The Next Big Leap in Asset Management Comes with Predictive Maintenance at Scale

Most manufacturers’ predictive maintenance (PdM) programs remain limited to certain assets and fewer sites, as they usually build their anomaly detection models asset by asset, failure mode by failure mode. This manual approach slows down the scaling process considerably.

To successfully discover operational faults, find root cause, analyze failure modes, review signals of wear and explore failure mechanisms at scale, PdM algorithms need data from various sources and need to be well-integrated with different systems.

Read this new ARC white paper to learn how to accelerate and scale your PdM initiatives with AI and real-time analytics.