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Salud, Ciencia y Tecnología Metaverse Basic and Applied Research Data & Metadata Interdisciplinary Rehabilitation Salud, Ciencia y Tecnología - Serie de Conferencias Community and Interculturality in Dialogue Seminars in Medical Writing and Education Health Leadership and Quality of Life Gamification and Augmented Reality Southern perspective / Perspectiva austral
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Published: 2024-05-20
DOI: https://doi.org/10.56294/dm2024251

Predicting saturation for a new fabric using artificial intelligence (fuzzy logic): experimental part

By
Mhammed EL BAKKALI ,
Mhammed EL BAKKALI

Higher School of Textile and Clothing Industries, Casablanca Morocco

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Redouane MESSNAOUI ,
Redouane MESSNAOUI

Higher School of Textile and Clothing Industries, Casablanca Morocco

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Mustapha ELKHAOUDI ,
Mustapha ELKHAOUDI

Higher School of Textile and Clothing Industries, Casablanca Morocco

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Omar CHERKAOUI ,
Omar CHERKAOUI

Higher School of Textile and Clothing Industries, Casablanca Morocco

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Aziz SOULHI ,
Aziz SOULHI

National Higher School of Mines of Rabat, Morocco

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Abstract

Weaving saturation can have harmful consequences, such as problems with loom performance, accelerated wear of mechanical parts and loss of raw materials. To avoid these problems, when designing and creating new fabrics, the densities and yarn qualities must be carefully matched with the weaves to ensure successful testing. To facilitate this task, this study focuses on the development of a practical fuzzy logic model for predicting the saturation of new fabrics. An experimental part was carried out to validate this fuzzy model. The fabric samples used in this study came from three different types of weaves, namely plain, twill and satin. These samples also included five weft counts (Nm) and eight different densities. The results obtained using the fuzzy logic model developed were compared with experimental values. The prediction results were satisfactory and precise, demonstrating the effectiveness of the fuzzy logic model developed. The mean absolute error of the calculated fuzzy model was 1.97%. It was therefore confirmed that this fuzzy model was both fast and reliable for predicting the saturation of new fabric

Keywords:

Weaving,
Fuzzy logic,
Modelling,
Saturation Index,
Weaveability,

How to Cite

1.
EL BAKKALI M, MESSNAOUI R, ELKHAOUDI M, CHERKAOUI O, SOULHI A. Predicting saturation for a new fabric using artificial intelligence (fuzzy logic): experimental part. Data and Metadata [Internet]. 2024 May 20 [cited 2024 Jul. 6];3:251. Available from: https://dm.saludcyt.ar/index.php/dm/article/view/251

Copyright Notice

The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.

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Vol. 3 (2024)
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