This invention describes a system that predicts when factory machines might break down. It gathers warning signals from various sensors on the machines, then uses specific computer models to find patterns in these signals. These patterns help create a health score for each machine, which is then used to anticipate potential failures before they occur.
Why it matters: The widespread adoption of IoT and industrial sensors since 2016 makes collecting the necessary event data much easier. Cloud computing and advanced machine learning tools have also matured, simplifying the deployment and scaling of the complex analytical models.
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