Modelling of the selected mechanical properties of the modern double-drum cards for manufacturing of spunlace nonwovens

Niedziela, Maciej; Sąsiadek, Michał; Woźniak, W

doi:10.1080/00405000.2020.1835154

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…They have observed that the friction force decreases as the weight of the fabric increases, and the friction force increases as the weight of the fabric decreases. Niedziela et al [9] emphasize the importance of carding when producing spunlace fabric in nonwoven textile. Many manufacturers have shown that they produce different carding machines, that these machines play an important role in delivering the products to water jets and in laying the fibers before they are bonded, and that the quality is affected as a result of these processes.…”

Section: Introductionmentioning

confidence: 99%

An Approach to Spunlace Fabrics: A Prediction on the Tensile Strength Using Artificial Neural Network and the Improvement of the Production Quality Using Fuzzy-Logic Controller

ÖDEV,

UYMAZ

2023

jbst

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In this study, firstly, the tensile strength of the spunlace fabric has been estimated by Artificial Neural Networks (ANN) method. For this purpose, an artificial neural network model was developed by taking the tensile strength values of spunlace fabric samples as reference values. In the production of spunlace fabric with water jet, it is the water jet that provides the mechanical bonding of the fibers and hence affects directly the breaking and tearing strength values of the fabric. The water jet pressure is controlled by pressure sensors, and a blockage in the water jet causes the pressure sensors to measure incorrectly and, as a result, a quality failure. In this respect, secondly aim of this study is to conceive a method to controller the water jet pressure using a fuzzy-logic controller (FLC) instead of pressure sensor control. During the production, the DC electric motor revolutions used in the water jet were kept constant by the fuzzy logic controller according to these reference values. And hence, it was provided that the strength quality of the spunlace fabric were maintained.

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Section: Introductionmentioning

confidence: 99%

An Approach to Spunlace Fabrics: A Prediction on the Tensile Strength Using Artificial Neural Network and the Improvement of the Production Quality Using Fuzzy-Logic Controller

ÖDEV,

UYMAZ

2023

jbst

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Pore size, shape and orientation analysis with respect to tensile tests in nonwoven spun-lace textiles using image processing

Niedziela

Sąsiadek

Woźniak

2022

The Journal of The Textile Institute

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Mechanical Properties of Spunlace Non-Wovens with a Porous Structure

Sąsiadek,

Dobrzańska-Danikiewicz,

Niedziela

et al. 2024

Coatings

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The paper describes the influence of the drum system construction of two modern carding machines on the porous structure of spunlace non-wovens composed of polyester and viscose. The non-woven fabric structure, including the number and size of the pores, determines the tensile strength of the composites obtained. The spunlace non-wovens were subjected to tensile strength tests in the machine, and cross-directions and microscopic observations of their structure were made. The results of the experiments were used to determine the relationship between the strength of the material and the porosity of its structure. This knowledge was used to prepare recommendations for the manufacturer of wet wipes in order to enable the selection of a carding machine for the mass production of final products with strength properties that meet market requirements and satisfy the end customer.

show abstract

Modelling of the selected mechanical properties of the modern double-drum cards for manufacturing of spunlace nonwovens

Cited by 3 publications

References 14 publications

An Approach to Spunlace Fabrics: A Prediction on the Tensile Strength Using Artificial Neural Network and the Improvement of the Production Quality Using Fuzzy-Logic Controller

An Approach to Spunlace Fabrics: A Prediction on the Tensile Strength Using Artificial Neural Network and the Improvement of the Production Quality Using Fuzzy-Logic Controller

Pore size, shape and orientation analysis with respect to tensile tests in nonwoven spun-lace textiles using image processing

Mechanical Properties of Spunlace Non-Wovens with a Porous Structure

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