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The purpose of the study is to optimize the blending ratio of Arecanut and cotton fibers to create yarn with the best quality for various applications, particularly home furnishings. The study aims to determine the effect of different blend ratios on the physical and mechanical properties of the yarn.

The study involves blending Arecanut and cotton fibers in various ratios (90:10, 75:25, 50:50, 25:75 and 10:90) at two different yarn counts (10/1 and 5/1). Various physical and mechanical properties of the blended yarn are analyzed, including unevenness, coefficient of mass variation (cvm%), imperfection, hairiness, breaking strength, elongation, tenacity and breaking work.

The research findings suggest that the blend ratio of 10:90 (10% cotton and 90% Arecanut fiber) produced the best results in terms of physical and mechanical properties for both yarn counts. This blend ratio resulted in reduced unevenness, cvm% and imperfection, while also exhibiting good mechanical properties such as breaking strength, elongation, tenacity and breaking work. The blend with a higher concentration of cotton generally showed better properties due to the coarseness of Arecanut fiber. As the goal of the study was to determine the best blend ratio that included the most Arecanut fiber based on its physical and mechanical properties, which is suitable for home furnishing applications, 75:25 Areca cotton blend ratio of yarn count 5/1 proved to be the best.

The study acknowledges that Arecanut fiber must be blended with other commercially used fibers like cotton due to its coarseness. While the study provides insights into optimizing blend ratios for home furnishings and packaging, further research may be needed to make the material suitable for clothing applications.

The research has practical implications for industries interested in utilizing Arecanut and cotton blends for various applications, such as home furnishings and packaging materials. It suggests that specific blend ratios can result in yarn with desirable properties for these purposes.

The study mentions that the increased use of Arecanut fibers can benefit the growers of Arecanut, potentially providing economic opportunities for communities engaged in Arecanut farming.

The research explores the utilization of Arecanut fibers, an underutilized resource, in combination with cotton to create sustainable yarn. It assesses various blend ratios and their impact on yarn properties, contributing to the understanding of eco-friendly textile materials.

Cotton fibre lots are graded and selected for yarn spinning based on their quality value which is a function of certain fibre properties. Cotton grading and selection has created a domain of emerging interest among the researchers. Several researchers have addressed the said issue using a few exponents of multi-criteria decision-making (MCDM) technique. The purpose of this study is to demonstrate a cotton selection problem using a recently developed measurement of alternatives and ranking according to compromise solution (MARCOS) method which can handle almost any decision problem involving a finite number of alternatives and multiple conflicting decision criteria.

The MARCOS method of the MCDM technique was deployed in this study to rank 17 cotton fibre lots based on their quality values. Six apposite fibre properties, namely, fibre bundle strength, elongation, fineness, upper half mean length, uniformity index and short fibre content are considered as the six decision criteria assigning weights previously determined by an earlier researcher using analytic hierarchy process.

Among the 17 alternatives, C9 secured rank 1 (the best lot) with the highest utility function (0.704) and C7 occupied rank 17 (the worst lot) with the lowest utility function (0.596). Ranking given by MARCOS method showed high degree of congruence with the earlier approaches, as evidenced by high rank correlation coefficients (Rs > 0.814). During sensitivity analyses, no occurrence of rank reversal is observed. The correlations between the quality value-based ranking and the yarn tenacity-based rankings are better than many of the traditional methods. The results can be improved further by adopting other efficient method of weighting the criteria.

The properties of raw cotton have significant impact on the quality of final yarn. Compared to the traditional methods, MCDM is reported as the most viable solution in which fibre parameters are given their due importance while formulating a single index known as quality value. The present study demonstrates the application of a recently developed exponent of MCDM in the name of MARCOS for the first time to address a cotton fibre selection problem for textile spinning mills. The same approach can also be extended to solve other decision problems of the textile industry, in general.

Novelty of the present study lies in the fact that the MARCOS is a very recently developed MCDM method, and this is a maiden application of the MARCOS method in the domain of textile, in general, and cotton industry, in particular. The approach is very simple, highly effective and quite flexible in terms of number of alternatives and decision criteria, although highly robust and stable.

This paper aims to investigate the influence of picking sequence, weave design and weft yarn material on the thermal conductivity of the woven fabrics.

This work includes the development of 36 woven samples with two weave designs (1/1 plain and 3/1 twill), three picking sequences (single, double and three pick insertion) and six different weft yarn materials (cotton, polyester having 48 filaments, polyester with 144 filaments, spun coolmax having Lycra in core and coolmax in sheath, filament coolmax and polypropylene). The thermal conductivity was measured using ALAMBETA tester.

The results showed that weft yarn material, weave design and picking sequence have a meaningful impact on the thermal conductivity of woven fabric. The value of thermal conductivity was lowest for the fabrics with three pick insertion and 3/1 twill weave in all weft yarn materials.

Plain woven fabric with single pick insertion is feasible for summer wear to enhance the comfort of wearer. By changing the warp yarn grouping and material, improved thermal conductivity/resistance can also be achieved.

