed by the loop using other variables that are much simpler to analyze.

Keywords

knitting process dyeing process dry relaxation wet relaxation loop length single jersey 1 × 1 rib

Manufactured knitted fabrics are popular given their excellent adaption capacity, hence this technology is used to manufacture underwear and sportswear. Weft-knitted fabrics also present a high degree of dimensional instability, which makes working with this fabric type throughout the manufacturing process complicated. To ensure dimensional stability throughout the lifetime of such garments, it is necessary to control the dimensional parameters during the entire production process and to confer the final garment with a minimum energy state to thus make it dimensionally stable.

Obtaining stable knitted fabrics is a purpose that has long since been a matter of concern. In 1926, Chamberlain¹ presented the first mathematical model to determine the knitted fabric loop configuration. Since then, other research works have undertaken relevant studies which conceptualise, define and mathematically formulate the dimensional behaviour of knitted fabrics.^2–18

For years, Münden's equations^19–21 have been applied to calculate the K factors that determine fabric dimension and loop rules. Doyle²² discovered that knit density depended on loop length (SL). Nutting and Leaf²³ introduced another variable into Münden's equations, namely yarn count. Knapton et al.^24,25 demonstrated that dimensional stability in plain-knitted fabrics can be achieved by mechanical means, relaxation techniques or chemical treatments. Fletcher and Roberts^26–31 studied the geometry, relationship and dimensional stability of knits fabrics. The Starfish project^32–37 is a long-term program of applied research whose basic aim is to create a comprehensive and systematic database describing the dimensional properties of finished cotton knits, and hence to derive a simple, rational and reliable system for predicting finished dimensions starting from the knitting and finishing specifications. The study by Ulson et al.³⁸ was based on determining the own K factors of each production process, based on differences between the K factors obtained in fabrics treated during a continuous bleaching process or an exhaustion bleaching process. Saravana and Sampath³⁹ predicted the dimensional properties of a double cardigan-type fabric using an “artificial neural network system.” Mobarock⁴⁰ proposed some mathematical ratios to predict the weight (GSM), width and final shrinkage of a finished cotton knitted fabric. Eltahan et al.⁴¹ and Eltahan⁴² determined the SL, tightness factor and porosity of a single jersey knitted fabric using mathematical equations. Sitotaw⁴³ and Sitotaw and Adamu⁴⁴ studied the dimensional characteristics of five knitted fabric structures made with 100% cotton and 95% cotton/5% elastane (EA). They concluded that the presence of EA significantly varied the outcome of the dimensional variables. Llinares et al.⁴⁵ proposed a procedure to calculate the SL of interlock fabrics by means of linear regression models to avoid applying standard UNE-EN 14970.

Objectives

This study is of great relevance for the technical textile industries, since it greatly simplifies the productive calculations for weft-knitted fabric companies. It offers an effective method for the estimation of the SL in the knitted fabrics in single jersey and 1 × 1 rib structures, after the knitting, dyeing and finishing processes. From the knowledge of the variables it is much easier to calculate, such as measurements as the wales per centimeter (WPCM) and courses per centimeter (CPCM) in the fabrics obtained in the knitting machines, without the need to perform a subsequent analysis based on the standard UNE-EN 14970.

In this way the quality control of the knitted fabrics is streamlined, being able to adjust the desired final characteristics of them more quickly contributes to the improvement of the increase in the quality of the final product.

The procedure employed by Llinares et al.⁴⁵ to calculate the SL of interlock fabrics can be applied to 1 × 1 rib and single jersey structures in cotton fabrics.

Experimental details

Materials and methods

The present study was carried out on knitted fabrics with a 1 × 1 rib and single jersey structure. The circular machines employed to produce these fabrics are described in Table 1. This study was conducted with 440 lots. Each lot included 20 pieces of fabric, each weighing 20 kg. In all the lots, one piece was identified so as to not lose its traceability and to analyze it throughout the production process. This meant that 200 pieces with a 1 × 1 rib structure and 240 pieces with a single jersey structure were studied.

Table 1.

