A statistical analysis of low-stress mechanical properties of warp-knitted fabrics

Abstract

Fabric hand is an indispensable characteristic for the selection of fabric and product development and the buying consideration for manufacturers and consumers. However, there is little comprehensive work on the hand feel property of warp-knitted fabrics due to the mainstream natural fibers (cotton, wool and silk) and other fabric structures (woven, weft-knitted and nonwoven). The increasing potential for the wide variety of applications and development of warp-knitted fabrics is not only because its fabric hand gives better determination for fabric marketing, but also because it provides extensive scope for fabric performance and appearance. This paper reports an experimental study on the integrated fabric hand behavior of a series of warp-knitted fabrics made for various apparel applications, such as sportswear, lingerie and leisure wear. These 105 fabrics were produced by varying different physical parameters, including fabric weight and fabric thickness. The Kawabata Evaluation System for Fabric (KES-F) was employed to obtain the fabric hand properties (primary hand value and total hand value) related with stiffness, smoothness and softness. All low-stress mechanical properties and fabric hand values from the testing results were used to verify the applicability of the KES-F on warp-knitted fabrics and to analyze the relationships of fabric parameters and hand characteristics. The results indicate that the KES-F is an appropriate tool to measure the hand attributes of warp-knitted samples, and moderate correlations between physical properties and mechanical behavior were found.

Keywords

fabric hand Kawabata Evaluation System for Fabric low-stress mechanical properties primary hand value total hand value warp-knitted fabric

Handle is a comprehensive term representing physical, psychological and social response to the touch of a fabric.¹ It is concerned with the subjective judgment of roughness, smoothness, harshness, pliability, thickness, etc.² As early as 1930, Peirce³ termed fabric hand as customers’ perception and he initially proposed evaluation of fabric handle using a series of measurable low-stress physical and mechanical properties of fabrics. Howorth and Oliver⁴ then pioneered the application of multiple factor analysis to identify factors affecting the handle of suiting materials. According to their analysis, the handle of worsted suiting can be specified in terms of three quality attributes: fabric smoothness, stiffness and thickness.

Fabric hand is an indispensable characteristic for the selection of fabric and product development and the buying consideration of manufacturers and consumers. However, there is little comprehensive work on the hand feel property of warp-knitted fabrics due to the mainstream natural fibers (cotton, wool and silk) and other fabric structures (woven, weft-knitted and nonwoven). The increasing potential for the wide variety of applications and development of warp-knitted fabrics is not only because its fabric hand gives better determination for fabric marketing, but also because it provides extensive scope for fabric performance and appearance.

Fabric objective measurement, as defined by Bishop,⁵ is “the evaluation of fabric handle, quality and related fabric-performance attributes, in terms of objectively measurable properties.” The most well-known method, the Kawabata Evaluation System for Fabrics (KES-F), aimed to relate objective measurement of important mechanical properties in fabric hand to subjective evaluation.^6–9 Hand descriptors, namely stiffness, smoothness, fullness and softness, were termed as primary hand values (PHVs). The quantitative component of the system was determined by a series of instruments that measure fabric responses to low deformations. The method of measuring fabric mechanical properties involves a complete fabric deformation–recovery cycle for tensile, shear, bending and lateral compression properties. In all cases, the deformation–recovery cycle was accompanied by a significant energy loss or hysteresis. The system relies on the multiple linear regression technique to correlate the mechanical measurements data to subjective fabric hand evaluation and shows clear physical interpretation of test results. Researchers have adopted the KES-F for evaluating low-stress mechanical properties of different textile materials.^10–14

However, the validity of multivariate regression analysis is often severely influenced by collinearity of data, which appears to exist between the mechanical parameters obtained from the KES-F instruments.¹⁵ There could be problems such as uncertainty, overlapping and instability in the meaning of the PHVs.¹⁶ Limitation also appears on the types of fabrics used in the equations calculating fabric hand values. Those equations are mostly based on woven and weft-knitted suit fabrics, which are obviously different from the warp-knitted fabrics used in this paper. In such a case, efforts have been made to investigate the applicability and accuracy of the KES-F on warp-knitted fabrics regarding hand characteristics and physical parameters.