The authors have studied the combined effect of different weft yarn materials with different picking sequences and different weave designs on thermal conductivity of the woven fabrics.

Nowadays, textiles play a striking role in various medical applications. Compression bandages are the most essential medical fabrics that help treat venous flow and edema. This study aims to investigate the characteristics of different woven compressive bandage structures produced using compact cotton and cotton/lycra.

Four samples were weaved by matt-plain2/2, twill2/2, stripe-stain4 and mock-leno structures. Several properties were tested that related to structural performance. Tensile strength, elastic and sub-bandage pressure are considered the main functional properties. Three different analysis tools were performed: chart-diagram, one-factor ANOVA and radar chart area.

The woven structures critically affected the performance of woven compression bandage samples as well as their classifications.

The woven structures critically affected the performance of woven compression bandage samples as well as their classifications.

This paper aims to determine the most practically applicable color-difference formula for yarn-dyed fabrics woven from warp and weft yarns in different color depths and to establish color-difference tolerance for perceptibility by evaluating yarn-dyed fabrics visually and instrumentally.

A total of 108 sample pairs were evaluated by a panel of 13 observers with perceptibility method under three typical light sources (A, D65 and cool white fluorescent). The data sets were statistically analyzed by the homogeneity of variance test (F-test), analysis of variance, standardized residual sum of squares and performance factor/3.

Light sources had a slight influence on the visual assessments of yarn-dyed fabrics. Among the eight color-difference formulae for measurements of yarn-dyed fabrics, CIEDE2000(2:1:1) outperformed all other tested formulae, and the color tolerance for the perceptibility of CIEDE2000(2:1:1) was 0.62. When the homochromy index (K) of warp and weft yarns of yarn-dyed fabric was lower than 1.25, the color difference based on ΔE*00(2:1:1) between the two samples was acceptable in terms of the color tolerance for perceptibility (i.e. 0.62).

The warp and weft yarns in different color depths could be woven in fabric with a relatively uniform color appearance.

This study could contribute to cost savings by reusing disqualified dyed yarns during the weaving manufacturing process.

The heat transfer properties play significant roles in the thermal comfort of the clothing products. The purpose of this paper is to find the relationship between heat transfer properties and fabrics' structure, yarn properties and predict the effective thermal conductivity of single layer woven fabrics by a parametric mathematical model.

First, the weave unit was divided into four types of element regions, including yarn overlap regions, yarn crossing regions, yarn floating regions and pore regions. Second, the number and area proportion of each region were calculated respectively. Some formulas were created to calculate the effective thermal conductivity of each element region based on serial model, parallel model or series–parallel mixing model. Finally, according to the number and area proportion of each region in weave unit, the formulas were established to calculate the fabric overall effective thermal conductivity in thickness direction based on the parallel models.

The influences of yarn spacing, yarn width, fabric thickness, the compressing coefficients of air layers and weave type on the effective thermal conductivity were further discussed respectively. In this model, the relationships between the effective thermal conductivity and each parameter are some polynomial fitting curves with different orders. Weave type affects the change of effective thermal conductivity mainly through the numbers of different elements and their area ratios.

In this model, the formulas were created respectively to calculate the effective thermal conductivity of each element region and whole weave unit. The serial–parallel mixing characteristics of yarn and surrounding air are considered, as well as the compression coefficients of air layers. The results of this study can be further applied to the optimal design of mixture fabrics with different warp and filling yarn densities or different yarn thermal properties.

Through this study, four different types of woven fabric structures were created by using cotton/banana blends with a 70:30 ratio by varying the weaving specifications. This study aims to investigate the comfort and mechanical properties of these woven materials.

Taguchi L16 experimental design (5 factors and 4 levels) with response surface methodology tool was used to optimize mechanical and comfort characteristics. The yarn samples used in this study are cotton/banana with a blend ratio of 70:30. Fabric type (A), grams per square metre (GSM; B), yarn count (C), fabric thickness (D) and cloth cover factor (E) are the chosen process characteristics.

The highest tensile strength and tearing strength of the cotton/banana blended fabric samples were obtained as 326.3 N and 90.3 k.gf/cm, respectively. Similarly, the highest thermal conductivity and overall moisture management capacity values were found to be 0.6628 and 3.06 W/mK X10⁻⁴, respectively. The optimized process parameters for obtaining maximum mechanical properties were using canvas fabric structure, 182 GSM, 36^s Ne yarn count, 0.48 mm fabric thickness and 23.5 cloth cover factor. Similarly, the optimized process parameters for obtaining maximum comfort properties were achieved using a twill fabric structure, 182 GSM, 32^s Ne yarn count, 0.4 mm fabric thickness and 23 cloth cover factor.

