Prediction of Sewing Thread Consumption for Over-Edge Stitches Class 500 Using Geometrical and Multi-Linear Regression Models

Abstract Rapid and precise methods (geometrical and statistical), which aim to predict the amount of sewing thread needed to sew a garment using different over-edge stitches of class 500 (501, 503, 504, 505, 512, 514, 515, and 516), have been provided. Using a geometrical method of different over-edge stitch shapes, sewing consumption value was determined to avoid the unused stocks for each stitch type. The prediction of the sewing thread consumption relative to each investigated over-edge stitch was proposed as a function of the studied input parameters, such as material thickness, stitch density, yarn diameter, and seam width (distance between the needle and the cutter and the distance between two needles). To improve the established models using a geometrical method, a statistical method based on multi-linear regression was studied. Geometrical and statistical results were discussed, and the coefficient R2 value was determined to evaluate the accuracy of the tested methods. By comparing the estimated thread consumption with the experimental ones, we concluded that the geometrical method is more accurate than the statistical method regarding the range of R2 (from 97.00 to 98.78%), which encourages industrialists to use geometrical models to predict thread consumption. All studied parameters contributing to the sewing thread consumption behavior were investigated and analyzed in the experimental design of interest. It was concluded that the most important parameter affecting thread consumption is the stitch density. The material thickness and the seam width (B1) have a little impact on thread consumption values. However, the seam thread diameter has a neglected effect on thread consumption.

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Determination of Sewing Thread Consumption for 602, 605, and 607 Cover Stitches Using Geometrical and Multi-Linear Regression Models

Autex Research Journal ◽

10.2478/aut-2020-0044 ◽

2020 ◽

Vol 0 (0) ◽

Author(s):

Malek Sarah ◽

Jaouachi Boubaker ◽

Adolphe Charles Dominique

Keyword(s):

Linear Regression ◽

Statistical Method ◽

Linear Regression Models ◽

Geometrical Method ◽

Material Thickness ◽

Sewing Thread ◽

Stitch Density ◽

Input Parameters ◽

Multi Linear Regression ◽

Consumption Value

AbstractThis work deals with prediction of the quantities of sewing threads required to sew a garment using cover stitches for the different classes of 600 (602, 605 and 607 cover stitches) by performing a rapid and precise methods (Geometrical and statistical). Sewing consumption value was estimated based on the geometrical method of different cover stitch shapes to prevent inventory of stocks for each stitch type. In the prediction of the sewing thread consumption for each investigated stitch, it was assumed that the consumption is a function of the input parameters, such as material thickness, stitch density, yarn linear density, and seam width. In addition, a statistical method based on multi-linear regression was established. The coefficient R2 value was determined to evaluate the precision of the geometrical and statistical methods. By comparing the theoretical thread consumption with the experimental ones, it is concluded that the geometrical method is more accurate than the statistical method regarding the range of R2 (from 98.78% to 99.38%), which encouraged industrialists to use geometrical models to predict thread consumption.The input parameters contributing to the sewing thread consumption behavior were studied and analyzed. It was concluded that the most important parameters influencing thread consumption are stitch density followed by seam width. Both yarn density and material thickness have a low contribution to the thread consumption value.

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Sewing Thread Consumption for Different Lockstitches of Class 300 Using Geometrical and Multi-Linear Regression Models

Autex Research Journal ◽

10.2478/aut-2019-0022 ◽

2020 ◽

Vol 20 (4) ◽

pp. 415-425

Author(s):

Malek Sarah ◽

Jaouachi Boubaker ◽

Khedher Faouzi ◽

Dominique Adolphe

Keyword(s):

