Maintenance has traditionally been either reactive, fix it when it breaks, or scheduled, service it on a fixed calendar whether it needs it or not. Both waste money: one through downtime and damage, the other through unnecessary work. Predictive maintenance uses data to find the middle path.
How it works
Sensors and system data reveal the early signs of wear, a motor drawing more current, a bearing vibrating, a filter restricting flow, long before failure. Maintenance is then done when the evidence says it is needed, not too early and not too late.
The benefits
- Fewer unexpected breakdowns and less downtime
- Maintenance effort focused where it is actually needed
- Longer equipment life from timely intervention
- Lower energy use from well-tuned plant
- Better planning of spares and labour
Built on integration
Predictive maintenance depends on the data that an integrated BMS and good instrumentation provide. It is a natural benefit of a well-connected building, and increasingly enhanced by the AI that spots the patterns humans miss.
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