Evaluation of Sewed Thread Consumption of Jean Trousers Using Neural Network and Regression Methods

Jaouachi, Boubaker; Khedher, Faouzi

doi:10.5604/12303666.1152518

Cited by 14 publications

(13 citation statements)

References 23 publications

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“…In addition to the suitable adjustments, requested by the Juki 252-F manufacturer's sewing machine, seam length (=10 cm) of each sample was cut and sewn. According to literature [14] of panty's consumption, the weight fabric parameter presents a nonnegligible effect (=10.18%) when weight of seamed fabric increases. Then, the seam was unraveled to get the needle, the bobbin, or looper threads consumed in 10 cm length.…”

Section: Methodsmentioning

confidence: 99%

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A Study of the Consumption of Sewing Threads for Women's Underwear: Bras and Panties

Brahem

Wissal

Khedher

et al. 2020

Autex Research Journal

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The article evaluates the amount of the consumed sewing thread for women’s underwear (underwear bras and panties). Based on the obtained findings, it was concluded that sewing thread amount depends enormously on the studied influential parameters. The present paper reports a contribution that allows industries and researchers to decrease the consumed amounts of sewing thread in case of women’s underwear and panties The study takes into account the different stitch structures and fabric characteristics that are usually used. The effects of influential input parameters, such as fabric thickness, number of assembled layers, stitch density, and tension of the thread, are investigated. Useful models have been found and can be used by industries to accuracy predict the thread consumption for women’s underwear and panties to launch the needed thread commands. The developed models use multiregressive method. In this study, the fabrics that have been considered are knitted fabrics because they are those used in women’s underwear. We found that women’s underwear bras consume more sewing threads than panties. Using linear regression method, good relationships (coefficients of correlation close to 1) between consumption behaviors and the investigated parameters such as fabric thickness, number of assembled layers, stitch number per centimeter, sizes and tension of threads, were found. Although, the increase of threads tension to sew female underwear decreases the consumed amount of threads, the increase of other studied parameters widely encourages the consumption values, especially for seams based on chain-stitch types.

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Section: Methodsmentioning

confidence: 99%

“…have been omitted and neglected [7][8][9]14]. After a literature review, no articles have been found dealing with our specifi c subject the sewing thread consumption of women's underwear and panties.…”

Section: Bras and Panties) Based On The Obtained Fi Ndings It Was Cmentioning

confidence: 99%

A Study of the Consumption of Sewing Threads for Women's Underwear: Bras and Panties

Brahem

Wissal

Khedher

et al. 2020

Autex Research Journal

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“…While some textile studies used a single activation function for all NN layers (e.g., sigmoid, 25 linear 19 ), most of the studies 3,5,7,15,20,21,23,24 proposed the usage of different activation functions for different layers (i.e., sigmoid and linear activation functions in the hidden and output layers, respectively). Several textile studies 26,27 aimed to perform the analysis of different activation functions to figure out the optimal function for a problem.…”

Section: Neural Network In Textile Industrymentioning

confidence: 99%

“…15 • Construction of models to reduce the consumption of textile-related materials, such as fabrics, yarns, dyes, and sewing threads 5 • Discovering patterns that can be used to produce better textile endproducts 13,61,68 • Analyzing textile data to achieve better customer satisfaction…”

Section: Advantages Of Dm Enabled In Textile Industrymentioning

confidence: 99%

“…Some studies were carried out for production planning 5 by evaluating and predicting the sewing thread consumption of jean trousers, automatic fabric fault detection [6][7][8] by classifying faults via real time fabric images, and performance development [9][10][11][12][13] by maintaining predictive models for the relationship between textile parameters and performance. Another type of problem for which the NN technique was used in the textile industry, was to predict the utility properties of textile materials, such as the moisture and heat transfer rate in fabrics 14 and air permeability of fabrics.…”

Section: Neural Network In Textile Industrymentioning

confidence: 99%

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Data mining and machine learning in textile industry

Yıldırım

Birant

Alpyıldız

2017

WIREs Data Min & Knowl

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Data mining has been proven useful for knowledge discovery in many areas, ranging from marketing to medical and from banking to education. This study focuses on data mining and machine learning in textile industry as applying them to textile data is considered an emerging interdisciplinary research field. Thus, data mining studies, including classification and clustering techniques and machine learning algorithms, implemented in textile industry were presented and explained in detail in this study to provide an overview of how clustering and classification techniques can be applied in the textile industry to deal with different problems where traditional methods are not useful. This article clearly shows that a classification technique has higher interest than a clustering technique in the textile industry. It also shows that the most commonly applied classification methods are artificial neural networks and support vector machines, and they generally provide high accuracy rates in the textile applications. For the clustering task of data mining, a K-means algorithm was generally implemented in textile studies among the others that were investigated in this article. We conclude with some remarks on the strength of the data mining techniques for textile industry, ways to overcome certain challenges, and offer some possible further research directions.

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Machine Learning Enhanced User Interfaces for Designing Advanced Knitwear

Bhömer

Liang

2019

Communications in Computer and Information Science

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Evaluation of Sewed Thread Consumption of Jean Trousers Using Neural Network and Regression Methods

Cited by 14 publications

References 23 publications

A Study of the Consumption of Sewing Threads for Women's Underwear: Bras and Panties

A Study of the Consumption of Sewing Threads for Women's Underwear: Bras and Panties

Data mining and machine learning in textile industry

Machine Learning Enhanced User Interfaces for Designing Advanced Knitwear

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