In contrast to synthetic fabrics, banana fibre and its blended materials are significant ecological solutions for apparel and functional clothing. Products made from banana fibre are a sustainable and green alternative to conventional fabrics. Banana fibre obtained from the pseudostem of the plant has an appearance similar to ramie and bamboo fibres. Numerous studies showed that banana fibre could absorb significant moisture and be spun into yarn through ring and rotor spinning technology. On the other hand, this fibre can be easily combined with cotton, jute, wool and synthetic fibre. The present utilization of pseudostem of banana plant fibre is very minimal. This type of research improves the usability of bananas their blended fabrics as apparel and functional wear.

The textile industry contributes 2 and 3% to the global and Indian Gross Domestic Product (GDP), respectively. India supplies a quarter of global cotton yarn. Yet, most yarn manufacturing companies use outdated methods and lack organisational skills and strategies. Improvement in processes in India could significantly help the industry worldwide.

The variables that influence the performance of the system were identified. Their interrelationships and impact were identified from the employees in the chosen case study, a yarn manufacturing industry. A System Dynamics (SD) approach was employed to study the benefits of implementing 5S lean strategies. The impact of each variable on various performance measures such as throughput, Work In Progress, processing time, waiting time, idle time, over-processing and scraps was analysed.

Improvement in outcomes reflected an enhanced adoption of leanness in the industry. The decision-makers can utilise this study to optimise the necessary parameters in the system and attain the desired productivity levels. Better resource management and reduced processing time helped increase the despatch rate by 9.735% and decrease the WIP by 23.01%. Time management helped to reduce the inventory, idle time and waiting time. Over-processing, defects and scraps were minimised, indicating a shift towards lean.

This study pioneers the use of SD simulation models for optimising yarn manufacturing using lean strategies. Improvement in performance measures by integrating these strategies opens avenues for future research using multiple approaches to address a problem.

Implementing 5S lean principles and simulations enhances productivity, reduces waste and optimises resource management for the yarn manufacturing industry. Decision-makers can employ simulation to witness the outcomes of their changes without investing cost and time and without associated implementation risks.

The use of a simulation model to witness the benefits of incorporating lean strategies in yarn production has not been explored. This approach could help the managers and policymakers understand their existing system's shortcomings and critical areas that require improvement.

The purpose of this study is to investigate the mechanical properties of denim fabrics constructed from ring-spun and open-end rotor spun yarns.

Yarns of 10s Ne count using cotton fibers were spun using the ring and open-end rotor spinning technologies. The yarns were used to produce a denim fabric on an air-jet loom with a 3/1 twill weave structure. Mechanical tests – tensile strength, tear strength, abrasion resistance and pilling resistance – of denim fabrics were evaluated. The test results were analyzed using analysis of variance with the help of Software Package for Social Sciences.

Denim fabrics made by using ring-spun yarns exhibited better tensile and tear strength properties than denim fabrics made by using open-end rotor spun yarns. On the contrary, denim produced using open-end rotor yarns have better abrasion resistance, pilling resistance and air permeability than those produced using ring-spun yarns.

Both spinning techniques have a significant influence on the properties of denim fabrics. Whenever better tensile and tear strength is required, it is better to use ring-spun yarns, while if the requirement is better abrasion resistance and pilling resistance with high air permeability, then open-end rotor spun yarns shall be used.

The essential properties of active sports fabrics are moisture management, quick-drying, body heat management and thermal regulations. Fibre type, blending nature, yarn and fabric structure and the finishing treatment are the key parameters that influenced the performance of the clothing meant for sportswear. This study aims to investigate the effect of fibre blending and structural tightness factors on bi-layer sport fabric's dimensional, moisture management and thermal properties.

In this study, 12 different bi-layer inter-lock fabrics were produced. Polyester filament (120 Denier) yarn was fed to form the backside of the fabric, and the face side was varied with cotton, modal, wool and soya spun yarns of 30sNe. Three different types of structural tightness factors were considered, such as low, medium and high were taken for sample development. The assessment towards dimensional, moisture management and thermal properties was carried out on all the samples.

The polyester-modal blend with a high tightness factor has shown maximum overall moisture management capability (OMMC) values of 0.73 and air permeability of 205.3 cm³/cm²/s. The same sample has shown comparatively higher thermal conductivity of 61.72 × 10^–3 W m^-1 °C^-1(Under compression state) and 58.45 × 10^–3 W m^-1 °C^-1 (under recovery state). In the case of surface roughness is concerned, polyester-modal blends have shown the lowest surface roughness, surface roughness amplitude and surface friction co-efficient. Among the selected fibre combinations, the overall comfort level of polyester-modal bi-layer knitted structure with a higher tightness factor is appreciable. Polyester-modal is more suitable for active sportswear among the four fiber blend combinations.

The outcome of this study will help to gain a better understanding of fibre blends, structural tightness factor and other process specifications for the development of bi-layer fabric for active sportswear applications. The dynamic functional testing methods (Moisture management and Thermal properties) were carried out to simulate the actual wearing environment of the sports clothing. This study will create a new scope of research opportunities in the field of bi-layer sports textiles.

This study was conducted to explore the influence of fibre blend and structural tightness factor on the comfort level of sportswear and to find the suitable fibre blend for active sportswear clothing.