With the interest of low cost, high productivity and wide structure variations, warp-knitted fabrics have become more attractive for various applications in economic and technological development. Although there are some experimental studies^17–20 on the mechanical properties of warp-knitted fabrics, there has been rather little research of the overall load–displacement measurement and integrated hand relationship with fabric physical properties. Therefore, the purpose of this report is to expound the interrelation of warp-knitted fabric with hand behavior in detail. Low-stress mechanical properties measured by the KES-F are verified so as to descant the significant coefficient of the experimental data.

Experimental details

Preparation of samples

One-hundred-and-five fabrics (their specifications are shown in Table 1) were selected on the basis of being 100% polyester warp-knitted fabrics, provided by Burltexplus Knitting Industrial Ltd and Tai Tung Interlining Ltd in Hong Kong. Fabrics were labeled and cut into pieces with approximate dimensions of 20 cm × 20 cm for KES-F measurement. All specimens were kept individually in a Butylated Hydroxytoluene (BHT-free) plastic bag in order to prevent getting dirty, folded or wrinkled before assessment.

Table 1.

Specifications of sample

Sample	Construction	Color	Weight (g/m²)	Thickness (mm)	Fiber content
1	Mesh	Deep blue	65	0.45	Polyester
2	Mesh	White	85	0.44	Polyester
3	Mesh	White	110	0.57	Polyester
4	Mesh	Gray	65	0.36	Polyester
5	Mesh	Gray	60	0.34	Polyester
6	Mesh	Deep blue	60	0.26	Polyester
7	Mesh	Gray	65	0.31	Polyester
8	Mesh	Black	65	0.29	Polyester
9	Mesh	Black	60	0.25	Polyester
10	Mesh	White	65	0.41	Polyester
11	Mesh	Black	65	0.43	Polyester
12	Mesh	Gray	70	0.47	Polyester
13	Mesh	Black	80	0.25	Polyester
14	Mesh	Black	110	0.35	Polyester
15	Mesh	Black	130	0.38	Polyester
16	Mesh	Green	110	0.62	Polyester
17	Mesh	Black	100	0.31	Polyester
18	Mesh	Gray	105	0.34	Polyester
19	Mesh	Black	110	0.47	Polyester
20	Mesh	Black	110	0.56	Polyester
21	Mesh	Black	120	0.56	Polyester
22	Mesh	White	100	0.34	Polyester
23	Mesh	Black	60	0.45	Polyester
24	Mesh	Deep blue	120	0.48	Polyester
25	Mesh	Black	130	0.45	Polyester
26	Mesh	Dark gray	100	0.52	Polyester
27	Mesh	Black	115	0.42	Polyester
28	Mesh	Orange-red	85	0.57	Polyester
29	Mesh	Gray	55	0.41	Polyester
30	Mesh	Dark gray	55	0.28	Polyester
31	3d mesh	Black	200	0.45	Polyester
32	Space mesh	Black	180	1.45	Polyester
33	Space mesh	Black	210	2.26	Polyester
34	Space mesh	Black	250	1.84	Polyester
35	Shiny mesh	Light gray	100	0.33	Polyester
36	Shiny mesh	Gray	75	0.32	Polyester
37	Shiny mesh	Blue	75	0.28	Polyester
38	Shiny mesh	Gray	110	0.36	Polyester
39	Brushed mesh	White	120	0.51	Polyester
40	Brushed mesh	Black	130	0.61	Polyester
41	Brushed mesh	Black	145	0.67	Polyester
42	Brushed mesh	Black	120	0.64	Polyester
43	Brushed mesh	Black	160	0.78	Polyester
44	Brushed mesh	Light gray	160	0.69	Polyester
45	Brushed mesh	Blue-gray	130	0.61	Polyester
46	3d brushed mesh	White	190	0.93	Polyester
47	Tricot	Black	110	0.29	Polyester
