New Dimensions of Various Interlock Knitted Derivatives

ABSTRACT

This study investigated the derivatives of interlock knitted structures by changing stitch type, location, and their percentage (%) on different performance properties. In the current study, 11 different interlock knit structures were developed by using multiple combinations of knit, tuck, and miss stitches and different types of testing, i.e., physical, mechanical, thermo-physiological comfort, tactile comfort, and dimensional properties, were performed and investigated. Analysis of variance (ANOVA) was performed to determine the statistical significance of structure on the properties. Based on the results, it was concluded that stitch type, percentage, and location have a prominent influence on the abovementioned properties of knit fabrics, which is also elaborated by interaction plots. The present research used a multi-response optimization technique, i.e., principal component analysis (PCA), to identify the best structure for industrial applications like uniforms, based on the optimization of abovementioned properties. Based on the results, it was suggested that a sample with an interlock cross relief structure was found to be the best in all aspects among all samples, followed by interlock pique and double tuck, which were ranked as 2nd and 3rd, respectively. This paper highlights the possible application of different interlock knitted structures according to end use for manufacturers.

摘要

本研究通过改变针脚类型、位置及其百分比（%）对不同性能的影响，研究了互锁针织结构的衍生物. 在目前的研究中，通过使用编织、收褶和漏针的多种组合，开发了11种不同的互锁编织结构，并进行了不同类型的测试，即物理、机械、热生理舒适性、触觉舒适性和尺寸特性，并对其进行了研究. 进行方差分析（ANOVA）以确定结构对性质的统计显著性. 结果表明，针脚类型、针脚百分比和针脚位置对针织物的上述性能有显著影响，并通过相互作用图进行了阐述. 本研究使用了一种多响应优化技术，即. 基于上述性能的优化，主成分分析（PCA）可确定制服等工业应用的最佳结构. 结果表明，在所有样品中，具有互锁交叉浮雕结构的样品在各个方面都是最好的，其次是互锁凸起和双褶分别排名第二和第三. 本文强调了制造商根据最终用途使用不同互锁针织结构的可能应用.

KEYWORDS:

• interlock fabric
• industrial applications
• mechanical properties
• comfort properties
• principal component analysis
• stitch type

关键词:

• 互锁织物
• 工业应用
• 机械性能
• 舒适性
• 主成分分析
• stich类型

Introduction

Knitting is one of the most widely used fabric manufacturing techniques, which is performed by interloping of yarns. Knitting is a more sustainable and simple process of fabric manufacturing as there is no need of preparatory process which is a pre-requisite for weaving (Pattanayak 2019). There are two types of knitting processes, i.e., weft and warp knitting, respectively. Weft knitting is further divided into circular and flat knitting. Primary knitted structures are jersey, rib, interlock, and purl. Besides knit/plain loop/stitch, there are tuck and miss stitches. By utilizing the mentioned stitches, primary structure has numerous secondary/derivative structures by varying the percentage and location of stitches. Knitting parameters and structures have a huge impact on the properties of fabric. Interlock knitted structure is a balanced structure with good softness properties. It is a double knit structure, and both sides of the fabric show face loops. It has various technical applications due to its characteristics like in protective textiles for station suits of firefighter (Balamurugan and Rachel 2012; Gokarneshan et al. 2012). It is preferred for use in various industrial uniforms due to its balanced extensibility in both directions, i.e., lengthwise and widthwise. It has applications in sports fabrics and sports shoes due to its hand/tactile properties and moisture management properties (Öner et al. 2013). Its application in medical textile has increased in the recent past due to its better performance and comfort properties as compared to rib structure (Pattanayak 2019). The usage of interlock knitted fabrics is gaining a rise day by day in the automobile industry as it has very high usage in the seat covers of luxury cars due to its better resilience properties and dimensional characteristics. Researchers compared the different basic knitted structures for summer wear. It was suggested on the basis of research that simple rib and interlock fabrics are suitable for low activity, while for severe activities double rib is recommended (Öner and Okur 2013). However, plaited interlock knitted fabrics with different fiber compositions can preferably be used for the next to the skin applications like summer wear and active wear due to its superior moisture management properties (Kumar and Kumar 2022). The thermo-physiological comfort properties of knitted fabrics used next to skin were also studied, and it was concluded that structural parameters such as tightness factor, thickness, fabric porosity, stitch density, and loop length had strong effect (Jhanji, Gupta, and Kothari 2015). Effect of number of tuck stitches in the plaited structure and effect of inlay yarn in double jersey fabric as inlay insertion, which is the structural parameter of the knitted fabric, were also investigated. It was concluded that inlay insertion and tuck stitches enhance the moisture management and thermal properties of the double knit fabrics (Kumar 2020). Different rib fabrics, i.e., 1 × 1, 2 × 2, 3 × 3, and the effect of structural properties of the rib on the thermal properties were also investigated. From research, it was concluded that decreasing the number of ribs, i.e., 1 × 1, tends to make the fabric tight and entrapped air in the fabric increased which reduced the heat loss. This improved the thermal properties of rib (Uçar and Yilmaz 2004). Studies on comfort properties of plain single jersey and 1 × 1 rib knitted fabrics were done and concluded that rib had less air permeability (AP) properties than jersey fabric due to higher thickness (Demiryürek, Uysaltürk, and Uysaltürk 2013). Three different types of knitted structures, i.e. single jersey, double jersey, and interlock fabrics, and their effect on the thermo-physiological properties of fabrics were also studied (Jordeva et al. 2017). The effect of structure and finishing treatment on the moisture management properties of cotton knitted fabrics was studied, and it was concluded that structure is a very important factor affecting the moisture transport properties of knitted fabrics (Chandrasekaran and Senthilkumar 2020). Fabric structures play an important role in the performance of different knitted fabrics. Knit structure is an important parameter in deciding the wicking and drying behavior of fabrics. Five different types of cotton knitted fabrics were developed, and their moisture behavior was studied. It was found that single pique and double pique knit fabrics had better diffusion and drying behavior. This study suggested the use of these knitted fabric structures in summer wear in heavy sweating conditions (Chen et al. 2022). Furthermore, a wide range of applications of rib and jersey knit structures can be found in literature. So, a lot of research has been done to study the performance properties of these two primary structures (jersey and rib) and their derivatives (Karthikeyan et al. 2017; Kumar 2020; Kumar, Kumar, and Prakash 2022; Margret et al. 2022; Suganthi et al. 2022). Although researchers have studied the properties of interlock knitted fabrics, only limited research has been done with reference to the combined effect of fiber blends and structures on the properties of knitted fabrics (Chen et al. 2020; Gokarneshan et al. 2012). In the present era, functionality and comfortability have become the hot topic for research. It can be achieved by raw material’s characters and structural design of yarn and fabric. Stitch is the basic unit of knitted fabrics, so it is very beneficial to study the impact of stitch type, percentage, and location on the properties of the finally developed product as a result of various combinations of stitches. By using various combinations of stitches, varying the percentage and location of knit, tuck, and miss stitches, a number of derivatives of interlock knit structures can be produced. From the literature it is obvious that a lot of work has been done regarding the effect of construction parameters and structure on the few properties of knitted fabric. But limited work has been done on investigating the interlock knitted structure and its derivatives by considering different properties like physical properties, mechanical properties, serviceability, dimeitsnsional stability, and comfort properties, i.e., thermo-physiological and tactile comfort properties altogether. There was a need to conduct a study that would primarily focus on the effect of structures related to stitch type, percentage, and location on the properties of interlock knitted fabrics.

