基于在线监测的针织机生产率预测模型

IF 0.7 4区工程技术 Q3 MATERIALS SCIENCE, TEXTILES

Fibres & Textiles in Eastern Europe Pub Date : 2023-10-01 DOI:10.2478/ftee-2023-0035

Sherien Elkateb, Ahmed Métwalli, Abdelrahman Shendy, Karim Moussa, Ahmed E. B. Abu-Elanien

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引用次数: 0

摘要

最近，工业4.0在纺织行业引入了突破，以满足客户需求。本研究旨在通过使用物联网(IoT)和机器学习(ML)概念的在线监测系统，准确估计针织机的生产率。实验中，在双纬针织机上安装传感器，在其他生产变量保持不变的情况下，采集机器速度、送纱速度和针长数据。由于相关结果揭示了测量参数之间的多重共线性问题，引入了两种预测模型。第二个模型的预测精度达到100%。从而提出了一种新的产量计算公式。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Online Monitoring-Based Prediction Model of Knitting Machine Productivity

Abstract 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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来源期刊

Fibres & Textiles in Eastern Europe 工程技术-材料科学：纺织

CiteScore

1.60

自引率

11.10%

发文量

审稿时长

13.5 months

期刊介绍： FIBRES & TEXTILES in Eastern Europe is a peer reviewed bimonthly scientific journal devoted to current problems of fibre, textile and fibrous products’ science as well as general economic problems of textile industry worldwide. The content of the journal is available online as free open access. FIBRES & TEXTILES in Eastern Europe constitutes a forum for the exchange of information and the establishment of mutual contact for cooperation between scientific centres, as well as between science and industry.