These tools leverage machine learning algorithms, big data analytics, and Internet of Things (IoT) devices to collect and analyze data. Sensors are placed on machinery to monitor various parameters such as temperature, vibration, and noise. The data collected is then processed by advanced software that uses predictive models to forecast potential failures. This allows maintenance teams to take proactive measures, thus avoiding unexpected breakdowns.