Measuring fabric handle to define luxury: an overview of handle specification in next-to-skin knitted fabrics from Merino wool

Abstract

An examination is presented of the relevance of luxury to the wool textile and garment supply chain. This examination leads to a review of the concept and importance of fabric handle as a means of defining important aspects of fabric quality. Examples are given for woven fabrics of the general relationships between subjectively assessed fabric handle attributes such as fabric softness and smoothness and measured low stress, generally high deformation, fabric properties such as fabric bending rigidity and extensibility. A brief overview is presented of the development of a system for predicting a set of subjectively assessed handle attributes for next-to-skin knitted fabrics from measurable fabric properties. Seven handle attributes selected by experienced assessors as being important for defining tactile sensations associated with next-to-skin knitted fabrics were: fabric smoothness, hairiness, softness, tightness, dryness, warmth and weight. Subjective assessments on a 1–10 scale of these seven attributes, plus an assessment of overall handle, were conducted by 12 experienced assessors on 74 next-to-skin knitted fabrics. The precision of the mean assessment of the 12 assessors ranged between 0.8 and 1.1, indicating that there was sufficient consensus on key fabric handle assessments to justify development of a method for predicting them from measurements of the physical properties of fabrics. All fabrics were tested using the PhabrOmeter fabric evaluation system, which records the force exerted during insertion of a fabric into and through an orifice. Geometric parameters were derived to describe the PhabrOmeter force-displacement curve results, and statistical models were developed to predict the average handle assessments of the 12 assessors. The precision of the models in predicting the handle intensities of eight fabric attributes on an independent validation set of 22 fabrics was significantly better than the precision of an individual assessor (confidence limits = 1.4–2.6 and 2.5–3.8, for predicted and assessed ratings, respectively). A case is made that this technology has the potential to assist in the growth of new markets for Merino wool products.