The Experts below are selected from a list of 105 Experts worldwide ranked by ideXlab platform
Bhupendra Singh Butola - One of the best experts on this subject based on the ideXlab platform.
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Modelling and prediction of antibacterial activity of knitted fabrics made from silver nanocomposite fibres using soft computing approaches
Neural Computing and Applications, 2019Co-Authors: Prakash Khude, Abhijit Majumdar, Bhupendra Singh ButolaAbstract:Antibacterial activity of knitted fabrics has been modelled and predicted by using two soft computing approaches, namely artificial neural network (ANN) and adaptive network-based fuzzy inference system (ANFIS). Four parameters, namely proportion of polyester–silver nanocomposite fibres in yarn, yarn count (diameter), Machine Gauge and type of fabric (100% polyester or 50:50 polyester–cotton), were used as input parameters for predicting antibacterial activity of knitted fabrics. For each of the input parameters, two fuzzy sets (low and high) were considered to reduce the complexity of ANFIS model. The sixteen linguistic fuzzy rules trained by ANFIS were able to explain the relationship between input parameters and antibacterial activity. A comparison between ANN and ANFIS models has also been presented. Both the models predicted the antibacterial activity of knitted fabrics with very good prediction accuracy in the training and testing data sets with coefficient of determination greater than 0.92 and mean absolute prediction error less than 5%. The robustness of the prediction results against data partitioning between training and testing sets has also been investigated. It is found that prediction accuracy of both the models was quite robust with ANFIS showing better performance with lesser number of training data.
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Leveraging the Antibacterial Properties of Knitted Fabrics by Admixture of Polyester-Silver Nanocomposite Fibres
Fibers and Polymers, 2018Co-Authors: Prakash Khude, Abhijit Majumdar, Bhupendra Singh ButolaAbstract:Leveraging the antibacterial properties of polyester-cotton knitted fabrics has been attempted in this research by admixture of small proportion of polyester-silver nanocomposite fibres. Polyester-cotton (50:50) yarns were spun by mixing 10, 20 and 30 % (wt.%) polyester-silver nanocomposite fibres with normal polyester fibres so that overall proportion of polyester fibre becomes 50 %. The proportion of cotton fibre was constant (50 %) in all the yarns. Three parameters, namely blend proportion (wt.%) of nanocomposite fibres, yarn count and knitting Machine Gauge were varied, each at three levels, for producing 27 knitted fabrics. Polyester-cotton knitted fabrics prepared from polyester-silver nanocomposite fibres showed equally good antibacterial activity (65-99 %) against both S. aureus and E. coli bacteria. Antibacterial properties were enhanced with the increase in the proportion of polyester-silver nanocomposite fibres, yarn coarseness and increased compactness of knitted fabrics. Yarn count and blend proportion of nanocomposite fibre were found to have very dominant influence in determining the antibacterial properties of knitted fabrics.
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Development and performance optimization of knitted antibacterial materials using polyester-silver nanocomposite fibres.
Materials Science and Engineering: C, 2015Co-Authors: Abhijit Majumdar, Bhupendra Singh Butola, Sandip ThakurAbstract:Abstract The development and performance optimization of knitted antibacterial materials made from polyester–silver nanocomposite fibres have been attempted in this research. Inherently antibacterial polyester–silver nanocomposite fibres were blended with normal polyester fibres in different weight proportions to prepare yarns. Three parameters, namely blend percentage (wt.%) of nanocomposite fibres, yarn count and knitting Machine Gauge were varied for producing a large number of knitted samples. The knitted materials were tested for antibacterial activity against Gram-positive bacteria Staphylococcus aureus . Statistical analysis revealed that all the three parameters were significant and the blend percentage of nanocomposite fibre was the most dominant factor influencing the antibacterial activity of knitted materials. The antibacterial activity of the developed materials was found to be extremely durable as there was only about 1% loss even after 25 washes. Linear programming approach was used to optimize the parameters, namely antibacterial activity, air permeability and areal density of knitted materials considering cost minimization as the objective. The properties of validation samples were found to be very close to the targeted values.
Abhijit Majumdar - One of the best experts on this subject based on the ideXlab platform.