The circular machines used to produce the knitted fabrics with 1 × 1 rib 100% cotton, 1 × 1 rib plated with elastane and 100% plain-knitted cotton structures

Structure	Model	Diameter (inches)	Gauge	Needles	No. feeders
1 × 1 Rib 100% CO	Mayer FV 2.0	14	E16	2 × 708	29
	Jumberca DVI	16	E16	2 × 804	32
	Jumberca DVI	18	E16	2 × 900	36
	Mayer FV 2.0	20	E16	2 × 1008	40
1 × 1 Rib 95% CO 5% elastane/plated	Mayer FV 2.0	16	E18	2 × 804	32
1 × 1 Rib 95% CO 5% elastane/plated	Mayer FV 2.0	18	E18	2 × 1008	36
Single jersey	Mayer MV4 II	17	E22	1176	54
	Mayer MV4 3,2	18	E22	1248	57
	Mayer MV4 II	22	E22	1512	69
	Mayer MV4 II	24	E22	1656	78

In the 1 × 1 rib structure, two different fabric types were obtained: a cotton fabric with a yarn count of 26.96 Ne and another cotton fabric with a yarn count of 30.26 Ne. From each fabric, 20 pieces were produced with the diameter of each machine as shown in Table 1 (14”, 16”, 18” and 20”), which gave 80 pieces with a yarn count of 26.96 Ne and 80 more with a yarn count of 30.26 Ne.

With the 1 × 1 rib structure, whose composition is 95% cotton-5% EA, plated cotton with a yarn count of 50.24 Ne with elastomer with a yarn count of 22 dtex half-plated in alternating courses were obtained. This gave 20 pieces of each selected machine diameter (16” and 18”) and 40 pieces were obtained.

For the single jersey structure, fabrics were produced with yarn counts of 26.96, 30.26 and 37.39 Ne using the machine diameters (17”, 18”, 22” and 24”), as indicated in Table 1. In all, 80 pieces were obtained from each employed yarn with yarn counts of 26.96, 30.26 and 37.39 Ne (corresponding to 20 pieces of diameter 17”, 20 of diameter 18”, 20 of diameter 22” and 20 of diameter 24”).

Two fabric relaxation states were distinguished after the knitting process ended.

Knitting and dry relaxation (KDR). Once the fabric had been produced, it was left in a conditioning atmosphere until a constant weight was obtained.

Knitting and wet relaxation (KWR). The conditioned fabric was left until a constant weight was obtained and was submitted to a dimensional stability analysis according to standard UNE EN ISO 6330, of September 2012,⁴⁶ procedure 9N.

It is necessary to bear in mind that during the KWR relaxation process, no scouring fabric is obtained because this process does not remove peptine from cotton and, therefore, fibers continue to perform hydrophobically. However, this process manages to eliminate the stresses that accumulate during the knitting process and provides a dimensionally stable fabric, but the results of the dimensional variables having nothing to do with those corresponding to a scouring and bleaching process. This relaxation state can be used as an intermediate state between the KDR state and that obtained after the scouring process, and it helps to predict the dimensional properties of the finished fabric.

The pieces identified in each lot were placed in a conditioning atmosphere until a constant weight was obtained. Then two samples of each piece were cut to analyze them in relaxation states KDR and KWR. This analysis consisted of establishing the number of loops per length unit and area unit (WPCM, CPCM and stitch density) in line with standard UNE-EN 14971⁴⁷ to determine the laminar weight according to standard UNE-EN 14970⁴⁸ and the factors (K_c, K_w and K_r) by applying Münden's equations.

The lots are bleached by the exhaustion process. The dyeing conditions and the added products are respectively indicated in Figure 1 and Table 2.

Figure 1.

Process diagram of scouring and bleaching fabrics.

Table 2.

Products employed for scouring and bleaching process

Process	Product
A	Tannex Noveco
B	Procuest ND
C	Liquid Soda Lye
D	Hydrogen Peroxide
E	Ledeblanc
F	Dianix violet BTE
G	Formic acid

After completing hydroextraction and then drying the lots, the pieces to be analyzed were identified, a sample of them was taken and they were left in a conditioning atmosphere.

Two relaxation states were distinguished after the dyeing process.

Dyed and dry relaxation (DDR). The dyed knitted fabric was left in a conditioning atmosphere until a constant weight was obtained.

