Machine Learning-Based Predictive Maintenance for Mechanical Equipment in Smart Manufacturing
A group-aware and explainable machine learning-based approach to normalized RUL prediction using vibration, current and operating condition features is suggested, which showed that unseen-tool generalization could be measured, but there was a variation between test tools that showed the difficulty of cross-tool degradation variability.