Meenakshi Ahirwar and Bijoya Kumar Behera
Denim fabric has become a wardrobe staple due to its versatility to be worn in a variety of fashions. This paper aims to study denim fabrics to understand their unique hand by…
Abstract
Purpose
Denim fabric has become a wardrobe staple due to its versatility to be worn in a variety of fashions. This paper aims to study denim fabrics to understand their unique hand by developing a hand evaluation system using computational method. Also, the effect of various washes was studied on the hand and surface morphology of denim fabrics.
Design/methodology/approach
Five different denim samples were manufactured with various washing treatments. The Kawabata Evaluation System was used to measure the low stress mechanical properties. Computation method was used to develop hand equations using multiple regression technique in the MS Excel software. The correlation coefficient analysis was done to determine the authenticity of the developed equations. Five primary hand attributes such as softness, smoothness, fullness, flexibility and stretchability were shortlisted by a panel of judges that influence the fabric handle.
Findings
The correlation coefficient between subjective and computational total hand values with thermal properties and without thermal properties was 0.88 and 0.85, respectively. The enzymatic wash fabric has the highest total hand value followed by the acid, bleach and stone-washed fabrics.
Originality/value
Although the hand evaluation system is available for conventional textiles like suiting and shirting fabrics, the method to predict fabric hand of non-conventional textiles such as denim fabrics remains an unexplored topic. The stresses acting on denim fabrics are completely different. Therefore, to the best of the author’s knowledge, a novel attempt has been made in this research work to develop a computational model to predict the total hand value of denim fabrics.
Details
Keywords
Md Samsu Alam, Abhijit Majumdar and Anindya Ghosh
Bending and shear rigidities of woven fabrics depend on fibre, yarn and fabric-related parameters. However, there is lack of research efforts to understand how bending and shear…
Abstract
Purpose
Bending and shear rigidities of woven fabrics depend on fibre, yarn and fabric-related parameters. However, there is lack of research efforts to understand how bending and shear rigidities change in woven fabrics having similar areal density. The purpose of this paper is to investigate the change in bending and shear rigidities in plain woven fabrics having similar areal density.
Design/methodology/approach
A total of 18 fabrics were woven (9 each for 100 per cent cotton and 100 per cent polyester) keeping the areal density same. Yarns of 20, 30 and 40 Ne were used in warp and weft wise directions and fabric sett was adjusted to attain the desired areal density.
Findings
When warp yarns become finer, keeping weft yarns same, bending rigidity remains unchanged but shear rigidity increases in warp wise direction. When weft yarns are made finer, keeping the warp yarns same, both the bending and shear rigidities of fabric increase in warp wise direction. Similar results for fabric bending and shear rigidities were obtained in transpose direction. There is a strong association between fabric shear rigidity and number of interlacement points per unit area of fabric even when fabric areal density is same.
Originality/value
Very limited research has been reported on the low-stress mechanical properties of woven fabrics having similar areal density. A novel attempt has been made in this research work to investigate the bending and shear rigidities of woven fabrics having similar areal density. Besides, it has been shown that it is possible to design a set of woven fabrics having similar bending rigidity but different shear rigidity.
Details
Keywords
The purpose of this paper is to investigate an alternative approach that can predict non‐linear relations.
Abstract
Purpose
The purpose of this paper is to investigate an alternative approach that can predict non‐linear relations.
Design/methodology/approach
An engineered approach to fabric development is described in which a radial basis function network is trained with worsted fabric constructional parameters to predict functional and aesthetic properties of fabrics. An objective method of fabric appearance evaluation with the help of digital image processing is introduced. The prediction of fabric properties by the network with changing basic fibre characteristics and fabric constructional parameters is found to have good correlation with the experimental values of fabric functional and aesthetic properties.
Findings
The radial basis function network can successfully predict the fabric functional and aesthetic properties from basic fibre characteristics and fabric constructional parameters with considerable accuracy. The network prediction is in good correlation with the actual experimental data. There is some error in predicting the fabric properties from the constructional parameters. The variation in the actual values and predicted values is because of small sample size. Moreover, the properties of worsted fabrics are greatly influenced by the finishing parameters which are not taken into consideration in the training of the network. Prediction performance can be further improved by including these parameters as input, during the training phase. In few cases, the network has predicted contradictory trends, which are found difficult to be explained.
Originality/value
The paper describes a radial basis function neural network model that can be used for the prediction of the fabric appearance values and comfort properties using fabric constructional parameters and some primary fibre mechanical properties as input parameters of the network.