48	Brushed tricot	Dark gray	100	0.4	Polyester
49	Brushed tricot	Black	160	0.95	Polyester
50	Brushed tricot	Black	260	0.67	Polyester
51	Brushed tricot	Orange	120	0.61	Polyester
52	Brushed tricot	White	160	0.68	Polyester
53	Brushed tricot	Gray	200	0.67	Polyester
54	Brushed tricot	Beige	200	0.57	Polyester
55	Micro brushed tricot	Pink	125	0.52	Polyester
56	Micro brushed tricot	Gray	125	0.57	Polyester
57	Micro brushed tricot	Gray	140	0.64	Polyester
58	Bird eye mesh	Gray	120	0.6	Polyester
59	Mesh	Dark orange	120	0.56	Polyester
60	Shiny mesh	Sliver	110	0.37	Polyester
61	Brushed mesh	Deep blue	75	0.38	Polyester
62	Brushed mesh	Deep blue	125	0.57	Polyester
63	Brushed mesh	Yellow	75	0.43	Polyester
64	Brushed mesh	Yellow	125	0.61	Polyester
65	Brushed mesh	Dark gray	125	0.55	Polyester
66	Brushed mesh	Dark gray	75	0.4	Polyester
67	Brushed mesh	Purple	75	0.4	Polyester
68	Brushed mesh	Light green	75	0.35	Polyester
69	Brushed mesh	Blue	75	0.36	Polyester
70	Brushed mesh	Red	160	0.77	Polyester
71	Brushed mesh	Red	75	0.45	Polyester
72	Brushed mesh	Red	125	0.65	Polyester
73	Brushed mesh	Green	125	0.6	Polyester
74	Brushed mesh	Red	125	0.6	Polyester
75	Brushed mesh	Pink	125	0.7	Polyester
76	Mesh	Black	65	0.42	Polyester
77	Mesh	Black	120	0.55	Polyester
78	Ultra micro mesh	Blue	45	0.33	Polyester
79	Ultra micro mesh	Light blue	75	0.41	Polyester
80	Brushed mesh	Light blue	85	0.49	Polyester
81	Brushed mesh	Blue	80	0.48	Polyester
82	Brushed mesh	Grass-green	75	0.45	Polyester
83	Brushed mesh	Deep blue	80	0.5	Polyester
84	Brushed mesh	Green	75	0.39	Polyester
85	Brushed mesh	Blue	125	0.55	Polyester
86	Brushed mesh	Dark berry	75	0.47	Polyester
87	Brushed mesh	Gray	75	0.41	Polyester
88	Brushed mesh	Deep blue	125	0.54	Polyester
89	Brushed mesh	Dark berry	75	0.43	Polyester
90	Mesh	Blue	75	0.39	Polyester
91	Mesh	Orange	75	0.4	Polyester
92	Mesh	Gray	130	0.38	Polyester
93	Mesh	Flame orange	65	0.4	Polyester
94	Brushed mesh	Navy	130	0.67	Polyester
95	Brushed tricot	Dark berry	110	0.45	Polyester
96	Brushed tricot	Ecehing blue	100	0.61	Polyester
97	Mesh	Princess blue	50	0.35	Polyester
98	Mesh	Moccancian blue	45	0.24	Polyester
99	Mesh	Pink glow	70	0.38	Polyester
100	Mesh	Blue granite	75	0.41	Polyester
101	Mesh	Air blue	75	0.47	Polyester
102	Brushed mesh	Alloy	80	0.52	Polyester
103	Space mesh	Black	140	1.56	Polyester
104	Ultra micro mesh	Earth	45	0.28	Polyester
105	Mesh	Light blue	110	0.59	Polyester

Fabric weight and thickness

The 105 warp-knitted fabrics were of different types: mesh, spacer mesh, shiny mesh, brushed mesh, tricot, brushed tricot and micro brushed tricot. Distinct fabric weight and thickness were measured and sample conditions were kept at 65 ± 2% relative humidity and 21 ± 2℃ for at least 24 hours before measurement. Fabric weights of different sizes (100 cm²) and thicknesses were calculated according to ASTM Standards D3776 and ASTM D1777, respectively. The fabric weight ranged from 55 to 260 g/m² and thickness ranged from 0.25 to 2.26 mm. These two basic physical properties are important for determining fabric hand value and mechanical properties.

