Measuring and Fuzzy Predicting Total Handle from Selected Mechanical Properties of Double Weft-Knitted Fabrics

Park, Shin-Woong; Hwang, Young-Gu

doi:10.1177/004051759906900104

Cited by 22 publications

(27 citation statements)

References 13 publications

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“…stretchiness, distortion, weight, flexibility, and smoothness were, respectively, where A, t is the weight percent of winter outerwear knitted fabrics in South Korea, and A, is from the New Zealand panel. Each value of percent importance indicates the degree of influence when one touches knitted apparel fabric [20][21][22][23]. From these results, we found that the trend of the weighted factor vector for winter outerwear knitted fabrics was quite similar in order of rank.…”

Section: Determ)btbg Weighted Factorsmentioning

confidence: 91%

“…The membership functions were based on earlier studies about objective assessments of light woven fabrics. and the selected mechanical properties were from Kawabata's six block mechanical properties [ 14,[20][21][22][23][24][25][26]. Figure 2 shows the nowchart of the fuzzy applied total hand evaluation model.…”

mentioning

confidence: 99%

“…26 j. Moreover the relationship between the six assigned weights and seven mechanical properties of Kawabata was higher than other factors [20]. and the establishment of A was based on the survey of a panel of judges (N = 30 in South Korea and N = 10 in New Zealand).…”

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confidence: 99%

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Comparison of Total Hand of Single Knitted Fabrics Made from lincLITE® and Conventional Wool Yarns

Park

Hwang²

2002

Textile Research Journal

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Two sets of single wool weft-knitted fabrics made from conventional yarn and lincLITE®, which was developed by the Wool Research Organization of New Zealand in an effort to make a softer and bulkier wool, are used to analyze a total hand evaluation model for outerwear knitted fabrics. Mechanical properties and total hand value are measured on the KES-FB system, and three kinds of fuzzy membership functions (a decreasing halfCauchy equation and two linear functions, increasing or decreasing) are used to calculate fuzzified overall hand values of the knitted fabrics. The weighted factor vectors surveyed by a Korean panel are strongly related to those of a New Zealand panel. Based on these surveys, we calculate the total hand value of the KES-FB and the fuzzy model. The latter results show that the bulkiness of single wool fabric knitted from lincLITE yarn is a little higher than the same fabric knitted from conventional yarn. Furthermore, the fuzzy total hand evaluation from the Korean panel is highly correlated with the result of the New Zealanders.Previous papers [20. 21 have reported on measurements and fuzzy models for double weft-knitted fabrics on the basis of seven mechanical properties. The hand of knitted fabrics can be affected by fiber type, yarn size, fabric structure, fabric geometry, and finish [1, 7. 9].There has been a great interest in hand evaluation due to the introduction of various kinds of knitted fabrics [ 1, 5, 6, l 1 ] and technical improvements of new synthetic or natural fibers [1, 6]. As new fibers and blends have developed, considerable work has focused on the physical and mechanical properties of fabrics, such as hand and drape [t. 6, 12, 14]. Considering the standardization of hand evaluation, a more effective link for hand is needed to predict the overall hand of knitted fabrics made from conventional and newly developed yarns.The Kawabata fabric evaluation system (KES-FB) provides an objective specification of hand value and total hand value on the basis of mechanical properties, but the system is not appropriate for knitted fabrics that have comparatively high flexibility and stretchiness [ 19]. However, mechanical properties such as bulkiness, flexibility, stretchiness, distortion, weight, and smoothness are recognized as important components for good comfort and quality knits [5,8,9,12,16,23]. Thus, an objective hand technique is needed for better evaluations of knitted fabrics.In this paper, we measure the mechanical properties of two knitted fabrics and then calculate the total hand value using the KES-FB system. We also analyze a fuzzy transformation function [20-23, 25, 26]. We focus on a fuzzy hand evaluation model and a comparison of total hand values by two evaluation methods for plain wool knitted fabrics of HncUTE~ and conventional yams. Experimental SPECIMEN PREPARATIONFor the study, single plain fabrics were knitted from two kinds of raw materials. lincLITE and conventional yam. Figures I is a representation of lincLITE yam. which was made from 100~c merino wool. A...

