A New Method for Measuring Fabric Drape with a Novel Parameter for Classifying Fabrics

With huge varieties of fabrics, the first challenge for any performance evaluation is to categorize the vast types of the products into fewer, more homogeneous and thus akin groups. Classification or sorting is arguably the first step of any scientific investigation, and comparison of product quality is meaningful only when conducted within a group of comparable products. A new criterion termed fabric linear density λ is first proposed in this paper so that fabrics can in general be divided into 4 groups. The derivation and validation of this parameter are provided. The importance of fabric drape is almost self-evident, but there is still no effective ways to measure this fabric attribute. The Cusick Drapemeter suffers from its low repeatability and low sensitivity, and is hence not widely or frequently used. The PhabrOmeter, along with the fabric linear density λ, is proposed and demonstrated in this study as a much more efficient alternative for fabric drape test. By actually testing 40 various fabrics, the principle, procedure and results of this method is presented in this paper. Introduction Visual attributes of textile fabrics represent a sub-group of sensory properties, perceived particularly by visual sense of consumers. Such visual qualities include fabric drape, surface state and luster, and, by logical extension, the fabric wrinkle recovery, fabric surface retention and stain resistance, i.e., all fabric appearance related esthetic characteristics. We call them fabric attributes to differentiate from the term fabric properties such as the fabric weight and fabric strength, for the latters are much easier to describe and with definitions widely accepted, and measurement methods well established. The importance of such fabric sensory attributes is indisputable. It is hard to imagine a Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 8 January 2018 doi:10.20944/preprints201801.0049.v1 © 2017 by the author(s). Distributed under a Creative Commons CC BY license. 2 consumer would buy a textile product without looking at it first. Therefore it can be stated that the success of any new fiber, new finish or new textile product is largely dependent on the acceptance of its sensory traits [1-3]. In this study, we focus on measurement of fabric drape performance. Fabric drape refers to the fabric shape or profile when held at the edge, such as used for curtains, or the way a fabric covers an object when used as a tablecloth or a skirt, often refereed to in the latter cases as the fabric formability, and is resulted from fabric’s response towards gravity due to its own weight [2, 3]. The current approaches in evaluating such quality attributes including drape are still quite primitive, lagging far behind the need for fast product development by the industry and for short product turn over time in the apparel market. They still largely rely on human sensory judgment, which in many cases is not readily reproducible and repeatable. It is interesting to note that the major fabric sensory attributes, hand, drape and wrinkle recovery, are interconnected and determined by the same group of mechanical properties [1, 4], thus laying down a foundation for instrumental measurement. Because of this close interconnectivity, it is possible that the same instrument properly configured can measure all such fabric attributes. Although there have been many attempts to develop instrumental means to measure such fabric attributes, but the resulted methods are not effective enough to meet the industrial requirements. Specifically, there has been a long history of research on measurement of fabric drape. Pierce[1] for instance proposed several simple methods including the “cantilever” and “loop” sample shapes to measure the bending resistance as “... strictly a measure of the draping quality of a fabric.” Such approaches have been reflected in several existing AATCC and ASTM standard tests. However Chu later pointed out that “two-dimensional distortion tests are incapable of differentiating between drape and paperinessi.e., 
it is possible to select a piece of paper and a piece of fabric both of which have the same bending properties, yet it is doubtful that the paper will drape as well as the cloth.” [2] A very thorough study of fabric drape was done by Cusick [3] and Hearle provided a comprehensive review of existing research on the subject [5]. Fabric drape was considered to be determined primarily not only by its bending but also shear resistance, and in that order [3, 5]. So now we know that it is the shear properties that differentiate between a piece of paper and a fabric. Then there is a review article in 1987 by Jacob and Subramaniam on the literature of fabric drape [6]. For instance, multiple regression analysis was used to determine whether certain deformation properties (stiffness, shear, extensibility) and structural characteristics (fabric weight, thickness, and density) can serve as reliable predictors of the drape of knitted fabrics [7]. Several studies focused on static and dynamic drape of fabrics[8-10]. There are also reported investigations on the draping behaviors of multi-layer textiles using digital image processing[11, 12]. As expected, the challenging question of theoretical modeling of fabric drape phenomena has attracted much interest [13-16] [17-27]. Searching and exploration for a better instrument for fabric drape test has been continuing up to this day, but only very few commercial products are available, notably the Fabric Drape Tester (better known as the Cusick Drapemeter [3] or Chu method [2] ), by tracing the shadow of a draped fabric on paper. However this test suffers from several shortcomings including low repeatability and low sensitivity [28-30] and thus has not been widely used by, for instance, the U.S. industry. It is a bit surprising that there is even not a U.S. standard for fabric drape test, a grave gap urgently required to fill. For anyone who has the experience of using the Cusick Drapemeter, several problems become immediately clear, including: Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 8 January 2018 doi:10.20944/preprints201801.0049.v1