Details
Keywords
Chukwudi C. Olumba, Cynthia N. Olumba and Chukwuma Ume
Taking a gender-sensitive approach, this study examines the socio-economic and institutional drivers of household vulnerability to the shocks occasioned by the COVID-19 pandemic…
Abstract
Taking a gender-sensitive approach, this study examines the socio-economic and institutional drivers of household vulnerability to the shocks occasioned by the COVID-19 pandemic. The study employs country-level panel data for Nigeria. Data collected were analysed using descriptive statistics, Pearson's chi-square, and ordered logistic regression. The study found significant heterogeneity in vulnerability to the COVID-19 shocks between the male-headed households (MHHs) and female-headed households (FHHs) (p < 0.1). The econometric results reveal that in the MHHs, the geographical location, livelihood diversification, and ownership of television were the significant drivers of vulnerability to COVID-19–related shocks. In the FHHs, credit constraints, household size, value of the household assets, geographical location, ownership of television and radio, and experiences of previous shocks were found to be significant drivers of vulnerability to COVID-19–related shocks. This study provides insights for designing inclusive social protection interventions and gender-sensitive COVID-19 recovery policies.
Details
Keywords
Grey cotton fibers with a mean fiber length and fineness of 29 mm and 4.2 micronair was pretreated, scoured and dyed. Three ring yarns were spun separately from 100% grey cotton…
Abstract
Grey cotton fibers with a mean fiber length and fineness of 29 mm and 4.2 micronair was pretreated, scoured and dyed. Three ring yarns were spun separately from 100% grey cotton (R.R.Y.), 50% dyed and 50% grey cotton blend (M.R.Y.) and 100% dyed cotton (D.R.Y.). The extent of fiber damage was assessed by measuring the length and the mechanical characteristics of cotton fibers after passing the fibers through the lap machine and the draw frame II. Properties of R.R.Y., M.R.Y. and D.R.Y. samples were examined. In terms of tenacity and elongation at break, grey and dyed cotton fibers, which were selected after being processed by the lap machine and the draw frame II, were very similar. The fiber length by number and weight of grey cotton was longer than that of dyed cotton, while the amount of fiber nep and short fiber content of dyed cotton were more than those of grey cotton.
The three yarn samples were the same in terms of elongation at break. The tenacity of R.R.Y. was the highest but the yarn sample was the lowest in terms of coefficients of mass variation (Cv%), imperfection and hairiness in comparison with the M.R.Y. and D.R.Y. samples.
Details
Keywords
Esra Zeynep Yıldız and Oktay Pamuk
The conversion of fabric into a garment involves many interactions such as the selection of suitable sewing thread, optimization of sewing parameters, ease of conversion of fabric…
Abstract
Purpose
The conversion of fabric into a garment involves many interactions such as the selection of suitable sewing thread, optimization of sewing parameters, ease of conversion of fabric into the garment and actual performance of the sewn fabric during wear of the garment. The adjustment of all sewing parameters is necessary to ensure quality. The purpose of this paper is to define the parameters that affect seam quality comprehensively.
Design/methodology/approach
This study primarily focuses on the studies dealing with the effect of various parameters on-seam quality in detail. A systematic literature review was conducted.
Findings
The interactions between parameters may lead to different results than the effect of a single parameter. In addition, changing some parameters may have a positive effect on one element of seam quality while having a negative effect on another. For this reason, it is very important to properly select the parameters according to the specific end use of the garment products and also to consider the interactions.
Originality/value
The knowledge of various factors that affect seam quality will be helpful for manufacturers to improve production performance and to be able to produce high-quality seam.
Details
Keywords
Mallika Datta, Devarun Nath, Asif Javed and Nabab Hossain
The focus of this research is to identify the optimum commercial grade sewing thread and stitch density to be used with woven linen shirting fabric used in making men’s formal…
Abstract
Purpose
The focus of this research is to identify the optimum commercial grade sewing thread and stitch density to be used with woven linen shirting fabric used in making men’s formal shirt. Maximum seam efficiency and interaction between the process parameters were assessed.
Design/methodology/approach
The classical method of optimisation involves varying one variable at a time and keeping the others constant. This is often useful, but it does not explain the effect of interaction between the variables under consideration. In this study, the response surface methodology was used for securing a more accurate optimisation of seam quality (seam efficiency) of woven linen shirting fabric. The response surface method is an empirical statistical technique used for multiple regression analysis of quantitative data obtained from statistically designed experiments by solving the multivariate equations simultaneously. Through this system, the input level of each process parameter, i.e. variable and the level of the selected response (seam efficiency), can be quantified. The central composite, Box–Behnken, is the common design used here.
