Performance monitoring and analysis for predictive maintenance of a circular knitting machine

Abstract

The objective of this research is to implement a system that tracks and analyzes real-time events to improve the performance and reliability of circular knitting machines in shirt, legging and sportswear production. These technological advances have not replaced the need for manual inspections. This leads to problems that go unnoticed, sudden breakdowns and lost production. By using temperature, RPM, current, voltage, humidity, airflow and lubrication sensors, the proposed system utilizes predictions to identify potential problems early on. Besides, being able to observe systems remotely will make it easier to oversee everything and make quicker data-based decisions. To be one step further to predictive maintenance from conventional approach in order to enhance the machine reliability, to keep the constant fabric quality, as well as to promote more ecological manufacturing of the garment products. This is an innovation that should improve efficiency and competitiveness in the textile industry, particularly in the large market of ready-made garments such as that in Bangladesh.