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Modelling and prediction of antibacterial activity of knitted fabrics made from silver nanocomposite fibres using soft computing approaches
Neural Computing and Applications, 2019Co-Authors: Prakash Khude, Abhijit Majumdar, Bhupendra Singh ButolaAbstract:Antibacterial activity of knitted fabrics has been modelled and predicted by using two soft computing approaches, namely artificial neural network (ANN) and adaptive network-based fuzzy inference system (ANFIS). Four parameters, namely proportion of polyester–silver nanocomposite fibres in yarn, yarn count (diameter), Machine Gauge and type of fabric (100% polyester or 50:50 polyester–cotton), were used as input parameters for predicting antibacterial activity of knitted fabrics. For each of the input parameters, two fuzzy sets (low and high) were considered to reduce the complexity of ANFIS model. The sixteen linguistic fuzzy rules trained by ANFIS were able to explain the relationship between input parameters and antibacterial activity. A comparison between ANN and ANFIS models has also been presented. Both the models predicted the antibacterial activity of knitted fabrics with very good prediction accuracy in the training and testing data sets with coefficient of determination greater than 0.92 and mean absolute prediction error less than 5%. The robustness of the prediction results against data partitioning between training and testing sets has also been investigated. It is found that prediction accuracy of both the models was quite robust with ANFIS showing better performance with lesser number of training data.
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Leveraging the Antibacterial Properties of Knitted Fabrics by Admixture of Polyester-Silver Nanocomposite Fibres
Fibers and Polymers, 2018Co-Authors: Prakash Khude, Abhijit Majumdar, Bhupendra Singh ButolaAbstract:Leveraging the antibacterial properties of polyester-cotton knitted fabrics has been attempted in this research by admixture of small proportion of polyester-silver nanocomposite fibres. Polyester-cotton (50:50) yarns were spun by mixing 10, 20 and 30 % (wt.%) polyester-silver nanocomposite fibres with normal polyester fibres so that overall proportion of polyester fibre becomes 50 %. The proportion of cotton fibre was constant (50 %) in all the yarns. Three parameters, namely blend proportion (wt.%) of nanocomposite fibres, yarn count and knitting Machine Gauge were varied, each at three levels, for producing 27 knitted fabrics. Polyester-cotton knitted fabrics prepared from polyester-silver nanocomposite fibres showed equally good antibacterial activity (65-99 %) against both S. aureus and E. coli bacteria. Antibacterial properties were enhanced with the increase in the proportion of polyester-silver nanocomposite fibres, yarn coarseness and increased compactness of knitted fabrics. Yarn count and blend proportion of nanocomposite fibre were found to have very dominant influence in determining the antibacterial properties of knitted fabrics.
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Development and performance optimization of knitted antibacterial materials using polyester-silver nanocomposite fibres.
Materials Science and Engineering: C, 2015Co-Authors: Abhijit Majumdar, Bhupendra Singh Butola, Sandip ThakurAbstract:Abstract The development and performance optimization of knitted antibacterial materials made from polyester–silver nanocomposite fibres have been attempted in this research. Inherently antibacterial polyester–silver nanocomposite fibres were blended with normal polyester fibres in different weight proportions to prepare yarns. Three parameters, namely blend percentage (wt.%) of nanocomposite fibres, yarn count and knitting Machine Gauge were varied for producing a large number of knitted samples. The knitted materials were tested for antibacterial activity against Gram-positive bacteria Staphylococcus aureus . Statistical analysis revealed that all the three parameters were significant and the blend percentage of nanocomposite fibre was the most dominant factor influencing the antibacterial activity of knitted materials. The antibacterial activity of the developed materials was found to be extremely durable as there was only about 1% loss even after 25 washes. Linear programming approach was used to optimize the parameters, namely antibacterial activity, air permeability and areal density of knitted materials considering cost minimization as the objective. The properties of validation samples were found to be very close to the targeted values.
