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Episode Description:
You know the alerts. The flashing messages. The alarms that go off after the damage is already done.
But what if you could see the failure before it becomes a crisis?
In this week’s episode, we explore how building operators and BAS professionals can move from reactive to proactive maintenance using the data already in their systems. It’s not about more alarms, it’s about better insight.
Topics Covered
- Why traditional alarms fail to prevent equipment breakdowns
- How to spot failure patterns in BAS data before alarms go off
- Reading trends like a technician to catch hidden mechanical issues
- Turning raw data into actionable maintenance work orders
- Using BAS evidence to support preventative strategies
Stop chasing failures. Start preventing them.
Click here to download or listen to this episode now.Podcast Video
How to Prevent Equipment Failures Using BAS Data
Building automation systems generate massive amounts of data every day. Most of it goes unused. Operators rely on alarms to alert them to problems, but by the time an alarm triggers, the damage is often already done. Mechanical wear has occurred, energy costs have increased, and occupant comfort has declined.
This episode of the Smart Buildings Academy Podcast focuses on how to use BAS data to detect and prevent failures before alarms are triggered.
Why Alarms Are Not Enough
Alarms only signal issues after systems fail to compensate. A rising discharge air temperature caused by a dirty coil, for example, may not trigger an alarm until comfort has been compromised. At that point, the equipment has already been under stress for weeks.
Operators often experience alarm fatigue. Repeated nuisance alarms lead to critical issues being overlooked. Many BAS systems lack alarms for vital data like valve positions, VFD speeds, and pressure readings.
Recognizing Failure Patterns in BAS Data
Failures develop gradually and appear in trend data long before alarms activate. Here are some early warning signs:
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Discharge air temperature drifting upward under constant load
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VFD speeds are increasing to maintain airflow
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Valves are staying open longer to achieve the same result
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Static pressure trends showing rising effort
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Runtime and cycle counts increasing without clear cause
These indicators point to mechanical degradation. Left unaddressed, they result in failures that require costly repairs.
How to Read Trends Like a Technician
Trend analysis reveals both normal and abnormal operation. Normal trends are repeatable and predictable. For example, static pressure and discharge temperatures should follow consistent daily patterns. Abnormal trends show drift, lag, or erratic behavior.
Examples include:
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Longer warm-up or cool-down times under similar outdoor conditions
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Temperature overshoots or oscillations in previously stable systems
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Sensors that flatline or behave erratically due to wiring issues
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Flat trends on valves or dampers that should be modulating
Technicians can use this data to diagnose failing control valves, dirty filters, fouled coils, and simultaneous heating and cooling conditions.
Turning BAS Data into Action
Once failure patterns are identified, technicians and operators can take preventive action:
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Generate work orders from trend data before alarms occur
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Use evidence from trend logs to justify repairs or replacements
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Transition from emergency responses to scheduled maintenance
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Reduce after-hours service calls and increase occupant comfort
Operators can support maintenance recommendations with real data. This builds trust with stakeholders and ensures repairs happen before major issues develop.
Summary
BAS data holds the key to preventing failures, but it requires a shift in mindset. Instead of reacting to alarms, operators must use data to anticipate problems. This proactive approach improves equipment life, energy efficiency, and comfort.
For a deeper discussion and insights from the field, listen to this episode on the Smart Buildings Academy podcast.
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