Parameters measured by the KES-F

Five specimens of each type of fabric were tested on the technical face side. The KES-F for measurement of fabric low-stress mechanical and surface properties comprises four separate instruments, namely KES-F-1 for tensile and shear properties; KES-F-2 for bending properties; KES-F-3 for compression properties; and KES-F-4 for surface properties. Low-stress mechanical properties, such as tensile, bending, shear and surface properties, were measured for both warpwise and weftwise directions. The tested property details are given in Table 2.

Table 2.

Properties measured by the Kawabata Evaluation System for Fabric

Properties	Symbols	Characteristic value	Unit
Tensile	EMT	Extensibility, strain	(%)
	LT	Linearity of Load	–
	WT	Tensile energy	gf.cm/cm²
	RT	Tensile resilience	%
Shearing	G	Shear stiffness	gf/cm.degree
	2HG	Hysteresis at Φ = 0.5°	gf/cm
	2HG5	Hysteresis at Φ = 5°	gf/cm
Bending	B	Bending rigidity	gf.cm²/cm
	2HB	Hysteresis per unit length	gf.cm²/cm
Compression	LC	Linearity of compression	–
	WC	Compression energy	gf.cm/cm²
	RC	Compression resilience	%
Surface	MIU	Coefficient of friction	–
	MMD	Mean Deviation of MIU	–
	SMD	Surface roughness	micron

The objective determination of hand is indicated as tensile, shear, bending, compression and surface properties. Measurements were used to predict the PHVs, such as smoothness, crispness, fullness and softness. The total hand value (THV) was determined from the primary hand and women’s suits for medium-thick fabrics (stiffness, smoothness, softness and soft feeling; Table 2) were selected for the expression of results of all fabric samples. The main reasons for choosing women’s suiting (KN-201-MDY) as the equation standard of fabric hand value from the KES-F are as follows. (i) According to the fabric types, sportswear, intimate and leisure wear are the three fundamental elements that suit for fabric description. Knit underwear in summer (KN-402-KT) and men’s summer suits (KN-101-SUMMER) were found to have too many negative results on hand values. Satisfactory results were obtained for women’s suiting and these were viewed as more conducive to better interpretation in the result and analysis. (ii) Women’s suiting can also be chosen from thin or medium-thick fabric types. This classification is based on the sample thickness. Among the samples, 89% were within the range of medium-thick fabrics in terms of thickness (0.323–2.490 mm) and 56% were in the weight range of 9.38–42.97 mg/cm². (iii) In the primary hand expression for women’s medium-thick fabrics, the term “sofutosa” is a unique semi-hand PHV that expresses the mixed feeling of the other three primary hands shown in Table 3. This hand expression is claimed to be used very frequently in the market and industry because of its importance as an intensive expression. Thus, such extra hand value can help one to obtain more hand information that distinguishes better fabric hand.

Table 3.

Primary hand expressions and the definitions from the Kawabata Evaluation System for Fabric

Primary hand	Definition
Stiffness (Koshi)	A feeling related to bending stiffness. Springy properties promote this feeling. A fabric that has compact weaving density and is woven from springy and elastic yarn makes this feeling strong.
Smoothness (Numeri)	A mixed feeling arising from smooth, limber and soft sensations. Fabric woven from cashmere fiber gives this feeling strongly.
Softness (Fukurami)	A feeling arising from bulky, rich and well-formed sensations. Springy properties in compression and thickness accompanied with warm feeling are closely related with this primary hand.
Soft feeling (Sofutosa)	Soft feeling, a mixed feeling of bulky, flexible and smooth feelings.

Results and discussion

Comparative study of low-stress mechanical properties on warp-knitted fabrics

The results of objective assessments of hand value were compared with physical properties, including weight and thickness. The correlations between mechanical properties and fabric parameters were explored in order to determine whether the hand feel characteristic was highlighted under quality evaluation. Objective measurement of warp-knitted fabrics using the KES-F was derived from low-stress mechanical parameters in terms of tensile, shear, bending, compression and surface properties. With the result of PHV and THV, fabrics were analyzed in relation to their fabric weight and thickness.