Dyed and wet relaxation (DWR). The dyed and conditioned knitted fabric was left until a constant weight was obtained. Then a dimensional stability test was run with it according to regulation UNE EN ISO 6330, of September 2012,⁴⁶ procedure 4N.

The relaxation states distinguished in the knitting and dyeing processes are represented in Figure 2.

Figure 2.

Relaxation states in the knitting and dyeing processes. KDR: knitting and dry relaxation; KWR: knitting and wet relaxation; DDR: dyed and dry relaxation; DWR: dyed and wet relaxation.

Results and discussion

Variables of interest are represented by a boxplot. A boxplot is a graphical rendition of statistical data based on the minimum, first quartile, median, third quartile and maximum. The term “boxplot” comes from the fact that the graph looks like a rectangle with lines extending from the top and bottom.

Figures 3–6 show the corresponding results of the variables WPCM, CPCM, stitch density/cm² (SD) and SL from analyzing the 1 × 1 rib pieces with yarn counts 26.96 and 30.26 Ne of 100% cotton and 50.24 Ne 100% of cotton with EA and 22 dtex (half-plated in alternating courses), in relaxations states KDR, KWR, DDR and DWR.

Figure 3.

Number of courses per centimeter (CPCM) for 1 × 1 rib fabrics. EA: elastane; KDR: knitting and dry relaxation; KWR: knitting and wet relaxation; DDR: dyed and dry relaxation; DWR: dyed and wet relaxation.

Figure 4.

Number of wales per centimeter (WPCM) for 1 × 1 rib fabrics. EA: elastane; KDR: knitting and dry relaxation; KWR: knitting and wet relaxation; DDR: dyed and dry relaxation; DWR: dyed and wet relaxation.

Figure 5.

Stitch density/cm² (SD) for 1 × 1 rib fabrics. EA: elastane; KDR: knitting and dry relaxation; KWR: knitting and wet relaxation; DDR: dyed and dry relaxation; DWR: dyed and wet relaxation.

Figure 6.

Loop length (SL) for 1 × 1 rib fabrics. EA: elastane; KDR: knitting and dry relaxation; KWR: knitting and wet relaxation; DDR: dyed and dry relaxation; DWR: dyed and wet relaxation.

Figures 7–10 show the corresponding results of the variables WPCM, CPCM, SD and SL in the analysis done with the single jersey pieces with yarn counts of 26.96, 30.26 and 37.39 Ne of 100% cotton in relaxation states KDR, KWR, DDR and DWR.

Figure 7.

Number of courses per centimeter (CPCM) for single jersey fabrics. KDR: knitting and dry relaxation; KWR: knitting and wet relaxation; DDR: dyed and dry relaxation; DWR: dyed and wet relaxation.

Figure 8.

Number of wales per centimeter (WPCM) for single jersey fabrics. KDR: knitting and dry relaxation; KWR: knitting and wet relaxation; DDR: dyed and dry relaxation; DWR: dyed and wet relaxation.

Figure 9.

Stitch density/cm² (SD) for single jersey fabrics. KDR: knitting and dry relaxation; KWR: knitting and wet relaxation; DDR: dyed and dry relaxation; DWR: dyed and wet relaxation.

Figure 10.

Loop length (SL) for single jersey fabrics. KDR: knitting and dry relaxation; KWR: knitting and wet relaxation; DDR: dyed and dry relaxation; DWR: dyed and wet relaxation.

Having analyzed the fabrics in relaxation states KDR, KWR, DDR and DWR, the intention was to observe the relation linking the variables to obtain models that predict the SL of all the aforementioned relaxation states.

The models obtained by linear regression to predict the SL of the analyzed 1 × 1 rib fabrics in relaxation states KDR and KWR are found in Table 3.

Table 3.

Valid models proposed by linear regression for all the studied 1 × 1 rib fabrics in relaxation states knitting and dry relaxation (KDR) and knitting and wet relaxation (KWR)

Sample	DV	IV	Relaxation states
			KDR		KWR
			Linear relation	R ²	Linear relation	R ²
1 × 1 rib	SL	CPCM	$SL = \frac{1}{0.182041 \cdot CPCM}$	97.80	$SL = \frac{1}{0.1470478 \cdot CPCM}$	99.68
	SL	WPCM	$SL = \frac{1}{0.215316 \cdot WPCM}$	99.42	$SL = \frac{1}{0.170679 \cdot WPCM}$	98.49
	SL	SD	$SL = \frac{1}{0.00105471 \cdot SD}$	95.72	$SL = \frac{1}{0.00664432 \cdot SD}$	96.70

DV: dependent variable; IV: independent variable; WPCM: wales per centimeter; CPCM: courses per centimeter; SD: stitch density/cm²; SL: loop length (cm).

