Prediction of Cloth Waste Using Machine Learning Methods in the Textile Industry

Atik, Ceren; Kut, Alp; Birant, Derya; Birol, Safak

doi:10.1109/iceee55327.2022.9772517

Cited by 2 publications

(2 citation statements)

References 15 publications

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“…In this way, the company can overcome the problems that may be encountered in terms of both re-source management and cost with the right amount of production. In the study, four machine learning methods (Support Vector Regressor, Random Forest, Decision Tree Regressor, and Bagging) were used and the results show that bagging gives the highest R2 value and minimum prediction error with 0.86 R2 when compared to other approaches (Atik, Kut, Birant, & Birol, 2022).…”

Section: Main Publications Related To Artificial Intelligence In the ...mentioning

confidence: 99%

Artificial Intelligence in the Management of Textile Companies: A Contextual Analysis

Bravo,

Iturralde

2024

OJBM

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The aim of this scientific contribution is to present a contextual analysis of the applications of artificial intelligence in the management and optimization of the textile industry. To achieve this objective, this scientific contribution carries out research in the domains of the Sopas research platform. In this research, the bibliometric and bibliographic analysis tools of this platform are used. In addition, the VOSviewer software is used to generate a term map from text mining. This document focuses on the following lines of results: 1) scientometric analysis of research related to artificial intelligence in the management of textile companies. 2) Main publications related to artificial intelligence in the management of textile companies. 3) A discussion on the application of artificial intelligence in the management of textile companies.

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Section: Main Publications Related To Artificial Intelligence In the ...mentioning

confidence: 99%

Artificial Intelligence in the Management of Textile Companies: A Contextual Analysis

Bravo,

Iturralde

2024

OJBM

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“…As other sectors are also adopting similar measures, leveraging AI presents the most practical approach to future-proofing the modern industry [2].The use of the internet of things (IoT) provides machine monitoring, less human effort and labor cost reduction [3]. The industrial IoT (IIoT) is used in textile condition and production monitoring.…”

Section: Introductionmentioning

confidence: 99%

Online Monitoring-Based Prediction Model of Knitting Machine Productivity

Elkateb,

Métwalli,

Shendy

et al. 2023

Fibres &Amp; Textiles in Eastern Europe

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Recently, Industry 4.0 introduced a breakthrough in the textile industry to meet customer demands. This study aimed to accurately estimate the production rate of a knitting machine through an online monitoring system using the Internet of Things (IoT) and machine learning (ML) concepts. Experimentally, a double knitting machine was attached with sensors for gathering data of the machine speed, yarn feeder speed and stitch length while other production variables remained constant. Two prediction models were introduced since correlation results revealed multicollinearity issues among the parameters measured. The second model achieved a prediction accuracy of 100 %. Thus, it presents a novel formula of production calculation.

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Prediction of Cloth Waste Using Machine Learning Methods in the Textile Industry

Cited by 2 publications

References 15 publications

Artificial Intelligence in the Management of Textile Companies: A Contextual Analysis

Artificial Intelligence in the Management of Textile Companies: A Contextual Analysis

Online Monitoring-Based Prediction Model of Knitting Machine Productivity

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