Tensile property

The extensibility (EMT), tensile linearity (LT) and tensile energy (WT) of warp-knitted fabrics show differences in the warpwise (w) and weftwise (c) directions. According to Figure 1, it is obvious that the average values of EMT(w), LT(w) and WT(w) are higher than that of EMT(c), LT(c) and WT(c), respectively. It is true that in warp-knitted fabric structures, extensibility in the warpwise direction is always higher than in the weftwise direction. Because of higher extensibility in the warpwise direction, more energy is needed to extend the warpwise samples than the weftwise. Under the t-test, the t_o values for relationship between EMT(w) and EMT(c), LT(w) and LT(c), and WT(w) and WT(c) are 5.68, 2.63 and 4.88, respectively, which are higher than the t-value (2.576), indicating that the relationships are significant at the 0.01 level (two-tailed). The warp fabrics statistically have better extensibility (EMT), tensile linearity (LT) and tensile energy (WT) in the warp direction than in the weft direction.

Figure 1.

Tensile property of warp-knitted fabrics.

The tensile resilience (RT), however, is higher in the weftwise direction than in the warpwise direction. The average value of RT(c) is 56.44% and RT(w) is 49.28%. As the tensile resilience measures the fabric recovery process in the force–extension curve, a higher tensile extensibility contributes to lower tensile resilience for longer time of fabric recovery process. This result is again attributable to the compact structure of warp-knitted fabrics.

The correlation coefficients for the tensile parameters are shown in Table 4. The tensile energy (WT) is highly correlated with tensile extension (EMT) for these 105 warp-knitted fabrics. The correlation coefficient between LT(w) and LT(c) is 0.696, which is significant at the 0.01 level. The correlation coefficient in the warpwise direction between WT(w) and EMT(w) was 0.845 and in the weftwise direction between WT(c) and EMT(c) was 0.857. Both values are significant at the 0.01 level. The fabric weight shows a negative correlation with extensibility and tensile energy in both warpwise and weftwise directions (Table 4). This implies that the fabric weight would affect the tensile extension and energy. Heavier fabrics, such as spacer mesh, brushed mesh and brushed tricot, have lower extensibility, which leads to lower tensile energy being needed. Light warp-knitted fabrics with high porosity, that is, plain mesh, shiny mesh and plain tricot, are generally easier to extend.

Table 4.

Correlation coefficients for tensile properties

	EMT(w)	EMT(c)	LT(w)	LT(c)	WT(w)	WT(c)	RT(w)	RT(c)	W	T
EMT(w)	1
EMT(c)	**0.731	1
LT(w)	0.072	−0.037	1
LT(c)	0.083	0.021	**0.696	1
WT(w)	**0.845	**0.532	−0.102	−0.08	1
WT(c)	**0.787	**0.857	−0.062	0.007	**0.815	1
RT(w)	−0.153	0.113	*0.211	−0.016	**−0.255	−0.026	1
RT(c)	0.079	−0.068	0.011	−0.1	0.102	0.001	**0.490	1
W	**−0.331	*−.247	0.007	0.015	**−0.331	**−0.293	**0.278	0	1
T	−0.189	−0.057	−0.132	0.006	*−0.197	−0.113	0.057	*−0.202	**0.687	1

w: warpwise direction; c: weftwise direction; W: weight; T: thickness.

Correlation is significant at the 0.01 level (two-tailed).

Correlation is significant at the 0.05 level (two-tailed).

Shearing property

Fabric shear rigidity is a measure of stability of the fabric membrane. Measurement of shear rigidity can be done with tension applied to the fabric in either the warpwise direction or the weftwise direction. Fabric shear rigidity measures the relative movement between the warpwise and the weftwise directions. The correlation between fabric shear parameters in the warpwise and weftwise directions is shown in Table 5. It can be shown that there is a direct relationship between fabric shear and shear hysteresis. The correlation coefficient between G(w) and 2HG(w) is 0.673 and between 2HG(w) and 2HG5(w) is 0.498, both significant at the 0.01 level. However, there is a lower correlation between G(w) and 2HG5(w), for which the correlation coefficient is 0.505. Under the t-test, the t_o values for the relationship between G(w) and 2HG(w), 2HG(w) and 2HG5(w), and G(w) and 2HG5(w) are 9.23, 5.83 and 5.94, respectively, which are higher than the t-value (2.576), indicating that the relationships are significant at the 0.01 level (two-tailed). The null hypothesis is rejected and this indicates that shear rigidity is related to shear hysteresis measured at a 0.5 degree shear angle on the KES-F, but is less related to shear hysteresis measured at a 5 degree shear angle.