The models obtained by linear regression that predict the SL of the studied single jersey fabrics in relaxation states KDR and KWR are shown in Table 4.

Table 4.

Valid models proposed by linear regression for all the studied single jersey fabrics in relaxation states knitting and dry relaxation (KDR) and knitting and wet relaxation (KWR)

Sample	DV	IV	Relaxation states
			KDR		KWR
			Linear relation	R ²	Linear relation	R ²
Single jersey	SL	CPCM	$SL = \frac{1}{0.336763 \cdot CPCM}$	99.73	$SL = \frac{1}{0.2378748 \cdot CPCM}$	99.91
	SL	WPCM	$SL = \frac{1}{0.1676147 \cdot WPCM}$	99.76	$SL = \frac{1}{0.1640665 \cdot WPCM}$	99.96
	SL	SD	$SL = \frac{1}{0.01453059 \cdot SD}$	99.84	$SL = \frac{1}{0.01010196 \cdot SD}$	99.85

DV: dependent variable; IV: independent variable; WPCM: wales per centimeter; CPCM: courses per centimeter; SD: stitch density/cm²; SL: loop length (cm).

The models obtained by linear regression to predict the SL of the 1 × 1 rib fabrics in relaxation states DDR and DWR are provided in Table 5.

Table 5.

Valid models proposed by linear regression for all the studied 1 × 1 rib in relaxations states dyed and dry relaxation (DDR) and dyed and wet relaxation (DWR)

Sample	DV	IV	Relaxation states
			DDR		DWR
			Linear relation	R ²	Linear relation	R ²
1 × 1 rib	SL	CPCM	$SL = \frac{1}{0.145206 \cdot CPCM}$	98.00	$SL = \frac{1}{0.145762 \cdot CPCM}$	99.03
	SL	WPCM	$SL = \frac{1}{0.209909 \cdot WPCM}$	99.50	$SL = \frac{1}{0.196380 \cdot WPCM}$	99.53
	SL	SD	$SL = \frac{1}{0.0079753 \cdot SD}$	96.40	$SL = \frac{1}{0.00753594 \cdot SD}$	97.26

DV: dependent variable; IV: independent variable; WPCM: wales per centimeter; CPCM: courses per centimeter; SD: stitch density/cm²; SL: loop length (cm).

The models obtained by linear regression that predict the SL of the studied single jersey fabrics in relaxation states DDR and DWR are presented in Table 6.

Table 6.

Valid models proposed by linear regression for all the studied single jersey fabrics in relaxation states dyed and dry relaxation (DDR) and dyed and wet relaxation (DWR)

Sample	DV	IV	Relaxation states
			DDR		DWR
			Linear relation	R ²	Linear relation	R ²
Single jersey	SL	CPCM	$SL = \frac{1}{0.2312112 \cdot CPCM}$	99.87	$SL = \frac{1}{0.2348527 \cdot CPCM}$	99.94
	SL	WPCM	$SL = \frac{1}{0.1994994 \cdot WPCM}$	99.89	$SL = \frac{1}{0.1844150 \cdot WPCM}$	99.90
	SL	SD	$SL = \frac{1}{0.001183330 \cdot SD}$	99.82	$SL = \frac{1}{0.01103993 \cdot SD}$	99.87

DV: dependent variable; IV: independent variable; WPCM: wales per centimeter; CPCM: courses per centimeter; SD: stitch density/cm²; SL: loop length (cm).

Figures 11–13 illustrate the linear regression models adjusted for the single jersey fabrics in relaxation state DWR.

Figure 11.

Linear regression model for single jersey fabrics (relation between courses per centimeter and loop length in the dyed and wet relaxation state).

Figure 12.