Findings
The maximum seam efficiency is 79.62 per cent and 83.13 per cent in warp and weft direction, respectively, with optimum areal density (G) of 110 g/m2 of woven linen shirting fabric. The most suitable stitch density and ticket number of commercial grade sewing thread for woven linen shirting fabric are 13-13.5 and 40, respectively.
Practical implications
This study could help apparel manufacturers to evaluate seam quality, i.e. seam efficiency of woven linen fabric for men’s shirting, more effectively from the proposed regression model. The optimisation of the commercial grade sewing thread size and stitch density used in this study for woven linen shirting fabric within the range of 110-150 g/m2 will facilitate apparel engineers in production planning and quality control.
Originality/value
There is dearth of research on seam quality for woven linen shirting fabric using commercial grade sewing thread and engineering of prediction regression model for the estimation of seam efficiency by using process parameters, namely, fabric G, thread size and thread density and their interaction.
Details
Keywords
Kaushal Raj Sharma, B.K. Behera, H. Roedel and Andrea Schenk
Drape of the fabric is its ability to hang freely in graceful folds when some area of it is supported over a surface and the rest is unsupported. When two‐dimensional fabrics are…
Abstract
Purpose
Drape of the fabric is its ability to hang freely in graceful folds when some area of it is supported over a surface and the rest is unsupported. When two‐dimensional fabrics are converted to three‐dimensional garment forms, a number of operations are required which affect drape behaviour of the fabric while present in garment form. In the present study, the effect of sewing and fusing of interlining on drape behaviour of men's suiting fabrics is investigated.Design/methodology/approach – The effect of sewing and fusing of interlining on drape behaviour of men's suiting fabrics is investigated. Comparisons were also made between different stitches (chain stitch and lock stitch), different seams for lock stitch and different types of interlinings for their effect on drape behaviour of fabrics. In addition to drape coefficient and number of folds, a new drape parameter – average amplitude to average radius (A/r) ratio – was also defined and calculated for drape image geometry.Findings – Drape coefficient has a good to strong correlation with A/r ratio and number of folds for most of the shell, sewn and interlining fused fabrics except for a few cases. A/r defines image in a more descriptive manner than drape coefficient. Drape coefficient changes with the types of seams and stitches used, as well as with the interlining used.Originality/value – This paper provides information on the effects of sewing (seams and stitch types) and fused interlining on drape behaviour of men's suiting fabrics.
Details
Keywords
The objective of this research paper is to investigate the important factors that contribute to the absorbency characteristics of terry fabric in order to produce highly absorbent…
Abstract
The objective of this research paper is to investigate the important factors that contribute to the absorbency characteristics of terry fabric in order to produce highly absorbent terry towels by using suitable raw materials and changing the fabric constructional parameters. Yarns produced from two varieties of cotton (100% J-34 and MCU-5) and their blends with bamboo and poly vinyl alcohol (PVA) with different counts, twist and number of plies are used to prepare terry fabric of varying loop densities, loop lengths and loop shape factors. The water absorption rate and the total amount of water absorbed are measured by a gravimetric absorbency testing system (GATS). It is found that loop density is the most important parameter for water absorption rate followed by loop length and yarn twist. For the total amount of water absorbed, loop density is again the most important parameter followed by yarn twist, loop shape factor and number of ply in the pile yarn. Furthermore, a Box-Behnken statistical design with 3 factors and 3 levels is used to determine the optimum construction parameters to obtain the desired absorbency characteristics of terry towels and also to see the interaction effect of the various factors.
Details
Keywords
The objective of this paper is to investigate the predictability of air permeability of cotton woven fabrics from their construction variables by using a feed-forward…
Abstract
The objective of this paper is to investigate the predictability of air permeability of cotton woven fabrics from their construction variables by using a feed-forward back-propagation network in an artificial neural network (ANN) system. In order to achieve this objective, a number of grey cotton fabrics meant for shirting end use are desized, scoured, and relaxed. The fabrics are then conditioned and tested for constructional particulars and air permeability. A multiple linear regression based approach for modelling is attempted and the prediction issues are briefly summarized. For neural network modelling, a three layer feed-forward network is formed and trained by using the Broyden– Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton algorithm. The predictive ability of the neural model is examined by comparing their results with experimental data. From the results, it is seen that high correlation exists between the actual and predicted values of the neural network model. The overall predictability of the model is good.