Main Article Content

Juan Bullon
Chemical and Textil Engineering Department, University of Salamanca. Spain
Spain
Biography
Angélica González Arrieta
Computer Sciences and Automation Department. University of Salamanca
Spain
Biography
Ascensión Hernández Encinas
Applied Mathematics Department. University of Salamanca
Spain
Biography
Araceli Queiruga Dios
Applied Mathematics Department. University of Salamanca
Spain
Biography
Vol. 6 No. 1 (2017), Articles, pages 41-50
DOI: https://doi.org/10.14201/ADCAIJ2017614150
Accepted: Feb 16, 2017
Copyright

Abstract

The textile industry is characterized by the economic activity whose objective is the production of fibres, yarns, fabrics, clothing and textile goods for home and decoration,as well as technical and industrial purposes. Within manufacturing, the Textile is one of the oldest and most complex sectors which includes a large number of sub-sectors covering the entire production cycle, from raw materials and intermediate products, to the production of final products. Textile industry activities present different subdivisions, each with its own traits. The length of the textile process and the variety of its technical processes lead to the coexistence of different sub-sectors in regards to their business structure and integration. The textile industry is developing expert systems applications to increase production, improve quality and reduce costs. The analysis of textile designs or structures includes the use of mathematical models to simulate the behavior of the textile structures (yarns, fabrics and knitting). The Finite Element Method (FEM) has largely facilitated the prediction of the behavior of that textile structure under mechanical loads. For classification problems Artificial Neural Networks (ANNs) haveproved to be a very effective tool as a quick and accurate solution. The Case-Based Reasoning (CBR) method proposed in this study complements the results of the finite element simulation, mathematical modeling and neural networks methods.

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https://doi.org/10.1007/978-3-642-32986-9_32