The aim of the present study is to investigate the effect of stitch type, location, and its percentage on different properties of derivatives of interlock knitted fabric for different end-use applications. As the effect of derivative on properties is the aim of the present study, fiber type remains constant, i.e., cotton fiber. In this study, an attempt has been made to analyze the altogether physical, mechanical, serviceability, comfort, and dimensional stability properties with respect to stitch type, percentage, and location. Different derivatives of interlock structures with different percentages of knit, miss, and tuck stitches were chosen from the literature (Nawab, Hmadani, and Shakaer 2017). Interlock knitted structure has wide scope in industrial applications, protective textiles, medical textile, and sports suits due to balance structure.

Out of the total selected structures, in two structures (plain interlock and horizontal tabular), there is an equal percentage of knit and miss stitches; in five structures (interlock modified, half milano, cross miss, rodier, and cross relief), there are both miss stitches and knit stitches; and in the last four fabric structures (double tuck, pique, half cardigan, and vertical tubular), there is a combination of all three types of stitches, namely, knit, miss, and tuck stitches. So, this is an effective way to analyze the influence of stitches on the properties of the fabric structures. Analysis of variance (ANOVA) is used to analyze the significance of effect of structures on fabric properties. Furthermore, for the performance analysis of samples, a comprehensive evaluation of different properties based on principal component analysis (PCA) was done. Finally, the industrial uniform was designed according to stitch characteristics with best performance. All the samples were categorized in accordance with the prioritized responses by using PCA. The findings of this study shall work as a guide for researchers/manufacturers in the selection of structure for apparel or technical applications.

Materials and methods

Materials

A 100% combed cotton yarn of linear density 19.7 Tex (30s Ne) was taken from Zahid Je(Pvt) Ltd. Cotton is one of the most consumable natural fiber due to its natural appearance, comfort, and moisture absorbency properties. Tensile properties of yarn were tested on Uster® Tensorapd as per ASTM D 2256. The tensile force, elongations, and tenacity were determined. Tenacity of yarn is 14.16cN/tex, and elongation % is 3.77.

The following chemicals were used for scouring and bleaching:

• Sequestering agent: Lufibrol® ANTOX liq, CAS Number Not disclosed (ARCHROMA GmbH).It is phosphonic acid derivative anionic.

• Detergent: Felosan® RG-N, CAS Number 69011-36-5 (CHT Germany GmbH). It is the mixture of fatty alcohol oxylates.

• Hydrogen peroxide, sodium hydroxide (caustic soda), and sodium silicate.

