Fabric Database and Fuzzy Logic Models for Evaluating Fabric Performance

Fabric Database and Fuzzy Logic Models for Evaluating Fabric Performance

Yan Chen (Louisiana State University Agricultural Center, USA), Graham H. Rong (Massachusetts Institute of Technology, USA) and Jianhua Chen (Louisiana State University, USA)
Copyright: © 2008 |Pages: 25
DOI: 10.4018/978-1-59904-853-6.ch021
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A Web-based fabric database is introduced in terms of its physical structure, software system architecture, basic and intelligent search engines, and various display methods for search results. A fuzzy linear clustering method is used to predict fabric drape coefficient from fabric mechanical and structural properties. Experimental data indicate that fuzzy linear clustering is quite effective for this purpose. A hybrid method combining fuzzy linear clustering with K-nearest neighbor is also applied for the prediction of the fabric drape coefficient with improved prediction accuracy. The study also reveals that the fuzzy linear clustering method can also be used for predicting fabric tailorability with good prediction accuracy. Mathematical principles of fuzzy comprehensive evaluation are summarized and a typical application for assessing fabric comfort is exhibited. Through the fuzzy calculation, a single numerical value is produced to express female preferences for six fabric types for use in blouses, slacks, and underpants with respect to fabric property changes in an incremental-wear trial. Finally, a neuro-fuzzy computing technique for evaluating nonwoven fabric softness is presented. The combinational use of the fuzzy logic models (CANFIS) and the neural network method makes a significant step toward launching a fabric database application for neural network computing as a routine laboratory evaluation.

Key Terms in this Chapter

Spunbond: Spunbond is a specific nonwoven web-forming process by extruding, drawing, and laying synthetic filament fiber on a convey belt for fiber collection.

Eigenvalue: It is a solution derived from a vector-characteristic equation, representing a variance of a main effect.

Drapability: It is the ability of a fabric to form pleating folds when deformed under its own weight.

Yarn Interlacing: It is a method of forming woven fabrics by weaving two sets of yarns.

Pure Bending Tester: It is an instrument for measuring fabric pure flexural deformation.

Fabric Drape Coefficient: It is a ratio of a projected pleating fold area formed by a piece of fabric after draping under its own weight to the original area of this piece of fabric without draping. The higher the fabric drape coefficient, the lower the fabric drapability.

Fabric Performance: Fabric performance is a general term to implicate fabric end-use properties regarding durability, comfort, and aesthetics. Typical fabric properties like breakage and abrasion, heat and moisture transport, hand and drape, and pattern and color are among those end-use properties.

Tailorability: It is the ease of converting a piece of 2-D fabric into a required piece of 3-D garment component.

Durability: Durability is a denotation for textile and apparel quality features related to product reliability. These features include the change of tensile strength, tear strength, abrasion resistance, colorfastness, and cracking and bursting strength during service life.

Fuzzy Linear Clustering: It is a fuzzy clustering method in which the prototype for each fuzzy cluster is a linear function of the input variables.

Softness: Softness is a type of fabric touch feeling by a human’s hand related to fabric bulky, flexible, and springy properties.

Fuzzy Clustering: It is a family of clustering methods that partition a set of given data objects into (nondisjoint) fuzzy clusters. Each fuzzy cluster is a fuzzy set, and each object’s membership degree in all the clusters sum up to one.

Fuzzy Set: A fuzzy set is a generalization of an ordinary (crisp) set. A fuzzy set S allows an element to have partial degree (between zero and one) of membership in S.

Artificial Neural Network (ANN): ANN is a computing paradigm that loosely simulates cortical structures of the brain. The simplest element of ANN is called a processing element, or node. Soft computing techniques are used to develop different types of ANN models based on different processing elements.

Shear Tester: It is an instrument for measuring fabric in-plane shear deformation.

Bounded Sum: Denoted by the symbol ?, it is defined a s or . Here, ? denotes and in Boolean algebra.

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