Table 5.

Correlation coefficients for shear properties

	G(w)	G(c)	2HG(w)	2HG(c)	2HG5(w)	2HG5(c)	W	T
G(w)	1
G(c)	**0.908	1
2HG(w)	**0.673	**0.700	1
2HG(c)	**0.663	**0.777	**0.883	1
2HG5(w)	**0.505	**0.448	**0.498	**0.517	1
2HG5(c)	**0.518	**0.63	**0.525	**0.693	**0.807	1
W	**0.585	**0.583	0.159	**0.283	**0.450	**0.567	1
T	**0.500	**0.470	**0.309	**0.399	**0.602	**0.645	**0.687	1

w: warpwise direction; c: weftwise direction; W: weight; T: thickness.

Correlation is significant at the 0.01 level (two-tailed).

It can also be seen from Table 5 that the correlation coefficient between G(w) and G(c) is 0.908, implying a positive relationship. This result means the shear test can be done in only one direction, as the two measurements are highly correlated. It should also be noted that a correlation was found between 2HG5(w) and 2HG5(c), being 0.807. Therefore, the shear test for all warp-knitted fabrics was conducted for tension applied in one direction (the warpwise direction). Similar to the results of tensile properties, shear rigidity shows a correlation with fabric weight and thickness, where the correlation coefficient between G(w) and W and T is 0.585 and 0.500, respectively (significant at the 0.01 level). Similar to the tensile property, the heavier and bulkier the fabric, the more difficult it is to shear in parallel with warpwise and weftwise yarns.

Bending property

A reasonably wide range of fabric bending rigidity values were observed in the 105 warp-knitted fabric samples. The highest value of warpwise bending rigidity is 1.448 gf.cm²/cm, and the lowest is 0.03 gf.cm²/cm. For the weftwise direction of the fabric, the highest and the lowest bending rigidity is 1.47 and 0.02 gf.cm²/cm, respectively.

Generally speaking, bending rigidity increases with increase of fabric weight per unit area. For all warp-knitted fabrics, bending rigidity in the weftwise direction is higher than in the warpwise direction, as shown in Figure 2. The unusually high value of bending rigidity (1.448 gf.cm²/cm) can be explained by the fact that this fabric (spacer fabric) is the thickest fabric (2.26 mm) among the 105 fabrics.

Figure 2.

Warpwise (wale direction) and weftwise (course direction) bending rigidities of warp-knitted fabrics.

As shown in Table 6, the coefficients of the correlation between bending rigidity (warpwise and weftwise directions) and fabric weight per unit area are 0.505 and 0.511, respectively. These results are similar and indicate that fabric bending rigidity is to some extent determined by fabric mass. In addition, there is a correlation between fabric thickness and bending properties (R = 0.772 and 0.735). It should be stressed that this physical property affects the bending rigidity value to a large extent because the thicker the fabric, the harder it is to crook the fabric. According to Table 5, the bending hysteresis shows a relationship with bending rigidity for all warp-knitted fabrics. The coefficient of the correlation between B(w) and 2HB(w) is 0.960. The coefficient of the correlation between B(c) and 2HB(c) is 0.990.

Table 6.

Correlation coefficients for bending properties

	B(w)	B(c)	2HB(w)	2HB(c)	W	T
B(w)	1
B(c)	**0.966	1
2HB(w)	**0.960	**0.908	1
2HB(c)	**0.979	**0.990	**0.934	1
W	**0.505	**0.511	**0.472	**0.482	1
T	**0.772	**0.735	**0.742	**0.733	**0.687	1

w: warpwise direction; c: weftwise direction; W: weight; T: thickness.

Correlation is significant at the 0.01 level (two-tailed).