Methods

Fabric manufacturing

A total of 11 samples were developed consisting of plain interlock and its 10 derivative structures. All the samples were developed on the interlock knitting machine FUKUHARA LDR-L (Japan). The interlock machine has 30-inch diameter and 20(E) gauge. The 0.30 ± 0.02 cm stitch length was set, and constant tension was maintained on machine. The tightness factor for all samples was kept 14.7 ± 0.1.

Scouring and bleaching

Wet processing comprised of scouring and bleaching (single stage) was done using laboratory model of soft flow machine named as “mini jet” dyeing machine. Samples were processed at 100°C. The recipe used for scouring/bleaching was: 3 g/L sodium hydroxide (caustic soda) (NaOH), 1 g/L detergent, 1 g/L sequestering agent, 4 g/L hydrogen peroxide (H₂O₂), and 1 g/L sodium silicate (Na₂SiO₃) as stabilizer. The fabric samples were end to end stitched and were run in bath containing the recipe for 1 h. After processing, the fabric was dried in air and relaxed for 48 h under standard atmospheric conditions.

Microscopic images

The microscopic images of all samples were taken using OPTIKA C-B10 microscope (Italy). OPTIKA C-B 10 microscope (via Rigla, 30 24010 Ponteranica BG-Italy, SN 536495) with an M-144 fixed microscope adaptor at 150×. The microscopic images were taken after wet processing. The loop design of all the samples was formulated on textile designing software named WISETEX software. The details of knitted fabric samples, i.e., structure their design repeat and microscopic images, are shown in Table 1.

Table 1. Structural representation and microscopic images of the developed samples..

Testing

All the testing procedures were performed after scouring/bleaching in wet relaxed state under standard atmospheric conditions as per standard ISO 139:2005.

Physical properties

To determine the mass per unit area (GSM (g/m²)), a fabric sample of 100 sq.cm was cut, and then GSM was determined according to the standard method ASTM D 3736. Thickness was measured according to ASTM D 1777. Courses and wales were counted using pick glass according to a lab-developed method.

Mechanical properties

Durability is an important parameter for high-performance apparel. Bursting strength and abrasion resistance are important properties to be evaluated. Serviceability of sample is also important w.r.t aesthetic and surface defect, which can be accessed by pilling resistance. The bursting strength of all developed knitted fabrics was determined by following the standard test method ASTM D 3786. The test was performed on instrument GATES LAB (Bursting Tester, GK-0(Germany); Jamshaid, Hussain, and Malik 2013). Pilling test of all samples was performed in accordance with standard method ISO 12945-1. Test was performed on the ICI pilling box model 3-P. The specimen size for pilling test is 10 cm² 3 specimens for each knitted fabric structure were tested and pilling was done on 18000 cycles. After that each specimen was analyzed for its grades by comparing with the pilling standard photographs. Rating between 1 and 5 is given to all samples (Jamshaid et al. 2021).

Abrasion resistance of fabrics was determined according to standard test method ISO 12947-2 by using Martindale abrasion tester (United Kingdom). A predetermined number of rubbing cycles was selected and entered the machine. The machine was stopped at each rubbing intervals of cycles to evaluate the fabric appearance till the samples were abraded.

Comfort properties

Comfort is related to three aspects namely, thermo-physiological, sensorial/tactile/hand, and psychological factors. Thermo-physiological comfort properties were also tested like AP of fabrics were tested on AP tester SDL ATLAS (M021A) instrument. The test sample was cut randomly from the fabric from wrinkle-free and spots-free areas of fabric, then the AP of test sample was determined according to the standard test method ASTM D 737. A pressure of 100 Pa was applied on 20 cm² of fabric at a temperature of 20 + 2°C and a relative humidity of 65. Moisture management was assessed according to the standard test method AATCC 195-2009 on moisture management tester CL/MMT/10-01. An average of three readings were taken. Thermal resistance (TR) of fabric was also tested using PERMEATEST (the Czech Republic) according to standard test method ISO 11092. Five readings were taken, and average was calculated. For each sample, five measurements were done, and the mean and standard deviation were calculated.

The fabric hand is associated with low-stress mechanical properties as investigated by previous studies (Vasile 2019). Compression, bending, roughness, and friction and primary sensory indices can be tested by Fabric touch tester (FTT; SDL ATLAS) by lab-developed method. For this research, the focus is on interlock structure for industrial applications, so two responses were selected from the whole set of data, i.e., compression average rigidity (CAR) and surface friction coefficient (SFC). While smoothness, softness, and relative hand value (RHV) were tested on Phabometer as per standard AATCC TM 202 (Jamshaid et al. 2021).

Dimensional stability

Fabric growth and stretch % (FG and FS) was tested in both directions, i.e., course wise and wale wise according to standard test method ASTM D 2594-99a. This test was performed on an instrument named Tensile strength tester, KG-300 (Japan). Sample dimension used for the test was 6“x 2”, and 1600 g weight was applied for the test.

