A mathematical model for objective hand evaluation of automotive seat fabrics

A mathematical model for objective evaluation of hand value of car seat fabrics was developed using a step-wise block regression method. The subjective assessment of fabrics was conducted by a panel of judges to identify the primary hand attributes and the related mechanical parameters playing an important role in the fabric hand evaluation. The primary attributes selected by judges were conformability, smoothness, softness and stretchability. The coefficient of concordance was determined to find out the agreement among the judges. From consumer point of view, conformability got the highest weightage in the survey. There is an excellent correlation between the subjective and objective primary hand values. The correlation between the subjective and the objective total hand values found to be very high (R > 0.9) both with and without stretchability parameter.

AN INTELLIGENT TECHNOLOGY BASED METHOD FOR INTERPRETING SENSORY EVALUATION DATA PROVIDED BY MULTIPLE PANELS

This paper presents an intelligent technology based method for analyzing and interpreting sensory data provided by multiple panels in evaluation of industrial products. In order to process the uncertainty existing in these sensory data, we first transform all sensory data on an unified optimal scale. Based on these normalized data sets, we compute the dissimilarities or distances between different panels 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 behaviour of each panel and the quality of the evaluation terms used. Also, based on a Genetic Algorithm with punishment policy and the dissimilarity between terms, we develop a procedure for interpreting terms of one panel using those of another panel. 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.

AN INTELLIGENT SENSORY EVALUATION METHOD FOR INDUSTRIAL PRODUCTS CHARACTERIZATION

This paper presents a new method for sensory evaluation of industrial products with uncertain information. In this approach, sensory data provided by different evaluators are transformed into measures of consistency on fuzzy satisfaction degrees. Based on these measures of consistency, we obtain the aggregated information for all evaluators and all attributes and measure the dissimilarity between evaluators and between used evaluation attributes. The effectiveness of this method has been validated in the fabric hand evaluation for a number of samples of knitted cotton.

The Application of The Principle of Information Theory to Fabric Hand Evaluation

In this paper, the author applies the principle of information theory to probe the role that experience plays in the process of fabric hand evaluation. 8 experts and 8 non-experts, two group judges assessed 8 medium-weight worsted fabrics for men’s suiting. The results have been analysed. The data show that the expert group has the higher ability of handling instinct attributes of a fabric than the non-expert group do. In other words, the experts seem to be more sensitive to the change of fabric physical and mechanical properties than the non-experts. And when a expert assesses a fabric by hand, he introduces few subjective factors, that is to say, the result of the evaluation of touch quality of a fabric by a expert has higher objectivity or reliability. This may provide a fundamental or a train of thought for the objective assessment of fabric hand in textile science and technology.