Compression property

There is a general trend that fabric thickness increases with increase of fabric weight. The correlation coefficient (R) between fabric thickness and weight is 0.687, as shown in Table 7.

Table 7.

Correlation coefficients for compression properties

	LC	WC	RC	W	T
LC	1
WC	**0.292	1
RC	**0.420	**0.487	1
W	*0.236	**0.494	**0.300	1
T	**0.553	**0.795	**0.642	**0.687	1

W: weight; T: thickness.

Correlation is significant at the 0.01 level (two-tailed).

Correlation is significant at the 0.05 level (two-tailed).

The results show that fabric weight has a correlation with fabric thickness when using the KES-F. It can be explained that when fabric thickness is measured under pressure, surface fibers and irregularities are compressed into the main body of the fabric. The result is denser fabric and, therefore, the measurement of fabric thickness under pressure gives a correlation with fabric weight.

For all fabrics tested, the correlation coefficient between fabric compression linearity (LC) and fabric weight (W) is relatively low at 0.236. Under the t-test, the t_o value for the relationship between LC and W is 2.46, which is higher than the t-value (1.960), indicating that the relationship is significant at the 0.05 level (two-tailed).

The correlation coefficient between fabric compression linearity (LC) and fabric thickness (T) is 0.553. The first result indicates that there may be a tendency for fabric compression linearity to be raised with increasing fabric weight and the second result shows that there is a moderate tendency for fabric compression linearity to be raised with increasing fabric thickness. It is found that increasing fabric thickness produces a softer fabric in compression.

The correlation coefficient between compression linearity (LC) and compression energy (WC) is 0.292, significant at the 0.01 level. Under the t-test, the t_o value for the relationship between LC and WC is 3.10, which is higher than the t-value (2.576), indicating that the relationships are significant at the 0.01 level (two-tailed). The two parameters are directly related because compression energy is measured as the total energy stored and the compression linearity is measured as the ratio of compression energy stored in the fabric to the total energy or area under a hypothetical linear compression–thickness curve. Therefore, a higher value of compression linearity would generally give a higher value of compression energy.

The compression energy (WC) shows a significant correlation with fabric thickness (T). The correlation coefficient between WC and T is 0.795. This result illustrates that a thicker fabric needs larger compression energy.

As Table 6 shows, a relationship exists between fabric thickness (T) and fabric compression resilience (RC). The correlation coefficient between RC and T is 0.642. It is clear that the fabric compression resilience goes up with an increase in fabric thickness. This result suggests that light fabric is relatively difficult to compress, having high compression resilience, or, in other words, thicker fabrics are more elastic in compression than thin fabrics.

Surface property

Fabric surface properties can be described using the KES-FB-4 surface tester to measure properties, such as coefficient of friction (MIU), fabric mean deviation (MMD) and fabric roughness (SMD).

As shown in Table 8, there is a relationship between fabric roughness (SMD) or the surface texture and fabric weight. These two properties have a negative correlation coefficient; R = −0.447, significant at the 0.01 level. This indicates that the surface roughness increases when the fabric weight decreases. This was because many lighter fabrics samples were assembled in the mesh fabric group. From KES-F measurement, surface friction and roughness are measured by using a steel pianowire contactor, which simulates a human fingerprint. The porosity and open structure of mesh fabrics increases the surface roughness (sensitive by contactor). Brushed samples with a smoother face apparently diminish the surface harshness.

Table 8.

Correlation coefficient of surface properties

	MIU(w)	MIU(c)	MMD(w)	MMD(c)	SMD(w)	SMD(c)	W	T
MIU(w)	1
MIU(c)	−0.099	1
MMD(w)	**0.353	**−0.542	1
MMD(c)	−0.029	−0.091	**0.327	1
SMD(w)	**0.277	−0.125	*0.212	−0.119	1
SMD(c)	**−0.326	**0.437	**−0.578	−0.142	0.05	1
W	0.062	−0.041	**0.276	**0.340	−0.127	**−0.447	1
T	−0.001	*0.204	0.133	0.181	−0.013	−0.19	**0.687	1

w: warpwise direction; c: weftwise direction; W: weight; T: thickness.

Correlation is significant at the 0.01 level (two-tailed).