The FG % and FS % were determined using the following formulas:

$FabricGrowth60sec\mathrm{\%}=100X\left(B-A\right)/A$

$FabricGrowth1hr\mathrm{\%}=100X\left(C-A\right)/A$

$FabricStretch\mathrm{\%}=100X(D-A)/A,$

where

A = Original length of the sample.

B = Length of sample after load was applied for 2 h and after 1 min of relaxation.

C = Length again after 1 h.

D = Length measured after the application of cyclic load.

Dimensional stability to washing was tested using Front load washing model FOM CLS 71 instruments (Electrolux) according to standard test method ASTM D 6207. The temperature for the test was set at 30°C.

Statistical analysis

The significance of results was analyzed by ANOVA using Minitab Statistical software package. Interaction plots were used to analyze the effect of different stitch types (knit, miss, and tuck %) on responses. PCA was done for multi-response optimization.

One-way ANOVA

One-way ANOVA was done to determine the significant effect of factors on different responses. It compares the means and elaborates that means are statistically significantly different from each other. p-Value is used to test the significance of null hypothesis in different statistical tools such as ANOVA. Null hypothesis explains that there is no correlation between the variables studied, which means that results are obtained accidentally as there is no significance of results with respect to the investigation. So, the p-value decides the credibility of the null hypothesis. Commonly p-value less than 0.05 is chosen to be significant by most researchers. So, if the significance value is too low, then we can easily reject the null hypothesis and declare that results are statistically significant suggesting that one variable has significant effect on the other variable. Interaction plots were used to interpret the interaction effect of different stitch types to determine whether the effect is statistically significant.

Principal Component Analysis (PCA)

PCA is very helpful technique for the classification and compression of data. It is used to reduce the dimensionality of a data set by generating new set of variables, which also retain the most of sample’s information. In this way data are summarized by means of smaller summary indices, hence it can be easily visualized and analyzed. The overview of PCA uncover the relationship between observations and variable. PCA is multivariate data analysis based on projection method. The PCA of the data was done in multiple steps as done by other researchers (Umair et al. 2017). In this study, PCA was performed to determine the best parameters for the samples subjected to the simultaneous optimization of multiple responses in the development of interlock derivatives for industrial uniforms.

Results and discussions

The results of all properties are given in Table 2. One-way ANOVA was used to analyze the significance of the results for all properties.

Table 2. Combined results of all properties.

Physical properties

Physical properties of fabric samples before and after scouring and bleaching are shown in Table 2. In Table 3, mass per unit area of the p-value is lower than 0.05, which demonstrates that results are statistically significant. The mass per unit area and thickness of all samples increased after scouring and bleaching, because during processing, knitted fabric tends to change its dimensional characteristics and shrinkage occurs which causes this change (Anand et al. 2002). All discussion-related results are done for washed/relaxed samples. It was observed that S4 has highest mass per unit area value among samples having knit and miss stitches. Knitted fabrics having stitches other than knit stitch normally have higher mass per unit area (Mishra et al. 2020). S4 sample has 58.33% miss stitches, so higher mass per unit area can be attributed to the presence of miss stitches which tends to narrower the sample. Also, location of stitch is an important parameter that can affect properties. Sample S7 has highest miss stitches, but due to the location of miss stitches, its mass per unit area is reduced. It can be observed that among the samples containing tuck stitches, S9 has highest mass per unit area value. This sample consists of 28% knit, 56% miss, and 16% tuck stitches. Combination of miss and tuck stitches increases the fabric mass per unit area, which is due to tuck stitches as in tuck stitch extra yarn is accumulated in loop which increase the areal density and thickness (Ince and Yildirim 2019). This was revealed by the previous studies that miss stitches or float stitches increase the thickness of fabric as the miss stitch yarn is not knitted and floated behind the knit or held loop, which increase the thickness. It was also mentioned that the presence of float stitches results in higher mass per unit area. Presence of tuck stitches also increase the thickness of fabric due to more yarn accumulation also result in increase in fabric mass per unit area (Assefa and Govindan 2020). The influence of different percentages of stitches are confirmed by the interaction plot of knit, miss & tuck stitches with reference to mass per unit area are shown in Figure 1(a) below. From the above Table 2 it is evident that sample having only miss stitches S7, S6, and S3 have the maximum thickness value this is because of presence of maximum number of miss/float stitches in fabric construction as in float stitches the floating yarn present on the back side and cumulate between the bilayers of fabric as a result increase the thickness value (Assefa and Govindan 2020). Sample S1 plain interlock has lowest thickness values among miss stitch combination due to alternate miss and knit stitch combination. S11 vertical tubular has lowest thickness among all stitch combinations. As it consists of hollow tubes and less yarn is used in the construction of structure as result minimum thickness is achieved. Vertical tubular also consist of lower percentage of tuck stitches as compared to miss and knit as a result low thickness.However usually tuck stitches increase the thickness (Uyanik and Topalbekiroglu 2017). S.8 has higher thickness value among the samples. This is due to the presence of higher percentage of tuck stitches in the sample, which is well known that the presence of tuck stitches increases the thickness value (Ahmed, Rahman, and Farha 2015). The significant effect of stitch type and percentage is acknowledged by the interaction plots for thickness shown in Figure 1(b).