A. Tamilarasi - One of the best experts on this subject based on the ideXlab platform.
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Predicting the fabric width of single jersey cotton knitted fabric using appropriate software
Industria Textila, 2019Co-Authors: I. Bhuvaneshwarri, A. TamilarasiAbstract:Prediction of any property of the material has attracted the attention of many scientists all over the world in order to produce better products. Information Technology (IT) field has many applications and plays dominant role in the production of various products in the industry. Knitted fabric should satisfy a number of requirements of consumer. Fabric width is a very important property which affects knitted fabric comfort properties. The deviation from the fabric width will either lead to more consumption of raw material or affect profit of the company. Hence, controlling the width of the fabric has an adverse effect on company’s profit and usage of raw materials. An investigation of the prediction of the width of the single jersey cotton knitted fabric in a fully relaxed state using Data mining technique in Rough set Computational based Priority Prediction Model (RCPPM) is reported. The inputs were yarn count, Machine diameter, required GSM, Machine Gauge, actual yarn count, lea weight, lea strength, twist multiplier, loop length, course per cm, wales per cm, length shrinkage, width shrinkage, and fabric width. The real-time textile dataset consisted of 7,505 single jersey cotton knitted fabric samples. The results showed that the fabric width obtained by using aforesaid model was found to yield very accurate values and compared favourably with the measured ones. This study will lead to the production of the knitted fabric with better comfort and dimensional stability.
Hiroshi Suzuki - One of the best experts on this subject based on the ideXlab platform.
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Comparison of End Breakage Rate due to Splices and Knots in Plain-Weft Knitting Zone
Journal of the Textile Machinery Society of Japan, 1991Co-Authors: Ryuzo Oinuma, Eiichi Sasaki, Hiroshi SuzukiAbstract:The effect of some factors on the end breakage rate in the plain-weft knitting zone due to three kinds of yarn joints (an air-splice, a weaver's knot and a fisherman's knot) is investigated experimentally, using a combed cotton yarn c 30s/1. End breakage in the plain-weft knitting zone due to an air-splice hardly occurs under any knitting condition. Therefore, the air-splice is a very useful yarn joint in weft knitting. The knitting defect due to a weaver's knot or a fisherman's knot is almost always caused by end breakage in the plain-weft knitting zone. This end breakage occurs near the knot on the take-down side. The end breakage rate in the plain-weft knitting zone due to a weaver's knot or a fisherman's knot increases with the increase in the depth of stitch draw, the Machine Gauge, the input tension, and the take-down weight. Under every knitting condition, the end breakage rate due to a fisherman's knot is more than that due to a weaver's knot.
Ripon Kumar Prasad - One of the best experts on this subject based on the ideXlab platform.
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a new approach for Machine Gauge production calculation of various kinds of rib and interlock knitted fabric structure
Journal of Textile Science and Technology, 2016Co-Authors: Ripon Kumar PrasadAbstract:Various types of rib and interlock fabrics found in the market depend on their structure such as 1 × 1 rib, 2 × 1 rib, 2 × 2 rib, 3 × 1 rib, 3 × 2 rib, 4 × 1 rib, 4 × 4 rib and 1 × 1 interlock, 2 × 2 interlock etc. These all types of fabric can be possible to knit in circular knitting Machine after Machine setting. When these fabrics are knit on the Machine, some needles are needed to drop or withdrawn from needle groove according to their design such as 1 × 1, 2 × 1, 2 × 2 etc. Due to needle dropping or withdrawing production per hour will changed as production per hour directly depends on the No. of active needle. No. of needle or active needle depends on Machine Gauge. This paper gives a new approach for Machine Gauge which is somewhat different from other thinking. This paper also shows the production calculation formula with their Machine setting for various rib and interlock fabric with their derivation. By this paper, one can easily understood about Machine Gauge and calculated production of any type of rib and interlock knitted structure. Complexity of calculating production can be reduced by this paper.
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A New Approach for Machine Gauge & Production Calculation of Various Kinds of Rib and Interlock Knitted Fabric Structure
2016Co-Authors: Ripon Kumar PrasadAbstract:Various types of rib and interlock fabrics found in the market depend on their structure such as 1 × 1 rib, 2 × 1 rib, 2 × 2 rib, 3 × 1 rib, 3 × 2 rib, 4 × 1 rib, 4 × 4 rib and 1 × 1 interlock, 2 × 2 interlock etc. These all types of fabric can be possible to knit in circular knitting Machine after Machine setting. When these fabrics are knit on the Machine, some needles are needed to drop or withdrawn from needle groove according to their design such as 1 × 1, 2 × 1, 2 × 2 etc. Due to needle dropping or withdrawing production per hour will changed as production per hour directly depends on the No. of active needle. No. of needle or active needle depends on Machine Gauge. This paper gives a new approach for Machine Gauge which is somewhat different from other thinking. This paper also shows the production calculation formula with their Machine setting for various rib and interlock fabric with their derivation. By this paper, one can easily understood about Machine Gauge and calculated production of any type of rib and interlock knitted structure. Complexity of calculating production can be reduced by this paper.