Correlation is significant at the 0.05 level (two-tailed).

Primary hand value and total hand value

The warp-knitted fabrics were measured objectively by using the KES-F. The calculated PHVs and the THV are analyzed by using the Hand Evaluation and Standardization Committee (HESC) translation equation for women’s suit medium-thick fabric materials.⁶ The PHV for fabric stiffness ranges from 1.08 to 9.82 for all warp-knitted fabrics. For smoothness and softness, the PHV ranges from 1.64 to 7.58 and from 0.51 to 7.98, respectively. The THV for these 105 fabrics ranges from 0.99 to 3.98.

The correlation matrix for the THV to the PHVs obtained from the measurements using the KES-F (Table 8) was calculated so as to access their relationship for the warp-knitted fabrics for women’s suits.

Table 9 shows that the PHVs of smoothness, softness and soft feeling are directly related to the THV, with R = 0.834, 0.907 and 0.736, respectively, significant at the 0.01 level. This means the PHVs of smoothness and softness for these warp-knitted fabrics make a significant positive contribution to the THV. Such analysis proves that the HESC equation standard is applicable and accurate to measure the hand characteristic of warp-knitted samples in this paper, even though the KES-F was not designated for warp-knitted fabrics. The relationships of the THV to fabric smoothness and softness are shown in Figures 3 and 4, respectively.

Table 9.

Correlation matrix for primary hand values and total hand value (THV)

	Stiffness	Smoothness	Softness	Soft feeling	THV	W	T
Stiffness	1
Smoothness	**−0.603	1
Softness	**−0.286	**0.853	1
Soft feeling	**−0.641	**0.957	**0.805	1
THV	−0.124	**0.834	**0.907	**0.736	1
W	**0.821	**−0.316	−0.015	**−0.390	0.111	1
T	**0.611	−0.042	**0.406	−0.058	**0.365	**0.687	1

W: weight; T: thickness.

Correlation is significant at the 0.01 level (two-tailed).

Figure 3.

Relationship between total hand value and primary hand value of smoothness.

Figure 4.

Relationship between total hand value and primary hand value of softness.

Depending on Table 9, the stiffness of warp-knitted fabric is highly correlated to weight and thickness. The correlation coefficients between fabric stiffness and fabric weight and thickness are 0.821 and 0.611, respectively. This represents that heavier and thicker fabric is stiffer consequently. It is necessary to point out that such analysis on warp-knitted fabric is corresponding and equivalent with Peirce’s work.³ The relationships of stiffness with weight and thickness are shown in Figures 5 and 6, respectively, but the relationship is weakly correlated.^21,22

Figure 5.

Relationship between fabric weight and hand value of stiffness.

Figure 6.

Relationship between fabric thickness and hand value of stiffness.

Conclusion

This paper reports the objective assessment of fabric hand for warp-knitted fabrics by the KES-F. The results of low-stress mechanical properties were compared with physical parameters. The effect of different fabric weight and thickness toward hand attributes, including stiffness, smoothness and softness, were explored. According to the experimental results and analysis, the following conclusions can be drawn.

The KES-F is an applicable and precise tool of measuring the mechanical performance and hand feature for warp-knitted fabrics.

Physical properties are found to be positively related to stiffness and THV and invalid for fabric smoothness and softness.

In accordance with THV rating, brushed mesh has the best fabric hand performance, for which most THVs achieve a score of 3 or above.

The physical attributes, such as fabric weight and thickness, have an effect on the low-stress mechanical properties but have a different extent depending on the fabric type. For example, light fabrics (e.g. mesh and tricot) are good in extensibility, shear stiffness and bending rigidity. However, heavy fabrics (e.g. spacer fabrics and brushed mesh) performed well for compression properties.

Statistical analysis was conducted to evaluate different pairs of properties with low correlation coefficient values. Such low correlation coefficient values may be due to the friction and viscoelasticity and geometry of threads. However, statistical analysis revealed that even at a low correlation coefficient, the relationship between those pairs of properties was still significant statistically.

Footnotes

Declaration of conflicting interests

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

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Hong Kong Polytechnic University. Grant number is RTBQ.

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