Figure 1. Interaction plots of physical properties.

Table 3. ANOVA results of fabric properties.

Response/Property	R-Sq (%)	p-Value
GSM	70.99%	.001
Thickness	77%	.002
Bursting Strength	66.29	.000
Abrasion Resistance	100	.000
OMMC	80.19	.000
Air Permeability	99.44	.000
Thermal Resistance	62.77	.005
CAR	30.37	.96
CRR	49.06	2.12
SFCa	44.30	1.75
SFCe	24.76	.72
Softness Score	99.92	.00
Drape	99.77	.000
Fabric Growth %	99.34	.000
Fabric Stretch%	99.82	.000
Dimensional Stability (walewise)	100	.000

Stitch length for all samples were set constant on the machine, i.e., 0.3 cm. After scouring and bleaching, the change in stitch length was observed in various samples. Change of stitch length tends to vary the density of fabric, hence mass per unit area, courses per cm, and wales per cm were also changed. Due to this change in stitch length, different properties like bursting strength of fabric samples were affected. It can be seen that in S4, S5, S6, and S7, the stitch length decreased after wet processing. Other samples retain their stitch length. The reduction in stitch length of samples is due to shrinkage that occurs during the processing (Ziko 2015).

Mechanical properties

The ANOVA result regarding bursting strength shown in Table 3 depicts that p-value of bursting is lower than 0.05, which suggests that results of bursting strength are statistically significant. From the results of bursting strength shown in Table 2, it can be seen that S11 has minimum bursting strength, which is due to the presence of tuck stitches that tend to decrease the bursting strength (Sitotaw 2017). S1 plain interlock structure has relatively high bursting strength among the samples due to its high elongation nature. It is also found by the previous researchers that plain structures have high bursting strength and structure with the presence of high percentage of tuck stitches results in lower bursting strength (Rassel 2019). In S9, due to higher mass per unit area, it has higher bursting strength. This is in accordance with the previous work (Jamshaid, Hussain, and Malik 2013). The strong interaction between the stitch types, percentages, and bursting strength are shown in Figure 2(a). The non-parallel lines in the plots confirmed the significant interaction.

Figure 2. Interaction plots for mechanical properties.

The results in Table 2 show the pilling grade of all samples. The photographic images of all samples after pilling test are shown in Figure 3. Higher pilling grades means high pill resistance and show less pilling. It was observed that S11 vertical tubular knitted structure has maximum pilling resistance, which can be due to the presence of vertical tubes that restrained the loops from moving, which leads to increase in pilling grade. Samples S8, S9, and S10 have higher pilling grade due to the presence of tuck stitches because increasing the percentage of tuck stitches increases the resistance to pilling (Ahmed, Rahman, and Farha 2015). The interaction between the stitch types, percentages, and pilling resistance are shown in Figure 2(b).

Figure 3. Photographic images after pilling.

It can be seen from Table 2 that the abrasion resistance was higher in S1 and S3 due to the location of the stitches. It helps to prevent the pull out of the fibers from the yarn. S11 vertical tubular has minimum values of abrasion resistance due to its rough surface, more fiber wear-off occurred.

Comfort properties

Thermo-physiological

Table 2 shows the thermo-physiological properties, i.e., AP, overall moisture management capacity (OMMC), and TR of all samples. The results of AP show that S8 interlock double tuck has the highest AP. The S8 consists of knit, miss, and tuck stitches. The higher permeability to air of the sample can be owing to the presence of tuck stitches as tuck stitches increase the porosity of structure which facilitates the air transportation and ultimately increase the AP. Tuck stitch is composed of held loop, which increase the porosity than the normal knit stitch. This is also manifested by the previous researchers (Abd El-Hady 2016). AP of the fabrics is mainly determined by the pore size so knit and tuck stitches allow greater porosity and pore size.

Although S9 sample has high percentage of tuck stitches, but due to high mass per unit area it has lowest AP. Due to the location of miss stitches, pores were not formulated, resulting in lowering the AP. This is in accordance with the previous research (Yang et al. 2020). Significant relationship between different types of stitches on the AP is shown in interaction plots in Figure 4(a).

Figure 4. Interaction plots of thermo-physiological comfort properties.

The 0.00 p-value of OMMC in Table 3 proved the significance of the results. It is OMMC, which is an index that ranges from 0 to 1. The higher the index, the better the performance (Karthikeyan et al. 2017). Previously investigated by the researchers, it is suggested that wetting time of fabrics is related to the absorbency of fabric. Moisture management and water permeability values were affected by the thickness and compactness of the fabric (Mansor, Ghani, and Yahya 2016). Moisture management properties of fabrics decrease as the mass of fabric increase (Selli and Turhan 2017). As in this work same raw material cotton fiber is used in the composition of all fabric samples. So difference in moisture management properties is due to the difference in knitted structure and structure parameters (Achour et al. 2015). Resistance to flow is less from fabric if absorption and spreading of water on the fabric increases.