Linear regression model for single jersey fabrics (relation between wales per centimeter and loop length in the dyed and wet relaxation state).

Figure 13.

Linear regression model for single jersey fabrics (relation between stitch density/cm² and loop length in the dyed and wet relaxation state).

For relaxation states KDR and KWR, it was possible to predict the SL variable by the models proposed for the analyzed 1 × 1 rib fabrics (Table 2) and single jersey fabrics (Table 3). The same can be stated for the models proposed in Tables 4 and 5 for the 1 × 1 rib and single jersey fabrics in relaxation states DDR and DWR, respectively. To this end, it was necessary to know some independent variables, such as the CPCM, WPCM and SD. These variables can be obtained quite quickly by applying standard UNE-EN 14971⁴⁷ and by simply using a thread counter. Nevertheless, in order to calculate SL according to standard UNE-EN 14970,⁴⁸ an apparatus that measures yarn length, and that must be used in a laboratory, is necessary. By using the models herein presented it is possible to avoid the whole process set out in the standard, which speeds up the process followed to obtain the SL.

All the proposed models had an R² that exceeds 95%, which accounted for optimum variability from the existing linearity with the independent variables CPCM, WPCM and SD.

The proposed models underwent a cross-validation process, which consisted of validating the models for a test data set, which comprised a collection of lots of each fabric and machine diameter. This analysis included calculating the SL of each lot in relaxation states KDR, KWR, DDR and DWR. In parallel, the values estimated by the proposed models were calculated. The estimated error was the difference between the estimated value and the actual value.

The errors estimated with the models proposed to estimate the SL in relaxation states KDR and KWR for the 1 × 1 rib fabrics (Table 2) fell within the 0.015–0.075 cm range. Applying the models that use the independent variables WPCM in relaxation state KDR (with a maximum estimated error of 0.015 cm) and CPCM in relaxation state KWR (with a maximum estimated error of 0.007 cm) is recommended because it is more accurate. In the single jersey fabrics (Table 3), the minimum estimated error was 0.004 cm, and the maximum estimated error was 0.011 cm. Given its better accuracy, using the models that estimate the SL from the independent variable WPCM is recommended.

The errors estimated with the models proposed to make estimations in relaxation states DDR and DWR for the 1 × 1 rib knitted fabrics (Table 4) fell within a minimum value of 0.010 cm and a maximum of 0.041 cm. Using the models that predict the SL with the variables WPCM or CPCM is recommended, regardless of being in relaxation state DDR, and for state DWR, which uses the variable WPCM. The models proposed for the single jersey fabrics (Table 5) in relaxation states DDR and DWR gave errors that ranged between 0.005 and 0.009 cm, and the most accurate models were those that used the independent variables WPCM and CPCM.

Conclusions

This study investigated the dimensional properties of two groups of fabrics: one formed by three single jersey fabrics and another by three 1 × 1 rib fabrics. Linear regression models are proposed to predict SL in relaxation states KDR, KWR, DDR and DWR for the following fabrics.

1 × 1 rib fabrics: two fabrics made with yarn lengths 26.96 and 30.26 Ne 100% cotton and a third one made with yarn length 50.24 Ne half-plated cotton in alternating courses, 22 dtex EA (Tables 2 and 4).

Single jersey fabrics made with yarn lengths 26.96, 30.26 and 37.39 Ne in 100% cotton (Tables 3 and 5).

When validating the models, the estimated errors made when using them for each structure were very small. So, it can be concluded that these models account for the variability obtained in all the proposed models.

What this demonstrates is that the proposed models can be suitably used to calculate the SL of the analyzed structures based on knowledge about some dimensional variables, for example, WPCM, CPCM and stitch density, in any relaxation state: KDR, KWR, DDR or DWR. This avoids having to follow the conventional procedure used to analyze them in line with standard UNE-EN 14970, and avoids operations to identify wales, the direction that samples unweave in, cutting a long a column, counting the number of loops along a given length, removing yarn from knitted fabric, placing the measuring machine pincers by foreseeing loss of twist to measure its length and repeating this whole process 10 times to then calculate its mean. By running this procedure, and depending on the structure to be analyzed, it may be necessary to invest a considerable amount of time. The proposed models speed up this process.

