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Learn how to increase the operational efficiency of the assets you manage, and improve overall equipment effectiveness by using IoT data and AI.
Reduce the operational costs of the facilities you manage, and create more engaging occupant experiences through the application of IoT data and AI.
Learn how IoT data and AI are being applied to transform the end-to-end engineering lifecycle.
Predictive monitoring is a game changing concept in almost every industry. The ability to accurately predict is so valuable — to so many — that entire businesses are built around helping other industries, especially industrial manufacturing, with everything from remote asset monitoring, to predictive maintenance, to asset management. But what can be predicted? How can it work within existing infrastructures? And what will it take to make a reality?
Predictive monitoring for industrial manufacturing provides a distinction from another sought-after goal — which we will address shortly — predictive maintenance. In the former, using remote asset monitoring, systems allow a company to monitor and observe the behavior of data points over time. The goal is to determine whether something needs to be done and what that task is — not when to do a prescribed task.
Predictive monitoring uses AI to notice what would otherwise be impossible to see. It does not perform any correlation or offer any insight. The user is merely alerted to the behavioral change and applies their knowledge of the process and their own skillset to determine what action, if any, is needed. The critical difference is that the user prescribes the action.