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Manufacturing processes in the textile industry. Expert Systems for fabrics production

机译:纺织工业中的制造过程。面料生产专家系统

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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.
机译:纺织业的特点是经济活动,其目标是生产用于家庭和装饰以及技术和工业目的的纤维,纱线,织物,服装和纺织品。在制造业中,纺织业是最古老,最复杂的行业之一,其中包括大量子行业,涵盖了从原材料,中间产品到最终产品生产的整个生产周期。纺织行业的活动呈现出不同的细分,每个细分都有自己的特征。纺织过程的持续时间及其技术过程的多样性导致不同子行业在业务结构和整合方面并存。纺织行业正在开发专家系统应用程序,以提高产量,提高质量并降低成本。纺织品设计或结构的分析包括使用数学模型来模拟纺织品结构(纱线,织物和针织物)的行为。有限元方法(FEM)在很大程度上促进了织物结构在机械载荷下的行为的预测。对于分类问题,人工神经网络(ANN)已被证明是一种非常有效的工具,可作为快速,准确的解决方案。这项研究中提出的基于案例的推理(CBR)方法是对有限元模拟,数学建模和神经网络方法的结果的补充。

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