Predictive maintenance reduces operational costs for organizations running and manufacturing expensive equipment by predicting failures from sensor data. In this talk, we will learn how MATLAB® and Predictive Maintenance Toolbox™ combine machine learning with signal processing techniques for predicting failures.
This webinar will focus on the workflow for estimating remaining useful life of machines by preprocessing, extracting, visualizing , and selecting trendable features from sensor data. The trendable sensors are used to construct a Similarity based RUL Estimator.
