Predictive maintenance uses AI and IoT sensors to forecast equipment failures, cutting costs and preventing downtime in ...

Most facilities already have the monitoring tools needed for predictive maintenance; the key is actively reviewing and interpreting the data. Electrical failures often develop gradually through trends ...

Manufacturers are navigating a tempestuous landscape, wrestling with the intertwined challenges of pandemic-induced disruptions, potential tariffs and evolving policy shifts that strain global supply ...

Renewable energy is an essential part of striving for sustainable operations across industries. Predictive maintenance is one tool that helps build a reliable renewable energy infrastructure. With the ...

In the era of Industry 4.0, manufacturing is no longer defined solely by mechanical precision; it’s now driven by data, connectivity, and intelligence. Yet downtime remains one of the most persistent ...

Predictive maintenance, based on more and better sensor data from semiconductor manufacturing equipment, can reduce downtime in the fab and ultimately cut costs compared with regularly scheduled ...

The dominant failure mode of industrial predictive maintenance is not model inaccuracy. It is a broken handoff between detection and response. This paper describes an integration architecture that ...

Daniel Penn Associates recently asked members of LinkedIn’s Association of Asset Management Professionals Group “What is the maintenance strategy that you use the most with your organization?” The ...

Chipmakers have begun to shift to predictive maintenance for process tools, but the hefty investment in analytics and engineering efforts means it will take some time for smart maintenance to become a ...