Linear Regression ◽

Statistical Method ◽

Theoretical Models ◽

Geometrical Model ◽

Linear Regression Models ◽

Geometrical Method ◽

Sewing Thread ◽

Yarn Count ◽

Multi Linear Regression ◽

Consumption Value

AbstractThis paper aims to provide rapid and precise methods to allow industrials to predict the amount of sewing thread needed to sew a garment using different lockstitches of class 300 (301, 301/301, 304, 308, 309, 310, 311, 312, and 315). To avoid unused stocks for each stitch type, a sewing consumption value was determined using a geometrical method of different lockstitch shapes. Furthermore, the relationships between overall geometrical models of the studied lockstitches of class 300 were developed. Indeed, based on the geometrical model of lockstitch type 301, all theoretical models proposed were investigated and proved to be accurate. Moreover, referring to the findings, the prediction of the sewing thread consumption relative to each investigated lockstitch was proposed as a function of the studied input parameters. To improve the established models using geometrical technique, a statistical method was conducted. In addition, based on multi-linear regression, compared geometrical and statistical results were discussed and the coefficient R2 value was determined to evaluate the accuracy of the tested methods. By comparing the estimated thread consumption with the experimental ones, we concluded that the accuracy of the models is significant (R2 ranged from 93.91% to 99.10%), which encourages industrialists to use geometrical models to predict thread consumption. Therefore, the accuracy of prediction using the geometrical method is more accurate than the statistical method regarding the range of R2 (from 92.84% to 97.87%). To classify the significance of all studied parameters, their contributions to the sewing thread consumption behavior were analyzed in the experimental design of interest. It was concluded that the most important parameters affecting thread consumption are stitch width, stitch density, and the gap between two needles. The thickness of fabric has a low contribution to the thread consumption value, whereas the effect of yarn count can be neglected.

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Application of multi-linear regression models and machine learning techniques for online voltage stability margin estimation

2010 IREP Symposium Bulk Power System Dynamics and Control - VIII (IREP) ◽

10.1109/irep.2010.5563288 ◽

2010 ◽

Cited By ~ 3

Author(s):

Bruno Leonardi ◽

Venkataramana Ajjarapu ◽

Miodrag Djukanovic ◽

Pei Zhang

Keyword(s):

Machine Learning ◽

Linear Regression ◽

Regression Models ◽

Voltage Stability ◽

Stability Margin ◽

Machine Learning Techniques ◽

Linear Regression Models ◽

Voltage Stability Margin ◽

Learning Techniques ◽

Multi Linear Regression

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

Autex Research Journal ◽

10.2478/aut-2019-0032 ◽

2020 ◽

Vol 20 (3) ◽

pp. 299-311

Author(s):

Brahem Mariem ◽

Messaoudi Wissal ◽

Khedher Faouzi ◽

Jaouachi Boubaker ◽

Dominique Adolphe

Keyword(s):

Linear Regression ◽

Regression Method ◽

Linear Regression Method ◽

Knitted Fabrics ◽

Fabric Thickness ◽

Sewing Thread ◽

Consumption Values ◽

Stitch Density ◽

Sewing Threads ◽

Influential Parameters

AbstractThe 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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Hourly predictive Levenberg–Marquardt ANN and multi linear regression models for predicting of dew point temperature

Meteorology and Atmospheric Physics ◽

10.1007/s00703-012-0192-x ◽

2012 ◽

Vol 117 (3-4) ◽

pp. 181-192 ◽

Cited By ~ 36

Author(s):

Mohammad Zounemat-Kermani

Keyword(s):

Linear Regression ◽

Regression Models ◽

Dew Point ◽

Linear Regression Models ◽

Point Temperature ◽

Dew Point Temperature ◽

Levenberg Marquardt ◽

Multi Linear Regression

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Sewing Thread Consumption for Chain Stitches of Class 400 Using Geometrical and Multilinear Regression Models

Autex Research Journal ◽

10.2478/aut-2019-0051 ◽

2019 ◽

Vol 0 (0) ◽

Author(s):

Sarah Malek ◽

Faouzi Khedher ◽

Dominique C. Adolphe ◽

Boubaker Jaouachi

Keyword(s):

Regression Models ◽

Geometrical Method ◽

Multilinear Regression ◽

Consumption Behavior ◽

Fabric Thickness ◽

Sewing Thread ◽

Stitch Density ◽

Statistical Results ◽

Consumption Value

Abstract This work deals with determination of rapid and precise methods to predict the amount of sewing thread needed to sew a garment using different chain stitches of the class 400 (from 401 to 407 chain stitches). At first, to avoid unused stocks, sewing consumption value was determined using a geometrical method (based on different chain stitch shapes). The prediction of the sewing thread consumption was proposed as a function of the studied input parameters, which are fabric thickness, stitch density, yarn linear density, and stitch width. Then, a statistical method based on the multilinear regression was studied. Geometrical and statistical results were discussed. Based on the R2 range, we concluded that the geometrical method is more accurate than the statistical one (from 98.16 to 99.19% and from 97.30 to 98.51%, respectively). Thus, this result encourages industrialists to use geometrical models to predict thread consumption. Also, all studied parameters, contributing to the sewing thread consumption behavior, were investigated and analyzed. The result shows that the most important parameters affecting thread consumption are stitch density followed by stitch width and fabric thickness. The yarn density has a low contribution on the thread consumption value.

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