S6 rodier has maximum value of OMMC, while S7 interlock cross relief has minimum value of OMMC. These both samples consist of knit and miss stitches in which the miss stitch percentage is higher than knit stitches. So, the difference in OMMC values can be explained on the basis of location of stitches. As in S7 sample, miss stitches number on cylinder track is more, which reduced the absorbency of sample, leading to decrease in OMMC value. While in case of S6, better absorbency may be the reason as liquid dispersion in fibrous material is facilitated by interconnected pores that are small and uniformly distributed (Behera and Mishra 2007).

Presence of tuck stitches in interlock pique structure results in enhancement of OMMC because the tuck stitches result in better absorbency because of capillary action and capillary tunnel created in inter-yarn spaces in structures.

Structures with miss stitches have lower OMMC value. It is in accordance with the previous research that knitted structures containing high percentage of float stitches have lower values of OMMC as compared to structures with knit stitch percentage (Öner and Okur 2013).

The significance of the TR results can be seen from ANOVA from Table 3. The p-value of the TR is lower than 0.05. Significant relationship between TR and different stitches can be seen in the interaction plot shown in Figure 4(c). TR properties of fabric are influenced by microscopic, mesoscopic, and macroscopic porosity (Ozkan and Kaplangiray 2020). TR or heat transfer properties of knitted fabrics are greatly influenced by the sequence of stitches in the design repeat knitted fabric construction as it determines the amount of air present in the structure (Bivainytė and Mikučionienė 2012).

It was found that S9 has highest TR. It is because of the thicker sample due to the higher number of tuck stitches. As thicker fabrics have higher TR, AP value of S9 is low as compared to other samples. It is also general trend that fabric having lower AP has high TR as the sample has better insulating property. Thermal properties of fabrics are highly influenced by the thickness of the samples (Oner 2019). As the thickness of fabric samples increases, it becomes difficult for the heat to pass through the fabric layer as a result TR values increases. S8 sample has second highest value due to higher number of tuck stitches. Sample consisting of high percentage of miss stitches decreases the thickness and can be seen in S2 and S3 (Ziaei et al. 2018). S5 horizontal tubular has better TR value with sample consisting of 50% knit and 50% miss stitches. Horizontal tubular structure tends to form air pockets in which air is entrapped as insulating medium causes higher TR (Basra et al. 2020).

Tactile comfort properties

The selected responses were CAR, which demonstrates the forces needed to compress per mm, and compression recovery rate (CRR), which illustrates the percentage of thickness changes after compressed. The results of FTT are shown in Table 2. The other response selected was SFC instead of roughness because roughness accounts for the softness, while friction is given by rubbing against metal, which is more related to the industrial application (Vasile et al. 2019). It was observed that difference in structure of knitted fabrics does not affect the compression and friction properties of fabric which is in accordance with the previous research (Balci and Okur 2019). Fabric structure does not have significant effect on the fabric touch properties which is manifested from the higher p-value as shown in Table 3. Compression properties are independent of loop length, density, and knitted structure as mentioned in previous studies (Anwar et al. 1997).

Other properties like softness and drape were also studied as shown in Table 2. Tactile comfort of fabrics mainly depends on the characteristics of yarn or fiber used in the fabric. The modulus, density, and structure of the fiber and yarn play important role in the tactile comfort (Kim and Kim 2018). S1 plain interlock was set as control sample, and all other samples were compared with it.

Results of tactile properties showed that S9 shows the highest RHV, i.e., 14.38, while S3 and S5 showed lowest RHV value 3.37 and 3.39, respectively. This was because of the fact that S9 sample was heavy and stable, so this sample has higher RHV as compared to all others. Fabric with tuck stitches showed higher value of relative hand. Location of stitches is an important factor w.r.t fabric surface. S3 and S5 have low RHV value due to rough surface (cords) so indented fabric (Uyanik and Topalbekiroglu 2017).

S7 shows highest value of softness, i.e., 77.89, and S9 showed the lowest value 56.13. In case of smoothness score, S6 interlock rodier showed the highest value 69.2, and S9 interlock pique and S11 vertical tubular showed lowest values 57.94 and 59.78, respectively. The high softness and smoothness values of S7 (Interlock cross relief) and S.6 (Interlock rodier) are due to higher percentage of successive miss stitches which is commonly present in both structures. Whereas the lower values of smoothness and softness as depicted by S9 (interlock pique) and S11 (interlock vertical tubular), respectively, are because of the presence of tuck stitches in both structures, which result in assembling of yarn at some specific spots within the structure. S10 interlock half cardigan showed highest resilience score 59.14, and S11 interlock vertical tubular showed lowest resilience value 37.72. It is affirmed from the results of ANOVA, as shown in Table 3, that results of softness and drape properties are statistically significant. The significant interaction between stitch types and their percentage and tactile comfort properties are shown in Figure 5(a–d).

Figure 5. Interaction plots of tactile comfort properties.

Dimensional stability

Fabric growth and stretch (%)

The experiment was performed in both directions, course wise and wale wise. From Table 2, it is evident that there is major change of dimension in course wise direction. Low-density knitted fabrics can be easily distorted upon application of force. FS properties were analyzed by former researchers, and it was concluded that mass per unit area and stitch length are dominant factors affecting the stretch properties (Tamanna et al. 2017). FS properties in course wise direction are significant, which is revealed from the higher p-value shown in Table 3.

