Sherien Elkateb, Ahmed Métwalli, Abdelrahman Shendy, Karim Moussa, Ahmed E. B. Abu-Elanien
{"title":"Online Monitoring-Based Prediction Model of Knitting Machine Productivity","authors":"Sherien Elkateb, Ahmed Métwalli, Abdelrahman Shendy, Karim Moussa, Ahmed E. B. Abu-Elanien","doi":"10.2478/ftee-2023-0035","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":12309,"journal":{"name":"Fibres & Textiles in Eastern Europe","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fibres & Textiles in Eastern Europe","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/ftee-2023-0035","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATERIALS SCIENCE, TEXTILES","Score":null,"Total":0}
引用次数: 0
Abstract
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.
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.