A fuzzy logic based method for analyzing sensory evaluation data

This paper presents a fuzzy logic based method for analyzing the data provided by different individuals in sensory evaluation of industrial products. In order to process the uncertainty existing in these sensory data, we first transform all sensory data into fuzzy sets on an unified scale using the 2-tuple fuzzy linguistic model. Based on these normalized data sets, we compute the dissimilarities or distances between different individuals and between different evaluation terms used by them, defined according to the degree of consistency of data variation. The obtained distances are then transformed into fuzzy numbers for physical interpretation. These fuzzy distances permit to characterize the evaluation behavior of each individual and the quality of the evaluation terms used. Also, based on these fuzzy distances, a data aggregation approach can be further developed for finding a compromise between all individuals. This method has been applied to the fabric hand evaluation for a number of samples of knitted cotton in order to identify consumers' preference of different populations.