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Section: Determ)btbg Weighted Factorsmentioning

confidence: 91%

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confidence: 99%

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Comparison of Total Hand of Single Knitted Fabrics Made from lincLITE® and Conventional Wool Yarns

Park

Hwang²

2002

Textile Research Journal

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“…(1998), Park and Hwang (1999), and Chen et al (2000), evaluated the handle of fabrics using a fuzzy transformation matrix. Mathematically, the process can be represented as follows:…”

Section: Fabric Handlementioning

confidence: 99%

Soft Computing Applications in Fabrics and Clothing: A Comprehensive Review

Majumdar

Mitra

Banerjee

et al. 2010

Research Journal of Textile and Apparel

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. ABSTRACTThis paper presents a comprehensive review of soft computing applications in the domain of fabrics and clothing. In the last two decades, soft computing techniques, such as artificial neural network, fuzzy logic and genetic algorithm, have been used abundantly for fabrics and clothing modelling, manufacturing, quality control and marketing. This review is aimed at presenting a compendium of research work done so far on the applications of soft computing techniques in fabrics and clothing science and engineering. In the beginning of the paper, a brief introduction of soft computing techniques is provided. Then, the applications of soft computing methods in fabric property modelling (tensile, bending, shear, drape, handle, comfort, thickness and compression, air permeability, porosity, etc.) are provided. In the subsequent sections, soft computing applications for fabric defect identification in static and dynamic conditions, fabric classification, fabric engineering, machine control and marketing, are discussed. The scope of future applications is included in the concluding section.

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“…In order to understand the sensations of assessors from textile materials and also to consider the uncertainty in sensory assessments, artificial intelligence and fuzzy logic techniques are suggested by some researchers (Pan, Yen, Zhao, & Yang, 1988b;Park & Hwang, 1999;Park, Hwang, Kang, & Yeo, 2000;Raheel & Liu, 1991). Principal component analysis (PCA) or factor analysis techniques have also been used by researchers for woven fabrics (Brand, 1964;Howorth, 1964;Howorth & Oliver, 1958;Lam & Postle, 2006;Stearn, D'Arcy, & Postle, 1983).…”

Section: Introductionmentioning

confidence: 99%

Instrumental evaluation of orthogonal tactile sensory dimensions for fine lightweight knitted fabrics

Wang

Mahar

Postle

2013

Journal of The Textile Institute

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Lightweight fabrics knitted from fine and ultrafine merino wool fibres are emerging as a niche market for next-toskin wear. The tactile sensory properties of these fabrics are investigated in this study. Seven pairs of bi-polar descriptors were defined from a survey as the most important tactile attributes for this target market. Furthermore, the existence of collinearity between the descriptive attributes was removed and three orthogonal tactile sensory dimensions were established by using principal component analysis. These three orthogonal tactile sensory dimensions explain 92.6% of the total variance of the seven tactile attributes. Partial least squares regression analyses showed that the Wool Handle Meter was capable of predicting the three tactile sensory dimensions.

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Measuring and Fuzzy Predicting Total Handle from Selected Mechanical Properties of Double Weft-Knitted Fabrics

Cited by 22 publications

References 13 publications

Comparison of Total Hand of Single Knitted Fabrics Made from lincLITE® and Conventional Wool Yarns

Comparison of Total Hand of Single Knitted Fabrics Made from lincLITE® and Conventional Wool Yarns

Soft Computing Applications in Fabrics and Clothing: A Comprehensive Review

Instrumental evaluation of orthogonal tactile sensory dimensions for fine lightweight knitted fabrics

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