Predictive maintenance uses sensor data and analytics to forecast equipment failure before it happens , reducing unplanned downtime and maintenance costs.
Definition
Predictive maintenance uses data from sensors, machine logs, and operational history to forecast when equipment is likely to fail, so maintenance can be scheduled before the breakdown occurs. It sits between preventive maintenance (time-based, fixed schedules) and reactive maintenance (fix it when it breaks). Effective PdM requires reliable sensor data, a solid data history, and analytical models that are tuned to the specific failure modes of each asset.
What this means when you're hiring
PdM roles combine reliability engineering knowledge with data analytics capability , two disciplines that rarely coexist in a single candidate. The people who can build the models often don't understand the physics of machine failure; the maintenance engineers who understand failure modes often can't build ML pipelines. I look for candidates who've shipped a PdM solution that was actually used by a maintenance team, not just validated in a lab.
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