The results of FS depicts that sample S5, which has 50% knit and 50% miss stitches, has maximum stretch percentage in both directions. As samples have equal percentage of knit and miss stitches in which float yarn is involved which has less extensibility than knit stitch. S5 has maximum percentage of knit stitches. Moreover, S1 (plain interlock) containing 50% knit and 50% miss stitches has higher stretch percentage in course direction but not in wales direction. This minimum stretch is because of the location of stitches, i.e., knit and miss stitches in plain interlock are present in alternative positions, which result in the formation of compact structure with better recovery.

The results of fabrics growth percentage as shown in Table 2 reveals that S7 containing 31.5% knit and 69% miss stitches has maximum growth percentage in course wise direction and minimum in wale wise direction. Due to the presence of more miss stitches, dimensional stability is affected. It is noteworthy that tuck stitches improve the stability of the knit fabrics, so in this case, the absence of tuck stitches result in a decrease in recovery (Bouagga and Sakli 2021). The effects of the stitch type and percentage on the FS and growth properties are shown in interaction plots in Figure 6(a–d).

Figure 6. Interaction plots of dimensional properties.

Dimensional stability to washing

The results of dimensional stability are statistically significant as demonstrated from the lower p- value shown in Table 3. The p-value of dimensional stability to washing is 0.00. Interlock structure among all weft knitted structure has comparably higher dimensional stability. Laundering influence the dimensional stability of knitted fabrics, and it has high dependency on loop shape factor and stitch type. Distortion of knitted structure occurs differently in course wise and length wise (Anand et al. 2002). In previous studies regarding dimensional stability to laundering, all types of knitted fabric shrank in different percentages less than 10%. Dimensional stability depends on raw material/fiber type and construction/geometrical parameters (Fletcher and Roberts 1952). In S3, S4, and S10, there was no shrinkage in course wise direction, while minimum shrinkage occurred in wale wise direction in S10. Presence of tuck stitches minimizes the shrinkage (Higging et al. 2003). This can be explained on the basic of location of stitches, as due to zigzag pattern as shown in Table 1, yarn becomes tight in loops, so shrinkage reduced (Mishra et al. 2020). The interaction plot shown in Figure 6(f) reveals that different stitch types do not have significant effect on the fabric shrinkage in course wise direction.

Principal Component Analysis (PCA)

The multi-response optimization of 11 responses were computed by PCA. In the first step, signal-to-noise ratio (S/N) is computed as per standard method and shown in Table 4.

Table 4. Signal-to-noise (S/N) ratios of the responses.

Factor	Responses
Sample code	Bursting strength (KPa))	Pilling resistance (grade)	Abrasion resistance (cycle)	OMMC	AP(mm/s)	TR(m2K/W)	Shrinkage (%)	FG (%)	FS (%)	Softness	Drape
S.1	49.8104441	2.55333333	89.54242509	−10.17283146	49.69620851	−37.91509326	25	0.403333333	−11.92674252	37.04953134	−4.034849628
S.2	47.72749436	2.86333333	89.54242509	−13.33847781	49.77955327	−33.96593285	4	0.640066667	8.062274724	37.26485994	−1.939557572
S.3	48.98114809	16.27	89.54242509	−12.62946391	53.68410459	−38.41637508	25	1.538466667	0.117849736	36.90898473	1.860976492
S.4	49.4057214	16	93.97940009	−12.43100877	53.30535069	−38.19676587	25	1.5961	1.96004801	36.68490248	2.029628326
S.5	5.15850867	2.55333333	93.06425028	−8.559956455	54.27402246	−37.40123886	4	0.575197667	8.118864425	36.78075583	−2.405728872
S.6	48.25053614	16.27	87.95880017	−7.515498398	51.52787876	−35.8915502	43.56	0.563581333	6.152559073	36.78033542	−2.492924581
S.7	51.13986503	16.54666667	92.04119983	−6.5669134	55.17613217	−38.52294577	56.25	0.062514	8.027463684	37.83408824	−12.04414118
S.8	5.88952926	2.55333333	92.04119983	−11.95157265	55.88176319	−36.63443721	6.25	0.2535	6.13377922	37.11431344	−5.970789915
S.9	49.28696998	2.25	87.95880017	−16.58954418	44.92301307	−39.24432766	25	0.5535	2.000190358	34.98077694	−2.599714195
S.10	35.06236379	2.86333333	93.97940009	−12.41196969	53.73397148	−37.224511	25	0.534781333	6.938240438	36.58857009	−2.748330384
S.11	4.55033784	25	84.08239965	−8.258626915	5.83672701	−38.5306697	4	0.6347	−2.400279496	37.20537239	−1.97492582

For comparison purposes, normalized signal-to-noise ratios were computed depending on the quality characteristics, i.e., the higher the better, the lower the better or the more nominal the better. Among 11 quality characteristics the category higher the better required, were chosen for OMMC, AP, TR, bursting strength, abrasion resistance, pilling resistance, softness and drape. While other category where, lower the better value required, were taken shrinkage%, FG %, FS %. Normalized signal-to-noise ratios are given in Table 5. The order of the multi-response performance index (MRPI) is also given in Table 5.

