A Development of AI Predictive Maintenance System using IoT Sensing

Abstract

This paper describes the development of a predictive maintenance system for cutting machines. In recent years, IoT and AI systems have been developed actively. As a result, sensors and embedded systems are becoming cheaper. Small and medium-sized companies attempt to use these inexpensive embedded systems for predictive maintenance. Therefore, we are developing the AI predictive maintenance system for these companies. In the system, the cutting sound emitted by a cutting machine is acquired by a sensor and an embedded system. The differences in the sounds are analyzed by AI using MATLAB and TensorFlow to predict the wear and tear of the tip of blade. The system was able to predict the tip wear degree with 90.5% accuracy.