Review of Application of Artificial Neural Networks in Textiles and Clothing Industries over Last Decades

2010-2011 > Academic research: refereed > Chapter in an edited book (author

Modelling the Effect of Resin-Finishing Process Variables on the Dimensional Stability and Bursting Strength of Viscose Plain Knitted Fabric Using a Fuzzy Expert System

The application of cross-linking resin is an effective method for improving and controlling dimensional stability, such as the shrinkage of viscose single jersey knits. However, such treatment often leads to a significant deterioration in the bursting strength of treated fabrics. In this regard, resin treatment using a softening agent can be an additional potential solution for retaining the bursting strength of treated fabrics. Resin treatment is one kind of chemical finishing process that inhibits cellulosic textile fibre swelling during wetting, provides fibre resistance to deformation and prevents shrinkage. The key objective of this study was to model the effect of resin-finishing process variables for predicting the shrinkage control and bursting strength of viscose single jersey knitted fabrics. The MATLAB (Version 8.2.0.701) fuzzy expert system was used to model the optimum resin and softener concentrations, as well as the best curing time for the prediction of maximum shrinkage control with a minimum loss in fabric bursting strength. The optimal process variables were found to be a resin concentration of 75 g/l, a softener concentration of 45 g/l and a curing time of 225 seconds. The fuzzy expert model developed in this study was validated using experimental data. It was found that the model has the ability and accuracy to predict fabric shrinkage and bursting strength effectively in the non-linear field

Artificial Neural Networks and Their Applications in the Engineering of Fabrics

WOS: 00036372550000

Yarn strength prediction: a practical model based on Artificial Neural Networks

Yarn strength is one of the most significant parameters to be controlled during yarn spinning process. This parameter strongly depends on both the rovings' characteristics and the spinning process. On the basis of their expertise textile technicians are able to provide a raw and qualitative prediction of the yarn strength by knowing a series of fiber parameters like length, strength, and fineness. Nevertheless, they often need to perform many tests before producing a yarn with a desired strength. This paper describes a Feed Forward Back Propagation Artificial Neural Network-based model able to help the technicians in predicting the yarn strength without the need of physically spinning the yarn. The model performs a reliable prediction of the yarn strength on the basis of a series of roving parameters, commonly measured by the technicians before the yarn spinning process starts. The model has been trained with 98 training data and validated with 50 new tests. The mean error in prediction of yarn strength, using the validation set, is less than 4%. The results have been compared with the one obtained by means of a classical method: the multiple regression. Nowadays, the developed model is running in the laboratory of New Mill S.p.A., an important textile company that operates in Prato (Italy)

Intelligent Techniques for Modeling the Relationships between Sensory Attributes and Instrumental Measurements of Knitted Fabrics

ABSTRACT The present investigation provides a promising tool for engineering industrial products design. In fact, two soft computing approaches, namely artificial neural network (ANN) and fuzzy inference system (FIS), have been applied to model the relationship between sensory properties and instrumental measurements of knitted fabrics. The prediction performance of these models was evaluated using the root mean square error (RMSE). The obtained results show the models' ability to predict tactile sensory attributes from the measured surface and compression properties. These neural and fuzzy models may help textile industrialists to satisfy the specific needs of consumers

Exploring the potential for functional enhancement of rugby union shirts through the development and implementation of sports-specific textile test methods

Determination of rugby union shirt prototype functional performance is currently reliant on generic Standard fabric test methods or unstructured human participant trials that, often, do not take into account the demands of the game. Current research, sponsored by Canterbury of New Zealand, describes the development and implementation of reproducible rugby shirt specific textile test methods to determine the effects of contemporary garment construction. Four rugby shirt functions were chosen for investigation: rugby ball-shirt friction interaction, garment strength, thermoregulatory response to exercise when clothed and on-field garment serviceability. Using a sled-type tribometer, the rugby ball-shirt friction interaction was investigated in a range of contemporary shirt designs during simulated light human interference. It was found that the addition of polymer grip textures did not necessarily enhance traction unless raised geometric textures, adhered to the fabric surface, promoted frictional interlocking with ball pimples. A fully-manufactured shirt, as opposed to Standard bulk stock fabric, tensile strength protocol was developed to benchmark a range of contemporary shirt constructions using the strip method. Tensile strength was affected by fabric construction and anisotropy whereby micromesh fabrics, particularly orientated in the course direction, were weakest. In some cases, seam specimens were much weaker than fabric specimens in the same shirt. The thermoregulatory response to rugby attire was investigated using a novel rugby backs­specific intermittent treadmill protocol designed to replicate the physiological and locomotive demands of competitive professional match-play. The thermal and moisture management properties of baselayer, padding and shirt technologies highlighted significant thermoregulatory effects of garment choice. The thermal functionality of baselayers was superior to that of a 100% cotton t-shirt and did not impose a further thermophysical load when worn beneath a team-shirt. Shoulder padding increased skin temperature, sweat rate and rate of change of core temperature, even when worn singly. The need for a structured rugby-shirt specific wearer trial was highlighted from observation of current procedures employed by manufacturers in the rugby shirt industry. Three distinct elements of the wearer trial process were investigated: wear-service conditions replicating the physiological intensity of game-specific demands of rugby, structured garment assessment techniques including failure criteria, and unbiased player questioning through self-administered questionnaires. The range of rugby shirt performance predictors and potential design weaknesses observed in the current research has highlighted the need for a more systematic research-led approach to prototype rugby shirt testing. It is hoped manufacturers will adopt the textile test methods described to better understand rugby apparel functionality, necessary for the potential improvement of match-day performance through superior garment design

The influence of woven stretch fabric properties on pattern design.

Conventional pattern construction and pattern making methods typically require the size measurements of a range of standard mannequins or human bodies in order to construct the varying pattern blocks for garment design. These various methods and skills, in the fashion industry, factory or studio are performed by pattern makers or producers, and are refined through the garment sampling and wearer trial system (an uneconomical trial and error) used on woven garments or on woven stretch garments to produce varying garment designs. This is particularly true when fabric stretch and recovery properties and values are encountered. There is a strong alliance with the heuristic knowledge. The aim of the present work is to investigate the influence of woven stretch fabric properties on pattern construction. The stretch and recovery properties of woven stretch fabrics will be taken account for pattern reduction and alteration for the development of a suitable garment pattern to fit the body shape and to meet the comfort requirement during the body movement. The relationship between the degree of alteration and reduction and the relevant fabric stretch properties is to be established. In this thesis, the stretch and recovery properties of various woven stretch fabrics have been measured. The conventional pattern is reduced and altered based on the comfort requirement for body movement, fit to body shape and the extension and recovery properties of the woven stretch fabric. Wearer trial test of the altered garment pattern of woven stretch fabrics is carried out for subjective and objective evaluation in the reference of the traditional woven garment pattern. Their comfort and garment appearances are evaluated by a panel of judges and the wearer. The size and shape stability of garments after the wearing tests are assessed. The results demonstrated that the new pattern method was significantly better for woven stretch fabric. The garment pattern for fit and comfort can be predicated and produced according to the extension and recovery properties of fabrics