At the same time, the present work demonstrates that the same procedure followed to predict the SL in interlock fabrics (2020) is valid to calculate the SL of the 1 × 1 rib and single jersey structures in any of the proposed relaxation states: KDR, KWR, DDR and DWR. To do so, the specific models for all three single jersey, 1 × 1 rib and interlock structures can be used.

This study propose to the reader an alternative procedure to find the value of the variable SL without the need to apply the standard UNE-EN 14970, in order to speed up the adjustment of the machines as much as possible for obtaining the desired fabric.

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

References

Chamberlain J. Hosiery yarns and fabrics. Leicester: Leicester College of Technology and Commerce, 1926, p.107.

Allan HS, Greenwood PF, Leah RD, et al. Prediction of Finished Weight and Shrinkage of Cotton Knits–The Starfish Project. Part I: Introduction and General Overview. Text Res J 1983; 53: 109–119.

Singh G, Roy K, Varshney, R, et al. Dimensional parameters of single jersey cotton knitted fabrics. Indian Journal of Fibre & Textile Research (IJFTR) 2011; 36

Amreeva

Kurbak

. Experimental studies on the dimensional properties of half milano and milano rib fabrics. Text Res 2007; 77: 151–160. .

Black

. Shrinkage control for cotton and cotton blend knitted fabrics. Text Res J 1974; 44: 606–611. .

Demiroz A. A study of graphical representation of knitted structures. PhD Thesis, UMIST, Manchester, UK, 1998.

Gravas

Kiekens

Langenhove

. An approach to the ‘Proknit’ system and its value in the production of weft-knitted fabrics. AUTEX Res J 2005; 5: 220–227. .

Growers

Hunter

. The wet relaxed dimensions of plain knitted fabrics. J Text Inst 1978; 69: 108–115. .

Heap

Greenwood

Leah

, et al. Prediction of finished weight and shrinkage of cotton knits—the Starfish Project: part I: introduction and general overview. Text Res J 1983; 53: 109–119. .

10.

Heap SA. Low shrink cotton knits textiles fashioning the future. In: textile institute annual world conference proceedings, Nottingham, United Kingdom, 1989.

11.

Heap

Stevens

. Shrinkage, if you can predict it you can control it. Cotton Technol Int 1993, pp. 13: 32–32.

12.

Wickham H. ggplot2: elegant graphics for data analysis. New York: Springer, 2016..

13.

Kurbak

Amreeva

. Creation of a geometrical model for milano rib fabric. Text Res J 2006; 76: 847–852. .

14.

Leaf

GAV

Glaskin

. Geometry of plain knitted loop. J Text Inst 1955; 46: T587 .

15.

Leong

Falzon

Bannister

, et al. An investigation of the mechanical performance of weft knitted milano rib glass/epoxy composites. Comp Sci Technol 1988; 52: 239–251. .

16.

Münden

. The geometry and dimensional properties of plain knit fabrics. J Text Inst 1959; 50: T448–T471. .

17.

Peirce

. Geometrical principles applicable to the design of functional fabrics. Text Res J 1947; 17: 123–147. .

18.

Poincloux

Adda-Bedia

Lechenault

. Geometry and elasticity of a knitted fabric. Phys Rev X 2018, pp. 8: 1–14.

19.

Münden

. The dimensional behaviour of knitted fabrics. J Text Inst 1960; 51: 200–209.

20.

Munden

. Knitting versus weaving. Text Merc Int 1963; 12: 10–13.

21.

Nayak

Kanesalingam

Houshyar

, et al. Effect of repeated laundering and dry-cleaning on the thermo-physiological comfort properties of aramid fabrics. Fiber Polym 2016; 17: 954–962.

22.

Doyle

. Fundamental aspects of the design of knitted fabrics. J Text Inst 1953; 44: 561–578.

23.

Nutting

Leaf

GAV

. A generalised geometry of weft knitted fabrics. J Text Inst 1968; 55: T45–53.

24.

Knapton

JJF

Ahrens

Ingenthron

, et al. The dimensional properties of knitted wool fabrics, part I: the plain knitted structure. J Text Inst 1968; 38: 999–1012.

25.

