How to avoid downtime with predictive maintenance - Plant Engineering
What happened
The Plant Engineering piece explains how advanced analytics and AI enable predictive maintenance to cut unplanned downtime by turning scattered operational data into actionable insights. The article stresses that data fragmentation and manual prep work are the primary obstacles, and that human experts remain critical to validate models. Watch whether teams have the SME time and spare-part plans in place before scaling analytics to avoid alert overload
Why the category manager should care
Treat predictive-maintenance pilots as a combined data + spare-parts procurement exercise, not just a software buy
Key facts
- Highlights the shift from time‑based to condition‑based maintenance
- Emphasizes data cleansing and human-in-the-loop validation
- Frames AI as improving prediction accuracy as labeled data grows