TY - JOUR
T1 - Real-Time Monitoring of Knitting Machine Performance Using IoT and Machine Learning: Innovations and Applications
AU - Elkateb , Sherien
AU - Métwalli , Ahmed
AU - Shendy , Abdelrahman
JO - Journal of Fiber Bioengineering and Informatics
VL - 4
SP - 297
EP - 309
PY - 2024
DA - 2024/09
SN - 16
DO - http://doi.org/10.3993/jfbim03031
UR - https://global-sci.org/intro/article_detail/jfbi/23426.html
KW - Internet of Things, machine learning, system accuracy, real-time monitoring, knitting machine.
AB - <p style="text-align: justify;">Textile technologies are revolutionising with Industry 4.0. This research aims to introduce a novel
real-time monitoring system in the knitting sector using the Internet of Things and machine learning
technologies to measure and display productivity precisely through an interactive dashboard. Sensors
were integrated into a circular knitting machine to track productivity and performance. A comparative
statistical analysis through three processing phases demonstrates the high accuracy and precision of
the current system, as evidenced by minimum variance and error values. The t-test results validate a
non-significant difference between actual and device-measured production. Thus, it enables real-time
monitoring, preventive maintenance, and cost-effective quality in knitting machines.</p>