Sign up for free and test all features of our software.
Great, that worked!
Unfortunately, that didn't work out. Please check that all mandatory fields have been completed.
Predictive maintenance for extruders
Ensure continuous production processes through reliable predictive maintenance for extruders.
Even minor deviations can quickly result in production and quality losses. Predictive maintenance provides insights into operational performance and detects anomalies at an early stage, before downtime occurs
A leading manufacturer of high-quality animal feed operates modern production lines for grinding and extrusion of feed. Extruder downtime quickly lead to production downtime and quality losses.
Early detection of anomalies that prevent unplanned downtime:
Bearing and gear damage due to increasing vibrations and temperatures
Material jams or blockages in the extruder due to mass flow deviations
Performance deviations due to process fluctuations
Continuous monitoring allows early detection of anomalies, reduces downtime and extends the lifespan of extruders.
AI in a production context instead of rigid threshold values
Detection of different recipes and operating states
Implemented in just a few days without complex IT project
Easy scalability to additional assets
Manufacturer- independent and flexible to use
Suitable for standalone machines and complex production lines
FAQ: Predictive maintenance for extruders
Can predictive maintenance detect material blockages on the extruder?
Yes. Material blockages typically alter machine load and, for example, vibration behavior. Deviations can often be identified early. Especially when additional process signals like pressure or mass flow are available.
What happens if extruders operate in different operating conditions (e.g., with different recipes or load changes)?
It is crucial that information about the framework conditions are available (e.g., recipe, speed, or load range). Only then deviations can be correctly assessed.
Which sensors/signals are typically needed for monitoring extruders?
For a simple start, a few signals are usually sufficient to reliably assess the condition and operation:
1. Vibration at bearing/housing points (motor, gearbox, critical bearing points) 2. Drive power (motor current/kW or ideally torque) 3. Speed / Run status as context (load condition, start-ups/shut-downs, downtimes)
Where should sensors ideally be placed on extruders?
Measurement points close to the source are most effective: - Bearing points on the drive - Gearbox housing - Motor bearings, possibly critical bearings on the extruder (depending on accessibility)
The goal is a clean acquisition of vibrations from rotating assemblies.
Can predictive maintenance also detect "creeping wear" on extruders?
Yes. Creeping wear often manifests as a gradual trend change, e.g., increasing power consumption (motor current/kW), elevated temperatures, or a slowly rising vibration level. Continuous evaluation of these signals makes such deviations visible early on.
Any further questions?
Our mechanical engineer Joel is happy to help you!
