• Science of Emotion and Sensibility
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• v.8 no.2
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• pp.117-128
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• 2005

The purpose of this study was to clarify the effects of constituent characteristics and the mechanical properties by KES-FB system on the visual texture images and preference of men's suit fabrics. Twenty different kinds of black fabrics, which were used mainly for the spring and summer men's suits, were selected and the subjective evaluation of the visual texture images was tested. Sixty experts in department of clothing and apparel industries participated in the subjective evaluation. Factor analysis showed visual texture images were classified into 4 categories : 'bulkiness', $'extensibility{\cdot}rapability'$, 'flexibility' and 'smoothness'. All of relationships were established between the mechanical properties and the visual texture images except the relation between 'flexibility' and bending properties. The significant factors affecting preference were 'smoothness', compression energy(WC), fabric count and 'flexibility', As the fabrics had higher value for 'smoothness' and 'flexibility' , and lower ones for compression energy and fabric count, they tended to be more preferred.

• Fashion & Textile Research Journal
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• v.15 no.2
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• pp.309-315
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• 2013

This study examines the difference of surface properties according to napping characteristic of artificial suedes, measuring surface structure observation, the contact/non-contact method roughness, warm-cool feeling of touch, and subjective hand evaluation. Surface and cross-section observations showed a discernible difference in fineness, curl, length, mount of napping, and covering power of base fabric. The surface properties of artificial suede evaluated by KES-FB4 showed that the shorter napping length the more smooth surface and the roughness increased reciprocally with friction resistance and surface contour when the nap length reaches a high level. The surface roughness measuring system applied a laser displacement sensor by a non-contact method to assess napping characteristic and the base fabric and napping height. Surface roughness decreased when napping was uniformly covered with base fabric; however, the surface roughness increased specifically with the uneven covering power of the base fabric. For qmax of the suedes, those that had short and smaller amounts of napping increased; however, the napping of length and amount at some stage generated a low qmax value. The warm sensation in all suedes were strongly perceived, but the cool sensation of the perception was lower in the subjective evaluation. Smoothness and softness were perceived when the suede has a long and large amount napping; however, smoothness and hardness were perceived when the suede was short and with the uneven covering power.

• Science of Emotion and Sensibility
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• v.12 no.1
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• pp.77-86
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• 2009

A comfort evaluation of car seat clothing has been proposed for high comforts interior seat clothing. Car seat covers have received wide spread attention due to their man-machine interface working. And then, it will be necessary for measurements on delicate basic mechanical-properties, which closely relate with human touch feeling of its materials. In this research, we have utilized $KES-FB^{(R)}$(Kawabata Evaluation System) series, $^ST300{(R)}$ analogue softness tester and friction tester for measurement a physical properties. In order to consider both kansei and physical properties on interior seat covers, we firstly have established subjective words of judgement for the seat covers. Secondly, related them to the objective measurement of physical properties. Each kansei-language has clearly defined as 'Softness', 'Elasticity', 'Volume' and 'Stickiness' for the adjectives of leather car seat covers. These technical terms have correlated to physical properties in other words, h (mm), bending moment ($gf^*$cm/cm), To-Tm (mm) and ${\mu}$. At this time, fuzzy logic has utilized to predict the value of kansei language through physical values. On the basis of this result, finally it is possible to predict quality index of car seat covers using neural networks technique. In short, we develop a quality evaluation system of car seat clothing combining four physical quantities with kansei engineering.