Table 5. Normalized S/N ratios and MRPI values.

Factor	Responses
Sample code	Bursting strength (KPa)	Pilling resistance (grade)	Abrasion resistance (cycle)	OMMC	AP(mm/s)	TR(m2K/W)	Shrinkage (%)	FG (%)	FS (%)	Softness	Drape	MRPI Values	Rank
S.1	0.91731172	0.494074074	0.551684874	0.640222398	0.435560203	0.251825497	0.598086124	0.777763143	0	0.725036347	0.569093557	0.9330	8
S.2	0.787754911	0.45962963	0.551684874	0.324372556	0.44316552	0	1	0.623397275	0.997176952	0.80050256	0.717972794	0.9487	7
S.3	0.865730569	0.97	0.551684874	0.395113854	0.799460834	0.156856887	0.598086124	0.037580764	0.600859445	0.675778977	0.988016584	0.8533	9
S.4	0.892138486	1	1	0.414914557	0.764899055	0.198462189	0.598086124	0	0.692759794	0.597244871	1	0.9492	6
S.5	0.93896089	0.494074074	0.907532609	0.801145717	0.853291597	0.349176003	1	0.665696174	1	0.630838595	0.684849379	1.3087	4
S.6	0.820287441	0.97	0.39167428	0.905355688	0.602702463	0.635188837	0.242870813	0.673270796	0.901908415	0.630691254	0.67865376	1.4207	2
S.7	1	0.939259259	0.80416286	1	0.935610265	0.136666906	0	1	0.995440361	1	0	2.2548	1
S.8	0.984429435	0.494074074	0.80416286	0.462749914	1	0.494447751	0.956937799	0.875464434	0.900971559	0.747740528	0.431536928	1.4196	3
S.9	0.884752299	0.527777778	0.39167428	0	0	0	0.598086124	0.679844495	0.694762345	0	0.671065913	0.2495	11
S.10	0	0.45962963	1	0.416814166	0.804011252	0.382657366	0.598086124	0.69205031	0.941103106	0.563483259	0.660506113	1.1090	5
S.11	0.341344962	0	0	0.831210632	0.539633979	0.135203596	1	0.626896698	0.47523944	0.779653959	0.715459732	0.6587	10

Conclusions

This study was mainly focused on effect of stitch type, percentage of stitch, and their location on interlock knitted fabric on different properties of interlock structure and its derivatives. The findings of this study will be helpful in future for various industrial and protective applications while keeping in view the characteristics of interlock structures. This study utilized a PCA for the simultaneous optimization of properties for industrial uniform. The simultaneous optimization suggested that S7 cross miss sample was ranked as best sample, while S6 interlock pique and S8 double tuck were ranked as 2nd and 3rd, respectively. Different knitted structures based on different properties can be beneficial for different end applications. S1 plain interlock knitted fabric can be used as lining materials for coats, jackets, evening dress, and lingerie due to its highest mechanical properties, high softness, smoothness, and drape along with moderate thermo-physiological properties. The Sample S6 Rodier structure exhibit high bursting strength, highest OMMC value with high abrasion resistance along with good smoothness properties can be preferably utilized for the active sportswear like athletics, cycling, football and swimming (Venkatraman 2013). AP is very important property with respect to comfort especially for active wear. So S8 interlock double tuck sample has good softness, OMMC, elasticity, and highest AP can be used for active wear (Karthik, Senthilkumar, and Murugan 2018). Knitted fabrics with interlock pique structure S9, is favorable to be used in automotive seat cushioning owing to the better pilling resistance, abrasion resistance, and moisture management. Knitted structure cross miss S4 provides better dimensional stability and softness properties, along with moderate AP, making it good to use for medical applications like medical dressings (Zhang and Ma 2018). Fabric structures like S10 half cardigan and S5 horizontal tubular having higher elasticity and comfort properties and can be used in sleepwear. This study will be beneficial for the selection of appropriate interlock fabric structure for the desired end applications. It was concluded from the study that manufacturermanufacturerss can manage properties by using different combinations of stitches, percentage, and location. In the future, more research is necessary to further investigate the properties by changing the fiber type.

Highlights

• Eleven interlock derivative structures were developed to analyze the effect of different stitch types, their location and percentage (%) on the physical, mechanical, thermo-physiological comfort, tactile comfort, and dimensional properties.

• From testing results and statistical technique, i.e., ANOVA, it was concluded that the effect of structure is significant on properties.

• From multi-response optimization technique, i.e., PCA, it was concluded that cross miss structure was ranked as best sample while Interlock pique and double tuck were ranked as 2nd and 3rd, respectively, for application as industrial uniform.

• This research will guide researchers/manufacturers to develop different knitted structures based on required properties according to application area.

Disclosure statement

No potential conflict of interest was reported by the author(s).