Predicting sewing thread consumption for lockstitch using regression model

Midha, Vinay Kumar; Sharma, Shailja; Gupta, Vaibhav

doi:10.1108/rjta-08-2016-0019

Cited by 10 publications

(12 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Jaouadi et al compared thread consumption using both regression analysis and neural network [14]. Recently, Midha et al have predicted sewing thread consumption for lockstitch using regression model [15]. Moreover, Rasheed et al studied a geometrical model to calculate the consumption of sewing thread for 504 overedge stitch [1].…”

Section: Introductionmentioning

confidence: 99%

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

Malek

Khedher

Adolphe

et al. 2021

Autex Research Journal

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

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

Malek

Khedher

Adolphe

et al. 2021

Autex Research Journal

View full text Add to dashboard Cite

show abstract

“…So far, the study for efficient method is not over and has been continuing until now. Recently, Midha has found sewing thread consumption for lockstitch based on regression model [5]. Abher and khedher considered the geometrical model to calculate the consumption of the sewing thread for a 301 lock stitch [2,6].…”

Section: Introductionmentioning

confidence: 99%

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

Malek

Jaouachi

Dominique

2020

Autex Research Journal

View full text Add to dashboard Cite

This 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.

show abstract

“…Many researchers studied the effect of various factors influencing sewing thread consumption and also developed different mathematical or geometrical models to estimate the sewing thread consumption for different stitch classes by using different techniques, i.e., fuzzy logic, regression analysis, artificial neural networks etc [1][2][3][4][5][6][7]. Thread consumptions estimation are done by garment manufacturers using various charts based on various tables and formulae which uses different variables and assumptions.…”

Section: Introductionmentioning

confidence: 99%