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Article

Selsabil El‐Ghezal Jeguirim, Mahdi Sahnoun, Amal Babay Dhouib, Morched Cheickrouhou, Laurence Schacher and Dominique Adolphe

The purpose of this paper is to model the relationship between manufacturing parameters, especially finishing treatments and instrumental tactile properties measured by…

Abstract

Purpose

The purpose of this paper is to model the relationship between manufacturing parameters, especially finishing treatments and instrumental tactile properties measured by Kawabata evaluation system.

Design/methodology/approach

Two soft computing approaches, namely artificial neural network (ANN) and fuzzy inference system (FIS), have been applied to predict the compression and surface properties of knitted fabrics from finishing process. The prediction accuracy of these models was evaluated using both the root mean square error and mean relative percent error.

Findings

The results revealed the model's ability to predict instrumental tactile parameters based on the finishing treatments. The comparison of the prediction performances of both techniques showed that fuzzy models are slightly more powerful than neural models.

Originality/value

This study provides contribution in industrial products engineering, with minimal number of experiments and short cycles of product design. In fact, models based on intelligent techniques, namely FIS and ANNs, were developed for predicting instrumental tactile characteristics in reference to finishing treatments.

Details

International Journal of Clothing Science and Technology, vol. 23 no. 5
Type: Research Article
ISSN: 0955-6222

Keywords

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