Knapton

JJF

Truter

Aziz

AKMA

. Geometry, dimensional properties and stabilization of the cotton plain jersey structure. J Text Inst 1975; 66: 413–419.

26.

Fletcher

Roberts

. The geometry of plain and rib knit fabrics and its relation to shrinkage in laundering. Text Res J 1952; 22: 84–88.

27.

Fletcher

Roberts

. The geometry of knit fabrics made of stape rayon and nylon and its relationship to shrinkage in laundering. Text Res J 1952; 23: 37–42.

28.

Fletcher

Roberts

. Distortion in knit fabrics and its relation to shrinkage in laundering. Text Res J 1953; 23: 37–42.

29.

Fletcher

Roberts

. Relationship of the geometry of plain knit cotton fabric to its dimensional change and elastic properties. Text Res J 1954; 24: 729–737.

30.

Fletcher

Roberts

. Elastic properties of plain and double knit cotton fabrics. Text Res J 1965; 35: 497–503.

31.

Fletcher

Roberts

. Dimensional stability and elasticity properties of plain knit wool fabrics with and without Wurlan finish. Text Res J 1965; 35: 993–999.

32.

Aton

. The Starfish Project: an integrated approach to shrinkage control in cotton knits. Part 4, The Starfish predictive modelo as a design toll. Knit Int 1986; 93: 37–40.

33.

Greenwood

. The Starfish project: an integrated approach to shrinkage control in cotton knits. Part 6, the influence of the laundering treatment. Knit Int 1986; 93: 58–60.

34.

Heap

Greenwood

Leah

, et al. Prediction of finished relaxed dimensions of cotton knits- the Starfish Project: part II: shrinkage and reference state. Text Res J 1985; 55: 211–222.

35.

Leah

. The Starfish Project: an integrated approach to shrinkage control in cotton knits. Part 5, finishing to achieve specification. Knit Int 1986; 93: 96–99.

36.

Stevens

. The Starfish project: an integrated approach to shrinkage control in cotton knits. Part 2, the influence of knitting and finishing variables on the relaxed (reference state) dimensions. Knit Int 1986; 93: 80–83.

37.

Urkitt

. The Starfish project: an integrated approach to shrinkage control in cotton knits. Part 1, introduction and definition of the reference state. Knit Int 1986; 93: 40–42.

38.

Ulson

Cabral

Souza

MAG

. Prediction of dimensional changes in circular knitted cotton fabrics. Text Res J 2010; 80: 236–252.

39.

Saravana

Sampath

. Prediction of dimensional properties of weft knitted cardigan fabric by artificial neural network system. J Ind Text 2012; 42: 446–458.

40.

Mobarok

AKM

. Prediction of dimension and performance of finished cotton knitted fabric from knitting variables. Ann Univ Oradea Fascicle Text 2012; 2: 99–103. .

41.

Eltahan

EAe

Sultan

Mito

A-B

. Determination of loop length, tightness factor and porosity of single jersey knitted fabric. Alexandra Eng J 2016; 55: 851–856. .

42.

Eltahan

. Effect of lycra percentages and loop length on the physical and mechanical properties of single jersey knitted fabrics. J Compos 2016, pp. 7: 1–7 .

43.

Sitotaw

. Dimensional characteristics of knitted fabrics made from 100% cotton and cotton/elastane yarns. J Eng 2018. Epub Ahead of print 2018. DOI:10.1155/2018/8784692.

44.

Sitotaw

Adamu

. Tensile properties of single jersey and 1x1 rib knitted fabrics made from 100% cotton and cotton/lycra yarns. J Eng Epub Ahead of print 2017, pp. DOI:10.1155/2017/4310782 .

45.

Llinares

Miró

Díaz

. Modelling loop length in weft-knitted fabrics with an interlock structure after the dyeing process with a stich density, wales and courses per centimeter analysis. J Text Inst 2020; 111(7): 934–940.

46.

UNE-EN ISO 6330: 2012. Procedimiento de lavado y secado domésticos para los ensayos textiles.

47.

UNE-EN 14971: 2006. Determinación del número de puntadas por unidad de longitud y unidad de área.

48.

UNE-EN 14970: 2007. Determinación de la longitud de hilo absorbido o consumido y de la masa lineal o título del hilo en los tejidos de punto por recogida.