A Fast Training Method of a Fabric Hand-Feel Panel under Industry Conditions, and Its Conformity with Other Human and Instrumental Approaches

Abstract

Under industrial daily business conditions, a heterogeneous group of employees with different backgrounds and activity fields was trained to function as a hand-feel panel to evaluate internal developments and optimizations, and to predict customer preferences in the main textile segments. Using sets of fabrics of typical constructions, different descriptors related to hand actions were elaborated and an evaluation method based on scaling, as well as ranking, was defined, based on AATCC 5-2006. Group performance was investigated by statistical concordance factors, by correlation with physical hand-feel assessment methods, and with a reference panel. Using a different fabric set, the panel’s ability to predict the average preferences of a larger consumer group was tested. Furthermore, the correlations of the system parameters of the different physical methods for the used fabrics were studied and discussed, showing the agreement and the disagreement aspects of the methods for the investigated fabrics.