Purpose -The purpose of this paper is to investigate the concept of "electrically conductive fabrics". The primer applications that import electrical conductivity properties to textiles and clothing are summarized. Also the heated fabric panels produced by steel yarns are evaluated. Single and multi-ply steel fabrics are applied to electrical current and their heating behaviors are observed and compared. Design/methodology/approach -The integration of electronic components with textiles to create very smart structures is getting more and more attention in recent years. Most of the textile materials are electrical insulators. Hence, various types of fibers and fabrics having reasonably good electrical conductivity are required especially for electronically functional apparel products. The textile-based materials being flexible and easily workable are the most preferred one in such cases. In this study, the steel yarns are placed in the fabric construction owing to their flexible characteristics. The heating panels used in this study are produced by conventional textile processes and applied to electrical current. For this purpose, an electronic circuit that contains textile-based warming panels connected to a power supply, has been developed. Findings -The heated steel fabric panels with different number of plies provide different heating degree intervals owing to the different resistance levels, Therefore, in the applications of textile-based heating elements it is suggested that the electrical characterization of conductive materials should be examined and the materials that have the most appropriate electrical resistance characteristic must be applied. Furthermore, in the circuits used for heating function, the current amount depends on the electrical features of heating structures. Consequently, the pads with different plies have various efficient heating in point of time. It is recommended that the appropriate heating pad dimensions, ply or conductive yarn amounts and sufficient power supply conditions should be evaluated and chosen according to the desired heating level. Originality/value -Electrically conductive stainless steel yarns are processed to form a heating panel that can be used within an electronic circuit as a warming mechanism.
The smart/interactive textile structures that integrate electronics and textile materials have realized their great potential in recent years. The garments, which can heat the body, will possibly be one of the most widely used products as electrotextiles for future use in daily life. In this study, steel-based conductive yarns were used to produce heating panels within the study about interactive electronic heated garment design. Portable power supplies were applied to fabric-based panels to obtain a heating function. In addition to an electronic circuit, a functional garment containing all of the systems was designed and produced. The performance of the heating garment prototype was evaluated on a thermal mannequin by testing in cold weather environments.
The textile-based materials, equipped with nanotechnology and electronics, have a major role in the development of high-tech milltary uniforms and materials. Active intelligent textile systems, integrated to electronics, have the capacity of improving the combat soldiers performance by sensing, adopting themselves and responding to a situational combat need allowing the combat soldiers to continue their mission. Meantime, smart technologies aim to help soldiers do everyth~ng they need to do with a less number of equipment and a lighter load. In this study, recent developments on smart garments, especially designed for military usage owing to their electronic functions, and intelligent textlle-based materials that can be used in battlefield, are introduced.
PurposeIdentification of human body shapes has been a key issue to develop sizing standards for ready‐to‐wear and to develop made‐to‐measure applications. Current methods to identify the body shapes are mostly based on subjective/visual determination approaches. The purpose of this paper is to look for numerical evaluation parameters for an objective method in order to classify the body shapes and to build up an automated process link.Design/methodology/approachFemale subjects were chosen for the experimental design. 3D body scanning technology was integrated in the process for measurement taking and body silhouette detection of the sample group. Based on this sample data set, body shape identification was realized by referees as visual analyses, and additionally, an objective method was tried out by using body dimensions as numerical evaluation parameters. Obtained results with the sample group were inserted in a database and a body shape calculation tool was developed.FindingsStatistical analyses showed that there is mostly a good agreement between the pairs of the evaluations including the objective calculation methods and the subjective assessments of the referees. The calculation tool was designed as web‐based software in order to integrate with further developments and automation purposes.Originality/valueA new automatic tool was developed to make the body shape classification objective and repeatable. By integrating this tool to the product development chain, a continuous process link can be provided for the companies through the way for better fitting clothing.
Purpose – The purpose of this paper is to develop an intelligent system for fashion style selection for non-standard female body shapes. Design/methodology/approach – With the goal of creating natural aesthetic relationship between the body shape and the shape of clothing, garments designed for the upper and lower body are combined to fit different female body shapes, which are classified as V, A, H and O-shapes. The proposed intelligent system combines genetic algorithm (GA) with a neural network classifier, which is trained using the particle swarm optimization (PSO). The former, called genetic search, is used to find the optimal design parameters corresponding to a best fit for the desired target, while the task of the latter, called neural classification, is to evaluate fitness (goodness) of each evolved new fashion style. Findings – The experimental results are fashion styling recommendations for the four female body shapes, drawn from 260 possible combinations, based on variations from 15 attributes. These results are considered to be a strong indication of the potential benefits of the application of intelligent systems to fashion styling. Originality/value – The proposed intelligent system combines the effective searching capabilities of two approaches. The first approach uses the GA for identifying best fits to the target shape of the body in the solution space. The second is the PSO for finding optimal (with respect to training mean-squared error) weight and threshold parameters of the neural classifier, which is able to evaluate the fitness of successively evolved fashion styles.
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