How ENLYZE automatically detects downtimes from machine data.
ENLYZE detects downtimes automatically based on machine data. The principle: a variable that reliably indicates whether the machine is producing is continuously monitored. When its value drops below a defined threshold, a downtime is detected.
The foundation of downtime detection is two configuration parameters:
Lead variable: A variable that clearly indicates whether the machine is producing. Typically a speed, throughput, or cycle rate.
Threshold: The limit below which a downtime is detected.
An extrusion line uses the winder speed as the lead variable. The threshold is configured at 5 m/min:
Values below 5 m/min: The machine is stopped (downtime).
Values at or above 5 m/min: The machine is producing.
Detection is accurate to the second and fully automatic. No manual input is required.
Extrusion
Haul-off speed, winder speed
Printing press
Line speed
Assembly line
Pieces per minute
Packaging
Cycle time, piece counter
To avoid short-term "flickering" (e.g. when speed briefly drops below the threshold and immediately rises again), a minimum duration can be configured. Only downtimes lasting longer than the minimum duration are recorded.
In addition to numerical variables, Boolean variables (True/False) can also be used as lead variables. In this case, you configure whether True or False represents a downtime.
Objective: No subjective assessment by employees.
Gap-free: Every downtime is captured, even at night or on weekends.
Second-accurate: Precise start and end times instead of estimates.
Automatic: No manual effort for basic tracking.
How to configure downtime detection in the ENLYZE App is described under Setting up OEE tracking.
Categories & assignment: How detected downtimes are assigned reasons.
Availability: How downtimes affect OEE availability.
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