Glossary
Operations and asset management

What is Condition-based maintenance?

Definition

Condition-based maintenance (CBM) triggers work when a measured condition, such as filter differential pressure or bearing temperature, crosses a set limit, instead of servicing equipment on a fixed interval.

Where CBM fits

CBM suits assets whose wear shows up in one clear signal: filters and strainers through differential pressure, belts and bearings through vibration or temperature, coils through approach temperature, and fans through current draw. Facility teams often adopt it first on a short list of critical assets before moving to trend-based prediction.

Limits and the typical maintenance mix

Each limit is tied to a known failure mode and set from manufacturer data or the asset's own history. Per the DOE FEMP O&M Best Practices Guide, the average US maintenance program is over 55 percent reactive, 31 percent preventive and 12 percent predictive, while top performers run under 10 percent reactive and 45 to 55 percent predictive. CBM is a common first step out of that reactive share.

Threshold alerts in Aqueduct

An Aqueduct maintenance alert is a rule on a metric with a condition, a value and a severity. In a control cluster the trigger can come from a different device than the one being serviced, for example a pressure sensor across an RTU filter raising a filter change alert. The device Health tab shows connection rate and battery or capacitor voltage, so a dying sensor is not mistaken for a worn asset.

Questions

Condition-based maintenance: common questions

Condition-based maintenance is a maintenance strategy that services an asset only when evidence says it needs it. Teams fix a limit for a signal tied to a known failure mode, monitor that signal, and open a work order when it is breached. Aqueduct's view of it is on the predictive maintenance page.

CBM reacts when a limit is crossed now. Predictive maintenance projects the trend to estimate when the limit will be crossed, so work can be planned earlier. Many programs start with CBM thresholds and add trend projection once enough history exists for each asset.

Those where a failure is costly and wear is measurable before the asset stops, such as chillers, air handlers and process pumps. Starting with a short list keeps alert volume manageable and proves value before sensors are added to less critical equipment across the asset base.

Not always. Many limits can use points the BMS or meters already report, such as supply air temperature or current draw. Extra sensors, for example differential pressure across a filter or vibration on a bearing, are added where the existing data cannot show the failure mode early enough.

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